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- ArticleAçık Erişim2022Spatial analysis of seasonal precipitation using various interpolation methods in the Euphrates basin, Turkey
Katipoğlu, Okan Mert
It is vital to accurately map the spatial distribution of precipitation, which is widely used in many fields such as hydrology, climatology, meteorology, ecology, and agriculture. This study aimed to reveal the spatial distribution of seasonal, long-term average precipitation in the Euphrates Basin with various interpolation methods. For this reason, Simple Kriging, Ordinary Kriging, Universal Kriging, Ordinary CoKriging, Empirical Bayesian Kriging, Radial Basis Functions (Completely Regularized Spline, Thin Plate Spline, Multiquadratic, Inverse Multiquadratic, Spline with Tensor), Local Polynomial Interpolation, Global Polynomial Interpolation, and Inverse Distance Weighting methods have been applied in the Geographical Information Systems environment. Long-term seasonal precipitation averages between 1966 and 2017 are presented as input for predicting precipitation maps. The accuracy of the precipitation prediction maps was based on linear regression analysis, root mean square error (RMSE), mean absolute error (MAE), correlation coefficient (R), and determination coefficient (R2) values obtained from the cross-validation tests. The most suitable method was chosen for the interpolation method that gives the lowest RMSE, MAE, and the largest R and R2. As a result of the study, Ordinary CoKriging in spring and winter precipitation, Local Polynomial Interpolation in summer precipitation, and Ordinary Kriging in autumn precipitation were the most appropriate estimation methods.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2022Analyzing the trend and change point in various meteorological variables in Bursa with various statistical and graphical methods
Katipoğlu, Okan Mert
Determining the trend in meteorological variables is vital in water resources planning, energy production, and the design of water structures. This study analyzed trends and years of change in seasonal and annual average, maximum, minimum temperature, maximum precipitation, average relative humidity, average wind speed, and sunshine duration values in Bursa. Innovative-Şen trend analysis was used to determine the trends, and the sequential Mann–Kendall method, standard normal homogeneity test, and Pettitt test were used to determine the year of change. In addition, meteorological variables were divided into three ranges as low, medium, and high, and the trends in these ranges were analyzed graphically with the ITA approach. The ITA tests showed statistically significant increases in average, minimum, and maximum temperatures and average wind speed in seasonal and annual periods. On the other hand, statistically significant decreasing trends were observed in the mean relative humidity and sum sunshine duration values in seasonal and annual periods. In addition, significant decreasing trends were observed in the 95% confidence interval in the summer and annual periods in the maximum precipitation values. According to the sequential Mann–Kendall method, there were changes in temperature values in 1995 and 2015, wind speed values in 1946, relative humidity values in 1975 and 1977, and sunshine duration values around 1996. This study’s outputs significantly contribute to planners and decision-makers in terms of managing water resources, drought, and flood risk, developing adaptation strategies against climate change and agricultural irrigation and crop production.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2022Analysis of spatial variation of temperature trends in the semiarid Euphrates basin using statistical approaches
Katipoğlu, Okan Mert
This study analyzes the spatial and temporal distribution of trends on monthly, seasonal, and annual mean temperatures (1967–2017) at 22 stations in the Euphrates Basin of Turkey. The recently proposed innovative trend analysis (ITA) and the nonparametric Mann–Kendall (MK) and Spearman’s rho (SR) test at 5% and 1% significance levels were applied to examine the temporal trends of temperatures. Before using the nonparametric trend analysis, the serial correlation of the temperature data was removed with the pre-whitening (PW) method. Then, MK-Z values were mapped in ArcGIS environment using the Empirical Bayesian Kriging (EBK) method to reveal the spatial variation of temperature trends. As a result, according to the ITA method, increasing temperature trends at 1% significance level dominate almost all periods. Based on the MK and SR tests, it was identified that increase trends were dominant at 1% and 5% significance levels in February, March, April, July, August, Spring, Summer, and Annual periods. According to the spatial temperature trend maps, significant increase trends occupy an important place in most of the basin in February, March, April, June, July, August, Spring, Summer, Winter, and Annual periods. The study results provide important information to water resources managers and decision-makers about the regions at significant risk in climate change in the Euphrates Basin.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2022Space-time variations of hydrological drought severities and trends in the semi-arid Euphrates Basin, Turkey
Katipoğlu, Okan Mert; Acar, Reşat
The main purpose of this study is to map the spatio-temporal variation of hydrological drought severities in the Euphrates Basin by using Kriging, Radial Based Function (RBF), Inverse Distance Weighting (IDW), Local Polynomial Interpolation (LPI), and Global Polynomial Interpolation (GPI) methods and to determine the distribution of hydrological drought trends. For this purpose, 18 streamflow observation stations and grid-based ERA5 reanalysis data were employed in and around the Euphrates Basin. The standardized runoff index (SRI) was calculated on monthly, 3-month, and 12-month time scales to determine hydrological droughts. Hydrological drought trends were determined by Mann Kendall (MK) and Modified Mann Kendall (MMK) tests. According to SRI, spatial-temporal distributions of droughts were mapped by Kriging, RBF, IDW, GPI, and LPI methods in the Geographical Information Systems environment. The LPI and Kriging method was selected as the most effective methods to predict hydrological droughts based on the cross-validation error. As a result of the trend analysis, the predominance of decreasing SRI trends in May (61.1%), June (72.2%), July (55.6%), August (61.1%) indicates that the basin is at risk of hydrological drought, especially in summer. According to the maps of spatial droughts, the widespread distribution of droughts in the basin indicated that the basin was greatly affected by hydrological droughts. For this reason, it has been emphasized that transboundary water effective management between riparian countries, planning of water structures, and effective implementation of the drought management plan is of great importance.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2021Standartlaştırılmış yağış indeksi hesabında kullanılan dağılım fonksiyonu etkisinin ve kuraklık karakteristiklerinin araştırılması
Katipoğlu, Okan Mert; Acar, Resat
Yağışın tipi ve yapısı; yükseklik, yer şekilleri, bitki örtüsü, deniz akıntıları, denize yakınlık ve uzaklık gibi parametrelere göre değişiklik göstermektedir. Bu nedenle yağış verilerinin tek bir dağılım ile ifadesi oldukça zordur. Yapılan çalışmada yağış verilerine hidrolojide sıkça kullanılan Gamma, Lognormal, Genelleştirilmiş Ekstrem Değer (GED), Weibull, Normal, Lojistik, Loglojistik dağılımları uydurularak elde edilen Standartlaştırılmış Yağış İndeksi (SYİ) ve Gamma SYİ değerlerinin hesaplanması ve bu değerlere run teorisi uygulanarak elde edilen kuraklık karakteristiklerinin karşılaştırılması amaçlanmıştır. Yağış verilerine en iyi uyan olasılık yoğunluk fonksiyonunun belirlenmesinde Kolmogorov-Smirnov (K-S), Anderson-Darling (A-D) ve Ki-kare (χ2) testleri ve grafiksel metotlar kullanılmıştır. Analizler sonucunda, Fırat havzasındaki yağışları GED dağılımının, Gamma dağılımından daha iyi temsil ettiği ve hesaplanan SYİ değerlerinde ortalama %2 sapma meydana geldiği tespit edilmiştir. Ayrıca havzada şiddetli ve uzun süreli kuraklıklar dikkat çekmektedir. Bu sebeple havzada kuraklık önlemlerinin alınması, kuraklık azaltma stratejilerinin geliştirilmesi ve sürekli bir şekilde uygulanması, su tasarrufunun sağlanması, kurak dönemlerde sigorta görevi gören yeraltı sularının korunması, sulama sistemlerinin modernleşmesi ve iklim değişikliğine karşı tedbirlerin alınması gerekmektedir.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2021Determination of Meteorological and Hydrological Drought Maps with Various Interpolation Methods in the Euphrates Basin
Katipoğlu, Okan Mert; Acar, Resat
Drought is a natural disaster that adversely affects various sectors such as hydroelectric power generation, health, industry, tourism, economy, agriculture and animal husbandry. For this reason, monitoring, determining the spatio-temporal distribution, and managing drought risks by taking precautions are of great importance. In this study, it is aimed to map the spatio-temporal changes of various meteorological and hydrological droughts in the Euphrates Basin according to drought classes with Kriging, Radial Based Function (RBF) and Inverse Distance Weighting (IDW) interpolation methods and to evaluate the drought risk situation in the basin. For this, Standardized Precipitation Index, Statistical Z-Score Index, Precipitation Anomaly Index, Standardized Precipitation Evapotranspiration Index, Reconnaissance Drought Index and Standardized Runoff Index values were used for 16 Meteorology Observation Stations and 18 stream-gauging stations in the Euphrates Basin. As a result of the analyses, it has been determined that the Kriging method is the most effective method in predicting meteorological droughts in the basin, and RBF is the most effective method in predicting hydrological droughts. Since the drought risk level of the basin is determined to be high, it is recommended to make a drought management plan in the study area, to reduce negative drought effects, and to take early warnings and drought precautions.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2021Estimation of missing temperature data by Artificial Neural Network (ANN)
Katipoğlu, Okan Mert; Acar, Resat
Ensuring more reliable and quality meteorological and climatological studies by providing data continuity and widening the data range. For this reason, missing values in meteorological data such as temperature, precipitation, evaporation must be completed. In this study, an artificial neural network (ANN) model was used to complete missing temperature data in the Horasan meteorology station. To establish the ANN model, monthly average temperature values of neighboring stations having similar climatic characteristics and altitude with Horasan were used as input. The monthly average temperature values of the Horasan station were used as output. Approximately 70% of the data was used for training, about 15% for testing, and about 15% for verification in the ANN model. Various statistical parameters were compared to determine the best network architecture and best model. As a result, the model's high determination coefficient (R2 = 0.99) and low mean absolute error (MAE = 0.61) showed that the ANN model can be used effectively in estimating missing temperature data.
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