Using the Budyko Framework for Calibrating a Global Hydrological Model

P. Greve, P. Burek, Y. Wada

Research output: Contribution to journalArticlepeer-review

28 Scopus citations


Global hydrological models (GHMs) have become an established tool to simulate water resources worldwide. Most of the GHMs are however uncalibrated and typically use a set of basic hydrological parameters, that could potentially lead to unrealistic projections of the terrestrial water cycle. The calibration of hydrological models is usually performed by using and comparing modeled to observed discharge. Accurate station data and reliable time series data of discharge are, however, often not available for many parts of the world and classic calibration approaches are therefore not feasible. In this paper, we aim to develop a new calibration approach that requires no additional data, is easy to implement, and substantially improves model performance, especially in regions where uncalibrated model performance is rather poor. This is achieved by using the Budyko framework, which provides a conceptual representation of the long-term water and energy balance. We use a state-of-the-art GHM and calibrate the model within nine river catchments of different sizes and characteristics. Since observed river discharge is available for these catchments, we are able to compare the Budyko-based calibration approach to a classic discharge-based calibration scheme and the uncalibrated model version. In all catchments, the Budyko-based calibration approach decreases biases and increases model performance compared to the uncalibrated model version although performance improvements obtained through a classic calibration approach are greater. Nonetheless, a Budyko-based calibration is a valuable, intermediate approach between use of a basic set of a priori hydrological parameters and classical calibration against discharge data.
Original languageEnglish (US)
JournalWater Resources Research
Issue number6
StatePublished - Jun 1 2020
Externally publishedYes

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Generated from Scopus record by KAUST IRTS on 2023-09-18


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