Appendix: Modelling systems
The term ‘modelling system’ refers to code in a computer language (Fortran, Delphi, Cþ þ, etc.)
describing real-world processes in physical and/or parameter-based equations. This is often also
simply called a ‘model’. It is important to realize that the word ‘model’ is also used for ‘modelling
implementations’. A modelling implementation is a modelling system in which all the characteristics
of a region are included. Such an implementation is ready to be used to support policy making and/or
operational management.
For this paper we used three modelling systems (SPHY, SWAT, WEAP) and six modelling
implementations (SPHY-MENA, WEAP-MENA, SPHY-Aral, WEAP-Aral, SWAT-Tana, WEAPTana). The three modelling systems will be summarized here; details can be found in the extensive
manuals for those models (see references under each model).
The SPHY (Spatial Processes in HYdrology) model was developed using the best components of
existing and well-tested simulation models: HydroS (Droogers en Immerzeel, 2010), SWAT
(Shrinivasan, 1998), PCGLOBWB (Sperna Weiland et al., 2010) and HimSim (Immerzeel et al.,
2012). SPHY was developed with the explicit aim to simulate terrestrial hydrology at flexible scales,
under various land use and climate conditions. The main terrestrial hydrological processes are
described in a physically consistent way so that changes in storages and fluxes can be assessed
adequately over time and space. SPHY is written in the meta-language of the PCRaster GIS package.
SPHY is grid-based, and cell values represent averages over a cell, but sub-grid variability is
taken into account. The most fundamental subdivision is that between open-water surface and land
surface in each cell. The hydrological processes on the land surface are confined to a single cell.
Within each cell, the parameterization is further subdivided on the basis of vegetation. Where a
distinction is made between land cover types at the sub-grid level, state variables are stored as the
cell average.
SPHY simulates, for each cell, precipitation in the form of rain or snow, which falls on land or on
open water. The land compartment is divided into two upper soil stores and a third groundwater
store, with their corresponding drainage components: direct runoff, interflow and base flow. The
resulting discharge along the channel with lateral in- and outflow and local gains and losses are
simulated. Any precipitation that falls on land can be intercepted by vegetation and partly or entirely
evaporated. Snow is accumulated when the temperature is sufficiently low; otherwise it melts and
adds to the liquid precipitation that reaches the soil as rain or through-fall. A part of the liquid
precipitation is transformed into surface runoff; the remainder infiltrates into the soil. The resulting
soil moisture is subject to soil evaporation when the surface is bare and to transpiration when
vegetated; the remainder contributes in the long term to river discharge by means of slow drainage
which is subdivided into subsurface storm flow from the soil and base flow from the groundwater
The SPHY model is in the public domain. Executable as well as source code can be obtained
from the developers.
SPHY requires input on state variables as well as dynamic variables at grid format. For the state
variables the most relevant are DEM, land use, land cover, reservoirs and soil characteristics. The
main dynamic variables are climate data such as precipitation, temperature and reference
evapotranspiration. Since SPHY is grid based, optimal use of remote-sensing data and global data
sources can be made.
For setting up the model, data on streamflows are not necessary. However, to undertake a proper
calibration and validation procedure, flow data are required.
The SPHY model provides a wealth of output data that can be selected based on the preferences of
the user. Spatial output can be presented as maps of all the hydrological processes. Maps often
displayed as output include actual evapotranspiration, runoff generation, and groundwater recharge.
These maps can be generated on a daily basis, but most users prefer monthly or annual aggregated
time periods.
q 2014 Taylor & Francis
Time series can be generated for each location in the study area, whether it is land, open water or
a stream. Time series often used are streamflow under current and future conditions, actual
evapotranspiration, and recharge to the groundwater.
Droogers, P., Immerzeel, W. W., Terink, W., Hoogeveen, J., Bierkens, M. F. P., van Beek, L. P. H.,
& Debele, B. (2012). Water resources trends in Middle East and North Africa towards 2050.
Hydrology and Earth System Sciences, 16, 3101 –3114.
Droogers, P., & Immerzeel, W.W. (2010). What is the best model?. H2O-Water Management,
2010– 4, 38 – 41.
Lutz, A.F., Immerzeel, W.W., & Droogers, P. (2012). Climate change impacts on the upstream water
resources of the Amu and Syr Darya River basins. Report FutureWater, 107.
Sivapalan, M. (2009). The secret to “doing better hydrological science”: Change the question!.
Hydrological Process, 23, 1391– 1396.
Sperna Weiland, F.C. (2011). Hydrological impacts of climate change interpretation of uncertainties
introduced by global models of climate and hydrology. Utrecht University. http://igitur-archive.l
Van Beek, L. P. H., Wada, Y., & Bierkens, M. F. P. (2011). Global monthly water stress: 1. Water
balance and water availability. Water Resources Research, 47, W07517.
Wesseling, C.G., Karssenberg, D., Van Deursen, W.P.A., & Burrough, P.A. (1996). Integrating
dynamic environmental models in GIS: the development of a Dynamic Modelling language.
Transactions in GIS, 1, 40 – 48.
The Soil and Water Assessment Tool (SWAT) is a river-basin-scale model developed to quantify the
impact of land management practices in large, complex watersheds. SWAT is a public-domain
model actively supported by the USDA Agricultural Research Service at the Grassland, Soil and
Water Research Laboratory in Temple, Texas, USA.
SWAT is a process-based continuous daily time-step model which evaluates land management
decisions in small to large watersheds. A natural sub-basin is usually composed of several land uses
(or crops) and soil types. In SWAT modelling, a sub-basin is required to represent a unique land use
(or crop rotation) and soil type. A straightforward approach is to use the predominant land use (or
crop rotation) and soil. SWAT also allows for non-spatial subdivision of sub-basins into smaller subunits based on land use and soil variations – virtual sub-basins. These are specified as percentages of
the larger sub-basin area.
SWAT has been applied in various basins in different countries and has been calibrated and
validated for different conditions.
SWAT can be considered the de facto standard in hydrological basin-scale modelling where land
use interactions are relevant. SWAT can be downloaded from the Internet and is free of charge.
There is extensive support by the developers as well as a group of active users.
SWAT requires spatially distributed data for the basin. The most important types are DEM, land
cover and soils. From the DEM, the sub-catchments are generated automatically, as is the stream
network. These sub-catchments, land cover and soils are then used to obtain homogeneous response
units (HRUs). Meteorological data at one or more locations in the basin provide sufficient
information to run the model. It is optional to include reservoirs and operational rules for these.
Multiple standardized databases are included to parameterize different land use types, crops, and
SWAT provides streamflow and land-based outputs. Streamflow can include water quality aspects
for every stream in the basin. The land-based results are extensive and include all the components of
the hydrological cycle as well as erosion, pollutants, nutrients and crop growth. All this information
is available per sub-catchment as well as per HRU.
Arnold, J.G., Srinivasan, R., Muttiah, R.S., & Williams, J.R. (1998). Large area hydrologic
modelling and assessment part I: Model development. Journal of the American Water Resources
Association, 34(1), 73 – 89.
Betrie, G. D., Mohamed, Y. A., van Griensven, A., & Srinivasan, R. (2011). Sediment management
modelling in the Blue Nile basin using SWAT model. Hydrology and Earth System Sciences, 15
(3), 807 –818.
Neitsch, S.L., Arnold, J.G., Kiniry, J.R., & Williams, J.R. (2011). Soil and Water Assessment Tool
(SWAT). Theoretical documentation, version 2009, Texas Water Resources Institute Technical
Report No. 406.
The WEAP (Water Evaluation And Planning) system includes a semi-physical, irregular-grid,
lumped-parameter hydrologic simulation model that can account for hydrologic processes within a
water distribution system. WEAP works with nodes and arrows as indicators of water flow and
While the model can be run on any time-step where routing is not a consideration, the model
description assumes a monthly time-step. The time horizon can be set by the user, from as short as a
single year to more than 100 years. Scenarios are evaluated with regard to water sufficiency, costs
and benefits, compatibility with environmental targets, and sensitivity to uncertainty in key
WEAP contains built-in models for rainfall runoff and infiltration; evapotranspiration; crop
requirements and yields; surface-water and groundwater interaction; and in-stream water quality. It
has a GIS-based, graphical ‘drag and drop’ interface. WEAP allows user-defined variables and
equations and has a model-building facility. It has dynamic links to spreadsheets and other models.
Data structures are flexible and expandable.
Although the WEAP model comprises both a hydrological component and a water management
component, it is more of a water planning model, focused more on water division, infrastructure and
economic evaluation than on the physical water hydrology.
Support of the model in terms of manuals, training, and support of developers is excellent.
Since WEAP’s primarily goal is to evaluate water allocation options, the major input is related to
demand and supply sites (nodes) that are connected by links. Examples of required input are urban
areas, agricultural areas, groundwater, reservoirs, catchment nodes, rivers and canals. The catchment
nodes can be specified to be more hydrological-oriented, including rainfall-runoff processes.
WEAP operates always in an optimization-of-water-allocation mode, based on priorities set for each
demand site. Outputs of WEAP include flows for all connection lines (rivers, canals) and met and
unmet demands for all the demand sites. Outputs are generated in a very attractive form and can be
exported in various formats.
Sieber, J., & Purkey, D. (2007). WEAP, water evaluation and planning system: User manual. USA:
Stockholm Environment Institute.
Yates, D., Purkey, D., Sieber, J., Huber-Lee, A., Galbraith, H., West, J., Herrod-Julius, S., Young, C.,
Joyce, B., & Rayej, M. (2009). Climate driven water resources model of the Sacramento Basin,
California. ASCE Journal of Water Resources Planning and Management, 135, 303– 313.
Yates, D., Sieber, J., Purkey, D., & Huber-Lee, A. (2005). WEAP21—A demand-, priority-, and
preference-driven water planning model. Water International, 30(4), 487– 500.
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