Enhancing Aquifer Reliability and Resilience Assessment in Data-Scarce Regions Using Satellite Data: Application to the Chao Phraya River Basin
There are serious ecological and environmental risks associated with groundwater level decline, particularly in areas with little in situ monitoring. In order to monitor and assess the resilience and dependability of groundwater storage, this paper proposes a solid methodology that combines data from land surface models and satellite gravimetry. In particular, the GRACE Groundwater Drought Index (GGDI) is used to analyze the estimated groundwater storage anomalies (GWSA) from the Gravity Recovery and Climate Experiment (GRACE) and the Global Land Data Assimilation System (GLDAS). Aquifer resilience, or the likelihood of recovery after stress, and aquifer reliability, or the long-term probability of remaining in a satisfactory state, are calculated using the core method. The two main components of the methodology are (a) calculating GWSA by subtracting the surface and soil moisture components from GLDAS, total water storage from GRACE, and comparing the results to in situ groundwater level data; and (b) standardizing GWSA time series to calculate GGDI and then estimating aquifer resilience and reliability based on predetermined threshold criteria. Using this framework, we validate GRACE-derived GWSA with in situ observations in eight sub-basins of the Chao Phraya River (CPR) basin, obtaining Pearson correlation coefficients greater than 0.82. With all sub-basins displaying values below 35%, the results raise significant questions about resilience and dependability. This method offers a framework that can be applied to assessments of groundwater sustainability worldwide.
Authors
- Ho Huu Loc (ORCID: https://orcid.org/0000-0002-8300-6699)
- Sangam Shrestha (ORCID: https://orcid.org/0000-0002-4972-3969)
- Yaggesh Sharma (ORCID: https://orcid.org/0009-0006-0038-5125)
- Mohanasundaram Shanmugam (ORCID: https://orcid.org/0000-0002-3199-8403)
- Seokhyeon Kim (ORCID: https://orcid.org/0000-0002-1819-8022)
- Mukand S. Babel (ORCID: https://orcid.org/0000-0003-4203-0059)
Institutions
- Kyung Hee University (KR)
- Asian Institute of Technology (TH)
- Wageningen University & Research (NL)
Publication Details
- Journal
- Remote Sensing
- Published
- 2025-05-15
- DOI
- https://doi.org/10.3390/rs17101731
- Citations
- 4
- Primary Topic
- Water resources management and optimization
- Type
- article
- Field-Weighted Citation Impact
- 4.58
Funders
- Ministry of Trade, Industry and Energy
- Ministry of Environment
- Ministry of Education, India
- Asian Institute of Technology
- Korea Environmental Industry and Technology Institute
- Korea Institute of Energy Technology Evaluation and Planning