Groundwater trend analysis and modeling is challenging due to partially explicable factors and unexplained human influence. Hurst index, Sequential Mann-Kendall, and Classical Mann-Kendall test offers a comprehensive groundwater trend analysis. A learning-based approach is developed to model groundwater levels using climatological variables of rainfall and temperature. The study is on 24 locations over Periyar river basin of Kerala, India, for the years 1996-2019, and during January, April, August, and November (JAAN) months. The significant trends were observed at 14 locations in at least one of the JAAN months, which is about 58%. Out of these, 8 locations exhibited positive trend signaling a decline in groundwater supplies. The developed model yielded notable improvements in precision with 50%, 79%, 75% and 83% of the locations in month-wise order. To gauge the model performance, observed and predicted location clusters obtained using k-means clustering are juxtaposed for the years 2017-2019, on both individual and average basis. This assessment indicated only one well transitioning in August, with the average approach resulting in a closer match to the original clustering for most of the wells. These findings shall benefit future stakeholders and policymakers in optimizing resource management strategies over the basin and wider.
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