@article{DONG2023, 
author = {Jiaping DONG and Yuntao YE and Jingjing GU and Yin CAO and Hongli ZHAO and Yunzhong JIANG},
title = {Influencing mechanism of multi-source environmental factors on the spatial distribution of precipitation in the Luanhe River Basin},
year = {2023},
journal = {Journal of Hohai University (Natural Sciences)},
volume = {51},
number = {3},
pages = {38-47},
keywords = {geodetector, statistical downscaling, factor detection, interaction detection, ecological detection, Luanhe River Basin},
url = {https://www.sciopen.com/article/10.3876/j.issn.1000-1980.2023.03.006},
doi = {10.3876/j.issn.1000-1980.2023.03.006},
abstract = {The purpose of this study is to quantitatively assess the influence of environmental factors on the spatial distribution of precipitation, to scientifically select the environmental factors for the statistical downscaling, and to address the problems of existing methods that cannot avoid the linearity assumption, ensure the immunity of multiple independent variables covariance and effectively explore the influence of factor interactions on the distribution of precipitation. By taking the Luanhe River basin as the research object, a quantitative analysis method based on GeoDetector is proposed and this study investigates the influence of environmental factors and their interactions on the spatial distribution of precipitation from three aspects: factor detection, interaction detection and ecological detection. Firstly, the factor detection results show that the influence of latitude, longitude, slope, slope direction, NDVI and elevation all exceed 1% in the annual, seasonal, monthly and tenday scales, and all these factors can directly affect the distribution of precipitation, among which latitude, longitude and elevation have the most significant influence on the distribution of precipitation. Secondly, the interaction detection results show that except for elevation-slope in February and NDVI-longitude in July, the other interactions are enhanced and the influences of all factors exceed 10%, which are more significant than that of single factor. Thirdly, the ecological detection results show that the influences of different environmental factors on the precipitation distribution are significantly different.}
}