The analysis of 2004 flood on Kozdere Stream in Istanbul

The climatic and physiographical factors of the Kozdere Creek Watershed are examined to find out the causes of the flood of August 11, 2004. Actual land use has been obtained from forest management stand plans and classified satellite images. The multispectral digital satellite data set belonging to years 1992, 1993, and 2005 was used to determine the status of land use. Physiographic factors, including the slope and the aspect, have been identified from digitized ortho-photo maps in the GIS environment. Since flow records of Kozdere are not available, flow values corresponding to different return periods were obtained using regression analysis of neighboring streams. No noticeable alteration of the land use occurred between 1992 and 2005. Since the physical factors are the same as they were during the 1985 rain, the flood after the 2004 rainfall cannot be due to the physiographical factors of the upper watershed. The existing channel in the neighborhood is not enough to convey even the 10-year return period flow. Thus, the 2004 flow did not fit into this cross-section and flooded houses on the alluvial fan. The cross-section of the Kozdere Creek passing through the PTT neighborhood should be increased, and the surface roughness should be decreased by covering the channel with concrete in order to prevent floods.     

Modeling Monthly Mean Flow in a Poorly Gauged Basin by Fuzzy Logic

The estimation of the monthly mean flow is a critical issue in many water resource development projects. However, in practice the mean flow is not easily determined in ungauged and poorly gauged basins. Therefore, in the literature, various flow estimation methods have been developed recently for mountainous regions which are generally ungauged or poorly gauged basins. In this study a fuzzy logic model based on the Mamdani approach was developed to estimate the flow for poorly gauged mountainous basins. This model was applied to the Solakli Basin which is located in the Eastern Black Sea Region of Turkey. Limited rainfall and flow data are available for this basin. In addition to these variables, the stream and time coefficients were introduced and used as variables for modeling. The data was divided into training and testing phases. The model results were compared with the measured data. The comparison depends on seven statistical characteristics, four different error modes and the contour map method. It was observed that the fuzzy model developed in this study yielded reliable results.