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The Budyko framework was firstly developed to estimate actual evaporation as a function of precipitation and the aridity index at steady state conditions. Based on this framework, the water storage change in the watershed is assumed to be negligible at large spatial and temporal scales. However, steady state conditions are not valid for many watersheds worldwide or at finer temporal or spatial scales. Accordingly, the application of the Budyko framework has become challenging for these situations. Therefore, many researchers have tried to extend the Budyko framework for non-steady state conditions. The aim of this study is to provide a review of the extended equations and to discuss using the Budyko framework in a changing world. While the extended equations are more complex than the original ones, they still require little data. Thus, the Budyko framework, either the original or the extended can be a very useful tool for hydrological modeling with lots of applications, especially in data scarce regions., Accepted Author Manuscript, Water Resources

The Budyko framework was firstly developed to estimate actual evaporation as a function of precipitation and the aridity index at steady state conditions. Based on this framework, the water storage change in the watershed is assumed to be negligible at large spatial and temporal scales. However, steady state conditions are not valid for many watersheds worldwide or at finer temporal or spatial scales. Accordingly, the application of the Budyko framework has become challenging for these situations. Therefore, many researchers have tried to extend the Budyko framework for non-steady state conditions. The aim of this study is to provide a review of the extended equations and to discuss using the Budyko framework in a changing world. While the extended equations are more complex than the original ones, they still require little data. Thus, the Budyko framework, either the original or the extended can be a very useful tool for hydrological modeling with lots of applications, especially in data scarce regions., Accepted Author Manuscript, Water Resources