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Application of the WEPP Model to Surface Mine Reclamation• By Application of the WEPP Model to Surface Mine Reclamation• by W. J. Elliot Wu Qiong Annette V. Elliot2 Abstract. Sediment from mining sources contributes to the pollution of surface waters. Restoration of mined sites can reduce the problems associated with erosion, and one of the most important objectives of surface mine reclamation is the control of surface runoff and erosion from reclaimed areas. Current methods for predicting sediment yield do not suit surface mine sites because non- agricultural soils and vegetation are involved. There is a need for a computer model to aid in identifying improved management systems and reclamation practices with suitable input data files and appropriate hydrologic modeling routines. The USDA Water Erosion Prediction Project (WEPP) resulted in the development of a computer model based on fundamental erosion mechanics. The WEPP model will be in widespread use by the mid 1990s by the Soil Conservation Service (SCSI, and will be the erosion prediction model of choice well into the next century. This paper gives an overview of the WEPP erosion prediction technology and its implications to surface mine reclamation, and reports on a research project that identifies critical watershed parameters unique to surface mining and reclamation through a sensitivity analysis of the WEPP Watershed Model. The study contributes to the validation of the WEPP Watershed Version by comparing estimates generated by the model with observed data from watersheds after surface mining. Additional Key Words: Erosion simulation INTRODUCTION control of surface runoff and erosion from reclaimed areas (Mitchell et al., 1983; Hartley As renewable fossil fuel energy reserves are and Schuman, 1984). depleted, the importance of coal as a source of energy will increase. McKetta (1974) predicted In regulating reclamation of surface mine that coal usage will have to triple to insure that sites, it is necessary for agencies and the energy needs of the USA are met. This contractors to have a method for predicting inevitable increase in coal usage will result in erosion rates before and after mining to aid in an increase in surface mining operations, along identifying improved management systems and with associated erosion and water quality reclamation practices. Current methods for problems (Barfield et al., 1983). In the USA, predicting soil erosion apply to agricultural soils sediment from mining sources contributes to and vegetation, and so are unsuitable for the pollution of surface waters, affecting water surface mine sites where the hydrologic used for drinking, swimming, fishing, and other conditions can be significantly different. With domestic and recreational purposes (Mitchell et current process-based computer models, the al., 1983). In addition, this sediment may large input data sets are too complex for affect the productivity of agricultural land and technicians and other field users to develop. the life of engineering works. Appropriate There is a need for a process-based computer restoration of mined sites can contribute to the model that can predict erosion and water 1 Paper presented at The Challenge of Integrating Diverse Perspectives in Reclamation, 10th National Meeting of ASSMR, Spokane, WA, 1993. 2 The authors are W.J. Elliot, Supervisory Research Engineer, lntermountain Research Station, USDA-Forest Service, Moscow, 10, and Wu Cliong, Graduate Research Associate, and A.V. Elliot, Engineering Research Associate, Dept. of Agricultural Engineering, The Ohio State University, Columbus, The research was supported by The Ohio Agricultural Research and Development Center, the USDA-AR$ National Soil Erosion Laboratory, W. Lafayette, IN, and the USDA-Forest Service Jntermountain Research Station, Moscow, 10. 116 quality problems associated with surface large input. data sets. However, they can mining with input files from readily available successfully be applied to many more data. conditions than statistical models as long as OBJECTIVES the factors affecting the processes can be identified and characterized (Foster and Meyer, The purpose of this study was to determine 1972). the suitability of the WEPP model for surface mining situations, and to contribute to the In 1984, the USDA Agricultural Research validation of the WEPPWatershed Version 91.5 Service (ARS) and SCS in cooperation with the by comparing estimates produced by the model Bureau of Land Management (BLM) and the with observed data from reclaimed surface Forest Service (FS) began a cooperative effort mine sites. known as the Water Erosion Prediction Project (WEPP). Their goal was to develop a user- The objectives of this paper are to: friendly process-based erosion prediction model that would operate on a portable computer, 1 . Give an overview of the WEPP erosion and could be used by SCS and other field prediction technology and its technicians as an aid in erosion prediction and implications to surface mine conservation planning for cropland, rangeland, reclamation. and forests. After five years of field, laboratory, and computer research, the first 2. Report on a research project that completed research version of the WEPP identifies critical watershed parameters program was released in August, 1989, and unique to surface mining and the first field version in 1991. It is expected reclamation through a sensitivity that the model will begin receiving wide-spread analysis of the WEPP Watershed use by SCS in the mid-1990s, and will be the Version. erosion prediction model of choice well into the next century (Foster and Lane, 1987). 3. Contribute to the validation of the WEPP Watershed Version by comparing The WEPP model is based on fundamentals estimates generated by the model with of infiltration, surface runoff, plant growth, observed data from watersheds after residue decomposition, hydraulics, tillage surface mining. management, soil consolidation and erosion mechanics (Nearing et al., 1989). Table 1 MODELING summarizes the important input parameters for the model. This model combines a process- Hydrologic computer simulation modeling based erosion model with a process-based makes a valuable contribution to agricultural hydrology model and a climate generator to research and practice (Ferreira and Smith, estimate soil loss and deposition, and so 1988). Research involving data collection from facilitate the selection of agricultural long-term field studies is a time-consuming and management practices for soil conservation. expensive process. An alternative approach is to carry out computer simulations to analyze The WEPP technology includes a Hillslope the hydrologic effects of management for given Profile Version, a Watershed Version, and a climate conditions. Grid Version (Lane and Nearing, 1989). The Hillslope Profile Version predicts when and Scientists are developing process-based where soil Joss and deposition will occur on a erosion prediction models for computers that hillslope, taking into account management allow the user to model the individual practices and climate. It is continuous, processes that lead to soil erosion, including simulating the processes that impact erosion rainfall intensity and distribution, infiltration and prediction as a function of time. However, the runoff, and soil detachment, transport, and model may also be used in the single-storm deposition. Process-based models initially mode (Lane and Nearing, 1989). required main frame computer capabilities and The individual processes that lead to soil 117 Table 1. Input requirements for WEPP Model · Input file Contents Slope Pairs of points indicating distance from top of slope and respective slope. Soil For top layer: Albedo, initial saturation, interrill and rill erodibility. For all layers: thickness, initial bulk density, initial hydraulic conductivity, field capacity, wilting point; contents of: sand, clay, organic matter, and rock fragments; cation exchange capacity. Climate For each day of simulation: precipitation amount, duration, time to peak rainfall, peak rainfall, maximum and minimum temperatures, solar radiation, average wind speed and direction. Management Type of vegetation (crop, range, or forest), plant growth parameters, tillage sequences and effects on soil surface and residue, dates of harvesting or grazing; if necessary, description of irrigation, weed control, burning, and contouring. Structure Relationships among the hillslope and channel elements of the watershed. erosion are the same for agricultural and erosion rates on downslope areas and forested lands, and also occur on reclaimed potentially causing inferior surface water mine sites. The erosion differences are due to quality. In the current Watershed Version, plant growth and in the hydrologic response of interflow may be accounted for by a channel ·.. the soils. On reclaimed surface mine sites, parameter. plant growth is slow, and alternative cover crops tiave been, and continue to be sought. VALIDATION The growth rates of many cover crops are With reference to the operational documented, and by studying the data, the requirements for the WEPP model, Foster and necessary crop growth files for the computer Lane (1987) stated that one of the major model could be generated. Crop growth factors important to the users is the validity of parameters measured on reclaimed surface the model. They stipulated that (p. 10-11): mine sites (Holmberg, 1980) could be formatted for the WEPP model. The WEPP The procedure must be sufficiently model not only predicts erosion, but also accurate to lead
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