A comparison between high-resolution satellite precipitation estimates and gauge measured data: case study of Gorganrood basin, Iran Donya Dezfooli, Banafsheh Abdollahi, Seyed-Mohammad Hosseini-Moghari and Kumars Ebrahimi ABSTRACT The aim of this paper is to evaluate the accuracy of the precipitation data gathered from satellites including PERSIANN, TRMM-3B42V7, TRMM-3B42RTV7, and CMORPH, over Gorganrood basin, Iran. The data collected from these satellites (2003–2007) were then compared with precipitation gauge observations at six stations, namely, Tamar, Ramiyan, Bahlakeh-Dashli, Sadegorgan, Fazel-Abad, and Ghaffar-Haji. To compare these two groups, mean absolute error (MAE), bias, root mean square error (RMSE), and Pearson correlation coefficient criteria were calculated on daily, monthly, and seasonal basis. Furthermore, probability of detection (POD), false alarm ratio (FAR), and critical success index (CSI) were calculated for these datasets. Results indicate that, on a monthly scale, the highest correlation between observed and satellite-gathered data calculated is 0.404 for TRMM-3B42 at Bahlakeh-Dashli station. At a seasonal scale, the highest correlation is calculated for winter data and using PERSIANN data, while for the other seasons, TRMM-3B42 data showed the best correlation with observed data. The high values of RMSE and MAE for winter data showed that the satellites provided poor estimations at this season. The best and the worst values of RMSE for studied satellites belonged to Sadegorgan and Ramiyan stations, respectively. Furthermore, the PERSIANN gains a better CSI and POD while TRMM-3B42V7 showed a better FAR. Donya Dezfooli Banafsheh Abdollahi Seyed-Mohammad Hosseini-Moghari Kumars Ebrahimi (corresponding author) Department of Irrigation & Reclamation Engineering, University of Tehran, Karaj, Iran E-mail: ebrahimik@ut.ac.ir Key words | CMORPH, daily precipitation, PERSIANN, remote sensing, statistical evaluation, TRMM INTRODUCTION Global precipitation observations are of paramount impor- tance in climate studies and examination of hydrological models. Therefore, accurate precipitation measurement at global and local scales plays a crucial rule in a better under- standing of the climate, hydrological cycle, simulation of hydrological processes and weather forecasts (Qin et al. ; Cai et al. ; Milewski et al. ). Given the fact that rain gauge stations are scattered and are accessed with substantial delays, it seems necessary to resort to other ways of precipitation estimations (Ghajarnia et al. ). Over the past three decades, a number of studies have been performed to develop different methods of precipitation measurements through making use of satellite images in order to improve the accuracy and make precipi- tation estimates in regions that lack comprehensive and reliable data (Liu et al. ). The only direct source of precipitation measurement is rain gauges, which might sometimes lack accuracy due to various reasons, including errors made by users, device fail- ure, and sensitivity and the impossibility of installing recorders in impassable regions. Furthermore, due to limit- ations in the number of rain gauge stations, no proper spatial distribution could be envisaged for precipitation. Pro- viding an overhead spatial coverage, satellites are nowadays 236 © IWA Publishing 2018 Journal of Water Supply: Research and Technology—AQUA | 67.3 | 2018 doi: 10.2166/aqua.2018.062 Downloaded from https://iwaponline.com/aqua/article-pdf/67/3/236/658718/jws0670236.pdf by guest on 15 June 2020