Abstract:The Soil and Water Assessment Tool (SWAT) was used to simulate the transport of runoff and sediment into the Miyun Reservoir, Beijing in this study. The main objective was to validate the performance of SWAT and the feasibility of using this model as a simulator of runoff and sediment transport processes at a catchment scale in arid and semi-arid area in North China, and related processes affecting water quantity and soil erosion in the catchment were simulated. The investigation was conducted using a 6-year historical streamflow and sediment record from 1986 to 1991; the data from 1986 to 1988 was used for calibration and that from 1989 to 1991 for validation. The SWAT generally performs well and could accurately simulate both daily and monthly runoff and sediment yield. The simulated daily and monthly runoff matched the observed values satisfactorily, with a Nash-Sutcliffe coefficient of greater than 0Ð6, 0Ð9 and a coefficient of determination 0Ð75, 0Ð9 at two outlet stations (Xiahui and Zhangjiafen stations) during calibration. These values were 0Ð6, 0Ð85 and 0Ð6, 0Ð9 during validation. For sediment simulation, the efficiency is lower than that for runoff. Even so, the Nash-Sutcliffe coefficient and coefficient of determination were greater than 0Ð48 and 0Ð6 for monthly sediment yield during calibration, and these values were greater than 0Ð84 and 0Ð95 during validation. Sensitivity analysis shows that sensitive parameters for the simulation of discharge and sediment yield include curve number, base flow alpha factor, soil evaporation compensation factor, soil available water capacity, soil profile depth, surface flow lag time and channel re-entrained linear parameter, etc.
Abstract. Temporal and spatial precipitation information is key to conducting effective hydrological-process simulation and forecasting. Herein, we implemented a comprehensive evaluation of three selected precipitation products in the Jialing River watershed (JRW) located in southwestern China. A number of indices were used to statistically analyze the differences between two open-access precipitation products (OPPs), i.e., Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) and Climate Prediction Center Gauge-Based Analysis of Global Daily Precipitation (CPC), and the rain gauge (Gauge). The three products were then categorized into subbasins to drive SWAT simulations. The results show the following. (1) The three products are highly consistent in temporal variation on a monthly scale yet distinct on a daily scale. CHIRPS is characterized by an overestimation of light rain, underestimation of heavy rain, and high probability of false alarm. CPC generally underestimates rainfall of all magnitudes. (2) Both OPPs satisfactorily reproduce the stream discharges at the JRW outlet with slightly worse performance than the Gauge model. Model with CHIRPS as inputs performed slightly better in both model simulation and fairly better in uncertainty analysis than that of CPC. On a temporal scale, the OPPs are inferior with respect to capturing flood peak yet superior at describing other hydrograph features, e.g., rising and falling processes and baseflow. On a spatial scale, CHIRPS offers the advantage of deriving smooth, distributed precipitation and runoff due to its high resolution. (3) The water balance components derived from SWAT models with equal simulated streamflow discharges are remarkably different between the three precipitation inputs. The precipitation spatial pattern results in an increasing surface flow trend from upstream to downstream. The results of this study demonstrate that with similar performance in simulating watershed runoff, the three precipitation datasets tend to conceal the identified dissimilarities through hydrological-model parameter calibration, which leads to different directions of hydrologic processes. As such, multiple-objective calibration is recommended for large and spatially resolved watersheds in future work. The main findings of this research suggest that the features of OPPs facilitate the widespread use of CHIRPS in extreme flood events and CPC in extreme drought analyses in future climate.
Identifying the feedback relationship between soil erosion and vegetation growth would contribute to sustainable watershed management. In order to study the long-term interaction between soil erosion and vegetation change, a comprehensive modeling framework was proposed by combining the Soil and Water Assessment Tool (SWAT) and the Environmental Policy Integrated Climate (EPIC) model. The Huangfuchuan Watershed was taken as an example area due to serious erosion and large-scale conversion of farmland to forest. Based on long-term variation analyses from 1956 to 2020, the effect of land cover change on runoff and sediment discharge was quantified using SWAT to create scenario simulations, and then environmental stresses factors (i.e., soil water content, nitrogen, and phosphorus contents) output by SWAT were input into EPIC to evaluate effects of soil erosion on potential biomass of vegetation. Results showed that the annual runoff reduction was 32.5 million m3 and the annual sediment reduction was 15 million t during the past 65 years. The scenario we created using the SWAT simulation showed that both forest and grassland reduced water yield, while bare land increased water yield by 10%. In addition, grassland and forest reduced soil erosion by 20% and 18%, respectively, while bare land increased sand production by 210%. The EPIC model results exhibited a negative correlation between the potential for vegetation biomass and erosion intensity. The average annual potential biomass of forest and grass under micro-erosion was 585.7 kg/ha and 485.9 kg/ha, respectively, and was 297.9 kg/ha and 154.6 kg/ha, respectively, under the extremely strong erosion. The results of this study add to the body of information regarding how soil erosion and vegetation biomass interact with each other. The proposed coupled SWAT-EPIC strategy may provide a way for further investigating the quantitative relationship between soil erosion and vegetation cover.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.