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Improving the representation of groundwater processes in a large-scale water resources model

Baron, Helen Elizabeth; Keller, Virginie D.J.; Horan, R.; MacAllister, Donald John ORCID: https://orcid.org/0000-0001-8893-9634; Simpson, Mike; Jackson, Chris; Houghton-Carr, Helen; Rickards, Nathan; Garg, Kaushal K.; Sekhar, Muddu; MacDonald, Alan ORCID: https://orcid.org/0000-0001-6636-1499; Rees, Gwyn ORCID: https://orcid.org/0000-0003-3300-0472. 2023 Improving the representation of groundwater processes in a large-scale water resources model. Hydrological Sciences Journal, 68 (9). 1264-1285. https://doi.org/10.1080/02626667.2023.2208755

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Abstract/Summary

This study explores whether incorporating a more sophisticated representation of groundwater, and human-groundwater interactions, improves predictive capability in a large-scale water resource model. The Global Water Availability Assessment model (GWAVA) is developed to include a simple layered aquifer and associated fluxes (GWAVA-GW), and applied to the Cauvery river basin in India, a large, human-impacted basin with a high dependence on groundwater. GWAVA-GW shows good predictive skill for streamflow upstream of the Mettur dam: Kling-Gupta Efficiency ≥ 0.3 for 91% of subcatchments, and improved model skill for streamflow prediction compared to GWAVA over the majority of the basin. GWAVA-GW shows some level of predictive skill for groundwater levels over seasonal and long-term time scales, with a tendency to overestimate depth to groundwater in areas with high levels of groundwater pumping. Overall, GWAVA-GW is a useful tool when assessing water resources at a basin scale, especially in areas that rely on groundwater.

Item Type: Publication - Article
Digital Object Identifier (DOI): https://doi.org/10.1080/02626667.2023.2208755
UKCEH and CEH Sections/Science Areas: Water Resources (Science Area 2017-)
ISSN: 0262-6667
Additional Keywords: GroundwaterBGS, IGRD, ODA, integrated water resource model, groundwater, India, Cauvery river
NORA Subject Terms: Hydrology
Date made live: 11 May 2023 13:29 +0 (UTC)
URI: https://nora.nerc.ac.uk/id/eprint/534516

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