An Integration Approach for Mapping Field Capacity of China Based on Multi-Source Soil Datasets
An Integration Approach for Mapping Field Capacity of China Based on Multi-Source Soil Datasets
复制标题
基于多源土壤数据集的中国田间能力测绘一体化方法
DOI：
10.3390/w10060728
复制
发表时间：
2018
期刊：
影响因子：
3.4
通讯作者：
Liu Zhenchen
中科院分区：
文献类型：
--
作者：
Wu Xiaotao;Lu Guihua;Wu Zhiyong;He Hai;Zhou Jianhong;Liu Zhenchen
田间持水量是土壤水分循环、农业灌溉和干旱监测的重要参数之一。采用人工测量的方法很难获得大范围的田间持水量分布，既费时又费力。基于中国3个土壤数据集和2388个田间持水量实测数据，利用已有的土壤传递函数（PTFs）和多元线性回归（MLR）建立了田间持水量集合成员。在对各集合成员的精度进行评估后，提出了一种用于估算中国250 m网格化田间持水量数据集的田间持水量分布和发展的集成方法。在区域尺度上，原位田间持水量与集合田间持水量的空间相关系数（R）为0.73，均方根误差（RMSE）为0.048 m3·m−3。集合场容量与实际场容量分布具有很好的一致性，与前人提供的场容量数据相比，偏差得到了修正。这是一个潜在的产品，在水文和农业实践中，在大尺度和精细尺度上，特别是在无测量的地区估计现场容量。
Field capacity is one of the most important soil hydraulic properties in water cycle, agricultural irrigation, and drought monitoring. It is difficult to obtain the distribution of field capacity on a large scale using manual measurements that are both time-consuming and labor-intensive. In this study, the field capacity ensemble members were established using existing pedotransfer functions (PTFs) and multiple linear regression (MLR) based on three soil datasets and 2388 in situ field capacity measurements in China. After evaluating the accuracy of each ensemble member, an integration approach was proposed for estimating the field capacity distribution and development of a 250 m gridded field capacity dataset in China. The spatial correlation coefficient (R) and root mean square error (RMSE) between the in situ field capacity and ensemble field capacity were 0.73 and 0.048 m3·m−3 in region scale, respectively. The ensemble field capacity shows great consistency with practical distribution of field capacity, and the deviation is revised when compared with field capacity datasets provided by previous researchers. It is a potential product for estimating field capacity in hydrological and agricultural practices on both large and fine scales, especially in ungauged regions.