Submitted as: development and technical paper
01 Feb 2023
Submitted as: development and technical paper |  | 01 Feb 2023
Status: this preprint is currently under review for the journal GMD.

Enhancing the representation of water management in global hydrological models

Guta Wakbulcho Abeshu, Fuqiang Tian, Thomas Wild, Mengqi Zhao, Sean Turner, A F M Kamal Chowdhury, Chris R. Vernon, Hongchang Hu, Yuan Zhuang, Mohamad Hejazi, and Hong-Yi Li

Abstract. This study enhances an existing global hydrological model (GHM), Xanthos, by adding a new water management module that distinguishes between the operational characteristics of irrigation, hydropower, and flood control reservoirs. We remapped reservoirs in the GranD database to Xanthos' 0.5-degree spatial resolution so that a single lumped reservoir exists per grid cell, which yielded 3790 large reservoirs. We implemented unique operation rules for each reservoir type based on their primary purposes. In particular, hydropower reservoirs have been treated as flood control reservoirs in previous GHM studies, while here, we determined the operation rules for hydropower reservoirs via optimization that maximizes long-term hydropower production. We conducted global simulations using the enhanced Xanthos and validated monthly streamflow for 91 large river basins where high-quality observed streamflow data were available. A total of 1878 (296 hydropower, 486 irrigation, and 1096 flood control and others) out of the 3790 reservoirs are located in the 91 basins and are part of our reported results. The Kling-Gupta Efficient (KGE) value (after adding the new water management) is ≥ 0.5 and ≥ 0.0 in 39 and 81 basins, respectively. After adding the new water management module, model performance improved for 75 out of 91 basins and worsened for only seven. To measure the relative difference between explicitly representing hydropower reservoirs and representing hydropower reservoirs as flood control reservoirs (as is commonly done in other GHMs), we use normalized-root-mean-square-error (NRMSE) and the coefficient of determination (R2). Out of the 296 hydropower reservoirs, NRMSE is > 0.25 (i.e., considering 0.25 to represent a moderate difference) for over 44 % of the 296 reservoirs when comparing both the simulated reservoir releases and storage time series between the two simulations. We suggest that correctly representing hydropower reservoirs in GHMs could have important implications for our understanding and management of freshwater resource challenges at regional-to-global scales. This enhanced global water management modeling framework will allow for the analysis of future global reservoir development and management from a coupled human-earth system perspective.

Guta Wakbulcho Abeshu et al.

Status: open (until 20 Apr 2023)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Guta Wakbulcho Abeshu et al.

Data sets

Input data for running Xanthos-Wm source code and the modeling outputs Guta Abeshu

Model code and software

Xanthos-Wm source code Guta Abeshu

Guta Wakbulcho Abeshu et al.


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Short summary
Most existing global hydrologic models do not explicitly represent hydropower reservoirs. We are introducing a new water management module to Xanthos that distinguishes between the operational characteristics of irrigation, hydropower, and flood control reservoirs. We show that this explicit representation of hydropower reservoirs can lead to a significantly more realistic simulation of reservoir storage and releases in over 44 % of the hydropower reservoirs included in this study.