地下水资源遥感评估技术研究进展

地下水的赋存和埋深是地下水资源勘察的重要内容。遥感技术具有数据获取快、综合成本低、观测尺度大等诸多优势。基于遥感的地下水资源评估技术一直受到研究人员的关注,也是遥感应用研究中的热点和难点。回顾总结了遥感技术在评估地下水赋存和埋深领域的应用与研究进展,根据不同评估技术的特点将其划分为单因子模型评估法、多因子综合模型评估法、重力卫星数据评估法3种。得出以下结论: ①地下水遥感评估技术经过多年发展,模型方法更加多样,精确度不断提高,可以作为传统地下水资源勘察的重要辅助手段; ②遥感评估地下水赋存的研究发展迅速,但针对地下水埋深信息的评估研究进展相对缓慢; ③高时空分辨率遥感技术和机器学习技术的结合运用、无人机遥感技术的应用是地下水资源遥感评估技术的未来发展方向。

Overview of the research progress of groundwater resources assessment technology based on remote sensing

The storage and depth of groundwater are important contents in groundwater resources survey. Remote sensing technology has advantages of fast data acquisition, low comprehensive cost and large observation scale. The groundwater resources assessment technology based on remote sensing has always attracted the attention of researchers, and it is also a hot and difficult issue in the field of remote sensing application research. This paper presents an overview of the application research progress of remote sensing technology in the assessment of groundwater storage and depth, and have divided the groundwater resources assessment technology into three types-single-factor model evaluation method, multi-factor comprehensive model evaluation method and evaluation method based on GRACE data auovding to their characteristics. Three conclusions are drawn. Firstly, the groundwater resources assessment technology based on remote sensing has been continuously enriched and the assessment accuracy has also been continuously improved after years of development, which can be used as an important auxiliary method for traditional groundwater resources survey. Secondly, the research on remote sensing evaluation technology for groundwater storage has developed rapidly, while these for groundwater depth have progressed relatively slowly. Thirdly, the combined use of high-temporal-spatial resolution remote sensing technology and machine learning technology, and the application of UAV remote sensing technology are future development directions of the groundwater resources assessment technology based on remote sensing.