中国水土保持科学2026，Vol.24Issue(3)：17-30,14.DOI:10.16843/j.sswc.2025344
基于Meta分析的黄土高原坡面典型水土保持措施减流减沙效应研究
A meta-analysis of the runoff and sediment reduction effects of typical soil and water conservation measures on slopes of the Loess Plateau
摘要
Abstract
[Objective]The Loess Plateau,widely acknowledged as one of the most ecologically fragile regions in China with the most severe soil erosion,serves as a critical area for soil and water conservation.Assessing the effectiveness and underlying driving mechanisms of conservation measures is essential for enhancing regional ecological security and sustainability.[Methods]This study was based on the observation of individual rainfall events.Meta-analysis was adopted to integrate multi-source data,including precipitation(P),slope gradient(S),slope length(L),and measure type(M).Furthermore,correlation analysis,redundancy analysis,and machine learning prediction models were combined to reveal the differences in the effects of different soil and water conservation measures and their dominant factors.[Results]1)Among vegetation and engineering measures,shrubs(50.07%)and fish-scale pits(36.93%)had the highest runoff reduction efficiency(RR),while shrubs(76.41%)and terraces(83.28%)achieved the highest sediment reduction efficiency(SR).For agricultural measures,ridge tillage achieved the highest RR(78.62%),whereas contour tillage showed the highest SR(40.63%).2)Correlation analysis showed P was extremely significantly negatively correlated with engineering SR(P<0.001);S was extremely significantly positively correlated with vegetation RR(P<0.001),but significantly(P<0.05)and extremely significantly(P<0.001)negatively correlated with engineering RR and agricultural SR,respectively;L had highly(P<0.01)significant negative correlations with vegetation SR and engineering RR.Redundancy analysis indicated M,L,M were the top contributors to RR of the three measure types,and L,P,S dominated their SR.3)Machine learning models predicted the RR and SR of soil and water conservation measures.XGBoost achieved the highest accuracy for vegetation RR(R2=0.74),MLP(Multi-Layer Perceptron)for engineering SR(R2=0.69),and Random Forest the smallest error for agricultural RR(R2=0.51).[Conclusion]This study systematically elucidates the differential effectiveness and key driving mechanisms of various soil and water conservation measures,thereby providing a scientific basis for their optimal allocation on the Loess Plateau.关键词
水土保持措施/Meta分析/机器学习/减流减沙/黄土高原Key words
soil and water conservation measures/meta-analysis/machine learning/runoff and sediment reduction/Loess Plateau分类
农业科技引用本文复制引用
金洋,张馨予,张帆,张守红..基于Meta分析的黄土高原坡面典型水土保持措施减流减沙效应研究[J].中国水土保持科学,2026,24(3):17-30,14.基金项目
国家重点研发计划项目"黄土高原小流域山水林田湖草沙综合治理与生态系统服务协同提升技术及示范"(2023YFF1305101) The National Key Research and Development Program"Integrated Management and Ecosystem-Service Enhancement Technologies for Mountain-Water-Forest-Field-Lake-Grass-Sand Systems in Small Watersheds of the Loess Plateau"(2023YFF1305101) （2023YFF1305101）
