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针对大范围地面土壤水监测会耗费大量人力物力等问题,为了获取密度较高同时又准确可靠的流域土壤水数据用于时间稳定性分析,寻找可以反映流域土壤水平均状况的代表性点,利用分布式水文土壤植被模型(DHSVM)模拟淮河黄泥庄水文站以上小流域293个采样网格上、中、下三层土壤含水量数据。结果显示:垂向方向上,黄泥庄流域土壤水分时间稳定性随深度递减;流域上层和中层具备时间稳定性特征的代表性点具有较高的一致性,易发生于流域主要土壤和植被类型覆盖区域,在此区域布设测点观测土壤水,可以更准确快速地捕获代表黄泥庄流域上层和中层平均土壤水分特征;采样点7、17和215可作为上、中层土壤的流域平均土壤水代表性点,利用它们预测流域土壤水平均值,可降低观测成本。研究成果可为流域土壤水监测方案设计提供参考。
Abstract：The large scale ground soil moisture monitoring costs a lot of manpower and materials resources. In order to analyze the temporal stability of soil moisture in watershed scale using dense, accurate and reliable data, and search the representative points which can reflect the average soil moisture content of the entire watershed, the simulated data of soil moisture content in the upper, middle and lower layers of the 293 sampling points in the small Huangnizhuang watershed of the Huaihe River Basin is acquired, using the Distributed Hydrological Soil Vegetation Model(DHSVM). The result shows the temporal stability of soil moisture in Huangnizhuang watershed decreases with depth in the vertical direction. The representative sampling points which can be used to represent the temporal stability of the watershed are consistent in the upper and middle layers. They are tend to locate in the area covering dominant vegetation and soil type. If sensors were laid out in this region, the features of watershed average soil moisture in the upper and middle layers could be captured efficiently. The sampling points, No. 7, 17 and 215 are considered to be the representative points of soil moisture in the upper and middle soil layers in watershed. They can be used to predict the mean soil moisture content for the watershed. Thus the observation cost is surely reduced. Our study offers reference for the establishment of ground networks of soil moisture monitoring stations in watershed scale.
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基本信息:
DOI：10.13928/j.cnki.wrahe.2019.05.013
中图分类号:S152.7
引用信息:
[1]魏玲娜,陈喜,董建志,等.基于分布式水文模拟的流域土壤水分时间稳定性分析[J].水利水电技术,2019,50(05):104-114.DOI:10.13928/j.cnki.wrahe.2019.05.013.
基金信息:
国家自然科学基金重点支持项目(91747203);国家自然科学基金项目(41807286);; 江苏省高校自然科学研究项目(17KJB170016);; 水文水资源与水利工程科学国家重点实验室“一带一路”水与可持续发展科技基金(2018490311,2018491711)
2019-04-15
2019-04-15
2019-04-15