| 引用本文: | 马春芽,王景雷,陈震,等.基于温度植被干旱指数的土壤水分空间变异性分析[J].灌溉排水学报,2019,38(3):28-34. |
| MA Chunya,WANG Jinglei,CHEN Zhen,et al.基于温度植被干旱指数的土壤水分空间变异性分析[J].灌溉排水学报,2019,38(3):28-34. |
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| 摘要: |
| 【目的】深入探讨区域土壤水分空间变异及其尺度效应，优化灌区尺度土壤水分采样精度，并提供合理采样方案。【方法】以人民胜利渠灌区为研究区，利用Landsat 8遥感影像，构建了温度植被干旱指数，根据其与土壤水分的相关关系获得研究区土壤水分分布。利用经典统计学和地统计学分析方法对2种尺度下土壤水分分布进行了空间变异性分析。【结果】不同尺度土壤水分服从正态分布，随着研究尺度和分辨率的增大，土壤水分的空间变异系数逐步增大；地统计学分析表明小尺度的块金基台比（C0/（C0+C））小于0.25，具有较强的空间相关性，而灌区尺度的块金基台比大于0.25小于0.75，具有中等强度的空间相关性。灌区尺度所选不同分辨率下土壤水分的变异系数、变程以及块金基台比变化很小。【结论】人民胜利渠灌区尺度土壤水分的获取不适宜用插值法，比较适宜用遥感法。 |
| 关键词: 温度植被指数； 土壤水分； 空间变异 |
| DOI：10.13522/j.cnki.ggps.20170036 |
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| Spatial Distribution of Soil Moisture Estimated Using Thermal Vegetation Drought Indices |
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MA Chunya，WANG Jinglei，CHEN Zhen，YIN Huanqing, CHEN Yong, HUANG Xiuqiao
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1. Key Laboratory of Water-saving Agriculture , Farmland Irrigation Research Institute, Chinese Academy of Agricultural Sciences, Xinxiang 453002, China; 2. Graduate School of Chinese Academy of Agricultural Sciences, Beijing 100081, China; 3. Key Laboratory of Crop Water Use and Regulation, Ministry of Agriculture, Farmland Irrigation Research Institute, Chinese Academy of Agricultural Sciences, Xinxiang 453002, China; 4. Huojia Management Office of Henan People’s Victory Canal Irrigation Area Administration, Xinxiang 453003, China; 5. Water Conservancy Bureau of Lanling County, Linyi 277700, China
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| Abstract: |
| 【Objective】Understanding inherent spatial variability of soil moisture at various scales can improve water management and soil moisture sampling in irrigation regions. The objective of this paper is to present a new method to estimate this based on vegetation drought indices.【Method】 The study was carried out in the People’s Victory Canal Irrigation District, and the Landsat 8 remote sensing imagery was used to estimate the vegetation drought index based on canopy temperature. The relationship between TVDI and the soil moisture calculated from the imagery and the ground-truth data was used to estimate soil moisture distribution in the studied area. Soil moisture variation at two spatial scales was studied using the classical statistical and geo-statistical methods.【Result】The soil moisture in the two spatial scales followed normal distribution, and the variation coefficient of the soil moisture increased with scale and spatial resolution. The corresponding ratio of the spatial heterogeneity C0/(C0+C), where C0 was the nugget and C0+C was the sill of the small scale, was less than 0.25, indicating a strong spatial autocorrelation at small scale. The corresponding ratio of spatial heterogeneity at regional scale was between 0.25 and 0.75, indicating a moderate correlation at regional scale. The variation coefficient, the variation range and the corresponding ratio of spatial heterogeneity all showed limited change at different resolutions at regional scale.【Conclusion】Our results alluded that using point-measured data and interpolation method is inappropriate to estimate soil moisture in the People’s Victory Canal Irrigation District, and remote sensing method works better for estimating soil moisture distribution at regional scale. |
| Key words: Temperature Vegetation Drought Index; soil moisture; spatial variability |
