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

Peng Bai,Xiaomang Liu

doi:10.3390/rs10081316

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.

Highlights

Precipitation is one of the most important water balance components of the global water cycle and its spatial–temporal variability directly affects the available water resources in a region [1,2].Accurate estimates of precipitation are crucial for scientific research and for water resources management, drought and flood forecasting, and debris-flow and landslide hazard forecasting [3,4,5,6,7,8]
Et al [39] performed a global-scale evaluation of 22 precipitation products using gauge observations and streamflow simulations; the results indicated that the MSWEP product outperformed the others in depicting precipitation temporal variations and in simulating streamflow observations
This study focuses on two gauge-scarce river basins on the Tibetan Plateau (TP): the source regions of the Yellow River (UYE) and Yangtze River (UYA) basins (Figure 1)

Summary

Introduction

Precipitation is one of the most important water balance components of the global water cycle and its spatial–temporal variability directly affects the available water resources in a region [1,2].Accurate estimates of precipitation are crucial for scientific research and for water resources management, drought and flood forecasting, and debris-flow and landslide hazard forecasting [3,4,5,6,7,8]. Radar precipitation observations suffer from several limitations, such as ground clutter, beam height variation, and beam blockage by mountains and high buildings [13,14]. These limitations cause the radar precipitation observations to usually need to be calibrated with the traditional rain gauge observations in the initial operating period of the radar [14,15]. The corresponding methods used to derive precipitation can be largely classified into the VIS/IR-based methods, the MW-based methods, and the merged methods using VIS/IR, MW, and PR [27] All these methods cannot observe ground precipitation directly, but rely on monitoring or modeling the precipitation-related variables to estimate precipitation indirectly. Similarity, MW and PR directly measure the content of hydrometeor within the cloud column and convert the measurements to ground precipitation estimates by empirically or physically based models

Methods

Results

Discussion

Conclusion