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 fro...
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MDPI AG
2025-05-01
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| author | Yaggesh Kumar Sharma S. Mohanasundaram Seokhyeon Kim Sangam Shrestha Mukand S. Babel Ho Huu Loc |
| author_facet | Yaggesh Kumar Sharma S. Mohanasundaram Seokhyeon Kim Sangam Shrestha Mukand S. Babel Ho Huu Loc |
| author_sort | Yaggesh Kumar Sharma |
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| description | 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 (<i>GWSA</i>) 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 <i>GWSA</i> 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 <i>GWSA</i> time series to calculate GGDI and then estimating aquifer resilience and reliability based on predetermined threshold criteria. Using this framework, we validate GRACE-derived <i>GWSA</i> 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. |
| format | Article |
| id | doaj-art-25f998d67fcd481da52c7add8a2cff86 |
| institution | DOAJ |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-05-01 |
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| series | Remote Sensing |
| spelling | doaj-art-25f998d67fcd481da52c7add8a2cff862025-08-20T03:12:15ZengMDPI AGRemote Sensing2072-42922025-05-011710173110.3390/rs17101731Enhancing Aquifer Reliability and Resilience Assessment in Data-Scarce Regions Using Satellite Data: Application to the Chao Phraya River BasinYaggesh Kumar Sharma0S. Mohanasundaram1Seokhyeon Kim2Sangam Shrestha3Mukand S. Babel4Ho Huu Loc5Department of Civil Engineering, College of Engineering, Kyung Hee University, Yongin 17104, Republic of KoreaWater Engineering and Management, Asian Institute of Technology, Pathumthani 12120, ThailandDepartment of Civil Engineering, College of Engineering, Kyung Hee University, Yongin 17104, Republic of KoreaWater Engineering and Management, Asian Institute of Technology, Pathumthani 12120, ThailandWater Engineering and Management, Asian Institute of Technology, Pathumthani 12120, ThailandWater Engineering and Management, Asian Institute of Technology, Pathumthani 12120, ThailandThere 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 (<i>GWSA</i>) 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 <i>GWSA</i> 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 <i>GWSA</i> time series to calculate GGDI and then estimating aquifer resilience and reliability based on predetermined threshold criteria. Using this framework, we validate GRACE-derived <i>GWSA</i> 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.https://www.mdpi.com/2072-4292/17/10/1731groundwater monitoringaquifer reliability and resiliencesatellite data analysisgravity recovery and climate experimentgroundwater drought index |
| spellingShingle | Yaggesh Kumar Sharma S. Mohanasundaram Seokhyeon Kim Sangam Shrestha Mukand S. Babel Ho Huu Loc Enhancing Aquifer Reliability and Resilience Assessment in Data-Scarce Regions Using Satellite Data: Application to the Chao Phraya River Basin Remote Sensing groundwater monitoring aquifer reliability and resilience satellite data analysis gravity recovery and climate experiment groundwater drought index |
| title | Enhancing Aquifer Reliability and Resilience Assessment in Data-Scarce Regions Using Satellite Data: Application to the Chao Phraya River Basin |
| title_full | Enhancing Aquifer Reliability and Resilience Assessment in Data-Scarce Regions Using Satellite Data: Application to the Chao Phraya River Basin |
| title_fullStr | Enhancing Aquifer Reliability and Resilience Assessment in Data-Scarce Regions Using Satellite Data: Application to the Chao Phraya River Basin |
| title_full_unstemmed | Enhancing Aquifer Reliability and Resilience Assessment in Data-Scarce Regions Using Satellite Data: Application to the Chao Phraya River Basin |
| title_short | Enhancing Aquifer Reliability and Resilience Assessment in Data-Scarce Regions Using Satellite Data: Application to the Chao Phraya River Basin |
| title_sort | enhancing aquifer reliability and resilience assessment in data scarce regions using satellite data application to the chao phraya river basin |
| topic | groundwater monitoring aquifer reliability and resilience satellite data analysis gravity recovery and climate experiment groundwater drought index |
| url | https://www.mdpi.com/2072-4292/17/10/1731 |
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