Improving the representation of groundwater processes in a large-scale water resources model
Improving the representation of groundwater processes in a large-scale water resources model
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DOI：
10.1080/02626667.2023.2208755
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发表时间：
2023-05
影响因子：
3.5
通讯作者：
H. Baron;V. Keller;R. Horan;D. J. MacAllister;Mike Simpson;C. Jackson;H. Houghton-Carr;N. Rickards;K. Garg;M. Sekhar;A. MacDonald;G. Rees
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文献类型：
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作者：
H. Baron;V. Keller;R. Horan;D. J. MacAllister;Mike Simpson;C. Jackson;H. Houghton-Carr;N. Rickards;K. Garg;M. Sekhar;A. MacDonald;G. Rees
摘要：本研究探讨了纳入更复杂的地下水表征和人-地下水相互作用是否能提高大规模水资源模型的预测能力。全球水资源可用性评估模型（GWAVA）包括一个简单的层状含水层和相关通量（GWAVA- gw），并应用于印度的高韦里河流域，这是一个高度依赖地下水的受人类影响的大流域。GWAVA- gw对Mettur大坝上游的流量具有较好的预测能力：91%的子集水区克林-古普塔效率≥0.3，与GWAVA相比，在大部分流域的流量预测模型技能有所提高。GWAVA-GW在季节性和长期时间尺度上对地下水水位显示出一定程度的预测能力，在地下水抽取水平高的地区，有高估地下水深度的倾向。总的来说，GWAVA-GW是评估流域水资源的有用工具，特别是在依赖地下水的地区。
ABSTRACT 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 sub-catchments, 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.