Mapping Farmland-Soil Moisture at a Regional Scale Using a Distributed Hydrological Model: Case Study in the North China Plain
Mapping Farmland-Soil Moisture at a Regional Scale Using a Distributed Hydrological Model: Case Study in the North China Plain
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DOI：
10.1061/(asce)ir.1943-4774.0001036
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发表时间：
2016-04
期刊：
影响因子：
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通讯作者：
Xuerui Gao;Chuiyu Lu;Luan Qinghua;Shuyu Zhang;Jiahong Liu;Dongmei Han
中科院分区：
文献类型：
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作者：
Xuerui Gao;Chuiyu Lu;Luan Qinghua;Shuyu Zhang;Jiahong Liu;Dongmei Han
土壤水分的时空分布和格局研究目前常用的方法是点测和遥感技术。然而，点测量被称为是成本密集和耗时，而遥感在描述土壤水分的空间和时间特征，特别是深层土壤的精度有限。本文介绍了一种基于分布式水文模型（MODCYCLE）和克里格插值（KIM）的区域尺度农田土壤水分遥感方法。以华北平原邯郸市为研究区域，对该方法进行了验证。结果表明，12个监测站的土壤水分观测数据与本文模拟结果具有较好的一致性。最大相对误差系数为8.8%，最小相关系数也在0.66以上，具有较好的可靠性和实用性。
AbstractCurrently, point measurement and remote sensing technique are two frequently used methods to study the spatial-temporal distribution and pattern of soil moisture. However, point measurement is known as cost-intensive and time-consuming, whereas remote sensing is limited in precision to describe spatial and temporal characteristics of soil moisture especially for deep layer soil. This study introduced a method to map farmland soil moisture using a distributed hydrological model (MODCYCLE) combined with the kriging interpolation method (KIM) at the regional scale. Handan City in the North China Plain was chosen as the study area to verify the method. According to the result, there is a significant consistency relationships between observed soil moisture data collected, respectively, from 12 monitoring stations and simulated results in this paper. The maximum relative error coefficient is as low as 8.8%, and even the minimum correlation coefficient is more than 0.66, which shows a good reliability an...