Coupling the modified SCS-CN and RUSLE models to simulate hydrological effects of restoring vegetation in the Loess Plateau of China

Abstract

Abstract. Predicting event runoff and soil loss under different land covers is essential to quantitatively evaluate the hydrological responses of vegetation restoration in the Loess Plateau of China. The Soil Conservation Service curve number (SCS-CN) and Revised Universal Soil Loss Equation (RUSLE) models are widely used in this region to this end. This study incorporated antecedent moisture condition (AMC) in runoff production and initial abstraction of the SCS-CN model, and considered the direct effect of runoff on event soil loss by adopting a rainfall-runoff erosivity factor in the RUSLE model. The modified SCS-CN and RUSLE models were coupled to link rainfall-runoff-erosion modeling. The effects of AMC, slope gradient and initial abstraction ratio on curve number of SCS-CN, as well as those of vegetation cover on cover-management factor of RUSLE, were also considered. Three runoff plot groups covered by sparse young trees, native shrubs and dense tussock, respectively, were established in the Yangjuangou catchment of Loess Plateau. Rainfall, runoff and soil loss were monitored during the rainy season in 2008-2011 to test the applicability of the proposed approach. The original SCS-CN model significantly underestimated the event runoff, especially for the rainfall events that have large 5-day antecedent precipitation, whereas the modified SCS-CN model was accurate in predicting event runoff with Nash-Sutcliffe model efficiency (EF) over 0.85. The original RUSLE model overestimated low values of measured soil loss and underpredicted the high values with EF values only about 0.30. In contrast, the prediction accuracy of the modified RUSLE model improved with EF values being over 0.70. Our results indicated that the AMC should be explicitly incorporated in runoff production, and direct consideration of runoff should be included when predicting event soil loss. Coupling the modified SCS-CN and RUSLE models appeared to be appropriate for evaluating hydrological effects of restoring vegetation in the Loess Plateau. The main advantages, limitations and future study scopes of the proposed models were also discussed.

Use of satellite and modeled soil moisture data for predicting event soil loss at plot scale

“…However, it was found in the scientific literature (Todisco et al, 2009;Bagarello et al, 2008;Risse et al, 1993) that the USLE/RUSLE model, and similarly (Tiwari et al, 2000) process-oriented models (e.g., Water Erosion Prediction Project, WEEP, Flanagan et al, 1995), tends to overestimate (underestimate) soil losses for low (high) erosive events. Foster et al (1982) noted that the USLE model is somewhat unsatisfactory for estimating soil loss from individual storms, and observed that including rainfall amount, rainfall intensity and runoff amount in the erosivity factor provided better performance. Foster et al (1982) also noted that erosivity factors with separate terms for rainfall and runoff erosivity were more appropriate.…”

“…Foster et al (1982) noted that the USLE model is somewhat unsatisfactory for estimating soil loss from individual storms, and observed that including rainfall amount, rainfall intensity and runoff amount in the erosivity factor provided better performance. Foster et al (1982) also noted that erosivity factors with separate terms for rainfall and runoff erosivity were more appropriate. Successively, Kinnell (1997) suggested that the sediment concentration for individual rainfall event is dependent on the event rainfall erosivity index per unit rainfall depth and developed the so-called USLE-M model, including direct measures of the runoff in the event rainfall-runoff erosivity factor (Kinnell and Risse, 1998;Kinnell, 2007Kinnell, , 2010Bagarello et al, 2011).…”

“…However, it is evident that a poor estimation of event runoff will produce a low-accuracy forecast of the soil loss. Gao et al (2012) coupled a modified SCS-CN (Soil Conservation Service curve number) and RUSLE model for runoff and soil loss simulation at plot scale in the Loess Plateau. In RUSLE2, runoff prediction for storm events is obtained using the SCS-CN method with empirical equations that vary the values of CN in association with both soil moisture and rainfall intensity (Kinnell, 2014).…”

Predicting plot soil loss by empirical and process-oriented approaches. A review

“…Should this be the case, b1 estimation procedures need to be developed. Currently, we know that, in the USLE-MM, b1 is greater than 1 but it does not exceed approximately 1.6 in central and southern Italy locations (Bagarello et al, 2008(Bagarello et al, , 2010a(Bagarello et al, , 2013a(Bagarello et al, , 2013b(Bagarello et al, , 2015a(Bagarello et al, , 2015b and it is equal to 1.55 at a Chinese experimental station (Gao et al, 2012). Therefore, it appears plausible to suppose that a single b1 value could be used in general for practical purposes.…”

“…A modified Soil Conservation Service -Curve Number (SCS-CN) model was applied by Gao et al (2012) to obtain an estimate of the plot runoff coefficient specifically usable with a USLE-MM type soil erosion model. In short, the event runoff, Qe (mm), is predicted by the following relationship: where P (mm) is total precipitation depth, lc is the initial abstraction coefficient, representing losses due to interception, surface storage and infiltration, S (mm) is the potential maximum retention, and Ms (mm) is the moisture of the soil profile before the start of the storm.…”