The Water Erosion Prediction Project (WEPP) model is utilized to simulate the sediment and runoff processes. According to previous studies, WEPP model provides impressive results in watersheds of diverse climates and scales. It is also capable of modeling the sediment transportation processes and consequently predicting subsequent deposition sites. In this study, the geo-spatial interface for WEPP (GeoWEPP) was employed as a GIS framework to extract the data required from the ASTER Global Digital Elevation Model (ASTER-GDEM) dataset which was subsequently used as the model input. The case study was based on monthly data consisting of average sediment and runoff estimation from the Emameh subbasin, in northern Iran. The model estimations were validated through field measurements. Two statistical measures of co-efficiency including the Nash-Sutcliffe Efficiency (NSE), and the coefficient of determination (R 2 ) were considered to evaluate how well the model predictions could explain the variability of observations in the field. The model performed favorably as corroborated by a reasonably high NSE of 0.99 and an R 2 value of 0.92 for sediment. In the case of runoff, the results were slightly inferior, but still acceptable with an NSE of 0.76 and R 2 value of 0.62.

No abstract

There are several principal driving forces behind the damaging coastal water resources depletion in many countries, including: high population growth, degrading water resources due to overexploitation and contamination, lack of awareness among local beneficiaries regarding sustainable management, and deficient government support and enforcement of conservation programs. To ensure a water resource system is productive in coastal areas, holistic and comprehensive management approaches are required. To address the aforementioned issues, a combined methodology which considers anthropogenic activities, together with environmental problems defined as the Overall Susceptibility Socio-Ecological System Environmental Management (OSSEM) has been investigated. The OSSEM model has been applied successfully in Spain based upon daily time series data. This research is ground breaking in that it integrates the OSSEM model in a geographic information system (GIS) environment to assess the groundwater contamination based on annual time series data and the assessment of system management by means of an overall susceptibility index (OSI). Centered on OSI indicators, the renewal, salinization and water deficit potentials in the Talar aquifer were estimated to be 4.89%, 4.61%, and 3.99%, respectively. This data demonstrates a high susceptibility in terms of environmental pollution, salinization, and water deficit.