Return to search

Hydrological evaluation of 14 satellite-based, gauge-based and reanalysis precipitation products in a data-scarce mountainous catchment

Availability of high-quality data is a major problem for climate and hydrological studies, especially in basins with complex topography where gauge network is typically limited and unevenly distributed. This study investigates the performance of 14 precipitation products – seven satellite-based (SPPs), two gauge-based (GPPs) and five reanalysis products (RPPs) – against ground observations (1998–2007) in the transboundary Jhelum River basin (33 397 km2). Among the seven SPPs (bias corrected), five demonstrate a significantly high correlation coefficient (CC > 0.7) with observed rainfall. However, most of the products tend to underestimate the seasonal precipitation amount, particularly in winter and spring. Likewise, Asian Precipitation – Highly Resolved Observational Data Integration Towards Evaluation of water resources APHRODITE (GPPs) and Japanese 55-year Reanalysis JRA-55 (RPPs) are the best-performing products in daily streamflow predictions, with Nash-Sutcliffe efficiency values of 0.68 and 0.62, whilst MSWEP (Multi-Source Weighted-Ensemble Precipitation), AgMERRA (Climate Forcing Dataset for Agricultural Modeling) and CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data) have also good potential in flow prediction. Generally, our results indicate that APHRODITE and JRA-55 could be used as alternative sources of precipitation data in the Himalayas region.

Identiferoai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:84472
Date13 April 2023
CreatorsSaddique, Naeem, Muzammil, Muhammad, Jahangir, Istakhar, Sarwar, Abid, Ahmed, Ehtesham, Aslam, Rana Ammar, Bernhofer, Christian
PublisherTaylor & Francis
Source SetsHochschulschriftenserver (HSSS) der SLUB Dresden
LanguageEnglish
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/acceptedVersion, doc-type:article, info:eu-repo/semantics/article, doc-type:Text
Rightsinfo:eu-repo/semantics/openAccess
Relation2150-3435, 10.1080/02626667.2021.2022152

Page generated in 0.0022 seconds