Assessment of Precipitation Obtained from Gridded Data Bases in Southern Baluchestan Basin

Precipitation is an important variable in hydrological studies. The high spatial and temporal variability of precipitation makes it difficult to monitor it with observations. The use of satellite data and weather models is a suitable solution for this problem. But, before using these data, their spa...

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Bibliographic Details
Main Authors: Mohsen Rezaei, MEHDI ّAzhdary Moghaddam, Gholamreza Azizyan, Ali Akbar Shamsipur
Format: Article
Language:fas
Published: Iranian Rainwater Catchment Systems Association 2023-03-01
Series:محیط زیست و مهندسی آب
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Online Access:http://www.jewe.ir/article_148005_5d5037ff8ec4a834199feae16130238b.pdf
Description
Summary:Precipitation is an important variable in hydrological studies. The high spatial and temporal variability of precipitation makes it difficult to monitor it with observations. The use of satellite data and weather models is a suitable solution for this problem. But, before using these data, their spatial and temporal accuracy should be considered. The aim of this study was to evaluate the accuracy of monthly precipitation data TRMM_3B43_V7, PERSIANN, and ECMWF-ERA5 in comparison with the data of 13 observation stations in the South Baluchestan basin during the period 2000 to 2018. For statistical evaluation of the mentioned data, the coefficient of determination (R2), N-S efficiency factor, the degree of bias (BIAS), index agreement (IA), and ratio root mean square error (RRMSE) were used. The results showed that the best performance was exhibited by TRMM (R2=0.624) and ERA5 (R2=0.562), respectively. PERSIANN data (R2=0.307) did not provide an accurate estimate of precipitation. TRMM data are usually better estimated in areas far from the sea, which usually have higher elevations and receive more precipitation. The TRMM data is overestimated and the ERA5 data is underestimated. Data from both databases performed better in the winter months.
ISSN:2476-3683