Calibration and validation strategies of SWAT+ for streamflow simulation: a systematic review

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Effective hydrological modeling with the Soil and Water Assessment Tool Plus (SWAT+) requires rigorous calibration and validation. However, achieving high model performance largely depends on the selection and application of appropriate strategies from the many available options. This systematic review evaluates and identifies the most effective data sources, calibration tools and software, and methodological approaches used in SWAT+ modeling studies. In total, 80 SWAT+ research articles published between 2017 and 2025 were collected from Scopus, Web of Science (WOS), and the SWAT+ literature database. Studies were selected following PRISMA guidelines. In data-scarce regions, satellite-derived and reanalysis products, such as Climate Hazards Group Infrared Precipitation with Station data (CHIRPS), Climate Forecast System Reanalysis (CFSR), and ERA5, provide practical alternatives to sparse ground-station networks with appropriate bias correction. In addition, the SWAT+ Toolbox with Dynamically Dimensioned Search (DDS) algorithm was the most widely used calibration software due to its accessibility and integrated optimization algorithms. The review further demonstrates that hybrid calibration approaches integrating automatic optimization with subsequent manual refinement consistently improve parameterization. Moreover, multi-site and multi-variable calibration using actual evapotranspiration (ETa) or soil moisture reduces parameter equifinality in heterogeneous watersheds. However, this review reveals that despite their demonstrated advantages, these advanced strategies remain underutilized. While Nash-Sutcliffe Efficiency (NSE) remains the dominant objective function, the Kling-Gupta Efficiency (KGE) is increasingly preferred for its superior handling of simulation biases. Statistical benchmarks reveal median NSE values of 0.65 for daily and 0.68 for monthly simulations across the literature. This review provides a methodological framework for researchers to prioritize advanced calibration strategies, ensuring robust and reproducible hydrological simulations for sustainable water resource management. Systematic review registration: https://osf.io/mdkbq .