Estimating natural groundwater recharge from rainfall and AEM data in crystalline aquifer
Accurate knowledge of natural recharge is an essential input to devise an effective management plan for groundwater resources. The paper presents an approach of utilizing airborne electromagnetic (AEM) resistivity data coupled with precipitation using lithology constrained rainfall (LCR) recharge re...
| Autores principales: | , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Wiley
2025
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| Acceso en línea: | https://hdl.handle.net/10568/175609 |
| Sumario: | Accurate knowledge of natural recharge is an essential input to devise an effective management plan for groundwater resources. The paper presents an approach of utilizing airborne electromagnetic (AEM) resistivity data coupled with precipitation using lithology constrained rainfall (LCR) recharge relationships to estimate natural recharge in a heterogeneous crystalline hard rock aquifer. AEM method, having the ability of rapid and dense data sampling, helps in improving the spatial estimation of groundwater recharge at a regional scale. A demonstrative study has been carried out in a granite hard rock terrain of southern India. The LCR recharge estimates are validated by the recharge estimates from the well-defined water table fluctuation (WTF) method. The estimated water level using LCR recharge is found in good agreement with the measured water level in the field, which indicates the robustness of the methodology. The paper also presents the role of data density on its spatial relationship through variogram analysis. |
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