Articles | Volume 29, issue 2
https://doi.org/10.5194/hess-29-567-2025
https://doi.org/10.5194/hess-29-567-2025
Research article
 | 
30 Jan 2025
Research article |  | 30 Jan 2025

The benefits and trade-offs of multi-variable calibration of the WaterGAP global hydrological model (WGHM) in the Ganges and Brahmaputra basins

Howlader Mohammad Mehedi Hasan, Petra Döll, Seyed-Mohammad Hosseini-Moghari, Fabrice Papa, and Andreas Güntner

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Ai, Z. and Hanasaki, N.: Simulation of crop yield using the global hydrological model H08 (crp.v1), Geosci. Model Dev., 16, 3275–3290, https://doi.org/10.5194/gmd-16-3275-2023, 2023. 
Akhil, V. P., Durand, F., Lengaigne, M., Vialard, J., Keerthi, M. G., Gopalakrishna, V. V., Deltel, C., Papa, F., and de Boyer Montégut, C.: A modeling study of the processes of surface salinity seasonal cycle in the Bay of Bengal, J. Geophys. Res.-Oceans, 119, 3926–3947, https://doi.org/10.1002/2013JC009632, 2014. 
Arendt, P. D., Apley, D. W., Chen, W., Lamb, D., and Gorsich, D.: Improving Identifiability in Model Calibration Using Multiple Responses, J. Mech. Design, 134, 100909, https://doi.org/10.1115/1.4007573, 2012a. 
Arendt, P. D., Apley, D. W., and Chen, W.: Quantification of Model Uncertainty: Calibration, Model Discrepancy, and Identifiability, J. Mech. Design, 134, 100908, https://doi.org/10.1115/1.4007390, 2012b. 
Arheimer, B., Pimentel, R., Isberg, K., Crochemore, L., Andersson, J. C. M., Hasan, A., and Pineda, L.: Global catchment modelling using World-Wide HYPE (WWH), open data, and stepwise parameter estimation, Hydrol. Earth Syst. Sci., 24, 535–559, https://doi.org/10.5194/hess-24-535-2020, 2020. 
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Short summary
We calibrate a global hydrological model using multiple observations to analyse the benefits and trade-offs of multi-variable calibration. We found such an approach to be very important for understanding the real-world system. However, some observations are very essential to the system, in particular, streamflow. We also showed uncertainties in the calibration results, which are often useful for making informed decisions. We emphasize considering observation uncertainty in model calibration.