Evaluating SM2RAIN and WRF reanalysis precipitation datasets over Turkey and hydrological model application

Management of water resources is a very important issue that countries are working on and considered as particularly challenging. Precipitation is one of the most important key factors in many hydrological studies. This study aims to evaluate precipitation data sets of satellite based SM2RAIN and WRF Reanalysis in comparison to Observations from meteorological gauge network over all Turkey for a relatively long period of time up to 10 years. These are very new data sets generated with recent technologies and this study is one of the pioneer applications over Turkey. One of the main objectives is seeking the performance of the SM2RAIN product for the possible usage in the future studies for hydrological applications in Turkey. The data sets are categorized and analyzed according to the regions in Turkey, altitude of stations, precipitation thresholds and time scales (daily, monthly, seasonal, yearly). Assessment of consistency and accuracy of the data sets are carried out with commonly used performance criteria. Results show that SM2RAIN and WRF Reanalysis have the highest correlation (R >0.8) in monthly based time scale in Southeast Anatolia region. Moreover, a hydrological modelling called "Modello Idrologico lumped in continuo" MILc, continuous model with an easy and simple use, is applied using SM2RAIN and Observed data as an input for three pilot basins in Turkey. Results show that SM2RAIN needs preprocess before to be used in hydrological predictions. On the other hand, further analysis shows that the simulated soil moisture content of MILc model has a high consistency with satellite soil moisture data (H14), Pearson correlation is as high as 0.88 when Observed precipitation is used as input.