Evaluating Water Resources Availability in Headwater Sub-catchments of Subarnarekha River Basin in a changing Environment using Remote Sensing and GIS Software

IJEP 42(9): 1034-1041 : Vol. 42 Issue. 9 (September 2022)

Mrigendra Kumar1 and Ramakar Jha2*

1. Chaibasa Engineering College, Chaibasa – 833 215, Jharkhand, India
2. National Institute of Technology, Patna – 800 005, Bihar, India


The Subarnarekha river basin, which is predominantly rural, is a river shared between Jharkhand, West Bengal and Odisha. The Jharkhand communities along the river largely depend on the availability of stream flow for their livelihoods which are now being threatened by the effects of a changing environment. The study assessed the effects of climate change on water resource availability in 7 selected headwater sub-catchments of the Subarnarekha river basin using the Pitman hydrological model. The model was driven by 10 statistically downscaled climate models forced with representative concentration pathway (RCP 3.5 and RCP 7.5) for the near 2021–2050 and far 2050–2080 futures. The results of water resource availability varied, depending on whether the short- or long-term scenarios were modelled. 60% of the sub-catchments predicted an increase in stream flow for the near and far-future under the RCP 3.5 emission scenario. Under the RCP 7.5 scenario, a decrease in stream flow was simulated for all sub-catchments with the decrease ranging from -4.07% to -61.59%. The reduction in water resources would be more significant in the drier parts of the basin than in the wetter parts, which are projected to maintain approximately 80% of current stream flow levels. The present study evaluates the geomorphic process of upper watershed of river Subarnarekha in the state of Jharkhand, India. Various spatial information is extracted with the help of remote sensing and GIS techniques, which provided an understanding of precise scenarios related to basin development.


Environment change, Delta change, Pitman model, Subarnarekha river basin, Rural livelihoods, Remote sensing, GIS


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