Soil moisture factor is one of the important parameters in the study of wind and sand fixation functions of ecosystems. Traditional methods often use potential evaporation, rainfall, and irrigation observed by meteorological stations to estimate soil moisture, which has significant limitations in terms of spatial continuity and data availability. Based on the development of remote sensing technology in soil moisture detection, we selected four remote sen-sing indicators for soil moisture (MODIS evapotranspiration ratio method, SMAP soil moisture ratio method, visible shortwave infrared drought index method, and remote sensing humidity index method) to improve the estimation of soil moisture factor in the modified wind erosion equation model (RWEQ), and used the improved algorithm to analyze the spatiotemporal variations and driving factors of wind prevention and sand fixation services in the northwest region of Liaoning Province from 2001 to 2021. The results showed that the MODIS evapotranspiration ratio method had the highest correlation with traditional meteorological methods in calculating soil moisture. The formula obtained by fitting the two could be used to improve the calculation of soil moisture factor in the RWEQ model. From 2001 to 2021, the wind prevention and sand fixation capacity in the northwest region of Liaoning Province showed strong spatial distribution characteristics in the northern and eastern regions, while weak in the central and western regions. According to Mann-Kendall trend testing, 72.7% of the regions in northwest Liaoning Province were showing an upward trend in their ability to prevent wind and fix sand. The application of geographic detector models for driving factor analysis showed that the change in wind and sand fixation capacity was a process of multiple factors interacting with each other, greatly influenced by soil type, annual wind speed, and economic development level. Moreover, the interaction between various driving factors had a higher impact on wind and sand fixation than that of single factors. The results could improve the RWEQ model estimation and provide technical support for the long-term analysis of ecological function formation mechanisms and driving forces in the northwest region of Liaoning.
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http://dx.doi.org/10.13287/j.1001-9332.202310.022 | DOI Listing |
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