Global mapping of volumetric water retention at 100,330 and 15000 cm suction using the WoSIS database

作     者：Maria Eliza Turek Laura Poggio Niels H.Batjes Robson Andre Armindo Quirijn de Jong van Lier Luis de Sousa Gerard B.M.Heuvelink Maria Eliza Turek;Laura Poggio;Niels H.Batjes;Robson André Armindo;Quirijn de Jong van Lier;Luis de Sousa;Gerard B.M.Heuvelink

作者机构：ISRIC-World Soll InformationWageningemthe Netherlands Graduate Program in Environmental EngineeringFederal University of ParunaCurtibaR Brazil Soll Geography and Landscope Group Wageningen UniversityWageningenthe Netherlands Department of PhysicsFederul University of LavrasMGBrarll CENA-Universiy of Sao PouloPinacicabasaoBrazil 

出 版 物：《International Soil and Water Conservation Research》 (国际水土保持研究（英文）)

年 卷 期：2023年第11卷第2期

页      面：225-239页

核心收录：

学科分类：082802[工学-农业水土工程] 090707[农学-水土保持与荒漠化防治] 0907[农学-林学] 08[工学] 0828[工学-农业工程] 09[农学] 0815[工学-水利工程] 

基　　金：Global Research Alliance on Agricultural Greenhouse Gases Universidade Federal do Paraná, UFPR 

主　　题：Digital soil mapping Soil hydraulic properties Pedometrics SoilGrids 

摘      要：Present global maps of soil water retention(SWR)are mostly derived from pedotransfer functions(PTFs)applied to maps of other basic soil *** an alternative, point-based mapping of soil water content can improve global soil data availability and *** developed point-based global maps with estimated uncertainty of the volumetric SWR at 100,330 and 15000 cm suction using measured SWR data extracted from the WoSIS Soil Profile Database together with data estimated by a random forest PTF(PTF-RF).The point data was combined with around 200 environmental covariates describing vegetation,terrain morphology,climate,geology,and hydrology using *** total,we used 7292,33192 and 42016 SWR point observations at 100,330 and 15000 cm,respectively,and complemented the dataset with 436108 estimated values at each *** cross-validation yielded a Root Mean Square Error(RMSE)of6380,7.112 and 6.48510^(-2)cm^(3)cm^(-3),and a Model Efficiency Coefficient(MEC)of0.430,0386,and 0.471,respectively,for 100,330 and 15000 *** results were also compared to three published global maps of SWR to evaluate differences between point-based and map-based mapping ***-based mapping performed better than the three map-based mapping approaches for 330 and 15000 cm,while for 100 cm results were similar,possibly due to the limited number of SWR observa-tions for 100 *** sources or uncertainty identified included the geographical clustering of the data and the limitation of the covariates to represent the naturally high variation of SWR.