Staffordshire University logo
STORE - Staffordshire Online Repository

Ranking of gridded precipitation datasets by merging compromise programming and global performance index: a case study of the Amu Darya basin

Salehie, Obaidullah, Ismail, Tarmizi, SHAHID, Shamsuddin, Ahmed, Kamal, Adarsh, S, ASADUZZAMAN, Md and DEWAN, Ashraf (2021) Ranking of gridded precipitation datasets by merging compromise programming and global performance index: a case study of the Amu Darya basin. Theoretical and Applied Climatology. ISSN 0177-798X

PrecipitationValidationADRB_Feb_2021_Accepted_Version.pdf - AUTHOR'S ACCEPTED Version (default)
Available under License Creative Commons Attribution 4.0 International (CC BY 4.0) .

Download (1MB) | Preview

Abstract or description

Accurate representation of precipitation over time and space is vital for hydro-climatic studies. Appropriate selection of gridded precipitation data (GPD) is important for regions where long-term in-situ records are unavailable and gauging stations are sparse. This study was an attempt to identify the best GPD for the data-poor Amu Darya River basin, a major source of freshwater in Central Asia. The performance of seven GPDs and 55 precipitation gauge locations was assessed. A novel algorithm, based on the integration of a compromise programming index (CPI) and a global performance index (GPI) as part of a multi-criteria group decision-making (MCGDM) method, was employed to evaluate the performance of the GPDs. The CPI and GPI were estimated using six statistical indices representing the degree of similarity between in-situ and GPD properties. The results indicated a great degree of variability and inconsistency in the performance of the different GPDs. The CPI ranked the Climate Prediction Center (CPC) precipitation as the best product for 20 out of 55 stations analyzed, followed by the Princeton University Global Meteorological Forcing (PGF) and Climate Hazards Group Infrared Precipitation with Station (CHIRPS). Conversely, GPI ranked the CPC product the best product for 25 of the stations, followed by PGF and CHRIPS. Integration of CPI and GPI ranking through MCGDM revealed that the CPC was the best precipitation product for the Amu River basin. The performance of PGF was also closely aligned with that of CPC.

Item Type: Article
Additional Information: This is a post-peer-review, pre-copyedit version of an article published in Theoretical and Applied Climatology. The final authenticated version is available online at:
Faculty: School of Creative Arts and Engineering > Engineering
Depositing User: Md ASADUZZAMAN
Date Deposited: 17 Mar 2021 10:57
Last Modified: 24 Feb 2023 14:01

Actions (login required)

View Item View Item

DisabledGo Staffordshire University is a recognised   Investor in People. Sustain Staffs
Legal | Freedom of Information | Site Map | Job Vacancies
Staffordshire University, College Road, Stoke-on-Trent, Staffordshire ST4 2DE t: +44 (0)1782 294000