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Attribution Analysis of Runoff Change in Min-Tuo River Basin based on SWAT model simulations, China

Jian Hu, Jie Ma, Chao Nie, Lianqing Xue, Yang Zhang, Fuquan Ni, Yu Deng, Jinshan Liu, Dengke Zhou, Linhuan Li, Zhigang Wang

2020Scientific Reports56 citationsDOIOpen Access PDF

Abstract

To consummate watershed data and better quantify the impact of climate changes and human activities on runoff, we examined the changes and response mechanisms of runoff in the Min-Tuo River Basin, China. In the examination, the Soil and Water Assessment Tool (SWAT) model was used to simulate possible evapotranspiration, actual evapotranspiration, and runoff in 1980, 1990, 1995, 2000, 2005, 2010, and 2015 under different land-use conditions. SWAT weather generator was used to supplement the missing meteorological data. This study presents a quantitative analysis of the climatic and anthropogenic factors contributing to the runoff alteration in the Min-Tuo River Basin using the Budyko methods. The results suggested that the reduced precipitation was the main cause of runoff reduction. The contributions of precipitation, possible evapotranspiration, and underlying surface alterationsof runoff were 56.18%, 37.08%, and 6.74%, respectively. Sensitivity analysis indicated that the runoff alteration was most sensitive to changes of landscape parameters. The aridity index and all the elasticities showed a spatial variations in the Min-Tuo River Basin. The influence of the three factors on runoff reduction varied with seasons. During the high-flow period, changes of the precipitation and possible evapotranspiration and underlying surface had the greatest effect on runoff reduction, while changes of underlying surfaces had the least effect.

Topics & Concepts

SWAT modelSurface runoffChinaStructural basinAttributionDrainage basinHydrology (agriculture)Environmental scienceWater resource managementGeographyGeologyGeomorphologyCartographyBiologyEcologyPsychologyArchaeologySocial psychologyGeotechnical engineeringHydrology and Watershed Management StudiesFlood Risk Assessment and ManagementHydrological Forecasting Using AI