Search

The Bosphorus Strait is a typical example of a narrow sea strait and, in general, has a two-layer flow structure. Driven by the water level difference between the Black Sea (north) and the Sea of Marmara (south), a lighter upper layer flows from north to south. A denser lower layer flow is caused by the density difference between the adjacent seas and flows in the opposite direction. In this study, the three-dimensional (3D) flow structure of the Bosphorus strait was modeled using the MIKE 3 hydrodynamic numerical code. Selecting the drag coefficient , buoyancy parameter , and turbulence Prandtl number as calibration parameters, the model was calibrated using genetic algorithms with available current measurements at three different depths for one given location. The root-mean-square errors of the calibrated model were calculated to be 0.266, 0.201, and 0.163 m/s at the depths considered, respectively. The model was also validated temporally, for four different time periods and spatially, at another location in the strait. The validated models show good overall agreement with the field measurements. This paper is also relevant to determining the hydrodynamic design criteria of marine structures, and safe marine navigation in the waterway will be considered. [ABSTRACT FROM AUTHOR]

Water quality monitoring network design is an iterative procedure, where an existing network should be reassessed from time to time on the basis of changing environmental demands and objectives in water quality management. In recent years, the economic and financial constraints faced by monitoring agencies have led to the initiation of network reduction procedures in the space domain (i.e., the reduction of the number of stations within a network). In this regard, the dynamic programming approach (DPA) can be effectively used to determine which monitoring sites are to be preserved when the network is consolidated for a fixed number of stations. However, previous studies on the use of the DPA methodology in network redesign have not yet resolved two basic questions: (1) what is the required (optimum) number of stations to be retained in the network to best represent the basin? and (2) how many subbasins should be selected when segregating the basin into smaller units as foreseen by DPA? Accordingly, the primary objective of this paper is to modify the DPA approach to determine the optimum number of stations to be retained when consolidating a monitoring network. In previous studies, the selection of subbasins in DPA was realized basically by subjective approaches based on general experiences of the designers so that the secondary objective of the study is to expand the capabilities of DPA by utilizing a more systematic approach to subbasin identification. The previously mentioned modifications to the DPA methodology are demonstrated in the case of a water quality monitoring network in Gediz River basin along the Aegean coast of Turkey. The results obtained indicate that DPA can also be an effective tool in optimizing the number of stations to be retained in a monitoring network. [ABSTRACT FROM AUTHOR]

Forecasting streamflow is extremely significant in hydrological studies to optimize the operation of water resources systems. Upper Euphrates Basin, which is located in eastern Turkey, is a snow-dominated basin and its runoff is largely affected by snowmelt. Snowmelt is an important water resource to many aspects of hydrology, including water supply, flood control, and erosion. Selection of a suitable tool was necessary to assess potential impacts of climate change on the hydrological cycle of this region. Hydrologic models are useful tools for the prediction of runoffs and interactions among hydrological variables within the hydrologic cycle. Because of limited data availability, lumped conceptual hydrological models are often used instead of distributed hydrological models. To assess the accuracy of lumped conceptual hydrological models, this paper presents simulation results of snowmelt runoffs of Upper Euphrates Basin by using two models that use the temperature index approach to calculate snowmelt process. The Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) and Large Basin Runoff Model (LBRM) were used for this purpose. [ABSTRACT FROM AUTHOR]