Articles | Volume 27, issue 19
https://doi.org/10.5194/hess-27-3485-2023
https://doi.org/10.5194/hess-27-3485-2023
Research article
 | 
06 Oct 2023
Research article |  | 06 Oct 2023

Calibrating macroscale hydrological models in poorly gauged and heavily regulated basins

Dung Trung Vu, Thanh Duc Dang, Francesca Pianosi, and Stefano Galelli

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Cited articles

Biancamaria, S., Lettenmaier, D. P., and Pavelsky, T. M.: The SWOT mission and its capabilities for land hydrology, Springer International Publishing, 117–147, https://doi.org/10.1007/978-3-319-32449-4_6, 2016. a
Bierkens, M. F. P.: Global hydrology 2015: State, trends, and directions, Water Resour. Res., 51, 4923–4947, https://doi.org/10.1002/2015wr017173, 2015. a, b
Birkinshaw, S. J., O'Donnell, G. M., Moore, P., Kilsby, C. G., Fowler, H. J., and Berry, P. A. M.: Using satellite altimetry data to augment flow estimation techniques on the Mekong River, Hydrol. Process., 24, 3811–3825, https://doi.org/10.1002/hyp.7811, 2010. a
Biswas, N. K., Hossain, F., Bonnema, M., Lee, H., and Chishtie, F.: Towards a global Reservoir Assessment Tool for predicting hydrologic impacts and operating patterns of existing and planned reservoirs, Environ. Model. Softw., 140, 105043, https://doi.org/10.1016/j.envsoft.2021.105043, 2021. a
Bonnema, M. and Hossain, F.: Inferring reservoir operating patterns across the Mekong Basin using only space observations, Water Resour. Res., 53, 3791–3810, https://doi.org/10.1002/2016wr019978, 2017. a, b
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Short summary
The calibration of hydrological models over extensive spatial domains is often challenged by the lack of data on river discharge and the operations of hydraulic infrastructures. Here, we use satellite data to address the lack of data that could unintentionally bias the calibration process. Our study is underpinned by a computational framework that quantifies this bias and provides a safe approach to the calibration of models in poorly gauged and heavily regulated basins.
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