Univrsity Of Tehran Press Water and Irrigation Management 2251-6298 11 2 2021 08 23 Analysis of TRMM precipitation data uncertainty in groundwater level modeling of Rafsanjan plain Analysis of TRMM precipitation data uncertainty in groundwater level modeling of Rafsanjan plain 207 222 82630 10.22059/jwim.2021.319364.862 FA Saman Seyf M.Sc. Student, Faculty of Civil Engineering, Department of Construction and Water Management, Science and Research Branch, Islamic Azad University, Tehran, Iran. Ahmad Sharafati Asisstant Professor, Faculty of Civil Engineering, Department of Construction and Water Management, Science and Research Branch, Islamic Azad University, Tehran, Iran Journal Article 2021 03 10 Precipitation information plays an important role in calculating aquifer nutrition using mathematical models. In recent years, with the availability of satellite precipitation data, especially TRMM and GPM satellites, new and innovative methods have been developed to overcome the lack of access to precipitation data. However, barriers such as data uncertainty also limit these methods. In this study, after correcting the satellite data error, this information was used as a feed parameter to MODFLOW code, and the groundwater level uncertainty was calculated by different Coppola functions. Examination of groundwater model outputs showed a 50% reduction in root mean square error index (RMSE). It is worth noting that about 90% of the aquifer had a difference of less than 10%, about 8% had a difference of 20 to 30% and about 2% of the aquifer had an approximate difference of 80% of the observational data ratio. The mentioned results show the proper performance and with a reliability coefficient of over 90% of the Coppola functions in calculating the groundwater level uncertainty using satellite precipitation data as the feeding parameter. Precipitation information plays an important role in calculating aquifer nutrition using mathematical models. In recent years, with the availability of satellite precipitation data, especially TRMM and GPM satellites, new and innovative methods have been developed to overcome the lack of access to precipitation data. However, barriers such as data uncertainty also limit these methods. In this study, after correcting the satellite data error, this information was used as a feed parameter to MODFLOW code, and the groundwater level uncertainty was calculated by different Coppola functions. Examination of groundwater model outputs showed a 50% reduction in root mean square error index (RMSE). It is worth noting that about 90% of the aquifer had a difference of less than 10%, about 8% had a difference of 20 to 30% and about 2% of the aquifer had an approximate difference of 80% of the observational data ratio. The mentioned results show the proper performance and with a reliability coefficient of over 90% of the Coppola functions in calculating the groundwater level uncertainty using satellite precipitation data as the feeding parameter. https://jwim.ut.ac.ir/article_82630_5f13226c9732489de199563c9d87df50.pdf