Satellite Data Assimilation for Groundwater Analysis
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Geology, Geomorphology and Hydrology".
Deadline for manuscript submissions: closed (30 November 2023) | Viewed by 7670
Special Issue Editors
Interests: groundwater; geographic information system; satellite data assimilation; sustainability
Interests: remote sensing; geochemical data; transport processes; water quality; data fusion
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Groundwater is increasingly in demand for municipal, agricultural, and industrial uses. Climate change has resulted in severe droughts, which further stress groundwater resources. Water managers are increasingly under pressure to manage aquifers in a sustainable fashion, but doing so requires a thorough understanding of aquifer dynamics, water balances, and how groundwater levels and storage are changing over time. Groundwater monitoring can be time-consuming and expensive and is especially difficult in developing countries where well data are both sparse and unreliable. Recent technological advances in remote sensing, data analytics, machine learning, etc. have made it possible to gain new insights into aquifer health, groundwater usage trends, recharge, and evapotranspiration using Earth observations. In particular, remote data products such as the Gravity Recovery and Climate Experiment (GRACE), Moderate Resolution Imaging Spectroradiometer (MODIS), Shuttle Radar Topography Mission (SRTM), and Enhanced Thematic Mapper (ETM) have all been used to directly or indirectly characterize groundwater. In this Special Issue, we invite papers that share state-of-the-art techniques for leveraging these and other remote sensing technologies for groundwater analysis, leading to more holistic and sustainable management of this precious natural resource.
Dr. Norman L. Jones
Dr. Gustavious Paul Williams
Guest Editors
Manuscript Submission Information
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Keywords
- groundwater
- sustainability
- aquifers
- recharge
- subsidence
- evapotranspiration
- data analytics
- machine learning