Abstract
Abstract. The prediction of water resource evolution is considered to be a major challenge for the coming century, particularly in the context of climate change and increasing demographic pressure. Water resources are directly linked to the continental water cycle, and the main processes modulating changes can be represented by global hydrological models. However, anthropogenic impacts on water resources, and in particular the effects of dams-reservoirs on river flows, are still poorly known and generally neglected in coupled land surface–river routing models. This paper presents a parameterized reservoir model, DROP (Dam-Reservoir OPeration), based on Hanasaki's scheme to compute monthly releases given inflows, water demands and the management purpose. With its significantly anthropized river basins, Spain has been chosen as a study case for which simulated outflows and water storage variations are evaluated against in situ observations over the period 1979–2014. Using a default configuration of the reservoir model, results reveal its positive contribution in representing the seasonal cycle of discharge and storage variation, specifically for large-storage capacity irrigation reservoirs. Based on a bounded version of the Nash–Sutcliffe efficiency (NSE) index, called C2M, the overall outflow representation is improved by 43 % in the median. For irrigation reservoirs, the improvement rate reaches 80 %.
A comprehensive sensitivity analysis of DROP model parameters was conducted based on the performance of C2M on outflows and volumes using the Sobol method. The results show that the most influential parameter is the threshold coefficient describing the demand-controlled release level. The analysis also reveals the parameters that need to be focused on in order to improve river flow or reservoir water storage modeling by highlighting the difference in the individual effects of the parameters and their interactions depending on whether one focuses on outflows or volume mean seasonal patterns.
The results of this generic reservoir scheme show promise for modeling present and future reservoir impacts on the continental hydrology within global land surface–river routing models.
Funder
Centre National de la Recherche Scientifique
Reference88 articles.
1. Abdolghafoorian, A. and Farhadi, L.: Uncertainty quantification in land surface
hydrologic modeling: Toward an integrated variational data assimilation
framework, IEEE J. Sel. Top. Appl. Earth Obs., 9, 2628–2637, https://doi.org/10.1109/JSTARS.2016.2553444, 2016. a
2. AQUASTAT: FAO's Global Information System on Water and Agriculture,
https://www.fao.org/aquastat/ (last access: 16 February 2022), 1994. a
3. Batalla, R. J., Gomez, C. M., and Kondolf, G. M.: Reservoir-induced
hydrological changes in the Ebro River basin (NE Spain), J. Hydrol., 290, 117–136, 2004. a
4. Baumgartner, A. and Reichel, E.: The world water balance: mean annual global,
continental and maritime precipitation and run-off, Elsevier, CRID 1573668924526185088, 1975. a
5. Biancamaria, S., Lettenmaier, D. P., and Pavelsky, T. M.: The SWOT mission and
its capabilities for land hydrology, in: Remote sensing and water resources, Springer International Publishing,
117–147, https://doi.org/10.1007/978-3-319-32449-4_6, 2016. a
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献