Extreme rainfall events and consequent floods are being observed more frequently in the Western Black Sea region in Turkey as climate changes. In this study, application of a flood early warning system is intended by using and calibrating a combined model system. A regional-scale hydro-meteorological model system, consisting of Weather Research and Forecasting (WRF) model, NOAH land surface model and fully distributed NOAH-Hydro hydrologic models, is used for simulations of 25 heavy-rainfall and major flooding events observed in the Western Black Sea region between years 2000 and 2011. The performance of WRF model system in simulating precipitation is tested with 3-dimensional variational (3DVAR) data assimilation scheme. WRF-derived precipitation with and without data assimilation and Multi Precipitation Estimates (MPE) are used in NOAH-Hydro model to simulate streamflow for flood events. Statistical precipitation analyses show that WRF model with 3DVAR improved precipitation up to 12% with respect to no-assimilation. MPE algorithm generally underestimates rainfall and it also showed lower performance than WRF model with and without data assimilation. Depending on reliability of precipitation inputs, NOAH-Hydro model produces reasonable flood hydrographs both in structure and volume. After model calibration is performed using assimilated precipitation inputs in Bartin Basin, NOAH-Hydro model reduced the average error in streamflow by 23.24% and 53.57% with calibration for testing events. With calibrated parameters, NOAH-Hydro model forced by WRF non-assimilated precipitation input also reduced the error in streamflow but with lower rates (16.67% and 40.72%). With a proper model calibration and reliable precipitation inputs, hydrologic modeling system is capable of simulating flood events.

Today, mainframes contain a considerable portion of business applications worldwide. It is estimated that the current inventory of production COBOL running on mainframes is 150 to 200 billion lines of code. Despite the efforts to change within the mainframe environment, these mainframes, nowadays, face major problems for host organizations due to a combined set of financial, business related, technical and organizational problems. Moreover, the factors like diminishing resources (COBOL programmers), lack of documentation, inability to integrate with other systems, increasing maintenance costs, etc. have caused the organizations search for migration solutions. To overcome this problem within the context of modernization, over the years several main migration approaches that ranges from simple screen scraping methods to complete re-write of applications or re-hosting of platforms have been developed. To contribute to the solution of this overall problem, this thesis proposes a methodology framework specifically for the COBOL/CICS based mainframes. The research studies in this topic within this field are mainly focused on the technical aspects whereas our concentration is covering not only that but the other essential aspects of the problem domain. These are organizational view, project management view and process view. Within the thesis study, a special interest is given to the modernization strategy selection among migration, rewrite, packaged and do-nothing alternatives. Experimental results are also provided within the thesis to prove the usability of the approach for this selection.

In this study, the plant layout problem of a worldwide Printed Circuit Board (PCB) producer company is analyzed. Machines are grouped into cells using grouping methodologies of Tabular Algorithm, K-means clustering algorithm, and Hierarchical grouping with Levenshtein distances. Production plant layouts, which are formed by using different techniques, are evaluated using technical and economical indicators.