Yazar "Dikbas, Fatih" seçeneğine göre listele

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    Analysis of temperature series: estimation of missing data and homogeneity test
    (Wiley-Blackwell, 2012) Firat, Mahmut; Dikbas, Fatih; Koc, A. Cem; Gungor, Mahmud
    In this study, missing value analysis and homogeneity tests were applied on the 267 meteorological stations having temperature records throughout Turkey. The monthly and annual mean temperature data of stations operated by the Turkish State Meteorological Service (DMI) for the period 1968-1998 were considered. For each station, each month was analysed separately and the stations with more than 5 years missing values were eliminated. The missing values of the stations were extrapolated by the Expectation Maximization (EM) method using the data of the nearest gauging station (reference station). In consequence of the analysis, annual mean temperature data are obtained by using the monthly values. These data have to be hydrologically/statistically reliable if they are to be used in later hydrological, meteorological, climate change and estimation studies. For this reason, the Standard Normal Homogeneity Test (SNHT), the (Swed-Eisenhart) Runs Test and the Pettitt homogeneity test were applied to detect inhomogeneities in the annual mean temperature series. Each test was evaluated separately and inhomogeneous stations were determined. Copyright (C) 2011 Royal Meteorological Society
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    Classification of Annual Precipitations and Identification of Homogeneous Regions using K-Means Method
    (Turkish Chamber Civil Engineers, 2012) Firat, Mahmut; Dikbas, Fatih; Koc, Abdullah Cem; Gungor, Mahmud
    Classification of Annual Precipitations and Identification of Homogeneous Regions using K-Means Method Reliable and correct estimation of hydrological and meteorological processes is one of the major problems in regions with insufficient hydrologic information and data. The classification of the hydrological variables and determination of homogeneous regions are the most important steps of regional studies. The purpose of this study is to classify the annual total precipitation series and to identify the homogeneous regions by K-Means method. The K-means method, which is the simplest and most commonly used clustering method, divides a data set into clusters by minimizing the sum of the Euclidean distance between each feature vector and its closest cluster centre. The annual precipitation records and longitude, latitude and altitude values obtained of 188 stations operated by the National Meteorology Works (DMI) in Turkey were considered for clustering analysis. The number of clusters was determined as 7 by means of clustering analysis. Moreover, the regional homogeneity test was applied for testing the homogeneity of regions.
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    Classification of precipitation series using fuzzy cluster method
    (Wiley-Blackwell, 2012) Dikbas, Fatih; Firat, Mahmut; Koc, A. Cem; Gungor, Mahmud
    The identification of hydrologically homogeneous regions is one of the most important steps of regional frequency analysis. The hydrologically homogeneous regions should be determined using cluster analysis instead of the geographically close regions or stations. In this study, fuzzy cluster method (Fuzzy C-Means: FCM) is applied to classify the precipitation series and identify the hydrologically homogeneous groups. The choice of appropriate cluster method and the variables that will be used according to the data of the basin is also very important. In the context of this study, total precipitation data of stations operated by National Meteorology Works (DMI) in Turkish basins for cluster analysis are used. The optimal number of groups is determined as six, based on different performance evaluation indexes. Regional homogeneity tests based on L-moments method are applied to check homogeneity of these six regions identified by cluster analysis. Regional homogeneity test results show that regions defined by FCM method are sufficiently homogeneous for regional frequency analysis. According to the results, FCM method is recommended for classifying the precipitation series and for identifying the hydrologically homogenous regions. Copyright (c) 2011 Royal Meteorological Society
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    Defining Homogeneous Regions for Streamflow Processes in Turkey Using a K-Means Clustering Method
    (Springer Heidelberg, 2013) Dikbas, Fatih; Firat, Mahmut; Koc, A. Cem; Gungor, Mahmud
    The major problem in ungauged basins for planning and management of water resources projects is to estimate the flood magnitudes and frequencies. The identification of hydrologically homogeneous regions is one of the most important steps of regional frequency analysis. In this study, K-Means clustering method is applied to classify the maximum annual flows and identify the hydrologically homogeneous groups. For this aim, the annual maximum river flows, coefficient of variation and skewness of annual maximum river flows, latitude and longitude at 117 stations operated by the General Directorate of Electrical Power Resources Survey and Development Administration throughout Turkey are used. The optimal number of groups was determined as seven. Regional homogeneity test based on L-moments method is applied to check homogeneity of these seven regions identified by clustering analysis. The results show that regions defined by K-Means method can be used for regional flood frequency analysis. According to the results, K-Means method is recommended to identify the hydrologically homogeneous regions for regional frequency analysis.
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    Missing data analysis and homogeneity test for Turkish precipitation series
    (Indian Acad Sciences, 2010) Firat, Mahmut; Dikbas, Fatih; Koc, A. Cem; Gungor, Mahmud
    In this study, missing value analysis and homogeneity tests were conducted for 267 precipitation stations throughout Turkey. For this purpose, the monthly and annual total precipitation records at stations operated by Turkish State Meteorological Service (DMI) from 1968 to 1998 were considered. In these stations, precipitation records for each month was investigated separately and the stations with missing values for too many years were eliminated. The missing values of the stations were completed by Expectation Maximization (EM) method by using the precipitation records of the nearest gauging station. In this analysis, 38 stations were eliminated because they had missing values for more than 5 years, 161 stations had no missing values and missing precipitation values were completed in the remaining 68 stations. By this analysis, annual total precipitation data were obtained by using the monthly values. These data should be hydrologically and statistically reliable for later hydrological, meteorological, climate change modelling and forecasting studies. For this reason, Standard Normal Homogeneity Test (SNHT), (Swed Eisenhart) Runs Test and Pettitt homogeneity tests were applied for the annual total precipitation data at 229 gauging stations from 1968 to 1998. The results of each of the testing methods were evaluated separately at a significance level of 95% and the inhomogeneous years were determined. With the application of the aforementioned methods, inhomogeneity was detected at 50 stations of which the natural structure was deteriorated and 179 stations were found to be homogeneous.