Abstract
The unplanned exploitation of groundwater has depleted the groundwater table in many parts of the world. As such, groundwater fluctuation study is an essential study for the proper management of water in a region. The fluctuation can be determined from the in situ measurement of groundwater level. However, the temporal and spatial resolution of the data is generally very coarse, specifically in developing countries. As such, in this study, a Generalized Regression Neural Network (GRNN) based model is developed for estimating the groundwater fluctuation of a region. The Gravity Recovery and Climate Experiment (GRACE) satellite data along with the hydro-meteorological data of the region are used in developing the model and the model is calibrated and validated using the observed groundwater level data. The field applicability of the model is demonstrated by applying the model in the state of Uttarakhand of India.
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