Mass balance calibration and reservoir representations for large-scale hydrological impact studies using SWAT

Climate change (CC) has a high impact on hydrological processes which calls for reliable projections of CC hydrological impacts at large scales. However, there are several challenges in hydrological modelling at large scales. Large-scale models are often not adapted and evaluated at regional scale due to high computation time requirements or lack of information on human interactions, such as dam operations and irrigation practices at local scale. In this study, we present a regionalised methodology that uses a hydrological mass balance calibration (HMBC) and global datasets to represent reservoir and irrigation practices and apply these to a SWAT+ model for Southern Africa. We evaluate the influence of HMBC and the representation on irrigation and reservoirs on model performance and climate projections. We propose a generalised implementation of reservoirs using global datasets and decision tables to represent irrigation and reservoir management. Results show that inclusion of irrigation, reservoirs and HMBC leads to improved simulation of discharge and evapotranspiration with fewer iterations than a full parameter calibration. There is a substantial difference between projections made by the regionalised model and default model when looking at local impacts. We conclude that large-scale hydrological studies that involve local analysis and spatial mapping of results benefit from HMBC and representation of management practices. The proposed methodology can be scaled up and improve overall projections made by global models.