Integrating water use systems and soil and water conservation measures into a hydrological model of an Iranian Wadi system

Water resources are precious in arid and semi-arid areas such as the Wadis of Iran. To sustainably manage these limited water resources, the residents of the Iranian Wadis have been traditionally using several water use systems(WUSs) which affect natural hydrological processes. In this study, WUSs and soil and water conservation measures(SWCMs) were integrated in a hydrological model of the Halilrood Basin in Iran. The Soil and Water Assessment Tool(SWAT) model was used to simulate the hydrological processes between 1993 and 2009 at daily time scale. To assess the importance of WUSs and SWCMs, we compared a model setup without WUSs and SWCMs(Default model) with a model setup with WUSs and SWCMs(WUS-SWCM model). When compared to the observed daily stream flow, the number of acceptable calibration runs as defined by the performance thresholds(Nash-Sutcliffe efficiency(NSE)≥0.68, –25%≤percent bias(PBIAS)≤25% and ratio of standard deviation(RSR)≤0.56) is 177 for the Default model and 1945 for the WUS-SWCM model. Also, the average Kling–Gupta efficiency(KGE) of acceptable calibration runs for the WUS-SWCM model is higher in both calibration and validation periods. When WUSs and SWCMs are implemented, surface runoff(between 30% and 99%) and water yield(between 0 and 18%) decreased in all sub-basins. Moreover, SWCMs lead to a higher contribution of groundwater flow to the channel and compensate for the extracted water by WUSs from the shallow aquifer. In summary, implementing WUSs and SWCMs in the SWAT model enhances model plausibility significantly.

Soil erosion assessment by RUSLE with improved P factor and its validation:Case study on mountainous and hilly areas of Hubei Province,China

The Revised Universal Soil Loss Equation(RUSLE)is widely used to estimate regional soil erosion.However,quantitative impacts of soil and water conservation(SWC)measures on conservation practice factor(P)of the RUSLE remain largely unclear,especially for the mountainous and hilly areas.In this study,we improved the RUSLE by considering quantitative impacts of different SWC measures on the P factor value.The improved RUSLE was validated against the long-term(2000-2015)soil erosion monitoring data obtained from 96 runoff plots(15—35°)in mountainous and hilly areas of Hubei Province,China;the result presented a high accuracy with the determination coefficient of 0.89.Based on the erosion monitoring data of 2018 and 2019,the Root Mean Square Error of the result by the improved RUSLE was 28.0%smaller than that by the original RUSLE with decrement of 19.6%—24.0%in the average P factor values,indicating that the soil erosion modelling accuracy was significantly enhanced by the improved RUSLE.Relatively low P factor values appeared for farmlands with tillage measures(P<0.53),grasslands with engineering measures(P<0.23),woodlands with biological measures(P<0.28),and other land use types with biological measures(P<0.51).The soil erosion modulus showed a downward trend with the corresponding values of 1681.21,1673.14,1594.70,1482.40 and 1437.50 t km^(-2)a-1 in 2000,2005,2010,2015 and 2019,respectively.The applicability of the improved RUSLE was verified by the measurements in typical mountainous and hilly areas of Hubei Province,China,and arrangements of SWC measures of this area were proposed.