Abstract

It is essential to investigate the influences of environmental elements on snow cover to understand the mechanism of the snowmelt process. These elements, as influencing factors, have spatial heterogeneity, which results in significant differences and uncertainties in the extent and range of their effects at different scales. However, little research has been conducted on the spatial interaction and mechanisms of these factors at multiple scales. This study selected the Manas River basin in the Tianshan Mountains as the study area. The study period is 2015–2020. The snow cover status index is calculated based on available Landsat8-OLS/TIRS data; influencing factors are collected from multiple datasets. Their relationships are explored using a novel zonal spatial panel model, fully considering the spatial, proximity, and scale effects. The findings are as follows: (1) There is a robust spatial interaction and proximity effect between snowmelt and various factors, and such effects display distinct spatial heterogeneity. The elevation (ELE), slope (SLP), land surface temperature (LST), and normalized digital vegetation index (NDVI) showed significant overall dominant effects on the snow melting process. The influencing factors with apparent proximity effects are LST, ELE, SLP, NDVI, and air temperature (TEMP), and their influence ranges are different. (2) The relative importance and significance rank of dominant influencing factors vary under different partition schemes and scales. As the scale decreases, the significance of terrain- and vegetation-related factors increases, whereas the significance of temperature- and elevation-related factors decreases, and the number of dominant factors also decreases. (3) The influencing factors represent distinct characteristics among each zone at the optimally partitioned scale we defined. The overall influencing pattern demonstrates a characteristic of being globally dictated by elevation and temperature, with local terrain factors, vegetation, and wind speed modifying this pattern. Our study provides practical data support and a theoretical basis for deepening our understanding of the influence mechanism of the snow melting process.

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