Evaluation of Five Satellite-Based Precipitation Products in Two Gauge-Scarce Basins on the Tibetan Plateau

Abstract

Abstract:The sparse rain gauge networks over the Tibetan Plateau (TP) cause challenges for hydrological studies and applications. Satellite-based precipitation datasets have the potential to overcome the issues of data scarcity caused by sparse rain gauges. However, large uncertainties usually exist in these precipitation datasets, particularly in complex orographic areas, such as the TP. The accuracy of these precipitation products needs to be evaluated before being practically applied. In this study, five (quasi-)global satellite precipitation products were evaluated in two gauge-sparse river basins on the TP during the period 1998-2012; the evaluated products are CHIRPS, CMORPH, PERSIANN-CDR, TMPA 3B42, and MSWEP. The five precipitation products were first intercompared with each other to identify their consistency in depicting the spatial-temporal distribution of precipitation. Then, the accuracy of these products was validated against precipitation observations from 21 rain gauges using a point-to-pixel method. We also investigated the streamflow simulation capacity of these products via a distributed hydrological model. The results indicated that these precipitation products have similar spatial patterns but significantly different precipitation estimates. A point-to-pixel validation indicated that all products cannot efficiently reproduce the daily precipitation observations, with the median Kling-Gupta efficiency (KGE) in the range of 0.10-0.26. Among the five products, MSWEP has the best consistency with the gauge observations (with a median KGE = 0.26), which is thus recommended as the preferred choice for applications among the five satellite precipitation products. However, as model forcing data, all the precipitation products showed a comparable capacity of streamflow simulations and were all able to accurately reproduce the observed streamflow records. The values of the KGE obtained from these precipitation products exceed 0.83 in the upper Yangtze River (UYA) basin and 0.84 in the upper Yellow River (UYE) basin. Thus, evaluation of precipitation products only focusing on the accuracy of streamflow simulations is less meaningful, which will mask the differences between these products. A further attribution analysis indicated that the influences of the different precipitation inputs on the streamflow simulations were largely offset by the parameter calibration, leading to significantly different evaporation and water storage estimates. Therefore, an efficient hydrological evaluation for precipitation products should focus on both streamflow simulations and the simulations of other hydrological variables, such as evaporation and soil moisture.

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

“…Apparently, the CPC model reduced its corresponding ET by using a higher ESCO parameter, so that the lack of precipitation inputs would be offset by less evaporation. This result is consistent with that reported by Bai & Liu (2018), who conducted a study at the source regions of the Yellow River and Yangtze River basins in the Tibetan Plateau. They further concluded that the impact of different precipitation inputs on runoff simulation is largely offset by parameter calibration, resulting in significant differences in evaporation and storage estimates.…”

“…Thus, this fundamental issue must be addressed before hydrologic modeling with open-access precipitation datasets can be utilized at maximum capacity; as without a thorough understanding of the water cycle's inner processes, the hydrologic models may be highly misleading and facilitate inappropriate management decisions. Bai & Liu (2018) used an HIMS model to simulate the runoff driven by CHIRPS, CMORPH, PERSIANN-CDR, TMPA 3B42, and MSWEP at the source regions of the Yellow River and Yangtze River basins in the Tibetan Plateau. They reported that parameter calibration significantly counterbalanced the impact of diverse precipitation inputs on runoff modeling, resulting in substantial differences in evaporation and storage estimates.…”

Evaluation of GPM-era Global Satellite Precipitation Products over Multiple Complex Terrain Regions

“…Bai and Liu [48] evaluated CMORPH, TMPA, MSWEP, and a few other SPPs over the complex terrain of the Tibetan Plateau and concluded that MSWEP generally provides the best validation results. The authors noted, however, that since MSWEP directly incorporates global-scale daily gauge data, evaluation of this product using the rain gauges could raise independence issues.…”

Performance of Two Long-Term Satellite-Based and GPCC 8.0 Precipitation Products for Drought Monitoring over the Yellow River Basin in China

“…The PERSIANN-CDR product was developed by the organization, which is Center for Hydrometeorology and Remote Sensing of the University of California (USA), using an artificial neural network model in combination with an algorithm for the classification of meteorological elements [34]. It constitutes a daily precipitation data with 0.25 • spatial resolution for the region 60 • S-60 • N over the quasi-global range from 1983 to the present [35]. It can be used for long-term (>30 years) precipitation assessment and drought monitoring and investigation of other extreme events attributable to climate change.…”