Simulations Of Water, Soil And Nutrient Losses At Slope And Watershed Scales Of The Loess Plateau

The Loess Plateau is one of the most serious soil erosion regions in China and even in the world.Severe soil erosion not only takes away a large amount of fertile soil in situ,but also has a long-term impact on soil productivity and crop yield,and also causes environmental effects of downstream water bodies.Modeling research is an effective way to reasonably calculate runoff loss,soil erosion and nutrient loss,which is of great significance to guide the allocation of soil and water conservation measures,optimize the utilization of soil and water resources,and rational land use planning.This study aimed at great demand of ecological environment construction in the Loess Plateau and the weakness of current basic theory research,the process of rainfall,runoff,erosion and nutrient loss on slope and watershed were studied and the rainfall-runoff model,soil erosion model,the nutrient loss model and its coupling model were developed to predict and simulate the process of nutrient loss and soil erosion of the Loess Plateau.The main conclusions of this study were as follows:?1?For rainfall-runoff model,a modified SCS-CN method?MSCS-CN?was proposed based on revised soil moisture accounting?SMA?procedure incorporating rainfall duration and a physical formulation for antecedent soil moisture?V₀?estimation.The proposed formulation for V₀ estimation has shown a high degree of applicability in simulating the temporal pattern of soil moisture in the experimental plot.The proposed method was calibrated and validated using a dataset of 189 rainfall-runoff events from two experimental watersheds on the Chinese Loess Plateau.The results indicated that the proposed method,which yielded model efficiencies both of 88% in calibration and validation,performed better than the original SCS-CN and another SMA based SCS-CN methods.The proposed method was then applied to a third watershed using the tabulated CN value and the two parameters of the minimum infiltration rate?fc?and coefficient???derived for the first two watersheds.The root mean square error between the measured and predicted runoff values was improved from 6 mm to 1 mm.Moreover,the parameter sensitivity analysis for the proposed method was performed,which indicates the parameter,the potential maximum retention?S?is the most sensitive,followed by fc.This modified SCS-CN method incorporating V₀ estimation and storm duration could be used for runoff prediction on the Chinese Loess Plateau.?2?For the soil loss model,the present study proposes the use of a rainfall–runoff erosivity factor to estimate storm-based soil loss using the CSLE.The factor was developed using data from three runoff-erosion plots in each of three different watersheds of the Loess Plateau over three different time periods?1956-1959;1973-1980;2010-2013?.The modified CSLE was evaluated using data from 165 storm–runoff events from six plots in two watersheds.The performance of the modified CSLE was compared with that of the storm-based Revised Universal Soil Loss Equation?RUSLE?.The findings during calibration?88 storms?and validation?77 storms?show the storm-based CSLE is highly accurate in terms of model efficiency as determined by the Nash–Sutcliffe efficiency?NSE??calibration: 65.7%,validation: 75.1%?and root mean square error?RMSE?(calibration: 4.36 t ha^–1,validation: 3.23 t ha^–1).The modified CSLE also performs better than the storm-based RUSLE during both calibration(NSE=58.3% and RMSE=4.81 t ha^–1)and validation(NSE=48.3% and RMSE=4.64 t ha^–1).The storm-based CSLE was then used to predict soil loss in the three experimental plots of the third watershed using the parameters obtained from the previously monitored six plots.Unlike the first and second watersheds,surface runoff in the third watershed was estimated using the modified Soil Conservation Service curve number?SCS-CN?method and compared to measurements.The measured and estimated runoff for the storm-based CSLE has NSE values of 64.7 and 60.8%,respectively.High NSE values indicate that the proposed storm-based CSLE,which incorporates the modified SCS-CN,can accurately predict storm-based soil loss that is normally caused by sheet and rill erosion at the field scale on the Loess Plateau.?3?For nutrient loss model,a sediment-bound nutrient loss model was proposed that accounts for the impacts of sediment,rainfall erosivity,slope gradient and land-use type on the enrichment ratio?ER?,and an existing runoff-associate nutrient loss model was further developed,and then we proposed a framework to integrate newly developed models for sediment-bound nutrient loss and runoff-associated nutrient loss with the modified storm-based Chinese soil loss equation?CSLE?model and modified Soil Conservation Service curve number?SCS-CN?model to predict particulate nutrient losses of nitrogen?N?,carbon?C?,and phosphorus?P?and soluble nutrient losses of P and nitrate.The data collected from literature included 330 storm events with experimental plot measurements of runoff,sediment,and particulate and soluble nutrient losses conducted on slopes in Loess Plateau,and these data were usedto calibrate and assess model performances.The accuracies of the model estimations were examined with the Nash-Sutcliffe efficiency?NSE?.The proposed models with optimized parameters showed high NSE for particulate N?98.5%?,C?98.9%?,and P?99.8%?and soluble P?95.8%?and nitrate?85.4%?when compared with the literature-reported measured losses.To test the models,independent literature data were compared with model-estimated values.The comparison showed agreement between the estimated and observed data with NSEs of 74.4,63.7,86.3,63.6 and 66.7% for particulate N,C and P,soluble P and nitrate,respectively.?4?For the watershed model,this study proposed a modified SWAT?LP-SWAT?model by incorporating the modified Soil Conservation Service curve number method,the storm-based Chinese soil loss equation and the nutrient loss model.The observed daily data of runoff and sediment over 16 years and the monthly soluble phosphorus?P?and nitrate losses over 9 years and 4 years,respectively at the outlet of the upper Beiluo river?UBR?basin were used to assess the model performances.The findings during calibration and validation showed that LP-SWAT was highly accurate in terms of model efficiency?calibration: 82.5%,82.8%,48.1%,and 49.1%;validation: 57.6%,56.6%,53.1%,and 65.4%?for runoff,sediment,soluble P loss and nitrate loss,respectively.High model efficiency indicated that LP-SWAT could accurately predict soil erosion and nutrient loss at the river basin scale for the Loess Plateau.Moreover,the temporal variations from month to year and the spatial variations at the sub-watershed scale for sediment and the total N and P losses were analysed using the data simulated by LP-SWAT.The results indicated that the critical loss period occurred in July and August,and the most erodible area was farmland on high slopes.Thus,the LP-SWAT model can serve as a decision management tool for stakeholders in the design of appropriate management strategies to control runoff and soil loss from the area;the model can also be used for fertilizer management in agricultural fields and for solving water quality and non-point source pollution problems...