Baron, Helen Elizabeth
ORCID: https://orcid.org/0000-0003-0070-8247; Keller, Virginie D.J.
ORCID: https://orcid.org/0000-0003-4489-5363; Horan, R.
ORCID: https://orcid.org/0000-0002-8304-0272; MacAllister, Donald John
ORCID: https://orcid.org/0000-0001-8893-9634; Simpson, Mike
ORCID: https://orcid.org/0000-0002-3633-2723; Jackson, Chris; Houghton-Carr, Helen; Rickards, Nathan
ORCID: https://orcid.org/0000-0002-7303-6739; 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.
10.1080/02626667.2023.2208755
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.
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