Hydrological appraisal of rainfall estimates from radar, satellite, raingauge and satellite–gauge combination on the Qinhuai River Basin, China

ABSTRACT

Multisource rainfall products can be used to overcome the absence of gauged precipitation data for hydrological applications. This study aims to evaluate rainfall estimates from the Chinese S-band weather radar (CINRAD-SA), operational raingauges, multiple satellites (CMORPH, ERA-Interim, GPM, TRMM-3B42RT) and the merged satellite–gauge rainfall products, CMORPH-GC, as inputs to a calibrated probability distribution model (PDM) on the Qinhuai River Basin in Nanjing, China. The Qinhuai is a middle-sized catchment with an area of 799 km². All sources used in this study are capable of recording rainfall at high spatial and temporal resolution (3 h). The discrepancies between satellite and radar data are analysed by statistical comparison with raingauge data. The streamflow simulation results from three flood events suggest that rainfall estimates using CMORPH-GC, TRMM-3B42RT and S-band radar are more accurate than those using the other rainfall sources. These findings indicate the potential to use satellite and radar data as alternatives to raingauge data in hydrological applications for ungauged or poorly gauged basins.

KEYWORDS:

• satellite rainfall
• radar rainfall estimates
• hydrological modelling
• ungauged catchment

Editor A. Castellarin Guest editor Y. Chen

Editor A. Castellarin Guest editor Y. Chen

Acknowledgements

The DEM, TRMM, GPM, ERA-Interim, C-morph, S-band, raingauge and flow data used in this study were downloaded/collected from the respective sources given in the text. The authors wish to extend their sincere gratitude to all of them. We also owe our sincere thanks to the Centre for Ecology and Hydrology (Wallingford, UK) for providing the PDM model. Finally, we gratefully acknowledge the help of Dr Geoff Austin who reviewed an earlier version of this paper.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ http://apps.ecmwf.int/datasets/data/interim-full-daily/levtype = sfc/.

² The data for the entire study period are archived at http://disc.sci.gsfc.nasa.gov/precipitation/tovas/.

³ https://rda.ucar.edu/datasets/ds502.0/index.html#!description.

Additional information

Funding

This research was supported by the National Natural Science Foundation of China [Grant 41675029]; the Natural Science Foundation of the Higher Education Institutions of Jiangsu Province, China [Grant 16KJB170005]; the National Basic Research Programme (973) of China [Grant 2013CB430102]; the Project of the State Key Laboratory of Severe Weather of the Chinese Academy of Meteorological Sciences [Grant 2016LASW-B12]; the Startup Foundation for Talents in Nanjing University of Information Science and Technology [Grant 2015r055]; and the Open Research Funding Programme of KLGIS [Grants KLGIS2015A01 and KLGIS2015A04].