模拟地下水储存动态的遥感技术:全面审查

IF 3.1 Q2 GEOSCIENCES, MULTIDISCIPLINARY
Abba Ibrahim , Aimrun Wayayok , Helmi Zulhaidi Mohd Shafri , Noorellimia Mat Toridi
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引用次数: 0

摘要

本研究考察了用于定量监测地下水储量变化的遥感(RS)技术的最新进展,并评估了这些技术目前的能力和局限性。分析技术的演变跨越了从依赖稀疏点数据的经验到使用复杂的机器学习算法对多平台卫星测量数据进行同化的过程。主要进展显示,通过整合粗分辨率重力数据和雷达图像的高分辨率地动观测数据,增强了局部地下水测量的特征。显著的进展包括通过整合重力恢复与气候实验(GRACE)和干涉合成孔径雷达(InSAR)数据提高了精度。现在,云计算有助于对大型地理空间数据集进行深入分析,以应对地下水量化挑战。虽然已经取得了重大进展,但目前存在的制约因素包括:空间和时间分辨率较低,限制了流域尺度的实用性;传感器校准和数据合并造成的不确定性传播;缺乏系统验证,妨碍了业务准备。解决这些限制因素对于持续改进地下水监测技术至关重要。本综述指出了克服这些局限性的可行途径,强调了卫星重力测量、雷达干涉测量和水文地质物理技术的标准化融合框架。为多源地下信息同化开发强大的基于云的建模平台是一项重要建议,强调了显著提高地下水量化精度的潜力。这篇综合评论为水资源和遥感专家提供了宝贵的资源,让他们深入了解不断发展的方法,并为地下水储存监测工具的未来发展铺平道路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Remote Sensing Technologies for Unlocking New Groundwater Insights: A Comprehensive Review

This study examined recent advances in remote sensing (RS) techniques used for the quantitative monitoring of groundwater storage changes and assessed their current capabilities and limitations. The evolution of the techniques analyses spans from empirical reliance on sparse point data to the assimilation of multi-platform satellite measurements using sophisticated machine learning algorithms. Key developments reveal enhanced characterisation of localised groundwater measurement by integrating coarse-resolution gravity data with high-resolution ground motion observations from radar imagery. Notable advances include improved accuracy achieved by integrating Gravity Recovery and Climate Experiment (GRACE) and Interferometric Synthetic Aperture Radar (InSAR) data. Cloud computing now facilitates intensive analysis of large geospatial datasets to address groundwater quantification challenges. While significant progress has been made, ongoing constraints include coarse spatial and temporal resolutions limiting basin-scale utility, propagation of uncertainties from sensor calibrations and data merging, and a lack of systematic validation impeding operational readiness. Addressing these limitations is critical for continued improvement of groundwater monitoring techniques. This review identifies promising pathways to overcome these limitations, emphasising standardised fusion frameworks for satellite gravimetry, radar interferometry, and hydrogeophysical techniques. The development of robust cloud-based modelling platforms for multi-source subsurface information assimilation is a key recommendation, highlighting the potential to significantly advance groundwater quantification accuracy. This comprehensive review serves as a valuable resource for water resource and remote sensing experts, providing insights into the evolving landscape of methodologies and paving the way for future advancements in groundwater storage monitoring tools.

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来源期刊
Journal of Hydrology X
Journal of Hydrology X Environmental Science-Water Science and Technology
CiteScore
7.00
自引率
2.50%
发文量
20
审稿时长
25 weeks
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