Reliability of Hydrology and Water Quality Simulations Using Global Scale Datasets

Physics-based, comprehensive, distributed hydrologic models, such as the Soil and Water Assessment Tool, are a prime choice of decision makers and watershed managers for analyzing the impact of different land management practices on watershed hydrology and water quality. However, the decisions framed through the application of such models are highly affected by the model input data accuracy. On a global scale, the majority of watersheds are data-limited (DL), and model input data at required spatial and temporal resolutions are unavailable, incomplete, or low in quality. Thus, the hydrological simulations are significantly influenced by poor representation and characterization of the system, which affects the reliability of simulations in DL regions. This study quantifies the effects of global-scale dataset usage in ecohydrological simulations. The global-scale datasets are generally coarse in spatial resolution and significantly affect the hydrology and water quality simulations. The average annual flow simulations were 35.7% higher for DL scenarios as compared to the data-intensive scenario. Researchers with limited data should take special care to ensure that their simulations allow them to take informed decisions so that effective and reliable management system is planned. Validation with locally available data for land use and management practices may help increase reliability.