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Recognition of district-wise groundwater stress zones using the GLDAS-2 catchment land surface model during lean season in the Indian state of West Bengal


Sahoo,  Satiprasad
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Chakraborty,  Subha
External Organizations;

Pham,  Quoc Bao
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Sharifi,  Ehsan
4.4 Hydrology, 4.0 Geosystems, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

Sammen,  Saad Sh.
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Vojtek,  Matej
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Vojteková,  Jana
External Organizations;

Elkhrachy,  Ismail
External Organizations;

Costache,  Romulus
External Organizations;

Linh,  Nguyen Thi Thuy
External Organizations;

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Sahoo, S., Chakraborty, S., Pham, Q. B., Sharifi, E., Sammen, S. S., Vojtek, M., Vojteková, J., Elkhrachy, I., Costache, R., Linh, N. T. T. (2021): Recognition of district-wise groundwater stress zones using the GLDAS-2 catchment land surface model during lean season in the Indian state of West Bengal. - Acta Geophysica, 69, 175-198.

Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5005117
Water is essential for irrigation, drinking and industrial purposes from global to the regional scale. The groundwater considered a significant water resource specifically in regions where the surface water is not sufficient. Therefore, the research problem is focused on district-wise sustainable groundwater management due to urbanization. The number of impervious surface areas like roofing on built-up areas, concrete and asphalt road surface were increased due to the level of urban development. Thus, these surface areas can inhibit infiltration and surface retention by the impact of urbanization because vegetation/forest areas are decreased. The present research examines the district-wise spatiotemporal groundwater storage (GWS) changes under terrestrial water storage using the global land data assimilation system-2 (GLDAS-2) catchment land surface model (CLSM) from 2000 to 2014 in West Bengal, India. The objective of the research is mainly focused on the delineation of groundwater stress zones (GWSZs) based on ten biophysical and hydrological factors according to the deficiency of groundwater storage using the analytic hierarchy process by the GIS platform. Additionally, the spatiotemporal soil moisture (surface soil moisture, root zone soil moisture, and profile soil moisture) changes for the identification of water stress areas using CLSM were studied. Finally, generated results were validated by the observed groundwater level and groundwater recharge data. The sensitivity analysis has been performed for GWSZs mapping due to the deficit of groundwater storage. Three correlation coefficient methods (Kendall, Pearson and Spearman) are applied for the interrelationship between the most significant parameters for the generation of GWSZ from sensitivity analysis. The results show that the northeastern (max: 1097.35 mm) and the southern (max: 993.22 mm) parts have high groundwater storage due to higher amount of soil moisture and forest cover compared to other parts of the state. The results also show that the maximum and minimum total annual groundwater recharge shown in Paschim Medinipore [(361,148.51 hectare-meter (ham)] and Howrah (31,510.46 ham) from 2012 to 2013. The generated outcome can create the best sustainable groundwater management practices based upon the human attitude toward risk.