Abstract
Due to climate change and human disturbances, rainfall spatial and temporal variabilities at the watershed have become increasingly prominent, significantly impacting the patterns of runoff generation and pollutant transportation. Originally, rainfall variabilities in space and time were frequently neglected or idealized in the traditional applications of hydrology and water quality models. This research attempted to investigate the responses of runoff quality and quantity simulation to rainfall spatial and temporal variabilities. We used Rainfall Hazard Modeling System (RainyDay model) combined with TRMM (Tropical Rainfall Measuring Mission) rainfall products to generate rainfall events for 500 return periods. Such events were resampled into eight rainfall scenarios with multiple levels of spatial and temporal variabilities. They were used to drive the Soil and Water Assessment Tool (SWAT) to simulate runoff quality (TP as the index) and quantity under multiple watershed scales and return periods at the Dongjiang River watershed. Analysis of Variance was employed to analyze the relative contributions of rainfall spatial and temporal variabilities to the total variabilities of runoff quality and quantity. The results highlighted that rainfall spatial and temporal variabilities would have notable impacts on runoff quality and quantity under multiple watershed scales and event magnitudes. For headwater at small watershed scales, rainfall spatial variability would have a relatively significant impact on runoff quality and quantity. For relatively larger watershed scales, rainfall temporal variability showed an increasingly important impact than spatial variability for smaller return periods, whereas the opposite results can be obtained for relatively larger return periods. The results can be caused by the following reasons:1) rainfall was concentrated in the middle and lower reaches of the watershed; 2) it was based on the daily scale. Our research suggested that attention should be paid to spatial and temporal variabilities of rainfall inputs in hydrological and water quality models.
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