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Öğe A novel metaheuristic optimization and soft computing techniques for improved hydrological drought forecasting(Pergamon-Elsevier Science Ltd, 2024) Katipoglu, Okan Mert; Ertugay, Neşe; Elshaboury, Nehal; Aktürk, Gaye; Kartal, Veysi; Pande, Chaitanya BaliramDrought is one of the costliest natural disasters worldwide and weakens countries economically by causing negative impacts on hydropower and agricultural production. Therefore, it is necessary to create drought risk management plans by monitoring and predicting droughts. Various drought indicators have been developed to monitor droughts. This study aims to forecast Streamflow Drought Index (SDI) values with various novel metaheuristic optimization-based Artificial Neural Network (ANN) and deep learning models to predict 1-month lead-time hydrological droughts on 1, 3, and 12-month time scales in the Konya closed basin, one of the driest basins in Turkey. To achieve this goal, the ANN model was integrated with the Firefly Algorithm (FFA), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) techniques and compared against long shortterm memory (LSTM) networks. While establishing the SDI prediction model, lag values exceeding the 95% confidence intervals in the partial autocorrelation function graphs were used. Model performance was evaluated according to scatter matrix, radar, time series, bee swarm graphs, and statistical performance metrics. As a result of the analysis, the PSO-ANN hybrid model with (R2:0.468-0.931) at station 1611 and the FFA-ANN hybrid model with (R2:0.443-0.916) at station 1612 generally have the highest accuracy.Öğe Drought Investigation Using SPI and SPEI Methods: A Case Study in Kırıkkale(Kırıkkale Üniversitesi, 2022) Aktürk, Gaye; Zeybekoğlu, Utku; Yıldız, OsmanDrought is one of the most important natural disasters with various social and environmental effects. Therefore, it is very important to choose a particularly suitable index for monitoring drought. Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) are widely used in drought monitoring. In this study, drought analysis was carried out using SPI and SPEI methods in order to examine the development and characteristics of drought in the city of Kırıkkale, which has semi-arid characteristics. SPI and SPEI values were calculated on 1, 3, 6, 9 and 12-month time scales by using monthly precipitation and temperature data from Kırıkkale meteorology station between 1963 and 2018. While calculating the potential evapotranspiration (PET) values in the SPEI calculation, Thornthwaite and Hargreaves models were used and two different SPEI values were obtained. As a result, high correlation values were obtained between all indices in the same time scale. It has been concluded that SPI and SPEI methods are applicable in the detection and monitoring of drought in the study area.Öğe Fırat-Dicle havzasında yıllık ortalama akımlar üzerinde iklim değişikliği etkilerinin iklim elastikiyeti metodu ile incelenmesi(2021) Alıvı, Abdulrezzak; Yıldız, Osman; Aktürk, GayeBu çalışma, Fırat-Dicle havzasında akarsu akımlarının (Q) yağış (P), potansiyel evapotranspirasyon (Ep) ve kuraklık indeksindeki değişimlere karşı tepkisini araştırmak amacıyla gerçekleştirilmiştir. Bu amaçla, havza içerisinde baraj etkisinde olmayan 37 adet alt havza tespit edilmiştir. Burada yıllık ortalama akımların yağış, Ep ve kuraklık indeksine olan hassasiyeti Schaake [1] tarafından önerilen iklim elastikiyeti metodu ile değerlendirilmiştir. Bu metot ile akışın yağış ve Ep hassasiyeti katsayılarının (sırasıyla ?P ve ?Ep ) havza genelinde ortalama değerleri sırasıyla 1,50 ve -0,50 olarak hesaplanmıştır. Buna göre; havzada yağışta meydana gelecek %10’luk bir artışın (azalışın) akışta ortalama %15’lik bir artışa (azalışa), diğer taraftan Ep‘deki %10’luk bir artışın (azalışın) ise akışta ortalama %5’lik bir azalışa (artışa) neden olacağı anlaşılmaktadır. Diğer yandan, akışın kuraklık indeksi hassasiyet katsayısının (?Ø) havza genelinde ortalama değeri -0,47 olarak hesaplanmış olup bu değer kuraklık indeksinde %10’luk bir artışın akışta ortalama %4,7’lik bir azalışa neden olacağını ifade etmektedir. Ayrıca, alt havzalara ait akışın iklim değişikliği hassasiyeti katsayıları (?P, ??Ep? ve ??Ø?) ile akış katsayısı (Q/P) arasında doğrusal olmayan ters bağıntılar olduğu ve dolayısıyla akıştaki azalma ile akışın iklimsel değişikliğe olan hassasiyetinin artacağı görülmüştür. Son olarak, havzada yüksek kotlardan alçak kotlara doğru gidildikçe ?P, ??Ep? ve ??Ø? değerlerinde göreceli bir artış olduğu tespit edilmiştir.Öğe Homogeneity and Trend Analysis of Temperature Series in Hirfanli Dam Basin(2022) Zeybekoğlu, Utku; Aktürk, GayeClimates areconstantly changing on atemporaland spatialscale, so they arenot static. In recentyears, globalwarming and changes in climatehaveshownmoreandmoreeffects on the hydrological cycle and water resources, and their effects have become so noticeable that they hinder sustainable life. For this reason, the studies on the investigation of the main causes of the observed changes in the climate, theevaluation of climatechangeas aprocess and thedetermination of the effects that will emerge, have increased over time. In the present study, the homogeneity of annual and seasonal temperature series in Hirfanli Dam basin were examined by using the Pettitt Test (PT), andthetrends were examined with the Spearman’s Rho (SR) test and Mann Kendall (MK) test. Hirfanli Dam basin,which islocated in thesemi-arid climateregionwhereclimatechangecan be seenduetoitslocation,waschosenasthestudyarea.Thetemperaturedata oftheGemerek, Kayseri, Kirsehir, Nevsehir, Sivas and Zarameteorologicalstations in the basin between 1965 and 2017wereanalyzed.Itwasnotedthatsummertemperaturesincreasedthroughoutthebasin. Significanttrendstoincreasewerealsodetectedinspringandautumn.Thetrendtoincreasewas statisticallysignificantata95%confidencelevelinallstationsexceptfortheZaraintermsof annual temperatures. Trend maps were prepared for the basin by using the results obtained here and theGeographicalInformationSystems.Itwasreportedthatthetendencytoincreaseinannual temperature series was because of the increase in summer temperatures at intense levels throughout the basin.Öğe Meteorological Drought Analysis and Regional Frequency Analysis in the Kızılırmak Basin: Creating a Framework for Sustainable Water Resources Management(Mdpi, 2024) Aktürk, Gaye; Çıtakoğlu, Hatice; Demir, Vahdettin; Beden, NeslihanDrought research is needed to understand the complex nature of drought phenomena and to develop effective management and mitigation strategies accordingly. This study presents a comprehensive regional frequency analysis (RFA) of 12-month meteorological droughts in the K & imath;z & imath;l & imath;rmak Basin of Turkey using the L-moments approach. For this purpose, monthly precipitation data from 1960 to 2020 obtained from 22 meteorological stations in the basin are used. In the drought analysis, the Standard Precipitation Index (SPI), Z-Score Index (ZSI), China-Z Index (CZI) and Modified China-Z Index (MCZI), which are widely used precipitation-based indices in the literature, are employed. Here, the main objectives of this study are (i) to determine homogeneous regions based on drought, (ii) to identify the best-fit regional frequency distributions, (iii) to estimate the maximum drought intensities for return periods ranging from 5 to 1000 years, and (iv) to obtain drought maps for the selected return periods. The homogeneity test results show that the basin consists of a single homogeneous region according to the drought indices considered here. The best-fit regional frequency distributions for the selected drought indices are identified using L-moment ratio diagrams and ZDIST goodness-of-fit tests. According to the results, the best-fit regional distributions are the Pearson-Type 3 (PE3) for the SPI and ZSI, generalized extreme value (GEV) for the CZI, and generalized logistic distribution (GLO) for the MCZI. The drought maps obtained here can be utilized as a useful tool for estimating the probability of drought at any location across the basin, even without enough data for hydrological research.Öğe Meteorolojik Kuraklığın Zamansal ve Alansal Özelliklerine İklim Değişikliğinin Etkisi, Sakarya Havzası Örneği(2021) Duvan, Akın; Aktürk, Gaye; Yıldız, OsmanKuraklık yerkürede yaşayan tüm canlı varlıkların yaşamını sürdürebilmesi için gerekli su miktarının belirli bir zaman süresince ortalamanın altına düşmesi sonucu yaşanan su kıtlığını ifade eden doğal bir afettir. Çalışmada yarı kurak iklimde bulunan Türkiye’de su sıkıntısı yaşayan Sakarya Havzası için uygulama yapılmıştır. Veri olarak meteoroloji gözlem istasyonlarından alınan gözlemlenmiş yağış verileri ile HadGEM2-ES küresel iklim modelinin RCP 4.5 ve 8.5 senaryoları ile elde edilen yağış projeksiyon verileri kullanılmıştır. Kuraklık şiddeti tespiti amacıyla Standart Yağış İndisi (SYİ), kuraklığın alansal dağılımını tespit edebilmek amacıyla da Ters Mesafe Ağırlıklı Enterpolasyon Yöntemi (Inverse Distance WeightingIDW) kullanılmıştır. Daha sonra havzanın kuraklık şiddeti-alan yüzdesi- frekans eğrileri oluşturulmuştur. Oluşturulan bu grafikler yardımıyla havza için kuraklığın zamansal ve alansal özellikleri incelenmiş, gözlemlenmiş yağış verileri ile elde edilen kuraklık şiddeti değerlerinin daha büyük olduğu görülmüştür.Öğe Modeling of irrigation water quality parameter (sodium adsorption ratio) using hybrid swarm intelligence-based neural networks in a semi-arid environment at SMBA dam, Algeria(Springer Wien, 2024) Achite, Mohammed; Katipoğlu, Okan Mert; Elshaboury, Nehal; Kartal, Veysi; Aktürk, Gaye; Ertugay, NeşeSodium adsorption rate (SAR), which significantly affects soil and plant health, is determined according to the concentration of sodium ions, calcium, and magnesium in irrigation water. Accurate estimation of SAR values is vital for agricultural production and irrigation. In this study, hybrid swarm intelligence-based neural networks are used to model sodium adsorption ratio in irrigation water quality parameters in a semi-arid environment at Sidi M'Hamed Ben Aouda (SMBA) dam, Algeria. For this, the nature-inspired optimization techniques of particle swarm optimization (PSO), genetic algorithm (GA), Jaya algorithm (JA), artificial bee colony (ABC), and firefly algorithm (FFA) and the signal processing technique of variational mode decomposition (VMD) have been combined with artificial neural networks (ANN). Correlation matrices were used to select the data entry structure in the established models. Water quality parameters with a statistically significant and medium to high relationship with SAR values were presented as input to the model. The overall performance was measured using various statistical metrics, scatter diagrams, Taylor diagrams, correlograms, boxplots, and line plots. In addition, the effect of input parameters on model estimation was evaluated according to Sobol sensitivity analysis. As a result, the GA-ANN algorithm demonstrated superior performance (MSE = 0.073, MAE = 0.193, MAPE = 0.048, MBE=-0.16, R2 = 0.934, WI = 0.968, and KGE = 0.866) based on the statistical indicators, indicating better results compared to other models. The second-best model, ABC-ANN (MSE = 0.084, MAE = 0.233, MAPE = 0.066, MBE=-0.135, R2 = 0.897, WI = 0.965, and KGE = 0.920) was also selected. The weakest prediction outputs were obtained from the VMD-ANN model. The accurate and reliable estimation of SAR in irrigation water has the potential to facilitate improvements in agricultural irrigation management and agricultural production efficiency for farmers, agricultural practitioners, and policymakers.Öğe Suspended sediment load prediction in river systems via shuffled frog-leaping algorithm and neural network(Springer Heidelberg, 2024) Katipoglu, Okan Mert; Aktürk, Gaye; Kılınç, Hüseyin Çağan; Terzioğlu, Zeynep Özge; Keblouti, MehdiSuspended sediment load estimation is vital for the development of river initiatives, water resources management, the ecological health of rivers, determination of the economic life of dams and the quality of water resources. In this study, the potential of Feed Forward Neural Network (FFNN), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Shuffled Frog Leaping Algorithm (SFLA) models was evaluated for suspended sediment load (SSL) estimation in Ye & scedil;il & imath;rmak River. The heat map of Pearson correlation values of meteorological and hydrological parameters in 1973-2021, which significantly impacted SSL estimation, was examined to estimate SSL values. As a result of the analysis it was developed a prediction model with three different combinations of precipitation, stream flow and past SSL values (M1: streamflow, M2: streamflow and precipitation, M3: streamflow, precipitation, and SSL). The prediction accuracy of the models was visually compared with the Coefficient of Determination (R2), Bias Factor (BF), Mean Absolute Error (MAE), Mean Bias Error (MBE), Root Mean Square Error (RMSE), Akaike Information Criterion (AIC), Kling-Gupta Efficiency (KGE) statistical criteria and Bland-Altan plot, boxplot, scatter plot and line plot. Based on the analyses, the PSO-ANN model in the M1 model combination showed good estimation performance with an RMSE of 1739.92, MAE of 448.56, AIC of 1061.55, R2 of 0.96, MBE of 448.56, and BF of 0.29. Similarly, the SFLA-ANN model in the M2 model combination had an RMSE of 1819.58, MAE of 520.64, AIC of 1069.9, R2 of 0.96, MBE of 520.64, and BF of 0.19. In the M3 model combination, the SFLA-ANN model achieved an RMSE of 1423.09, MAE of 759.88, AIC of 1071.9, R2 of 0.81, MBE of 411.31, and BF of -0.77. Overall, these models can be considered good estimators as their predicted values are generally close to the measured values. The study outputs can help ensure water structures' effective lifespan and operation and take precautions against sediment-related disaster risks.Öğe The Effect Of Precipitation Deficits On Hydrological Systems In The Çatalan Dam Basin, Turkey(Kırıkkale Üniversitesi, 2018) Aktürk, Gaye; Yıldız, OsmanDrought is a naturaldisaster that has various social and environmental impacts. Since Turkey islocated in a semi-arid region, drought events take place frequently. The time,duration and intensity of drought can not be predicted, so that drought in anyregion can be analyzed by using probabilistic and statistical methods. In thisstudy, the Çatalan Dam Basin, a subbasin of the Seyhan River Basin was selectedto examine the effects of droughts caused by rainfall deficiencies on riverflows, dam reservoirs and soil moistures. The Standardized Precipitation Index(SPI) method was utilized for meteorological, hydrological and agriculturaldrought analysis in the selected dam basin. In the scope of the study, firstlymeteorological drought analysis was carried out by using SPI time series atdifferent time scales and then the most appropriate time scale for monitoringthe hydrological drought on river flows and reservoir storages was determined.After that, by using SPI time series at different time scales, the mostappropriate time scale for monitoring the agricultural drought on soilmoistures was determined. Also, the relationship between river flows and soilmoistures was investigated. Also, it was determined that groundwater levelsplay important roles on soil moisture rates. The study results actually provideimportant information for drought mitigation and sustainable water resourcesmanagement at the basin scale.
