黄土高原沟壑区典型流域不同算法土壤侵蚀集成模拟比较  

Ensemble simulation for soil erosion of a typical watershed in the gully region of Loess Plateau on the basis of different algorithms

作　　者：宋克鹏 李一帆 曲思仪 周帆 王彬[3] 王盛萍[1] SONG Kepeng;LI Yifan;QU Siyi;ZHOU Fan;WANG Bin;WANG Shengping(School of Water Resources and Hydropower Engineering,North China Electric Power University,102206,Beijing,China;School of Environmental Science and Engineering,North China Electric Power University,102206,Beijing,China;School of Soil and Water Conservation,Beijing Forestry University,100083,Beijing,China)

机构地区：[1]华北电力大学水利与水电工程学院,北京102206 [2]华北电力大学环境科学与工程学院,北京102206 [3]北京林业大学水土保持学院,北京100083

出　　处：《中国水土保持科学》2024年第2期81-89,共9页Science of Soil and Water Conservation

基　　金：国家重点研发计划项目课题“典型工程区水资源植被承载力与防护林体系优化配置技术研究与示范”(2022YFF1302501);水专项项目课题“密云水库水源地保护和监管集成技术示范”(2017ZX07108-002)。

摘　　要：为探究集成模拟技术对减少不同模型模拟土壤侵蚀的不确定性,以黄土高原昕水河流域为研究对象,采用Bates-Granger(BG)集成、等权重集成和Granger-Ramanathan集成技术,对广泛运用的Morgan-Morgan-Finney(MMF)、修正土壤流失方程(RUSLE)和中国土壤流失方程(CSLE)等进行集成模拟。集成模拟以流域出口泥沙观测进行率定,并根据纳什系数(NSE)、相关系数(R)、均方根误差(RMSE)进行模型模拟评价。结果表明:1)对于单一模型而言,MMF模拟效果在多数情况下优于CSLE和RUSLE模拟效果;2)集成模拟可显著改善土壤侵蚀模型模拟效果,集成模拟前后,模型评价指标如NSE、R、RMSE分别提高23.6%、15.8%、46.4%;3)不同集成模拟中BG集成算法在模型不确定性方面更加稳定、可靠。研究认为,在基于经验性模型开展流域土壤侵蚀模拟时,可以采用集成模拟技术进一步提升其模拟性能。[Background]The Loess Plateau is one of the most severely eroded areas in the world,and quantification of soil erosion has been an important research work in the Loess Plateau of China.Although there exist many different soil erosion models for simulating soil erosion,few studies have used ensemble models to simulate soil erosion.[Methods]To investigate whether ensemble simulation can effectively improve soil erosion simulation,this study used the techniques of Bates-Granger(BG),equal weight(EW)and Granger-Ramanathan(GR)to integrate three widely used empirical-based soil erosion models,being Morgan-Morgan-Finney(MMF),Revised Universal Soil Loss Equation(RUSLE),and Chinese Soil Loss Equation(CSLE),respectively,for simulating soil erosion and sediment yield of a loess watershed,i.e.,Xinshui River watershed.The training period(1991-2000)was for estimating the weight of each model,and the testing period(2001-2005)was for examining the applicability of the various ensemble approaches.The model performance was evaluated in terms of Nash coefficient(NSE),correlation coefficient(R),and root mean square error(RMSE),by against the measured sediment yield at the outlet of the watershed.Uncertainties of the model simulation were also evaluated by means of confidence interval.[Results]1)The three individual models differed in their performances,with MMF performing the best compared with the other two.2)Ensemble techniques greatly improved the performance of soil erosion simulation,and reduced uncertainties among various modelling tools.Comparing the best ensemble simulation with the best individual model,performances of NSE,R,and RMSE were improved by 23.6%,15.8%,and 46.4%,respectively.3)BG technique provided more accurate predictions than the other methods did,the width of the confidence interval for BG technique smaller than that of the others,indicating a more stable and reliable performance.[Conclusions]The performance of the widely used empirical soil erosion models(e.g.,RUSLE,CSLE)could be further enhanced by using the

关 键 词：土壤侵蚀模型 集成模拟 Bates-Granger Granger-Ramanathan 等权重 黄土高原流域 

分 类 号：S157.1[农业科学—土壤学]