| 引用本文: | 王庆明,,张越,郑荣伟, 等..基于遥感模型SDI的土壤盐渍化临界水位研究[J].灌溉排水学报,2022,41(3):98-104. |
| WANG Qingming,ZHANG Yue,ZHENG Rongwei, et al..基于遥感模型SDI的土壤盐渍化临界水位研究[J].灌溉排水学报,2022,41(3):98-104. |
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| 摘要: |
| 【目的】基于遥感模型快速识别大尺度空间土壤盐渍化程度并及时预警，以防止土壤盐渍化。【方法】通过分析归一化植被指数（NDVI）、盐分指数（SI）和地下水埋深之间的响应关系，探讨了一种基于遥感模型SDI（Salinization Detection Index）的土壤盐渍化临界地下水位确定方法，并应用于民勤绿洲区。【结果】①植被NDVI与土壤盐渍化程度具有指数关系，盐渍化遥感监测指数SDI可以综合反映区域植被长势和土壤盐渍化程度。②SDI和地下水埋深在空间分布上呈显著负相关关系，说明SDI能够较好地反应土壤盐渍化程度。【结论】民勤绿洲区轻度盐渍化、中度盐渍化和重度盐渍化对应的地下水埋深分别为4.7、3.2、1.8 m。 |
| 关键词: 土壤盐渍化；民勤绿洲；遥感模型；临界地下水位 |
| DOI：10.13522/j.cnki.ggps.2021160 |
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| A Remote Sensing Model to Determine the Critical Groundwater Depth for Soil Salinization |
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WANG Qingming, ZHANG Yue, ZHENG Rongwei, et al.
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1. State Key Laboratory of Hydrology-water Resources and Hydraulic Engineering, Hohai University, Nanjing 210024, China;
2. China Institute of Water Resources and Hydropower Research, Beijing 100038, China;
3. General Institute of Water Conservancy and Hydropower Planning and Design, Ministry of Water Resources, Beijing 100120, China;
4. Zhejiang Tongji Vocational College of Science And Technology, Hangzhou 311215, China
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| Abstract: |
| 【Objective】Evaporation of groundwater via capillary rise could result in solute accumulation in the proximity of the soil surface, which increases steadily when the groundwater table rises above a critical depth. Knowing this critical depth is crucial for water and salt management but difficult to determine in situ as it depends not only on groundwater depth but also on soil textures and other factors. The purpose of this paper is to propose a remote-sensing method to estimate this critical depth.【Method】Based on remote sensing images and ground-truth data, we first calculated the relationship between the normalized difference vegetation index (NDVI), soil salinization index (SI) and groundwater depth. We then proposed a salinization detection index (SDI) to determine the critical groundwater depth and validated it against data measured from a field at Minqin oasis.【Result】①There was an exponential relationship between NDVI and SI; SDI correctly described the relationship between vegetation health and soil salinization across the studied region. ②The spatial distribution of SDI and groundwater depth were inversely correlated, indicating that SDI can be used as a proxy of soil salinization. Critical groundwater depth associated with mild, moderate and severe soil salinization was 4.7 m, 3.2 m and 1.8m respectively.【Conclusion】We proposed a remote sensing model to estimate soil salinity and the critical groundwater depth, above which a further rise in groundwater table would cause soil salinization. Application of the model to field data showed that it is accurate and reliable to predict soil salinization and the critical groundwater depths associated with different levels of soil salinization. |
| Key words: soil salinization; Minqin oasis; remote sensing model; critical groundwater depth |
