Hyper-resolution hydrological modeling of a managed watershed: The application of CWatM at 30 arc-seconds resolution in the Upper Bhima basin. - Archive ouverte HAL Access content directly
Conference Poster Year : 2019

Hyper-resolution hydrological modeling of a managed watershed: The application of CWatM at 30 arc-seconds resolution in the Upper Bhima basin.

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Abstract

The Community Water Model (CWatM) is an open-source hydrological model designed to assess water availability, anthropogenic and non-anthropogenic water demands, and environmental needs. CWatM is applied at a hyper-resolution (less than 1 kilometer) to extend the application of the model to relatively smaller regions and to better understand the increasing competition of water resources in the context of rapid urbanization. The results are demonstrated for the Upper Bhima basin in India of around 50,000 km2, where the region is already experiencing competition for water resources and increasing demands will continue to stress allocations between urban and agricultural sectors. CWatM has been applied previously from 5-30 arc minute resolutions, and this study presents the developments involved in increasing the resolution to 30 arc-seconds (< 1 km) and a coupling to the MODFLOW groundwater model at 500 m resolution. These developments include better simulating surface water, reservoir, and groundwater interactions, irrigation water management, and crop-water use. With the new features of the model, we can better assess the interaction of changes in land cover, climate, water use, reservoir management, irrigation water management and distribution, and groundwater management.
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Dates and versions

insu-02395495 , version 1 (05-12-2019)

Identifiers

  • HAL Id : insu-02395495 , version 1

Cite

Mikhail Smilovic, Peter Burek, Luca Guillaumot, Yoshihide I Wada, Jun Young Lee, et al.. Hyper-resolution hydrological modeling of a managed watershed: The application of CWatM at 30 arc-seconds resolution in the Upper Bhima basin.. American Geophysical Union Fall Meeting 2019, Dec 2019, San Francisco, United States. , pp.H11O-1729, 2019. ⟨insu-02395495⟩
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