A new way to incorporate storage change term improves the efficacy of the Budyko framework as compared to using effective precipitation

The Budyko framework is a strong contender to be a useful tool for studying the impacts of climate change and human activities on the water balance components. This framework proves to be more effective and suitable for catchments with negligible storage changes, which is assumed to be true when taking long-term means. Since the storage change might not be negligible even at decadal scales, the efficacy of the framework at shorter timescales has been debated. Hence, the framework suffers from temporal scaling issues, which have been a central focus in hydrological research. Previous studies have replaced the precipitation term with effective precipitation (Precipitation – Storage change) to tackle this problem at a finer temporal scale. Here, we assess the efficacy of using effective precipitation for various climate change and human intervention scenarios. A closed-loop environment was developed using synthetic data as a business-as-usual scenario and various change scenarios were introduced by adding realistic linear trends in meteorological and hydrological datasets. We found that the effective precipitation strategy works for natural storage variations but fails when human-induced storage changes such as groundwater abstraction is considered.  Therefore, we propose an improved Budyko framework that has storage change index as the third axis added to the traditional Budyko framework. We demonstrate that this novel framework acts as a robust way of partitioning precipitation at finer temporal scales with accuracy better than the existing approaches.