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Acta Physica Polonica A
|
2015
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vol. 128
|
issue 2B
B-222-B-224
EN
In this study, the geomorphologic parameters of Damlıca basin are determined by using Geographic Information Systems (GIS). The digital elevation model (DEM) of the basin is downloaded from Aster-GDEM web page and this digital map is used in the GIS computer program to obtain the geomorphologic parameters of the Damlıca basin, such as the area of the basin, its perimeter, river length, slope, etc. The extracted parameters are compared with the parameters obtained by conventional methods. This study shows that the geomorphologic parameters of the Damlıca basin obtained using GIS are much more precise than those produced by conventional methods.
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EN
In this study, synthetic unit hydrograph parameters which are q_{p}, t_{p}, t_{b} are calculated by using Synder, Mockus, SCS (Soil Conservation Service) and DSI (State Hydraulic Works) methods. First according to observed data, calculations were done. Then the mentioned above methods, which are based on both topographic map and geographic information systems values, were applied. Three catchments, Damlıca, Vize, Kumdere were studied. Synder, Mockus, SCS and DSI methods were applied for each catchment.
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Cross-Drainage Culvert Design by Using GIS

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EN
A culvert is a structure that allows water to flow under a road, railroad, trail, or similar obstruction, from one side to the other side. Typically embedded, so as to be surrounded by soil, a culvert may be made from a pipe, reinforced concrete or other material. In order to minimize the impact of a water crossing on the environment, culverts require the proper size, design and installation, to ensure that they do not cause downstream erosion, upstream flood, alter stream habitat or block organism passage. In this study, the size of a box culvert has been determined by getting more realistic maximum flow rates, by using data of a geographic information system. The results of this study have been compared with the rational method. The size of the culvert, which is calculated by using data from geographic information system will be more realistic and efficient, compared to the culvert, calculated by rational method.
EN
For developing unit hydrographs of catchments, the detailed information about the rainfall and the resulting flood hydrographs are needed. Such information, however, is available only for a few locations and for the remote locations such information is normally very scanty. In this study, Snyder based synthetic unit hydrographs were developed by using both, the digitized map and the digital elevation model of a case study of a small catchment in Turkey. Multi-output neural network technique was applied to predict three unit hydrograph parameters: peak discharge q_{p}, time to peak t_{p} and time base t_{b} of a number of unit hydrographs observed in the catchment, based on most relevant geomorphological and meteorological parameters. Multi-output neural network was observed to outperform the conventional synthetic unit hydrograph methods. The advantage of the proposed multi-output neural network is based on the fact that it predicts the three parameters of the unit hydrograph, based on a single model, compared to the conventional neural network technique, which utilizes a model for each parameter.
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EN
This study is based on laboratory experiments for computing depth of local scour around group bridge pier, considering the effects of upstream flow conditions, size of pier, median size of bed material and spacing between bridge piers on the maximum scour depth and scour pattern around bridge piers. The study was conducted using a physical hydraulic model for bridge piers, operated under clear-water condition and using uniform cohesionless sand as bed material. Three different models of bridge piers, having different sizes were used for showing the effect of the size on the local scour.
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