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Introduction:
Soil erosion is the most widely recognized and most common form of land degradation and, therefore, a major cause of falling productivity (Stocking et 2001). Soil is a major problem in India and worldwide. Narayana (1983) indicates that around 53% of the total land area of India suffers from the problem of soil erosion. UN’s Food and Agricultural organization reports that around 5-7 million hectares of land is lost due to erosion worldwide . Major sources of clean and fresh water are undisturbed forests and watersheds which are necessary to sustain ecosystem. The loss of cropland is a serious problem because the World Health Organization and the Food and Agricultural Organization report that two-thirds of the world population is malnourished. Overall, soil is being lost from agricultural areas 10 to 40 times faster than the rate of soil formation imperiling humanity’s food security (David Pimentel & Michael Burgess). High infiltration rates and low levels of overland flow result from the vegetation and litter that protect the soil against the forces of erosion (Baker 1990; Croke et al. 1999; Elliot and Ward 1995). Although soil managers attempt to minimize impacts of their activities, the removal of vegetation and the alteration of soil properties due to logging, road building, prescribed fire and other anthropogenic activities may significantly impact soil erosion and water quality (Lindeburgh 1990; Lousier 1990; Rice 1999; Tiedemann et al. 1979).
Various kinds of remediation can only be suggested if we know the extent of damage and more exactly which areas are more susceptible. There are several methods for estimation of soil loss. Soil erosion prediction technology began over 70 years ago when Austin Zingg published a relationship between soil erosion (by water) and land slope and length, followed shortly by a relationship by Dwight Smith that expanded this equation to include conservation practices. But, it was nearly 20 years before this works expansion resulted in the Universal Soil Loss Equation (USLE) , perhaps the foremost achievement in soil erosion prediction in the last century. The USLE has increased in application and complexity, and its usefulness and limitations have led to the development of additional technologies and new science in soil erosion research and prediction. Main among these new technologies is the Water Erosion Prediction Project (WEPP) model, which has helped to overcome many of the shortcomings of the USLE, and increased the scale over which erosion by water can be predicted. Areas of application of erosion prediction include almost all land types: urban, rural, cropland, forests, rangeland, and construction sites. Empirical models have been and are still used because of their simple structure and ease of application. One of the most important problems with empirical models of soil erosion is its lack of accuracy in processing the huge number of data which should be digitalized by GIS system and analyzed by mathematical models. MPSIAC is an empirical model to estimate the quantity and quality of sediment. In fact quantifying and digitalizing the sediment data is an important breakthrough in sediment assessment models development (Nearing et al., 1999). This problem could be partially solved by estimating soil loss using models (Lufafa et al., 2003). As soil erosion is a product of few different interacting factors, there is not a simple model to assess all the contributing elements in the same time (Daroussin and King, 2001). The Universal Soil Loss Equation (USLE) is the most widely used empirical erosion model (Wischmeier and Smith, 1965). It estimates soil erosion from an area simply as the product of empirical coefficients, which must therefore be accurately evaluated. Original values of such coefficients were derived from field observations in different areas within the eastern part of the U.S., but they have been expanded with time using information gathered by researchers who have applied the USLE (and derived models) in different countries in the world (Renard et al., 1997). The MPSIAC model (PSAIC, 1986) was developed primarily for application in arid and semi-arid areas in the southwestern USA, and is believed to appropriate for the same environmental conditions in Iran (Sadeghi, 1993). Both the MPSIAC and the RUSLE models are factor-based, which means that a serious of factors, each quantifying one or more processes and their interactions, are combined to yield and overall estimation of soil loss. As a consequence, attention must be paid to the reliability of results when an application is made outside the range of experimental and calibration conditions. Different models can be tailored together which can prove to be very powerful tool in the analysis and estimation. However, a poorly designed model can lead to bad decisions and unwanted outcomes, making it imperative to validate the predictive ability and limitation of a new model before it is widely used as a management tool (Westervelt 2000).
The Water Erosion Prediction Project (WEPP) Model is a physically based erosion simulation model built on the fundamentals of hydrology, plant science, hydraulics, and erosion mechanics. The model was developed by an interagency team of scientists to replace the Universal Soil Loss Equation (USLE) and has been widely used in the United States and the world. WEPP requires four inputs, i.e., climate, topography, soil, and management (vegetation); and provides various types of outputs, including water balance (surface runoff, subsurface flow, and evapotranspiration), soil detachment and deposition at points along the slope, sediment delivery, and vegetation growth. The WEPP model has been improved continuously since its public delivery in 1995.
The geo-spatial interface of the WEPP model called GeoWEPP uses digital geo-referenced information integrated with the most common GIS tools to predict sediment yield and runoff. The model determines where and when the sediment yield and runoff occurs and locates possible deposition places. GeoWEPP was developed as a collaborative project conducted by the Agriculture Research Service, Purdue University, and the USDA National Soil Erosion Research Laboratory. GeoWEPP integrates WEPP model and TOPAZ (TOpography PArameteriZation) software within the ArcView 3.2 To predict sediment yield and runoff at watershed scale,. In GeoWEPP, necessary input files (land cover, land use, slope, climate, soil, and management) are generated within WEPP and topographic data are parameterized by using TOPAZ based on DEMs. Finally, watershed outputs are produced by using GIS functions in ArcView.
Literature Review:
W.H. Wischmeier & Smith (1965, 1978) after summarizing and analyzing the more than 10,000 plot-years of soil erosion and runoff data developed the Universal Soil Loss Equation (USLE).
Foster et al. (1985) made the case for replacing the USLE and expressed the requirements for a USLE replacement, discussed the theory that might be used and explored the experimental challenges that might be encountered and the experimental approaches that might be followed in replacing the USLE.
Meyer (1984) expressed clearly that the development of soil erosion modeling had proceeded along an evolutionary path. This is particularly evident in the development of the USLE and technologies later developed that use considerable portions of the USLE.
Elliot et al. (1991) concluded that GeoWEPP model incorporates digital elevation data to quickly generate runoff and sediment outputs in textual and digital formats on small watersheds with limited spatial variability.
Brooks et al. (1991) indicate that soil loss and sediment yield control measures need a clear estimate of soil erosion rate that could tolerate high level crop productivity, that is, economically and ecologically sustainable
Povilaitis et al. (1995) successfully tested that WEPP model, which is used in GeoWEPP in agricultural settings to accurately predict runoff and sediment yield.
Laflen et al. (1997) discuss that WEPP was developed to replace the empirically-based Universal Soil Loss Equation with a user-friendly simulation model that could be readily modified to nearly any type of watershed at any location.
Ascough II et al. (1997) find that WEPP model is a continuous distributed-parameter soil erosion assessment tool that can be applied to representative hill slopes and a channel network at small watershed scales.
Mortlock (1998) after comparing of the performance of WEPP with other state of-the-art erosion models using common data sets concluded that data quality is an important consideration and primarily process-based models not requiring calibration have a competitive edge to those in need of calibration.
Renschler et al. (2000) recommend a GIS-driven graphical user interface user-friendly approach to combine the decision-support of an environmental prediction model and the spatial capabilities of a GIS for practical assessment purposes.
Renschler (2002) indicates that GeoWEPP, a geo-spatial erosion prediction model, is the integration of the advanced features of GIS (Geographical Information System) within WEPP model such as processing digital data sources and generating digital outputs
Jetten et al. (2003) conclude that the difficulty associated with calibrating and validating spatially distributed soil erosion models summarize the results of model comparison workshops.
Legesse et al. (2003) concluded that physically based models are able to explain the spatial variability of most important land surface characteristics such as topography, slope, aspect, vegetation, soil, as well as climate parameters including precipitation, temperature and evaporation.
Jetten et al. (2003) conclude that difficulties related to accurate estimation and data handling can be improved by using ‘optimal’ models, describing only the dominant processes within a given landscape.
Alaaddin (2008) suggested that GeoWEPP model can assist watershed-related management institutions to quickly and accurately generate acceptable predictions of sediment yield and runoff outputs in textual or graphical format based on digital data base of the watershed.