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    مصطلحات موضوعية: Hidrometeorological Model, WRF, Hidrolojik Model, Tahmin, Taşkın, Yağış, Uydu Algoritması, Gözlemler, Veri Asimilasyonu, Evidence is showing that global warming or climate change has a direct influence on changes in precipitation and the hydrological cycle. Extreme weather events such as heavy rainfall and flooding are projected to become much more frequent as climate warms. On the other hand, hydrologic predictions are critical for decision-making related to flood mitigation and water resources, but current climate or atmospheric forecasts do not generally provide the required level of support. The reasons for this include the coarse spatial resolution of climate forecasts, the lack of an interface between these forecasts and a hydrologic model, and insufficient input of fine-scale data into the modeling system. Progress in these areas is needed so that land-atmosphere feedbacks, impacts of climate conditions, and initial mesoscale structure of hydrometeorological conditions can be more accurately accounted for during the hydrologic prediction cycle. In this vein, the use of satellite- derived precipitation data is providing a pathway toward enhancing the spatial resolution of available data, while the coupling of land-surface and atmospheric models is advancing the simulation of these critical processes. In addition, with the use of three dimensional data assimilation technique the initial structure of the regional hydrometeorology is more reliable. This combination of assimilating finer-scale data and improving the depiction of related processes can be expected to improve the skill in hydrological forecasting. Specifically, the research proposed herein aims to use an advanced version of hydrological model with a fine-scale hydrometeorological system consisting of the Weather Research and Forecasting (WRF) model linked to the NOAH land-surface model. The performance of the modeling system will be evaluated for the selected heavy rainfall events and associated flooding conditions over the West Black Sea Basin in Turkey. WRF with data assimilation provided improvements on the magnitude and timing of precipitation events and these improvements reflected on flood hydrographs simulated by hydrologic model. Satellite algorithm generally underestimated precipitation and therefore it is found to be less successfull with repsect to WRF model. Because there is a need of reliable precipitation fields in obtaining reasonable flood prediction the use of assimilation technique in WRF modeling system is very important

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