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Coupling a large-scale hydrological model (CWatM v1.1) with a high-resolution groundwater flow model (MODFLOW 6) to assess the impact of irrigation at regional scale

  • Luca Guillaumot*
  • , Mikhail Smilovic
  • , Peter Burek
  • , Jens De Bruijn
  • , Peter Greve
  • , Taher Kahil
  • , Yoshihide Wada
  • *Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

In the context of changing climate and increasing water demand, large-scale hydrological models are helpful for understanding and projecting future water resources across scales. Groundwater is a critical freshwater resource and strongly controls river flow throughout the year. It is also essential for ecosystems and contributes to evapotranspiration, resulting in climate feedback. However, groundwater systems worldwide are quite diverse, including thick multilayer aquifers and thin heterogeneous aquifers. Recently, efforts have been made to improve the representation of groundwater systems in large-scale hydrological models. The evaluation of the accuracy of these model outputs is challenging because (1) they are applied at much coarser resolutions than hillslope scale, (2) they simplify geological structures generally known at local scale, and (3) they do not adequately include local water management practices (mainly groundwater pumping). Here, we apply a large-scale hydrological model (CWatM), coupled with the groundwater flow model MODFLOW, in two different climatic, geological, and socioeconomic regions: The Seewinkel area (Austria) and the Bhima basin (India). The coupled model enables simulation of the impact of the water table on groundwater-soil and groundwater-river exchanges, groundwater recharge through leaking canals, and groundwater pumping. This regional-scale analysis enables assessment of the model's ability to simulate water tables at fine spatial resolutions (1 km for CWatM, 100-250 m for MODFLOW) and when groundwater pumping is well estimated. Evaluating large-scale models remains challenging, but the results show that the reproduction of (1) average water table fluctuations and (2) water table depths without bias can be a benchmark objective of such models. We found that grid resolution is the main factor that affects water table depth bias because it smooths river incision, while pumping affects time fluctuations. Finally, we use the model to assess the impact of groundwater-based irrigation pumping on evapotranspiration, groundwater recharge, and water table observations from boreholes.

Original languageEnglish
Pages (from-to)7099-7120
Number of pages22
JournalGeoscientific Model Development
Volume15
Issue number18
Early online date20 Sept 2022
DOIs
Publication statusPublished - 2022

Bibliographical note

Funding Information:
This study was partially supported by the WaterstressAT project (grant no. KR19AC0K17504), funded by the Austrian Climate and Energy Fund as part of the Austrian Climate Research Programme 12th call (2019). This work was also conducted as part of the Belmont Forum Sustainable Urbanisation Global Initiative (SUGI) Food–Water–Energy Nexus theme for which coordination was supported by the US National Science Foundation under grant ICER/EAR-1829999 to Stanford University. The Austrian partners ÖFSE and IIASA are funded by the Austrian Research Promotion Agency (FFG). UFZ receives funding from the Federal Ministry of Education and Research (BMBF).

Publisher Copyright:
© 2022 Luca Guillaumot et al.

Funding

This study was partially supported by the WaterstressAT project (grant no. KR19AC0K17504), funded by the Austrian Climate and Energy Fund as part of the Austrian Climate Research Programme 12th call (2019). This work was also conducted as part of the Belmont Forum Sustainable Urbanisation Global Initiative (SUGI) Food–Water–Energy Nexus theme for which coordination was supported by the US National Science Foundation under grant ICER/EAR-1829999 to Stanford University. The Austrian partners ÖFSE and IIASA are funded by the Austrian Research Promotion Agency (FFG). UFZ receives funding from the Federal Ministry of Education and Research (BMBF).

FundersFunder number
Stanford University
Österreichische Forschungsförderungsgesellschaft
Bundesministerium für Bildung und Forschung
Klima- und Energiefonds
Bundesministerium für Bildung und Frauen
International Institute for Applied Systems Analysis
National Science FoundationICER/EAR-1829999, 1829999

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 6 - Clean Water and Sanitation
      SDG 6 Clean Water and Sanitation

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