# AN ASSESSMENT OF THE PERFORMANCE OF FEDERALLY REGULATED SEDIMENTATION PONDS by

AN ASSESSMENT OF THE PERFORMANCE OF FEDERALLY REGULATED SEDIMENTATION PONDS by William Benton Vandivere A Thesis Submitted to the Faculty of the SCHOOL OF RENEWABLE NATURAL RESOURCES In Partial Fulfillment of the Requirements For the Degree of MASTER OF SCIENCE WITH A MAJOR IN WATERSHED MANAGEMENT In the Graduate College THE UNIVERSITY OF ARIZONA 1980 STATEMENT BY AUTHOR This thesis has been submitted in partial fulfillment of requirements for an advanced degree at The University of Arizona and is deposited in the University Library to be made available to borrowers under rules of the Library. Brief quotations from this thesis are allowable without special permission, provided that accurate acknowledgment of source is made. Requests for permission for extended quotation from or reproduction of this manuscript in whole or in part may be granted by the head of the major department or the Dean of the Graduate College when in his judgment the proposed use of the material is in the interests of scholarship. In all other instances, however, permission must be obtained from the author. SIGNED: APPROVAL BY THESIS COMMITTEE This thesis has been approved on the date shown below: , - 7 2 il/A- . MARTIN MAI,U FOGEL Date gement IJI-1 GOJ ( DONALD ROSS DAVIS Assistant Profess .r of Hydrology and Wate fesoAices LOUIS . HEKMAN Assistant Prof ssor of Renewable Natur Resources X/C6/ 3 (t O - Date' Date ACKNOWLEDGMENTS The author is greatly indebted to his principal advisor, Dr. Martin Fogel, for providing the opportunity to develop and expand his intellectual facilities. His avowed skepticism was at once refreshing and realistic and will continue to endear him to his students. Additional thanks must be directed toward Dr. Louis Hekman and Dr. Donald Davis, whose patience and guidance were well appreciated. The periodic assistance from Dr. John Thames also contributed to the author's pursuit of a practical understanding of the field of hydrology. Best wishes and sincere affection are ext4nded to friends and colleagues of the author during his brief tenure with the School of Renewable Natural Resources. A genuine comaraderie existed, and hopefully will continue between us, expecially Steve Blake, Jeff Franklin, and Todd Rasmussen. Their input was always informative and much valued. A special heartfelt thanks goes to Ms. Paula-Ann Cech who faithfully supported the author through good times and bad and without whose help both his entire graduate and a significant part of his life experience would have been left unfulfulled. Appreciation is expressed for the timely work done by Phyllis Miller in preparing the final manuscript. Also, the author wishes to acknowledge the aid received from Andy Ward of the Agricultural Engineering Department of the University of Kentucky who supplied access to the DEPOSITS sedimentation model. iv Portions of this study were carried out under grant #14-34-0001-9056 from the Office of Water Resources Technology entitled "The Role of Hydrologic Variability in Complying with Regulatory Enforcement Standards for the Rehabilitation of Surface-mined Coal Lands." The author wishes to thank the taxpayers of this country for this funding. TABLE OF CONTENTS Page LIST OF ILLUSTRATIONS LIST OF TABLES ABSTRACT 1. vii viii ix INTRODUCTION 1 2. REVIEW OF LITERATURE AND PERTINENT REGULATORY STATUTES 4 Sedimentation Ponds and Manipulated Environments Animal Feedlots Construction Sites Surface Mining Operations Uncertainty in the Sedimentation Process Applicable Regulatory Statutes 3. SITE CHARACTERISTICS AND FORMULATION OF STUDY Hypothetical Watershed Development of Hydrologic Inputs Model Components and Operation: Program INFLUX Precipitation Infiltration Runoff Sediment Sedimentation Pond Design DEPOSITS Sedimentation Model 4. RESULTS AND DISCUSSION Pond Sensitivity Analysis National Soil Material with Untreated Pond Inflow Hydrologic Uncertainty and Implications for Pond Performance Model Adaptability and Regional Bias • • 4 5 7 9 13 16 21 21 22 25 25 27 34 36 38 43 49 49 57 66 70 vi TABLE OF CONTENTS, Continued. Page 5. CONCLUSIONS AND RECOMMENDATIONS 72 APPENDIX A: SEDIMENTATION POND DESIGN 77 APPENDIX B: INFLUX VARIABLE DESCRIPTION 109 APPENDIX C: PROGRAM LISTING OF INFLUX 112 APPENDIX D: PROGRAM AND INPUT LISTING OF DEPOSITS 116 LIST OF REFERENCES 137 LIST OF ILLUSTRATIONS Figure Page 1. SCS Type I and II 24-hr. rainfall distribution 26 2. Data points and infiltration curve for 0.5 year old spoil material, J-3 experimental area 29 3. Generalized flowchart for hydrologic linkages . . 31 4. SCS triangular hydrograph 37 5. Schematic diagram of sedimentation pond and dewatering device 44 6. Plug flow routing for DEPOSITS sedimentation model 7. Predicted peak effluent concentrations and contours in mg/2 for Black Mesa minspoil with altered inputs and untreated pond inflow vii 47 58 LIST OF TABLES Table Page 1. Point precipitation-frequency values for Black Mesa Mine, Arizona, in inches 24 2. Discretization of Type II rainfall distribution for 24 hr. duration 28 3. Discretization of J-3 infiltration capacity curve 32 4. 5. 6. 7. Precipitation characteristics and predicted peak effluent sediment concentrations for routed Black Mesa storms, 5-10 yr. return periods: minespoil with untreated pond inflow 51 Precipitation characteristics and predicted peak effluent sediment concentrations for routed Black Mesa storms, 12-25 yr. return periods: minespoil with untreated pond inflow 53 Particle size distributions for undisturbed experimental waterhseds: Black Mesa, AZ 59 Predicted effluent sediment concentrations for routed Black Mesa storms: natural soil material with untreated pond inflow 61 Predicted peak effluent sediment concentrations for routed, selected Black Mesa storms: minespoil with chemical treatment of inflow 63 Predicted event sedimPnt yield for simulated conditions at Black Mesa, AZ: 5-10 yr. return periods 64 Predicted event sediment yield for simulated conditions at Black Mesa, AZ: 12-25 yr. return periods 65 A.1 Size fraction distributions for sediment production: J-3 experimental watershed, Black Mesa Mine 84 A.2 Rating relations for final pond design 88 8. 9. 10. A.3 Stage-discharge relations for final pond design viii 91 ABSTRACT A study was undertaken to evaluate the performance of federally regulated sedimentation ponds, used in conjunction with surface mining operations in the semi-arid southwest. Emphasis was placed on the assessment of pond performance under conditions of hydrologic uncertainty represented by precipitation inputs of varying frequencies and durations. A hypothetical watershed with characteristics common to the study area functioned as the medium for surface water flux to the detention facility. Pond design was based on accepted hydrologic and engineering procedure and concurred with published federal reclamation statutes. Computer programs were utilized to model both the temporal characteristics of southwestern convective rainfall and the generation of water and sediment inflaws resulting from the application of storms over the watershed. A previously developed sedimentation routine was then used to determine effluent sediment concentrations corresponding to the modeled events. Three watershed-pond conditions were investigated to assess the efficacy of the sedimentation pond in meeting effluent quality standards. Results indicated that poor pond performance ensured unless chemical treatment was maintained. Since variations in precipitation intensity influenced predicted pond performance, it was recommended that hydrologic uncertainty be considered in the drafting of regional reclamation statutes. ix CHAPTER 1 INTRODUCTION As natural phenomena the fluvial processes of erosion and sedimendation proceed at a rate determined by prevailing hydrometeorological and geologic conditions. A quasi-equilibrium is established over time which affects a balance between hillslope development and stream regimen. Man's intervention, however, often results in short term distortions in this delicately adjusting mechanism. The national addiction to non-renewable fossil fuels has led to a recent expansion in possibly the most environmentally disruptive of human activities; the surface mining of coal. An immediate consequence of this disruption is an acceleration in the rates of erosion and sedimentation observed in the effected areas. Extensive soil loss from surface mine sites inhibits generation of protective vegetative cover and befouls area stream flow, threatening indigenous aquatic life. In an effort to mitigate the environmental damage wrought by mining operations, the 95th Congress enacted preventative measures embodied in the Surface Mining Control and Reclamation Act of 1977. The Act expressed the intent to assure reclamation of mined land while not unduly burdening mine operators. Of course, the high priority given continued access to the coal resource was sustained. The federal statutes represent baseline criteria for acceptable mining and reclamation procedures. States have been presented with the 1 2 option of developing their own standards, as long as they are at least as stringent as those outlined by the Act. In addition, states have been encouraged to consider regional variabilities in the drafting of their federal counterparts. A permanent regulatory program has been published by the Office of Surface Mining (OSM) for purposes of setting standards for mining and reclamation practices which are consistent with the legislative intent of Congress. Considerable attention was paid to the maintenance of the hydrologic balance in and adjacent to areas subjected to mining disturbances. Central to this concept was the desire to minimize changes in water quality and quantity, drainage patterns,and groundwater systems. Consideration of feasible alternatives convinced OSM that the use of sedimentation ponds in conjunction with other sediment control measures provided the best available technology for removing suspended solids from mine site runoff. In the semi-arid regions of the western U.S., extreme variability in the occurrence and nature of precipitation introduces an element of uncertainty into the design process for sedimentation ponds. Since assessment of the effects of regional hydrologic and climatic uncertainty on reclamation efforts has been left unaddressed by federal statutes, a need has arisen for evaluation of the uncertainties and their implications for the design and expected performance of mandated sedimentation ponds. The present study attempts to aid in the appraisal of the effects of hydrologic uncertainty on the performance of federally regulated sedimentation ponds. Specifically, its purpose is threefold: 3 (1) Compile a model capable of simulating the performance of sedimentation ponds designed in accordance with federal statutes and generally accepted engineering-hydrologic practice. (2) Assess the effects of precipitation uncertainty, in particular, the influence of variable rainfall intensity and rainfallrunoff volume on sediment yields from minespoil watersheds and on the effluent quality of event based discharges from sedimentation ponds functioning on these watersheds. (3) Evaluate current federal performance criteria for sedimentation ponds functioning in a semi-arid environment where precipitation influx is limited and predominantly convective in character. CHAPTER 2 REVIEW OF LITERATURE AND PERTINENT REGULATORY STATUTES The following section is devoted to a review of research and legislation currently influencing the design and evaluation of the performance of sedimentation ponds. Initially, studies dealing with the application of sedimentation ponds to the problem of alleviating pollutant migration under disturbed conditions are summarized. A brief examination of work aimed at delineating the effects of uncertainty in the sedimentation process follows. Concluding the chapter is a condensed review of recently promulgated federal statutes especially relevant to the present investigation. Sedimentation Ponds and Manipulated Environments Literature pertaining to the design and performance of sedimentation ponds was rather sparse until the advent of federal water quality legislation in the early nineteen seventies. In response to newly enacted state and federal guidelines for pond design, researchers concerned themselves with the evaluation of ponds, existing or hypothetical, which conformed to applicable regulatory statutes. Relevant studies have focused on the utilization of detention basins for purposes of mitigating environmental degredation in three disturbed settings: 4 5 (1) animal feedlots; (2) construction sites; and (3) surface mining operations. The requirement for detention facilities at feedlot locations stems from the desire to limit discharge of organic waste products as well as nutrient and sediment-laden water into receiving streams. Discharge from areas disturbed by construction and surface mining, while also potentially deleterious to existing chemical balance in streams, is primarily undesirable from the standpoint of the intensive stream sediment loading it engenders. Animal Feedlots Due to the objectionable nature of runoff from animal feedlot areas, detention facilities are often designed to preclude any discharge of runoff generated by the 10-yr, 24-hr. or 25-yr., 24-hr. rainfall event. Wensink and Miner (1975), using simulated rainfall and temperature inputs for Oregon feedlot sites, analyzed the performance of a hypothetical detention basin. Dewatering of stored runoff was accomplished solely by pumpage in response to irrigation demand which was dependent upon antecedent temperature and moisture conditions. Reservoir storage volume was determined using two design methods. A "retention return period" method, employing the SCS rainfall-runoff relations and rainfall frequency data published by the National Oceanic and Atmospheric Administration (NOAA) was compared with a "sufficient design" technique. The latter method sized the facility on the basis of total storage of all runoff resulting from storms falling within the bounds of the design event. The authors concluded that for most cases the 6 "return period" design technique produced either insufficient storage or resulted in unreasonably expensive basins. The "sufficient design technique, on the other hand, was found to minimize the required pond volume for the appropriate pumping rate while more adequately satisfying environmental protection standards. A similar investigation (Koelliker, Manges, and Lipper, 1975) carried out in Kansas examined the effect of regional precipitation variability on detention basin response. Evaporation, as well as irrigation pumpage, was incorporated into the analysis. Basin performance as measured by frequency of overflow was considerably worse in regions experiencing lengthly periods of persistent rainfall. Drier regions generally subject to single rainfall events with longer interarrival times created fewer basin overflows. Consideration of chronic wet periods was, therefore, viewed as the critical factor in the sizing of detention facilities. It should also be noted that most discharges resulted from storms substantially less than the design event. Hydrologic conditions typical of North Carolina dairy feedlots were modeled by Overcash and Phillips (1978) to evaluate established guidelines for the animal production industry. Linear and non-linear rainfall-runoff models were applied to assess the efficiency of using the mandated 25-yr., 24-hr. storm for retention basin design. At representative SCS curve number values for specific feedlot locations, the rainfall magnitude at which incremental rainfall produced a correspondingly high (95%) runoff response was determined. This quantity was found to correlate closely with that corresponding to the 7 appropriate 25-yr., 24-hr. rainfall value extracted from records of the U.S. Weather Service and HISRAS (Hydrologic Information and Retrieval System). On this basis, the authors concluded that the 25-yr., 24-hr. storm appeared justifiable from a basin design viewpoint. Construction Sites Construction and urbanization denude substantial areas of land exposing it to the heightened erosive capabilities of rainfall. Rapid deterioration of water bodies adjoining these disturbed areas has necessitated regulatory controls directed at easing the impact of accelerated sediment production on water quality. Because of the extensive nature of the problem, a multitude of field evaluation and model studies have ensued. Noteworthy, is the development of a sediment discharge model (Curtis, 1976) describing water and sediment transport in urbanizing areas. Model results revealed a tendency for both peak sediment discharge and total volume of sediment discharge to increase with increasing rainfall intensities. The use of sedimentation ponds for reducing sediment concentrations in construction site runoff and the turbidity of receiving streams has become widespread. Oscanyon (1975) introduced a set of design criteria for the design of sediment basins on construction sites in Maryland. It was assumed that even a well designed and adequately maintained structure would remove no smaller than .005 mm diameter sediment. Alternative on-site measures were cited as offering a greater margin of sediment control where higher percentages of clay are contained in pond 8 influent. An examination of the relative merits of in-stream and offstream sedimentation ponds was undertaken by Reed (1975). Both types of ponds performed equally well in removing sediment, with reductions of 80 percent for most storms. The in-stream pond, however, sustained higher mean turbidity levels for longer periods of time than its offstream bounterpart. Curtis and McCuen (1977) derived a mathematical model of a detention basin coupled with a watershed hydrologic model for assessment of basin hydraulic efficiency. Trap efficiencies for the basin were found to increase with decreasing proportions of smaller, lighter particles in the inflow. In addition, both decreased initial storage and smaller orifice diameters for perforated risers increased modeled trap efficiencies. Decreased basin depth along with a concommitant increase in surface area also produced increased trap efficiencies. The effect of basin depth and area on performance was reaffirmed in a study by Bondurant, Brockway, and Brow (1975). Specifically, the authors recommended that in order to achieve a reduction in forward velocity and depth of settling, the design would have to include (1) adequate sediment storage volume, (2) decreasing flow depth towards the outlet, and (3) a means for reducing entrance velocities to the pond. Higher removal efficiencies were obtained at higher flow rates due to the greater relative proportion of finer particles transported at low flow rates. 9 Surface Mining Operations Surface mining is one of the single most devastating operations practiced by man upon his environment. Studies involving the application of sedimentation ponds to mining operations and subsequent reclamation efforts have again tended towards either the development of acceptable guidelines or the appraisal of previously enacted legislation referring to pond design and performance. Curtis (1974) conducted a study to determine sediment production from mined areas and to propose criteria for calculating detention basin storage volume. The first six months following the termination of mining was indicated as the most critical period for sediment production. Major factors contributing to sediment yield were deduced to be methods of mining and handling of overburden and rapid establishment of vegetative cover. The effectiveness of onsite sediment control measures coupled with an in-stream sedimentation pond was analyzed by White and Plass (1974) for a mining operation in West Virginia. It was noted that pond removal efficiency was greatest for low intensity stormllow. A review of sedimentation mechanics and earlier methods for determination of sediment basin trap efficiency was presented by Haan and Barfield (1978). Among the methods examined were that of the EPA (1976) and the DEPOSITS sedimentation model (Ward, Haan, and Barfield 1977a). The EPA (1976) methodology, a derivative of the prior work of Camp (1945), was described as plausible for steady state flows, but inadequate in its representation of semi-dry basin performance. Because of its superior capabilities for handling typical field 10 conditions, the DEPOSITS model (Ward et al., 1977a) was favored by the authors for more accurately depicting actual basin functioning. Another conclusion reached by Haan and Barfield (1978) was that given identical outflow riser configurations, a basin containing a permanent pool capacity will produce higher quality effluent than one lacking permanent storage. This was attributed in part to the lessened probability that resuspension of deposited sediments would occur. The construction of the DEPOSITS model is described in detail by Ward, Haan, and Barfield (1977b). Model verification was completed using data published in a report by the EPA by Hittman Associates, Inc. (1976a). The authors of the DEPOSITS formulation expressed misgivings over the methods used in the EPA study. In particular, data collection techniques were deemed unacceptable and the method for determining actual basin performance was questioned. The equation developed for determination of trap efficiency assumed instantaneous flow through the basin. This assumption neglected the effect of varying detention times for the different portions of throughflow and depended entirely on simultaneous readings of influent and effluent sediment concentrations over a short time period. Since the DEPOSITS model accounted for varying flow rates and reservoir detention times, the authors felt that it embodied a more realistic conception of the actual sedimentation process and was, therefore, of greater value as a tool for evaluation of pond performance. The ground breaking investigation on the performance of sedimentation ponds at eastern mining sites by Kathuria, Nawrocki, and Becker for the EPA (1976a) contributed much to the recent discussion on 11 performance standards prompted by OSM. In-field evaluation of nine functioning ponds in W. Virginia, Kentucky and Pensylvania was conducted in an attempt to determine trap efficiencies and to identify characteristics influencing pond behavior. Sampling was carried out during both baseline and rainfall operating conditions. Theoretical removal efficiency computed by means of Ideal Settling Theory was compared to a measure of actual removal efficiency expressed as: 10 c R(% solids removed) = 1 6 l X 100 (1) 6 10 C2 where C 1 is the concentration of suspended solids in the influent in mg/1 and C 2 is the concentration of suspended solids in the effluent in mg/l. Poor maintainance and lack of conformance to approved design plans were cited as major factors inhibiting attainment of desired trap efficiencies. It was recommended that either a ten hour minimum detention time or a maximum overflow velocity of 2 X 10 -5 m/sec. be maintained in order to achieve higher suspended solids removal efficiencies. Maximization of pond surface area and continuous provision for a minimum depth of 1.0 m. (3.3 ft.) were advised to limit resuspension of settled sediment. The authors also acknowledged that in most cases flocculating agents would be required for removal of fine grained sediments. 12 Inefficiencies inherent in settling finer sediment particles were again recognized in an EPA study (1976). Referring to Ideal Settling Theory, the study suggested that required settling area for a sediment detention structure be computed as: A=0 0 /V s , where Qo is the pond overflow rate and V s is the critical settling velocity of the smallest particle to be retained. Factors causing deviations from Ideal Settling Theory were outlined. Additionally, a number of design innovations accruing from years of experimentation with existing ponds were presented. Ward, Haan and Barfield (1978) furthered understanding of the basin design process with their work on the hydrology and hydraulics of sediment basins. Various hypothetical basin geometries together with different riser configurations were analyzed. Predictive equations for estimation of peak effluent sediment concentration and basin trap efficiency were derived through regression analysis on data generated by the DEPOSITS sedimentation model (Ward et al., 1977b). Three baseline conditions for simulation of pond performance were examined: (1) a dry basin prior to the storm event; (2) a permanent pool below the riser crest prior to the storm event; and (3) a permanent pool followed by a base flow event occurring after the storm event. Notably, the authors were of the opinion that effluent standards could not be met with perforated risers (principle spillway), and thus, they were not evaluated. A number of illuminating conclusions were advanced regarding basin design-performance interaction. Where the percentage of finer than 20 micron (II) particles exceeded 30 percent, it was the authors contention 13 that trap efficiencies would not exceed 80 percent in basins providing a detention time of less than 12 hours for the 10 yr.-24 hr. design event. Moreover, it was felt that if sediment in the inflow contained greater than 20 percent of particles finer than 20g, it was unlikely that water quality standards would be achieved unless flocculating agents were utilized or storage in excess of 24 hours was possible. An investigation pursued by McCarthy (1977) was mentioned as having indicated that flocculants could provide an economical solution to achievement of water quality standards. In his work on sediment control on three watersheds near Centralia, Washington, the author estimated chemical treatment costs of $10/ac.-ft. of runoff. Direct reference to the current federal statutes concerning sedimentation pond design has been made by Krishnamurthi and Blazer (1978). The authors contended that trap efficiency was more dependent on functional design characteristics than on a particular magnitude of flow. It was recommended that instead of requiring use of the designstorm concept for basin design, modeling of the physical characteristics of the storm events should dictate design logic. Redirected emphasis on sediment concentrations in streamflow as opposed to point source pollutant concentrations in pond effluent was also suggested. Uncertainty in the Sedimentation Process Transport of sediment from contributing watersheds to receptor watercourses is closely correlated with overland water discharge. Thus, the uncertainties involved in the sedimentation process are related, in 14 part, to those germane to hydrologic systems. There are, however, other sources of uncertainty introduced when a physical conceptualization of the process is entailed. No attempt has been made in this review to encompass all of the existing volumes devoted to empirical and fully deterministic treatment of reservoir sedimentation. Only those formulations which recognize the uncertainties inherent in the sedimentation process are surveyed. Apart from readily discernable sources of random hydrologic behavior, uncertainty affecting sedimentation also resides in factors such as type of land use, vegetative cover, soil structure and erodibility, gulley headcutting, and other natural and man-induced processes which contain elements of randomness (Woolhiser and Renard, 1978). The uncertainty involved in appraising the erodibility of soil subjected to the dynamic conditions of surface mining has been acknowledged by field researchers of the SCS (EPA 1977). Another factor in the determination of erosion from watersheds is rainfall energy (Wischmeier and Smith, 1965). The effect of regional precipitation uncertainty on the rainfall erosion index (El) of the USLE has been examined by Renard and Simanton (1975). Spatial and temporal variability in El values resulting from air-mass thunderstorms were shown to be considerable even for watersheds located in close proximity to one another. Woolhiser and Blinco (1975) discussed a study by Krumbein (1968) in which the author classified three stages of statistical development in sedimentology; descriptive statistics, analytical 15 statistics, and application of stochastic process models. Descriptive statistics emphasizes the characteristics of the sample while analytical statistics concerns itself primarily with extracting sample information for the purpose of inferring population characteristics. The stochastic model derives from consideration of the random properties of the phenomena. The analytic category is exemplified by the work of Shirley and Lane (1978), Flaxman (1972), and Weber, Fogel, and Duckstein (1976). Shirley and Lane (1978) derived a mathematical erosion simulation model and made a least squares fit to observed data for a small watershed near Tombstone, Arizona. In his study of sediment yield characteristics for the western U.S., Flaxman (1972) utilized multiple regression analysis on logged reservoir and stock pond sedimentation data to derive an expression for watershed sediment production. Independent variables were assumed to be: the ratio of average annual precipitation to average annual temperature, watershed slope, the percent of soil particles coarser than 1 millimeter (mm) in the surface 2 inches of soil, and a descriptor of aggregation potential in that same 2 inch soil surface layer. The utility of multiple regression models for the prediction of sediment yield has been scrutinized by Weber et al. (1976). Data obtained from Flaxman's (1972) study was used to assess the applicability of four linear and logarithmic transformation models. It was concluded on the basis of regression analysis and economic loss function analysis that the linear model was preferable to the other log transformation models evaluated. 16 Referring to the work of Parzen (1962), Woolhisen and Blinco (1975) state that: "A stochastic process is the dynamic part of probability theory and we observe a stochastic process whenever we examine a process developing in time in a manner controlled by probabilistic laws." There exists a number of partial and wholly stochastic models which can be included in Krumbein's (1968) third category. Model studies linking stochastic rainfall-runoff relations with deterministic sediment yield relations have been constructed by Auernhamer et al. (1977), Renard and Lane (1975), and Fogel, Duckstein and Musey (1976). A methodology for determining reservoir sediment yield based on limited rainfall data and a derivative of William's (1975) sediment yield model was elaborated by Smith, Davis, and Fogel (1977). Effective rainfall, event duration, and number of events per season were viewed as random variables, thus dictating the random nature of the computed sediment yield. Mathematical derivation of stochastic process models has appeared in the work of Woolhiser and Todovoric (1971), Woolhiser and Blinco (1975), and Woolhiser and Renard (1978). Mathematical representations were advanced by Woolhiser and Blinco (1975) for the stochastic processes of precipitation influx, evapotranspiration, porous media flow, and surface streamflow. A distribution function for sediment yield resultant from the modeling of watershed stochastic processes was also presented. Applicable Regulatory Statutes Since the purpose of this analysis is the assessment of sedimentation ponds designed in accordance with federal statues for surface 17 mining and reclamation operations, a brief overview of the applicable design, performance, and effluent standards set forth in those statues is offered. All referenced quotations have been excerpted from the Federal Register (1979). Although more recent editions may have appeared during the interim period, it is assumed that no major alterations in the text have ensued. Perhaps the most straightforward of all the design criteria is that pertaining to required sediment storage volume for the pond (Federal Register, p. 15400): Sedimentation ponds shall provide a minimum sediment storage volume equal to (1) The accumulated sediment volume from the drainage area to the pond for a minimum of 3 years. Sediment storage volume shall be determined using the Universal Soil Loss Equation, gully erosion rates, and the sediment delivery ratio converted to sediment volume, using either the sediment density or other empirical methods derived from regional sediment pond studies if approved by the regulatory authority, or (2) 0.1 acre-foot for each acre of disturbed area within the the upstream drainage area or a greater amount if required by the regulatory authority based upon sediment yield to the pond. The regulatory authority may approve a sediment storage volume of not less than 0.035 acre-foot for each acre of disturbed area within the upstream drainage area, if the person who conducts the surface mining activities demonstrates that sediment removed by other sediment control measures is equal to the reduction in sediment storage volume. More controversial is the detention time provision (Federal Register, p. 15400): Sedimentation ponds shall provide the required theoretical detention time for the water inflow or runoff entering the 18 pond from a 10-year, 24-hour precipitation event (design event). Theoretical detention time is defined as the average time that the design flow is detained in the pond and is further defined as the time difference between the centroid of the inflow hydrograph and the centroid of the outflow hydrograph for the design event. Runoff diverted under Sections 816.43 and 816.44, away from the disturbed drainage areas and not passed through the sedimentation pond need not be considered in sedimentation pond design. In determining the runoff volume, the characteristics of the mine site, reclamation procedures, and on site sediment control practices shall be considered. Sedimentation ponds shall provide a theoretical detention time of not less than twenty-four hours, or any higher amount required by the regulatory authority, except as provided under sub-paragraphs (1), (2), or (3) of this paragraph. (3) The regulatory authority may approve a theoretical detention time of less than 24 hours to any level of detention time, when the person who conducts the surface mining activities demonstrates to the regulatory authority that the chemical treatment process to be used - (i) Will achieve and maintain the effluent limitations; and (ii) Is harmless to fish, wildlife, and related environmental values. Dewatering requirements governing the design and performance of the pond spillway systems or other modes of discharging stored storm runoff are outlined as follows (Federal Register, p. 15400): The water storage resulting from inflow shall be removed by a nonclogging dewatering device or a conduit spillway approved by the regulatory authority, and shall have a discharge rate to achieve and maintain the required theoretical detention time. The dewatering device shall not be located at a lower elevation than the maximum elevation of the sedimentation storage volume. (e) Each person who conducts surface mining activities shall design, construct, and maintain sedimentation ponds to prevent short-circuiting to the extent possible. (g) There shall be no outflow through the emergency spillway during the passage of the runoff resulting from the 10-year, 24-hour precipitation event or lesser events through the sedimentation pond. (h) Sediment shall be removed from sedimentation ponds when the volume of sediment accumulates to 60 percent of the design sediment storage volume. 19 (i) An appropriate combination of principal and emergency spillways shall be provided to safely discharge the runoff from a 25-year, 24-hour precipitation event, or larger event specified by the regulatory authority. The elevation of the crest of the emergency spillway shall be a minimum of 1.0 foot above the crest of the principal spillway. Finally, the requirement which ultimately assures compliance with water quality guidelines (Federal Register, p. 15400): (0 The design, construction, and maintenance of a sedimentation pond or other sediment control measures in accordance with this Section shall not relieve the person from compliance with applicable effluent limitations as contained in 30 CFR 816.42. The purpose of dictating the use of sedimentation ponds is, of course, to clarify polluted water delivered from those areas disturbed by mining. Following are passages associated with water quality standards and effluent limitations (Federal Register, p. 15398): (a) (1) All surface drainage from the disturbed area, including disturbed areas that have been graded, seeded, or planted, shall be passed through a sedimentation pond or a series of sedimentation ponds before leaving the permit area. - (2) Sedimentation ponds and other treatment facilities shall be maintained until the disturbed area has been restored and the vegetation requirements of Sections 8.6.111816.117 are met and the quality of the untreated drainage from the disturbed area meets the applicable State and Federal water quality standards requirements for the receiving stream. (7) Discharges of water from areas disturbed by surface mining activities shall be made in compliance with all Federal and State laws and regulations and, at a minimum, the following numerical effluent limitations: 20 Effluent limitations, in milligrams per liter (mg/1) except for pH Effluent characteristics Iron total Maximum allowable Manganese total 7.0 Average of daily values for 30 consecutive discharge days 3.5 4.0 Total suspended solids. 7 0.0 pH Within range of 6.0 to 9.0 2.0 35.0 To be determined according to collection and analytical procedures adopted by the Environmental Protection Agency's regulations for wastewater analysis (40 CFR 136). Based on representative sampling, The manganese limitations shall not apply to untreated discharges which are alkaline as defined by the Environmental Protection Agency (40 CFR 434). In Colorado, Montana, North Dakota, South Dakota, Utah and Wyoming, total suspended solids limitations will be determined on a case-by-case basis, but they must not be greater than 45 mg/1 (maximum allowable) and 30 mg/1 (average of daily value for 30 consecutive discharge days) based on representative sampling. (b) A discharge from the disturbed areas is not subject to the effluent limitations of this Section, if (1) The discharge is demonstrated by the discharger to have resulted from a precipitation event equal to or larger than a 10-year, 24-hour precipitation event; and (2) The discharge is from facilities designed, constructed, and maintained in accordance with the requirements of this Part. (c) Adequate facilities shall be installed, operated, and maintained to treat any water discharged from the disturbed area so that it complies with all Federal and State laws and regulations and the limitations of this Section. CHAPTER 3 SITE CHARACTERISTICS AND FORMULATION OF STUDY This chapter begins with a description of the hypothetical watershed which functions as the medium for this study. Regional and site-specific characteristics which aid in defining the resultant hydrologic regime are detailed. Next, the procedure followed in evaluating the magnitude of precipitation associated with particular frequency-duration storms is outlined. The construction and methodology of the INFLUX program which generates the required inputs for utilization by the DEPOSITS sedimentation routine is then examined. Procedural aspects of sedimentation pond design, including composition of rating curves for the reservoir, are described. A somewhat abbreviated analysis of the DEPOSITS routine concludes the chapter. The reader is advised to refer to the appendices for clarification of the computational logic of the aforementioned routines. Hypothetical Watershed The characteristics of the hypothetical watershed developed herein for hydrologic analysis are indicative of reclaimed surfacemined watersheds on the Black Mesa in northeastern Arizona. Black Mesa coal seams, being mined presently by Peabody Coal Co., range from 5 to 28 feet in thickness (Fogel, Heckman, and Vandivere, 1979). Following 21 22 the extraction of the mineral, the spoil material is recontoured so as to approximate, as closely as possible, the original topography. The study drainage area was assumed to encompass 50 acres of graded spoil material. Average watershed slopes of 6.7 percent and a slope length of 250 feet have been chosen. Contour-grid determination (Williams and Brendt, 1977) of existing basin slopes on experimental watersheds at Black Mesa was used to calculate the former value while the latter fell within the range suggested to the author by Hamon (1979). Spoil material was assumed similar to that found on the J-3 spoils experimental watershed located on the mesa. Lack of structure, relatively high clay and low organic content, and low infiltration capacity distinguish this material from surrounding natural soils. Natural precipitation which varies from 9 to 13 inches in the Black Mesa region has been assumed to be the only available source of moisture for production of water and sediment discharge from the watershed. Approximately half of the annual moisture influx is derived from summer convective storm activity. The remaining portion is delivered by frontal storm systems in the form of rain or snow. Runoff-generating events are few and often far between, thus delineating the largely ephemeral nature of streamflow in the area. Development of Hydrologic Inputs In order to adequately assess the overall performance of the sedimentation pond, it was felt that a wide spectrum of hydrologic events should be incorporated into the investigation. It was deemed 23 appropriate that the precipitation-frequency maps published by NOAA (1973) be used for determination of point rainfall volumes at the study site, since it is common practice among designers possessing limited data to utilize thie material. An extensive network of both recording and non-recording raingages provided the Weather Bureau (NOAA) researchers who compiled the maps with point rainfall volumes for specific sites in the western U.S. Isopluvials were then constructed on the basis of extrapolated data drawn from multiple linear regression equations relating topographic and climatologic factors to variations in precipitation frequency values. Frequency analysis was carried out using the annual series method and empirically derived factors for conversion to partial duration series. A total of 38 precipitation events were defined through use of the maps and accompanying equations and diagrams. Precipitation in the form of snowfall was neglected under the assumption that runoff and sediment production resulting from snowmelt at the site is minimal. Point precipitation values were left unaltered by depth-area analysis due to the small area of the watershed. The suggested one or two percent reduction due to areal distribution of rainfall seemed questionable in light of the uncertainties involved in the Weather Bureau procedure. A summary of these estimated precipitation volumes for the chosen durations and return periods appears in Table 1. 24 Table 1. Point precipitation-frequency values for Black Mesa Mine, Arizona, in inches*. Duration hr. 5 8 0.17 0.46 0.52 0.55 0.56 0.59 0.25 0.59 0.66 0.70 0.71 0.75 0.50 0.81 0.92 0.97 0.99 1.04 1.13 1.0 1.03 1.16 1.23 1.25 1.32 1.43 2.0 1.15 - 1.37 - 1.48 1.60 6.0 1.39 - 1.65 - 1.80 1.93 12.0 1.63 - 1.88 - 2.00 2.19 24.0 1.85 - 2.10 - 2.24 2.45 Return period (T), yr.** 10 12 15 *All values were obtained through subjective interpolation of isopluvial contours. **T = 1 P E , where P E is the exceedence probability. 1 25 25 Model Components and Operation: Program INFLUX The INFLUX program has been composed for this thesis with the expressed purpose of integrating the limited data base available for the mine site into the evaluationof storm-watershed response. It was the intention of the author that the physical characteristics of storm events be given fuller consideration, at least where the mathematical modeling was concerned. Precipitation As in the case of the methodology picked for determination of precipitation frequency values, an attempt was made to enlist a scheme for temporal distribution of rainfall which was founded on essentially valid statistical analysis. The Type II rainfall distribution developed by the SCS (Kent, 1973) was chosen due to its large data base and qualified recognition by the hydrologic community. Rainfall depth-duration relationships outlined in Weather Bureau technical papers (1953, 1954, 1956) were applied by the SCS to the analysis of cumulative rainfall and duration for recorded storms throughout the U.S. The resultant Type II curve represented the curve of best fit for the bulk of the continental United States, including all of Arizona. As can be discerned from Figure 1, the greatest 30-minute depth occurs near the middle of the 24-hour period. Because the selection of the period of maximum intensity was intentionally related to hydrologic design considerations, meterological relevance may not always be retained (Kent, 1973). 26 t7Z d / xd 1 1V.101. 01. Tit/AN IV a3ivintAmov ou_va 27 For purposes of modeling, the distribution has been broken down into 22 intervals of varying lengths. Any storm regardless of duration can be apportioned through time with the aid of this discretized Type II distribution. A sample distribution for a storm of 24-hour duration has been entered in Table. 2. Use of this distribution, in conjunction with the infiltration component which is discussed in the next section enables the investigator to determine both the rainfall excess and the duration of that effective rainfall. This is necessary if the effect of individualized storm rainfall intensity on sediment yield and subsequent pond performance is to be realized. An index of maximum storm rainfall intensity has been calculated as the ratio of the rainfall volume for the fifteenth increment to its corresponding duration. Its description as an index derives from the lack of actual influence it exercises over runoff and sediment production as will become evident later in this chapter. Infiltration A component infiltration model which relates infiltration rate to the availability of soil moisture storage has been applied to the INFLUX routine. Drawing on the prior work of Blumer (in prep.), an infiltration curve for the J-3 experimental watershed (see Figure 2)was utilized for determining that portion of storm precipitation which translated into runoff. The J-3 watershed is monitored for precipitation runoff, infiltration and sediment yield by the School of Renewable Resources, University of Arizona. The Blumer data, in lieu of sufficient 28 Table 2. Discretization of Type II rainfall distribution (1) for 24 hr. duration. Time (hrs) Time (pdf) (2) Precip. (pdf) (2) Time (cdf) (3) 0 2.0 4.0 6.0 7.0 8.0 8.5 9.0 9.5 9.75 10.0 10.5 11.0 11.5 11.75 12.0 12.5 13.0 13.5 14.0 16.0 20.0 24.0 0.000 .083 .084 .083 .042 .041 .021 .021 .021 .010 .011 .020 .021 .021 .010 .011 .021 .021 .020 .020 .084 .166 .167 0.000 .022 .026 .032 .020 .020 .013 .014 .016 .009 .009 .023 .031 .048 .104 .276 .072 .037 .027 .027 .060 .072 .048 0.000 .083 .167 .250 .292 .333 .354 .375 .396 .406 .417 .437 .458 .479 .489 .500 .521 .542 .562 .583 .667 .833 1.000 (1) from Kent (1973) (2) probability density function (3) cumulative distribution function Px/P24 (Ratio of accumulated rainfall to total) 0.000 .022 .048 .080 .100 .120 .133 .147 .163 .172 .181 .204 .235 .283 .387 .663 .735 .772 .799 .820 .880 .952 1.000 29 0 0 0.2 0.4 0.6 0.8 1.0 TIME, hours Fig. 2. Data points and infiltration curve for 0.5 year old spoil material, J-3 experimental area. (Blumer, in prep.) 30 documentation, was assumed to represent an average antecedent soil moisture condition for the watershed. Repeated attempts of fitting this data to established infiltration models (Huggins and Monke, 1966; Holtan 1961) proved futile owing to the uncharacteristically rapid decay displayed by the J-3 infiltration curve. Consequently, a tabular representation of infiltration rate vs. available soil moisture storage was opted for use in the computer routine. A listing of the discretized time-storage relations for infiltration can be found in Table 3. The interactive procedure involving the rainfall and infiltration components is now described. The reader is referred to the flowchart of Figure 3 for clarification during the ensuing discussion. At the outset of a storm run, an estimate of the initial available moisture volume for the topsoil unit is made. This unit is assumed to be underlain by a geologic stratum of greatly reduced permeability which effectively impedes the downward progress of infiltrated water. Upon saturation of the topsoil unit, additional precipitation influx is converted entirely to runoff. Available soil moisture was computed as the difference in stored water between saturation and the wilting point for plant life. Pressure potentials for these levels were assumed to be zero and -12 bars, respectively. Since the interarrival time for convective rainfall activity is generally short, it was felt that this lower bound for available soil moisture better reflected probable site conditions. incorporating volumetric water content values for Black Mesa spoil material developed by Fischer (1976), an available soil moisture storage volume of 1.8 inches of water was computed for an accompanying topsoil layer thickness of 6 inches. 31 ( START Read in parameters and initialize / Increment discretized rainfall Compute incremental rainfall volume and duration No Compute max. storm intensity No Set infiltration rate steady-state Yes • Determine infil. rate for computed deficit Calculate infiltrated volume Calculate infiltrated volume Updated moisture deficit Yes = Set infiltrated volume remaining storage Accumulated stored volume infil. rate infil. vol. Write Accumulate stored volume Set moisture deficit Accumulate rainfall excess and duration = Yes Write total rainfall excess and duration Construct triangular hydrograph Fig. 3. Generalized flowchart for hydrologic linkages. 32 Table 3. Time (hr.) 0-.10 .11-.20 .21-.30 .31-.40 .41-.50 .51-.60 .61-.70 ** .71-.80 .81-.90 .91-1.00 1.00 Discretization of J-3 infiltration capacity curve. Ave. Infiltration Rate for Interval (in/hr)* Infiltrated Volume (in.) 1.93 1.21 .76 .50 .36 .29 .25 .22 .22 .22 .22 * Using trapezoidal approximation for area determination ** Threshold for steady-state infiltration rate .21 .12 .08 .05 .04 .03 .02 .02** .02 .02 .02 33 Following initialization of the stored soil moisture variable, TFILL, the routine enters into a loop which calculates successive incremental values of rainfall volume, RAINV. After each iteration of RAINV, the infiltration rate corresponding to the present value of the soil moisture deficit (AVAIL-TFILL), is applied over the proper time increment, RAINPD. An interpolation factor, TERP, has also been included to better approximate the continuous decay process of infiltration. A check has been introduced at this juncture to determine whether or not sufficient storage has accumulated for the steady state infiltration value, SSINF, to be activated. As can be observed in Table 3, the steady-state infiltration rate corresponds to a cumulative infiltrated volume of approximately .55 inches of water. The entered value for SSINF is thus referred to if the computed soil moisture deficit falls below (1.8 - .55), or 1.25 inches. Next, the volume of infiltrated water for the interval, FILL, is added to the preceeding value of TFILL. This volume is equal to the product of RAINPD and either ACTFIL or SSINF, both of which represent infiltration rates for non-steady and steady state behavior, respectively. The updated value of TFILL is then used in evaluating the following iteration of rainfall. This procedure is repeated until the SSINF is attained, from whenceforth the infiltrated water is introduced at that rate and TFILL is set equal to AVAIL, thereby assuring maintenance of the steady-state condition. 34 Runoff Once the abstraction is satisfied, if there remains any effective rainfall for the increment, it accumulates as rainfall excess, TRAINX. In addition, the duration for any increment over which excess rainfall is generated is added to the value representing the duration of storm rainfall excess, expressed by the variable, DUREX. As TRAINX is actually the depth of water per unit area of the watershed which is available for transport overland, its extrapolation over the entire basin establishes the volume of total runoff delivered to the detention facility. Use of the DEPOSITS sedimentation routine, described at the end of this chapter, requires as an input the distribution of incoming flows to the pond. The triangular hydrograph method (Kent, 1973) used by the SCS for hydrologic design of conservation and drainage structures was chosen for this purpose because of its simplicity and applicability to ungaged watersheds. Limitations on its general use include a maximum drainage area of 2000 acres and average slopes of less than 30 percent. Calculation of the peak discharge from which constrUction of the inflow hydrograph.can•be accomplished is expressed by the equation: KAQ q= t where q = peak flow rate in cubic feet per second. K = watershed parameter, a function of hydrograph geometry A = watershed area in square miles Q = volume of rainfall excess in inches over duration D t = time from initiation of runoff to attainment of peak flow 35 The time to peak is closely related to the time of concentration for a watershed and is calculated by the following expression: D t = 2 where +L D = duration of rainfall excess in hours, and L = basin lag time in hours. The drainage basin lag time, L, is computed by the equation: .8 0.7 (S + 1) L= where 1900 Y 0 • 5 L = basin lag time in hours 1 = length of mainstream to farthest divide in feet, _ 1000 10 , CN CN = A retardance factor approximated by the curve number representing the watershed hydrologic soil cover complex, and Y = average slope of watershed in percent An empirical relationship derived from small watershed data describes the hydraulic length: 1 = 209a where 0.6 1 = hydraulic length in feet, and a = drainage area in acres When peak flow has been computed for an event, the program simu- lates construction of the triangular inflow hydrograph at a chosen time interval of .05 hours. The choice of this particular interval satisfied the minimum routing requirement of 5-10 time steps for the rising limb of the hydrograph for all of the storms examined. Two simple linear 36 expressions are necessary for hydrograph constructions: ORD(J) = PEAK/TPEAK x CUMIN(J), for the rising limb and ORD(J) = PEAK - (PEAK/1.67 x TPEAK) x (CUMIN(J) - TPEAK) ), for the receding limb where ORD(J) = the inflow hydrograph ordinate for the jth step in cfs, PEAK = peak flow rate in cubic feet per second, TPEAK = time to peak in hours, and CUMIN(J) = cumulative time at the jth step in hours. A graphical representation of the triangular hydrograph is presented in Figure 4. Sediment Since the primary objective of the study was to assess the effect of uncertainties in the physical characteristics of precipitation on sediment yield and pond performance, a desirable sediment yield model had to incorporate a certain degree of specificty with regard to these factors. To this end, the modified Universal Soil Loss Equation (USLE) assembled by Williams (1975) for determination of event based sediment yield was chosen. A hydrologically more specific formulation of the USLE, the modified equation is given as: . 56 xKxLSxCxP Y = 95x(Qxq) where Y = the event sediment yield in tons, Q = runoff volume in acre-feet q = peak flow rate in cfs K = soil erodibility factor, 37 _ 484 A(Q) A g ap L INCREMENT OF EXCESS RAINFLOW OR INFLOW D OUTFLOW HYDROGRAPH I- < TIME /ID Tp tbi Fig. 4. SOS triangular hydrograph. 38 LS = length-slope factor C = crop management factor, and P = erosion control practice factor The last four variables are equivalent to those utilized in the USLE and their values must be estimated according to the methods outlined by the SCS. Peak flow rate and runoff volume are obtained from earlier program components. The modified USLE resulted from experiments conducted on small watersheds in the Texas Blacklands which are also part of the semi-arid zone of the Western U.S. Uniform prediction accuracy was maximized in development of the equation. Predictive ability was found to be greater for larger storms than for smaller ones. This, however, coincides with the importance ascribed to larger storms in the production of sediment. Because the formulation was based on sediment yields and not gross erosion, use of the modified equation negates the requirement for application of a delivery ratio for the purpose of determining the transport efficiency of overland flow. Sedimentation Pond Design Upon completion of computer evaluation of the 10-yr., 24-hr. design storm event, sufficient information exists to enter the pond design process. A trapezoidal basin configuration has been chosen which, within the restrictions of the study, offered a simplified, yet not overly inaccurate, representation of actual pond geometries. 39 A detailed description of the design procedure is presented in the DEPOSITS design manual (Ward, Haan, and Tapp 1979), therefore, only highlights of the procedure are addressed here. The reader is referred to Appendix A which contains the final design aspects for the pond used in subsequent analysis. There are six basic steps involved in the design procedure used herein: (1) Determination of design storm characteristics including water and sediment volume and the accompanying inflow hydrograph. In addition, accumulated 3-yr. sediment storage volume must be computed using the USLE and a sediment delivery ratio. Due to difficulties in determining the sediment volume derived from gully erosion, that factor has been neglected. (2) Site selection based on surrounding topography, location with respect to disturbed area and active alluvial systems, and hydraulic design considerations. (Basin length, as measured from inlet to outlet, should equal or exceed twice the average basin width). (3) Preliminary design of dam embankment with provision for an emergency spillway and freeboard, and delineation of the prinipal spillway configuration. (4) Compilation of operating curves for the reservoir, specifically those relating reservoir stage to surface area and spillway discharge. 40 (5) Routing of the design storm through the reservoir using any established procedure- The DEPOSITS sedimentation routine was applied in this case. (6) Repetition of steps 2-5 until sufficient detention time has been achieved. Keeping with the practice of using established methods for actual pond design, inflow volume was computed with the aid of the SCS rainfallrunoff equation described by Kent (1973). The SCS equation is given as: where Q = accumulated direct runoff in inches P. = accumulated rainfall in inches I a = initial abstraction including surface storage, interception, and infiltration. S = potential maximum retention The initial abstraction has been empirically approximated as a fraction of the potential maximum retention by the relation: I a = .2S Therefore, the resultant expression for determination of runoff volume is: Q = (P - .2S) (P + .8S) 2 A great deal of freedom has been allowed by the regulatory agency in working out the particulars of pond design. Prudent 41 engineering practice is relied upon to minimize inefficiencies in hydraulic behavior, consequently providing a maximum of design flexibility. Some assumptions adopted in the process of modeling the hydraulic behavior of the dewatering system used for pond simulation should be stated. A perforated pipe spillway was employed because of the ease it exhibited in achieving adequate detention times for routed basin inflows. Characteristics of the structure include a corrugated metal riser and two sets of circular perforations comprised of three perforations per set, each perforation measuring two inches in diameter. Three hydrau- lic conditions are assumed to adequately describe flow through the principle spillway. Initially, as the reservoir stage exceeds that corresponding to the successive dewatering sets, the discharge can be described by the orifice flow equation: = Ca (2gH) where 05 Q = discharge in cubic feet per second, C = orifice discharge coefficient, assumed = .60, a = cross-sectional area of orifice in square feet, g = acceleration due to gravity in feet per second squared, and H = head on the orifice, measured from the orifice center to reservoir water level, in feet. When water level adjacent to the riser transcends the spillway crest elevation, weir flow ensues. Morris and Wiggert (1972) suggest use of the following equation for description of this condition: 42 1/2 Q= where a(2gH) (1 +K+K+ K L ) 1/2 e b c H = head on conduit outlet measured from the reservoir level to six-tenths the conduit diameter above the invert. K e = entrance loss coefficient, Kb = correction factor for energy losses in bends, and K c = friction factor The pipe flow values were extraced from Table 5.3 of the DEPOSITS user's manual (Ward et al.,1979) which presents discharge values as a function of conduit diameter, head, and conduit length for (K e + K b ) = 1.0. As is true of larger impoundment structures, the hydraulically active portion of the pond excludes that volume which must be allocated for deposited sediment, referred to as "dead storage." Some of the design details affecting hydraulic performance have been set out in the regulatory statutes, highlighted in Chapter 2, however, others such as positioning of the spillway and maintainance of minimum depths or permanent pool volumes have been neglected. The accumulations of further data on actual and simulated pond performance may expectedly lead to amendments to the current criteria covering pond design. To enable relative differentiation between storm characteristics, and their effect on pond performance, maintainance of a baseline condition for the pond was essential. Established federal statutes relating to pond design and effluent limitations convinced the author that a "critical" condition is defined by the following elements: (1) a dead storage equal to 60 percent of the calculated 3-year sediment 43 accumulation corresponding to the specified cleanout level for the pond; and (2) a permanent pool consisting of the volumetric difference between the cleanout level and that of the first orifice set. A graphic representation of general pond features is presented in Figure 5. DEPOSITS Sedimentation Model The DEPOSITS sedimentation routine (Ward et al.,1977b) is a mathematical model used to describe the transport and deposition of sediment delivered to and routed through a sedimentation pond. Impetus for model development came mainly from the desire to provide a means with which the user could more adequately assess the prospective performance of sedimentation ponds, and as a gage to weigh the necessity of additional or alternative methods of sediment control. The model has been verified using data from 11 functioning ponds and was found to explain greater than 90 percent of the variation in basin trap efficiency. Flow within the pond is described in terms of the idealized plug flow concept. This assumes that no mixing takes place between plugs and that each successive plug entering the pond assumes the position maintained by its immediate predecessor. Although it simulates basin performance, the model does not pretend to describe the complexities of actual hydraulic behavior in the basin. The sedimentation process defined in the model can be elucidated by tracing the movement of a sediment-laden plug of inflow through the basin. Upon entering the pond, the plug is assumed to possess a specified sediment distribution with depth. Furthermore, each plug is subdivided into four layers at 0.125, 0.375, 0.625, and 0.875 of the 44 La Lu o >0 Lu < tx o co 0 I— E ww 0 (r) I. O I. (,) >> 45 average flow depth. As the plug progresses, fall velocities required for particles to reach these distances are computed as the depth traversed divided by the detention time for the plug. Particle diameters corresponding to the computed fall velocities are then determined by applying Stokes Law of Ideal Settling: D where .5 V x 51.5 x (SG -1) D = particle diameter in millimeters, V = corrected fall velocity in feet per hour, = water viscosity in centimeters squared per second SG = particle specific gravity, and 51.5 is equal to 0.8 times the gravitational acceleration (32.3 ft/sec) times a conversion factor to achieve equation dimensionality. The correction factor of 0.8 compensates for the effect of non-spherical particles on settling theory. The proportion of sediment remaining in any layer of the plug is subject to the law of continuity: I - 0 = ds — dt where I = mass of incoming sediment 0 = mass of outgoing sediment dl= differential of mass of stored sediment with respect dt to time Deposition occurs and is assumed irreversible as soon as a particle reaches the reservoir bed. 46 When the plug is discharged, its sediment concentration is thus dependent not only on the withdrawal characteristics employed, but also on the detention time and the redistributed sediment profile within the plug. A graphic conceptualization of the plug flow routing process is presented in Figure 6. Required inputs to the DEPOSITS model are readily available and are minimally dependent on in-field evaluation: 1. Inflow hydrograph. 2. Viscosity of the flow. 3. Stage-area curve for the basin. 4. Stage-discharge curve for the basin. 5. Stage-discharge distribution curve. 6. Degree of dead storage or short circuiting. 7. Sediment inflow graph or load. 8. Particle size distribution and specific gravity of the suspened sediment. Stage, as referred to in the model, is the depth of water above the lowest level on the basin bed. A uniform outflow rate with depth is assumed by the model if a stage-discharge distribution curve for the basin is not specified. If sediment distribution data is lacking, sediment concentration is made proportional to the water inflow rate. For effluent concentrations to be determined, the total incoming sediment load must be inputed. In addition, the model has the capability to simulate changes in basin geometry resulting from deposition during the event. This makes 47 o SAO 31V2:1 MO 1 A 48 it especially desirable from the standpoint of prospective time series analysis of hydrologic events and corresponding pond performance. A caveat should be inserted here concerning the computation of detention time in the DEPOSITS routine. As is required by the regulatory statutes, detention time is calculated as the time between the centers of mass of the inflow and outflow hydrographs and is represented by the program variable, CENTME. In situations where a permanent pool exists, which remains as storage after dewatering, the computed centroidal detention time will only approximate the average theoretical detention time for the storm event. This is due to the fact that the detention time for the volume of stored flow discharged during the routing process has been maintained for an extended period of time. The DEPOSITS routine has included another measure of detention time which gives special consideration to the permanent pool volume, identified in the program as the variable STRMTM. Because of the complexity and sheer bulk of the DEPOSITS sedimentation model responsibility for a more detailed explanation of program operation has been delegated to the DEPOSITS Design Manual (Ward et al., 1979). CHAPTER 4 RESULTS AND DISCUSSION The following pages document the results of model runs for the Black Mesa hypothetical watershed and companion sedimentation pond. A discussion addressing the implications of hydrologic uncertainties on pond performance is then offered. The chapter ends with some thoughts on model adaptability and regional bias. Pond Sensitivity Analysis Prior to initiation of the present study, the author, along with his colleagues, expected that only one watershed condition would need be examined in order to assess the effect of hydrologic variability on pond performance. This, as the study unfolded, turned out not to be the case. To, in effect, unmask the hydrologic uncertainties as they affected the efficacy of basin performance, two additional sets of runs had to be made. Thus, the following modeling schemes were investigated: (1) minespoil material with untreated pond inflow, (2) natural soil material with untreated pond inflow, and (3) minespoil material with chemically treated pond inflow. The reader is directed to Appendix B for a sample listing of required DEPOSITS input parameters and their associated values. 49 50 Minespoil Material with Untreated Pond Inflow A total of 38 precipitation events encompassing varying frequency-duration relationships were evaluated for this condition using the INFLUX and DEPOSITS models. Peak effluent sediment concentra- tions resulting from routing the specified event flows through the pond are listed along with precipitation characteristics in Tables 4 and 5, while sediment yields for all conditions simulated are compiled in Tables 9 and 10, pages 64 and 65. Since the Williams equation (1975) for event-based sediment yield was used in generating incoming sediment loads, estimates had to be made for the equation's variables corresponding to the proper siteinflow conditions. These values were based on projected 3-yr. averages as follows: K = 0.35, LS = 1.26, C = 0.63, P = 0.35. The estimated crop management factor (C) value of 0.63 represents an assumption that during the first year no vegetative growth occurred, while in the second and third years, a meager 10 percent cover was established. Justification for the remaining variable values listed can be found in Appendix A covering pond design. On first inspection, these values may appear low, however, it must be remembered that irrigation has been neglected and natural rainfall is limiting. The distribution used in apportioning incoming sediment is equivalent to that utilized in the pond design process and appears in Appendix A. Data presented in Tables 4 and 5 suggest that pond performance is linked less to rainfall volume than to its intensity, represented by 51 0 Co Cl 7:1 cU 4-1 4-1 cd di 4-• 0 co Cl CU 4-1 CJ CL) 0 C11 0 CIO CO nr) Ce) -X c•-4 Ce) CO -X so C11 Lin ce) Ln 0") co cn c0 ce) cn r-, .1- CO 01 CO -;--. Nj 1/40 al CO 0 c•I Co Q Q N. hCO 10 r -1 r. 1/1 Ce) n.o -X -X (041 cf-) cf) cn L.0 C.) 0 0 CU 0 Q 4-1 0 4 0 .6-+ •,1 Cl (1) cr) 0 -0 0)0) Co 4-J ,"-:•• 4-1 E 0.) 14-1 C/G (1) G-1 •• c-‘) CO o..z cr) CO O '% E 0 no Ccl CT1 CA co c-s) s.0 CO N. 01 0 Ln r-1 CA CO CA (Ni ... CO 1 -1 01 0 co un Ce) .1- 0 CN1 NI r-1 ce) 1-n Ce) Cr, co 0 Cr) r•-• C•1 r-1 CA C Cr") 1--1 Le-1 (-.1 v-1 431 co C CN1 Ill a, c*, ) CN) C•1 Gr, cG Co 1-41 Cl a) 0 1.1 •1-1 cd a - G1 0)4-J u )-; CoX a) I Ci Co ci) 0 4-) c.) cd -G o•N un CN .0 N. Co Le) CA NI t-4 1-1 1/4.0 CT1 C1.1 CO 0 N un 4-1 CO 1/40 1/4.0 CO CO 0 Ce) E 4-3 Cl Cl cd CL) 0 •,-4 4-J (71 4-1 Z • Cl C71 a. 4 Cl .1-1 C.) • $.4 4-3 Cl Cl I— Cl 1-1 -ri ai Ln Co a) Ci 0 4-J 0 1-4 Co Ce) L11 01 c'n 0 Cr) .0 • ,-I Ln ,,43 .0 C11 0•L s.0 0 0 0 1-1 ;-• -G CA CO . r-1 Q Cl 0 h, L.r) N- crn cn N.J cn 0 0 0 r-1 r-1 uN 0)0) 0 P:1 4-) "0 Cl 4-) 0 1-1 4-) 14-1 04 0 .1-4 C.) 0)7-1 0 f:1-1 14-1 W . Tl -0 0 0 a. .LJ 0 r.z.) 4 N. te) 0 1-1 CA ul Cl I I I 4-1 1 -1 1 -1 >1 >1 1-1 >, • I C) L-1 W 4 Cl0 W . W • W 4 4 4 t -i • CsJ I I 1-1 1-1 w 4 W. 4 C•I . 1/4.0 1-1 CN1 I I I 4 N. r-I In NI • • W .0 tin • W 4 4 Cl ,-C N ,--I ln C.1 0 1-el 1 1 $-1 r-1 • CA • 1 I 1 1 1 >1 >1 >1 1 1 1 CL) r-I CO cr• tri O0) 4-) cil 4-1 Ln Ln in 3-4 1-1 >1 Ln un ln >1 CO CO CO CO 1-1 >1 ••1 >, C 0 tri 0 0 ri ri 0 0 ri 4 tri 52 $.4 a) :: 0 '10 a) 0 4-1 Ca ri › ..1 1-1 0 4-1 C.1 0 ,--4 Ca 4../ • 0 .0 0 4-1 1-4 a. 4.J CU z •ri 0 P . Q3 -C1 )-I 04-J ri CD 4-J-r -4 c0 -0 4-1 .1-1 ,--I 0.-4 "Cl g .1-1 Cd C.) 4-i (1) g 0 4.4 P. 0 0 Cl) 1-_4 1-1 ID) >1 4-1 CO 0 0' 4-1 g Q) 0 r-1 4-1 44 0 W a. cd 44 cd r. C.) -0 0 0 = .7) g g 0 0 -,--i 0 4- 1 0 40 -,-I -4 0 1-1 4-1 0 .0 •,-1 $4 4-1 • (f) 1- g .4-JO _4 al -H 4 F-1 4.1 1-1 4-2 '0 ri "0 4-4Q) 01:. CD 0 NO ”-I c.) CO ri 1-1 P. 7, 0E-4 •,-1 4-1 Cf) cci C..) Q) ci) _Q) En 0) I.) 4-J4 4.+ 4- ) al -1: u —-'. -H W c.) CO LI-1 O -cl a) w 0 fa.) 4-1 -0 Cl ct › QI 4.) QJ I)) z ic 0 0 Q1 •,-1 1--44-J 1:2.4-4 Q)0 G4 ,—I 0. E1--i `,. 4a) 4J C)) al ,o W 0 c.i ID) a) 0 c.) 1-1 -,-1 4-1 .L.J cd 3-1 4-1 CCI ••-I 0. 1:. -7- 4 cd 4-J a Q) -40 0.'-1 CO -‹ Q) r1 (t N4-4 4-_4 ca )4 ID) CO 1-1 Ca Mt 4-3 Cl 'OC) Q) 14 11) 4../ —.4 Q) /-1 0. <O 4-4 ri • • • • ▪ 53 cn G cU O +.1 .r-I cd 4-) a) cd 4.: 4c ic4(.x 4C 4'. 4.: •X 4: N. s.0 cr) N. 01 CV CV Cr1 CI1 n--1 ,.0 0 Cn 0 al k.0 CO ...14 . Cr) CV %.0 Cr) 0 C1I V) ....1- V) CO 0 ri CO 0 ri 1-1 01 CO 01 01 ‘.0 01 01 0 ,./D ....1* Cr) CV -..1- ri VO ..1- Ce) Ce) CV i-1 r--1 4-) G G 0 c.) 4 G 4.4 O .r4 cJ 4.) G •*-1 C) 0 1-1 ai "Li cl) G cn .0 .0 4-1 G CO L4-1 • 0 ul rl ON ce) 0 ce) CO N. ri N. 1.11 CO %.0 ce) r-I cr.% Q).. • on Ln co Cr. 01 CV If) 0-1 N. ce) tr) CO Q c\ I Ln a, 0 .0 if) 01 ol .0 Ln cc) on c.1 c.1 di Ln 0 • CV 0 Cr) on cN CV CN '4-40 L4-1 (1) C) ci a) G • 1-1 ^0 4-1 cU 4-1 CD >1 (N tr) 014 CV "0 I g CN 0 ri CO CO s..0 CO N. 01 CV N. Ce) CO CO N. N. CO u.0 s.0 Cr) 0 (N 1-1 11) 111 1-1 Ce) N. CO 0 0 lx) uN ON N. if) (N Cr) CO N. N.ce) CO N. u") ce) 1-1 (N • crt 0 tr) Cr) CV CO (N •• C/1 E 4-1 1.4 Cf) 0 .1-1 4-1 1-i CC) Cl) U cl: (.) c1) Q)QJ • Z 4-1 s-0 ri Cr) 14. 1 Oin Ln N. C1 CV if1 N. 0 • • 0 0 0 0 0 CV CO 0 0 -4 Cr) C, ") 0 Ce) CS) V) CN cn CO Q CV • • • n-1 cN1 CN1 c.1 cN1 •-1 (J c.) 1-1 O O pO . 4-1 "0 0 c1 CL) 4-1 4-4 g g fa. 0 **-1 1-1 L) P "0 a) 14 G $-1 0 0 P4 44 PLI • P 4 4 1-4 4 P . 4.4 ...1 4 1-1 .4 4 P )-1 )-1 P 0 4 4 4 N. Ln 0 4 N. Ln 0 -0 -G 4 1.r) c.1 --.1^ c \I Ln ,--1 n--I cNi in 4 4;-4 '.4 - I I 1 1.4 4-1 ?, P., P. ›, c•I n-1 I (N 4 ri CN %.0 ri C, 4 v-I I - I 1 >, ?, 1 I I 1-1 >1 1-1 ›, I IrLrl Ir) 1-41 1-1 ri ri ri • ri C1I ...? CV s.0 ri CV I ›, ).4 1-11 -14 -44-44-4 P., P., P.. P., P. in Ir) CV 1 u-1 I Le) CV I I I in I P 4 -G 1.r) If 54 the aforementioned intensity index. This index, as previously defined, represents the ratio of the rainfall depth to duration for the critical intensity index. This index, as previously defined, represents the ratio of the rainfall depth to duration for the critical fifteenth time increment of the discretized SCS Type II rainfall distribution. The standard rainfall intensity expressed as the rainfall rate in inches/hr. over the corresponding time period was felt to be too cumbersome for comparative purposes. Consequently, the cited intensity index was chosen in its stead. Readers are cautioned not to confuse the two concepts, lest unwarranted protests ensue. Tracing causal connections, it becomes evident that the link between intensity and pond performance is due to the ability of short duration-high intensity storms to generate relatively large amounts of sediment accompanied by high peak discharge rates and short inflow hy- drograph base times. Examination of successively routed plugs through the reservoir indicates an accelerated introduction of the plug corresponding to the observed peak inflow rate and peak influent sediment concentration. Because the shortened time base of the inflow hydrograph, this rapidly introduced plug affects a greatly reduced detention time which is responsible for the higher peak effluent sediment concentrations simulated by the model. Low intensity-longer duration storms, on the other hand, display the attenuated inflow hydrograph characteristics which contribute to the attainment of increased plug detention periods, especially for the plug associated with peak inflow rate and sediment concentration. 55 In both cases, the clay fraction was responsible for the bulk of that sediment extant in the pond effluent. There was, however, a greater percentage of silt-sized particles in the effluent of simulated low intensity-longer duration events. Although an apparent inconsistency, this appears to accrue from the difference in discharge characteristics associated with the two storm types. The greater volume of stormflow produced by the low intensity-extended duration events results in an increased time period over which higher stage levels and subsequent discharge rates are registered. Since the increased range of depths associated with these events now encompasses both dewatering orifice sets, relatively greater plug detention times are offset by the increased settling depths which must be traversed by entrained particles to avoid incorporation into the pond effluent. Another aspect of data listed in Tables 4 and 5 which merits attention is the gulf which separates the peak effluent concentrations computed for all the events modeled and the current OSM-EPA effluent water quality standard of 70 mg/l. This is attributable to two interrelated factors. Coincidental with the required 24-hr. theoretical detention time is the notion that sedimentation ponds can only be depended upon to remove sediment corresponding to minimum particle size of 20 g (0.02 mm). Corresponding to the middle of the silt sized particle range, this lower limit precludes the maintainance of high trap efficiencies for watershed soils with a high proportion of particles residing in the clay and lower silt fractions. Thus, ponds 56 designed according to the federal guidelines cannot be expected to even remotely approach Federal effluent limitations where these conditions are present. In an effort to clarify the projected effect storm characteristics have on the actual attainment of pond effluent standards, it was necessary to negate the overriding influence of the soil particle size distribution on simulated pond performance. A sensitivity analysis was conducted on pond peak effluent concentrations to determine the size fraction distribution and crop management factor value which when inputed would enable differentiation between storms that successfully achieved water quality standards and those which failed. The results of this analysis are shown in Figure 7. A clear distinction can now be made between the two storm regimes studied. Inspection of Tables 4 and 5, listing storm characteristics and peak effluent concentrations from which Figure 7 was derived, provides further evidence of the critical nature of high intensity-short duration storms with regard to pond performance. For the particle size distribution and "C" factor value noted in Figure 7, intensity index (PINTMX) values in excess of 40 in/hr. resulted, for all but one case, in a failure to meet the 70 mg/1 standard. Conversely, all modeled events which were calculated to have intensity index values less than 40 in/hr. satisfied the requirement. The crop management factor value used represented cover conditions which in the opinion of the study advisers could exist only under irrigated conditions. Even for these conditions, the resulting particle size distribution would in reality be unattainable. 57 The most obvious departure the data exhibit from the stated OSM performance criteria relates to the water quality exemption for storms possessing proven generated inflow volumes in excess of that produced by the applicable 10 yr.-24 hr. event. The demarcation of event concentrations represented by the vertical line in Fig. 7 suggests a marked preference for the exempted stormf lows in attaining effluent sediment concentration standards. Moreover, a substantial number of storms which exhibited high effluent concentrations spawned only nominal inflow volumes. National Soil Material with Untreated Pond Inflow Because of the overwhelming failure of all routed stormflows in achieving federal water quality statutes, modeling of a control situation for comparative purposes was viewed appropriate. All factor values included in the sediment yield prediction equation, with the exception of the "C" factor, were left unchanged for condition 2 model runs. The "C" value chosen, 0.09, correspond to a cover percentage of 40, describing a vegetal mix of grassy surface and limited canopy. In addition, the particle size distribution calculated for the incoming sediment was derived from data for natural experimental watersheds located at Black Mesa. A tabulation of this data appears in Table 6. Generally, similar observations can be made in viewing natural condition data as for those concerning untreated minespoil conditions. Although peak effluent sediment concentrations are somewhat lower than those resulting from minespoil simulation, they still exceed the 58 90.0 PARTICLE SIZE DISTRIBUTION: 80.0 <.002 mm = 0 % .002 mm 5- X 5 .063 mm = 5 % .063mm <X 5-.125 mm =87% >.125 mm = 8 % 70.0 Crop management factor = .09 60.0 I, 111.3 102.2 100 50.0 • 94.4 0. q 90 >F— ET) 40.0 80 70 LLI 1— Z 30.0 ca.; 60 50 40 20.0 • • 40.4 44: 1 10.0 0.0 0.0 3170 493 1.0 2.0 3.0 4.0 5.0 INFLOW VOLUME, AC.-FT. Fig. 7. Predicted peak effluent concentrations and contours in mg/2. for Black Mesa minespoil with altered inputs and untreated pond inflow- 59 Table 6. Particle size distributions for undisturbed experimental watersheds: Black Mesa, AZ. Watershed Event Date * * %Clay%Silt * * %V.f.Sand%Sand 7-11-77 14.6 62.0 12.1 11.3 8-12-77 22.7 32.0 32.6 12.7 8-15-77 40.6 36.4 18.5 4.5 8-15-77 16.7 49.7 27.5 6.1 8-15-77 36.9 29.0 28.4 5.7 8-12-77 37.6 30.8 22.2 9.4 8-7-77 32.4 39.1 19.1 9.4 J-3 Natural J-7 Natural 8-12-77 13.4 6.7 33.1 46.8 8-15-77 16.2 33.9 29.8 20.1 8-15-77 27.7 43.0 14.2 15.1 8-17-77 42.2 38.0 9.4 10.4 8-17-77 37.3 20.8 23.4 18.5 7-22-77** 47.1 31.9 13.0 8.0 8-5-77** 51.6 17.3 7.6 23.5 8-16-77** 71.5 5.5 17.6 5.4 28.2 35.1 22.5 14.2 Average fraction %: *clay: <.002 mm .002 mm x < .063 mm silt: v.f. sand: .063 mm < x < .125 mm sand: >.125 mm **assumed outliers 60 effluent standard by two orders of magnitude. The precipitation characteristics were unaltered for those runs, therefore, it is not surprising that the previously cited tendencies relating storm characteristics to pond performance are again evident. A listing of effluent concentrations can be found in Table 7. The question which begs attention here is: given the magnitude of sediment concentrations in runoff generated under natural conditions, why should sediment concentrations in runoff from disturbed areas be required to register at levels corresponding to two orders of magnitude less? Rationale for such a restriction seems to derive more from difficulties inherent in determining ambient stream sediment concentrations than from any conceptual analysis of the hydraulic regime. Even a cursory review of current sediment transport theory reveals the longaccepted principle that a stream-hillslope system will strive towards maintenance of a dynamic equilibrium between the supply of sediment and the stream's capacity to transport it. Thus, it appears conceivable that the high quality water discharged from sedimentation ponds into streams or appurtenant drainageways carrying natural runoff could actually lead to downstream scouring which in turn could result in resuspension of previously deposited channel material. Acceptance of Federal rationale aside, the inadvertant distortion of the existing hydrologic regime in this manner seems a distinct possibility. Minespoil Material with Chemically Treated Pond Inflow A selected group of representative storms was simulated for minespoil conditions and the introduction of a cationic polyelectrolyte • ▪ • o • • ▪ • • 61 Ci c.n 0 461 CO r-1 1-r1 0 0 1-r) (T 4-1 -0- CO 01 c43 V) 04 n.0 CO 1/40 c,44 4-1 4-1 tr)01 (71 4- 0 0itcv s.0 ce) u") O cr, r-- 4-) cv -.I- (' ) cv Lc) Cr) CV CA rk rk rki VD 0 C'n CO 4.4-4 COO CV CN1 Cr) (.31 CA r-- c0 r-- I-I Cr) CA rk (1) 0 46-4 CO cl aJ k 0 In • -o Ci 0 $.4 k • ,.= ,.=1-4 ..ckl ,a cd o 4-4 4-1 o 1 4 -1 k -Q r-- ,--i in cv I.; 0 LC i kl kl .= ,.= •-a • 44-4 c.1 , 4-4-1 s-i k .0 0 S-I $.4 , .-- }-; .= W ,.= 4-1 CV ,.0 4-1 4 CV -0- r-4 c*44 i I I i I i I kl ›N k 4-1 k ›, kl 4..1 >1 k Ln CV I I I I I I I kl >1 k 4-4 k k >1 4-1 >1 kl k >1 CA ri 4 ..0 I >1 • 4-, 4 cr-4 cv Ln in ii-) in if-) Lc) Li-L ri In ri Lin 4-1 4-1 4-1 4-1 4---1 ri ri CV CV Lc) L.r) CV Li-) CV c‘l -H CO O 0 -0 0 ca )4 -0 4_i CI O 4-1 Ci ra O O r..) 4.4 C1.4 E C) )-1 4-i u CO 0 4-4 4-1 •Ci 4-.1 E (1.1 4-41 CO 0 41-4 CI) L0 CO Clco 0 444-1 4.4 (1) .1-44 0 ) - 1 Cr‘ cn co Ln re) Cr) • C) co tr) co cD co L.r) sz) n0 O CA C•4 ‘--1 CO 01 O O Cr crN 41-1ce) 4-1 4-4 Ci t-4-4 U C44 0 c-V In CO CV 4-1 -0-cn (-A Ln cv L.0 In cr4 n.0 00 cv 0 Ci P -1 O r-i 4-4 4-4 4-4 0.1 E 0 Ci 0 o 4-J r-1 "Cl -4-4 4-4 4-i P-1 O al 4.1 4-4 -C 4-4 • $-4 .0 ..0 $.4 w • kl 4-1 4-1 k .0 -0 .0 .0 C1I , 0 0 r-- ri Ln CA 0 In .0 (1) 77 • • • 4-1 › Cr.3 I U 111 ..1 a) 00 4-4 4 -1 .k ›N >1 cia a) 4_i v-L Ln Ln k >-n Ln CV L.0 ,--1 ..t cv 4-4 4 ..4 4_ : ..4 4-4 .0 .0 .0 • 0 .0 .0 4--- Ln O ,t1 N- rk C1I in ,-i ,--I in cv 0 $11 .4.C -I .ti .L. ,--I cv n.0 Li-, 1111111111111111 k ›N Ln kl LE) 4-1 ›, in kl kl kl Ln Ln 00 4.1 P', CO k >1 00 1- 1 4--1 CO k >1 0 ,-i 4-1 ›, 0 n-i k ›N k ki 0 r-I 0 ,-1 0 ,--1 k ›, 0 ,-1 62 into the pond influent. The addition of a flocculant of this type affects a change in the effective particle size distribution which defines the settling characteristics of incoming sediment. Actual determination of the effects of a coagulant or flocculant on particle size distributions should be based on lab experimentation. Explanation of this procedure is presented in Ward et al. (1979). For study purposes, and estimate of the flocculant effect was made as a result of conversations the author had with Rick Ellwagner (1980), a sales representative for the Tucson office of American Cyanamid. These discussions produced the following estimates: clay fraction -> reduced to 0.1% silt fraction -> effective size increased to 0.1 mm. The value listed for the unaffected clay fraction percentage is a conservative one, and should produce equally conservative peak effluent concentrations. The amount of flocculant required to produce this change was quoted to the author at 0.1 lb./ton of solids at a cost of $.60/1b. Results for scheme 3 runs appear in Table 8. Pond trap efficiency for all routed events was extremely high, on the order of 99.9%. Only one of the events resulted in abrogation of the effluent standard. For the above mentioned rate of application and per pound cost of flocculant, the total cost for treatment of an event which generates on incoming sediment load of 30 tons is approximately 63 Table 8. Predicted peak effluent sediment concentrations for routed, selected Black Mesa storms l : minespoil with chemical treatment of inflow. 2 Storm Event, Peak Effluent Sediment frequency-duration Concentration, mg/), ' 2 5 yr. - 1 hr. 53.5 8 yr. - .50 hr. 63.7 10 yr. - 2 hr. 44.3 10 yr. - 24 hr. 46.8 15 yr. - .17 hr. 112.2 25 yr. - .50 hr. 65.8 25 yr. - 24 hr. 40.1 Event sediment yields appear in Tables 9 and 10. Estimated effective particle size distribution: < .002 mm = .1% > .1 mm = 99.9% Crop management factor, C = .63 Precipitation characteristics for all storms appear in Tables 4 and 5. 64 Table 9. Predicted event sediment yield for simulated conditions at Black Mesa, AZ.: 5-10 yr. return periods. 1 Storm Event frequency-duration Event Sediment Yield, tons condition 1 2 5 yr. - .17 hr. 88.5 12.6 5 yr. - .25 hr. 112.7 16.1 5 yr. - .50 hr. 133.5 19.1 5 yr. - 1 hr. 157.7 22.5 5 yr. - 2 hr. 132.0 18.0 5 yr. - 6 hr. 125.5 17.9 5 yr. - 12 hr. 121.7 17.4 5 yr. - 24 hr. 113.5 16.2 8 yr. - .17 hr. 101.8 14.5 8 yr. - .25 hr. 126.9 18.1 8 yr. - .50 hr. 161.4 23.1 8 yr. - 1 hr. 186.3 26.6 10 yr. - .17 hr. 110.9 15.8 10 yr. - .25 hr. 138.9 19.8 10 yr. - .50 hr. 174.8 25.0 10 yr. - 1 hr. 197.7 28.2 10 yr. - 2 hr. 170.7 24.4 10 yr. - 6 hr. 153.4 21.9 10 yr. - 12 hr. 136.8 19.5 10 yr. - 24 hr. 137.2 19.6 lYields for condition 3 are equivalent to those cited for condition 1, unaltered. Yields for condition 2 are equivalent to those cited for condition 1, altered 2 Minespoil material without treatment of inflow for original and altered inputs, respectively. 65 Table 10. Predicted event sediment yield for simulated contitions at Black Mesa, AZ: 12-25 yr. return periods.* Storm Event frequency-duration Event Sediment Yield, tons condition 1 12 yr. - .17 hr 114.0 16.3 12 yr. - .25 hr. 141.9 20.3 12 yr. - .50 hr. 180.2 25.7 12 yr. - 1 hr. 202.2 28.9 15 yr. - .17 hr. 122.3 17.5 15 yr. - .25 hr. 153.9 22.0 15 yr. - .50 hr. 193.8 27.7 15 yr. - 1 hr. 218.0 31.1 15 yr. - 2 hr. 190.4 27.2 15 yr. - 6 hr. 166.1 23.7 15 yr. - 12 hr. 139.0 19.9 15 yr. - 24 hr. 150.6 21.5 25 yr. - .50 hr. 218.5 31.2 25 yr. - 1 hr. 237.8 34.0 25 yr. - 2 hr. 190.3 27.2 25 yr. - 6 hr. 158.2 22.6 25 yr. - 12 hr. 159.6 22.8 25 yr. - 24 hr. 144.4 20.6 *Footnotes are equivalent to those cited in Table 9. 66 $2.00/event. Initial capital investment to cover purchase of the application mechanism would be the only significant additional cost required. The resultant reduction or elimination of pollution fines would accelerate the expected amortization of this expenditure. It can therefore be inferred that under the conditions applied in this investigation, the addition of chemical flocculants is absolutely necessary to approach a no-risk situation for fully contained (no emergency spillway overflow) pond inflows. Of course, federal regulatory policy has rarely, if ever, been directed towards a total elimination of risk. The next few paragraphs address the consequences of hydrologic uncertainty for pond performance. Hydrologic Uncertainty and Implications for Pond Performance In assessing the uncertainty in modeling any natural phenomena, three sources must be considered: (1) uncertainty in model choice, (2) sample uncertainty, and (3) imperfect understanding of the physical process itself. Of the three, only the first two are partially controllable by the modeler. The models used for rainfall distribution and sediment yield are both indicative of the uncertainty involved in model selection. It is entirely possible that the SCS rainfall distribution scheme utilized in the determination of rainfall excess fails to adequately describe the temporal characteristics of southwestern convective storms. Other distributions are available which differ in the timing and extent 67 of the high intensity burst exhibited by observed storms. This could have a significant effect on production of runoff and sediment yield, because of the effects of varied intensities on infiltration rates and satisfaction of prevailing soil moisture deficits. At best, these projected scenarios would only slightly reduce the measured pond effluent concentrations, for their effects would be damped by the persistence of the large clay fraction. Another model application providing a source of uncertainty for the study is that of the modified USLE (Williams, 1975). George Foster, a hydraulic engineer with the U. S. Department of Agriculture, who specializes in the use of soil loss equations, has stated that Williams' (1975) formulation may not perform well in situations where raindrop impact accounts for a significant portion of soil erosivity, since this factor is neglected in Williams' equation (oral communication 1980). However, sediment yields computed via Williams' (1975) equation are well within the range of 3-4 tons/acre observed by members of the University of Arizona research team at Black Mesa (Fogel, 1980). Model uncertainty also enters into consideration in the case of the DEPOSITS sedimenation model (Ward et al.,1977b). As acknowledged by its developers, the plug flow concept used for the routing process is an imperfect device for modeling actual basin hydraulic and sedimentation processes. The authors feel that a partial mixing model would provide a more accurate description of pond performance but its comparable complexity would be substantial. Inclusion of a partial 68 mixing model could be expected to result in no more than a moderate reduction in simulated peak effluent concentrations because of the mixing which would take place between incoming sediment-laden plugs and the better clarified water stored in the permanent pool. Differences in the relationships describing Black Mesa sediment yields for the present study and previous work by Fogel et al. (1979) exemplify the uncertainty involved in the use of sampled data. Limited data utilized in the prior study suggested a linear relationship between event sediment yield and the product of runoff volume and peak flow. This study, however, employs the non-linear relation between the aforementioned variables cited by Williams (1975). Both the uncertainty inherent in the limited amount of data available to Fogel et al. (1979) and that residing in the infiltration data used herein make determination of the actual sediment yield relationship difficult. Retention of the linear relation for sediment yield computation in this investigation would have led to inordinately high sediment yields and correspondingly high effluent sediment concentrations. Due to the lack of adequate data, the non-linear sediment yield relationship was assumed to satisfactorily represent existing conditions at Black Mesa. Uncertainty due to an imperfect understanding of the physical phenomena is extreme for the examined processes linking rainfall with erosion sediment transport and reservoir sedimentation. It must be remembered that the precipitation events modeled in the study are relevant in the statistical sense. That is, their occurrence is not an established certainty. An idea of this variability is provided 69 by computation of the probability associated with at least one 5 yr. return period storm occurring in the next 10 years: Assuming independence of annual rainfall and a probability of exceedance, p, equal to the reciprocal of the return period: P E = 1/T = 0.20 For a geometric distribution: p (at least one 5 yr. storm occurs in 10 yrs.) = 1-p (no occurrences in 10 yrs.) = 1 - (1-p) 10 = 1 - (0.80) 10 = 0.89 Entire summers void of any runoff producing rainfall whatsoever are not unheard of for the region. Conversely, storm sequences could occur during which overlapping of storm routing periods might produce emergency spillway discharges. Moreover, all individual inflow volumes within the sequence could conceivably fall below that of the computed design storm, resulting in simultaneous satisfaction and abridgement of federal statutes. The stochastic nature of precipitation characteristics such as intensity and rainfall depth should also be recognized since their association has been shown by this investigation to greatly influence the predicted performance of sedimentation ponds. Other variable factors which contribute to the uncertain comprehension of physical phenomena include soil erodibility, complex hillslope flow systems, gully formation, and the degree to which natural 70 in-pond aggregate formation affects settling rates. Vandivere, Davis, and Fogel (1979) investigated the uncertainty involved in applying the USLE to semi-arid surface mining sites. Results of hydrologic simulation on Black Mesa spoils showed an extremely large variance in the predicted 3-yr. sediment yields. The USLE overpredicted the 3-yr. sediment accumulation. This means that for the present study the basis for allocation of dead storage for the pond entails additional uncertainty. Also, variation in the particle size distribution with flow rate makes obtaining a representative size distribution problematic (dilmoth, Hill, and Ettinger, 1979). Model Adaptability and Regional Bias This model has been designed with general application in mind. Use of accepted mathematical descriptions for the component parts should assure it a high degree of adaptability to strip mine situations throughout the semi-arid U. S. Its reliance on field data is minimal, therefore, a limited data base should not preclude its utilization. As pond sampling data increases, verification of the model can be undertaken along with regional optimization of parameter values. Lack of verification notwithstanding, the model appears to perform satisfactorily in generating sediment yields and simulating basin trap efficiencies consistent with the imputed particle size distributions. Inherent regional bias is evident in all phases of the model due primarily to the simplicity afforded the present study in neglecting winter precipitation and spring snawmelt. For application to areas where frontal storm systems produce a significant portion of annual 71 precipitation, runoff, and sediment yield, a winter precipitation model coupled with a snawmelt accounting procedure can be added to the SCS Type II rainfall model used herein for convective storm activity. Alternative sediment yield models can also be substituted for the one used for this study, although regionalization of the parameters in the Williams (1975) equation is fairly straightforward, given adequate erosion and sediment yield data. Regardless of the methods used for determining water and sediment inflows to the sedimentation pond, the DEPOSITS routine (Ward et al., 1979) can be applied with equivalent accuracy to any region, as long as the modeled pond is designed properly. Provisions are available for simulating chemical treatment, density currents and short-circuiting and numerous withdrawal conditions. An additional attribute of the routine lies in its ability to model reservoir deposition over time. This enables its conjunctive use for purposes of hydrologic time series analysis, especially where event sequences related to frontal storm systems are simulated. The application of the INFLUX program in its present form is limited to small watersheds of 2000 acres or less where the bulk of runoff and sediment yield is derived from summer convective storms. Also, an infiltration curve based on representative field conditions is required. Computer time and consequent costs for the model are low. The combined cost of INFLUX and DEPOSITS models for the 38 selected precipitation events was under $1.50 per run, excluding print costs. This should make the package more desirable to prospective users. CHAPTER 5 CONCLUSIONS AND RECOMMENDATIONS A model has been compiled herein which enables simulation of sedimentation pond response to inflows generated by selected precipitation events on surface mined and natural watersheds. Procedures utilized in design of the pond reflect both the consideration of published federal criteria and recognition of current engineering practice. In the development of hydrologic inputs to the model, attention was directed toward an adequate description of the physical characteristics of convective precipitation. Application of the model is limited to small watersheds where spring snowmelt is negligible in the production of sediment and convective rainfall accounts for the bulk of annual runoff. The model was shown to successfully reproduce observed sediment yields and simulate pond effluent sediment concentrations which coincided with computed trap efficiencies. Simulation was undertaken for three watershed-pond conditions: (1) minespoil material with untreated inflow; (2) natural soil material with untreated inflow; and (3) minespoil material with treated inflow. Results indicated that in every case pond discharge for conditions 1 and 2 grossly exceeded federal standards for concentrations of suspended solids. Only when condition 3 was evaluated did a majority of routed pond inflows succeed in meeting the established standards. This suggests that in most semi-arid mining environs, current Federal guidelines for 72 73 the design of sedimentation ponds are totally incompatible with the attainment of established effluent quality criteria. Therefore, if the logic of a national effluent water quality standard is upheld, mine operators will have to rely heavily on additional measures in order to both reduce erosion and create depositional opportunities for transient flaw. For the semi-arid regions of the west, precipitation uncertainty makes it highly improbable that the healthy vegetative cover required to forestall excessive erosion and sedimentation can be achieved without an effective irrigation schedule. However, as the present study has shown, maintenance of a good stand of vegetation by no means assures compliance with published Federal effluent criteria. A crop management factor as low as 0.09 which corresponds to irrigation-derived vegetal cover proved insufficient in attaining Federal standards under prevailing soil and precipitation conditions. The overriding factor affecting pond performance is the character of the incoming sediment. In situations where the clay fraction of the particle size distribution is as clearly dominant as that observed in runoff from graded minespoils at Black Mesa, attainment of the desired effluent sediment concentrations will definitely require the addition of flocculants or coagulating agents to pond inflows. Application of chemical additives results in a significant increase in pond trap efficiencies due to the effective redistribution of particle sizes. Acceptance of this prerogative would assure compliance with federal regulations at minimal cost. Furthermore, the initial capital 74 expenditure required would likely be offset by a concomitant elimination of federally or state imposed pollution fines. In an effort to clarify the effect of precipitation uncertainty on projected pond performance, an alteration of documented sediment and management characteristics was applied to condition 1. Analysis of subsequent runs revealed a tendency for high-intensity-short duration storms accompanied by lesser inflow volumes to exceed effluent limitations. Conversely, the low intensity-long duration storms associated with greater inflow volumes which are exempted from federal regulations consistently displayed pond effluent concentrations within the allowable limits. Thus, the use of the 10 yr-24 hr. rainfall event as a design criteria for sedimentation ponds which do not operate according to a total containment policy appears to be unsubstantiated. The obvious dependence of predicted pond performance on the characteristics of individual precipitation events along with the uncertainty associated with the occurrence of these events offers ample justification for the consideration of hydrologic uncertainty in the sedimentation pond design process. Only then will designers and regulators be able to assess their position in the light of hydrologic reality. It must be recognized that even conditions existing on reclaimed watersheds are dynamic over time. Changing cover densities and the initially accelerated transport of fines could affect a substantial reduction in the influent clay fraction for a large portion of the projected pond lifetime. This decrease, however, would have relatively little influence on observed peak effluent sediment concentrations. 75 The poor quality of pond effluent simulated for undisturbed natural watershed conditions calls into question the applicability of current federal statutes pertaining to pond effluent limitations to the semi-arid regions of the western U. S. Ambient sediment concentrations measured in eastern streams are indicative of the comparatively lush vegetative cover and overlying canopy which effectively reduce both rainfall energy and the overland transport of sediment. Typically, semiarid zones exhibit sparse vegetal cover and a restricted protective canopy which effectively reduce both rainfall energy and the overland transport of sediment. Typically, semi-arid zones exhibit sparse vegetal cover and a restricted protective canopy, conditions which favor greater erosive activity, transport capacities, and consequently, higher ambient stream sediment concentrations. In addition, releasing effluent at concentrations considerably below that of ambient levels may lead to changes in downstream channel morphology as adjustments are made to accommodate the new flow regime. It seems sensible, therefore, to encourage the consideration of regional diversity in the establishment of effluent criteria for state regulatory proposals. Further research is required to assess the probabilities associated with the occurrence of rainfall events incorporating specific intensity-volume relationships. Risk analysis could then be attempted so that the effect of hydrologic uncertainties on the design and expected performance of detention facilities can be concretized. Since the highest intensity storm events have been shown to produce the highest peak effluent sediment concentrations, the critical precipitation scheme for 76 semi-arid regions would most likely include a close sequence of these events. Consecutive days of runoff-producing rainfall would lead to an overlapping of routing periods. Greatly reduced detention times for the routed inflows could then result in pipe discharge of heavily sediment-laden flow through the principal spillway and eventual emergency spillway overflow. Another subject which requires investigation is the principle of total containment regarding all inflows less than that corresponding to the computed design event. Although this design would produce increased detention times for runoff generated by the high intensity precipitation events, the critical scenario outlined above still applies because storage capacity is limiting and the potential for emergency spillway discharge remains. Moreover, despite reassurances to the contrary (Nadolski, 1980), the author suspects that resuspension of deposited sediments by the accompanying horizontal dewatering device is likely, therefore increasing the risk of violating water quality standards. The model described in this study maintains a slight regional bias, but can be easily adapted to other areas and conditions. It retains enough flexibility to enable its use in the analysis of hydrologic time series and is also relatively inexpensive to run. Because of its lack of reliance on recorded data, the model is applicable to ungaged watersheds, thereby increasing its range of utilization. Validation of the model in its present form is necessary so that expansion of the data base for semi-arid lands can be realized. This is important if the western states are to draft mining and reclamation regulations which are relevant to native conditions. APPENDIX A SEDIMENTATION POND DESIGN A comprehensive discussion of the procedural elements contributing to the finalized sedimentation pond design is presented below. The design process is subdivided into three components. Determination of water storage volume is followed by a description of the procedure used to compute the required sediment storage volume. The basin dimensioning is outlined and the operating characteristics of the reservoir, in the form of stage-area-storage volume and stage-discharge relationships, are formulated. A listing of DEPOSITS output resulting from routing the design storm through the basin not only confirms the legitimacy of the design, but also provides the reader with a feeling for the power of the model in describing basin performance. References are cited in parenthesis adjacent to the source material used for design purposes. Basin Capacity and Dimensioning The procedure outlined here for calculation of basin storage volume is presented in Ward et al. (1979). Based on an approximation of inflow-outfow relationships by triangular hydrographs, the required design storage volume is given as: V = 0.0413 tb. (qpi. - qpo) 1 s where 77 78 V s = water storage volume in acre-feet, -bi = base time for the inflow hydrograph in hours, and q . ,q = peak inflow and outflow rates, respectively, in p, i po cubic feet per second. As pointed out in Chapter 3, the design method used for computation of the inflow hydrograph was the SCS triangular hydrograph method described by Kent (1973). The geometry of the hydrograph dictates the following relationship for its time base: T = AD — +L p 2 where AD = duration of rainfall excess in hours, and L = basin lag time in hours. A 30 minute storm duration was assured representative for design pruposes and the lag time was calculated to be .17 hours, therefore: T= 0.5 2 + 0.17 = .42 hours and t bi = 2.67 x .42 = 1.12 hours. Runoff was determined with the use of the SCS rainfall runoff relation (Kent, 1973): (P - .2S) 2 = (1) + .8S) where the maximum potential retention, S, is related to a curve number index which assesses the runoff producing potential of the watershed. 79 Based on soil type, vegetative cover, and antecedent moisture condition, the relationship is expressed as: S = 1000 CN - 1 0 where CN represents the watershed curve number. For average antecedent conditions and characteristics common to graded spoil material at Black Mesa, a curve number of 89 was estimated. Thus, a value of 1.24 was calculated for the variable S. The resultant runoff volume was computed as: Q (2.10 - .2(1.24)) 2 2.10 + .8(1.24) = 1.12 inches Next, using the SCS equation for peak runoff determination, KOA where . = peak inflow rate in cubic feet per second, K = a watershed parameter, assured equal to 484 for chosen hydrograph geometry, Q = rainfall excess in inches, and A = drainage area in square miles. Substituting for equation unknowns: 80 484(1.12)(.078) q pi .42 = 100.83 cfs The remaining factor in the storage volume equation is the projected peak outflow rate from the reservoir given by Ward et al. (1979): q = t . q ./t P0bi pl bo where q = peak outflow rate, po t bo = time base of outflow hydrograph in hours, and t bo = (3 x t d ) + tbi where t d = required detention time in hours. As stated in the federal statutes (Federal Register, P. 15400), a theoretical detention time of 24 hours is the minimum acceptable period for pond design, therefore: t bo = (3 x 24) + 1.12 = 73.12 hours Additionally: q po = (1.12 x 100.83)/73.12 = 1.54 cfs Inflow runoff volume for a triangular hydrograph is: V = 1/2 q . t . Pi bi where V = inflow volume in cfs-hr. 81 V - 100.83 X 1.12 2 Thus, = 56.5 cfs-hr. Converting to acre-feet: V = 56.5 cfs-hr. X ac-ft. 12 cfs-hr. = 4.7 ac.-ft. In lieu of the aforementioned storage equation, empirical relationships for inflow and storage volumes on page 57 of the design manual are used: S/V = for q .83 = .015 This results in a required storage capacity, neglecting sediment storage, of: S = .83(4.7) = 3.9 ac.-ft. Sediment Storage Volume The level of the lowest dewatering device is required to be no less than that corresponding to 100% of the 3-year accumulated sediment storage volume. Since the regulations state that the Universal Soil Loss Equation (USLE) and an appropriate delivery ratio must be utilized for this calculation (Federal Register, p. 15400) its application to the hypoethetical situation is now developed. The USLE is an empirically derived formula based on thousands of plot years of data including natural and simulated rainfall conditions for 82 a variety of cultivation and management practices. Recent accumulation of data has provided for an extension of its usage to surface mine conditions (EPA 1977). The USLE is expressed as follows: A = where RxKxLSxCxP A = annual soil loss in tons per acre, R = rainfall erosion index, K = soil-erodibility factor, LS = length and steepness of slope factor, C = cropping management factor and P = erosion control practice factor The equation is dimensionally correct and the reader is referred to the current USDA-ARS users guide (Wischmeier and Smith, 1978) for a detailed discussion of factor development and application. Selection of parameter values was predicated upon 2 assumptions: 1. Only post-mining conditions were to be examined and no unnatural disturbances or hydrologic inputs were affected. 2. Essentially no vegetative cover is established during the first year and only 10% cover is generated over the next two years. Estimated factor values and justification for the choices made are: R = 30 evaluated from isoerodent map for Arizona (SCS 1976) K = .35 estimated value for Black Mesa grade spoil material (Fogel et al., 1979) LS = 1.26 derived from estimated average slopes of 6.7% and a slope length of 250 ft. 83 C = 1.0, .45 estimated values for zero and 10% cover respectively (EPA, 1977) P = .35 estimate based on practice of contour gouging or pitting currently employed at Black Mesa (EPA, 1977) Thus, yearly annual soil loss per acre for the 3 years is: A = (30 x .35 x 1.26 x 1.0 x .35) .9 = 4.17 tons/acre/year 1st year A = (30 x .35 x 1.26 x .45 x .35) .9 = 1.88 tons/acre/year 2nd, 3rd years where .9 represents the assumed delivery ratio defined as the ratio of sediment delivered to the watershed outlet to the gross watershed erosion. Over the entire extent of the 50-acre watershed the expected 3-yr. sediment yield would be: 50 ac.(4.17 tons/ac./yr. x 1 yr. + 1.88 tons/ac./yr./x 2 yr.) = 396.5 tons For storage to be allocated in the pond, the sediment yielded must be converted into a volumetric quantity reflecting the properties of the incoming sediment (Federal Register, p. 15400). An accounting of recorded incoming sediment size fraction distributions for the J-3 experimental watershed is offered in Table A.1. Particle diameters in millimeters for the size fraction descriptors appearing in the table are: coarse-medium: > .125 sand: very fine: silt: clay: .063 < x < .125 .002 < x < .063 < .002 84 Table A.1. Size fraction distributions for sediment production: J-3 experimental watershed, Black Mesa Mine. Storm date Size fraction, % of total Sand Silt Clay Coarse-med. Very fine 7-11-77 7-11-77 7-11-77 7-11-77 7-19-77 7-19-77 7-19-77 7-19-77 7-22-77 7-22-77 7-22-77 7-22-77 8-05-77 8-05-77 8-05-77 8-05-77 8-12-77* 8-12-77* 8-12-77* 8-15-77 8-15-77 8-15-77 8-15-77 8-22-77 8-22-77 8-22-77 8-22-77 Average 14.5 1.9 2.9 4.3 2.4 5.5 5.7 8.0 2.9 2.4 4.3 2.7 5.4 5.7 11.4 3.9 1.6 .8 2.8 .5 2.2 .5 .7 .4 .4 2.6 2.9 2.3 2.0 2.0 2.2 3.0 2.9 1.9 2.7 1.8 1.5 2.9 .9 2.4 2.2 6.3 1.7 2.3 .9 1.6 .9 1.9 .8 1.2 .8 .8 2.1 1.8 39.1 47.4 45.4 48.0 48.9 44.8 46.4 43.8 36.6 40.1 36.7 28.8 41.1 41.2 24.7 40.7 10.3 4.7 2.5 51.7 49.8 36.9 44.0 52.3 51.1 45.5 51.3 44.1 48.7 49.7 45.5 45.7 46.8 46.0 45.5 58.7 56.0 56.4 67.6 51.1 50.9 57.6 53.7 85.8 93.6 93.1 46.9 46.1 61.8 54.1 46.5 47.7 49.8 44.0 3.9 2.0 43.2 50.9 *Unrepresentative, assumed outliers. P age Missing in Original Volume 86 An obvious inconsistency appears in the computed average size fraction percentages when matched against those used below in figuring the sediment density value. This is the result of assumptions made later in the study regarding the possibly anamolous character of the indicated measured sediment distributions for the indicated storm events. This, however, only lends to the conservative nature of the pond design. The density of stored sediment is assumed to accrue from conditions outlined in the DEPOSITS manual (Ward et al., 1979) for "reservoir operation type III" representing a normally dry reservoir: W = WP +WP +WP cc mm s s where W = density of sediment in pound per cubic foot, Wc,W m Ws unit weights for clay, silt, and sand fractions, respectively, for a dry reservoir in pounds per cubic foot, and P P P = proportion of each of the same three above c m s mentioned constituents, expressed as a decimal fraction. Therefore: W = 40(.553) + 72(.39) + 97(.06) = 55.7 lb/ft 3 Finally, the required sediment storage volume is: ft 3-ac.-ft. 396.5 tons x 2000 lb/ton x 55.7 lb. x 43,560 ft j = .33 ac. ft. When the required water storage capacity is combined with the sediment storage volume, the total design storage capacity results: 87 Total storage volume = 2.9 + .33 = 4.23 ac.-ft. Stage area-discharge Relations - Assuming the reservoir bed is constant at stage 0.00 feet, the surface area and storage capacity are listed as a function of elevation above the bed in Table A.2. The required sediment storage volume evidently corresponds to a stage of .97 feet. This stage height was designated as the location of the first de-watering orifice set. Results of earlier trial designs suggested a riser crest elevation of approximately 9.0 feet. A second orifice set was also added at a stage level of 6.0 feet. With the riser configuration set, the only information lacking in the determination of the stage-discharge relationship is that of the head relation for pipe-full flow as described in Chapter 3. This entails completion of a preliminary basin dimensioning and embankment design so that the positioning of the culvert and its outlet elevation can be obtained. Given the computed basin capacity, dimensioning of the basin can be undertaken. Assuming a trapezoidal configuration with bottom width, b o , length, 1, and design depth, y d , accompanied by embankment slopes of 1 vertical to 2 horizontal (Federal Register, p. 15400), the following dimensions have been chosen: yd = 15 ft. b = 50 ft. = 285 ft. o L 88 Table A.2. Stage (ft.) Rating relations for final pond design. Surface Area (ac.) Storage Capacity (ac.-ft.) 0.00 .33 0.00 0.97 .35 0.33 1.00 .35 0.34 2.00 .38 0.71 3.00 .40 1.10 4.00 .43 1.52 5.00 .46 1.96 6.00 .48 2.43 7.00 .51 2.93 8.00 .54 3.45 9.00 .56 4.00 9.50 .58 4.29 10.00 .59 4.58 11.00 .61 5.18 12.00 .64 5.81 13.00 .67 6.46 14.00 .69 7.14 15.00 .72 7.85 Trapezoidal Basin: Surface Area = (b + 4)L o Y Storage Capacity = b L + 2 2 L 0 y y 89 Check for length to width ratio at design depth: b L/b 15 • 50 + 2(15 x 2) = 110 ft. 15 • 285/110 • 2.6 which satisfies the suggested ratio of greater than 2.0 (Ward et al., 1979). Allowing 5 ft for embankment freeboard and emergency spillway section: H = total height of embankment = 20 ft. Minimum top width must be >((H + 35)/5) (Federal Register, p. 15400) (H + 35)/5 = 55/5 = 11 ft. Total width of the embankment = 2(2 x 2) + 11 ,-. 90 ft. Assume a culvert length = 90 ft. and culvert diameter = 8 in. Optimum critical slope to produce pipe full flow (S ) c op. = 111 n 2 D 1/3 (Portland Cement Association, 1964) where n = Manning's roughness factor, assumed = .024 D = culvert diameter in feet (S c ) op for an 8 inch diameter corrugated metal pipe = .079 ft/ft. Fall height of conduit over projected length = 90 x .079 = 7.1 ft. Assuming a distance of .5 ft. between the center of the lowest dewatering orifice and the center of the culvert at its connection with the riser, 90 head for pipe flaw condition = 7.1 + .5 + 8.03 + h = (15.6 + h) ft. where h is the head on the spillway crest. Stage-discharge relations based on the hydraulic equations given in Chapter 3 for the finalized pond design are presented in Table A.3. This information, along with the stage-area data appearing in Table A.2, provides the primary inputs required by the DEPOSITS model for routing of sediment laden water through the reservoir. An output generated by the DEPOSITS routine for the 10 yr-24 hr. design event is listed in the following pages. Variables appearing in the output are defined in the DEPOSITS "glossary of terms" which is located in Appendix C. 91 Table A.3. Stage-discharge relations for final pond design. Q orifice Q Stage weir (cfs.) (cf s) (ft.) head 1 a1 head 2 Q pipe total (cfs.) (cfs.) a2 head a H -pipe - - - - - 0.00 0.00 - - 0.97 - - - - - - - - 0.00 1.00 0.03 .05 - - - - - - 0.05 2.00 1.03 .32 - - - - - - 0.32 3.00 2.03 .44 - - - - - - 0.44 4.00 3.03 .54 - - - - - - 0.54 5.00 4.03 .63 - - - - - - 0.63 6.00 5.03 .70 - - - - 7.00 6.03 .77 1.0 .31 - - - - 1.08 8.00 7.03 .83 2.0 .44 - - - - 1.27 9.00 8.03 .89 3.0 .54 - - - - 1.43 9.50* 8.53 .09 3.5 .06 0.5 2.44* 16.1 2.51* 2.66 10.00 9.03 .09 4.0 .06 1.0 6.91 16.6 2.54 2.69 11.00 10.03 .10 5.0 .07 2.0 19.54 17.6 2.62 2.79 12.00 11.03 .10 6.0 .08 3.0 35.90 18.6 2.70 2.88 13.00 12.03 .11 7.0 .08 4.0 55.28 19.6 2.77 2.96 14.00 13.03 .11 8.0 .09 5.0 77.26 20.6 2.84 3.04 15.00 14.03 .12 9.0 .09 6.0 101.56 21.6 2.90 3.11 0.70 *Transition to pipe flow occurs at stage = 9.5 ft; orifice discharge at stages > 9.5 ft. are reduced by 90% due to submergence of orifices. 92 0 LIJ o Q 0 0 o • 0 1-• a Z 1.• Li .2 0 0 CJ X tn 0 0 • .-4 QC 0 1-• Li! 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CO CP CD 04 M UN 47 ap CO op CG cco CP CP CP CP CP CP CP Is". CP • • • • • • • • • • • • Pn P. r. r- ....... p. 1, uNuN aN,r4 un in '00,0% 4 .. 041 -4 -4 C7 CP ... CP CO CD C7 a P. JD CD CD • • • • • • • • • • • • • • Or .7 .7.7 .7 .7 P. P. JD 40 UN UN en en n4 04 V po y4 04 no 04 P4 04 po 04 n, ni • • . • . • • • . _r • e4 eq I nlelo Otelole mm mm 1 41 0. 4-11 r•-• _r • • . • • • • • • • • • • z 4) JD ,n p. 1.n P. P. r- op ma) co CD o. r. o. r. rn r- r. r. r- VVVV NI ..... -4 • • • • • • • • • 0 • • • 7 CD CD CD D 3 0 CD CD CD 0 D CD O 7 7 3 CD CD D <3 <3 CD D CI 7 • • . • • • . • • • • • a CD CD CD CD 0 3 CD CD CD CD CD CD 7 CD 0 <3 D CD CD 0 3 CD C7 .4) C3 V 4' 43 CD • • • • • • • • • • • • pn Se .0 .000 Cr Cp CP CD CD .74ro • a p. r- p- p. p. p. p. p. p. P. p. P. r- APPENDIX B INFLUX VARIABLE DESCRIPTION Program INFLUX computes event-based rainfall, infiltration, runoff, sediment yield, and the inflow hydrograph required for utilization of the DEPOSITS sedimentation routine. Included within are component models which are described in Chapter 3. The program requires the following inputs: event return period, precipitation volume and duration, and infiltration rates and corresponding soil moisture storage values. The variables appearing in INFLUX are defined below. Where appropriate, values for the hypothetical watershed and units of the variables are noted. Arrays are indicated by an asterisk. Variable *ACTFIL Definition Value and Units Actual value for infiltration rate for a time increment in./hr. Initial soil moisture storage capacity. inches Cumulative time for inflow hydro graph hours Draingage area for hypothetical watershed. 50.0 acres Duration of precipitation event hours DUREX Duration of rainfall excess hours FACTC USLE crop management factor FACTK USLE soil erodibility factor AVAIL *CUMIN DAREA *DURA 109 110 Variable Definition FACTLS USLE length-slope factor FACTP USLE erosion control practice factor *FILL Volumetric infiltration for a time increment *ORD Discharge corresponding to .05 hr. increments *PCTDC Cumulative density function for total rainfall duration *PCTDP Probability mass function for rainfall duration PCTR PEAK PINTMX Value and Units inches Proportion of total rainfall for time increment Peak flow rate for the event cfs Intensity index representing the highest storm rainfall intensity *PRECIP Total rainfall volume for the event inches *RAINCD Cumulative density function for duration of rainfall hours *RAINEX Volume of rainfall excess for an increment inches *RAINPD Probability mass function for duration of incremental rainfall hours *RAINV Volume of rainfall occurring over a time increment inches *RETURN Return period for a precipitation event years RUN VOL Runoff volume for a precipitation event ac.-ft. 111 Value and Units Variable Definition SEDYD SSINF *STOFIL Sediment yield for a precipitation event tons Steady-state infiltration rate in./hr. Infiltration rate corresponding to the prevailing soil moisture deficit for an increment in. /hr. Available moisture storage capacity for an increment inches TBASE Time base of the inflow hydrograph hours TERP An interpolation factor for infiltration rate computation TFILL Accumulated soil moisture storage volume inches TLAG Watershed lag time hours Time to reach peak flow rate for a precipitation event hours Volume of rainfall excess for a precipitation event inches *STORE TPEAK TRAINX APPENDIX C PROGRAM LISTING OF INFLUX 112 113 PROGRAM INFLUX (INPUT,OUTPUT,TAPE 5.INPUT,TAPE 6 -OUTPUT) C THIS COMPONENT ANALYZES PRECIPITATION EVENTS OF CERTAIN FREQUENCY AND C DURATION AND DETERMINES CHARACTERISTICS OF MATER AND SEDIMENT INFLUX C TO THE SEDIMENTATION POND DIMENSION PCTR(22),PCTDP(22),PCTDC(22),ACTFIL(22),FILL(22) DIMENSION RAINP0(22),RAINCD(22),RAINV(22),RAINEX(22),STORE(8) DIMENSION STOFIL(8),RETURN(38),DURA(38),PRECIP(38) DIMENSION CUMIN(100),ORD(100) READ(5,1)(PCTR(I),PCTDP(I),PCTDC(I),I.1,22) 1 FORMAT(3F10.3) READ(5,2) STOFIL 2 FORMAT(8F5.2) READ(5,3) STORE 3 FORMAT(8F5.2) DO 150 M..1,38 READ(5,4) RETURN(M),DURA(M),PRECIP(M) 4 FORMAT(I3,2F7.2) WRITE(0,9) RETURN(M),OURA(M) 9 FORMAT("1",20X,"**** HYDROLOGIC SUMMARY:",I4," YR.",F6.2," HR. EVE ).NT ****") DUREX.0.0 JRAINX.0.0 SSINF..22 C SSINF REPRESENTS STEADY STATE INFILTRATION RATE IN INCHES/HR. TFILL.0.0 C AVAIL REPRESENTS INITIAL MOISTURE STORAGE CAPACITY IN INCHES AVAIL-1.8 C STORE REPRESENTS AVAILABLE MOISTURE STORAGE CAPACITY IN INCHES FILL IS THE VOLUMETRIC INFILTRATION IN INCHES FOR THE TIME INCREMENT C APPORTION RAINFALL VOLUME AND DURATION ACCORDING TO SCS TYPE II C STORM DISTRIBUTION WRITE(6,10) lù FORMAT(////, 5X," RAINPD(N)",10X," RAINCD(4)",10X," RAINV(N)",10X," I INFIL. RATE"plUX," INFIL. VOLUME") WRITE(6,11) 11 FORMAT(6X,9("-"),11X19("-."),11X,8("- - "),11X , 11(" - ") , 11X ,13 (" - ")) DO 80 N.1,22 RAINPD(N)=PCTDP(4)*DURA(M) RAINCD(N)=PCTDC(N)*DURA(M) RAINV(N).PRECIP(M)*PCTR(N) IF(N •NE. 15) GO TO 13 MAX. PRE:IF • INTENSITY, PINTMX, OCCURS AT 15TH DURATION INCREMENT PINTMX.RAINV(N)/RAINPO(N) 13 WRITE(6,15) RAINPD(N),RAINCD(N),RAINV(N) 15 FORMAT(8X,F5.2,14X,F5.2,16X , F5.2) C FIND 'NFU-. RATE CORRESPONDING TO ACTUAL AVAILABLE MOISTURE STORAGE IF((AVAIL-TFILL) .GT. 1.25) GO TO 18 C ACTFIL IS THE ACTUAL VALUE FOR INFILTRATION RATE OVER THE INTERVAL IN C INCHES/HR. AZTFIL(N).SSINF FILL(N).SSINF*RAINPD(N) GO TO 30 18 DO 2 0 K=1,8 IF((AVAIL-TFiLL) •GE. STORE(K)) GO TO 23 20 CONTINUE 23 IF(K .EQ. I) GO TO 25 TERP.((AVAIL-.TFILL)-STORE(K))/(5TOREST 0 RE ( K )) ACTFIL(N)=STJFIL(K)+TERP*(STOFIL(K - 1) - STUFIL ( K )) GO TO 26 25 ACTFIL(N)=STOFIL(K) 26 FILL(N).ACTFIL(N)*RAINPD(N) IF(CAVAIL-•(TFILL+FILL(N))) .LE. 0.00) GO TO 27 TFILL=TFILL+FILL(N) 114 GO TO 45 27 FILL(N)wAVAILTFILL 30 TFILLwTFILL+FILL(N) AVAIL.TFILL 45 WRITE(6,50) ACTFIL(N),FILL(N) 50 FORMAT("+",63X,F9.2,15XpF8.2) C CALCULATE VOLUME OF RAINFALL EXCESS FOR INCREMENT RAINEX(N)=RAINV(N)FILL(N) IF(RAINEX(N) .GT. 0.0) GO TO 70 GO TO 80 70 DUREX.DUREX+RAINPD(N) TRAINX.TRAINX+RAINEX(N) 80 CONTINUE WRITE(6,82) PRECIP(M),PINTMX 82 FORMAT("0"," PRECIP. VOLUME • " 1 F6.2," INCHES",/," MAXIMUM PRECIP. 1INTENSITY •",F6.2," IN./HR.") WRITE(8,85) DUREX,TRAINX 85 FORMAT("0"," DURATION OF RAINFALL EXCESS w",F5.2," HRS.",/p" TOTAL 2 RAINFALL EXCESS P",F5.2," INCHES") C CALCULATE PEAK FLOW RATE, TIME TO PEAK, AND TIME OF HYDROGRAPH BASE DAREA-50.0 C TLAG REPRESENTS THE LAG TIME IN HRS. FROM CENTROID OF RAINFALL EXCESS C DURATION TO HYDROGRAPH PEAK TLAGw.17 C TPEAK REPRESENTS TIME IN HRS. FROM THE INITIATION OF RUNOFF TO THE C HYDROGRAPH PEAK C TBASE REPRESENTS TIME IN HRS. CORRESPONDING TO THE HYDROGRAPH BASE TPEAKm(DUREX/2+TLAG) PEAKw(484.0*DAREA/64000*TRAINX)/TPEAK TBASE.2.67*TPEAK C CALCULATE EVENT BASED SEDIMENT YIELD VIA REGIONALIZED WILLIAMS EQN. C RUNVOL REPRESENTS RUNOFF VOLUME IN AC. FT. RUNVOLw(TRAINX*DAREA)/12.0 FACTLS.1.26 FACTCw.09 FACTKw.35 FACTPw.35 C SEDYD 15 THE EVENT SEDIMENT YIELD IN TONS 5EDYUw95.0*(RUNVOL*PEAK)*w.564.FACTC1FACTK*FACTLS*FACTP WRITE(6,90) PEAK 90 FORMAT("0"," PEAK FLOW FOR EVENT • "..F7.2," CFS") WRITE(6p93) TPEAK 93 FORMAT(" "p" TIME TO PEAK DISCHARGE w",F5.2," HRS.") WRITE(6,95) RUNVOL 95 FORMAT(" "." VOLUME OF INFLOW TO POND • ",F5.2," AC. FT.") ORITE(6,96) TBASE 96 FORMAT(" "," TIME BASE OF INFLOW HYDROGRAPH • ",F5.2p" HRS.") WRITE(0/98) SEDYD ;a FoRmArin 1 SEDIMENT YIELD FROM WATERSHED FOR EVENT • ",F9.1," TON 3S") C CUMIN REPRESENTS THE CUMULATIVE TIME FOR THE INFLOW HYDROGRAPH C CALCULATE ORDINATES OF INFLOW HYDROGRAPH C WITH 4 TIME INCREMENT OF .05 HRS. WRITE(6,110) £10 FORMAT("1"p2OX," INFLOW HYDROGRAPH COORDIUTES") WRITE(6,111) 111 FORMAT(21Xp29(""..")) " " WRITE (6,112) 112 FORMAT("0",22X," TIME(HRS.)",1X," DISCHARSE(CFS)") WRITE(8,113) 113 FORMAT(24X,4("-"),8X,9("-")) INPERwINT(TBASE/.05+1.0) DO 140 .1.1,INPER 115 CUMIN(J).J/20.0 IF(CUNIN(J) • GT. TBASE) GO TO 150 IF(CUMIN(J) .GT. TPEAK) GO TO 115 C Q0(J) REPRESENTS THE DISCHARGE CORRESPONDING TO J INCREMENTS OF .05HR ORD(J)*PEAK/TPEAK*CUMIN(J) GO TO 120 115 ORD(J).PEAK....(PEAK/(1.67*TPEAK)*(CUMIN(J)-TPEAK)) 120 WRITE(15 125)CUMIN(J).ORD(J) 125 F3RMAT("0",22X,F5.2.11X,F5.1) 140 CONTINUE 150 CONTINUE , STOP END APPENDIX D PROGRAM AND INPUT LISTING OF DEPOSITS Input Listing of Deposits The following is a listing and description of the inputs required by the DEPOSITS sedimentation model (Ward et al., 1977b). Typical variable values are presented, and their implications for model functioning appear parenthetically. VariableDefinition Value NSTORM Number of inflow events required 1.0 CONSED Control variable determining the calculation of the inflow sediment concentrations. (concentrations are approximated by the model) 1.0 DEPOST Control on use of the deposition option. (no deposition option) 1.0 MASS Total mass of incoming sediment in tons FLOW Indicator of desired outflow con- ditions. (uniform withdrawal) 1.0 TRP Control variable providing for testing of several outlet structures (model straightforwardly determines trap efficiency) 1.0 FILTER Enables alteration of initial stage- discharge curve due to deposition. (no disposition effect considered) 1.0 DENSTY Density of deposited sediment SG Specific gravity of sediment par- ticles in g/cm3 116 16.1 .89 2.65 117 VariableDefinitionValue Viscosity of the flow in cm 2 /sec. VISCOS DELTAT DELPLG SET SHORT Time increment for the inflow hydro- graph and inflow sediment-graph in hours. .20 Time increment for outflow plug rou- ting in hours .20 Dictates the relationship between the sediment load and the inflow rate. (Sets inflow sediment concentration proportional to the inflow rate) .0152 Basin short-circuiting option (plug flow through basin is assumed) 2.0 1.0 FIX Correction factor for simulation of turbulence or flocculation (turbulence and flocculation are neglected) 1.0 FLOWAV Determines how particle size distribution varies with flaw rate. (one representative distribution is maintained throughout) 0.0 FRACTN Control variable defining the sediment distribution during inflow to the basin. (sediment load is completely mixed with storm inflow) 0.0 SLAG Simulates a lag between peak inflow rate and peak inflow sediment concentration. (effect is neglected) 0.0 DEAD Volume of stored flow and/or sediment bypassed during routing, in ac.-ft. (volume set equal to 60% of calculated 3-yr. sediment storage) MP Number of outflow distribution points 18 Number of inflow hydrograph values (inflow hydrograph constructed from 2 values) >2 .20 118 Variable Definition Number of stage-area and stage discharge values Value 18 NS Number of particle size fractions MS Number of outflow hydrograph points (set equal to maximum allowable) LS Number of values required to fill the permanent pool volume (pool is filled internally by the program) PERCNT Percent finer values inputed for particle size distribution 0.0, 28.2, 63.3, 85,8, 100.0 SIZE Particle sizes corresponding to inputed percent finer values in millimeters 0.0, .002, .063, .125, 1.00 STGI Stage values at the riser used for rating curves AREA Area values corresponding to inputed stage values DISCHB Discharge values corresponding to inputed stage values INFLOW Inflow hydrograph values for the storm 5 400 0 119 PROGRAM SEDIMT (INPUT OUTPUT,TAPE5.INPUT,TAPE6.OUTPUT) , * **** ********* ***** ************** **************** ***** ***** **** ***** ****** THE DEPOSITS PROGRAM APRIL 1979 THE DEPOSITS PROGRAM WAS DEVELOPED AT THE AGRICULTURAL ENGINEERING DEPARTMENT AND THE INSTITUTE FOR MINING AND MINERALS RESEARCH AT THE UNIVERSITY OF KENTUCKY, LEXINGTON KENTUCKY. THE UNIVERSITY OF KENTUCKY ASSUMES NO RESPONSIBILITY FOR ANY RESULTS OBTAINED WITH THE MODEL. THE DEPOSITS COMPUTER PROGRAM IS A SIMULATION MODEL FOR ESTIMATING THE PERFORMANCE OF A SEDIMENT DETENTION BASIN. THE MCDEL WILL DETERMINE THE BASIN TRAP EFFICIENCY, CHANGE IN BASIN GEOMETRY DUE TO SEDIMENT DEPOSITS AND THE EFFLUENT SEDIMENT CONCENTRATIONS FOR A GIVEN STORM EVENT. ************************************************** ***** ********* ******* *** ****** **** ** * ******* *** ***** ****** ******* ******* ********** ******* ***** **** GLOSSARY OF TERMS ACINFL ACOUT • ACCUMULATED INFLOW VOLUME (ACRE-FEET) • ACCUMULATED DISCHARGE FROM THE RESERVOIR. (ACRE-FEET) ACT CONTROL FLAG USED TO TERMINATE SIMULATION. (ACRE-FEET) AR AREA CONTROL VALUE USED IN DEVELOPING NEW AREA CURVE. ARA• AREA CONTROL VALUE USED IN DEVELOPING NEW AREA CURVE. • AREA CONTROL VALUE USED IN DEVELOPING NEW AREA CURVE. ARC = AREA CONTROL VALUE USED IN DEVELOPING NEW AREA CURVE. ARE AREAA • SURFACE AREA OF SURFACE PLUG LAYER. (ACRES) AREA• BASIN SURFACE AREA AT EACH STAGE POINT. (ACRES) AREAC SURFACE AREA OF THIRD PLUG LAYER. (ACRES) AREAB • SURFACE AREA OF SECOND PLUG LAYER. (ACRES) AREAD • SURFACE AREA OF BED PLUG LAYER. (ACRES) • DESIGN BASIN SURFACE AREA AT EACH STAGE POINT. (ACRES) AREAS AROLD • SURFACE AREA AT EACH STAGE POINT PRIOR TO DEPOSITION. (ACRES) • AVERAGE DEPTH OF FLOW AT EACH INFLOW TIME STEP. (FEET) AVDEP AVDPTH • AVERAGE DEPTH AT EACH STAGE POINT. (FEET) AVETME • DETENTION TIME OF FLOW CONTAINING SEDIMENT. (HRS) AVSTG • AVERAGE DEPTH AT EACH INFLOW TIME. (FEET) AVTME • SUM OF THE PRODUTS OF THE PLUG VOLUMES TIMES THE PLUG DETENTION TIMES. (ACRE-HRS) SPOOL• VOLUME OF INFLOW USED TO FILL THE PERMANENT POOL. (ACRE-FEET) = VOLUME OF SEDIMENT DEPOSITED BELOW EACH STAGE VALUE.(ACRE-FEET) CAP CAPAC • DESIGN CAPACITY OF THE BASIN AT EACH STAGE VALUE. (ACRE-FEET) • BASIN CAPACITY AT EACH INFLOW TIME. (ACRE-FEET) CAPACA CAPCH • VOLUME CONTROL VALUE USED TO DEVELOP NEW STAGE CAPACITY CURVE. 120 C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C • DESIGN CAPACITY OF THE BASIN AT EACH STAGE VALUE. (ACRE—FEET) • VOLUME CONTROL VALUE USED TO DEVELOP NEW STAGE CAPACITY CURVE, (ACRE—FEET) CAPMAX • MAXIMUM VOLUME OF RESERVOIR BASIN. (ACRE—FEET) CAPNW • RESERVOIR VOLUME AT EACH STAGE POINT FOLLOWING DEPOSITION. (ACRE—FEET) CAPOOL • VOLUME OF THE PERMANENT POOL. (ACRE—FEET) CAPO • CALCULATED CAPACITY VALUES BEFORE SMOOTHING. (ACRE—FEET) CAPREM . TOTAL VOLUME OF SEDIMENT DEPOSITED BY STORM. (ACRE—FEET) CAPSAV • VOLUME OF THE BASIN AT THE PEAK STAGE. (ACRE—FEET) CENTME • DETENTION TIME FROM HYDROGRAPH CENTERS. (HRS) CHECK • AREA CONTROL VALUE USED TO DEVELOP NEW AREA CURVE. (ACRES) CONCED • INFLOW SEDIMENT CONCENTRATIONS. (MG/L) CONSED • CONTROL VARIABLE DETERMINING THE INPUT OF INFLUENT SEDIMENT CONCENTRATIONS. (MG/L) COR • CONTROL VALUE USED TO SMOOTH NEW STAGE—CAPACITY CURVE. DEAD • DEAD STORAGE VOLUME. (ACRE—FEET) DELPLG • TIME INCREMENT OF EACH OUTFLOW PLUG. (HRS) DELTAT a INFLOW HYDROGRAPH TIME INCREMENTS. (HOURS) DENSTY • DENSITY OF THE SEDIMENT DEPOSITS. DEP • VOLUME OF SEDIMENT DEPOSITED DURING EACH DISCHARGE INCREMENT. (ACRE—FEET) DEPCAP . CHANGE IN STORAGE CAPACITY DUE TO SEDIMENT DEPOSITS. (ACRE—FEET) DEPI • CHANGE IN STORAGE CAPACITY FOLLOWING SMOOTHING COMPUTATIONS. (ACRE—FEET) DEPOC . SMOOTHING CONTROL VARIABLE. DEPO • CONTROL VARIABLE USED IN SMOOTHING OF NEW BASIN GEOMETRY CURVES. DEPOST . CONTROL VARIABLE DETERMINING USE OF THE DEPOSITION OPTION. DEPTH • AVERAGE DEPTH DURING DETENTION OF EACH PLUG. (FEET) DEPTH1 • DEPTH OF THE SECOND PLUG LAYER. (FEET) DEPTH2 • DEPTH OF THE THIRD PLUG LAYER. (FEET) DEPTH3 • DEPTH Of THE BOTTOM PLUG LAYER. (FEET) DETAVE = AVERAGE DETENTION TIME OF DISCHARGED FLOW. (HRS) DETTME • DETENTION TIME OF EACH PLUG. (HOURS) DIAMTR • PARTICLE SIZE WITH A FALL VELOCITY OF VELOC. (MM) DIFF • CONTROL VALUE USED TO SUBDIVIDE THE TOP LAYER. DISCH • DISCHARGE RATE AT EACH STAGE VALUE. (CFS) DISCHA . DESIGN DISCHARGE RATE AT EACH STAGE VALUE. (CES) DISCHB • DISCHARGE VALUE FOR EACH STAGE POINT. (CES) DPTH • STAGE DEPTH FOR EACH DISCHARGE AND AREA VALUE. (FEET) DPTH • DEPTH VALUES ON THE OUTFLOW DISTRIBUTION CURVE. (FEE) EFLNT • EFFLUENT CONCENTRATION FOR EACH OUTFLOW INCREMENT. (MG/L) ERROR • ERROR IN DETERMINING THE NEW BASIN CAPACITY. (ACRE—FEET) FALL • REQUIRED DEPTH OF SETTLING. (FEET) • CONTROL VARIABLE DETERMINING THE USE OF AN OUTLET FILTER. FILTER FIX • CORRECTION FACTOR TO MODIFY THE FALL DEPTH. FLOWIN • FLOW RATE AT WHICH THE SEDIMENT DISTRIBUTION WAS DETERMINED. C FLOW• C C C C C C C C C C FRACTN INFLOW LS LLS MASS M MS MS N C NFLNT • C NS • CAPCO CAPC (CFS) • . • • • • • . • CONTROL VARIABLE DETERMINING THE INPUT OF AN OUTFLOW DEPTH DISTRIBUTION. IF FRACTN GREATER THAN 0.1 FLOW OCCURS AS A DENSITY CURRENT. INFLOW RATE AT EACH INFLOW TIME. (CES) NO OF INFLOW VALUES USED TO FILL THE PERMANENT POOL. NO OF INFLOW VALUES USED TO FILL THE PERMANENT POOL. (LLS=LS) SEDIMENT INFLOW LOAD. (TONS) NUMBER OF INFLOW VALUES. NUMBER OF OUTFLOW ROUTING VALUES. NUMBER OF OUTFLOW ROUTING VALUES. NUMBER OF STAGE VALUES. THE INFLUENT CONCENTRATIONS AT EACH INFLOW TIME PCINT. (MG/L) NUMBER OF PARTICLE SIZE DISTRIBUTION VALUES. 121 C NSTORM COUTFL1 COUTFL2 COUTFL3 COUTFL4 C OUTPCT CPCT CPCTOUT C PEAKIN CPEAK• CPERCNT • • • • . • • • • . CINDICATED PFLNT C C PLGCEN C PLGTME C PLGVOL C PSTAGO C SED C SEDAVE C C SEDAV2 C SEDEND C SEDMNT C SEDOUT C SEDPLG CSEDTOT C SEDT CSET C C C C SFLNT SG SHORT SIZES CSIZEST C C C SIZE SIZOUT SLAG • • • • • • . • • • . . • • . . • . = • • . • CSMOOTH • C C C C C C SMOTH2 STAGE• STAGEA STAGO STAG• STAREA CSTARTV C STGAR C STGIN C STGOUT C STG1 C51 G2 C STG3 STORM• C SIP C STPV C CSTRMOT CSTRMTM SUMTME C SUMVOL C • • • • • . • • • • = . . . • • • . • • . c sum:. C C SUM2 T TMEIN TOTAL• . TOTVOL c c C CONTROL VARIABLE DETERMINING THE NUMBER OF STORM EVENTS. OUTFLOW DISTRIBUTION FOR THE TOP PLUG LAYER. ( ) OUTFLOW DISTRIBUTION FOR THE SECOND PLUG LAYER. ( ) OUTFLOW DISTRIBUTION FOR THE THIRD PLUG LAYER. ( ) OUTFLOW DISTRIBUTION FOR THE BOTTOM PLUG LAYER. ( ) FINER OF SEDIMENT IN THE POND EFFLUENT. PERCENT OF SEDIMENT REMAINING IN SUSPENSION IN EACH LAYER. SEDIMENT LOAD FOR EACH PARTICLE SIZE IN THE EFFLUENT. PEAK INFLOW RATE. (CES) PEAK DISCHARGE RATE. (CFS) PERCENT OF PARTICLES CAPABLE OF FALLING THE RESPECTIVE DEPTH DURING THE PLUG DETENTION TIME. PEAK INFLOW SEDIMENT CONCENTRATION. (MG/L) THE TIME OF INFLOW OF EACH PLUG OF OUTFLOW. (HOURS) THE TIME OF OUTFLOW FOR EACH PLUG. (HOURS) THE VOLUME OF EACH PLIG. (ACRE-FEET) PEAK STAGE VALUE. (FEET) PERCENT OF THE TOTAL SEDIMENT INFLOW CONTAINED IN EACH PLUG. AVERAGE EFFLUENT SEDIMENT CONCENTRATION OF FLOW CONTAINING SEDIMENT. (MG/L) AVERAGE EFFLUENT SEDIMENT CONCENTRATION OF ALL FLOW. (MG/L) ACCUMULATIVE TOTAL PERCENT OF THE INITIAL SEDIMENT DISCHARGED. PROPORTION OF SEDIMENT ASSOCIATED WITH EACH INFLOW INCREMENT. FRACTION OF SEDIMENT CONTAINED IN EACH PLUG. ( 1 PERCENT OF SEDIMENT DISCHARGED IN EACH PLUG. ACCUMULATED VOLUME OF SEDIMENT INFLOW. ACCUMULATED VOLUME OF SEDIMENT DISCHARGED. EXPONENT OF FLOW SEDIMENT LOAD RELATIONSHIP. INFLOW SEDIMENT CONCENTRATIONS. (MG/L) SPECIFIC GRAVITY OF THE SEDIMENT PARTICLES. SHORT-CIRCUITING CONTROL VARIABLE. FINER OF INFLOW DETERMINED AT PEAK INFLOW RATE. ( ) INFLOW PARTICLE SIZES DETERMINED AT PEAK INFLOW RATE. (MM) PARTICLE SIZE ASSOCIATED WITH EACH PERCENT FINER. (MM) FINER OF EFFLUENT SEDIMENT PARTICLES. LAG INCREMENTS OF TIME OF FLOW PEAK BEHIND SEDIMENT PEAK. AREA SMOOTHING FUNCTION. AREA SMOOTHING FUNCTION. DEPTH OF FLOW FROM THE LOWEST BED ELEVATION. (FEET) STAGE AT EACH ROUTING TIME. (FEET) STAGE AT EACH OUTFLOW TIME. (FEET) STAGE VALUES PRIOR TO EACH STORM EVENT. (FEET) AREA UNDER THE AVERAGE DEPTH-TIME CURVE. (ACRE-FEET) VOLUME OF INFLOW AT THE START OF THE ROUTING CYCLE. (ACRE-FEET) AVERAGE STAGE AFTER EACH INCREMENT OF INFLOW. (FEET) STAGE DURING INFLOW OF EACH PLUG. (FEET) STAGE DURING THE PLUG OUTFLOW. (FEET) DESIGN STAGE VALUES. (FEET) STAGE CONTROL VARIABLE USED IN SMOOTHING CALCULATION. STAGE CONTROL VARIABLE USED IN SMOOTHING CALCULATION. STORM INFLOW VOLUME. (ACRE-FEET) ACCUMULATED VOLUME OF OUTFLOW. (ACRE-FEET) ACCUMULATED INFLOW AT TIME Ti. (ACRE-FEET) STORM VOLUME DISCHARGED. (ACRE-FEET) DETENTION TIME INCLUDING STORED FLOW. (HRS) VARIABLE USED IN EVALUATING THE STORM DETENTION TIME. VOLUME OF FLOW DISCHARGED. (ACRE-FEET) DEPO**2.0*(AREA(J)-AREA(J-1))+SUM2 DEP0*(AREA(J)-AREA(J-1))+SUM2 TIME TAKEN TO FILL PERMANENT POOL. (F R S) TIME DURING INFLOW. (HOURS) VOLUME OF DISCHARGE USED IN COMPUTATION OF CENTME. VOLUME OF DISCHARGE USED IN COMPUTATICN OF CENTME. 122 C TRAP C TRP C Ti• C VAR C VELOC C VISCOS C VOL C VOLACT C VOLA• CVOLS• C VOLE• C VOLD C VOLC C VOLIN C VOLOUT C C VOLSED C VOLTME C VOLTOT C VOLUME C X1 C X2 C . TRAP EFFICIENCY. ( ) • INPUT VALUE OF REQUIRED TRAP EFFICIENCY. ( ) TIME SINCE THE START OF INFLOW. (HRS) • VARIABLE USED IN SMOOTHING CALCULATION. • FALL VELOCITY. (FEET/HOUR) • VISCOSITY OF THE FLOW. (CM.SO./SEC) • VOLUME OF EACH PLUG LAYER. (ACRE FEET) • INCREMENTAL CHANGE IN BASIN VOLUME. (ACRE FEET) — — • • • • • • • • • • VOLUME OF EACH PLUG. (ACRE—FEET) VOLUME OF FLOW BELOW THE SURFACE PLUG LAYER. (ACRE—FEET) VOLUME OF FLOW BELOW THE SECOND PLUG LAYER. (ACRE—FEET) VOLUME OF FLOW BELOW THE THIRD PLUG LAYER. (ACRE—FEET) VOLUME OF EACH LAYER ALLOWING SETTLING INTO THE NEXT LAYER. VOLUME OF INFLOW ACCOUNTED FOR AFTER EACH PLUG DISCHARGES. FRACTION OF INFLOW SEDIMENT LOAD ROUTED AT THE END OF EACH TIME POINT. CALCULATED CAPACITY AT EACH STAGE VALUE STAGO. (ACRE FEET) AVERAGE TIME DURING THE INFLOW OF EACH INCREMENT OF FLOW. TOTAL VOLUME OF INFLOW (ACRE—FEET) VOLUME OF INFLOW DURING EACH INFLOW TIME INCREMENT. (ACRE—FEET) ROUTING VOLUME USED TO SOLVE CONTINUITY EQUATION. (ACRE—FEET) ROUTING VOLUME USED TO SOLVE CONTINUITY EQUATION. (ACRE FEET) — COMMON/HOLD/INFLOW,MXPLLS/DELTAT DIMENSION FLOWIN(400),SIIEST(10,400),SI2OUT(10,400),PCTOUT(10p400) DIMENSION DEPTH1(400) , DEPTH2(400),DEPTH3(400)PDEPTH(400) DIMENSION PERCNT( 4 00) , X1(400),X2(400),SEDPLG(400),SFLNT(400) DIMENSION PLGVOL( 4 00),AROLD(400)/CAPNW(400),DIFF1400),STP(400) DIMENSION ACINFL(400),VOLUME(400)pSTARTV(400),STPV(400),STAGE(400) DIMENSION STAGEA( 4 00),CAPACA(400),T1(400),DISCHA(400),CAPAC(400) DIMENSION DISCH(400) , NFLNT(400),EFLNT(400),CAPC0(400),CONCED(40C) DIMENSION AREAA(400),AREAB(400),AREAC(400),AREAD(400),INFLOW(400) DIMENSION VOL(4,400),SED(4,400),VELOC(4,400),FALL(4,400) DIMENSION VOLC(3,400),DEP(4,400),PCT(4,400),PERCT(5,400) DIMENSION AREAS(50)PSIZE(50),OUTFL1(50),OUTFL2(50),OUTFL3(50) DIMENSION OUTFL4(50),STG1(50),DISCHB(50),AREA(50),DPTH(50) DIMENSION SI2ES(50),VOLA(400),VOLB(400),VOLE(400),VOLD(400) DIMENSION DIAMTR(5,400),VOLSED(400),VOLACT(400),SEDMNT(400) DIMENSION AVDPTH(400),AVSTG(400),STGIN(400),STGOUT(400),STAGO(400) DIMENSION STAREA(400),STGAR(400),ACOUT(400),VOLOUT(400),TMEIN(400) DIMENSION VOLTME(400),SEDTOT(400),SEDOUT(400),OUTPCT(20) DIMENSION PLGTME(400),VOLIN(400),DETTME(400),PLGCEN(400) DIMENSION STAG(400),AVDEP(400),SEDEND(400),SEDT(400) REAL OUTFL1pOUTFL2pOUTFL3p0UTFL4 REAL NFLNIPMASSPINFLOWPNSTORM READ(5,5100)NSTORM,CONSED,DEPOST,MASS,FLOW,TRP,FILTER,DENSTY,SGPVI 1SCOS IF(NSTORM.LT.0.0) DELTAT.CONSED IF(NSTORM.LT.0.0) LLS.0.0 IF(NSTORM.LT.0.0) CALL WASH IF(NSTORM .LT. 0.0) GO TO 3950 READ(5,5000) DELTAT,DELPLG,SET,SHORT,FIX,FLOWAV,FRACTN,SLAG,DEAD 5000 F0RMAT(9F8.0) READ(5,5200)MP,M,NsNS,MS,LS READ(5,5100)(PERCNT(NL),NL*1,NS) READ(5,5100)(SIZE(NL),NL•liNS) READ(5,5100)(STG1(I),I*1,N) READ(5,5100)(AREAS(I),I*1,N ) 20 READ(5 , 5100)(DISCHB(I),I*1,N) 5100 FORMAT(10F8.0) PO 40 I*1,N — 123 AREA(I)AREAS(I) OISCH(I)=DISCH8(I) STAGE(I)=STG1(I) 40 CONTINUE NNNeNSTORM DO 3900 IN=1,NNN READ (5,5100) NSTORM , CONSED , DEPOSTJMASSPFLOW,TRP,FILTER,DENSTY,SGoVI 1SCOS READ(5,5000) DELTAT , DELPLG , SET,SNORT,FIX,FLOWAV,FRACTNPSLAGsDEAD READ(5,5200)MP,M,NoNS,M5,LS LLS=LS IF(M.GT.LS) READ(5,5100)(INFLOW(I),I=1,M) IF(M.LE.LS.AND.LS.GT.0.0)READ(5,5100)(INFLOW(I),I=1,M) 1F(M.LE.LS) CALL WASH IF(M.LE.LS)M=MX IF(CONSED.GT.1.99.AND.CONSEO.LE.2.01) GO 10 60 GO TO 80 60 READ( 5, 5100) (CONCED(I),I.1,M) 80 CONTINUE DO 100 I=1,N AROLD(I)=AREA(I) STAG(I)=STAGE(I) 100 CONTINUE CAPC0(1)=0.0 PEAKIN=0.0 DO 120 .1=1), M • IF(INFLOW(J) .GT. PEAKIN .AND. J•GT. LS) PEAKIN=INFLOW(J) 120 CONTINUE DO 140 1=1,N DPTN(I)=STG1(I) 140 CONTINUE IF(FLOW.GT.3.99.AND.FLOW.LE.4.01) GO TO 260 DO 160 I=1,MP OUTFL1(I)=25.0 OUTFL2(I)=25.0 OUTFL3(I)=25.0 OUTFL4(I)=25.0 160 CONTINUE IF(FLOW.GT.2.99.AND.FLOW.LE.3.01) GO TO 200 DO 180 I=1,MP IF(FLOW.GT.0.99.AND.FLOW.LE.1.01) GO TO 240 OUTFL1(I)=0.0 OUTFL2(I)=0.0 OUTFL3(I)=0.0 OUTFL4(I)=100.0 180 CONTINUE GO TO 240 200 DO 220 I=1,MP OUTFL1(I)=100.0 0UTFL2(I)=0.0 OUTFL3(I)=0.0 0UTFL4(I)=0.0 220 CONTINUE 240 CONTINUE GO TO 280 260 CONTINUE 5200 FORMAT(6I8) READ(5,5100)(DPTN(I),I=1,MP) READ(5,5100)(OUTFL1(I),I=1,MP) RE4D(5,5100)(OUTFL2(I),I.1.01P) READ(5,5100)(OUTFL3(I),I=1,MP) READ(5,5100HOUTFL4(I),I.1,MP) 280 CONTINUE 124 WRITE (5,5300) 5300 FORMAT(1H1) WRITE(6.5400) 5400 F 0 RMAT(// , 15X,"*************** ******* ********* THE DEPOSITS MODEL. 1 JANUARY 1979 «) WRITE (6,5500) 5500 FORMAT(////,45X,"***** INPUT CONTROL VARIABLES *****") WRITE (5,5500) 5600 FORMAT(//,15X,"MP",BX,"M",9X,"N",10X."NS",7X."MS",7X,"LS") WRITE(6 , 5700)MP,M.N,NS.MS,LS 5700 FORMAT(//p7X,6I10) WRITE (6,5800) 5800 FORMAT(//,15X,"NSTORM",4X,"CONSED",4X,"DEPOST",4X,"FLOW".6X,"TRP". 17 X , "FILTER" ,4 X , "FIX",7X,"FRACTN",7X,"FLOWAV") WRITE (6,5900 )NSTORM , CONSED , DEPOST.FLOW,TRP,FILTER,FIX,FRACTN 1 .FLOWAV 5900 FORMAT(//p9X,8F10.2,6X,F10.2) IF(FRACTN.LE.0.1) GO TO 300 WRITE (5,6000) 6000 FORMAT(//,15WINFLOW SEDIMENT DISTRIBUTION",10WDENSITY CURRENT" 1) GO TO 320 300 WRITE(6,6100) 6100 FORMAT(//p15X,"INFLOW SEDIMENT DISTRIBUTION",10WCOMPLETE MIXING" 1) 320 CONTINUE WRITE( 5,6200) 6200 FORMAT(// , 15X , "MASS",7X."VISCOS",5X,"DELTAT",4X,"DELPLG",4X 1 "DENSTY" , 6X,"SG",8X,"SET",6X,"SHORT",6Xs"SLAG",6X,"DEAD") WRITE(6,6300) MASS , VISCOS,DELTAT,DELPLG,DENSTY,SG,SET,SHORT,SLAG, 10E AD 6300 FORMAT(//,11X,F10.3,2X,F10.408F10.2) WRITE(6,6400) 6400 FORMAT(//,45X,"***** DEPOSITS ERROR MESSAGES *****") IF(VISCOS.LE.0.005) WRITE(6,6500) IF(VISCOS.GE.0.2) WRITE( 6,6500) IF(M .GT. 400) WRITE(6,6450) 6450 FORMAT(//.15X,"***** ERROR ***** • INFLOW ARRAY STORAGE EXCEEDED. 1") 6500 FORMAT(//,15X," ERROR ***** • USE DEFAULT VISCOS • 0.0114 CM. 1S0./SEC.") IF(SG.LE.1.0) WRITE(6,6600) IF(SG•GE.4.0) WRITE(6,6600) IF(MS.GT•400) WRITE(6,6550) 6550 FORMAT(//,15X,"***** ERROR ***** • OUTFLOW ARRAY STORAGE EXCEEDED. 1") 6600 FORMAT(//p15X,"***** ERROR ***** • USE DEFAULT SG • 2.65 •") IF(SG.LE.1.0) 5G-2.65 IF(SG•GE.4.0) SG-2.65 IF(VISCCS•LE.0.005) VISCOSm0.0114 IF(VISCOS.GE.0.2) VISCOS .0.0114 IF(N.GT•50) WRITE( 6,6550) IF(M.GT•400) Mm399 IF(MS•GT•400) MS.399 IF(N.GT•50) Nm49 THE VALUE OF NS CANNOT EXCEED 10. IF(NS.GT•10) NSm10 6650 FORMAT(//,15X," ERROR ***** • BASIN GEOMETRY ARRAY STORAGE 1 EXCEEDED.") IF(STAGE(1).GT.0.001) WRITE (5,6700) 6700 FORMAT(//p15X,"***** ERROR ***** • ELEVATION VALUES CHANGED TO STA 1GE VALUES.") DO 340 I•lsN 125 STAGE(I).STAGE(I)—STAGE(1) 340 CONTINUE AVDEP(1).0.0 X1(1).0.0 X2(1).0.0 FLOWIN(1).INFLOW(1) AVTME=0.0 CAPAC(1)80.0 CAPNW(1).0.0 AVDPTH(1)=0.0 DO 360 J.2,N CAPAC(J) . (AREA(J)+AREA(.1-1))*(STA6E(J)-5TAGE(J-1))/2.04.CAPAC(J-1) CAPNW(J).CAPAC(J) IF(DISCH(J).E0.0.0) VAR-STAGE(J) X 1 (J)=CAPAC(J)—(DISCH(J)/2.0)*DELTAT*.08264 X 2 (J).CAPAC(J)+(DISCH(J)/2.0)*DELTAT*.08264 CAPCO(J) . (AREAS(J)+AREAS(J-1))*(STG1(J)—STG1(J-1))/2.0+CAPCO(J-1) 360 CONTINUE C C C C IF NO LS IF THE PERMANENT POOL IS TO BE FILLED INTERNALLY BY THE PROGRAM DUMMY VALUES SHOULD BE ENTERED TO FILL THE PREMANENT POOL. MUST BE ENTERED AS ZERO. YOU USE THE WASH MODEL, M MUST ALSO BE SET TO ZERO. DO 980 J.1,N IF(DISCHB(J) • LE. 0.001) CAPOOL.CAPAC(J) 980 CONTINUE AVSTG(1)=0.0 C SEDMNTs SEDEMENT CONCENTRATION FOR EACH TIME INCREMENT (VOLUMETRIC). NFLNT(1)-0.0 CAP-0.0 SEDMNT(1).0.0 SEDTOT(1)=0.0 TOTVOL.0.0 CENTME.0.0 TOTAL-O.0 STORM.0.0 SEDOUT(1).0.0 VOLSED(1).0.0 ACINFL(1)=0.0 MM.M+1 DO 440 I.2,N SUM1.0.0 SUM2.0.0 DO 380 J.2,I IF(AREA(J).EQ.AREA(J —1)) GO TO 460 DEPO. STAGE (I)—(STAGE(J)+STAGE(J-1))/2.0 SUM1.DEPO**2.0*(AREA(J)—AREA(J-1))+SUM1 SUM2.0EP0*(AREA(J)—AREA(J-1))+SUM2 380 CONTINUE IF(SUM2.LE.0.0) GO TO 400 AVDPTH(I).SUM1/SUM2 GO TO 420 400 AVOPTH(1).0.0 420 CONTINUE 440 CONTINUE GO TO 540 460 DO 520 J.2,N IF(CAPAC(J).LE.0.0) GO TO 480 AVDEP(J).(CAPAC(J-1)IAVDEP(J-1)+(CAPAC(J)—CAPAC(J-1))*(STAGE(J)+ST 1AGE(J-1))/2.0)/CAPAC(J) AVDPTH(J).(STAGE(J)—AVDEP(J))*2.0 GO TO 500 480 AVDPTH(J).0.0 AVDEP(J)-0.0 126 500 CONTINUE 520 CONTINUE 540 CONTINUE DO 560 S.MM,MS INFLOW(I).0.0 560 CONTINUE ACINFL(1)=CAPOOL BPOOL.CAPOOL VOLUME(1).CAPOOL DO 580 1=2,MS ACINFL I ACINFL(I 1)+C(INFLOW(I-1)+INFLOW(1))/2.0)*OELTAT*.08264 VOLUME(I)=ACINFL(I)-ACINFL(I-1) 580 CONTINUE STAREA(1).0.0 STP(1)=CAPOOL STGAR(1).0.0 SUMTME.0.0 VOLTOT=0.0 STARTV(1)=CAPOOL STAGEA(1).0.0 CAPACA(1)=0.0 DISCHA(1).0.0 T1(1).0.0 MR.(MS)/(DELPLG/DELTAT)+.01 PEAK-C. 0 DO 600 I=MM,MS CONCED(I)=0.0 600 CONTINUE IF(CONSED.GT.1.99.AND.CONSED.LE.2.01) MASS-0.0 DO 740 4=2.MS IF(CONSED.GT.1.99.AND.CONSED.LE.2.01) GO TO 620 IF(SET .LT. 1.0) ST-Z.0 SEDMNT(J)*(VOLUME(J)**SET) IF(LS.GE.J) SEDMNT(J)=0.0 IF(SLAG.GT.O.O.AND.SLAG.LT.1.01) 5EDMNT(J-1).SEDMNT(J) IF(SLAG.GT.1.01.AND.J.GT.2) SEDMNT(J-2)=SEDMNT(J) IF(J.EO.MS.AND.SLAG.GT.0.0) SEDMNT(J).0.0 IF(J.EO.MS.AND.SLAG.GT.0.0) SEDMNT(J-1)-0.0 GO TO 640 620 SEDMNT(J).(CONCED(J)+CONCED(J-1))*VOLUME(J)/(SG*2000.0) MASS.MASS+0.001359*(CONCED(J)+CONCED(J-1))*VOLUME(J)/2.0 640 CONTINUE IF(J.GT.LS) STORM • STORM + VOLUME(J) SEDTOT(J)=SEDTOT(J-1)+5EDMNT(J) IF(CONSED.GT.1.99.AND.CONSED.LE.2.01) GO TO 650 IF(SLAG.GT.O.O.AND.SLAG.LT.1.01) SEDTOT(J-1)=SEDTOT(J) IF(SLAG.GT.1.01.4ND.J.GT.2) SEDTOT(J-2)=SEDTOT(J) 650 STP(J).STP(J-1)+VOLUME(J) STPV(J-1)=STARTV(J-1)+VOLUME(J) C DO AN ITERATION TO FIND STAGE FROM STPV DO 660 K.2,N IF(STPV(J-1).LT.X2(K))G0 TO 680 IF(STPV(J-1).GT.X2(N)) GO 10 3860 660 CONTINUE 680 STAGEA(J).STAGE(K-1)+((STPV(J-1)-X2(K-1))/(X2(K)-X2(K-1)))*(STAGE( 1K)-STAGE(K-1)) AVSTG(J)=AVOPTH(K-1)+USTPV(J-1)-X2(K-1))/(X2(K)-X2(K-1)))*(AVDPTH 1(K)-AVDPTH(K-1)) CONTINUE DO 700 KK.2,N IFISTAGEACJI.LT.STAGE(KK)) GO 10 720 IF(STAGEA(J-1).GT.STAGE(N) ) GO 10 3860 700 CONTINUE ( ). - 127 720 CAPACA(J).X1(KK-1)+((STAGEA(J)—STAGE(KK--1))/(STAGE(KK)...STAGE(KK-1) 1))*(X1(KK)-•X1(KK-1)) C DO AN ITERATION TO FIND DISCHARGE FOR STAGEA DISCHA ( .1). DISCH(KK - 1)+USTAGEA(J)—STAGE(KK-1))/(STAGE(KK)—STAGE(KK 1 - 1)))*(DISCH(KK)—DISCHMK--1)) IF(DISCHA(J).GT.PEAK)PEAK.DISCHA(J) CONTINUE STARTV(J).CAPACA(J) IF(STARTV(J).LT.0.0) STARTV(J).0.0 1 1( 4 ).(J..-1)*0ELTAT IF(J.GT.LS) SUMTME.SUMTME+(4-1.-LS)*DELTATSVOLUME(J) 1F(J.GT.LS) VOLTOT.VOLTOT+VOLUME(J) STAREA(J) . ABSUAVSTG(J)+AVSTG(J-1))*(DELTAT/2.0)) STGAR(4).STAREA(J)+STGAR(J-1) C THIS PART OF THE PROGRAM DIVIDES THE OUTLET HYDROGRAPH INTO PLUGS OF EQUAL C TIME INCREMENT DELPLG. THE PLUG IS THEN ROUTED THROUGH THE RESERVOIR AND C THE DETENTION TIME,STAGE AT OUTFLOW, AVERAGE DEPTH AND THE VOLUME OF C THE PLUG IS DETERMINED. 740 CONTINUE PFLNT.0.0 IF(CONSED.GT.1.99.AND.CONSED.LE.2.01) GO TO 860 C PFLNT WILL BE THE PEAK INFLOW CONC_ DO 820 JS.2sM IF(VOLUME(JS).E0.0.0) GO TO 780 NFLNT(JS).(SEDMNT(JS)*1.*MASS*735.48)/(VOLUME (4 S)*SEOTOT(M)) IF(NFLNT(JS).GT.PFINT) GO TO 760 GO TO 800 760 PFLNT.NFLNT(JS) GO TO 800 780 NFLNT(JS).0.0 800 CONTINUE 820 CONTINUE 14.0 DO 840 IK.2,M IF(NFLNT(IK).E0.0.0) GO TO 840 IJ.IJ+1 SFLNT(IJ).NFLNT(IK) 840 CONTINUE GO TO 900 860 DO 880 J 5 .1,M NFLNT(JS)=CONCED(JS) IF(NFLNT(JS).GT.PFLNT)PFLNT.NFLNT(JS) 880 CONTINUE 900 CONTINUE DO 920 J.J.MM,MS NFLNT(44).0.0 920 CONTINUE DO 940 1.1,4 SED(I,J).0.0 DIAMTRUI,J).0.0 VELOC(I,4).0.0 FALL(I,J).0.0 VOL(I,J)=0.0 PCT(I,J).0.0 VOLC(I,J).0.0 940 CONTINUE SEDPLG(1).0.0 SUMVOL.0.0 STRMOT=0.0 SEDEND(1).0.0 DEPTH(1).0.0 ACOUT(1) . 0.0 128 PLGVOL(1).0.0 PLGTME(1).0.0 VOLOUT(1).0.0 VOLIN(1).DEAD TMEIN(1).0.0 SEDT(1).0.0 DETTME(1)=0.0 PLGCEN(1).0.0 VOLTME(1)=0.0 AREAA(1).0.0 AREAB(1).0.0 AREAC(1).0.0 AREAD(1).0.0 VOLA(1).0.0 VOLB(1).0.0 VOLE(1).0.0 VOLD(1).0.0 DEPTH(1)80.0 DEPTH2(1)=0.0 DEPTH3(1).0.0 DO 960 Lm2,MS ACOUT(L).ACOUT(L 1)+((DISCHA(L-1)+DISCHA(L))/2.0)*DELTAT*.08264 - 960 CONTINUE PSTAGO.0.0 PEFLNT-0.0 C PEFLNT WILL BE THE PEAK EFFLUENT CONC. C PSTAGO WILL BE THE PEAK STAGE DEL.0.0 DO 2420 NN.21MR PLGTME(NN).PLGTME(NN -1) + DELPLG LR.(DELPLG+.01)/DELTAT P.LR*(NN -1)+1 PLGVOL(NN).ACOUT(P)-ACOUT(P-LR) VOLIN(NN).VOLIN(NN-1)+PLGVOL(NN)*SHORT IF(VOLIN(NN).GT.CAPOOL.AND.VGLIN(NN-1).LT.CAPOOL) T.PLGTMENN) IF(T.GT.DEL) TwDEL IF(SHORT.LE.1.000)SHORT.1.0 PLGCEN(NN) • (PLGTME(NN) + PLGTME(NN-1)1/2.0 C DO AN ITERATION TO FIND TMEIN FROM VOLIN DO 1000 NP.2..M IF(VOLIN(NN) .LT. STP(NP) .AND. VOLIN(NN) .LE. STP(NP-1)) GO TO 10 125 IF(VOLIN(NN).LT.STP(NP)) GO 10 1020 1000 CONTINUE GO TO 1025 1020 TMEIN(NN)=T1(NP-1)+((VOLIN(NN)-STP(NP- 1) )/(STP(NP)-STP(NP-1)))*DEL 1TAT GO TO 1035 1025 TMEIN(NN)-0.0 1035 CONTINUE FLOWIN(NN)=INFLOW(NP) IF(FLOWAV.GT.0.0) GO TO 1040 GO TO 1120 1040 DO 1060 I•1,NS IF(FLOWIN(NN).E0.0.0.AND.FLOWIN(NN-1).EC.0.0) GO TO 1080 SIZEST(I,NN).(2.*FLOWAV/(FLOWIN(NN)+FLOWIN(NN-1)))**.3*PERCNT(I) IF(SIZEST(1,NN).GT.100.) SIZEST(IpNN)=100. 1060 CONTINUE GO TO 1100 1080 SIZEST(I,NN).PERCNT(I) 1100 CONTINUE 1120 CONTINUE VOLTME(NN)m(TMEIN(NN)+TMEIN(NN-I))/2.0 129 DETTME(NN).PLGCEN(NN)-VOLTME(NN) IF(DETTME(MN).LT.0.0) DETTME(NN).0.0 SEDTINN) . SEDTOT(NP - 1)+((VOLIN(NN)-STP(NP-1))/(STP(NP)-STP(NP-1))) 1*(5EDTOT(NP)-SEDTOT(NP-1)) IF((VOLIN(NN)-STP(NP -1)) .LT. 0.0) SEDTINN)80.0 SEDOUT(NN).(SEDT(NN)-SEDT(NN-1))/SEDTOT(M) STGIN(1).0.0 STGOUT(1).0.0 STAGO(1).10.0 DO 1140 II.2,MS IF(VOLTME(NN).I.T.T1(II)) GO 10 1160 IF(VOLTME(NN).GE.T1(MS)) GO TO 2080 C DO AN ITERATION TO FIND DEPTH FOR VOLTME 1140 CONTINUE 1160 STGIN(NN).STGAR(II-1) 4. A8S(UVOLTMENN)-T1(II-1))/(71(II)-T1(II-1)) 1)*(STGAR(II)-STGAR4II-1))) CONTINUE DO 1180 II.2,MS IF(PLGCEN(NN).LT.T1(II)) GO TO 1200 C DO AN ITERATION TO FIND DEPTH FOR PLGTME 1180 CONTINUE 1200 STGOUT(NN).STGAR(II-1)+((PLGCEN(NN)-T1(II-1))/(71(II)-71(II-1)))*( 1STGAR(II)-STGAR(II-1)) STAGO(NN).STAGEACII-1)+((PLGCEN(NN)-71(II-1))/(71(II)-T1(II-1)))*( 1STAGEA(II)-STAGEA(II-1)) IF(DETTME(NN).LE.0.0) DETTME(NN).0.0 IF(STAGO(NN).GT.PSTAGO) GO TO 1220 GO TO 1240 1220 PSTAGO.STAGO(NN) 1240 IF(DETTME(NN).E0.0.0) GO TO 2120 DEPTH(NN).(STGOUT(NN)-STGIN(NN))/DETTME(NN) If(DEPTH(NN).LE.0.0) DEPTH(NN)=0.0 DEPTH1(NN)*0.75*DEPTH(NN) DEPTH2(NN)=0.5*DEPTH(NN) DEPTH3(NN)=0.25*DEPTH(NN) DO 1260 LM=2,N IF(DEPTH(NN).LT.STAGE(0)) GO 10 1280 1260 CONTINUE 1280 VOLA(NN). CAPAC(LM-1)+((DEPTH(NN)-STAGE(LM- 1))/(STAGE(LM)-STAGE(LM 1-1)))*(CAPAC(LM)-CAPAC(LM -1)) AREAA(NN)=AREA(LM-1)+((DEPTH(NN)-STAGE(LM-1))/(STAGE(LM)-STAGE(LM 11)))*(AREA(LM)-AREA(LM-1)) CONTINUE C CAPSAV WILL COMPUTE THE CAPACITY AT PEAK STAGE DO 1300 I.1.2,N IF(PSTAGO.LE.STG1(IJ)) GO TO 1320 1300 CONTINUE GO TO 1340 1320 CAPSAV.CAPAC(IJ-1)+ ((PSTAGO-STG1(IJ-1))/(STG1(IJ)-STG1(IJ-1))) 1*(CAPAC(IJ)-CAPACCIJ-1)) 1340 DO 1360 LM=2,N IFIDEPTH1(NN).LT.STAGE(LM)) GO 10 1380 1360 CONTINUE CONTINUE 1380 VOLUNN)=CAPAC(LM-1)+C(DEPTH1(NN)-ST4GE(0-1))/(STAGE(LM)-STAGE(LM 1-1)))*(CAPACUM)-CAPAC (LM-1)/ AREAB(NN)RAREAUM-1)+C(DEPTH1(NN)-STAGE(LM-1)1/(STAGE(LM)-STAGE(LM 1-1)))*(AREA(LM)-AREA(LM-1), CONTINUE DO 1400 LM=2,N IF(DEPTH2(NN).LT.STAGE(LM)) GO TO 1420 1400 CONTINUE 1420 VOLE(NN). CAPAC(LM-1)+((DEPTH2(NN)-STAGE(LM-1,)/(STAGE(LM)-STAGE(1. 130 1M - 1)))*(CAPAC(LM)—CAPACUM —1)) AR E AC(NN)*AR EA ( LM -1) + ( lDEPTH 2 (NN) — STAGE(LA-1))/(STAGE(LM)—STAGEILM 1 - 13))*(AREA(01)4.AREA(M-1)) CONTINUE DO 1440 LM=2,N IF(DEPTH3(NN).LT.STAGE(LM)) GO TO 1460 1440 CONTINUE 1460 VOLD(NN)* CAPAC(LM-1)+((DEPTH3(NN)—STAGE(LR-1))/(STAGEUM)—STAGEIL 1M - 1)))*(CAPAC(LM)—CAPACILM-1)) AREAD ( NN )= AREA(LM -1 )+C(DEPTH3(NN)—STAGE(LM-1))/(STAGE(LM)—STAGE(LM 1 .41)))*(AREAILM).4AREA(01-1)) CONTINUE VOL(1,NN).VOLA ( NN)—VOL8(NN) VOL(2 , NN).VOLB(NN)—VOLE(NN) VOL(3,NN).VOLE(NN)—VOLD(NN) VOL(4,NN).VOLD(NN). FALL(1,NN).0.875*DEPTH(NN)*FIX fALL(2,NN)=0.625*DEPTHINN)*FIX FALL(3,NN).0.375*DEPTH(NN)*FIX FALL(4,NN).0.125*DEPTH(NN)*FIX IF(PLGVOL(NN).1T..00001) GO TO 2080 VELOC(1,NN).FALL(1,NN)/(DETTME(NN)) VELOC(2,NN)-FALL(2)NN)/(DETTME(NN)) VELOC(3,NN).FALL(3,NN)/IDETTMECNN)) VELOC(4,NN)=FALL(4,NN)/(DETTME(NN)) DIAMTR(1 , NN).30RT(VELOC(1,NN)*VISCOS/(51.5*(SG-1))) DIAMTR(2 , NN).SORTIVELOC(2,NN)*VISCOS/(51.5*(SG-1))) DIAMTR(3 , NN)=SORTCVELOC(3,NN)*VISCOS/(51.5*(SG-1))) DIAMTR( 4, NN)=SORT(VELOC(4,NN)*VISCOS/(51.5*(SG-1))) CONTINUE IF(FLOWAV.GT.0.0) GO TO 1640 DO 1480 LP.2,NS IF(DIAMTR(1,NN).L.T.SIZE(LP)) GO TO 1500 1480 CONTINUE 1500 PERCT(1 , NN).PERCNTUP - 1)+( (DIAMTR(1,NN)—SI2E(LP-1))/(SIZE(LP)—SIZE 1(LP —1)))*(PERCNT ( LP)—PERCNT(LP —1)) DO 1520 LP*2,NS IF(DIAMTR(2/NN).LT.SI2E(LP)) GO TO 1540 1520 CONTINUE 1540 PERCT(2,NN)=PERCNT(LP-..1)+((DIAMTR(2,NN)—SIZE(LP-1))/(SI2E(LP)—SIZE 1(LP*1))).0(PERCNTUP) —PERCNT(LP —1)) DO 1560 LPs2,NS IF(DIAMTR(3pNN).LT.SIZE(LP)) GO TO 1580 1560 CONTINUE 1580 PERCT(3,NN).PERCNT(0-1)+I(DIAMTR(3,NN)—SIZE(LP-1)3/(5IZEILP)—SIZE 1(LP-1)))*(PERCNT(LP)—PERCNT(0-1)) DO 1600 LP.2,NS IF(DIAMTR(4,NN).I.T.SIZE(LP)) GO TO 1620 1600 CONTINUE 1620 PERCT(4,NN)=PERCNT(LP-1)+((DIAMTR(4,NN)—SIZE(LP-1))/(SIZE(LP)—SI2E l(LP-1)))*(PERCNT(LPC—PERCNT(LP-1)/ GO TO 1820 1640 DO 1660 LP.2/N5 IF(DIAMTR(1,NN).LT.SIZE(LP)) GO TO 1680 1660 CONTINUE 1680 PERCT(1,NN).SIZEST(LP-1,NN) .0(IDIAMTR(1,NN)—SIZE(LP-1))/(SIZE(LP) 1— SIZE( LP-1)))*(SIZEST(LP,NN)—SIZEST(LP-1,NN)) DO 1700 LP.2,NS IftDIAMTR(2,NN).I.T.SIZE(LP)) GO TO 1720 1700 CONTINUE 1720 PERCT(2,NN).SI2EST(LP-1,NN) +((DIAMTR(2,NN)—SIZE(LP-1))/(SIZE(0) 1 —SIZE( 0-1 )))*(SIZEST(LP,NN)—SIZEST(LP-1,NN)) 00 1740 LP=2,NS 131 IF(DIAMTR(3,NN).LT.SIZE(LP)) GO TO 1760 1740 CONTINUE 1760 PERCT(3,NN).SIZEST(LP-1,NN) +((DIAMTR(3,NN)—SIZE(LP1))/(SIZE(LP) 1— SIZE( LP• 1 )))*(SIZEST(LP,NN)—SIZEST(LP-....1,NN)) DO 1780 LF*2,NS IF(DIAMTR(41,NN).LT.SI7E(LP)) GO TO 1800 1780 CONTINUE 1800 PERCT( 4, NN).SIIEST(LP1,NN) +((DIA)TR(4 , NN)SIZE(LP-1))/(SIIE(LP) 1 SIZE(LP1)))*(SIZEST(LP,NN)-4SIZEST(LP1,NN)) 1820 CONTINUE VOLC( 1, NN).V0L(1 , NN)*(2.0*AREAB(NN)/(AREAA(NN)+4REA8(NN))) VOLC( 2, NN) . V01(2 , NN)*(AREAC(NN)*2.0/(AREAC(NN)+AREA8(NN))) VOLC(3 , NN).VOL(3,NN)*(2.0*AREAD(NN)/(AREAC(NN)+AREAD(NN))) IF(VOL(2,NN).LE.0.0) GO TO 2080 IF(FR#CTN.GT.0.0j) GO TO 2000 PCT(1,NN) .PERCT(4,NN) 0IFF(NN).(STAGO(NN)...-VAR)4.2.0 IF(DIFF(NN).GT.0.0.AND.DIFF(NN).LT..125*DEPTH(NN)) GO TO 1840 GO TO 1980 1840 DIAMTR(5 , NN)*SORT(DIFF(NN)*VISCOS/(51.5*(SG-1)*DETTME(NN))) IF(FLOWAV.GT.0.0) GO TO 1900 DO 1860 LP=2,NS IF(DIAMTR(5,NN).LT.SIZE(LP)) GO TO 1880 1860 CONTINUE 1880 PERCT(5,NN).PERCNT(Lp1)+((OIAPjTR(5,NN)—SIZE(1.1 1-.- 1) )/(SIZE(LP)SIZE l(LP ..1)))*(PERCNT(LP)PERCNT(LP —1)) GO TO 1960 1900 DO 1920 LP.2,NS IF(DIAMTR(5,NN).LT.SIZE(LP)) GO TO 1940 1920 CONTINUE 1940 PERCT(5,NN)=SIZEST(LP-.-1,NN) +((DIAMTR(5,NN)—SIIE(LP-1))/(SIZE(LP) 1 —SIZE(LP1)))*(SIZEST(LPoNN)—SIZEST(LP...1,NN)) 1960 CONTINUE IF(DIFF(NN).1.7.0.125*DEPTH(NN))PCT(1,NN).PERCT(5,NN) 1980 CONTINUE IF(PERCT(1,NN).I.T.O.0)PERCT(1,NN).0.0 IF(PERCT(2,NN).LT.0.0)PERCT(2,NN).0.0 IF(PERCT(3,NN).L7.0.0)PERCT(3,NN).0.0 IF(PERCT(4,NN).LT.0.0)PERCT(4,NN).0.0 IF(PERCT(1,NN).GT.100.)PERCT(1,NN).100. IF(PERCT(2,NN).GT.100.)PERCT(2,NN)=100. IF(PERCT(3,NN).GT.100.)PERCT(3,NN).100. IF(PERCT(4,NN).GT.100.)PERCT(4,NN).100. PCT(2,NN).(VOL(2,NN)*PERCT(4,NN)+VOLC(1,NN)*(PERCT(3,NN)..-PERCT(4,N 1N)))/VOL(2,NN) PCT(3,NN).(VOL(3,NN)*PERCT(4,NN)+VOLC(2,NN)*(PERCT(2,NN)—PERCT(4,N 1N)))/VOL(3,NN) PCT(4,NN).(VOL(4,NN)*PERCT(4,NN)+VOLC(3,NN)*(PERCT(1,NN)—PERCT(4,N 1N)))/VOL(4,NN) GO TO 2020 2000 PCT(1,NN)•0.0 PCT(2,NN)80.0 PCT(3,NN).0.0 PCT(4,NN).PERCT(4,NN) 2020 CONTINUE DO 2040 LM-2,N IF(STAGO(NN).LT.DPTH(LM)) GO TO 2060 2040 CONTINUE 2060 SED(1,NN).PCT(1/NN)*SE0OUT(NN)*(OUTFL1(LM-1)+((STAGO(NN)—OPTH( L M-1 1))/(OPTH(LM) OPTH(LM-11))*(OUTFL1(LM)—OUTFL1(01-1 ) )) SED(2,NN)=PCT(2,NN)SEEDOUT(NN)*(OUTFL2(LM-1)+(ISTAGO(NN)—DPTH(LM-1 1))/(DFTH(LM) — OPTH(LM .-1)))*(OUTFL2(LM)-0UTFL2(04-1))) SED(3 , NN).PCT(3JINN)*SEDOUT(NN)*(0UTFL3(LM..-1)+((STAGO(NN).-..DPTH(L-1 — 132 1))/(DPTH(LM) DPTH(LM ...1)))*(OUTFL3(LM)OUTFL3(01-+1))) SED(4,NN)*PCT(4,NN)*SEDOUT(NN)*(OUTFL4(LM-1)+((STAGO(NN) —DPTH(LM-1 1))/(OPTH(LM) OPTH(LM-1)))*(OUTFL4(LM)—OUTFL4(LM-1))) SEDPLG(NN )•(SED(1,NN)+SED(2,NN)+SED( 3,NN )+SED(4oNN) ) /100.0 IF(SEDPLG(NNI.GT.SEDOUT(NN)*100.)SEDPLG(NN).100.4.SEDOUT(NN) GO TO 2100 2080 SEDPLG(NN).0.0 PCT(1,NN).0.0 PCT(2,NN)=0.0 PCT(3,NN).0.0 PCT(4,NN).0.0 2100 CONTINUE GO TO 2140 2120 SEDPLG(NN).100.0*SEDOUT(NN) PCT(1,NN).100.0 PCT(2yNN).100.0 PCT(3,NN).100.0 PCT(4,NN)*100.0 IF(DEPTH(NN).LE.0.0) DEPTH(NN).0.0 2140 CONTINUE SEDEND(NN).SEDEND(NN-1)+SEDPLG(NN) DO 2200 L5=1,NS IF(FLOWAV.LE.0.0) SIZEST(LS,NN).PERCNT(LS) PCTOUT(L.S,1).0.0 IF(SEDPLG(NN).LE.0.0) GO TO 2160 SUOUT(LSAN).100.*SEDOUT(NN)*SIIEST(LS,NN)/SEDPLG(NN) IF(SIZOUT(LS,NN).LE.0.0)SIZOUT(LS,NN).0.0 GO TO 2180 2160 SIZOUTILS,NN)=SIZEST(LSPNN) SEDPLG(NN).0.0 2180 CONTINUE IF(SIZOUT(LS,NN).GT.100.),SIZOUTILS,NN).100. PCTOUT(LS,NN)=PCTOUT(LS,NN-1)+SEDPLG(NN)+SIZOUT(LS,NN) 2200 CONTINUE VOLOUT(NN)=SEDOUT(NN)+VOLOUT(NN-1) ACT.1.001*(STRMOT+CAPOOL—DEAD) IF(ACT •GT. STORM) GO TO 3440 IF(PLGVOL(NN).E0.0.0) GO TO 2240 EFLNT(NN)u(SEDPLG(NN)/PLGVOL(NN))*MASS*7.3548 IF(EFLNT(NN).GT.PEFINT) GO TO 2220 GO TO 2260 2220 PEFLNT.EFLNTINN) GO TO 2260 2240 EFLNT(NN).0.0 2260 CONTINUE IF(PLGTMEINN) •GT. DEL) TOTAL.TOTAL+PLGCEN(NN)*PLGVOL(NN) IF(PLGTME(NN).GT.DEL) TOTVOL • TOTVOL +PLGVOL(NN) IF(TOTVOL.GT.0.0) CENTME.TOTAL/TOTVOL—SUMTME/VOLTOT IF(VOLIN(NN) .GT. 8POOL) AVTME.AVTME+(DETTME(NN))*PLGVOL(NN) IF(VOLIN(NN).GT.E(POOL) SUMVOL.SUMVOL+PLGVOL(NN) IF(SUMVOL.GT.0.0) DETAVE+AVTME/SUMVOL IF(VOLIN(NN).GT.BPOOL) STRMOT.STRMOT+PLGVOL(NN) IF(CENTME.LE.0.0) CENTME.DETAVE STRMTM.(CENTME*STRMOT+(DETTME(NN-1)*(STORM—STRMOT)))/STORM AVETMEs(DETAVE*STRMOT+DETTME(NN-1)*(STORM STRMOT))/STORM IF(STRMOT.GT.STORM/AVETME.DETAVE IF(STRMOT.GT.STORM) STRMOT-STORM IF(DEPOST.LT.1.99) GO 10 2420 DEP(1,NN)=MASS+0.0007360*(100.0—PCT(1,NN))*SEDCUT(NN)*(CUTFL1(LM 1 1)+( CSTAGOINNi—OPTHUM-1))/(OPTH(LM)—DPTH(LM-1)))*(OUTFL1(01) OUTFL 11(LM-1)))1(10U00.0*DENSTY) DEP(2,NN).MASS*0.0007360*(100.0—PCT(2,NN))*SEDOUT(NN)*(OUTFL2(LM 1 1)+USTAGO(NN)—DPTH(LM-1))/(DPTH(LM)—OPTH(LM-1)))*(OUTFL2(LM)—OUTFL — . — — - — - 133 1) +I(STAGO ( NN) - DPTH(LM- 1))/(DPTH(LM) - DPTH(L(j-1)))*(OUTFL3(LM)-OUTFL 13(LM-1)))/(10000.0*DENSTY) DEP (4, NN ) =MASS* 0 . 0007360 *(100.0- PCT(4,NN))*SEDOUT(NN)*(OUTFL4(LK-1 1) +USTAGO(NN) - DPTH(LM - 1))/(DPTH(LM)DPTH(LM-1)))*(OUTFL4(LM)-OUTFL 14(LM-1)))/(10000.0*DENSTY) C THIS PART OF THE PROGRAM DETERMINES THE CHANGE IN BASIN CAPACITY C DUE TO DEPOSITION. DO 2400 I=1,N 1F(AVDPTH(I).LT.DEPTH3(NN)) GO TO 2320 IF(AVDPTH(I).LT.DEPTH2(NN)) GO TO 2340 IF(AVOPTH(I).LT.DEPTH1(NN)) GO TO 2360 IF(AVDPTH(I).L.T.DEPTH (NN)) GO TO 2380 CAPNW(I)=CAPNW(I)-(DEP(4,NN)+DEP(3,NN)+DEP(2,NN)+DEP(1,NN)) GO TO 2400 2320 CAPNW(I)=CAPNW(I)-DEP(4,NN)*AVDPTH(I)/DEPTH3(NN) GO TO 2400 2340 CAPNW(I)=CAPNW(I)-(DEP(4,NN)+DEP(3,NN)*(AVDPTH(I)-DEPTH3(NN))/DEPT 1H2(NN)) GO TO 2400 2360 CAPNW(I)=CAPNW(I)-(DEP(4,NN)+DEP(3,NN)+DEP(2,NN)..(DEP(2,NN)*(AVOPT 1H(I)-DEPTH2(NN))/DEPTH1(NN))) GO TO 2400 2380 CAPNW(I)=CAPNW(I)-(DEP(4,NN)+DEP(3.NN)+DEP(2.NN)..(DEP(1.NN)*(AVOPT 1H(I)-DEPTH1(NN))/DEPTH(NN))) 2400 CONTINUE . 2420 CONTINUE 3440 NE=NN-1 DO 3500 I=1.NS IF(NN.LT.MR) GO TO 3460 IF(SEDEND(MR).LE.0.0) GO TO 3460 OUTPCT(I)=PCTOUT(I,MR)/SEDEND(MR) GO TO 3480 3460 IF(SEDEND(NN).LE.0.0) OUTPCT(I)=0.0 IF(SEDEND(MR).LE.0.0) OUTPCT(I)=0.0 IF(SEDEND(NN).GT.0.0) OUTPCT(I)=PCTOUT(I,NN)/SEDEND(NN) 3480 CONTINUE 3500 CONTINUE TRAP.(100.0-SEDENDINN-1)) SEDAV2=(SEOEND(NN-1)/(STRMOT+BPOOL-DEAD))*MASS*7.358 IF(STRMOT.GT.0.0) SEDAVE=SEDEND(NN-1)*MASS*7.358/STRMOT IF(STRMOT.LE.0.0) SEDAVE=0.0 WRITE (6,6900) 6900 FORMAT(1H1) WRITE (6,7000) 7000 FORMAT(45X,"***** STORM EVENT SUMMARY *****") WRITE(67100) CAPOC). 7100 FORMAT(//,15X."PERMANENT POOL CAPACITY",18X,"=",F10.2,5X,"ACRE -FT" 1) WRITE(6,7200) DEAD 7200 FORMAT(//,15X,"DEAD STORAGE".29X."=",F10.2,5X,"ACRE-FT") WRITE(6,7300) STORM 7300 FORMAT(//,15X,"STORM RUNOFF VOLUME".22X,"8",F10.2,5WACRE-FT") WRITE(6,7400) STRMOT 7400 FORMAT(//.15X,"STORM VOLUME DISCHARGED ".17X."=".F10.2,5WACRE-FT 1") WRITE(6.7500) CAPSAV 7500 FORMAT(//,15X,"POND VOLUME AT PEAK STAGE".16X,"=",F10.2,5X,"ACRE-F IT") WRITE(6,7800) PSTAGO WRITE(6,7600) PEAKIN INFLOW RATE",25X."="pF10.2.5X,"CFS") WRITE(6,7700) PEAK 7700 FORMAT(//,15X,"PEAK DISCHARGE RATE"..22X."="5, F10.2,5X."CFS") 7600 FORMAT(//,15X,"PEAK 134 7800 FORMAT(//,15X,"PEAK STAGE",31X,".",F10.2,5X,"FT") WRITE(6,7900) PFLNT 7900 FORMAT(//015X,"PEAK INFLOW SEDIMENT CONCENTRATION",7X,"•",F10.1,5X 1,"MG/L") WRITE(6,8000) PEFLNT 8000 F0RMAT(//,15X,"PEAK EFFLUENT SEDIMENT CONCENTRATION",5X,".",F10.1, 15X,"MG/L") WRITE(6,8050) SEDAVE 8050 FORMAT(//,15X,"STORM AVERAGE EFFLUENT CONCENTRATION", 5X,".", 1F10.1,5WMG/L") WRITE(6,8100) SEDAV2 8100 FORMAT(//,)_5X,"AVERAGE EFFLUENT SEDIMENT CONCENTRATION",2X,".", 1F10.1,5X,"MG/L") WRITE(6,8200) TRAP 8200 FORMAT(//,15X,"BASIN TRAP EFFICIENCY",20X,".",F10.2,5X," ") WRITE(6,8300) AVETME 8300 FORMAT(//,15X,"DETENTION TIME OF FLOW WITH SEDIMENT",5X,".",F10.2, 15X,"HRS") WRITE(6,8400)CENTME 8400 FORMAT(//,15X,"DETENTION TIME FROM HYDROGRAPH CENTERS",3X,".",F10. 12,5X,"NRS") WRITE(6,8450) STRMTM 8450 FORMAT(//,15X,"DETENTION TIME INCLUDING STORED FLOW",5X,".",F10.2, 15X, "MRS") WRITE(6,8500) MASS 8500 FORMAT(//,15X,"SEDIMENT LOAD",28X,".",F10.215X,"TONS") WRITE (6,9200) IF(FLOWAV.EQ.0.0) GO TO 3540 WRITE(6,8600) FLOWAV 8600 FORMAT(//,15X," PARTICLE SIZE DISTRIBUTION AT INFLOW RATE 1 •",F10.2,2X,"CFS *****") WRITE(6,8700)(SIZE(I),Ia1,NS) 8700 FORMAT(///,15X,"SIZE (MM)", 10F8.4) WRITE(6,8800)(PERCNT(I),I=1,NS) 8800 FORMAT(/ ,15X," FINER",1X,10F8.1) DO 3520 I.1,NS SIZES(I).(FLOWAV/PEAKIN)**.3*PERCNT(I) IF(SIZES(I).GT.100.) SIZES( 1)-100. 3520 CONTINUE WRITE(6,8900) PEAKIN 8900 FORMAT(//,15X," ***** PARTICLE SIZE DISTRIBUTION AT INFLOW RATE 1 .",F10.2,2X,"CFS *****") WRITE(6,8700)(SIZE(I),I.1,NS) WRITE(6,8800) (SIZES(I),I.1,NS) GO TO 3560 3540 WRITE(6,9000) 9000 FORMAT(//p15X,"***** PARTICLE SIZE DISTRIBUTION OF SEDIMENT INFLOW 1 WRITE(6,8700)(SIIE(I),I.1,NS) WRITE(6,8800)(PERCNT(I),I.1,NS) 3560 CONTINUE WRITE (6,9100) 9100 FORMAT(//,15X," ***** PARTICLE SIZE DISTRIBUTION OF EFFLUENT 1") WRITE(6,8700)(SIZE(I),I.1,NS) WRITE(6,8800)(OUTPCT(I),I.1,NS) 9200 FORMAT(1H1) WRITE (6,9300) le) 9300 FORMAT(//,32X,"***** OUTFLOW WITHDRAWAL DISTRIBUTION WRITE(6,9400) 9400 FORMAT( ///,15X, "STAGE",10X, "OUTFLOW 1", 10X, "OUTFLCW 2", 10X, "OUTFLO 1W 3",10X,"OUTFLOW 4") WRITE (6,9500) 135 9500 FORMAT(/,16X,"(FT)",13X,"( )",16X,"( )",16x,"( )",16x,"( )•) DO 3580 IR=1,MD WRITE(6,9600) DPTH(IR),OUTFL1(IR),OUTFL2(IR),OUTFL3(IR),OUTFL4(IR) 9600 FORMAT( 10X,F10.2,7X,F10.2,9X,F10.2,9X,F10.2,9X,F10.2) 3580 CONTINUE WRITE(6,9700) 9700 FORMAT(1H1) WRITE (6,9800) 9800 FORMAT(//y42X," BASIN GEOMETRY *****") IF ( DEPOST.GT.1.99.AND.MASS.GT.0.01) GO TO 3640 IF(MASS.GT.0.0) GO TO 3720 WRITE (6,9900) 9900 FORMAT ( //// , 15X,STAGE",10X,"AREA",7X,"AVERAGE DEPTH",5X,"DISCHARG lE",7X,"CAPACITY") WRITE (6,10000) 10000 FORMAT(/#16X,"(FT)",9X,"(ACRES)",10X,"(FT)",10X,"(CFS)",9X,"(ACRES 1—FT)") DO 3600 IL•1,N W R ITE (6,10100) STG 1( IL) , AREAS(IL),AVDPTH(IL),DISCHB(IL),CAPAC(IL) 10100 FORMAT(/ ,10X,F10.4, 5 X , F1 0 .2,5X,F10.2,5X,F10.2,5X,F11.4,5X) 3600 CONTINUE WRITE (6,10200) 10200 FORMAT(1H1) WRITE(6,10300) WRITE(6,10400) 10300 FORMAT(//p45X,"***** STORM HYDROGRAPHS E SEDIMENTGRAPHS to) 10400 FORMAT ( ////s 8 X , "7/ME" , 8WINFLOW",7X,"DISCHARGE",6WDETENTION TIM E" , 3X , "STAGE",8X,•DEPTH",8X,"SEDIMENT") 1 WRITE(6,10500) 10500 FORMAT(/,8X,"(HRS)",8X,"(CFS)",9X,"(CFS)",11X,"(HRS)",9X,(FT)",9X 1,"(FT)",11X,"( )") DO 3620 LL=2,NE JM=(DELPLG/DELTAT)*(LL-1)+1.0 WRITE (6,10600 )PLGTME(LL),INFLOW(JM),OISCHAUM),DETTME(LL),STAGO(LL 1),DEPTH(LL),SEDEND(LL) 10600 FORMAT ( /y 5 X , F 7 .2 , 6X,F7.2,8X,F7.2s8X,F7.2,7X,F7.2,7X,F7.2,7X,F7.2) 3620 CONTINUE GO TO 37C0 3640 WRITE(6,10700) 10700 FORMAT(//,6X, "STAGE", 9X,"DEPTH",6X,"DESIGN AREA",5X,"NEW AREA", 15WAVERAGE DEPTH",5X,"DISCHARGE",3X,"DESIGN CAPACITY",3X,"NEW CAP 2ACITY") WRITE (6,10800) 10800 FORMAT(/, 6X , "(FT)" , 11X , "(FT)",9X,"(ACRES)",8X,"(ACRES)",10X,"(FT) 1",11X,"(CFS)",7X,"(ACRE—FT)", 7X,"(ACRE—FT)") DO 3660 IL=1,N WRITE(6,10900) STG1(IL),STAGE(IL),AREAS(IL),AREA(IL),AVDPTH(IL),DI 1SCH(IL),CAPCO(IL),CAPACCIL) 10900 FORMAT( F10.2,5X,F10.2,5X,F10.2,5X,F10.205X,F10.2,5X,F10.2,5 1X,F10.2,5X,F10.2) 3660 CONTINUE WRITE (6,11000) 11000 FORMAT(1H1) WRITE (6,11100) .) 11100 FORMAT(//,45X," STORM HYDROGRAPHS E SEDIMENTGRAPHS WRITE(6111200) 11200 FORMAT ( / ,3 X , "TIME" , 8WINFLOW",7X,"DISCHARGE",5X,"DETENTION TIME", 14)( r"STAGE" ,8 X , "DEPTH" , 8X,"SEDIMENT",8X,"INFLUENT",7X,"EFFLUENT") WRITE(6,11300) 11300 FORMAT ( / ,3 X , "(HRS)" ,8 X , "(CFS)",9X,"(CFS)",11X,"(HRS)",9X,"(FT)",10 1X,"(FT)",10)(,"( )" , 11X , "(MG/L)",9X,"(MG/L)") DO 3680 LL=2,NE JM=(DELPLG/DELTAT)*(LL-1)+1.0 136 WRITE(6,11400)PLGTME(LL),INFLOW(JM),DISCHA(JM),DETTME(LL),STAGO(LL 1),DEPTH(LL),SEDEND(LL),NFINT(JM),EFLNT(Li) 11400 FORMAT( F7.2,6X,F7.2,8X,F7.2,8X,F7.2,7X,F7.2,7X,F7.2,7XpF7.2,9 1X,F8.1,8X1F7.1) 3680 CONTINUE 3700 CONTINUE GO TO 3780 3720 WRITE(6,11500) 11500 FORMAT(//,15X,"STAGE",10WAREA",7WAVERAGE DEPTH",5WDISCHARGE" 1,7X, "CAPACITY") WRITE (6,11600) 11600 FORMAT(/,16X,"(FT)",9X,"(ACRES)-",10X,"(FT)",10X,"(CFS)",9X,"(ACRES 1—FT)") DO 3740 Itml,N WRITE(6,11700)STG1(IL),AREAS(IL),AVDPTH( IL),DISCH8(IL),CAPACCIL) 11700 FORMAT(/ $10X,F10.4, 5X,F10.5,5X,F10.2,5X,F10.2,5X,F11.5,5X) 3740 CONTINUE WRITE (6,11800) 11800 FORMAT(1H1) WRITE (6,11900) 11900 FORMAT(//,45X,"***** STORM HYDROGRAPHS I SEDIMENTGRAPHS *****") WRITE(6,12000) 12000 FORMAT(/p3X,"TIME"s8X,"INFLOW",7X , "DISCHARGE"y 5 WDETENTION TIME", 14X,"STAGE",8X,"DEPTH",8X,"SEDIMENT",8WINFLUENT" ,7 X , "EFFLUENT" ) WRITE (6,12100) 12100 FORMAT(/,3X,"(HRS)",8X,"(CFS)",9X,"(CFS3" , 11X , "(HR5)" ,9 X , "(FT)" ,10 1X,"(FT)",10X,"( )",11X,"(MG/L)",9X,"(MG/L)") DO 3760 LL.2,NE 4MA(DELPLG/DELTAT)*(LL-1)+1.0 WRITE(6,12200)PLGTME(LL),INFLOW(JM) , DISCHAUM) , DETTME(LL) , STAGO ( IL 1),DEPTH(LL),SEDEND(LL),NFLNT(JM) , EFLNT(LL) f7.2,6X,F7.2,8X,F7.2,8X,F7.2,7X,F7.2,7X,F7.2,7X,F7.2,8 12200 FORMAT( lx,F8.0,8X,F7.0) 3760 CONTINUE 3780 CONTINUE 3800 CONTINUE 12300 FORMAT(1H1) WRITE (6,12300) IF(TRP.GT.1.0) GO TO 3820 GO TO 3840 3820 IF(TRP.GT.TRAP) GO TO 20 3840 CONTINUE GO TO 3880 3860 WRITE(6,12400) 12400 FORMAT(//,15X,"*#*** ERROR **A** • THE RESERVOIR CAPACITY IS EXCEE 1DED") 3880 CONTINUE 3900 CONTINUE 3950 STOP END SUBROUTINE WASH RETURN END LIST OF REFERENCES Auernhamer, M. E., M. M. Fogel, L. H. Hekman, Jr., and J. L. Thames. 1977. Stochastic prediction of sediment yields from strip mine spoils of the arid southwest. Proceedings of the 1977 Meetings of the Arizona Section - AWRA, Vol. 7, Las Vegas, Nevada, pp. 33-40. Blumer, S. In preparation. Master's thesis. School of Renewable Natural Resources. University of Arizona, Tucson. Bondurant, J. A., C. E. Brockway, and M. J. Brown. 1975. Some aspects of sedimentation pond design. Proceedings, National Symposium on Urban Hydrology and Sediment Control, Lexington, Kentucky, pp. 117-122. Camp, T. R. 1946. Sedimentation and the design of settling tanks. Transactions of the American Society of Civil Engineers, 3: 895-958. Curtis, D. C. 1976. A deterministic urban storm water and sediment discharge model. Proceedings, National Symposium on Urban Hydrology, Hydraulics, and Sediment Control, Lexington, Kentucky, pp. 151-162. Curtis, D. C., and R. H. McCuen. 1977. Design efficiency of stormwater detention basins. Proceedings ASCE, Journal of the Water Resources Planning and Management Division, 103(WR1): 125-140. Curtis, W. R. 1974. Sediment yield from strip-mined watersheds in eastern Kentucky. Proceedings, Second Research and Applied Technology Symposium on Mined-Land Reclamation, Louisville, Kentucky, pp. 88-100. Federal Register, Surface coal mining and reclamation operations - Permanent regulatory program, OSM, Dept. of the Interior, Vol. 44, No. 50, 3-13-79, Book 3, Part II, pp. 15311-15463. Fischer, J. N. 1976. Simulation of hydrologic processes for surfacemined lands. Ph. D. dissertation, The University of Arizona, Tucson, 122 pages. Flaxman, E. M. 1972. Predicting sediment yield in the Western United States. Proceedings ASCE, Journal of the Hydraulics Division, 98(HY12): 2073-2086. 137 138 Fogel, M. M., L. Duckstein, and A. Musey. 1976. Event-based formulation of watershed management. Proceedings, ASCE Specialty Conference on Environmental Impact of Irrigation and Drainage, Ottawa, Ontario, Canada, pp. 349-373. Fogel, M. M., L. H. Hekman, and W. B. Vandivere. 1979. Sediment yield prediction from Black Mesa coal spoils. Paper presented at the 1979 Winter Meeting, American Society of Agricultural Engineers, New Orleans, La., 7 pages. Fogel, M. M. 1980. Professor of Watershed Management, School of Renewable Natural Resources, University of Arizona. Oral communication. Haan, C. T., and B. J. Barfield. 1978. Hydrology and Sedimentology of Surface Mined Lands. Office of Continuing Education and Extension, University of Kentucky, 286 pages. Hamon, W. R. 1979. Research Hydraulic Engineer, USDA-SEA-ARS, Coshocton, Ohio. Oral communication. Holten, H. N. 1961. A concept for infiltration estimates in watershed engineering. USDA-ARS, pp. 41-51. Huggins, L. F., and E. J. Monke. 1966. The mathematical simulation of the hydrology of small watersheds. Technical Report 1, Purdue University Water Resources Center, Lafayette, Indiana. Kent, K. M. 1973. A method for estimating volume and rate of runoff in small watersheds. Soil Conservation Service, U. S. Department of Agriculture, SCS-TP-149, 61 pages. Kielliker, J. K., H. L. Manges, and R. I. Lipper. 1975. Modeling the performance of feedlot-runoff-control facilities. Transactions of the American Society of Agricultural Engineers, Vol. 18, No. 6, pp. 1118-1121. Krishnamurthi, N., and J. L. Balzer. 1978. Design-storm for sedimentation ponds. American Geophysical Union 1978 Annual Meeting, San Francisco, California, 12 pages. Krumbein, W. E. 1968. Statistical methods in sedimentology. Sedimentology (Amsterdam) 10(1): 7-23. McCarthy, R. E. 1977. Erosion and sediment control for coal surface mine areas. National Symposium on Soil Erosion and Sedimentation by Water, Chicago, Illinois. Morris, H. M., and J. M. Wiggert. 1972. Applied hydraulics in engineering. 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