Effects of Land-Cover Changes and Other Remediations on Hydrology of Xinjiang River Sub-Watershed

To determine whether reforestation efforts in the denuded hills have significant impacts on hydrology in the Xinjiang River watershed, the authors examined eight land-cover scenarios to compare hydrologic responses and to provide a conceptual basis for restoration practices. The authors analyzed a 17-year time period using remote sensing to develop land-cover classification for the watershed. Climate, soil and terrain data for the watershed were used as input in the SWAT （soil and water analysis tool） to quantify and compare the impacts on hydrologic processes. The model was calibrated to a two-year record of stream discharge measurements. The results show significant increase in forest-cover on hills （13%）. However, the hydrological response is not very significant considering the changes in forest-cover, the surface runoff and percolation ratios only changed by 2% and 1% over time. Installment of earthen irrigation ponds in the outlets of sub-basin with maximum runoff had provided the most significant hydrologic improvements and could provide irrigation water to increase crop yield on remaining cropland. The study will provide information to the local government to aid decision-making in sustainable reforestation programs resulting in better hydrologic functioning for sustainable water resource management.

Evaluation of alternative surface runoff accounting procedures using SWAT model

For surface runoff estimation in the Soil and Water Assessment Tool(SWAT)model,the curve number(CN)procedure is commonly adopted to calculate surface runoff by dynamically updating CN values based on antecedent soil moisture condition(SCSI)in field.From SWAT2005 and onward,an alternative approach has become available to apply the CN method by relating the runoff potential to daily evapotranspiration(SCSII).While improved runoff prediction with SCSII has been reported in several case studies,few investigations have been made on its influence to water quality output or on the model uncertainty associated with the SCSII method.The objectives of the research were:(1)to quantify the improvements in hydrologic and water quality predictions obtained through different surface runoff estimation techniques;and(2)to examine how model uncertainty is affected by combining different surface runoff estimation techniques within SWAT using Bayesian model averaging(BMA).Applications of BMA provide an alternative approach to investigate the nature of structural uncertainty associated with both CN methods.Results showed that SCSII and BMA associated approaches exhibit improved performance in both discharge and total NO3 predictions compared to SCSI.In addition,the application of BMA has a positive effect on finding well performed solutions in the multi-dimensional parameter space,but the predictive uncertainty is not evidently reduced or enhanced.Therefore,we recommend additional future SWAT calibration/validation research with an emphasis on the impact of SCSII on the prediction of other pollutants.