%0 Journal Article %T Evaluation of TRMM satellite accuracy and efficiency in estimating monthly rainfall in Gorganroud watershed %J Iranian journal of Ecohydrology %I Faculty of New Sciences and Technologies, University of Tehran %Z 2423-6098 %A Emami, Hossein %A Salajegheh, Ali %A Moghaddamnia, Alireza %A Khalighi Sigaroudi, Shahram %D 2020 %\ 09/22/2020 %V 7 %N 3 %P 719-729 %! Evaluation of TRMM satellite accuracy and efficiency in estimating monthly rainfall in Gorganroud watershed %K Estimating rainfall %K TRMM Satellite %K Homogeneous Tests %K validation %K Watershed Gorganroud %R 10.22059/ije.2020.261641.917 %X Satellite remote sensing methods especially the TRMM satellite are used to estimate the precipitation of watersheds with a dispersed rainfall station. It is necessary to compare the rainfall data of the TRMM satellite with the observation precipitation data. We first used four statistical methods: Standard Normal Homogeneity Test, Buishand, Pettit, and Von Neuman, the accuracy and quality of precipitation data of rainfall stations in the Gorganroud watershed was investigated in order to predict the accuracy and performance of the TRMM satellite rainfall data. After extracting the results of homogeneous tests, by comparing with the data of adjacent stations, a suspicious station was removed from the study due to the lack of conformity with the data of adjacent stations. Then, in order to evaluate the TRMM satellite performance in estimating monthly precipitation, it was compared with the observational precipitation data using Bias, RMSE, R2 and NSE. The results showed that the R2 value for all rain gauge stations in the Gorganroud watershed is between 0.31 and 0.75. RMSE was obtained between 15.85 and 56.82. The rain gauge stations located in the Gorganroud watershed have a NSE value of -0.82 to 0.66. The Bias index is between -55.74 and 69.01. Also, the R2, RMSE, NSE and Bias values for the whole Gorganroud basin were obtained 0.79, 20.94, 0.57 and -28.13 respectively. The results of the TRMM efficiency evaluation in the monthly rainfall estimation showed that it has a good performance in estimating the precipitation and is very valuable for areas without a station. %U https://ije.ut.ac.ir/article_77765_c01c90a27aac26e28d12087b84c89008.pdf