Identifying driving factors of the runoff coefficient based on the geographic detector model in the upper reaches of Huaihe River Basin

Abstract: Various climate and watershed characteristics determine the runoff coefficient (RC), and their interactions are complicated. Understanding the driving factors of the RC is important for understanding the long-term water balance and how it might change. Using the upper reaches of the Huaihe River Basin as the study area, remote sensing data were used to produce a RC map. The geographical detector was selected to quantify the individual and interactive influences of 13 driving factors on the RC. The results revealed that moderate resolution imaging spectroradiometer evapotranspiration (ET) data can be used to produce a mean average RC map based on the water balance equation. The dominant factors influencing the RC were found to vary at different scales. Precipitation had the largest correlation coefficient with the RC at the watershed scale. For the pixel scale, results from the geographical detector indicated that actual evapotranspiration (AET) and precipitation had the highest explanatory rate for the RC in the small watershed region and the whole study area (0.785 and 0.248, respectively). Climate factors, elevation, and normalized difference vegetation index had a substantial influence on the RC. Any two factors exhibited bilinear or nonlinear enhanced relationships in their interactions. The largest interactions between the factors were AET and precipitation, which exceeded 0.900. This study serves to better understand and explain runoff’s complex interrelationships.

Object Details

• Location: Deutsche Nationalbibliothek Frankfurt am Main
• Extent: Online-Ressource
• Language: Englisch

References and Relationships

• Bibliographic citation: Identifying driving factors of the runoff coefficient based on the geographic detector model in the upper reaches of Huaihe River Basin ; volume:14 ; number:1 ; year:2022 ; pages:1421-1433 ; extent:13 ; Open Geosciences ; 14, Heft 1 (2022), 1421-1433 (gesamt 13)

Contributors, Places and Time

• Creator: Li, Xinchuan ; Niu, Yun ; He, Qiaoning ; Wang, Huaijun

Further information

• DOI: 10.1515/geo-2022-0438
• URN: urn:nbn:de:101:1-2022121413592378010777
• Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Last update: 15.08.2025, 7:26 AM CEST