Hydrological evaluation of open-access precipitation data using SWAT at multiple temporal and spatial scales

Abstract

Abstract. Temporal and spatial precipitation information is key to conducting effective hydrological process simulation and forecasting. Herein, we implemented a comprehensive evaluation of three selected precipitation products in the Jiang River Watershed (JRW) located in southwest China. A number of indices were used to statistically analyze the differences between two open-access precipitation products (OPPs), i.e. Climate Hazards Group Infra-Red Precipitation with Station (CHIRPS) and CPC-Global (CPC), and the rain gauge (Gauge). The three products were then categorized into sub-basins to drive SWAT simulations. The results show: (1) the three products are highly consistent in temporal variation on a monthly scale, yet distinct on a daily scale. CHIRPS is characterized by overestimation of light rain, underestimation of heavy rain, and a high probability of false alarm. CPC generally underestimates rainfall of all magnitudes; (2) All three products satisfactorily reproduce the stream discharges at the JRW outlet with better performance than the Gauge model. On a temporal scale, the OPPs are inferior with respect to capturing flood peak, yet superior at describing other hydrograph features, e.g. rising and falling processes and base flow. On a spatial scale, CHIRPS offers the advantage of deriving smooth, distributed precipitation and runoff due to its high resolution; (3) The water balance components derived from SWAT models with equal simulated streamflow discharges are remarkably different between the three precipitation inputs. The precipitation spatial pattern results in an increasing surface flow trend from upstream to downstream. The results of this study demonstrate that evaluating precipitation products using only streamflow simulation accuracy will conceal the dissimilarities between these products. Hydrological models alter hydrologic mechanisms by adjusting calibrated parameters. Specifically, different precipitation detection methods lead to temporal and spatial variation of water balance components, demonstrating the complexity in describing natural hydrologic processes.