HBV and IWRM Watershed Modelling User Guide

HBV and IWRM Watershed Modelling User Guide
Mekong River Commission
HBV and IWRM Watershed
Modelling User Guide
MRC Information and Knowledge Management Programme
DMS – Detailed Modelling Support for the MRC Project
December 2010
Finnish Environment Institute
in association with
EIA Centre of Finland Ltd.
DMS-Project, Mekong River Commission
DMS - Detailed Modelling Support to the MRC Project
HBV and IWRM Watershed Modelling User Guide
MRC Information and Knowledge Management Programme
December 2010
Jorma Koponen, Hannu Lauri, Noora Veijalainen and Juha Sarkkula
Finnish Environment Institute
Mechelininkatu 34a
00260 Helsinki
Finland
Tel: +358-9-403 000
Fax: +358-9-40300 390
www.environment.fi/syke
[email protected]
2
EIA Ltd.
Tekniikantie 21 B
02150 Espoo
Finland
Tel: +358-9-7001 8680
Fax: +358-9-7001 8682
www.eia.fi
[email protected]
MRCS/IKMP --- December 2010
HBV and IWRM Watershed Modelling User Guide
TABLE OF CONTENTS
TABLE OF CONTENTS................................................................................................................... 3
1
STRUCTURE OF THE USER GUIDE ...................................................................................... 7
1.1
STRUCTURE OF CHAPTER AND INFORMATION BOXES ........................................................... 7
1.2
EXERCISES ........................................................................................................................ 8
2
IWRM MODELLING BACKGROUND ...................................................................................... 9
2.1
WHAT IS IWRM MODELING ................................................................................................. 9
2.2
HISTORICAL OVERVIEW OF THE MRC IWRM MODEL DEVELOPMENT .................................. 10
3
LUMPED HYDROLOGICAL MODELLING ............................................................................ 12
3.1
OVERVIEW OF LUMPED AND DISTRIBUTED MODELLING ....................................................... 12
3.2
NOOA EXPERIENCES OF LUMPED AND DISTRIBUTED MODELLING ....................................... 14
3.3
GENERAL PRINCIPLES OF THE LUMPED HBV MODEL .......................................................... 15
3.4
EIA HBV MODEL .............................................................................................................. 19
3.5
EIA HBV MODEL APPLICATION STEPS ............................................................................... 21
3.5.1 Install modelling software .......................................................................................... 21
3.5.2 Prepare input data into the HBV model format ......................................................... 21
3.5.3 Data preparation using the 3D model user interface ................................................ 21
3.5.4 Data preparation with the DTT (Toolbox Data Transfer Tool) using the ToolBox
Knowledge Base data ............................................................................................................. 27
3.5.5 Create model application ........................................................................................... 31
3.5.6 EIA HBV model calibration ........................................................................................ 35
3.6
APPLICATION OF THE EIA HBV MODEL TO THE THEUN HINBOUN WATERSEHD IN THE LAO
PDR 37
4
DISTRIBUTED HYDROLOGICAL MODELLING................................................................... 39
4.1.1 Water quality and erosion computation ..................................................................... 42
4.1.2 Input and output data................................................................................................. 43
4.1.3 Model user interface .................................................................................................. 44
5
BASICS FOR USING THE IWRM MODEL ............................................................................ 47
5.1
SOFTWARE INSTALLATION ................................................................................................ 47
5.2
FILE SYSTEM .................................................................................................................... 50
5.2.1 Model system files ..................................................................................................... 50
5.2.2 Model application files ............................................................................................... 50
5.2.3 TXD file format ........................................................................................................... 51
5.3
STARTING THE IWRM MODEL SOFTWARE ......................................................................... 53
5.3.1 Starting the software from EIAModels desktop shortcut icon ................................... 53
5.3.2 Starting the software from vmp-file............................................................................ 55
5.4
IWRM USER INTERFACE................................................................................................... 56
5.4.1 Main menu ................................................................................................................. 56
5.4.2 Tools menu bar .......................................................................................................... 58
5.4.3 Model window ............................................................................................................ 60
5.4.4 Layer window ............................................................................................................. 61
5.4.5 Command window ..................................................................................................... 62
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5.4.6 Data table window ..................................................................................................... 63
5.4.7 Timeseries window .................................................................................................... 64
5.5
OPEN EXISTING MODEL APPLICATION ................................................................................ 66
5.6
SAVING MODEL APPLICATION ............................................................................................ 67
6
CREATING NEW IWRM APPLICATION ............................................................................... 68
6.1
CREATING A MODEL GRID ................................................................................................. 68
6.1.1 RLGis getting started ................................................................................................. 68
6.1.2 Data needed .............................................................................................................. 69
6.1.3 Creation of raster data files from ESRI shapefiles .................................................... 70
6.1.4 DEM processing ........................................................................................................ 70
6.1.5 Land use processing ................................................................................................. 74
6.1.6 Soil data processing .................................................................................................. 75
6.1.7 River network computation ........................................................................................ 76
6.1.8 Create river data layer ............................................................................................... 79
6.1.9 Creation of the grid file .............................................................................................. 80
6.2
SOIL AND LAND USE RECLASSIFICATION ............................................................................ 81
6.2.1 Soil reclassification .................................................................................................... 81
6.2.2 Land use reclassification ........................................................................................... 84
6.2.3 Reclassification steps ................................................................................................ 86
6.3
USEFUL RLGIS ACTIONS .................................................................................................. 87
6.3.1 Calculating upper areas............................................................................................. 87
6.3.2 Create a new landuse/DEM layers for catchment..................................................... 88
6.4
USAGE OF THE CREATED GRID IN THE IWRM MODEL ......................................................... 89
7
IWRM MODEL DATA MANAGEMENT.................................................................................. 91
7.1
REQUIRED MODEL INPUT DATA ......................................................................................... 91
7.2
FILES............................................................................................................................... 92
7.3
WEATHER DATA ............................................................................................................... 93
7.3.1 Weather data format .................................................................................................. 93
7.3.2 Weather data file management ................................................................................. 95
7.3.3 Weather data interpolation ........................................................................................ 95
7.4
START AND END STATES .................................................................................................. 96
7.5
SURFACE MODEL ............................................................................................................. 97
7.6
LANDUSE TYPES AND PARAMETERS .................................................................................. 97
7.6.1 Landuse types ........................................................................................................... 97
7.6.2 Landuse parameters.................................................................................................. 98
7.7
SOIL TYPES AND PARAMETERS ......................................................................................... 98
7.7.1 Soil Types .................................................................................................................. 98
7.7.2 Soil Parameters ......................................................................................................... 98
7.8
WATER QUALITY VARIABLES AND PARAMETERS ................................................................. 99
7.8.1 Water quality variables .............................................................................................. 99
7.8.2 Water quality parameters .......................................................................................... 99
7.9
GRID DATA ..................................................................................................................... 100
7.9.1 Grid info ................................................................................................................... 100
7.9.2 Grid modification ...................................................................................................... 100
7.10
LOADS ........................................................................................................................... 101
7.11
FLOWS .......................................................................................................................... 102
7.12
RESERVOIRS ................................................................................................................. 103
7.13
IRRIGATION AND GROUNDWATER .................................................................................... 104
7.14
TIMESERIES ................................................................................................................... 105
7.14.1 Adding new timeseries points .................................................................................. 105
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7.14.2 Editing timeseries .................................................................................................... 105
7.14.3 Timeseries output .................................................................................................... 106
7.15
FIELD ANIMATION OUTPUT .............................................................................................. 108
8
MODEL PARAMETERS ....................................................................................................... 110
8.1
SURFACE MODEL ........................................................................................................... 110
8.2
LANDUSE TYPE PARAMETERS ......................................................................................... 110
8.2.1 Precipitation and Interception .................................................................................. 110
8.2.2 Evaporation.............................................................................................................. 110
8.2.3 Snow model ............................................................................................................. 111
8.2.4 Vegetation model ..................................................................................................... 111
8.2.5 Surface model.......................................................................................................... 111
8.3
SOIL TYPE PARAMETERS ................................................................................................ 111
8.3.1 Soil model ................................................................................................................ 111
8.3.2 Erosion model parameters ...................................................................................... 112
9
CROP, IRRIGATION AND WATER TRANSFER MODELLING.......................................... 116
9.1
BASIC MODEL DIVERSION STRUCTURE AND CONTROLS .................................................... 116
9.2
CROP MODELLING .......................................................................................................... 119
9.3
WATER TRANSFERS ....................................................................................................... 124
10
GROUNDWATER ............................................................................................................ 127
11
CALCULATION ............................................................................................................... 130
11.1
COMPUTATIONAL PARAMETERS ...................................................................................... 130
11.2
RUNNING THE MODEL ..................................................................................................... 130
12
RESULTS ........................................................................................................................ 132
12.1
VIEWING TIMESERIES ..................................................................................................... 132
12.2
RESULT COMPARISONS .................................................................................................. 134
12.3
COMPARISON TESTS ...................................................................................................... 135
12.4
NUMERICAL TIMESERIES OPTIONS................................................................................... 139
12.5
ANIMATION OPTIONS ...................................................................................................... 139
13
SENSITIVITY ANALYSIS ................................................................................................ 141
14
CALIBRATION ................................................................................................................ 148
14.1
MANUAL CALIBRATION .................................................................................................... 148
14.2
AUTOMATIC OPTIMISATION ............................................................................................. 148
14.3
CALIBRATION STEPS....................................................................................................... 149
14.4
CALIBRATION TOOLS ...................................................................................................... 150
PART II – MODEL DESCRIPTION .............................................................................................. 153
15
RUNOFF MODEL ............................................................................................................ 154
15.1
METEOROLOGICAL DATA INTERPOLATION ........................................................................ 154
15.2
TEMPERATURE............................................................................................................... 154
15.3
PRECIPITATION .............................................................................................................. 154
15.4
INTERCEPTION ............................................................................................................... 155
15.5
SNOWPACK.................................................................................................................... 156
15.6
VEGETATION MODEL ...................................................................................................... 157
15.7
EVAPOTRANSPIRATION ................................................................................................... 158
15.8
INFILTRATION ................................................................................................................. 161
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15.9
15.10
SOIL CALCULATION......................................................................................................... 162
SOIL TEMPERATURE AND SOIL WATER FREEZING ............................................................. 165
16
RIVER AND LAKE COMPONENT .................................................................................. 168
16.1
RIVER MODEL ................................................................................................................ 168
16.2
LAKE MODEL .................................................................................................................. 170
17
NUTRIENT LEACHING MODEL ..................................................................................... 171
17.1
GENERAL....................................................................................................................... 171
17.2
CALCULATION OF SOLUBLE PHOSPHORUS ....................................................................... 172
18
EROSION MODEL .......................................................................................................... 173
18.1
SURFACE RUNOFF INSIDE A GRID CELL ............................................................................ 173
18.2
THE SOLID MATERIAL DETACHED BY PRECIPITATION ........................................................ 177
18.3
SOLID MATERIALS IN RIVERS AND LAKES ......................................................................... 178
PART III – APPENDICES ............................................................................................................ 179
19
6
REFERENCES ................................................................................................................ 180
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HBV and IWRM Watershed Modelling User Guide
1 STRUCTURE OF THE USER GUIDE
The user guide contains three different types of material:
Model description: the model equations and theory are described in detail
Software operation: the main model controls and functions are described in
detail with practical examples
Background information: includes broader modelling context and research
results.
The material has been constructed and structured as user-friendly as possible to serve
the needs of users with different backgrounds and purposes of model use. The
material includes illustrative figures and diagrams to make it easier for the user to
follow and apply the information. The linkages between model operation and model
description have been established to facilitate the better understanding of the theory
behind the different parts of the model.
1.1 STRUCTURE OF CHAPTER AND INFORMATION BOXES
Each chapter begins with the small text box with short introduction to the chapter and
list of the sub-headings in the chapter including links to the places in text where the
sub-headings are. The example of the small white text is provided boxes presented
below:
Text box at the beginning of each chapter works as a chapter introduction. Each
sub-heading, as shown below) is linked to the place in question in text. Thus, it is
easy to move to the point interested
0.1 [link to the sub-heading]
The steps to guide user through use of certain part of the model are described with the
numbered lists:
1. the main steps are described with numbers:
a. the sub-steps are described with letter
The text boxes provide more detailed information for example the parameters and
other functions. The boxes also provide model examples based on the projects the
model has been applied.
Box 1.
Example of text box.
Aim of text boxes:
to provide more detailed and in depth information
or theory background of the parameters, to offer
modelling examples, etc
The links between Model operation and Model description parts are marked as an
underlined blue text following the page number inside the brackets [page_number]
where the link is pointing to.
This is the example of the link: See Box 1 [7]
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The information box is marked with the blue info-symbol
as illustrated below.
The information box provides important information of the programme.
The text box with the blue info symbol provides important information
of the programme which should be taken into account when running
the software.
The trouble-shooting information box is marked with the orange no-symbol
as
illustrated below. The information box provides information of the trouble shooting
when possible malfunction of the programme occurs.
The text box with the orange no-symbol provides information of the
trouble shooting when possible malfunction of the programme occurs
The additional information box is marked with the blue computer symbol
as
illustrated below. This box provides e.g. more detailed information of the parameter,
description of some term, etc.
The text box with the blue computer symbol provides additional
information of the issue dealt in the text. This can be e.g. explanation
of the parameter, description of some term, etc.
Whether you should have any further comments and/or questions related to the IWRM
model system, this material, or other matters related to the model or modelling work,
please contact to EIA staff by email.
1.2 EXERCISES
The text box with the gears defines exercises. The exercises are
aimed at illustrating the main concepts and training for model use and
application.
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2 IWRM MODELLING BACKGROUND
2.1 WHAT IS IWRM MODELING
IWRM modelling can be understood in two ways. First of all it is a tool for
supporting the IWRM approach and process. For this reason IWRM modelling
needs to link different water uses, environment and socio-economic factors
together. For instance, IWRM modelling needs to address impacts of hydropower
development in terms of hydrology/flow regime, flooding, water quality, irrigation,
erosion, fisheries and agriculture productivity, forestry, habitats, losses and
benefits and livelihoods. Both local and cumulative/regional impacts need to be
addressed. Specific requirement for IWRM modelling comes from the participatory
nature of the IWRM process: IWRM should be able to support all levels of
governance, also the grass root level. This requires that IWRM model should be
easy to use, transparent and should provide illustrative results that can be utilised
in a decision making process and in communicating information to different
stakeholders.
The second way in defining IWRM modelling is to consider it without reference to
the established IWRM process and concept. In this way the integrated aspects of
modelling are highlighted. The modelling can and should integrate the following
components:
hydrology – natural water cycle is the basis for all other model components
land use – land use impacts the hydrological response of the watershed
and is an integral part of environmental and socio-economic assessment
flooding – flood pulse is the basis of the high productivity of the Mekong
system; flooding has both positive and negative socio-economic impacts
ground water – ground water can be an important asset for communal and
agricultural water usage; ground provides important dry season base flow
erosion – watershed, river bank, river bed and coastal erosion; flow regime
changes, land use changes, climate change (rainfall intensity) and
reservoir sediment trapping impact sediment input to the system and
deposition/erosion balance
water quality – land use changes (diffuse load), fertilisers, pesticides,
municipal and industrial wastes, aquaculture, saline intrusion, river flow,
reservoirs and climate change among others impact water quality
agriculture – crop yield and value, irrigation, erosion and agrochemicals are
some of the issues
forestry – hydrology, watershed erosion, forest production, diffuse load of
nutrients and sediments are the main interest issues
hydropower and other reservoirs – flow regime changes, sediment trapping,
water quality, erosion, fisheries production and greenhouse gas production
are some of the local issues
habitats – basis for biodiversity and productivity of natural systems
valuation of losses and benefits – basis for socio-economic impact
assessment; monetary valuation tells only part of the story, for instance
vulnerability needs to be considered
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socio-economics – model results and socio-economic data can be
integrated in GIS tools; vulnerability, livelihoods and cost/benefit analyses
are part of the socio-economic assessment.
It is not practical or even possible to include all of the factors in one model. The
MRC modelling ToolBox is based on the idea of using number of models either
separately or coupled together for integrated assessment. The IWRM model
integrates quite a lot of factors, but for instance detailed flooding processes,
aquatic productivity and river bank and coastal erosion are modelled with the 3D
model using the DSF or IWRM model results as boundary values. The ToolBox
development is a continuous process. Some of the system modules are more
developed than others. Especially groundwater, habitats and socio-economics
tools need further development. Also application of the existing models is an ongoing process. One of the main needs and challenges is integrated and
comprehensive modelling of the Mekong Delta.
Country exercise: Select a national priority area for IWRM modeling,
identify main (inter-connected) issues, build a conceptual model,
present the result for discussion
Exercise: Initiate preparation of a scientific article on IWRM
modeling. Publish it in a peer-reviewed scientific journal.
2.2 HISTORICAL OVERVIEW OF THE MRC IWRM MODEL DEVELOPMENT
The EIA IWRM hydrological model is developed by Environmental Impact Assessment
Centre of Finland Ltd (EIA Ltd.) in cooperation with different research organisations
(especially the Aalto University/Technical University of Helsinki). The current
development is conducted under and in cooperation with the MRCS.
The incentive for creating the IWRM model originates from a River IIjoki watershed
modelling project in Finland 1991 – 1994. The project was realised in cooperation with
the Helsinki University of Technology (HUT), National Board of Waters and
Environment and Oulu Water and Environment District. During the project a semidistributed hillslope model for a large watershed was developed by HUT. The model
included a sub-grid land type distribution. In connection with this, EIA Ltd. developed of
fast solution for complicated river network hydrodynamics and water quality, first
version of the graphical user interface and visualisation software for river water quality
distributions including animations. The objectives of the project were to study dynamics
and distribution of nutrients from agriculture, forestry and peat mining under different
development scenarios and to support obligatory water quality monitoring. The
modelling approach was in practice complicated and slow. To improve the approach,
accuracy and usability of watershed modelling a distributed model development was
initiated.
The model system development intensified in 1999 – 2001 when a project Decision
Support System for River Basin Management (RiverLife) was executed. The project
was financed by the European Commission, the four Ostrobothnian Province
Associations and Technology Development Centre TEKES. The project developed
support tools for cost-effective river basin management in co-operation with 12 other
institutes. The developed system combines river base modelling, database
connections, decision support modules and internet technologies. The main tool was
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HBV and IWRM Watershed Modelling User Guide
the EIA distributed, gridded, physical river basin model including hydrology, nutrients
and sediments. Special feature of the system was utilisation of GIS raster data. Special
emphasis of the project was on the model validation (both hydrology and water quality)
and usability of the tools for decision makers, authorities and research scientists. The
developed system is the basis for the current IWRM model framework.
In the Mekong the distributed model (VMOD) and the system tools (RiverLife) were
applied and further developed in 2001 – 2004 as part of the MRC WUP-FIN modelling
project. The model was applied to 13 sub-basins of the Tonle sap.
The distributed model was applied to Nam Songkhram in 2004 – 2007 during the
second phase of the WUP-FIN project. The model was used in combination of the 3D
model for climate change scenario, Mekong impact and reservoir studies.
The model was applied to the Lao Nam Ton area 2007 as a pilot study for the MRC
and German GTZ land management project. The data is utilised in the IWRM regional
training course for exercises.
The 2009 – 2010 MRC DMS project has integrated some of the DSF data
(precipitation, reservoirs, irrigation) and functions (IQQM reservoirs) in the model
system. The model has been applied to the whole Mekong Basin and used for the BDP
scenario studies. The modelling system has proved to be quite useful especially for
sediment impact studies (reservoir sediment trapping), but the model has given also
good results for hydrological studies (China dams and year 2010 low flow). The IWRM
model has been integrated under the DSF in 2010 in cooperation with the Halcrow
Consultants. The DSF/IQQM and FAO56 crop model has been integrated in the model
system. The model has been tentatively selected as a primary tool for Lao PDR line
agency IWRM, land management and climate change adaptation work and will
integrate economic evaluation of water resources and crops.
Previously the hydrological and water quality part of the IWRM has been called VMOD.
Because of the new functionalities and uses and to avoid confusion, it is considered
better to use the IWRM for also the VMOD part of the system.
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DMS-Project, Mekong River Commission
3 LUMPED HYDROLOGICAL MODELLING
The lumbed hydrological HBV model concepts, methods and parameters are largely
applicable for the IWRM modelling. Starting from more simple model helps focusing on
the main model principles and getting prepared for the more advanced tools and
methods.
3.1 OVERVIEW OF LUMPED AND DISTRIBUTED MODELLING
A lumped model is one in which the dependent variables of interest are a function of
time alone. In general, this will mean solving a set of ordinary differential equations
(ODEs).
A distributed model is one in which all dependent variables are functions of time and
one or more spatial variables. In this case, we will be solving partial differential
equations (PDEs).
A semi-distributed model describes watersheds as inter-connected sub-catchments.
The current DSF SWAT applications are semi-distributed whereas the IWRM model
applications and fully distributed based on a regular computational grid.
A conceptual model is a descriptive model of a system based on qualitative
assumptions about its elements, their interrelationships, and system boundaries.
A physically based model is a numerical model based on physical equations
describing the system under study. Contrast a numerical model to physical (scale)
model.
In many cases both lumped and distributed models are a mixture of conceptual and
physically based components. The distributed models are in general more physically
based because their structure corresponds more closely to the physical processes
occurring in any watershed. For instance a rainfall-runoff process is a function of
terrain that can be described with a distributed model but not with a lumped one.
The advantages of lumped approach are:
fast application
automatic calibration of the model parameters
easy understanding of the watershed system as a whole
easy accounting of main water amounts and dynamics
often quite good or at least reasonable results compared to measured values
first order approximation of parameters for distributed modelling
fast checking of more complicated distributed model applications
good applicability for operational water resources and flood monitoring systems,
also in national scale.
When a watershed is represented with a lumped system no spatial description is
included except lump parameters such as total area of the watershed. The
disadvantages of a lumped and more conceptual approach are:
lumped model can’t describe heterogeneity of the watershed including land use,
topography, precipitation, soil properties and different time scales in different
parts of a watershed
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HBV and IWRM Watershed Modelling User Guide
because the lumped model parameters describe actual physical watershed
parameter values in average sense and the lumped process correspond to the
watershed processes in a conceptual, averaged or statistical way, model ability
to forecast changing conditions and future is limited
for the same reason lumped system may not be able to describe correctly
extreme events
the possibilities for scenario modelling are limited; for instance the impact of
land use change is impossible to take into account if land use is not explicitly
included in the model
obviously the lumped model is less accurate for large catchments, but this can
be circumvented if a watershed can be divided into smaller sub-catchments
because of absence of spatial resolution lumped model is more difficult or
impossible to combined with GIS data.
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3.2 NOOA EXPERIENCES OF LUMPED AND DISTRIBUTED MODELLING
Figure 1. Relative research and application effort for distributed and lumped models
(NOOA 2010).
Figure 1 shows relative research and application efforts for distributed and lumped
models. It can be seen that there is a lag between development and application and
distributed modelling effort is clearly increasing after the end of the 1990’ies. It is also
interesting to notice that number of distributed applications has not decreased
significantly although the research effort has decreased dramatically since 1990.
NOOA gives one reason for the success of the distributed models: most successful
models in an operational use are models which have well developed parameterization
tools.
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Figure 2 shows comparison between lumped and distributed model results for a
catchment. It can be observed, if the initial flood event is not considered, that the
distributed model describes better the peaks and falling floods. However, the
difference between the lumped and distributed models is not dramatic.
Figure 2. Comparison between observations and distributed and lumped model results in
the Baron Fork catchment at Eldon, USA (NOOA 2010).
3.3 GENERAL PRINCIPLES OF THE LUMPED HBV MODEL
The material in this chapter is based on the SMHI (Swedish Meteorological and
Hydrological Institute) original documentation.
The HBV model (Bergström, 1976, 1992) is a rainfall-runoff model, which includes
conceptual numerical descriptions of hydrological processes at the catchment scale.
The HBV model was originally developed by SMHI in the early 70´s to assist
hydropower operations. The aim was to create a conceptual hydrological model with
reasonable demands on computer facilities and calibration data. The HBV approach
has proven flexible and robust in solving water resource problems and applications
now span a broad range. The HBV-model is named after the abbreviation of
Hydrologiska Byråns Vattenbalansavdelning (Hydrological Bureau Waterbalancesection). This was the former section at SMHI, the Swedish Meteorological and
Hydrological Institute, where the model was originally developed.
Figure 3 shows the schematic structure of the HBV model. Each catchment area
receives precipitation which can be divided into different areas and into snow and
water fractions. The precipitation is routed through surface and deep storages to the
catchment outlet.
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Figure 3. Schematic representation of the HBV model structure (SMHI). Each catchment
area receives precipitation which can be divided into different areas and into snow and
water fractions. The precipitation is routed through surface and deep storages (base flow)
to the catchment outlet (SMHI).
The general HBV water balance can be described as:
P = precipitation
E = evapotranspiration
Q = runoff
SP = snow pack
SM = soil moisture
UZ = upper groundwater zone
LZ =lower groundwater zone
lakes = lake volume
dt = time step.
The left side of the equation describes hydrological dynamic processes and right side
change of the storages including snow, soil, groundwater and lake storages.
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HBV and IWRM Watershed Modelling User Guide
The time step is usually one day, but it is possible to use shorter time steps. The input
information to the HBV model is:
Precipitation records (on daily or shorter timestep)
Air temperature records (if snow is present)
Evapotranspiration (can be also calculated from for instance minimum and
maximum temperatures)
Runoff record (catchment outlet discharge) for calibration
Geographical information about the river catchment
The model consists of subroutines for meteorological interpolation, snow accumulation
and melt, evapotranspiration estimation, a soil moisture accounting procedure and
routines for runoff generation. It is possible to run the model separately for several
subbasins and then add the contributions from all subbasins. Calibration as well as
forecasts can be made for each subbasin.
The standard model uses a rather crude weighting routine and lapse rates for
computation of areal precipitation and air temperatures. In HBV-96 a geostatistical
method, based on optimal interpolation (e.g., Daley, 1991) was introduced (not
available in the EIA implementation).
The runoff generation routine is the response function which transforms excess water
from the soil moisture zone to runoff. It also includes the effect of direct precipitation
and evaporation on a part which represents lakes, rivers and other wet areas. The
function consists of one upper, non-linear, and one lower, linear, reservoir. These are
the origin of the quick (superficial channels) and slow (base-flow) runoff components
of the hydrograph. Level pool routing is performed in lakes located at the outlet of a
subbasin.
Although the automatic calibration routine is not a part of the model itself, it is an
essential component in the practical work. The standard criterion (Lindström, 1997) is
a compromise between the traditional efficiency, R2 by Nash and Sutcliffe (1970) and
the relative volume error, RD:
In practice the optimisation of only R2 often results in a remaining volume error. The
criterion above gives results with almost as high R2 values and practically no volume
error. The best results are obtained with w close to 0.1. The automatic calibration
method for the HBV model developed by Harlin (1991) used different criteria for
different parameters. With the simplification to one single criterion, the search method
could be made more efficient. The optimisation is made for one parameter at a time,
while keeping the others constant. The one-dimensional search is based on a
modification of the Brent parabolic interpolation (Press et al., 1992).
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Figure 4. The dots represents either HBV operational forecasting applications, consulting
studies or scientific tests.
In different model versions HBV has been applied in more than 40 countries all over
the world (Figure 4). It has been applied to countries with such different climatic
conditions as for example Sweden, Zimbabwe, India and Colombia. The model has
been applied for scales ranging from lysimeter plots (Lindström and Rodhe, 1992) to
the entire Baltic Sea drainage basin (Bergström and Carlson, 1994; Graham, 1999).
The model is used for flood forecasting in the Nordic countries, and many other
purposes, such as spillway design floods simulation (Bergström et al., 1992), water
resources evaluation (for example Jutman, 1992, Brandt et al., 1994), nutrient load
estimates (Arheimer, 1998). HBV has been used for the following applications:
flood warnings - streamflow and volume forecasting for appraisal of flood risks,
and development of flood risk maps
hydropower - short term inflow forecasts for operational hydropower planning
at dispatch centers and volume forecasts of up to a year for seasonal reservoir
planning
pre-feasibility studies - quality control of water stage and discharge records,
extension of historical records and ground water simulations
irrigation - determination of evapotranspiration and forecasting inflow to
reservoirs and storage pounds to aid regulation of irrigation schemes
dam safety - design flood computations including reservoir management
strategies
climate change - studies of the effect of changing climate conditions on run-off
patterns, soil moisture, ground water change and evapotranspiration
In Scandinavia the HBV-system is the standard operational run-off forecasting tool in
nearly 200 basins. The HBV model is the standard forecasting tool in Sweden, where
some 45 catchments are calibrated for the national warning services, mainly in small
and unregulated rivers. Forecasting for hydropower companies are made in an
additional 60 catchments. Hydrological forecasts can be divided into:
1. short range forecasts - For small catchments and local inflows, forecasts can
be issued for timesteps down to one hour a number of days ahead, depending
on requirements and the resolution of the meteorological forecasts.
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2. medium range inflow forecasts - Most commonly used application with time
steps from 12 to 24 hours for a period up to ten days. The system allows the
operator to check, approve or update the forecasts depending on how critical
the inflow situation really is.
3. seasonal inflow volume forecasts - Based on the HBV model, the technique
uses historical statistics to calculate forecasts of up to a year for seasonal
reservoir planning or appraisal of flood risks. The service improves profitability,
but also allows provision of reliable information to the public. In case of high
discharge, this is an important factor for good relations with the community.
3.4 EIA HBV MODEL
The EIA HBV model is a modified version of original SMHI HBV model. The EIA
application includes a simple graphical user interface that uses the same data formats
and system software as all other EIA models.
Figure 5 shows the schematic structure of the EIA HBV model. The model uses four
storages: surface, middle, groundwater and river/lake ones. Surface water can infiltrate
to the middle storage and middle storage water can be passed through a porous soil or
small holes (perlocation) to the groundwater storage. The middle and groundwater
storages discharge to a river/lake storage and catchment outflow is finally obtained
from the river/lake storage.
Precipitation
etr
Snow
model
PET
yield
Ssurf (surface storage)
Infiltration
Smid (mid storage)
Percolation
qmid
qgw
Sground (groundw. st.)
qriver
Sriver (river st.)
Figure 5. EIA HBV model schematic structure.
The model input data are:
PREC = precipitation, mm/d
TAVG = average daily air temperature at 2m height, C
TMIN = min daily air temperature at 2m height, C
TMAX = max daily air temperature at 2m height, C
TLR = temperature lapse rate, K/m
SWIN = incoming shortwave radiation, MJ/m2/d
CLOUD= cloudiness, 0-1
RHUM = relative humidity, 0-1
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WIND = wind speed, m/s
ATMP = atmospheric pressure at sea level, mb
EPAN = pan evaporation, mm/d
The actual data required depends on the evaporation method selected (see below).
The model parameters are:
Petmethod – potential evapotranspiration computation method
o
Off – pet is given directly in a time series file
o
PrTa – Priestly Taylor method, required TAVG, KIN and CLOUD
o
Epan – pan evaporation, requires EPAN
o
Tminmax – requires TMIN and TMAX
o
Penman – requires KIN, TAVG, WSPEED, RHUM, CLOUD
Latitude – latitude in degrees for radiation computation
Petcoor- multiply potential evapotranspiration by this value, usually 1
Albedo – land surface albedo for incoming radiation computation
Z0 – roughness coefficient, m, for penman PET computation
Zd – roughness displacement height, m, for penman PET computation
Zm – wind speed measurement height, m, for penman PET computation
Rainmult – multiply precipitation values by this number
Intcpmult – fraction of the precipitation that fills interception storage (water
caught by vegetation), 0 = no interception
Intcpmax – interception storage maximum value, mm
Psurfmax – surface storage max value
Pinfexp – infiltration exponent
Pkperc– percolation rate coefficient for emptying mid storage to ground water
storage
Pkmid1 – mid storage emptying coefficient
Pkmid0 – storage limit value for additional mid storage emptying coefficient
(saturation point or increased emptying when storage fills up)
Plmid0 – additional mid storage emptying coefficient
Pkground – ground water storage emptying coefficient
Pkriver – river water storage emptying coefficient
Pcmid – mid storage concentration coefficient
Pcground – ground water concentration coefficient.
Using these parameters the processes in the Figure 5 can be expressed as:
Infiltration = yield (Ssurf/Ssurfmax)infexp
Percolation = Pkperc * Smid
qmid = (Pkmid1 + Pkmid0) * Smid
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qgw = Pkground * Sground
qriver = Pkriver * Sriver
etr = PET * Ssurf / Ssurfmax
yield = precipitation – interception
d(Ssurf)/dt= yield – etr – Infiltration (Surface storage change per time unit =
precipitation yield – evapotranspiration – infiltration to the middle storage)
d(smid )/dt = Infiltration – qmid – Percolation
d(sground )/dt = Percolation – qgw
d(sriver)/dt = qmid + qgw - qriver
3.5 EIA HBV MODEL APPLICATION STEPS
3.5.1 Install modelling software
The VIVSetup.exe modelling software package needs to be installed for the user
interface, analysis tools and the HBV model.
If the MRC ToolBox DTT (Data Transfer Tool) is utilised for preparing the model input
(and output) data, then DTT needs to be installed.
3.5.2 Prepare input data into the HBV model format
HBV model as well as the IWRM and 3D models use txd ASCII file format. The txdformat is presented in Chapter 5.2.3. Starting from any ASCII format, the txd-files can
be prepared by three different ways:
1. edit and format data with a text editor
2. use 3D model user interface to import data
3. use the DSF DTT (Data Transfer Tool); the preferred method
4. use the TXD time series tool by Tess Sopharith.
The first method is error prone and is not recommended. The second method is
presented here in case the DTT is not available. The third method is preferred as it
utilises standard data management tools and procedures, facilitates linking of different
models and utilises the MRC ToolBox Knowledge Base. The third method is also
easies once data is in the Knowledge Base. The last method is easy and practical and
has been proven quite popular in practical work.
3.5.3 Data preparation using the 3D model user interface
1. Select EIAModels on the Windows desktop or Start/Programs menu
or
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2. Select Models/ 3D in the EIA dialog window and press OK-button
2. Select Source data/ Application setup…
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3. Give the path of the Data directory where the HBV application data is, e.g. c:\temp\,
press OK-button
4. Select Source data/ Timeseries data files…
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5. Select Import data from the dialog window
6. Check New file; give files to read from and write to (path must be included!), how
many header lines there are in the input file, input file time format (e.g. DD/MM/YYYY);
define station information - station location/name, lat-long or UTM coordinates and
station elevation if available.
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7. Push Variable information-button and edit/add variables. For each variable give
name, unit and variable number in the input file.
7. File is created and can be edited with Edit data- and Edit header-buttons.
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8. Edit the output file with a text editor and delete unnecessary lines in the header, for
instance in the example below lines dbname, lat, lon and zpos should be deleted.
3.5.4 Data preparation with the DTT (Toolbox Data Transfer Tool) using the ToolBox
Knowledge Base data
1. Start the DTT tool
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2. Select source application, normally KB (ToolBox Knowledge Base)
3. Select source scenario, start and end dates and destination application (this must be
DMS!)
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4. Select destination folder, this should be the same where you run the HBV-model.
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5. Press Next-button and select points and variables, for instance precipitation
6. Press Add to Destination-button
7. Add Sitename and Frequency by pushing …-button in the Sitename column
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8. Add Easting, Northing and Elevation if they are missing by double clicking the
corresponding column and typing in information
9. Press the Run-button to create the file, the filename is the output parameter +
sitename
3.5.5 Create model application
Select EIAModels on the Windows desktop or Start/Programs menu
or
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2. Select Watershed conceptual HBV in the EIA dialog window and press OK-button
3. Save the file in the HBV application directory.
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3. In Parameters/ Files menu provide Name of the application area, area in km 2 and
out, initial, end and cmp files. The out and cmp files are in txd-format. The cmp file is
the observed discharge of the catchment outlet.
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4. Give weather files for the model in Parameters/ Weather files. Use Add-button to
add one or more files.
5. Model is ready to be run in Model/ Run menu. The computational time should
correspond to the weather file information.
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6. Additional parameters can be defined through the Parameters menu. For instance a
lake can be defined in the menu.
3.5.6 EIA HBV model calibration
Model parameter optimization methods can be used to find optimal values for the
parameters. An optimization method is able to automatically go through a set of
parameter values and find the best possible fit to measured data with a given criteria.
An optimisation algorithm is also included into the HBV model interface. To select
optimization variables select Parameters/ Variables available for optimization. Not too
many variables should be selected because finding a global optimal set of parameter
values becomes more difficult and uncertain more there are variables.
To start the parameter optimisation, select Model/Optimize from the menu. The
maximum and minimum allowed values can be specified for each parameter. The
ranges can be set also automatically (Small ranges or Full ranges buttons). The
maximal number of iterations can be also specified.
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The optimized model run can be compared to the measured values by selecting
Results/ Comparison. The Results report window provides r2 of the fit (see previous
chapter) and average computed and measured discharge.
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3.6 APPLICATION OF THE EIA HBV MODEL TO THE THEUN HINBOUN WATERSEHD IN THE LAO
PDR
Hands-on-exercise: Given data in csv-format, prepare HBV model
input data. The files are Weather_Laksao.csv (weather data) and
THPP.csv for catchment outflow (reservoir inflow).
Hands-on-exercise: Given data and instructions in previous
chapters, apply the EIA HBV model to the Theun Hinboun catchment
(area 8920 km2) including model calibration. Identify peak catchment
flows for the data given. Objective of the modeling is to plan storage
capacity for accommodating maximum discharge situations.
Figure 6. Location of the Theun Hinboun hydropower development area (ADB).
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Hands-on-exercise: After obtaining discharges, calculate weekly,
monthly and flood season average discharges using the
ModelingToolbox DMS time series analysis tool. Hint: locate HBV
model txd-output file, double click it, select time series layer, use
Compute/One timeseries/Grouping statistics – analysis tool.
Koponen)
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4 DISTRIBUTED HYDROLOGICAL MODELLING
The IWRM model is a distributed physically based/conceptual hydrological model
based on grid representation of the modelled catchment. Hydrological processes in the
catchment are simulated using simplified physically based formulations. The
catchment is described in the model as a group of grid cells and water balance, runoff
and leaching of nutrients are calculated separately for each grid cell. From the grid
cells, runoff is collected to the catchment’s outflow point with a river net model, where
calculation of lakes is included as well. The model can be used, for example, to inspect
the effect of land-use changes to catchment hydrology. The model includes also a
nutrient leaching and transport module that enables, for example, simulation of the
effect of land-use changes to water quality.
The model is based on rectangular grid (Figure 7), where each grid cell is individually
computed and has an own set of parameters such as ground slope and aspect,
vegetation type and soil type. These grid values are obtained from digital elevation
model, land use data and soil type data. In each of the grid cells simulated hydrological
process, include precipitation, snow hydrology, infiltration, evapotranspiration,
seasonal vegetation development, soil water content, groundwater height, and flow
into streams. Groundwater flow and stream flow are computed between grid cells.
Typical grid cell sizes range from 0.01 to 1 km2. Computation time resolution depends
on input data resolution, for daily data 3 to 6 hour time step have been used. An
application can include any number of grid cells. However, computational time
increases with increasing number of grid cells.
Model
grid - 3d view
b)
a)
Figure 7.
View from Vortsjarvi river watershed (in Estonia)
Visualisation of a IWRM model grid,
displaying a) land elevation with colours
and stream flow network and b) surface flow routing directions.
Typical model setup requires digital elevation model and land use data from the target
catchment. Running and calibration of the model requires meteorological and
hydrological time series, e.g. precipitation, daily average temperature, and river flow.
The model requires calibration since usually some of the model parameters are not
known from measurements and must be determined by calibration.
In grid cells containing ground the calculation is divided vertically from top down to
vegetation layer, ground surface layer and two soil layers. In permanent lake areas
there is only one water layer in use. In the calculation, following processes are taken
into account (see also Figure 8):
Interpolation and correction of meteorological data
-
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Temperature
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-
Precipitation
Interception of precipitation in vegetation
Infiltration of water in the soil
Water accumulation in pond storage and surface runoff
Evaporation
-
From interception storage
-
From ground surface
-
Through vegetation from soil
Plant growth
-
Seasonal crop growth based on temperature sum
-
Perennial plants leaf area index change based on temperature sum
Crop water demand
-
FAO56 method of calculating evapotranspiration for different crops
-
rice paddy water ponding, return flows and farm losses included
-
sub-division of basic grid cells into crop areas with full calculation of
hydrology for each crop area
Water movements
-
Between soil layers
-
From grid cell to another
-
From grid cell to river or lake
In winter conditions
40
-
Accumulation and melting of snow
-
Effect of soil freezing on soil properties
-
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Evapotranspiration
Precipitation
Flow from
grid boxes
above
Pintakerros
Surface
layer
overflow
kerros
1 1
Soil
Layer
interflow
kerros
2 2
Soil
layer
Wilting point
Field capacity
Maximum capacity
Figure 8.
ground water flow
Flow to river
Components of grid cell water balance.
For each day, the model first interpolates daily meteorological data to each grid cell
using height correction when required. In the surface model, interception is first
estimated using a simple storage model and vegetation leaf area index. If needed,
snow model is then applied. Infiltration is computed using Green-Ampt model, possible
overflow is accumulated into pond storage and surface runoff. Evaporation is
estimated using interpolated potential evaporation, pond and interception storages, soil
moisture, and vegetation data in the grid cell.
In the model, the soil has been divided into two layers and the layer depths can be
defined freely. The water storage of both layers is divided into two differently behaving
parts in field capacity water content. In flow through soil the flow amount is influenced
by horizontal conductivity of the soil, ground water height and grid cell slope. The water
leaving from each grid cell can continue on to a river in the grid cell or to a lower grid
cell determined by the flow net. In surface runoff the amount of water leaving from the
grid cell to the next grid cell or to a river depends on ground surface flow resistance
and ground slope.
The river model uses river network that is calculated from model grid elevations and
digitized river network. An example of a river grid is shown below in Figure 9. All the
river nodes in a watershed are connected to a single outflow point at watershed area
border.
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Figure 9.
Part of a river network, digitized river and watershed boundaries shown in blue
and red, and computed flow network with black arrows.
The river flow computation is based on kinematic wave approximation of the St.
Venant equations (flow speed depends only from slope and flow depth) with trapezoid
river cross sections. The river model is solved numerically from upstream cells to
downstream direction, so downstream surface height does not affect the upstream
flows. This method enables usage of a reasonably large time step and therefore
shortens computation times.
Lakes are handled separately. Any set of neighbouring grid cells can be set to be a
lake. Each lake is a storage that keeps account of the water level as a difference from
the reference water level. Water level changes are linearly related to volume changes,
which are computed from inflow, outflow and lake evaporation. Outflow from the lake is
computed as a function of the water height using river section equations or a given
surface height/flow amount curve. Evaporation from lakes happens at potential rate.
4.1.1 Water quality and erosion computation
IWRM has been configured to compute following water quality variables:
suspended sediment (SSED) divided into clay, silt and sand
total phosphorous (PTOT)
total nitrogen (NTOT)
dissolved inorganic phosphorous (DIN)
dissolved inorganic nitrogen (DIN)
IWRM model has been also used to simulate algal growth (eutrophication).
Several different methods can be used for water quality computations. These are listed
below from simplest to more complex methods:
Flow-dependent concentration, where the concentration of a water quality
variable in output depends on the outflow value. The concentration may have
linear or non-linear dependency on the outflow amount. Calibration to water
quality measurements or pre-calibrated parameters is required.
A method where ground water and overflow may have different and flowdependent concentrations. Calibration to water quality measurements or precalibrated parameters is required.
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Erosion modelling is provided for suspended sediments and nutrients. Soil type
erosion parameters are required from literature or calibration. Water quality
measurements are helpful in model verification.
The above methods deal with nutrient leaching from the soil. The nutrient transport in
rivers is computed with mass conservative advection equation. Lakes are handled as
pools, where all incoming nutrients immediately mix to whole lake volume.
Sedimentation in rivers depends on flow speed in each river segment. Sedimentation
in lakes occurs in given lake sedimentation rate.
The IWRM erosion model calculates the amount of soil material detached from the soil
by surface runoff. The soil material is assumed to be detached in two ways: by the
motion energy of rain drops and by surface runoff as rill flow. Usually the flow cannot
transport all the detaching material, and some of the sediment is deposited on the
bottom of the rill. The erosion model is calculated for every grid cell in the case that
surface runoff occurs.
4.1.2 Input and output data
The IWRM model setup requires a lot of geographical data; at least an elevation model
is required to set up the model grid. Land use data is needed as well - often sufficient
land use information can be obtained from normal maps, but satellite image based
information is often the best alternative. If detailed soil information is not available,
values based on land use types and typical soil parameters from literature can be used.
Long time series of meteorological and hydrodynamic data are required - the longer
the time series used for modelling are, the more reliable the results usually are. As a
result, hydrological variables at any point in the watershed during the computation
period are obtained. Reliability of the results depends on quality of the input data,
success of the calibration, and suitability of the modelling approach to the modelled
catchment. Below is a summary of the input data required and output data produced
by the IWRM model:
Input data
digital elevation model of the catchment (e.g. 50m resolution)
land use data for the catchment
soil type data for the catchment (new version of IWRM only)
catchment boundary line
shorelines of lakes in the catchment
optionally digitized river network of the catchment
precipitation (mm/d), at least one station
average temperature, (°C), if snow calculation is used
potential evaporation computed from one of the following
-
pan evaporation (mm/d)
-
min and max temperature (°C),
-
average temperature (°C), cloudiness (%)
-
average temperature (°C), short wave radiation (MJ/d), wind speed
(m/s), relative humidity (%)
average outflow (m3/s), at least one station for calibration of the model
water quality measurements, for calibration of the water quality model
Computed result (daily values)
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average daily river flow (m3/s) at any point within the catchment
other model variables at any point within the catchment, for example,
evaporation (mm/d), corrected precipitation (mm), lake surface height (m), and
ground water height (m)
4.1.3 Model user interface
With the model user interface (Figure 10) one can set model parameters, drive the
model and look at the model results. The basis of the model interface is a map window,
which shows the model grid and related information for the chosen model case. Land
use, soil type, elevation model and flow net can be chosen to be shown on the map.
The user guide for the IWRM model and user interface can be found in chapter 3.
Additionally, any kind of GIS information can be added to IWRM in raster or vector
format. For the more advanced modification and analysis of the GIS data and for
building model grids, RLGis application can be used (user guide in chapter 2).
Figure 10.
Model user interface. Model window, where land use and flow layers and time
series and weather points can be seen.
Model’s land use and soil types and parameters associated with them are in a central
position in the use of the model. For placing and modifying the parameters there are
similar dialogs for both parameter groups. Below (Figure 11 and Figure 12) are the
dialogs associated with land use types.
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Figure 11.
Dialog for land use types, where a list of the land use types in use can be
seen.
Figure 12.
Setting of land use parameters, on the left parameter classes, on the table in
columns land use types and on the rows individual parameter values.
The model results are provided as time series and 2D-animations. For the processing
of time series, there is a separate time series window, where time series can be drawn
and analysed. Typical tasks that can be performed in the time series window are for
example the comparison of two time series visually or with different goodness of fit
tests and the calculation of monthly and yearly averages. In the Figure 13 below, a
flow comparison in two time series windows is shown.
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Figure 13.
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Comparison of measured and calculated time series.
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5
BASICS FOR USING THE IWRM MODEL
5.1 SOFTWARE INSTALLATION
Prior to use of the IWRM hydrological model software the software has be installed to
the computer. Follow the steps provided below in order to fulfil the setup procedure.
1. Double click the VivSetup.exe or VivSetupFull.exe file
You have to be signed to the computer as an Administrator or user
with administrator’s rights to be able to install the software properly.
2. Press Next >> in the Welcome to setup window
3. Software License Agreement: Read carefully the “Master end-user license
agreement” prior to accept the agreement by pressing Yes
4. User information: Write your name and company/organisation/university you
are based in to the User information window. Accept the user information by
pressing Next >>
5. Select components: Select the programme components you want to install.
You have to select at least the following components to be able to run the
IWRM model:
a. Viv base system
b. IWRM
Also the RLGis component is advised to be installed. RLGis is GIS programme
supporting the files used in the IWRM model and needed for data preparation
of some of the model input data.
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The Flow & Water quality models component can be left out if you don’t need
to use the EIA 3D hydrodynamic model. This can be also installed later if
needed.
When you have selected the components you want to install, press Next >> to
continue.
6. Choose destination location: Select the location you want to install the
model software. The suggested directory [C:\EIAModels\VIV] is recommended
to be selected as it is also used in this manual as the reference directory. Thus,
by selecting this directory it would be easier to follow the manual as well. Also,
some parts of the model and data processing don’t support spaces in the file
names and thus, it is not recommended to install the programme for example
under the “programme files”.
If you wish to change the directory, press Browse and select the folder and
location you want to install the software to.
Press Next >> to continue.
7. Start installation: You can check once more the target directory and user
information to be sure that everything is ok before starting the installation.
Press Next >> to start the installation.
You can follow the installation process from the Installation process window.
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8. If the following window appears, the EIAviv has been successfully installed to
your computer. Press Finish to exit the installation.
If the model software setup is not working or there comes an error
message the reason can be following:
Some of the Viv-software components are running.
 check this by going to Task manager and there processes.
If you see a process of Viv, end that process and try to install
the software again
You haven’t had the administrator rights when installed the
software
 sign in to the computer as administrator
You don’t have enough space in your hard disc
 release space in your hard disc and try to install again
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In many Setups two folders (VIV and VIVH) will be installed.
The VIV folder contains the programs for the EIA 3D model and the
VIVH programs for the IWRM model. Make sure you have the right
folder selected when you use the model, otherwise it will not open
properly. The folder used can be changed with VivDirSetup.exe which
is provided in VinSetup.exe.
5.2 FILE SYSTEM
The IWRM model system consist two groups of files:
model system files
model application files
5.2.1
Model system files
The model system files are installed during the model software installation (Section 5.1)
and are typically located under C:\EIAModels\VIVH folder. The model system files
contain the models and user interface programs.
Don’t make any changes to the files in VIV-folder nor move these files
or the software may not work properly anymore.
5.2.2
Model application files
The model application files define the actual model application grids and contain also
model related data. These files are installed in C:\EIAModels directory under each
model application sub-directory. Illustration below shows the model application
directory structure.
C:\EIAModels
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VIV – model system files
Example_model – model application files
hyddata – time series data files
IWRMexamp.vmp – flow model parameters
Make sure that the model grid *vmd is in the same folder than the
model application file (*.vmp – file). In case it is in different folder, its
path has to be defined properly in Source data – Application setup
part of the menu.
Models can be started by opening a preferred model directory under the application
directory, and double clicking a model parameter file. For example, to start the
example_model open the C:\EIAModels\example_model directory and double click
"example_model.vmp" file (this is a flow model parameter file).
File types listed below are found in the model application directories. Double clicking
files marked with underlined bold type in windows explorer will start associated model
user interface with the selected file.
IWRM model directory
*.vmp – IWRM model parameters
Data file types (for example in hyddata-subdirectory)
*.txd – timeseries data files (see txd format below)
*.ipd – RLGis geographic data
5.2.3
TXD file format
TXD file format a text file format for storing structured table data. The file contains
contain two parts, the file header and the file data. The file header contains any
number of file identification information and a data definition. The data part contains
any number of data rows divided into data fields as defined the file header.
txd2
identification line
identification line
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…
field definition
field definition
…
data
data line
data line
The file should always start with a row containing the text "txd2". After this line come
the file identification lines, where each line consists of an item identifier and an item
value. The item identifier must be a string starting with a letter and containing no
spaces or tabs. The item value can be a number or a string. For example,
location "Koijärvi 2"
ypos 65.236
xpos 22.183
Additional identifiers, such as data source, missing value identifier and coordsys
explanation can be added to further identify the data.
A field definition is composed of a field type, field name and field length/format.
Following field types are available.
str
bool
byte
int
real
time
date
- string
- integer 0-1
- integer 0-255
- integer 32-bit
- real number
- time, e.g. date and clock values together
- date value
Time type fields have a format definition instead of length definition. The format
definition is a string in double quotes (“”) containing letters D,M,Y,h,m,s, meaning date,
month, year, hour, minute and seconds, for example “YYYYMMDDhhmmss”.
time date “YYYYMMDD hhmm”
After the field definitions there is a line containing the word “data”, and after this the
data lines. Data values must be always separated by at least one space character, the
field lengths do not include this space character. Below is an example of a complete
txd file. String fields in the middle of the row may not contain spaces within the string,
for the last field of the row this restriction does not apply.
txd2
location "Koijärvi 2"
xpos 22.183
ypos 65.236
missing -9999
time date “YYYYMMDD hhmm”
int wdir_degr 3
real wspeed_m/s 5
DATA
19990101 1200 234 5.0
19990102 1200 34 3
19990103 1200 45 35.0
19990104 1200 43 45.0
Summary of standard file ids:
location –
statid –
xpos –
ypos –
coordsys –
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data location name
station identifier (usually 4 characters long string is used)
measurement point x – coordinate, can be UTM or longitude
measurement point y – coordinate, can be UTM or latitude
optional, defines the coordinate system for xpos and ypos
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dbname –
pidfile –
missing –
optional, defines measurement data file in measurement point file.
defines measurement point file in measurement data file
identifies missing data value used in file
Summary of standard field names:
date –
depth –
variable –
value –
pid xpos –
ypos –
name –
contains time value of measurement
contains measurement depth in meters
contains variable code if several variables are in same file
contains variable values, used together with "variable" field
contains a unique identifier for the location, usually a 4 character
long string is used (e.g. BAT1, KCH3)
in measurement point file, contains point x-coordinate
in measurement point file, contains point y-coordinate
in measurement point file, contains location name
Summary of some of the standard codenames and units for variables:
PREC
QRIVER
HRIVER
EPAN
TAVG
TMIN
TMAX
SWIN
CLOUD
RHUM
WIND
precipitation
measured flow
water level
pan evaporation
daily average air temperature
daily minimum air temperature
daily maximum air temperature
incoming shortwave radiation, MJ/m2/d
fraction of the sky covered by clouds, 0-1
relative humidity, 0-1
wind speed, m/s
5.3 STARTING THE IWRM MODEL SOFTWARE
To start the IWRM program, select IWRMstart.ip from the start menu or desktop. The
main window of the IWRM model user interface can be seen below
There are two options to start the IWRM model application:
From the EIAModels shortcut icon on the desktop
By open the model application and at the same time the model software by
open the *.vmp file under the C:\EIAModels\[model_application_name]
directory
5.3.1
Starting the software from EIAModels desktop shortcut icon
1. double click the EIAModels shortcut icon on your desktop
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If the EIAModels shortcut icon doesn’t exist in your desktop there are
two options:
Your installation hasn’t been completed successfully
 re-install EIA model software to your computer
Someone has removed the shortcut icon from your desktop
 go to folder C:\EIAModels\VIV
 click right mouse button the file named EIAModels.ip
 select Create shortcut and the shortcut is created to the
folder you are in
 copy/cut/drag the shortcut into your desktop
2. Select the Watershed IWRM model and press OK
3. The IWRM2-window opens with the main menu, tool-bar and noname.vmp
model window
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5.3.2
Starting the software from vmp-file
1. go to the directory of the model application you want to open (e.g.
C:\EIAModels\IWRMEXAMP)
2. double click the model application you want to open (e.g. river1.vmp)
3. The model software opens with the model application you wanted to open
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If the EIAModels doesn’t open as shown above, there are few options
to check:
Your installation of the model software hasn’t been completed
successfully
 re-install EIA model software to your computer
During your installation you haven’t been logged in as an
administrator and part of the software registration hasn’t been
finished and thus, the software doesn’t work properly.
 log-on to the computer as Administrator and install the
model software again
You have the wrong program directory selected. With
VivDirSetup.exe select the correct folder, the default folder is
C:/EIAMODELS/VIV
5.4 IWRM USER INTERFACE
The IWRM model user interface main window is shown below. The window contains a
menu, a toolbar and a work area. The menu is used to select actions to be performed.
The toolbar contains, for example, tools for moving around in the model grid area. The
work area may contain different type of windows, for example model window, time
series windows and data table windows (Figure 14).
Main menu
Tools menu bar
Data table
window
Layer window
Time series
window
Model window
Report window
Figure 14.
5.4.1
IWRM hydrological Model graphical user interface.
Main menu
The menu structure of the model reflects model usage, which is divided into six main
menu item:
1. File handling and model grid importing, File menu
2. View control options, View menu
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3. Input data definition an setting model parameters, Data menu
4. Model computation and parameter optimisation, Model menu
5. Examination of results, Results menu
6. Window control, Window menu
Each main menu item is divided into main functional classes listed below:
1. Application handling, File menu
a. Application file handling – opening and saving applications
b. Editing files and selecting editor to be used
c. Exit application.
2. View control options, View menu
a. Set map marker size for items (e.g. reservoirs, irrigation areas, time
series points)
b. Set application coordinate system
c. Open report and command windows.
3. Data definitions, Data menu
a. Define grid file, land use change, precipitation area files
b. Define output files and locations
c. Define system files (model and processing files)
d. Start and end states
e. Weather data files, weather interpolation and correction
f.
Definition of evaporation method
g. Soil, land use, crop, crop pattern classes and types
h. Water quality variables
i.
Model parameters
j.
Control definitions including hydropower reservoirs, irrigation, water
transfers, groundwater pumping, river discharges
k. Timeseries and field drawing management
l.
Statistics output definitions.
4. Model computation and optimisation, Model menu
a. Computational parameters
b. Model computation
c. Model optimisation.
5. Examination of results, Results menu
a. Flow comparison with measured values
b. Timeseries results
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c. Animation results
d. Statistics results
e. Running of macros for automated output processing and reporting.
6. Window control, Window menu
a. Window management
The main menu bar and tools menu bar change according to the
active window.
5.4.2
Tools menu bar
The tools menu bar shows several tools related to picture handling and data item
management.
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These tools are available when the model main window is active. The tools are
described below:
Tool
Function
Zoom. Magnify or zoom into the picture. Click the button and then
drag a rectangle with mouse to the window.
Zoom back. Maximum view or Zoom out. Click this button to return to
the no zoom state. No effect if no already in maximum view.
Move view. Click this button and drag the view in the desired
direction.
Copy as metafile. Copy the picture to clipboard as a picture
(Windows metafile). Can be used to transfer pictures to text
processing and drawing programs.
Copy as bitmap. Functions often better than the metafile copy option.
Layer data info. Gives information on the data of the selected layer to
the command window.
Modify layer data.
selected area.
Change the values of the layer data in the
Cancel layer modification in the selected area.
Add data item. Click the button and press with the left mouse button
the location you want to add a data item. Select the type of data item.
Remove data item. Click the button and select the data item to be
removed with the right mouse button. Does not work yet.
To release the selected tool click it. You can see the selected tool as
pressed down. E.g. zooming tool is selected in illustration below:
You can also click right mouse button when the mouse cursor is over
the map and the zoom is released:
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5.4.3
Model window
The model window shows the computational model grid, where usually water is
displayed with blue and land with different colours. The colours depend on whether soil,
land use or DEM is selected to be displayed.
The grid is decorated with symbols representing different model input and output data
items, for example:
Time series site (output)
Weather (input)
Water quality load (input)
River discharg point – add, subtract or set (input)
Irrigation, water transfer and water diversion
(input)
Groundwater pumping (input)
(Hydropower) reservoir (input)
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5.4.4
Layer window
The IWRM layer window is in the left hand side of the IWRM main window. It displays
the layers and controls in the model, their order and activity. The layers can be either
the model inputs or outputs.
Different layers can be activated by clicking the square next to them at the left window
with the left mouse button. The layer is active if there is a circle in the middle of the
square.
The layers are shown in the window in the order they will be drawn (upper layer will be
drawn on top of the lower layer).
The layers can be managed by clicking the right mouse button on top of the layer and
choosing from different options.
1. To view and modify the layer properties choose Properties… The properties
window is different for different layers. In the properties window for grid data
layers one can change the name of the layer and modify palette colours.
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2. To remove the layer choose Remove
3. To move the layers up or down in the window and in the order they are drawn
select MoveUp or MoveDown
4. To draw a histogram from the layer data choose Histogram. Select use palette
data by ticking the box next to it and if you like select % (otherwise will be
number of grid cells). Press Compute and the histogram in table showing the
percentage or number of cells in each class will appear in a separate window.
5.4.5
Command window
Command window informs the possible errors within the model use. User can also give
commands to the programme if needed. Most of the commands, however, will be given
through the GUI and Command window provides mostly information from the
programme to the user.
You can open the Command window from View – Show Cmd window
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5.4.6
Data table window
The model input data, as discharge measurements, water level, etc, can be accessed
and/or edited and analysed through the data table window:
The table itself shows the date of the data and data itself. As can be seen the Menu
bar and toolbar have changed from the one which is available when model window is
open.
1. The information data table window can be plotted as picture and statistics can
be calculated
a. The properties of the timeseries (name, coordinates, etc.) can be seen
from Table/Properties.
b. To plot the weather timeseries, select the entire column with the
variable you want to plot (to select an entire column, click the left
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mouse button on top of the name of the column), or the time period of
that column. Then press from the menu Data/plot as line (plots as a
line, for example for temperature) or Data/plot as bar (plots as a bar,
for example for precipitation).
c. To calculate the statistics (sum, average, min, max etc.) of the weather
data, select the entire data or part of the data and select
Data/Statistics.
2. Sometimes it is necessary to modify the data files (add missing data, take
away measurement errors). These actions can be done by modifying this data
table window.
a. You can save the changes you have made to the table by pressing
Store button.
b. To insert new rows go to the place where you want new rows (for
example where there is dates missing) select Edit/Insert Row. To
remove rows go to the correct place and select Edit/Remove Row(s).
c. Data can be copied from one weather file to another by selecting the
data and using commands Edit/Copy and Edit/Paste. Make sure that
the same day does not occur several times. Press Store to save the
changes.
d. To save part of the weather data to another file, select the desires time
period (select the dates as well). Then select Data/Write selection to
file.
e. Then import data from file select Data/Import lines from file and
select the correct file.
If you do some changes to data table which you want to keep, you
must always save the changes by pressing Store on the toolbar.
Sometimes when you want to modify the files shown in the data
table window more, it may be easier to open the data file in Excel or
similar program, do the modifications and safe the file again in txd
form.
5.4.7
Timeseries window
Timeseries window shows the output data timeseries as picture.
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The picture handling tools are available when the timeseries window is active. The
tools for picture handling are
The first three tools from left and the fifth tool are the same as in IWRM main window
toolbars (see chapter 0). The functions of the other two tools are
Tool
Function
Picture properties. Displays a format window, where picture
properties (line colour, type, name etc.) can be modified.
Copy as textdata. Copies the picture data in text format to clipboard.
Works only for timeseries pictures. Can be used, for example, to
transfer picture data to spreadsheet.
Picture properties can be changed with the Picture properties tool
window, where the outlook of the picture can be managed will open.
. A format
The window shows all the timeseries drawn in the picture in the window on the left.
The timeseries being managed can be changed from the window in the left hand
corner of the main window. The colour of the timeseries can be changed from Colours
Line Color and Fill Color (for dots and areas). The timeseries can be drawn as line,
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bar, column or line and the sizes and widths of these can be changed from the right
hand corner of the window.
To change the coordinates of the picture choose CoordSystem from the list.
1. The Header of the picture can be given from Header.
2. The titles of the x-axis and y-axis can be given from Title.
3. The minimum and maximum values of the x- and y-axis of the picture can also
be changed from Min and Max.
The picture can be saved with the copy as metafile tool
. While the correct picture
is activated press the copy as metafile button. Then go to the application where you
want the picture to be (for example a Microsoft Word document) and select Paste. The
picture will appear in the application.
Different tests and comparisons can be performed for the results while in the
timeseries result window with the options of the Compute menu. Some of the options
are described in more detail in the chapter 12.2 Result comparisons.
5.5 OPEN EXISTING MODEL APPLICATION
Existing model application can be opened by selecting from the menu bar File - Open
and selecting the application in vmp format.
Existing model application can also be started directly by double clicking the
application name (*.vmp).
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5.6 SAVING MODEL APPLICATION
The model application can be saved by selecting from the menu bar File - Save or if
you want to save the application with a different name File - Save As.
You are not able to undo the saved model settings. Thus, if you are
making big changes on the parameters or other model settings, it is
always good to keep the original model application saved with
another name (see above Save as).
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6 CREATING NEW IWRM APPLICATION
In this chapter the basics for creating a IWRM model are presented including
creation of the model grid with RLGis application and set up of a new IWRM
application
The chapter is divided to two parts:
6.1 Creating a model grid
6.3 Useful RLGis actions
6.4 Usage of the created grid in the IWRM
6.1 CREATING A MODEL GRID
This chapter is made for the user guide for creating the grid for EIA IWRM Model.
Below the process is described.
The model grid is a division of the catchment to be modelled. In order to generate the
grid, a digital elevation model (DEM) of the target area is needed. The model grid cell
size is usually larger than the DEM grid so the model grid elevations need to be
computed from the DEM grid. Typically arithmetic average is used to combine height
values. After averaging the model grid should modified so that it has the following
properties:
For each model grid point, that is not the outflow point; there is a neighbouring
grid point that has a lower or equal elevation than the point in question.
There is one outflow point, into which all the other points flow. The outflow
point is at the border of the modelled area.
Land use data, if imported from satellite picture, also needs grouping. For this data,
averaging is not feasible; instead, land type distribution preserving computation is used
to group the data into larger grid cells. The computation aims to preserve the relative
sizes of different land use types.
To create the grid the original data can be in many different forms: digital elevation
model (DEM), depth points, contour lines; and in many different file types: *.shp, *.bil,
*.ipd, *.dig, etc. Thus, basic knowledge of the GIS in general should be known as well
as the basics about the use of some common GIS applications.
6.1.1 RLGis getting started
The description of the RLGis programme can be found in the appendices
To open the RLGis program, select rlstart.ip or select EIAmodels and select from data
processing RLGis. The RLGis new application window will open.
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6.1.2 Data needed
Required input data
Following data is required to create a IWRM model grid.
DEM, in one or more files for the target area
Watershed boundary for the target area, or larger watershed including the
target area
Land use data in one or more files for the target area
Soil data in one or more files for the target area
Raster data, e.g. DEM, land use and soil data, must be in BIL or TIFF format. Vector
data, e.g. boundaries, rivers and lakes must be in ESRI shape file format.
If land use or soil data is not available, a single class land use or soil type can be used
for testing purposes. In this case a dummy land use or soil data grid is created by
copying the DEM grid and setting values of the grid to one.
The DEM, land use data and soil data have to be in the same grid
size to create the IWRM grid. The grid sizes can be changed to the
same size in the RLGis.
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6.1.3 Creation of raster data files from ESRI shapefiles
6.1.4 DEM processing
1. Import DEM data (raster) with command Add Layer – Import file - *.bil or *.tif
("Add Layer" button is in the sidebar above layer list)
a. A file selection window opens. Select preferred file in the file window
and click Open
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b. A Import grid data window opens, select preferred coordinate area, or
just click OK
c. A new layer containing the selected data is opened in the window.
2. Combine files to a single layer if required
a. Select the two raster layer to be combined to single layer from the layer
list. Use control to select both layers.
b. The grids must be next to each other, and have same size grid box
c. Select GeogrComp - Grid - Grid – join two adjacent grids
d. A new raster layer will be created containing the combined grid data
3. Convert DEM to float type and meters. Often DEM data is encoded to
decimeters or centimeters, and stored as integers. IWRM requires meters to be
used in the DEM, and the DEM must be of float type. To convert layer, first the
layer type must be set to float, and then, if not already in meters, the data
values must be converted to meters.
a. First select the DEM layer from the layer list
b. To convert the data to float format select GeogrComp – Grid - Gridchange grid type command, and select the To format to singlepr.float,
and click OK
c. If the DEM data is not meters, use the command GeogrComp/Grid/Grid
– transform values to change the values to meter. After giving the
command, enter a suitable computation formula to the dialog window
and click OK. For example, to convert from decimeters to meters, set
the transform values computation formula to "X*0.1".
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d. The DEM is now of float type and in meters.
4. Import watershed boundary (shape file)
a. Select command Add Layer – Import file - *.shp
b. A file selection window opens. Select preferred file in the file window
and click OK
c. The shape file is opened and drawn on the screen
5. Decide on enclosing rectangle that contains the target watershed. It should be
at least 2 x target model box size larger than bounding box of the watershed
boundary. The enclosing rectangle (=bounding box) can be created using the
following steps.
a. Select the watershed boundary line using the Select/Edit Lines tool
.
b. Select GeogrComp - Line - Line – bounding box command from the
menu
c. To expand the bounding box, give a suitable number (meters), for
example "3000" to the dialog window and then click OK.
d. A new layer containing the watershed boundary bounding box is
created.
e. Click Select None-tool
to cancel watershed boundary selection
6. Cut DEM data (=raster) to enclosing rectangle (=polygon)
a. Select polyline or polygon layer containing the cutting polygon from the
layer list
b. Use the Select/Edit Lines tool
to select the cutting polygon
c. Select the line layer containing the cutting polygon and a raster layer to
cut from the layer list
d. Select GeogrComp – Grid - Grid – extract data using polygon
command from the menu
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e. A new layer containing raster data inside the selected polygon is
created.
7. Combine DEM grid boxes to model resolution using "Min"
a. Select the DEM raster layer from the layer list
b. Select GeogrComp – Grid - Grid – combine grid boxes command
from the menu
c. In the appearing dialog, give number of grid boxes to combine together,
combination method, and click OK. The combined grid box value is
computed from the set of values in the original grid using one of the
following methods
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Min – minimum of the values
-
Max – maximum of the values
-
Avg – average of the values
-
Median – count values in each class, select one that has the
largest count
-
Diff – difference between Max and Min
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d. A new raster layer will be created, in which the grid boxes are
combined.
8. Cut DEM to target watershed using the same procedure as in point 6 but with
the watershed boundary as the polygon.
9. Save the layer by clicking the right mouse button on the top of the layer name
in the list on the left and by selecting Save
10. Save the project as RLGis application in .gip file format from File/Save As
6.1.5 Land use processing
The Land use is processed in a similar way to the DEM processing.
1. Import land use data with command Add Layer – Import file - *.bil or *.tif
2. If required, combine files to a single layer with GeogrComp - Grid - Grid –
join two adjacent grids (see more details above in chapter 6.1.4)
3. Cut land use to enclosing rectangle with GeogrComp – Grid - Grid – Extract
data using polygon
4. Make sure DEM and land use left bottom corner coordinates match. Adjust if
necessary.
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5. When feasible, reclassify land use to obtain a smaller number of land use
classes
a. Select the landuse layer from the layer list
b. Select GeogrComp – Grid - Grid – reclassify command from
command menu.
c. RLGis will check values in the grid layer, and displays a reclassification
table containing grid data values in the first column of the table, and
new values in the second column of the table.
d. Change the values of the second column of the table to new values,
and the click Store button in the toolbar. To cancel the classification,
click Cancel.
e. The reclassification replaces the original values of the selected layer.
f.
To modify the colors of the new classification, press the right mouse
button while on top of the layer and choose Color palette. Colors can
be modified by pressing the left mouse button on top of the cell
showing the current color, choosing the new color from the opening
dialog window and pressing OK. To delete the colors not in use,
change the number in the number of colors cell. To save the changes
made, press OK.
6. Combine land use grid boxes to model resolution with GeogrComp – Grid Grid – combine grid using the option "Median"
a. Note that the amount of area used for each land use do change in this
process, especially if there usually are many land use classes within a
combined grid box
7. Cut Land use to target watershed with GeogrComp – Grid - Grid – Extract
data using polygon and save the layer
6.1.6 Soil data processing
The Soil data is processed in a similar way to the land use and DEM processing.
1. Import Soil data with command Add Layer – Import file - *.bil or *.tif
2. Combine files to a single layer if required with GeogrComp - Grid - Grid – join
two adjacent grids
3. Cut Soil data to enclosing rectangle with GeogrComp – Grid - Grid – Extract
data using polygon
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4. Make sure DEM and soil data left bottom corner coordinates match. Adjust if
necessary.
5. When feasible, reclassify soil data to obtain a smaller number of soil classes
with GeogrComp – Grid - Grid – reclassify
6. Combine Soil data grid boxes to model resolution with GeogrComp – Grid Grid – combine grid using the option "Median"
a. Note that the amount of area for each soil class do change in this
process, especially if there usually are many soil type classes within a
combined grid box
7. Cut Soil data to target watershed with GeogrComp – Grid - Grid – Extract
data using polygon and save the layer
6.1.7 River network computation
1. Open the processed DEM layer done in step 1.
2. To get the river network right, it is advisable to 'carve' rivers and lakes to DEM,
that is, to lower the elevation in locations where there is river or lake. This is
done in steps 4-11.
3. If the DEM is accurate enough it can be used directly to calculate the river
network. In this case steps 7-11 are used. To successfully compute flow
directions for a DEM layer, the DEM must fill following criteria:
a. The DEM represents some real watershed, so that all the grid boxes of
the DEM flow to single outflow point. The DEM must be cut using the
boundary of the watershed.
b. The outflow point of the watershed is the lowest point in the DEM, and
is located at the boundary of the DEM
c. The computation algorithm is able to solve sinks and flat areas,
however, the results may not be realistic if the DEM too coarse or
inaccurate.
4. Import any river and lake data you have on the area Add Layer – Import file
5. Create a new grid layer from river lines
a. Select the river line layer and an example grid data layer from the layer
list (for example the DEM) and select GeogrComp – Line – Polyline convert to grid command. The resulting grid type, position and box
size will be taken from the example grid layer and will be preset using
the example grid. Select as WriteOpti the option new grid. A new grid
will be created.
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b. Draw lakes (polygon data) to the grid obtained in previous step using
the GeogrComp – Line - Polygon – convert to grid command while
the grid is selected. As WriteOpti, select the option set to grid. The
data will be set to the grid created in the previous step.
c. Multiply the new river/lake grid values with, for example 5, by selecting
GeogrComp – Grid - Grid – transform values and setting the
multiplying factor to the selected value and pressing OK.??
6. Subtract grid obtained river/lake grid from DEM using GeogrComp – Grid Grid – two grid computation command. From the two matrix computation
window select the operator as – sign and Result area as Second (the DEM).
This operation will produce a new DEM which is used from here on.
7. Ensure that the lowest grid point of DEM is at the target watershed outflow
point, at the boundary of the watershed grid.
a. If necessary you can lower the outflow point elevation by using the
Modify Gridded data tool
when the DEM layer is selected and
setting the value to the lowest grid point value.
8. Create an empty flow layer
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a. Activate the DEM. Select GeogrComp – Flow - Flow –Create empty
flow from DEM
9. If lake data is available, set lakes to flow layer using lake data.
a. Select the lake polygon layer and the new flow layer from the layer list,
and select GeogrComp – Flow - Flow – set lakes using polygons
command from the menu.
b. Lakes and also be set from land use raster data using GeogrComp –
Flow - Flow – set lakes from land use command.
10. Compute flow layer from lowest point
a. Select the flow layer and the DEM layer
b. Select GeogrComp – Flow - Flow –compute from lowest point
c. The computation may take quite long time, depending on the size and
complexity of the DEM.
11. Verify flow layer using map data, change where needed
a. To change the existing flow network, select the flow layer and use the
Modify Gridded data
tool to select the grid cell to be modified.
The arrow showing the flow direction in the selected grid cell will show
in different color.
b. The flow direction of the grid cell is defined by the outflow direction. To
change the outflow direction of the grid cell, click the mouse in the new
outflow direction.
c. To change the flow direction of a river the outflow direction of several
grid cells may have to be changed.
d. Make sure that the flow network is continuous and there are no loops.
e. Save the modified flow network layer by choosing the layer, clicking the
right mouse button and choosing Save.
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The way the flow network is shown in the model window can be
changed by selecting the flow layer from the list and click right mouse
button, by select Properties and by changing the Threshold value.
With a smaller threshold value, the flow network is shown in more
detail. If the value is set to 0 flow network in every grid cell can be
seen. By ticking the arrows cell, the flow direction can also be seen.
6.1.8 Create river data layer
1. Select the flow-layer and dem-layer
2. Create new river data layer from the flow data layer using command
GeogrComp – Models - Models – create river data
a. The parameter defining the river properties can be changed
b. Parameters wmult and wexp define the width of the river
c. Parameters dmult and dexp define the depth of the river
d. Parameters nmult and nexp define the Manning friction of the river
3. The variable shown in the RiverData layer can be changed
a. Click the right mouse button while on top of the RiverData layer in the
layer window and select Properties
b. Choose the variable you want to display from the Display Data and
press OK
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4. River data can be modified if necessary in selected grid cell
a. Select the variable you want to modify as described above
b. Select the Modify Gridded data tool
.
c. Select the grid cell you want to modify with the left mouse button
d. Change the value of the variable and press OK.
6.1.9 Creation of the grid file
1. Set DEM, soil type, and land use grid types in the layer options dialog of each
grid, if not already set.
a. Select each layer, press the right mouse button and select properties
or alternatively double click each layer. Rename the layer in the new
window opens. Select dem, landuse and soil from the drop-down list
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to the appropriate layers. RLGis needs this information when creating a
model grid.
b. Save the layer by clicking the right mouse button on the top of the
layer name in the list on the left
2. Select DEM, soil type, land use, flow and river data layers from the layer list
3. Select GeogrComp – Models - Models – create IWRM2 grid from the menu.
4. Write a name for the model grid file in the file window, and click OK.
5. vmd format file with the name you gave will be automatically created in the
same directory as the layer files.
6.2 SOIL AND LAND USE RECLASSIFICATION
Available land use and soil classes are in most of the cases based on geological,
vegetation, habitation etc. types. In contrast hydrological modelling requires
hydrological classes. Because of this mapping of original classes to hydrological
ones is required. Another reason for using reclassification is facilitation of calibration
through reduction of classes. Because many classes differ only slight hydrologically it
makes sense to group them togehter. It should be noted that for instance SWAT model
uses reclassification and large number of original classes are grouped into a few
representative ones for model simulations.
6.2.1 Soil reclassification
From the FAO soil types present in the Mekong River Basin (Table 3), a new
classification has been obtained by analyzing the hydrological behaviour of each soil
class and associating those that had common characteristics.
The new classification was based on the document Lecture Notes on the Major Soils of
the World (Driessen 2001) and its associated CD-ROM containing sample soil profiles
for each of the 30 World Reference Base (WRB) soil types (Figure 18). Table 4 shows
the proposed soil classification for the Mekong River Basin.
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Table 3. Soil types in the Mekong basin
Table 4. Soil reclassification
Properties such as sand, silt and clay percentages were obtained from the soil profiles
mentioned earlier; for the case where two soil classes were merged into a new one
(based on their similarities), their properties were averaged.
As a summary of the above two tables, Table 5 shows Mekong model soil classes and
original FAO class reclassification into the 8 model classes. It should be noted that
users are not limited to these 8 classes but can use any classification and
number of classes relevant to their application.
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Table 5. Soil classes
Model class
Title
Explanation
1
Water
Permanent water body
2
Acrisols
Subsurface accumulation of clays, low
base saturation
3
Histosols
Organic material
4
Argic
Argic/Ochric horizon, sand on top, clay
below
5
Ferrasols
Deep strongly weathered soils
6
Alluvial
Permanent or temporary wetness
7
Lithosols
Limited soil development
8
Cracking
Hard when dry, plastic when wet
FAO class
Explanation
Reclassified as
1
Ferric Acrisols
1
2
Gleyic Acrisols
1
3
Orthic Acrisols
1
4
Ferrasols
4
5
Gleysols
5
6
Lithosols
6
7
Fluvisols
5
8
Luvisols
3
9
Nitosols
7
10
Histosols
2
11
Vertisols
7
12
Planosols
3
Once the textural classes percentages were identified, parameters for the IWRM
model such as thr (soil residual water content), thf (field capacity) and ths (maximum
water content/saturation) were estimated by using the Soil Water Characteristics Hydraulic Properties Calculator found in Working Paper No.5 (Sarkkula 2006) and
developed by Saxton and Rawls (2006).
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6.2.2 Land use reclassification
Land use reclassification is based on previous modelling work in the Mekong Basin
(Table 6). Land use characteristics and parameterization were taken from the MRC
WUP-FIN Nam Songkhram model except leaf area index (LAI). LAI for various land
surfaces have been defined by Hageman (An improved land surface parameter
dataset for global andregional climate models. Max-Planck-Institute for Meteorology,
Report 336, Hamburg, 2002) and these values were used in the model with some
adaptations.
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Table 6. Landuse classes
Class
number
Title
1
Water
2
Decidious forest
3
Evergreen forest
4
Shrub and grassland
5
Irrigated agriculture
6
Agriculture
7
Floodplain
8
Urban
9
Glacier
GLC2000
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Explanation
Reclassified as
1
Tree Cover, broadleaved, evergreen
3
2
Tree Cover, broadleaved, deciduous, closed
2
3
Tree Cover, broadleaved, deciduous, open
2
4
Tree Cover, needle-leaved, evergreen
3
5
Tree Cover, needle-leaved, deciduous
2
6
Tree Cover, mixed leaf type
2
7
Tree Cover, regularly flooded, fresh water (&
brackish)
7
8
Tree Cover, regularly flooded, saline water
7
9
Mosaic: Tree cover / Other natural vegetation
2
10
Tree Cover, burnt
4
11
Shrub Cover, closed-open, evergreen
4
12
Shrub Cover, closed-open, deciduous
4
13
Herbaceous Cover, closed-open
4
14
Sparse Herbaceous or sparse Shrub Cover
4
15
Regularly flooded Shrub and/or Herbaceous Cover
7
16
Cultivated and managed areas
6
17
Mosaic:
6
18
Mosaic:
6
19
Bare Areas
4
20
Water Bodies (natural & artificial)
1
21
Snow and Ice (natural & artificial)
9
22
Artificial surfaces and associated areas
8
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6.2.3 Reclassification steps
Reclassification can be done in the RLGis software, for instance for soil classification:
a. Select the soil layer from the layer list
b. Select GeogrComp – Grid - Grid – reclassify command from
command menu.
c. RLGis will check values in the grid layer, and displays a reclassification
table containing grid data values in the first column of the table, and
new values in the second column of the table.
d. Change the values of the second column of the table to new values,
and the click Store button in the toolbar. To cancel the classification,
click Cancel.
e. The reclassification replaces the original values of the selected layer.
f.
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To modify the colors of the new classification, press the right mouse
button while on top of the layer and choose Color palette. Colors can
be modified by pressing the left mouse button on top of the cell
showing the current color, choosing the new color from the opening
dialog window and pressing OK. To delete the colors not in use,
change the number in the number of colors cell. To save the changes
made, press OK.
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The reclassification in the above figure is based on the 3S soil classification. Below is a
corresponding table that shows the original soil code, soil type, reclassfication number
and soil type explanation. The whole table contains altogether nearly 250 soil classes.
6.3 USEFUL RLGIS ACTIONS
6.3.1 Calculating upper areas
RLGis can be used to calculate the upper area of a point or a subcatchment. The
calculation is based on the flow net of the model so make sure the flow net is correct
and modify it if it is incorrect (modifying river network is described in chapter 2.2.3).
1. Select the point which upper area you want to calculate, or the lowest point of
the subcatchment.
2. Select the flow layer from the window in the left.
3. Select GeogrComp – Flow - Flow- calculate upper area
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4. This action will create a new grid layer with the grid cells that are upstream of
the point chosen selected. The border of this area can be modified to a line.
5. Select the grid layer you created earlier and select GeogrComp – Grid - Gridboundary to polyline
6. This action will produce a new line layer with the boundary line of the upstream
area or sub-catchment. This boundary line can then be used to extract the
smaller area from the entire catchment as is described next.
6.3.2 Create a new landuse/DEM layers for catchment
To extract the desired catchment or sub-catchment:
1. Select the (sub)catchment border and select the border layer also from the
window on the left.
2. Select the (sub)catchment border from the map with Select - Edit Lines tool
. From the window on the left select the (sub)cathement border AND land
use layer from the list on the left (use shift to select both). The (sub)catchment
border must also be selected on the map. Select GeogrComp – Grid - Gridextract data using polygon
3. The new layer name appears in the list on the left. Double click it and the new
window opens. Rename the layer. Select landuse from the drop-down list.
RLGis needs this information when creating a model grid.
4. Save the new land use layer by clicking the right mouse button on the top of
the layer name in the list on the left
5. Do the same with DEM from point “Select the (sub)catchment border and DEM
layer from the list on the left (use shift to select both). The (sub)catchment
border must also be selected on the map. Select GeogrComp – Grid - Gridextract data using polygon”
6. Extract the desired river layer:
a. Select the (sub)catchment border AND river layer from the list on the
left (use shift to select both). The (sub)catchment border must also be
selected on the map. Select Edit - Select inside polygon.
b. Select Edit - Copy
c. Select Edit - Paste and select Add as new layer
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7. This river layer will be used only for comparison. Often this layer contains loops
or other anomalies, and it cannot be used by the model.
8. Remove the original layers (the whole basin layers) by clicking the right mouse
button and selecting Remove.
9. Zoom to the (sub)catchment with Zoom to selected layers tool
10. Save the project as .gip file format from File - Save As
6.4 USAGE OF THE CREATED GRID IN THE IWRM MODEL
1. Open program IWRM or IWRM2 (IWRMstart.ip)
2. Select File - New from the menu
a. Add the name of the vmd file created earlier with RLGis to cell Gridfile
3. Select Data - Weather Data files
a. Press Add to add each Precipitation, Evaporation and Temperature file
(must be type .txd)
b. Make sure the stations have the right coordinate systems
4. Select Data - Landuse types
a. Press Add to add each landuse type, make sure the number of types is
the same as the landuse types in the grid
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5. Do the same for all the soil types by selecting Data - Soil types and adding
each type.
6. Set the parameter values, outputs, computational parameters and surface
model as detailed in the following chapters
The instructions on the use of the IWRM model are found in the following chapters.
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7 IWRM MODEL DATA MANAGEMENT
Most of the actions for data management can be found in menu Data:
7.1 REQUIRED MODEL INPUT DATA
For the grid file made in the RLGis:
Land height data: formats bil, tiff, ascii text
Land use data: formats: bil, tiff, ascii text
Soil type data: bil, tiff, ascii text
Digitized watershed borders
Optional: Digitized river data, formats: Esri shape file (SHP), ascii text
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Other input data besides the gridfile:
Daily precipitation (several stations), formats: ascii text (txd2)
Daily temperature (average or minimum and maximum), formats: ascii text
(txd2)
River flow measurements (m3/s), formats: ascii text (txd2)
In case water quality is computed: River water quality measurements, formats:
ascii text (txd2)
Optional data (can be used for verification and also for more accurate
computations):
o
Pan evaporation, formats: ascii text (txd2)
o
Incoming short-wave or total radiation
o
Wind speed
o
Relative humidity
7.2 FILES
For managing program files select Data – General files from the menu
1. Gridfile, which has been made in RLGis (see previous chapter), includes e.g.
the land use, soil, DEM, and flow information for the model.
2. There are three output files: common, time series and fields. In common output
file, the computation parameters are stored when computation finishes. Time
series output file includes the values for selected output variables. Field output
file includes the data for selected field variables.
3. The Files do not usually need to be modified. Only when a new project is
started is the gridfile changed.
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The information in the Files window do not usually need to be
modified. Only when a new project is started or the gridfile has been
modified in RLGis is the Gridfile changed.
7.3 WEATHER DATA
7.3.1 Weather data format
Weather data includes data of precipitation, temperature and optionally evaporation
used as input for the hydrological model. The model needs data from at least one
precipitation and one temperature station. If the evaporation calculation method is set
to pan evaporation, the model requires data from at least one evaporation station as
well.
The weather data can be seen by clicking the correct weather data point (blue square)
from the map and selecting timeseries.
The weather data can is shown in a data table window, which can be managed as
described in the chapter 5.4.6 Data table window.
Weather data files, usually files having an extension .txd, contain measured weather
information used to drive the hydrological model. The model then combines the data
from several sources using given algorithm, such as “use the closest data point”.
Weather files are ascii-text files in a specific 'txd2' format, containing a file header
followed by data lines. A weather file can contain measurements of several variables
from one point for several moments in time. The data lines in the file must be ordered
by time in ascending order. The different variables can also be in separate files.
The file header defines what variables the following data lines will contain. The
following data lines have each a time value and the data values of measured variables
defined in the header. The different data items on a line are separated by on or more
spaces or tabulators.
The file header contains a number of header lines followed by a header item name and
header item value. Header item names may be any character strings, but the header
line having type definition int or real followed by a variable name are used in reading
the file. Each of these lines says that in the following data lines there is a variable
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named here. The order of the lines defines the order in which the data values appear
on the data line.
As an example below a data file header and few data lines
txd2
location BAN_THA_KOK_DAENG
statid 180305
xpos 341172
ypos 1995322
zpos 145
time date "DD.MM.YYYY"
real PREC 8
real EPAN 8
data
01.01.1981 0
3.5
02.01.1981 0
4
03.01.1981 0
4
04.01.1981 0
4
05.01.1981 0
3.5
The fist line is always 'txd2' identifying the file format. The next header lines define the
measurement point name, station id, and point location coordinates for the model. The
following lines define what the following data lines hold: first defines time column and
time format, next lines real variable Precipitation and Pan Evaporation. Time format is
given in quotes.
Weather variables recognized by the model
PREC (mm/d, mm/h)
daily or hourly precipitation
TAVG ( C)
daily average temperature at 2m height
TMIN ( C)
daily minimum temperature at 2m height
TMAX ( C)
daily maximum temperature at 2m height
EPAN (mm)
daily Pan evaporation
SWIN (MJ/m2/d)
incoming shortwave radiation, MJ/m2/d
CLOUD
fraction of the sky covered by clouds, 0-1
RHUM
relative humidity, 0-1
WIND (m/s)
wind speed, m/s
Variable combinations that can be used to in the model
PREC goes with anything
EPAN and TAVG or TMIN and TMAX
TMIN and TMAX
TAVG and CLOUD
TAVG and SWIN
TAVG, SWIN and CLOUD
Weather files can be combined in the model in any way, as long as there is at least
one point having precipitation information, and at least one point having temperature
information. However, if there are several files containing temperature information
each of there files must have same variables defined, otherwise data interpolation
cannot be done. For missing data values the value –9999 should be used.
Time format can be changed using header item time format. The time formats may
contain the items YYYY, MM, DD, hh, mm, ss in any order separated by spaces or
some other characters. The characters in the string are interpreted as follows: Y years,
M months, D days, h hours, and m minutes. Below some examples
"YYYYMMDD hhmm"
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"YYYY MM DD hh"
"DD/MM/YYYY hh.mm"
7.3.2 Weather data file management
For managing and editing the weather files – Select Data - Weather Data files
1. To edit the weather file, first select the desired weather file and then click Edit.
a. In Weather file window, it is possible to reset the location of the
weather file
b. If needed multiply the measured data with desired coefficient. Also the
file where the measurements are found can be redefined.
2. To add new weather file, select Add.
b. Define the file name, location and measurement file.
If the measurement file includes the location of the weather station in
correct format the program will read it automatically. In this case you
do not have to define the location but press the map -> grid button to
move the location information of the x- and y-coordinated to grid
coordinates
7.3.3 Weather data interpolation
Weather data interpolation is managed from Data - Weather data interpolation
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1. Here you can set the interpolation type and height correction for different
variables.
7.4 START AND END STATES
Initial and end state files can be managed from Data - Start End states from the menu
1. In the beginning, an initial state file is not available. Hence the file name has to
be none. After the first run, end state of that can be used as the initial file for
the next run.
a. Run the calculation first without an initial state file (give “none” in the
initial file field), then copy the name of end state file to the initial state
file and give the end state file a new name. The calculation will start in
the same state as it ends.
b. Make sure the end state is appropriate to be used as initial state. For
example if the calculations are started during the dry season, the end
state should be from dry season as well.
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7.5 SURFACE MODEL
For setting common parameters – Select Data - Surface model
1. The latitude of the application area can be defined. The petmethod and
snowmethod can be chosen as well. Normally if measured evaporation data is
available, petmethod = Pan evaporation.
7.6 LANDUSE TYPES AND PARAMETERS
7.6.1 Landuse types
Landuse types have to be defined in the model
1. For managing the landuse types – Select Data - Landuse types
2. For each land use type, the name and code number need to be defined.
a. When setting up a new application, add new landuse types for every
landuse class from Add. Give name and code number (different
number for every type) for each landuse type.
b. To change the name or number of Landuse types select Edit.
c. To remove landuse type select Remove.
d. To change the order of landuse types, select MoveUp or MoveDown.
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All the land use types which are in the landuse grid have to be
defined in this field. The number of the landuse classes should
correspond to the number of landuses in the model grid.
7.6.2 Landuse parameters
The IWRM model has separate parameters for every landuse class.
1. The parameters can be found Data - Landuse parameters…
a. Landuse parameters are divided to Precipitation, Evaporation, Snow
model, Vegetation and Surface model parameters
2. To change the parameter value(s), write the new value and then for saving the
changes press Close. Normal Copy-Paste commands can be used for
managing the values.
7.7 SOIL TYPES AND PARAMETERS
7.7.1 Soil Types
Soil types have to be defined in the model.
1. For managing the soil types – Select Data - Soil types.
2. For each soil type, the name and code number need to be defined. Soil types
are managed in the same way as LU types.
a. When setting up a new application, add new soil types for every soil
class by selecting Add. Give name and code number (different number
for every type) for each soil type.
b. To change the name or number of soil types select Edit.
c. To remove soil type select Remove.
d. To change the order of soil types, select MoveUp or MoveDown.
7.7.2 Soil Parameters
The IWRM model has separate parameters for every soil class.
1. The parameters can be found Data - Soil type parameters…
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a. Parameters in Soil type parameters… are divided to Infiltration, Soil
layer 1, Soil layer 2 and Erosion parameters.
2. To change the parameter value(s), write the new value and then for saving the
changes press Close. Normal Copy-Paste commands can be used for
managing the values.
7.8 WATER QUALITY VARIABLES AND PARAMETERS
Water quality variables are managed in a similar way to landuse and soil types.
7.8.1 Water quality variables
Water quality parameters can be defined in the model (optional)
1. For managing the water quality variables types – Select Data – Water quality
variables.
2. For each land use type, the name and code number need to be defined.
a. When setting up a new application, add new soil types for every soil
class by selecting Add. Give name and code number (different number
for every type) for each soil type.
b. To change the name or number of soil types select Edit.
c. To remove soil type select Remove.
7.8.2 Water quality parameters
Water quality parameters are defined for each land use type
1. Water quality parameters are found in Data - Water quality parameters…
2. Parameter in Water quality parameters… are divided to Character loads and
Constant Concentration Model.
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3. The water quality parameters can be changed in the same way as landuse and
soil parameters.
7.9 GRID DATA
7.9.1 Grid info
The information of the grid data can be viewed by selecting Data - Grid info from the
menu. The following window appears:
Do not change the grid data in the Grid info box since it will affect the
function of the grid. For modification of the grid data, use the RLGis
program as detailed previously.
7.9.2 Grid modification
Some grid data can be changed by selecting Data – Grid modification.
1. River data of conductivity and river width can be changed by changing the
multiplier of this data. This action will multiply all the data with the same factor.
2. Lake output point’s conductivity and river width can be changed by changing
the multiplier of this data. This action will multiply all the data with the same
factor.
Grid values can be also edited by selecting Modify layer data tool button (pressed in
the figure below), selecting the layer to be modified (Landuse in the figure below),
selecting area to be modified in the map by mouse and specifying new value. New grid
is greated by the GrMake button tool. The new grid needs to be specified as the model
input and the model re-loaded before it is in use.
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You can also use the RLGis program for grid modification. It has
much more options than the IWRM model user interface.
7.10 LOADS
Loads are used as input for the water quality calculations. New loads can be defined in
two ways in the same way as new timeseries points.
1. For adding water load points– Click Add data Item Tool
a. Click the location you want the load point to be placed
b. Click the left mouse button.
c. Select the new LoadPoint
d. Give name to the point.
e. Define the variable and unit.
f.
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Give the name of the data file or then constant value.
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2. All the Load points in the model can be seen from Data - Loads. The Loads
can be edited, removed and added in the same way as timeseries
7.11 FLOWS
Flow points can be used to add, subtract or set the flow in the river. They are used to
simulate pumping of the water for example for irrigation, diversions which add water to
river and dams that regulate the river or lake.
To add a new flow point– Click Add data Item Tool
a. Click the location of flow point
b. Click the left mouse button.
c. Select the new river discharge option
d. Give name to the point.
e. Select whether you want the flow point to subtract or add discharge or set the
discharge
f.
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Give the constant value which is subtracted or added or to which the outgoing
discharge is set to or give the name of the data file.
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7.12 RESERVOIRS
Reservoir points are used to specify reservoir dimensions and operational rules. To
add a new flow point– Click Add data Item Tool
a. Click the location of reservoir point
b. Click the left mouse button.
c. Select the new reservoir option
d. Give name to the point.
e. Select whether you want to use simple rule curve, monthly rule curve or rule
curve with monthly pattern. Edit the rule curves and patterns.
f.
You can also specify discharge as a time series.
g. Specify volume-are-average depth relations (volume-depth is used in
reservoir sedimentation).
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Reservoir information can be also read automatically from IQQM
files by the command (use command window):
readIQQMreservoir(filename), where filename is an IQQM sqq-file.
7.13 IRRIGATION AND GROUNDWATER
Irrigation and groundwater are discussed in separate chapters.
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7.14 TIMESERIES
The model gives the results for each timeseries point after the calculation. Hence, the
desired variables can be observed in any point of the watershed.
7.14.1 Adding new timeseries points
New timeseries can be added in two ways
1. For adding timeseries points – Click Add data item tool
a. Click the location of timeseries point (preferably a point with flow
measurements)
b. Click the left mouse button.
c. Select Ts point.
d. Give the name of the measurement file if available. Give the timeseries
point a name (if the measurement file does not include a name already
or if there is no measurement file).
2. If you know the coordinates of the timeseries point or have them defined in the
measurement file you can also add timeseries by selecting Data – TsPoints or
double click the TsPoints layer in the layer window
a. Click Add
b. Define the name, location and /or the measurement file for the
timeseries point.
7.14.2 Editing timeseries
All the timeseries in the model can be seen from Data - TsPoints.
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1. To edit timeseries select the button Edit. Same window as when adding a new
timeseries will open. Here you can change the name, location and input file for
the timeseries.
2. To remove timeseries select the button Remove and press OK
3. You can also add new timeseris from the button Add as described above
7.14.3 Timeseries output
To choose the parameters to be stored in timeseries points – Select Data - TsOutput
from the menu. To select the desired output variables, tick the cell next to the derided
variable.
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Below is a list of additional clarifications to the time series output names:
Meteorology
o
shortwave = shortwave radiation
o
pet = potential evaporation [mm/d]
o
etr = evapotranspiration [mm/d]
o
atmpressure = atmospheric pressure
Snow
o
water equiv. = snow water equivalent [mm]
o
cover = water content of snow layer [mm]
o
l1= soil layer 1
o
l2 = soil layer 2
o
storage = water storage (m3)
Soil
Vegetation
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o
lai = leaf area index
o
T index = temperature sum [ C]
o
T neg index = temperature sum calculated from 5 C [ C]
River & Lake
o
runoff, unit [m3/s]
o
river A/ lake V = river cross-section or lake volume.
7.15 FIELD ANIMATION OUTPUT
The variables can also be printed as a 2D animation for the calculation period. Field
output defines the outputs for animation.
1. To choose the parameters to be stored as a field output – Select Data FieldOutput from the menu.
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2. To select the desired field output variables, tick the cell next to the desired
variable. For further explanations refer to the explanations in the time series
menu above.
3. The field output can be viewed as an animation for the whole watershed
(Results – Field data).
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8 MODEL PARAMETERS
Model parameters can roughly be divided into three sets: model grid data, such as
elevation, slope etc. included in the vmd-gridfile, general parameters such as
computation time and land use and soil type parameters, such as vegetation data for
each land use type.
Grid parameters are included in the vmd-gridfile, and are set using the RLGis-program.
General parameters including latitude, computations time and computation timesteps,
and can be set in Data - Surface Model and Model - Computation parameters
dialogs.
Land use type parameters are set in a table that accessible through Data - Landuse
parameters, soil type parameters are found in Data - Soil type parameters and water
quality parameters in Data - Water quality parameters. In the landuse and water
quality parameter tables each land use type has an own row of parameters and in the
soil type parameter table each soil type has an own row of parameters. Below is a list
of the parameters.
8.1 SURFACE MODEL
PETmethod - potential evapotranspiration method (required data must be available):
o
Off
o
Priestly-Taylor
o
TMinMax (Minimum and maximum temperature must be available)
o
Penman
o
Penman-Monteith
o
Pan evaporation (Pan Evaporation data must be available)
o
PET in weather file
Snomethod - snow accumulating and melting calculation method:
o
Off
o
Degreeday
8.2 LANDUSE TYPE PARAMETERS
8.2.1 Precipitation and Interception
rainmult
- correction coefficient for precipitated water (~ 1.05 – 1.1)
snomult
- correction coefficient for precipitated snow (1.325)
intercpmax
- interception storage maximum size
intercpmult
- fraction of area where interception occurs
8.2.2 Evaporation
petcorr
alb0
z0
zd
zm
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- potential evapotranspiration correction coefficient (1)
- surface albedo for shortwave radiation (0.6)
- aerodynamic roughness coefficient
- aerodynamic roughness zero-plane displacement
- wind measurement height
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8.2.3 Snow model
snomeltcoeff
snomeltmin
snofrzcoeff
snofrzmax
snoevapmult
rainsnomin
rainsnomax
snowcomult
snocomp
snowedens
roonewsnow
8.2.4 Vegetation model
topt
tbase
hemerg
hmature
pmidec
etob
minbm
laimethod
laimin
laimax
rzf1
rzf2
8.2.5
Surface model
Infpratemult
Infsratemult
impervious
dz0
mnover
rmn2
ddepth
dspacing
soilp1
soilp2
pbare
pcanopy
- snow melt coefficient
- minimum temperature for snow melt
- snow refreezing coefficient
- maximum refreezing temperature
- snow evaporation multiplier
- minimum temperature for liquid precipitation
- maximum temperature for snow
- maximum snow water holding capacity
- snow compression coefficient
- density coefficient for snow
- density of new snow
- optimum temperature for plant growth
- minimum temperature for plant growth
- temperature sum where after the plant will start to grow
- temperature sum when mature
- temperature sum where after the plant will start to wither
- energy to biomass conversion efficiency
- minimum biomass
- method for leaf area calculation (constant, depends on the
temperature sum)
- minimum leaf-area index value
- maximum leaf-area index value
- the amount of roots in soil layer 1
- the amount of roots in soil layer 2
- intensity factor of precipitation
- intensity factor of snow melt
- fraction of impervious ground of the grid area
- size of the pond storage (mm)
- coefficient for surface runoff
- Drainage depth for ditched areas
- Drainage spacing for ditched areas
- phosphorus number for soil layer 1
- phosphorus number for soil layer 1
- fraction of bare soil of the grid area
- fraction of high vegetation of the grid area
8.3 SOIL TYPE PARAMETERS
8.3.1 Soil model
infkz
infpsis
dz1
thr1
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- vertical conductivity for the infiltration model
- pressure parameter for the infiltration model
- depth of soil layer 1
- wilting point of soil layer 1/soil residual water content
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thf1
ths1
kz1
kx1
pclay1
psilt1
psand1
pgravel1
porgc1
- field capacity of soil layer 1
- maximum water content of soil layer 1
- vertical conductivity of soil layer 1
- horizontal conductivity of soil layer 1
- fraction of clay in soil layer 1
- fraction of silt in soil layer 1
- fraction of sand in soil layer 1
- fraction of gravel in of soil layer 1
- fraction of organic matter in soil layer 1
dz2
thr2
thf2
ths2
kz2
kx2
pfe2
pclay2
psilt2
psand2
pgravel2
porgc2
- depth of soil layer 2
- wilting point of soil layer 2
- field capacity of soil layer 2
- maximum water content of soil layer 2
- vertical conductivity of soil layer 2
- horizontal conductivity of soil layer 2
- coefficient of exponential runoff for soil layer 2
- fraction of clay in soil layer 2
- fraction of silt in soil layer 2
- fraction of sand in soil layer 2
- fraction of gravel in of soil layer 2
- fraction of organic matter in soil layer 2
8.3.2 Erosion model parameters
tau0
- critical shear stress
ksd
- soil splash detachment
ker
- soil erodability
The main parameters correspond to the schematic model processes shown in the
figure below.
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Evapotranspiration
Precipitation
petcorr
rainmult
lai
dz0
Flow from
grid boxes
above
overflow
Pintakerros
Surface
layer
mnover
dz1
kerros
1 1
Soil
Layer
infkz
z
interflow
kx1
kz1
dz2
kerros
2 2
Soil
layer
ground water flow
kx2
Flow to river
Wilting pointthr
Field capacity
thf
Maximum capacity
ths
,
Figure 15. Main model processes and parameters.
A selection of the model parameters are given in the Table below. The Table lists
model parameters, their explanations, units and ranges. Also sensitivity analysis is
presented (see next Chapter). Colours signify main calibration parameters (orange and
light green) and change of the flow indicators.
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Table. Selection of model parameters, their explanations, units and ranges. Table shows also
sensitivity analysis results for the 3S basin (see the next chapter)
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The table is based on the following baseline values:
cumulative flow 1.1.2004 - 31.12.2005 591'527 m3/s (sum of daily discharges)
base flow (dry season flow) 1.1 - 15.3 2005 388 m3/s
peak flow '3702 m3/s
peak time 21.9.2005 00:00
laimethod 4 (water).
Only one land use and soil class is used in the sensitivity analysis for the whole basin.
Table 2 shows model parameter values for snow calculation. These parameters are
needed in the Mekong for the Tibetan Plateau.
Table 2. Model parameters for snow calculation.
NOTE: Evaporation from snowpack is approximately 2 mm/month
Most important erosion parameters are pbare (see Table 1) and ksd:
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9 CROP, IRRIGATION AND WATER TRANSFER MODELLING
9.1 BASIC MODEL DIVERSION STRUCTURE AND CONTROLS
Irrigation, industrial and municipal water consumption and inter or intra basin water
transfer can be defined in the user interface. Inter-basin transfer and other water uses
where water is not returned to the modelled area can be defined with a river
discharge control. With it water can be added or subtracted from any grid point or
river flow specified. The addition, subtraction or set discharge can be specified to be
either constant or read from a time series.
The second option specifies water diversion into irrigation or other use with impact on
basin hydrology and flow. User selects first the irrigation or other area where water is
diverted to either by giving the grid cell coordinates numerically or specifying the area
on map with mouse (Figure 16). The coordinates can be changed in the dialog window
in the “Irrigation area” block (Figure 17). Diversion point is specified by giving either the
map or grid coordinates in the “Diversion point” dialog. Water extraction can be defined
from river, groundwater, lake or reservoir.
Diversion amount can be defined with 3 options: crop demand, constant diversion or
time series based diversion. Constant and time series based diversions are distributed
to the specified irrigation or other water use area. When crop demand is selected crop
mix can be defined for the selected irrigation area. When crop demand is selected only
one grid cell can be selected for the irrigation area because otherwise the distribution
of the crop areas within multiple basic grid cells would not be well defined.
The most important feature of the crop model is that the crop areas are calculated as
any other grid cell with full hydrology including infiltration, soil moisture, lateral
surface and soil water flow etc. The crop areas enable practical modelling not only of
many different crop types but also in general different land use types. The crop cells
are sub-divisions of the basic grid cells and can be considered to increase the model
grid resolution.
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Figure 16. Definition of an irrigation and water diversion areas in the model user
interface.
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Figure 17. Irrigation, diversion and water use definitions in the IWRM model user
interface.
Crop modelling is based on the FAO56 (Allen et. al. 2000) and DSF/IQQM (Beecham
2003) approach. It includes the following factors:
How much area and what crop type is planted each year. The area and
crop mix may also be specified as a time series file that changes each
year.
How much water each crop type needs for evapotranspiration and ponding.
How much water needs to be diverted from the river system, lake, reservoir
or groundwater to meet the crop requirement.
How much water is actually diverted from the river system depending on
the water availability.
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How much water is either returned to the river system as irrigation return
flow or farm losses.
The approach differs from the MRC DSF approach in a number of ways:
Simulation of the crops, irrigation demands and hydrology is done within one
model. In the DSF reference evapotranspiration is calculated with SWAT, then
provided for the IQQM for crop demand calculation which is in turn provided
back to the SWAT.
Crop modelling is fully coupled with hydrological simulation. In the IQQM
hydrology is not simulated. Full coupling enables crop and irrigation feedback
on the hydrology, for instance irrigation return flow can affect available
irrigation water or water availability can impact crop growth and crop status in
turn water demand.
In SWAT a watershed is divided into conceptual HRUs (Hydrological Response
Units) that describe characteristic areas with similar hydrology. In the IWRM a
watershed is divided into grid cells that use elevation, land use and soil type
specified for each location.
In practice the description of the watersheds and river systems is much more
accurate in the IWRM than in the SWAT. For instance in the basin-wide
application SWAT modelling area has been divided into about 800 sub-basins
but in the IWRM with 5 km resolution in about 33’000 grid cells and in the 2 km
resolution into more than 200’000 cells.
9.2 CROP MODELLING
Following the FAO56 the crop water demand modelling is based on calculation of the
reference evapotranspiration. The Penman-Montheit method for the evapotranspiration
has been identified as the most universal and applicable one: “The analysis of the
performance of the various calculation methods reveals the need for formulating a
standard method for the computation of ETo. The FAO Penman-Monteith method is
recommended as the sole standard method. It is a method with strong likelihood of
correctly predicting ETo in a wide range of locations and climates and has provision for
application in data-short situations. The use of older FAO or other reference ET
methods is no longer encouraged.” (Allen et. al. 2000)
The actual crop water demand is obtained with the help of a specified crop coefficient:
ETc
Kc ETo
where ETc is crop evapotranspiration [mm/d], Kc crop coefficient [dimensionless], and
ETo reference crop evapotranspiration [mm/d].
The irrigation demand (Dreg) needs to take into account farm loss (lost water between
diversion point and irrigation area) and excess water use that is returned to the
drainage system. The total demand is then
Dreq
Ireq * (1 FIR) * (1 FOF )
where Ireg is irrigation requirement, FIR is the factor for return water and FOF the factor
for farm loss. Example of the return flow and farm loss impact on downstream river
discharge is shown in Figure 18. The black line shows baseline without irrigation and
the red one with irrigation included for dry and wet season rice. Irrigation requirement
is the difference between the naturally available, precipitation and natural flow provided
water, and the actual crop requirement. The crop requirement includes crop
evapotranspiration and ponding water in case of rice. In the model ponding water is
transferred to available surface water and evapotranspiration is not double-counted in
the crop water demand.
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Figure 18. Irrigation water demand for dry and wet season rice as well as downstream
flow in case of no irrigation (black line) and irrigation included (red line).
Use can specify crop types and corresponding crop return and farm loss monthly
factors (Figure 19 and Figure 21). Model system contains default DSF crops and their
factor values that can be added by “Add set types”-button (Figure 19).
Crop types are defined through the menu “Data/Crop types”:
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Figure 19. IWRM model crop type definitions.
Figure 20. IWRM model crop monthly factors.
Similar to the crop types user can define ponding depth types and daily ponding water
depths in cm (Figure 21 and Figure 22).
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Figure 21. IWRM model rice paddy water ponding types.
Figure 22. IWRM model rice paddy water daily ponding depths [cm].
Each irrigation area can contain many different crop areas. The pump capacities and
crop areas (“crop mixes”) can be defined in the model in a crop mix dialog (Figure 23).
The pump capacities and crop areas can be specified either as constant or yearly time
series.
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Figure 23. Definition of the IWRM model pump capacities and crop mixes.
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9.3 WATER TRANSFERS
Water diversion is defined upstream of the transfer point:
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Select constant diversion or time series in the irrigation dialog window:
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Black line is baseline and red with 10 m3/s diversion.
Diversion location flow:
Flow downstream of the transfer location:
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10 GROUNDWATER
Previously IWRM model (VMOD) has had different groundwater formulations, but there
exist public domain groundwater models that could be also used in combination with
the model. The two main issues with groundwater modelling are (i) applicability of any
specific groundwater model to a selected modelling scale (basin-wide to sub-basin
scale) and (ii) existence of necessary soil data. In general soil characteristics such as
soil type and soil thickness are poorly known in the Mekong region, and groundwater
model has been designed taking this into account. Also there is indication that aquifers
play minor role in comparison to saturated soil water.
Model results in a groundwater irrigation case corresponding to the Figure 16 are
shown in the following figures. The time series in Figure 24s hows crop demand in
case of using groundwater for irrigation. Observe that the demand is seriously limited
by the groundwater availability. Figure 25 shows corresponding change in downstream
irrigation area river discharge. Figure 26 shows the groundwater depth in the water
diversion (groundwater pumping) point. The groundwater amounts are not able to
provide for the large irrigation demand in the case study and ground water is depleted
fast when irrigation is applied.
Groundwater use is selected in the irrigation dialog window:
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Figure 24. Irrigation demand in case of groundwater pumping.
Figure 25. Impact of groundwater irrigation on downstream irrigation area discharge.
Black line without irrigation, red line with irrigation.
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Figure 26. Groundwater (soil saturated water) depth in case of no irrigation (black line)
and with groundwater pumping (red line) in the groundwater diversion point.
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11 CALCULATION
The actions in this section can be found under the Model menu
11.1 COMPUTATIONAL PARAMETERS
To manage the computation parameters – Select Model - Computation parameters
from the menu.
1. Check the computation options. In normal calculations, soil model should be
two-level, river model kinematic (does not take into account downstream
water levels) or kinematic + wlevel (takes downstream water levels into
account), and lake model dynamic.
2. The startdate and enddate of the calculation have to be given in YYYY MM
DD –mode.
3. The Max landtype accords the maximum number of landuse types (rows in
Data/Landuse types). The landuse types with a higher code number will be
reduced to the highest code number in calculation.
11.2 RUNNING THE MODEL
To run the model – Select Model - Run from the menu
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1. It is still possible to change the start and end date of the calculation in this
window. To run the model press Compute. The model run will typically take
some minutes to be finished.
2. To view the report generated during the calculation – Select Data – Files Messages – Show or Results - Run message file
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12 RESULTS
12.1 VIEWING TIMESERIES
The results from the model calculations can be viewed in two ways
1. Click the desired timeseries point (yellow square) from the map with the left
button of the mouse and by choosing the desired variable from the list that
opens under timeseries.
a. All the variables chosen from Data - TsOutput are shown in the list
2. If you have a measurement file you want to compare the results against use
the comparison option.
a. Flow comparison options can be
Comparison options from the menu.
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b. Give name of the comparison (measurement) file of the point you want
to see in Flow datafile. Select the time series point you want to
compare with from Ts point dropdown list.
c. To compare the measured and calculated flow (defined above) –
Select Results - Flow comparison from the menu.
The timeseries drawn in the picture are listed in the small window on the left.
1. The timeseries can be deactivated and activated by clicking the square on the
left of the timeseries name. The circle in the middle of the square tells if the
timeseries is active or not. Only active timeseries are shown in the picture.
2. To select a timeseries click the left mouse button on top of the timeseries name
so that the background turns grey.
3. To save the timeseries, select the correct timeseries by clicking that timeseries
in the window in the left and press the right mouse button. Select Save as from
the menu, give a name to the timeseries and press Save.
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4. To manage the timeseries select the correct timeseries by clicking that
timeseries in the window in the left and press the right mouse button. From
hear he timeseries can be edited (Edit), removed entirely (Remove) and their
order can be changed (MoveUp and MoveDown).
5. The timeseries window can be managed using the timeseries window tools,
which are described in chapter 5.4.7 Timeseries window. The appearance of
the timeseries window (line colors and types, axis etc) can be modified using
the Picture properties tool
.
6. The picture can be saved by clicking the copy as metafile tool
while the
correct picture is activated. The picture can then be pasted to appropriate
application (for ex. MS Word) by selecting paste in that application.
12.2 RESULT COMPARISONS
Different results can be brought together from separate windows by clicking one
picture with the left mouse button, holding that button down and dragging and dropping
from to the other picture window. This way results from different timeseries points can
be brought to one window.
You can compare the results from different runs in the same window in two ways.
1. Keep the window from the previous run opened while you calculate the model
again. Then draw the new results in a different window and bring the results
form the two windows together by dragging and dropping one window to
another.
2. The second way is to save the timeseries you want to compare as a txd file
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a. Click the right mouse button on top of the selected timeseries and
select Save as... from the list opening. the timeseries a name and
press Save
b. Do the changes necessary, run the model again and draw a new
picture from the new results.
c. While the picture with the new results is active, push the Add button on
top of the small window on the left, select Timeseries (txd).
d. Select the timeseries you saved earlier. Press OK in the window that
opens. You don’t need to change the variable or the dates in the
window, even if they are not correct.
e. This timeseries will now appear in the new result picture as a new
timeseries.
12.3 COMPARISON TESTS
Different tests and comparisons can be performed for the results while in the
timeseries result window with the options of the Compute menu. There are several
options and only the most commonly used one’s are described below.
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The timeseries that is evaluated has to be chosen by clicking the name of the
timeseries on the left window (press control to select more than one). The timeseries is
selected when it appears in grey background.
For Compute - One timeseries the actions available include for example
1. Cumulative series. This action produces a new timeseries in the picture
showing the cumulative value of the timeseries chosen.
2. Grouping statistics. With this action you can calculate for example monthly
and yearly averages, maximums, and minimums. You can also group the
timeseries to winter and summer (or this action can also be used to group to
dry season and wet season) and change the start dates of these periods.
Choose the time period and statistics you want to evaluate from the dropdown
menus in Grouping and in Statistics. Then press OK. The action will produce
a new timeseries in the old picture.
3. Histogram. Produces a histogram of the selected timeseries. In the Histogram
parameters window opening, the number of divisions, minimum and maximum
limit can be changed if necessary.
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a. The histogram will be drawn in a separate window. The properties
(colors, titles etc.) of the histogram picture can be managed with the
picture properties tools in the same way as for timeseries pictures.
For Compute - Two timeseries the options are for example
1. r^2 of common points. Calculates the r2 measure of fit between the two
timeseries chosen in a result window. The r2 measure of fit can be used to
evaluate the model performance when it is used between the measured and
the calculated series. The r2 fit will appear in a TsComputeReport window.
2. subtract. Subtracts the second timeseries from the first and produces a new
timeseries in the picture with this subtraction. Can be used to evaluate the
differences between the two timeseries.
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3. x-y plot. Plots the two timeseries selected in an x-y plot in a separate window.
For Compute - Selected timeseries (one, two or more)
4. Statistics. Calculates the statistics (average, standard deviation, minimum,
maximum) of the selected timeseries in a separate results window.
5. Correlations. Calculates the correlation between the selected timeseries in a
separate result window.
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12.4 NUMERICAL TIMESERIES OPTIONS
To view the timeseries results in numerical format select one option of the following list:
Results – Summary timeseries (these are sum time series for the whole
application area)
Results – Time series points (all points and variables)
After drawing a time series select a time series on the left time series layer
window and right click it
12.5 ANIMATION OPTIONS
To view the animation for selected field variables select Results – Field Data:
One can select the variable to be animated, scale and color palette from the menu.
This opens the animation window:
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Drawing options such as the color scale and date font and position can be changed by
double clicking the layers in the left layer menu. Animations can be drawn either
continuously or stepped forward or backward with the play menu on the upper left
hand corner of the animation window.
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13 SENSITIVITY ANALYSIS
Model sensitivity analysis shows how much model outputs change in relation to the
model parameter and input changes.
The sensitivity analysis will be easier and results more clear if only one land use and
soil class is used. The class values can be edited in the IWRM model user interface by:
1. Select land use layer from the layer list. The layer needs to be active (white circle in
the land use box is visible; if not click the box with mouse)
2. Select the "Modify layer data" tool.
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3. Select the whole model area by dragging the mouse. Type in the land use class
number (for instance 2).
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4. Do the same for the soil layer.
5. Save modified grid by clicking the GrMake button and by giving a new grid filename.
6. Specify the grid filename in Data/General files-menu.
7. Save the project file (File/Save-menu) and open it (File/Open) to start using the new
grid file.
8. Add time series point to the outflow point.
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9. Select the baseline parameters in Data/Landuse parameters... and Data/Soil
parameters... Modifications are needed only for selected landuse (2) and soil type.
10. Run the baseline for two years period e.g. startdate 19960101 enddate 19971231
11. Plot time series of discharge by clicking outflow point/timeseries/River disch
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12. Change one parameter at a time, for instance Data/Land use parameters. Change
only for the selected land use and soil class.
13. Change the output filenames for the new scenario run in Data/General files
14. Compute the model and check the flow change compared to the baseline situation.
Compare the last year of the simulation period that the initial state does not affect the
results
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13. For instance calculate change in cumulative, baseline and peak flow and timing of
flood pulses.
Dry season average flow (baseline flow):
Yearly peak flow:
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Timing of a peak (YYYYMMDD hhmmss value):
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14 CALIBRATION
IWRM model is mostly physically based model, but it has some simplifications and
usually the data available is not sufficient to determine the values of the parameters.
Hence, calibration of the model is usually needed to find the combinations of
parameters within their physical boundaries that give the best possible results for the
model. For calibration discharge observations from at least one point in the watershed
are needed. The discharges the model calculates are then fitted as closely as possible
to the observed discharges by calibration.
Calibration of the model can be done either manually or by automatic optimisation
routine included in the model.
The calibration process starts with the identification of the most important parameters
to be calibrated. The amount of parameters in the model is so large that the calibration
of all of them either manually or automatically is very time consuming. Some of the
parameters have only very little effect on the results or are set by physical limitations
and can be left out of the calibration. The possible limits of the chosen parameters
should also be estimated.
14.1 MANUAL CALIBRATION
Manual calibration can be time consuming and difficult but if there is some data
available to determine the approximate parameter values and the modeller has an
adequate understanding of the model and the modelled watershed it can give good
results.
The manual calibration process involves changing the values of the most important
parameters chosen for calibration, calculating the model and evaluating the model
performance by for example calculating the r2 of measured and calculated flows. If the
model performance is better than with the previous parameter values, the parameter
values are adopted. Usually only one or two parameters are changed at once. This
process is continued until the model performance is deemed adequate or it cannot be
improved without going out of the physical limits of the parameters.
14.2 AUTOMATIC OPTIMISATION
The model has an automatic optimisation routine, which can be used to calibrate the
model.
The optimisation criteria is to maximize the r2 fit to measured flows, so in order to
perform optimisation the measured flow and the corresponding timeseries point in the
model should be defined in the Results - Comparison options dialog.
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To optimise model parameters select the Model - Optimise. The column use defines
the parameters that are included in the optimisation. The column value defines the
starting value for the parameter and min and max define the minimum and maximum
values for the parameters.
1. For selecting the parameters available for optimisation, the value in the field
use should be set 1. The value 0 means that the parameter is not available for
optimisation.
2. To set the limits of the parameters, change the values in columns min and max
for the desired parameter.
3. To get good results N should be at least 100-200, which also means that the
optimisation time will be several hours, even days.
4. To start optimisation, open the Model - Optimise dialog cell and press
Optimise. For changing the optimisation loops, the value of N can be changed.
The optimisation algorithm is slow, since the model evaluation usually takes a long
time and tens or hundreds of evaluations are needed to optimise the model. It is
advisable to optimise only few (up to five) parameters at one time.
14.3 CALIBRATION STEPS
Effective calibration depends on the application. However, it is possible to give some
general guidelines and steps for effective calibration procedure:
1. Calculate long enough to eliminate impact of the initial state (compare to the
model menu Data/Start and end states for giving initial values)
2. Maintain first proportionality of the class parameters (use for instance "Group
modification"-tool presented next chapter); fine tune later by changing
parameter proportions between main classes
3. Calibrate first rainmult and petcorr (rain and evaporation correction coefficients)
for obtaining rough correspondence with the observed flow amounts
4. Calibrate first baseflow during the dry season; use Table 1 "base flow"-column
to identify what parameters should be used and how much
5. Calibrate then wet season flow
6. Calibrate first rainmult and petcorr and soil layer thicknesses (pond storage on
the surface) dz0, dz1 and dz2 as they represent uncertainty in data
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7. Other soil properties may need to be calibrated because uncertainties of the
soil data (water content related parameters and horizontal hydraulic
conductivity).
14.4 CALIBRATION TOOLS
1. Set the calibration time series point and corresponding discharge observations
(Results/Comparison options).
2. Compute the model and compare with measurements (Results/Flow comparison).
The time series window shows the modelled and observed discharge. The Reportwindow shows statistical fit (R2) and average observed and computed flow.
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3. Change model parameters and run model again to find a better fit. Group parameter
tool (Data/ Group parameters) can be used to change parameter values in all land use
or soil classes. Value in the modification window (see below) either multiplies or adds
value to a parameter in all classes. Modtype defines modification type: 1 multiplies and
2 adds the value to the parameters. Modification type 1 maintains the ratio of the
parameter values across the different classes.
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PART II – MODEL DESCRIPTION
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15 RUNOFF MODEL
This chapter gives the model description of the runoff model component of the
IWRM hydrologic model including equations and theory.
The chapter is divided to ten parts:
15.1
Meteorological data interpolation
15.2
Temperature
15.3
Precipitation
15.4
Interception
15.5
Snowpack
15.6
Vegetation model
15.7
Evapotranspiration
15.8
Infiltration
15.9
Soil calculation
15.10 Soil temperature and soil water freezing
15.1 METEOROLOGICAL DATA INTERPOLATION
Meteorological data is given to the model as point measurements, which are then used
to compute a separate value for each model grid cell. Supported computation methods
include using closest measurement point data (and inverse of distance weighted
interpolation, not yet in new model version).
15.2 TEMPERATURE
Measured temperature values are corrected to model area using elevation data with
given temperature lapse rate. The lapse rate can be time dependent and given with the
daily temperature data as a time series.
T
Tmeas
T
Tmeas
hpoint
hmeas
Ltemp
L temp ( h po int
(1)
h mead )
= corrected temperature
= measured (or interpolated) temperature for grid cell, °C
= location height, m
= measurement location height, m
= temperature lapse rate (0.0059 - 0.0098 K/m)
15.3 PRECIPITATION
Daily precipitation measurements are used for precipitation information. The measured
precipitation is corrected against systematic measurement errors and elevation effect,
and divided into snow and water partitions using corrected air temperature.
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Rw
1
(T Tmin ) /( Tmax
0
Rw
Tmax
Tmin
P
Pw
Ps
T Tmax
Tmin ) Tmin T
T Tmin
Tmax
= precipitation water content
= maximum temperature for snow precipitation, °C
= minimum temperature for water precipitation, °C
Pm (1 L prec ( h po int
h mead ))
R wCw P
(1 R w )C s P
P
Lprec
hpoint
hmeas
Pw
Ps
Cw
Cs
Pm
(2)
(3)
= height corrected precipitation measurement, mm
= precipitation height correction multiplier
= location height, m
= measurement location height, m
= precipitated water estimate, mm
= precipitated snow estimate, mm
= correction coefficient for precipitated rain
= correction coefficient for precipitated snow
= measured (or interpolated) precipitation for grid cell, mm
15.4 INTERCEPTION
Interception is modelled using one layer interception model. Only liquid precipitation is
affected by interception; intercepted snow is expected to eventually fall on the snow
pack on the ground as snow or water, or to evaporate. Interception is applied only to
part of precipitation, namely that falling on canopy. Rest of the precipitation is
considered as through fall directly on the ground surface. Interception parameters are
set in the model based on land use type. The interception storage has a maximum size,
given as parameter, and after it is filled all precipitation ends up in ground surface
(Table 1).
While computing evapotranspiration, the potential evapotranspiration is first tried to be
satisfied from the interception storage and after this the remainder is used to compute
transpiration.
I(t+dt) =min (Imax, max (dt (Ac Pw - PET) + I(t), 0))
(5)
Imax = laisc * LAI(t)
Pw
I(t)
Imax
Ac
PET(t)
laisc
LAI
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= precipitated water, mm
= canopy interception storage, mm
= canopy interception storage capacity, mm
= area covered by canopy (0-1)
= potential evapotranspiration
= leaf area interception storing capacity
= leaf area index
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Table 1.
Interception storage maximum size (Woodall, 1984).
Vegetation
Moist tropical forest
Grasses
Soil cover
Interception
0.19
0.13
0.03
15.5 SNOWPACK
Wintertime conditions require modelling of snow pack. Snow melt is currently
computed using degree-day approach
Smelt = Kmelt(T(t) - Tmelt),
T(t)>Tmelt
Smelt = 0,
T(t)<Tmelt
Sfreeze = Kfreeze(Tfreeze - T(t))1/2,
T(t)<Tfreeze
Sfreeze = 0,
T(t)>Tfreeze
(6)
(7)
Ssnow(t+1) = Ssnow(t) + Sfreeze - Smelt + Ps
Swater(t+1) = min (Swater(t) + Smelt-Sfreeze + Pw, Kret Ssnow(t+1))
(8)
Syield(t) = max (Swater(t) + Smelt - Sfreeze + Pw - Kret Ssnow(t+1), 0)
Smelt
Kmelt
T(t)
Tmelt
Tfreeze
Sfreeze
Ssnow
Swater
Kret
Syield
= snowmelt, mm
= degree-day coefficient, mm/ C
= average daily air temperature, C
= snowmelt minimum temperature, C
= refreezing maximum temperature, C
= amount of refrozen water, mm
= snow water equivalent, mm
= snow water content, mm
= maximum snow water content coefficient (about 0.1)
= yield, mm
Snow depth can be modelled, if required, using following equations:
hsnow(t+1) = Ssnow(t)/ (
hnewsnow = Ps/
snow(t+1)
newsnow
snow(t)
+Pw/
+ Scompr)+hnewsnow
water
(9)
= Ssnow(t+1)/hsnow(t+1)
hsnow
= snow depth, m
= snow density, kg/m3
snow
hnewsnow = new snow depth, m
3
newsnow = density of new snow, kg/m
Ssnow = snow water content, m
Scompr = snow compression coefficient, kg/m3
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15.6 VEGETATION MODEL
In the model, vegetation water uptake depends on the leaf area index (LAI, Table 2).
For the computation of leaf area index in the model, several different methods can be
used. Parameter laimethod (in Landuse parameters) defines the different methods for
calculating leaf area index, which are: leaf area calculation off (0=LAI_off), constant
leaf area index (1=LAI_const), annual leaf area index (2=LAI_annual) and perennial
leaf area index (3=LAI_perennial). (At the moment if lai calculation is off lai is constant
3 and if lai is constant then lai is 1) Laimethod can be set separately for each land use
type.
Table 2.
Leaf area index in different environments (Dingman, 1994)
Community
Desert
Tundra
Grassland prairie
Savannah
Deciduous hardwood forest
Tropical forest
Temperate conifer forest
LAI
<1
1
1
1-3
3-7
>9
10 - 47
The model describing the growth of seasonal crops or annual plants is also used to
describe the leaf growth and withering during the growth period of perennial plants and
deciduous trees. The computation method used to calculate the leaf area index of
annual and perennial plants is an adaptation of the commonly used EPIC crop model.
The development of crops is based on daily average temperature sum. The
temperature sum is put to zero in the beginning of the year where after it is calculated
from the average temperature:
Tsum(i) = Tsum(i-1) + max (Tavg(i-1) - Tbase, 0)
(10)
Tsum(i) = temperature sum for day i, °C
Tavg
= average daily temperature for day i, °C
Tbase = minimum growth temperature, °C (usually about 5 °C
Plant maturity index is directly dependable of the temperature sum
PMI = max (Tsum/Hmature,1)
(11)
PMI
= plant maturity index (0-1)
Hmature = heat sum value for mature plant, degree days, plant dependent
parameter
The daily growth of a plant i.e. the production of new biomass depends on the
incoming amount of solar radiation and is limited by lack of water and the average air
temperatures deviation from the optimum growth temperature of the plant.
B(i) = B(i-1) + Bnew
Kbio = 0.02092 Kin (1- exp (-0.65 LAI))
Bnew = 0.001 cb Kbio min (Swater, Stemp)
(12)
Swater = Etr /PET
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Stemp = sin ( /2 (Tavg-Tbase)/ (Topt-Tbase))
Kbio
B
Bnew
LAI
cb
Topt
Swater
Stemp
= radiation available for growth
= biomass for day i
= amount of produced biomass
= leaf area index
= utilization coefficient of radiation
= optimal growth temperature for the plant, °C
= stress coefficient for lack of water
= stress coefficient for temperature
For seasonal crops the daily development of leaf area index is calculated based on the
phase of growth. In the beginning of growth the leaf area index increases rapidly.
When the temperature sum is high enough, the plant is mature; leaf area index does
not increase any more and the plant starts to wither.
LAI = LAImax B/ (B+0.552 exp (-6.8 B)),
PMI < PMIdec
LAI = LAISmax (1-PMI)/ (1-PMIdec)
PMI > PMIdec
(11)
LAImax = maximum leaf area index
LAISmax = maximum leaf area index the plant has reached during this growing
season
PMIdec = fraction of growing season when leaf area index starts declining (e.g.
0.75)
For perennial plants such as deciduous trees the development of leaf area index is
calculated similarly to seasonal crops, except that a minimum leaf area index can be
given to the plant.
LAI = LAImin + (LAImax–LAImin) B/ (B+0.267 exp (-13.6 B)), PMI < PMIdec
LAI = LAImin + (LAISmax - LAImin) (1-PMI)/ (1-PMIdec)
(12)
PMI < PMIdec
LAImin = minimum leaf area index
The withering of perennial plants can be set to start from a certain day of the year or
from reaching the maturity index, which ever is reached first:
LAI = LAImin + (LAImax–LAImin) B/ (B+0.267 exp (-13.6 B)), PMI < 1 ja dn<dmax
(13)
LAI = LAImin + (LAISmax - LAImin ) max (1-0.05*(dn -dmax),0) PMI > 1 tai dn>dmax
dn
= number of the day (1-365) from beginning of the year
dmax = day number when LAI starts declining
15.7 EVAPOTRANSPIRATION
Evapotranspiration is calculated in the model by first calculating the potential
evapotranspiration (PET) with an appropriate method depending on the available input
data.
If air temperature, incoming radiation, humidity and wind speed data are available,
Penman-Monteith formulation can be used:
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PETP
s(Ta ) Rtot
c Cat e sat (Ta )(1 Wa )
v s (Ta )
a a
w
(14)
PETp
Ta
ca
Cat
Wa
= potential evaporation using Penman equation, mm
= air temperature, °C
= heat capacity of air, J/kg
= atmospheric conductance, m/s
= relative humidity
= density of water, kg/m3
w
= density of air, kg/m3
a
= water latent heat of vaporisation, J/kg
v
esat(T) = saturation vapour pressure of water, mb
s(Ta) = d esat/ dT
= psychrometric constant, 0.66 mb/°C
Rtot
= total radiation, J/d
Cat=va*(6.25 ln ((zm - zd)/ z0))(-2)
zd = 0.7 hveg
(15)
z0 = 0.1 hveg
va
zm
zd
z0
hveg
= wind speed, m/s
= wind measurement height, m
= displacement height, m
= roughness length, m
= vegetation height, m
Potential evapotranspiration can also be calculated using pan evaporation
measurements.
PETpan
PanCorrect ion ( M ) E pan
(16)
PETpan = potential evapotranspiration (Pan Evaporation method), mm
Epan
= measured pan evaporation, mm
PanCorrection(M) = monthly pan correction coefficient
M
= month number (1-12)
If daily average temperature and total radiation are known, the Priestly-Taylor method
can be used
PETPT
PT
w
s(Ta )( Rtot )
v s (Ta )
(17)
PETPT = potential evapotranspiration (Priestly-Taylor method), mm
= 1.26 (parameter)
PT
If daily maximum and minimum temperatures are available, the Hargreaves-Samani
method can be used:
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PETHS
0.0032 K cs (Ta 17.8)(Tmax Tmin ) 0.6
2.5 0.0022Ta
PETHS
Tmin
Tmax
Kcs
(18)
= potential evapotranspiration (Hargreaves-Samani method), mm
= daily minimum air temperature, °C
= daily maximum air temperature, °C
= clear sky shortwave radiation, J/m2/d
Radiation data, if missing, can be approximated from temperature and cloudiness data
using following method (Croley 1989):
Rtot
(1 a) K L
Kin
(1 a)(0.355 0.68(1 C)) Kcs ,
L (
at
at
(19)
1) (Ta 273.15)4
(0.53 0.065(esat (Ta ))0.5 )(1 0.4C)
C 1 1.25( K / Kcs 0.2) (If C not measured but K is)
C
A
at
K
Kcs
L
= cloudiness (0-1)
= surface albedo
= emissivity of atmosphere
= Stefan-Bolzmann coefficient, J/m2/d/K4
= incoming shortwave radiation, J/m2/d
= clear sky shortwave radiation, computed from date and latitude, J/m2/d
= long wave radiation, J/m2/d
Relative humidity data, if missing, can be approximated from daily minimum
temperature
Wa=esat(Tmin)/esat(Tavg)
(20)
Actual evaporation is calculated from potential evapotranspiration. If the pond storage
is large enough or if there is enough water in the root zones of plants (i.e. the water
content is at or above field capacity) and leaf area index is greater than two,
evaporation occurs in the potential rate. Otherwise the water content deficit or the leaf
area index limits the amount of evaporation.
Es = max (min(s(0), PET),0)
E1 = min(s(1)/sfc(1),1)*min(0.5 LAI,1) frz1 (PET - Es)
(21)
E2 = min(s(2)/sfc(2),1)*min(0.5 LAI,1) frz2 (PET - Es)
Es
s(0)
s(1)
s(2)
E1
E2
sfc(i)
160
= evaporation from pond storage, mm
= amount of water in pond storage, m3
= amount of water in soil layer 1, m3
= amount of water in soil layer 2, m3
= evaporation from soil layer 1, mm
= evaporation from soil layer 2, mm
= field capacity of layer i in cubic meters = area*(thf(i)-thr(i))*dz(i), m3
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frz1
frz2
= fraction of roots in soil layer 1
= fraction of roots in soil layer 2, frz1+frz2 = 1
15.8 INFILTRATION
Infiltration is the process by which water arriving at the soil surface enters the soil.
Water that has reached the soil surface is absorbed in the soil or if this is not possible
accumulated in pond storage. After the pond storage has been filled, the water flows
as surface runoff to a river or next grid cell as defined by the flow net. If the ground is
saturated by water in the entire profile, all the precipitation will end up in the pond
storage and as surface runoff.
The infiltration model is needed when the there is more water coming to the surface of
a soil layer than the layer can infiltrate. When the infiltration begins, the soil layer water
content is assumed to be a constant 0 in the entire layer. Generally as the infiltration
progresses the soil layer is saturated to depth L(t) at moment t and the edge of the
saturated layer progresses downwards with a speed defined by soil parameters. The
amount of infiltrated water at moment t can be expressed as follows (Dingman, 1994):
fi(t) = Ksat(H0 + L(t) + Pwf)/ L(t)
fi(t)
Ksat
H0
(22)
= the amount of infiltration at moment t, m/s
= conductivity of saturated soil, m/s
= thickness of water layer on soil surface (usually assumed to be small),
m
= thickness of saturated layers, m
= capillary pressure at the lower edge of the saturated layer, (m)
L(t)
Pwf
In the beginning phase of infiltration, until the moment tp (time of ponding), the soil
layer can absorb water in a rate corresponding to precipitation. After moment tp
infiltration slows down and part of the precipitation accumulates in the pond storage or
ends up as surface runoff. Time of ponding can be calculated in the following way
(Dingman 1994):
tp = Ksat Pwf (
tp
w
sat
0
sat
–
0)
/ (w(w - Ksat))
(23)
= time of ponding, s
= amount of precipitation, m/s
= soil layer maximum/saturation water content
= soil layer moisture/water content in the beginning of infiltration
The amount of water infiltrated during the entire precipitation event can be calculated
as follows
Fi(t) = L(t) (
Fi(t)
sat
–
0)
(24)
= infiltrated amount of water at moment t, m
When we take into account that fi(t) = dFi(t)/ dt, L(t) can be eliminated from the
equation and the following equation is reached:
dFi(t) / dt = Ksat(1 + Pwf / (Fi(t) / (
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sat
-
0)))
(25)
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The value of Fi(t) can not be calculated directly from this equation. Explicit Green-Ampt
formulation (Salvucci and Entekhabi 1994), which approximates the implicit solution of
Fi(t) with less than 2 % error, is used in the model.
If daily precipitation measurements are used, precipitation intensity and duration need
to be estimated. In the parameterisation, melting and rainfall are both assumed to
occur as one continuous event with a constant intensity. The intensities have the
following parameters:
Ip = mpw Pw (9 exp (-0.1mpw Pw) + 1)
(26)
Ism = msmSm
Ip
Ism
mpw
msm
Pw
Sm
= intensity of precipitation, cm/h
= intensity of melting, cm/h
= correction coefficient for intensity of precipitation
= correction coefficient for intensity of melting
= daily precipitation, cm/h
= daily melting, cm/h
With the computation method the fraction of infiltrated water and fractions of water in
pond storage and as surface runoff are obtained for each precipitation event. Surface
runoff is assumed to occur as sheet flow in the width of the entire grid cell. The depth
of the flow is calculated by dividing the water amount in excess of the pond storage
volume evenly on the grid cell area. The slope is the grid cell slope subtracted with
remainder of water levels in the grid cell being calculated and the grid cell below it.
Flow speed is assumed to depend only of water depth and slope. The calculation
formulas for surface runoff are presented below together with the soil calculation.
15.9 SOIL CALCULATION
In the model the soil has been divided into two layers and the depths of these layers
can be defined freely. Typically the upper layer is approximately 20-80 cm deep and
the lower layer 1-15 meters deep. For example, in a field the surface layer is typically
around 20 cm and represents the ploughed layer. Lower layer is around 1-15 meters
and represents the depth where the ground water normally moves.
The water storage of both layers is divided into two differently behaving parts at field
capacity water content. When the water content is smaller than the field capacity
(between withering point – field capacity), the soil water can be used by plants but
does not flow away from the soil layer. When the water content is above field capacity
(between field capacity - maximum capacity) the water flows from soil to the next lower
grid cell or to a river.
In surface runoff the amount of water leaving from the grid cell to the next grid cell or to
a river depends on ground surface flow resistance and ground slope. In flow through
soil the amount of flow is influenced by horizontal conductivity of the soil, ground water
height and grid cell slope. The calculation variables for a grid cell are shown below in
Figure 27.
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yield
es
qin(0)
s(0)
fs1
e1
qin(1)
fo0
qret1
fo1
s(1)
e2
f12
qret2
fo2
qin(2)
s(2)
sfc (i)
smx(i)
Figure 27.
Calculation variables for grid cells
Soil model calculation:
Variables
s(0)
s(1)
s(2)
= pond storage, m3
= first soil layer storage, m3
= second soil layer storage, m3
Parameters:
area = grid cell area, m2
ly
= grid cell width, m
lx
= grid cell length, m
kz(i)
= vertical conductivity of saturated soil, layer i, m/d
kx(i)
= horizontal conductivity of saturated soil, layer i, m/d
ths(i) = maximum water content/saturation of soil, layer i
thf(i) = field capacity, layer i
dz(i) = depth of soil layer I, m
tanb = tangent to soil surface slope, tan(slope)
n
= Manning’s friction coefficient for surface runoff (defined in RiverData in
RLGis program)
f
= coefficient of exponential runoff for lowest soil layer
Conduced parameters:
Mn
= 86400/n,
smx(i) = water storage capacity of layer i in cubic meters, [m3] = area*(ths(i)thr(i))*dz(i)
sfc(i) = field capacity of layer i in cubic meters [m3] = area*(thf(i)-thr(i))*dz(i)
thd(i) = fraction emptied by gravitation for layer i = ths(i) – thf(i)
Initial values:
Yield = amount of water coming to the surface of the top soil layer, m3/d
Pet
= potential evaporation, m3/d
qin(i) = horizontal discharge from upper grid cells to this grid cell for layer i, m3/d
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Vertical flow:
qret1=max(s(1)-smx(1),0)
qret2=max(s(2)-smx(2),0)
fs1=min(yield+s(0),area*kz(1))
(27)
f12=max( min(kz(2)*area, max(s(1)-sfc(1),0))-max(s(2)-smx(2),0) ,0)
Storage size:
h0=max(s(0)-smx(0),0)/area
h1=max(s(1)-sfc(1),0)/(area*thd(1))
(28)
h2=max(s(2)-sfc(2),0)/(area*thd(2))
Horizontal flow:
dsurf = tanb – (wlnext – wlthis)/lx
fo0=pow(h0,1.667)*sqrt(dsurf)*mn*ly
fo1=h1*kx(1)*tanb*ly
(29)
fo2=h2*kx(2)*exp(-f*(dz(2)-h2)) *tanb*ly
if h2<0, fo2=0
if h2>h2max, fo2= return kx(2)*(1/dz(2)+f)*h2-kx(2)*f*dz(2)
qlat0=qin(0)-fo0
qlat1=qin(1)-fo1
(30)
qlat2=qin(2)-fo2-fdrain
fdrain: (under)drain flow, see below
wlnext
wlthis
= water level in next grid cell’s centre point, m
= water level in this grid cell’s centre point, m
Updating space variables:
ds(0)/dt=yield - fs1 + qret1 - es + qlat0
ds(1)/dt=fs1 - f12 - e1 - qret1 + qret2 + qlat1
(31)
ds(2)/dt=f12 - e2 - qret2 + qlat2
If grid cell has ditches or (under)drains the outflow from them is calculated by
Hooghoudt's formula
qdrain = 4Kh (2D + h)/ L2
qdrain
K
h
D
L
164
(32)
= outflow from ditch or drain, m/d
= water conductivity, m/d
= height difference between the drain and ground water level, m
= soil depth under the drain, m
= drain spacing, m
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The water leaving from each grid cell can continue on to a river in the grid cell or to
lower grid cell determined by the flow net. If the grid cell has a stream or a river, the
division of water between the river and the lower grid cell is determined by the slope of
the grid cell and the river slope. The calculation principle is shown in Figure 28.
p next
slope
p river
river
p river
slope
p next
Figure 28.
The fractions of water flowing from a grid cell to the river and to next grid cell.
pnext= 0.25 sin( )/ sin( )
(33)
priver = 1 - pnext
pnext
priver
= fraction flowing to lower grid cell
= fraction flowing to river
= ground surface slope in the grid cell to the river
= river slope in the grid cell
Especially if
and
are equal flow to the river is 75 % and to next grid cell 25 %.
15.10 SOIL TEMPERATURE AND SOIL WATER FREEZING
Soil temperature is calculated in a separate grid. The height of the grid cells
correspond to the height of the first soil layer’s grid cells. The model calculates soil
surface temperature, temperature conductance to the soil from the surface and soil
water freezing and melting. The lower boundary value for temperature is given by a sin
curve and the range and average of the sin curve are given as parameters.
The conductance of heat in the soil is calculated with diffusion equation.
T
t
z
T
ks
ks
T
z
(34)
= temperature, C
= temperatures diffusivity, m2/s
Temperature diffusivity is calculated as follows:
ks
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vs
c
(35)
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c
d d
c
w w
c
d d
c
d d
c
w
c
i i
c
vs
c
0 T
(ci -
lfw
(1-T/Tf ) n f -1 ) Tf
Tf
T
T
Tf
c
0
= specific heat capacity for soil, J/kg/K
= coefficient for soil heat conduction, m2/d (about 0.25-0.3 for dry land)
= density of dry soil material, kg/m3 (about 1600 kg/m3)
= density of water, kg/m3
= density of ice, kg/m3
= specific heat capacity for dry soil, J/kg/K
= specific heat capacity for water, J/kg/K
= soil moisture content
= water latent heat of fusion, J/kg
= soil temperature, C
= temperature below which all water is ice, C
d
w
I
cd
cw
lfw
T
Tf
When the temperature drops below zero the soil water begins to freeze. The actual
freezing point for water in soil material is not always zero, but depends on the moisture
content of the soil. Here a simplified method, where freezing is assumed to take place
between temperatures 0 and Tf, is used.
The proportion of frozen soil and water conductivity of partly frozen soil can be
calculated from:
(36)
I 1
1 T / Tf
I 1
Kice
K
I
T
nf
nf
Tf
T 0
T Tf
= water conductivity in partly frozen soil, m/d
= water conductivity in entirely unfrozen soil, m/d
= proportion of ice
= soil temperature, C
= exponent for freezing curve (default value 2)
During summer, measured air temperature is used as soil surface temperature. While
the ground is covered by snow, the surface temperature is calculated by discretion of
the equation describing heat conductivity for snow layer and soil models first grid cell.
The following formula is then reached:
(37)
a = Ksnow dsoil/ (Ksoil dsnow)
Tsurf
Tsoil
Ta
Ksnow
166
= soil surface temperature, C
= temperature in soil surface layer 1, C
= air temperature, C
= heat conductivity of snow, m2/d (new snow: 0.08, old snow 0.42)
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Ksoil
dsoil
dsnow
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= heat conductivity of soil, m2/d (for mineral soil 0.27 m2/s)
= soil layer depth, m
= snow depth, m
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16 RIVER AND LAKE COMPONENT
This chapter dives the model description for the river and lake component of the
IWRM hydrologic model including equations and theory.
The chapter is divided to two parts:
16.1 River model
16.2 Lake model
16.1 RIVER MODEL
The river model uses river network that is calculated from model grid elevations and
digitized river network. If needed the calculated river network can be modified to better
fit the actual river network. When runoff from sufficiently large area goes through one
grid cell, a stream or a river is formed in that grid cell. An example of a river grid is
show in Figure 29 below. For a watershed, all the river nodes are connected to a single
outflow point at watershed area border.
Figure 29
Part of the flow and river network and elevation model in Nam Songkhram
IWRM model application.
Rivers are described in the model with a kinematical model simplified from the St.
Venant equations. The flow speed in rivers depends on channel cross section, bottom
slope and water depth. Optionally also the water level in the downstream grid cell can
be taken into account.
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The St. Venant equations representing the river discharge are:
A
A
u
u
A
qs
t
x
x
u
u
y
u
g
gS0
t
x
x
Cc
g
uu
Cc2 R
(38)
R1/ 6 / n
A
u
y
qs
S0
R
g
n
= cross section, m2
= flow speed, m/s
= water depth, m
= side flow, m3/s
= bottom slope, m/m
= hydraulic radius = A/ P, m, P=wetted perimeter, m
= gravitational acceleration, 9.81 m/s2
= Manning’s friction parameter
The equations have been simplified with the following assumptions:
1)
River cross section is a modified trapezoid (Figure 30).
mn2
w2
b2
d
b1
mn1
w1
Figure 30.
River cross section.
River parameters:
d
= river bank height, m
w1
= river bottom width, m
w2
= river width at bank height = w1 + 2d tan (b1), m
b1
= river bank slope
b2
= floodplain slope
mn1
= Manning’s friction parameter for river channel
mn2
= Manning’s friction parameter for floodplain
River cross section area is calculated from the water height:
A = y (w1 + y tan (b1)),
y<d
A = d (w1 + d tan (b1)) + (y - d) ((w2 + (y-d) tan (b2)),
y>d
y
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(39)
= river depth, m
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2) The flow speed depends only on bottom slope and water depth (kinematical wave
approximation)
u
y 2/ 3
( S0 )1/ 2
n
(40)
The river model is solved numerically from upstream cells to downstream direction,
using a method that iterates the flow speed and water depth from the side flow and the
upstream flow using above equations. This method enables usage of a reasonably
large time step and therefore shortens computation times.
16.2 LAKE MODEL
Any of the grid cells can be set to be a lake. Lakes are handled as storages that keep
account of the water level as a difference from the reference water level. Water level
changes are linearly related to volume changes, which are computed from inflow,
outflow, precipitation and lake evaporation. Evaporation from lake occurs at potential
rate. Outflow from a lake depends on the lake water height. Water level is calculated
from lake volume based on a volume-water level curve, which can depend on the lake
area or can be given separately.
Vlake(t)=Vlake(t-1)+Qin-Qout-Elake
ylake=dVlakeVlake
(41)
Alake=dAlakeVlake
Qlake
Au
where
V0
y0lake
A0
Vlake
ylake
Alake
dVlak
dAlake
Qlout
y
w, ,S0
170
y(w y tan )
y 2/ 3 1/ 2
S0
n
= lake reference volume, m3
= lake surface height reference level, m
= lake reference area, m2
= lake volume difference from reference volume, m3
= lake surface height difference from reference height, m
= lake area difference from reference area, m2
= lake volume difference to surface height difference multiplier
= lake volume difference to area difference multiplier
= lake outflow, m3/s
= lake surface height – lake outlet bottom height, m
= lake outlet parameters
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17 NUTRIENT LEACHING MODEL
This chapter gives the model description for the nutrient leaching component of the
IWRM hydrologic model.
The chapter is divided to two parts:
17.1 General
17.2 Calculation of soluble phosphorus
17.1 GENERAL
The calculation of leaching is based on calculated flows and the distribution of the
flows to different flow components. In the model concentrations based on the
properties of the grid cell are given to each component of flow i.e. surface flow,
interflow, drain, and groundwater flow. Based on these concentrations the loads
ending up from the grid cell to a river are calculated. For modelling loads caused by
population and fallout a constant load not dependable on flow can be defined for a grid
cell.
The concentration of water flowing out of the grid cell is calculated as follows:
cout = (c0 fo0 + c1 fo1 + c2 fo2 + c3 fdrain) / (fo0 + fo1 + fo2 + fdrain)
cout
c0
c1
c2
c3
fo0
fo1
fo2
fdrain
(42)
= concentration of runoff water (g/m3)
= concentration of surface runoff, parameter (g/m3)
= concentration of interflow, parameter (g/m3)
= concentration of groundwater flow, parameter (g/m3)
= concentration of drain flow, parameter (g/m3)
= amount of surface runoff (m3)
= amount of unsaturated layer runoff (m3)
= amount of groundwater runoff (m3)
= amount of ditch runoff (m3)
In the model the leaching of nutrients is calculated with the previous method. In the
calculation of soluble phosphorus the concentrations depend on both land use and soil
type. In the calculation of solid material a more physically based approach is used by
using an erosion model described below.
In the river and lake models the leached substances can in the case of soluble
substance be used for biological activity or in the case of particle substances deposited
in the bottom of a lake or a river. Biological processes are not taken into account in the
model.
The concentrations of different flow components can be defined in several different
ways for the calculations. The simplest way is to use values found in literature and
correct them according to water quality measurements in the area modelled.
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17.2 CALCULATION OF SOLUBLE PHOSPHORUS
The soluble phosphorus is assumed to be mainly from fields, point sources and
population load. In forested areas the soluble phosphorus is mainly from decomposing
organic matter.
Corrected soluble phosphorus concentrations are calculated in the model for each
fraction of flow, i.e. surface runoff, interflow, drain and groundwater flow, based on the
soil type of the field. The relative differences between soil types correspond to values
reported by Havlin (Havlin 2004) while the absolute values are calibrated in the model
to fit the local conditions.
Concentration of soluble phosphorus for surface runoff:
cPO4surf = 0.43 kpo4,
cPO4surf = 1.00 kpo4,
cPO4surf = 1.40 kpo4,
cPO4surf = 2.33 kpo4,
Psoil For clay soils
Psoil For silt soils
Psoil For sand soils
Psoil For peat soils
(43)
Psoil = soil surface layer’s phosphorus value, mg/l
kpo4 = phosphorus concentration of the runoff water per soils phosphorus unit,
g/mg
The phosphorus concentrations from field for other flow fractions are also calculated in
a way corresponding to surface runoff, however with separate concentration
coefficients (kpo4) for each flow fraction. Separate phosphorus values are given to
surface and bottom soil. In the calculation of surface runoff and interflow the soil type
and phosphorus value of surface soil is used. In the calculation of drain flow the
phosphorus value of surface soil and the soil type of bottom soil is used and in the
calculation on bottom flow the bottom soil parameter are used.
Parameters
Soil quality division into clay, silt, sand and moraine soils, based on a soil map
soilsurfP = concentration of phosphorus for surface runoff per surface soils
phosphorus value unit
soilbaseP = concentration of phosphorus for groundwater flow per bottom soils
phosphorus value unit
soilditchP = concentration of phosphorus for ditch flow per surface soils
phosphorus value unit
soilmidP = concentration of phosphorus for interflow per surface soils phosphorus
value unit
soilp1 = phosphorus value for surface soil
soilp2 = phosphorus value for bottom soil
Nutrients in rivers and lakes
Soluble phosphorus is assumed to be carried in rivers without changes. In lakes
soluble phosphorus can be used partly or entirely by algae and sediment in the bottom
along detritus. This process in however not included in the model.
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18 EROSION MODEL
This chapter gives the model description for the erosion model component of the
IWRM hydrologic model.
The chapter is divided to three parts:
18.1 Surface runoff inside a grid cell
18.2 The solid material detached by precipitation
18.3 Solid materials in rivers and lakes
The IWRM erosion model calculates the amount of soil material detached from the soil
by surface runoff. The soil material is assumed to be detached in two ways: caused by
the motion energy of rain drops and as scour from rill bottoms caused by surface runoff
as rill flow. The detachment caused by rain drops depends on the intensity of rain and
soil properties. The detachment of solid materials caused by rill flow is proportional to
the shear stress caused by the flow. Usually the flow cannot transport all the detaching
material, but some of the sediment is deposited on the bottom of the rill. The upper
boundary for the sediment transport capacity is reached when material is deposited at
the same rate as it is detached.
The erosion model is calculated inside each grid cell for every grid cell in the case that
surface runoff occurs. In the erosion model the grid cell is divided into smaller slices in
the flow direction and mass balance is calculated for each slice between the incoming,
leaving, detaching and depositing material (Figure 31).
Figure 31.
The function of the erosion model.
18.1 SURFACE RUNOFF INSIDE A GRID CELL
Surface runoff begins when ground surface pond storage has been filled. If the slope
angle and grid cell width inside the grid cell are constants, flow in location x from the
upper edge of the grid cell can be stated as follows:
qo = x po + qup
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(44)
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DMS-Project, Mekong River Commission
qo
x
po
qup
= surface runoff per unit width in point x from grid cell’s upper side, m2/s
= distance from upper side of the grid cell,
= amount of surface runoff (precipitation or melting), m/s = 0.001/3600
mm/h
= amount of surface runoff from upper grid cell to this grid cell per unit
width, m2/s
Soil erosion begins when flow shear stress exceeds the soil type dependable value of
critical shear stress c. The critical shear stress in the model is a parameter
dependable on soil type. When the shear stress exceeds the value of critical shear
stress, the flow is able to change the bottom shape and starts forming rills. Surface
runoff is assumed to be sheet flow until critical shear stress is reached and after this
the flow is assumed to be rill flow.
Flow speed of sheet flow can be calculated from the Manning’s equation
u = R2/3 S1/2 / n = d2/3 S1/2 / n
u
R
d
n
S
(45)
= flow speed, m/s
= hydraulic radius = A/ P, where P = wetted perimeter (for sheet flow the
flow depth can be used), m
= flow depth, m
= Manning's friction coefficient
= slope
Based on conservation of mass:
Q = Au
Q
A
(46)
= discharge, m3/s
= flow cross section area, m2
For sheet flow per unit width:
q = d u = d5/3 S1/2 / n = x po + qup
q
(47)
= flow discharge per unit width, m2/s
When flow depth d is solved, we get:
d = ((x po + qup) n S-1/2) 3/5
(48)
The flow shear stress is calculated as follows:
= gRS,
for channels
(49a)
= gdS,
for flow, where R~d
(49b)
g
S
174
= shear stress, Pa (Pa= kg/(m s2))
= density of water, kg/m3
= acceleration of the earth gravity, 9.81 m/s2
=slope, equal to tan ( ), where = slope angle (sin (x) ~ tan (x) at angles
below 15 degrees)
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For sheet flow shear stress in point x can be calculated from formulas (49b) and (48):
= gdS = g ((x po + qup) 3/5 n3/5 S7/10
(50)
If qup = 0, the location xc, where critical shear stress of the soil is exceeded, is:
xc =1/(n po) (
0
/ ( g S7/10))5/3
(51)
The detachment of solid material due to shear stress caused by the flow is evaluated
with the following formula:
e = ke ( e
ke
c
c)
(52)
= detachment of solid material per unit area, kg/s m2
= erosion coefficient
= flow shear stress, Pa
= critical shear stress, Pa
The solid material in the flow is deposited in the following way:
Dp = vs c
Dp
C
vs
(53)
= sedimentation per unit area, kg/s m2
= concentration of solid material, kg/m3
= sedimentation speed, m/s
Since the mass of the sediment is conserved, the change in the amount of transported
material in a small slice of slope with the width of dx can be written as follows:
Mout – Min = erosion – deposition + qside cs
Mout
Min
qside
cs
(54)
= amount of substance flowing in, kg
= amount of substance flowing out, kg
= side flow, m3/s
= concentration of side flow, kg/m3
qside is dx po, where po is the overflow of the pond storage (m/s) and cs is the
concentration of the overflow.
(q + dq) (c + dc) – q c = dx wf e - dx wf vs c + dx po cs
q
wf
vs
e
(55)
= flow discharge per width meter, m2/s
= flow width, m/m
= speed of descent, m/s
= amount of erosion, kg/(s m2)
Term dg dc is small and is left out. We now get:
q dc + dq c = dx wf e – dx wf vs c + dx po cs
(56)
dq is the same as qside, by substituting this in the above equation we get:
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DMS-Project, Mekong River Commission
q dc/ dx = wf (e – vs c) + po (cs - c) = wf e - (wf vs + po) c + po cs
(57)
For numeric solution, the grid cell is divided into n slices (0 … n) x with index i:
(ci - ci-1)/ x = 1/ qi (wfi ei
(wfi vs + po) ci + po cs)
(58)
After simplification and by substituting wf with P, we get the following equation.
ci+1 = (qi ci-1 + x (Piei + pocs)) / (qi + x (Pivs + po))
(59)
The concentration of surface runoff in the lower edge of the grid cell can be calculated
with this formula.
In the previous formula the terms P, Pe and cs are unknown.
According to Gilley et al. (Gilley et al. 1990) the rill density is approximately one rill per
meter. The width of the rills can be calculated with the formula:
wf = c Qd
wf
Q
c
d
(60)
= width of the rill, m/m
= flow in the rill, m2/s
= 1.13
= 0.303
According to Govers et al. (2000) Flow speed in the rills can be calculated with the
formula:
u = a Qb
u
a
a
(61)
= flow speed in the rill, m/s
= 3.54, b
= 0.294
= 4.19, b
= 0.344
for homogenous loose soils
when soil contains rocks
From formulas (46) and (61) we get
A = 1/ a Q1-b
(62)
If the rill’s cross section is assumed to be rectangular, the depth of the rill can be
calculated with the following formula:
h = Q/ (wf u) = 1/ (ac) Q1-b-d
(63)
h
= depth of the water in the rill, m
a,b,c,d = parameters
The shear stress of the rill per length unit can be stated as follows (Gimenez & Govers
2002)
rill
P = gRSP = gAS = gSQb-1/ a
(64)
The term e P in the mass balance equation can now be written as
P e = P ke( -
176
c)
= ke( gSQ1-b/ a - P
c)
(65)
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If we assume the rill to have a rectangular cross section
P = wf + 2h = c Q d +2 Q1-b-d/ (ac)
(66)
Because d=0.303 and 1-b-d = 0.35…0.4 depending on the soil type, the term can be
approximated as:
P = (c + 2/ ac) Qd
(67)
The mass balance equation can now be calculated.
18.2 THE SOLID MATERIAL DETACHED BY PRECIPITATION
The solid material concentration of side flow and pond storage water is evaluated
based on detachment of solid materials caused by precipitation.
Ds = ksd Ke P exp (- bh)
Ds
ksd
Ke
P
B
H
(68)
= detachment of solid materials caused by precipitation
= soil type detachment sensitivity for precipitation, g/J
= kinetic energy of precipitation, J/m2 mm
= amount of precipitation, mm
= parameter, values 0.9 - 3.1, here a value of 2.0 has been used
= water depth at ground surface, mm
Water raining from an open sky has a kinetic energy
Ke=8.94 + 8.44 log10(i)
i
(69)
= intensity of precipitation, mm/h
For water stopped by vegetation and dripping from there to the ground the kinetic
energy is:
Ket = 15.8 sqrt (h) - 5.87,
h > 0.14 m
Ket = 0,
h < 0.14m
Ket
H
(70)
= kinetic energy, J/ (m2 mm)
= effective height of vegetation, m
The values of soil type detachment sensitivity ksd for different soil types have been
tabulated below in Table 3.
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DMS-Project, Mekong River Commission
Table 3.
Detachment sensitivities of soil types.
Soil type
Clay
Clay loam
Silt
Silt loam
Loam
Sandy loam
Loamy sand
Fine sand
Sand
Detachment sensitivity, g/J
Low
Average
High
1.7
2.0
2.4
1.4
1.7
1.9
0.8
1.2
1.6
0.8
1.5
2.3
1.0
2.0
2.7
1.7
2.6
3.1
1.9
3.0
4.0
2.0
3.5
6.0
1.0
1.9
3.0
Solid materials are handled in the model with three solid material variables
representing different size classes. The size classes are the following:
Table 4.
Fractions of solid material.
Class
Clay
Silt
Sand
Variable
SS0
SS1
SS2
Size (mm)
0.006
0.02
0.2
Sed. speed (m/d)
0.1
1.3
10
18.3 SOLID MATERIALS IN RIVERS AND LAKES
In the waterway the solid materials settle down according to a sedimentation speed
given as parameter. The sedimentation speeds in the model can be set separately for
river channels, lakes and surface runoff.
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HBV and IWRM Watershed Modelling User Guide
PART III – APPENDICES
www.eia.fi
179
DMS-Project, Mekong River Commission
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