三峡库区典型农业小流域土壤饱和导水率特征  

Characteristics of Soil Saturated Hydraulic Conductivity in Typical Agricultural Small Watershed of Three Gorges Reservoir Area

作　　者：韩唯 陈晓燕[1,2] 陶婷婷[1,2] Han Wei;Chen Xiaoyan;Tao Tingting(Key Laboratory of Soil and Water Conservation and Ecological Restoration of Chongqing,Southwest University,Chongqing 400716,China;College of Resources and Environment,Southwest University,Chongqing 400716,China)

机构地区：[1]西南大学水土保持生态修复重庆市重点实验室,重庆400716 [2]西南大学资源环境学院,重庆400716

出　　处：《水土保持通报》2024年第5期83-91,99,共10页Bulletin of Soil and Water Conservation

基　　金：重庆市技术创新与应用发展专项重点项目“中低产坡耕地质量提升及土壤固碳增汇协同生态技术集成与应用”(CSTB2022TIAD-LUX0005);国家自然科学基金项目“饱和紫色土坡面降雨片流与集中水流侵蚀过程及动力机制”(42177314);重庆市研究生科研创新项目“野外长坡面侵蚀-沉积泥沙分选时空变化特征研究”(CYS23200)。

摘　　要：[目的]通过简单易测的土壤性质来建立传递函数从而间接获得土壤饱和导水率(K_(s)),为三峡库区典型农业小流域土壤水分运移及模拟提供数据支撑。[方法]试验以三峡库区石盘丘小流域为研究对象,通过测定典型土地利用类型(耕地、园地、草地)的饱和导水率及其他土壤基本理化性质,结合相关性和主成分分析,分别运用多元线性回归(MLR)、BP神经网络(BP-ANN)、支持向量机(SVM)法构建研究区表层土壤饱和导水率的传递函数模型。在此基础上,选取4种常见的饱和导水率传递函数模型,验证其在本研究区的适用性。[结果]土壤K_(s)均值大小表现为:草地>园地>耕地,且在不同土地利用类型间存在显著差异;土壤饱和导水率与容重、有机质含量、饱和含水量、土壤质地显著相关;与多元线性回归、BP神经网络、支持向量机构建的K_(s)传递函数模型相比,以往采用的土壤传递函数模型对本研究区土壤饱和导水率的预测效果较差,三种方法建立的传递函数预测精度表现为:SVM>BP-ANN>MLR,而采用主成分P 1和主成分P 2作为输入变量的预测精度更佳。[结论]不同土地利用类型下的K_(s)值具有较强的空间变异性,通过BP神经网络和支持向量机构建的饱和导水率传递函数模型能满足本研究区K_(s)预测要求,其中支持向量机法的预测精度优于BP神经网络。[Objective]The pedo-transfer functions was established through the simple and easily measurable soil properties,and the soil saturated hydraulic conductivity was obtained indirectly,in order to provide data support for soil water transport and simulation of typical agricultural small watershed of the Three Gorges reservoir area.[Methods]Using the Shipanqiu watershed of the Three Gorges reservoir area as the research object,the soil saturated hydraulic conductivity(K_(s))and other basic physical and chemical properties of typical land use types(cultivated land,garden land,and grassland)were measured.In addition to correlation and principal component analysis,multiple linear regression(MLR),BP neural network(BP-ANN),and support vector machine(SVM)methods were used to construct pedo-transfer functions for the saturated hydraulic conductivity of the surface soil in the study area.Furthermore,four common pedo-transfer functions were selected to verify their applicability in this study area.[Results]The average soil K_(s)values were in the order of grassland>garden>cultivated land,with significant differences among different land use types.The saturated hydraulic conductivity of the soil was significantly correlated with bulk density,organic matter content,saturated water content,and soil texture.Compared with the K_(s)pedo-transfer functions established through multiple linear regression,BP neural network,and support vector machine,the previously used soil transfer functions model have poor prediction performance for soil saturated hydraulic conductivity in this study area.The forecast accuracy of the transfer function created using the three methods was in the order of SVM>BP-ANN>MLR,and the forecast accuracy created using principal component P 1 and P 2 as input variables was better than others.[Conclusion]The K_(s)values under different land use types have strong spatial variability.The pedo-transfer functions built through BP-ANN and SVM can meet the prediction requirements of K_(s)in this study area,and the predi

关 键 词：三峡库区 农业小流域 饱和导水率 土壤传递函数 支持向量机 BP神经网络 

分 类 号：S152.7[农业科学—土壤学]