DU Xiaotong,FANG Xiuqin,WANG Wei,et al.Estimation of Soil Moisture in Root Zone of Semiarid Area Based on SMAR Model[J].Research of Soil and Water Conservation,2020,27(03):119-127,133.
基于SMAR模型的半干旱区根系层土壤湿度估算
- Title:
- Estimation of Soil Moisture in Root Zone of Semiarid Area Based on SMAR Model
- 文章编号:
- 1005-3409(2020)03-0119-09
- Keywords:
- CDF matching; SMAR model; surface layer; root zone; soil moisture
- 分类号:
- S152.7
- 文献标志码:
- A
- 摘要:
- 根系层土壤湿度控制植被根系的水分吸收和蒸腾过程,是陆地—大气相互作用中的一个重要变量。为了获得根系层土壤湿度的时空分布,以半干旱区的老哈河流域为研究对象,利用具有物理基础的土壤水分分析关系(SMAR)模型,并结合遥感土壤湿度产品进行研究。结果表明:利用土壤物理属性、归一化植被指数(NDVI)和实际蒸散发作为自变量进行多元线性回归分析,可以建立SMAR模型参数的估算方程(p<0.05,双尾t检验)。将遥感土壤湿度产品与SMAR模型结合估算区域根系层的土壤湿度具有良好效果,与基于实测数据的估算结果比较,其相关性R主要分布在0.5～0.9,平均值为0.692(p<0.05,双尾t检验),平均绝对误差、平均相对误差、均方根误差和标准偏差总体均<0.1。SMAR模型与遥感数据产品结合能够良好地模拟出区域尺度根系层土壤湿度的空间分布状况。该研究为更大尺度根系层土壤湿度的估算提供支撑,也能更好地运用于干旱半干旱区农业规划、干旱监测及其他水文模拟。
- Abstract:
- Soil moisture in root zone controls the process of water absorption and transpiration of vegetation, which is an important variable in land-atmosphere interaction. In order to obtain the spatial and temporal distribution of soil moisture in root zone, we select the Laohahe River Basin located in the semiarid area as the research area, and examine the patterns of soil moisture in root zones by using the physical soil moisture analytical relationship(SMAR)model and the remote sensing soil moisture products. The results show that the equation for estimating the parameters of SMAR model (p<0.05, two-tailed t-test)can be established by using soil physical properties, the normalized vegetation index and the actual evapotranspiration as independent variables for multivariate linear regression analysis. The combination of remote sensing soil moisture products and SMAR model has a good performance for the estimation of soil moisture in the root zones of the region. Compared the estimation results based on the remotely sensed SM products with the ones based on the field measurements, the correlation coefficients mainly distributed in range of 0.5～0.9, with the average value of 0.692 (p<0.05, two-tailed t-test). The mean absolute error, the mean relative error, the mean square root error, and the standard deviation are generally less than 0.1. In general, the combination of SMAR model and remote sensing data products can well estimate the spatial distribution of soil moisture in root zones at the regional scale. This study can provide the support for the estimation of soil moisture in the root zones at larger scale, and can improve agricultural planning, drought monitoring and other hydrological simulation in the arid and semi-arid areas.
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备注/Memo
收稿日期:2019-08-18 修回日期:2019-09-10资助项目:“十三五”国家重点研发计划项目“陆地水循环演变及其在全球变化中的作用研究”(2016YFA0601500)第一作者:杜晓彤(1995—),女,江苏盐城人,硕士研究生,主要从事土壤湿度的估算,分布式水文模型集成的研究。E-mail:1216528854@qq.com通信作者:方秀琴(1978—),女,安徽池州人,博士,副教授,主要从事地表参数遥感反演、水文模型集成及山洪灾害防治等方面的研究。E-mail:kinkinfang@hhu.edu.cn