首页|期刊导航|水土保持研究|基于UAV数据的黄河中游多沙粗沙区小流域水土保持措施空间优化配置及减沙潜力研究

基于UAV数据的黄河中游多沙粗沙区小流域水土保持措施空间优化配置及减沙潜力研究OA

Spatial optimization of soil and water conservation measures and sediment reduction potential in small watersheds of rich and coarse sediment area in middle reaches of Yellow River based on UAV data

中文摘要英文摘要

[目的]研究高精度数据下黄河中游多沙粗沙区小流域的土壤侵蚀状况,提出水土保持措施空间优化配置方案,为小流域综合治理提供理论参考.[方法]以黄河中游多沙粗沙区3个典型小流域(海勒斯太沟、六道沟、杨家沟)为研究区,基于小流域2023年无人机正射影像、多光谱数据、DSM数据以及土壤野外采样数据等,利用RUSLE模型、最优参数地理探测器和GIS技术分析3个小流域土壤侵蚀空间变异特征及其驱动因素;提出植被覆盖度(FVC)在可持续阈值内(<65%)提升10%~35%以及梯田、淤地坝空间优化配置方案,进而评估单一水土保持措施和多措施组合配置情景下的减沙潜力.[结果](1)3个小流域2023年土壤侵蚀均以微度和轻度侵蚀为主,但强烈及以上侵蚀面积占比在11.69%~15.65%,水土保持率介于45.83%~65.32%.(2)坡度、土地利用和植被覆盖度是土壤侵蚀空间变异的主导因素,且坡度与土地利用交互作用的非线性增强效果最为显著.(3)小流域水土保持措施配置的减沙效益排序为FVC提升+梯田+淤地坝>FVC提升+梯田>FVC提升+淤地坝>FVC提升>单一工程措施.在可持续阈值区内FVC提升35%时,3个小流域减沙潜力为23.74%~30.97%;在FVC提升35%+梯田+淤地坝配置情景下,3个小流域减沙潜力为26.37%~35.71%.[结论]UAV数据提升了土壤侵蚀强度识别和水土保持措施空间优化配置的精度,3个小流域的谷坡和裸地区是侵蚀防控的关键区.流域多措施优化配置具有显著减沙效应,但应以植被恢复为核心,工程措施为补充.

[Objective]This study aims to investigate the soil erosion conditions in small watersheds of rich and coarse sediment area in the middle reaches of the Yellow River using high-precision data,and to propose a spatial optimization scheme for soil and water conservation measures,providing theoretical references for the comprehensive management of small watersheds.[Methods]Three typical small watersheds(Hailesitaigou,Liudaogou,and Yangjiagou)in the rich and coarse sediment area of the middle reaches of the Yellow River were selected as the study area.Based on 2023 UAV orthophotos,multispectral data,DSM data,and field soil sampling data of the small watersheds,the Revised Universal Soil Loss Equation(RUSLE)model,optimal parameters-based geodetector,and GIS techniques were used to analyze the spatial variation characteristics of soil erosion and its key driving factors in the three small watersheds.Schemes for the improvement of fractional vegetation cover(FVC)by 10%~35%within a sustainable threshold(<65%)and for the spatial optimization of terraces and check dams were proposed.Subsequently,sediment reduction potential under scenarios of single and multiple soil and water conservation measures was evaluated.[Results](1)In 2023,soil erosion in the three small watersheds was predominantly very slight and slight erosion,while the proportion of areas with intense or higher erosion reached 11.69%~15.65%.The soil and water conservation rate ranged from 45.83%to 65.32%.(2)Slope,land use,and FVC were the dominant drivers of the spatial variation of soil erosion,and the nonlinear enhancement effect of the interaction between slope and land use was the most significant.(3)The soil and water conservation measures in the small watersheds ranked in terms of sediment reduction benefits as follows:FVC increase+terraces+check dams>FVC increase+terraces>FVC increase+check dams>FVC increase>single engineering measures.When FVC was increased by 35%within the sustainable threshold,the sediment reduction potential of the three small watersheds was 23.74%~30.97%.Under the scenario of 35%FVC increase+terraces+check dams,the sediment reduction potential in the three small watersheds was 26.37%~35.71%.[Conclusion]UAV data significantly enhance the accuracy of soil erosion intensity identification and the spatial optimization of soil and water conservation measures.The valley slopes and bare land areas in the three small watersheds are the key areas for erosion control.The optimization of multiple measures in the watersheds demonstrates significant sediment reduction effects,but vegetation restoration should be taken as the core,with engineering measures serving as a supplement.

陈新佳;付金霞;吴楚瑜;韩颖;王文静;杨芷茵

西北农林科技大学 资源环境学院,陕西 杨凌 712100西北农林科技大学 资源环境学院,陕西 杨凌 712100西北农林科技大学 资源环境学院,陕西 杨凌 712100西北农林科技大学 资源环境学院,陕西 杨凌 712100西北农林科技大学 资源环境学院,陕西 杨凌 712100西北农林科技大学 资源环境学院,陕西 杨凌 712100

农业科技

UAV数据RUSLE模型土壤侵蚀驱动因素探测水土保持措施优化配置减沙潜力

UAV dataRUSLE modelsoil erosiondetection of driving factorsoptimization of soil and water conservation measuressediment reduction potential

《水土保持研究》 2026 (2)

24-34,11

国家重点研发计划项目课题(2022YFF1300805)国家自然科学基金黄河水科学研究联合基金(U2243210)

10.13869/j.cnki.rswc.2026.02.045

评论