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 Jialing River watershed (JRW) located in southwestern China. A number of indices were used to statistically analyze the differences between two open-access precipitation products (OPPs), i.e., Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) and Climate Prediction Center Gauge-Based Analysis of Global Daily Precipitation (CPC), and the rain gauge (Gauge). The three products were then categorized into subbasins to drive SWAT simulations. The results show the following. (1) The three products are highly consistent in temporal variation on a monthly scale yet distinct on a daily scale. CHIRPS is characterized by an overestimation of light rain, underestimation of heavy rain, and high probability of false alarm. CPC generally underestimates rainfall of all magnitudes. (2) Both OPPs satisfactorily reproduce the stream discharges at the JRW outlet with slightly worse performance than the Gauge model. Model with CHIRPS as inputs performed slightly better in both model simulation and fairly better in uncertainty analysis than that of CPC. 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 baseflow. 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 with similar performance in simulating watershed runoff, the three precipitation datasets tend to conceal the identified dissimilarities through hydrological-model parameter calibration, which leads to different directions of hydrologic processes. As such, multiple-objective calibration is recommended for large and spatially resolved watersheds in future work. The main findings of this research suggest that the features of OPPs facilitate the widespread use of CHIRPS in extreme flood events and CPC in extreme drought analyses in future climate.

Evaluation and Hydrological Application of a Data Fusing Method of Multi-Source Precipitation Products-A Case Study over Tuojiang River Basin

“…CCBWA integrates multiple rainfall points screened by MIDSM into FMSPP and establishes the corresponding assumed station point located in the geometric center. Because the monthly-scale precipitation is more consistent and less biased than the daily-scale precipitation [38,39], the monthly scale CC has been chosen to calculate the weighting factors. The weighting factor is mathematically expressed as:…”

“…In the validation period of 1993 to 1999, the simulation performance decreased marginally; NS and R 2 reduced slightly (0.1-0.2), and PBIAS almost doubled. Overall, the performance could be evaluated as "good" according to the SWAT performance rating criteria proposed in the literature [38].…”

Assessment of the GPM IMERG and CHIRPS precipitation estimations for the steppe part of the Crimea

“…Multiple approaches are used to test the Integrated Multi-satellitE Retrievals for GPM (IMERG) and FEWS -the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS), including direct comparisons with ground-based data on measured precipitation (Ning et al 2016;Nashwan et al 2019;Satgé et al 2019); cross-comparisons with other products and ground-based data (Wang et al 2018;Beck et al 2019;Xiao et al 2020); and indirect estimations obtained by assessing the accuracy of runoff models (Pang et al 2020). The generalized analysis of these publications demonstrates that in most cases, several factors (topographic features, wet or arid regions, winter or summer periods, frequency of extreme precipitation events, etc.)…”

Multi-Spatial Resolution Rainfall-Runoff Modelling—A Case Study of Sabari River Basin, India

“…Parameter estimation and runoff simulation of basin interior are possible via employing scaling or regionalization or a combination of both techniques. The transfer of parameters from other similar basins is done through the above techniques, and then a model is executed either in lumped-or semi-distributed mode for runoff estimation [11][12][13][14][15][16][17][18][19]. Aside from regionalization technique, another important question is the appropriate spatial resolution for the modeling context.…”