黄土高原千河流域土壤侵蚀风险时空变化及归因分析

Spatio-temporal variation and attribution of soil erosion risk in the Qianhe River Basin, Loess Plateau

  • 摘要: 千河流域是黄土高原南部渭河的一级支流,受自然环境与高强度人类活动的双重影响,其土壤侵蚀驱动机制具有显著的复杂性与空间异质性,目前尚缺乏针对性的定量解析。本文基于RUSLE模型对千河流域2000—2020年土壤侵蚀时空变化进行分析,并结合地理加权回归模型(GWR)和地理探测器定量(GeoDetector)分析了土壤侵蚀的主控因子及其交互作用。结果表明:千河流域2000—2020年土壤侵蚀总体呈减弱趋势,土壤侵蚀模数由约12.46 t·hm−2·a−1下降至10.58 t·hm−2·a−1,主要以微度和轻度侵蚀为主;空间分布格局为周围低,中部高;在驱动机制上,自然要素中的地形因子(坡度、高程)提供了侵蚀发生的基本约束,而在人类活动因子中,土地利用是影响千河流域土壤侵蚀的主要因素,其解释力为0.235,坡度和土地利用类型的交互作用对土壤侵蚀解释力最大为0.307;风险探测识别出在坡度8°~15°、高程10001500 m之间降雨侵蚀力为14001700 MJ·mm·hm−2·h−1·a−1,且土地利用为草地的区域易发生强烈土壤侵蚀。千河流域土壤侵蚀的时空演变特征研究,为流域的土壤侵蚀防治提供了重要数据支持和理论指导。

     

    Abstract: The Qianhe River basin, a main tributary of the Weihe River in the southern Loess Plateau, exhibits highly complex and spatially heterogeneous soil erosion drivers due to influences from natural environments and intensive human activities. To date, targeted quantitative analyses remain scarce. We employed the RUSLE (Revised Universal Soil Loss Equation) model to analyze the spatiotemporal changes in soil erosion in the Qianhe River basin from 2000 to 2020, and used the Geographically Weighted Regression (GWR) model and GeoDetector analysis to identify the key factors on soil erosion and their interactions. Results indicate that soil erosion in the basin showed an overall decreasing trend from 2000 to 2020, during which the soil erosion modulus decreased from 12.46 to 10.58 t·hm2·a−1, being characterized mainly by erosion in slight to light level. The spatial distribution pattern exhibited lower erosion in the periphery and greater erosion in the central area. Regarding the driving mechanisms, among natural factors, topographic elements (slope, elevation) provided fundamental constraints for the regional erosion. Among human activity factors, land use emerged as the primary determinant of soil erosion in the basin with the explanatory power of 0.235. The interaction between slope and land use type exhibited the highest explanatory power at 0.307 for soil erosion. Risk detection identified areas prone to severe soil erosion as those with slopes between 8°~15°, elevations between 10001500 m, rainfall erosion potential of 14001700 MJ·mm·hm2·h−1·a−1, and grassland land use. This study provided an important data support and theoretical guidance for erosion prevention and control in the watershed.

     

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