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The present study attempted to understand the dimensions of changing agrarian livelihoods because of haphazard adaptation of capitalistic shrimp aquaculture. Specifically, using multi-temporal Google-based geodatabase, we quantified the artificial conversion of agrarian landscape in an inland freshwater region of coastal Bengal. Further, we examined the long-term viability of transformed livelihoods by adopting a modified version of the Sustainable Livelihood Approach (SLA). The assessment of changing livelihoods was based on empirical information acquired through field surveys, focus group discussion (FGD) and key informant interviews (KII). Results from the geostatistical analysis depicted that the shrimp culture in the research area was very recent. In 2010, only 0.03 percent of the total area was occupied by shrimp ponds. However, within a decade and an expansion rate of 18 percent/annum, the conversion spread to 1/3 of the total study area. The findings also clarified that the adaptation of shrimp cultivation increased the overall profit by 6400 USD/ha/year over agricultural output, and resulted in a quick rise in the standard of living for the shrimp farmers. However, in the long run, due to decreasing productivity and salinization of the surrounding land, the conversion resulted in massive depeasantization, augmentation of wasteland, and biased wealth accumulation led to a wide rich-poor gap. Therefore, the entire ecosystem will suffer in the near future, if the local government does not strictly impose Standard Operating Procedures (SOPs).

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The present study aims to examine the spatio-temporal and seasonal uctuation of groundwater levels in an eastern Indian semi-arid region. Also, it attempted to investigate the involvement of different signi cant groundwater usage factors in causing such variations and trends. Furthermore, by evaluating temporal patterns and the in uence of the crucial drivers, generate meaningful predictions for raising community awareness about the future. A combination of statistical, spatial analysis, and machine learning techniques were used to ful ll the objectives. Overall, the ndings revealed that the south-eastern corner (consisting of Bundwan and Barabazar Blocks), the far western region (especially Jhalda I and II Blocks), and some of the eastern Blocks are most vulnerable to groundwater scarcity. The monitoring stations in this region are typically suffering a signi cant declining trend in groundwater level, with a substantial amount of Sen's Slope. In contrast, the centrally positioned Blocks have lesser susceptibility.The MLR analysis and spatial thematic maps demonstrate a strong association between this spatial pattern of declining groundwater table and the groundwater drivers in consideration. Thus, it is acceptable to suggest that drivers from the human world must be included in the groundwater management planning of the Purulia district. Finally, the predictions from the time series con rm that if no interventions are implemented, the average groundwater level will decline by 2.5 meters by 2030. Therefore, Purulia urgently requires a realistic plan to prevent future generations from becoming refugees in their own land.

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The present study aims to examine the spatio-temporal and seasonal fluctuation of groundwater levels in an eastern Indian semi-arid region. Also, it attempted to investigate the involvement of different significant groundwater usage factors in causing such variations and trends. Furthermore, by evaluating temporal patterns and the influence of the crucial drivers, generate meaningful predictions for raising community awareness about the future. A combination of statistical, spatial analysis, and machine learning techniques were used to fulfill the objectives. Overall, the findings revealed that the south-eastern corner (consisting of Bundwan and Barabazar Blocks), the far western region (especially Jhalda I and II Blocks), and some of the eastern Blocks are most vulnerable to groundwater scarcity. The monitoring stations in this region are typically suffering a significant declining trend in groundwater level, with a substantial amount of Sen's Slope. In contrast, the centrally positioned Blocks have lesser susceptibility. The MLR analysis and spatial thematic maps demonstrate a strong association between this spatial pattern of declining groundwater table and the groundwater drivers in consideration. Thus, it is acceptable to suggest that drivers from the human world must be included in the groundwater management planning of the Purulia district. Finally, the predictions from the time series confirm that if no interventions are implemented, the average groundwater level will decline by 2.5 meters by 2030. Therefore, Purulia urgently requires a realistic plan to prevent future generations from becoming refugees in their own land.

In the original publication of the article, the order of Figs. 7, 8, 9, 10, 11 and 12 was published incorrectly. The Figs. 7, 8, 9, 10, 11 and 12 are arranged correctly in this correction.The original article has been corrected.