Yazarlar
- Katipoğlu, Okan Mert(57)
- Akın, Fatih(15)
- Manga, Muge(12)
- Achite, Mohammed(11)
- Balli, Esra(11)
- Kartal, Veysi(10)
- Yilmaz, Harun(10)
- Destek, Mehmet Akif(9)
- Elshaboury, Nehal(8)
- Demirci, Oğuz Kürşat(7)
- Ganjehsarabi, Hadi(7)
- Yilmaz, Ilker(7)
- Cam, Omer(6)
- Cengiz, Orhan(6)
- Dinçer, Selin(6)
- Elbeltagi, Ahmed(6)
- Manga, Müge(6)
- Seyhan, Aslıhan Kurnuç(5)
- Sigeze, Ciler(5)
- Çatık, Abdurrahman Nazif(5)
- Abdallah, Mohammed(4)
- Acar, Reşat(4)
- Ballı, Esra(4)
- Bazrafshan, Ommolbanin(4)
- Berhail, Sabri(4)
- Dogan, Ahmet(4)
- Kilic, Ugur(4)
- Kuziboev, Bekhzod(4)
- Makhmudov, Samariddin(4)
- Mohammadi, Babak(4)
- Pande, Chaitanya Baliram(4)
- Pandey, Kusum(4)
- Sari, İdris(4)
- Sarıgöl, Metin(4)
- Uzun, Sinem(4)
- Çatik, Abdurrahman Nazif(4)
- Acar, Resat(3)
- Bakirci, Kadir(3)
- Dalkilic, Huseyin Yildirim(3)
- Ekici, Selcuk(3)
Yayınlar
- ArticleAçık Erişim2023Travel option-based environmental comparison between passenger aircraft and high-speed rail
Çam, Ömer; Kilic, Ugur
The short-haul flights have higher emission values than medium or long-haul flights when emissions per distance are considered. In this study, the potential to reduce greenhouse gas emissions by replacing short-haul flights which carried out by a narrow-body commercial aircraft from/to Konya City in Turkey with regional jets or high-speed trains (HSRs) has been investigated. The flight trajectory is selected from Konya Airport to İstanbul Sabiha Gökçen Airport, and that trajectory is a frequently performed domestic flight between Konya and İstanbul. The IMPACT platform is used for the calculation of fuel burn and gas emissions. According to the results, traveling with regional jets or high-speed trains from/to Konya City which is the most 15th polluted city in Europe, provides advantages in terms of environmental impact. Traveling with HSR which is the best traveling option in this study, provides approximately 3.3 times more green travel than the currently used narrow-body passenger aircraft between Konya and İstanbul. In addition, this mode of transportation can become more environmentally friendly by using renewable energy sources to produce its electricity needs. It is expected that this study will serve as a guide for airline and high-speed rail operators and regulators to determine the most environmentally efficient travel options based on fuel burn and emission parameters.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2023A comparison of the environmental impact of turboprop and turbofan-powered aircraft
Kilic, Ugur
Purpose: This study aims to examine turboprop- and turbofan-powered aircraft, with the same seating capacity flying on the same route and trajectory, and investigate their environmental effects. Design/methodology/approach: The integrated aircraft noise and emissions modeling platform developed by EUROCONTROL is used for the calculation of fuel burn, CO2, H2O and other gas emissions (NOx, SOx, CO, HC, soot and other trace compounds) for the per phase of flight. Findings: The striking findings are that turboprop-powered aircraft offer lower required thrust, fuel consumption and total emissions for a short-haul flight, but turbofan-powered aircraft have lower particulate matter, CO and HC emissions than turboprop-powered aircraft. This study suggests that turboprop-powered aircraft are superior to turbofan-powered aircraft in terms of environmental impact for a short-haul flight. Practical implications: The current research conducts comprehensively fuel consumption and amounts of emissions aspects of turboprop- and turbofan-powered aircraft for sustainable development of airlines by a versatile simulation approach and sheds light on airlines intending to create fleets. Originality/value: The research offers a systematic aircraft selection for investigators, scientists, airline operators, policy analysts and legislators, by a comprehensive computer simulation method that acknowledges consistently the fuel consumption and detailed emissions analysis of turboprop- and turbofan-powered aircraft.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2023Using multi-criteria performance measurement models to evaluate the financial, operational and environmental sustainability of airlines
Tanrıverdi, Gökhan; Merkert, Rico; Karamaşa, Çağlar; Asker, Veysi
Airline sustainability, defined as both decarbonization and long-term financial survival, has become critical especially since the onset of the COVID-19 pandemic. Our paper investigates the multi-dimensional effects of the COVID-19 crisis on airlines’ sustainability performance using data from 56 airlines for the period before, during and early after the pandemic (2017–2021). We develop and use a novel multi-criteria MEREC–CoCoSo/Borda performance measurement model tailored to the airline industry. Our results suggest that while operational results have dominated sustainability weights throughout the period, the financial pillar has gained considerably in importance while the decarbonization criterion decreased in weight in 2020. However, from 2021, decarbonization started to become more important again in the “new normal” and sector recovery. In terms of overall and sustained sustainability, low-cost carriers and small full-service carriers with predominantly domestic networks are ranked as best performers. Renewing fleet, attaching decarbonization conditions to government aid and reviewing airport slot policies are important to prepare the aviation industry for the next pandemic or disruption.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2023Is export quality a viable option for sustainable development paths of Asian countries?
Manga, Muge; Cengiz, Orhan; Destek, Mehmet Akif
This paper investigates the role of export quality in climate action goal of the sustainable development goals in emerging Asian countries. For this purpose, the empirical model that observes the impact of real GDP, energy use and export quality index on carbon emissions is constructed and is analyzed by ARDL bounds testing approach for the period from 1970 to 2014. We also include the square of real GDP as independent variable to observe the existence of environmental Kuznets curve (EKC) hypothesis which implies the parabolic relationship between economic growth and environmental degradation. The findings show that increase in export quality leads to a fall in CO2 emissions for China and India. In contrast, the effect of increasing export quality increases CO2 emissions in Thailand and the Philippines. Lastly, our asymmetric causality results show that the positive shocks of export quality causes positive shocks of CO2 emissions in Thailand and Indonesia. Furthermore, we found that positive export quality shocks cause negative CO2 emissions shocks in India while negative export quality shocks cause positive CO2 emissions shocks in China. We also confirm the inverted U-shaped EKC hypothesis in China and Thailand.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2023Towards A Political Economy of Renewable Energy: Does Democracy and Globalization Matter for Central and Eastern European Countries (CEECs); [W kierunku ekonomii politycznej energii odnawialnej: czy demokracja i globalizacja mają znaczenie dla krajów Europy Środkowej i Wschodniej (CEEC)]
Cengiz, Orhan; Manga, Müge
Renewable energy policy is one of the remarkable parts of the sustainable development path. However, the polit-ical-economic dimension of renewable energy policies is not so much widely discussed. Besides, democracy and globalization are essential factors affecting renewable energy. Hence, this paper examines the relationship between renewable energy consumption, democracy, and globalization in the Central and Eastern European Countries (CEECs) during the period 1995-2021. Economic growth and CO2 emissions are used as control variables in the model. The study employs the panel vector autoregressive (PVAR) estimation technique to quantify the relation-ship between renewable energy consumption, democracy, and globalization by including economic growth and CO2 emissions. The findings from the PVAR analysis suggest that participatory democracy and globalization pos-itively affect renewable energy consumption, while liberal democracy, economic growth, and CO2 emissions have a negative impact on it. Furthermore, the PVAR Granger causality test outcomes indicate an interactive causal relationship between variables.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2023Revealing the trend and change point in Hargreaves equation based on potential evapotranspiration values with various statistical approaches
Katipoğlu, Okan Mert
Hotter and drier weather conditions due to climate change negatively affect water resources and agricultural production. For this reason, it is vital to analyze the change in potential evapotranspiration (PET) values, which is one of the most important parameters related to plant growth and agricultural irrigation planning. This study analyses the trends and changes in monthly and annual PET values between 1965 and 2018 at Erzincan, Bayburt and Gümüşhane meteorological stations in Turkey. For this purpose, monotonic trends in PET values were determined by Spearman’s rho (SR), Mann–Kendall (MK), Şen slope (SS), and innovative trend analysis (ITA) tests and change points were analyzed with the sequential MK (SQMK) test. The Hargreaves equation was used to calculate the PET values. As a result of the study, according to MK and SR tests, while increasing trends at 95% and 99% significance levels were dominant at Erzincan and Bayburt stations, no statistically significant trends were found at Gümüşhane station except in February. ITA generally detected more than 5% increasing trends in PET data’s low, medium, and high values. According to ITA slope analysis, there are significant increase trends in PET values at all periods, trend 1% significance level. According to the SQMK test, it was revealed that the trend started in PET values, especially in 1995, 2005, and 2010. The findings emphasized the importance of taking measures against decreased agricultural production and managing water resources effectively.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2023Suitable habitat prediction with a huge set of variables on some Central Asian tulips
Davron, Dekhkonov; Temur, Asatulloev; Umida, Tojiboeva; Sari, Idris; Komiljon, Tojibaev Sh.
Tulipa (Liliaceae) is cultivated as an ornamental plant worldwide and its wild representatives hold valuable genetic resources for breeders are facing the effects of climate change in Central Asia like all of wild plant species. Therefore, the effects of climate change on two Central Asian species (T. korolkowii Regel and T. lehmanniana Mercklin) plus the current suitable habitat for two endemics (T. intermedia Tojibaev and J.J. de Groot, T. scharipovii Tojibaev) to Uzbekistan and one endemic (T. ferganica Vved.) to Ferghana Valley were investigated in the study. Because endemic species are valuable for any territory, we cannot trust a limited number of variables that are commonly used for modeling distribution of species. For that, 41 bioclimatic and ecologic variables were utilized in the investigation. The results showed that T. lehmanniana is a species most affected by climate change, while T. korolkowii appears low necessity for its conservation action. Tulipa ferganica mainly grows in some protected areas of Kyrgyzstan which cannot provide protection against climate change and this may help to mitigate its extinction caused by human-driven disturbance. Thus, the conservation implications of these results are discussed.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2023Effects of hydrogen addition on combustion and flame propagation characteristics of laser ignited methane/air mixtures
Yilmaz, Harun; Schröder, Lukas; Hillenbrand, Thomas; Brüggemann, Dieter
In this study, effects of hydrogen addition on combustion and flame propagation characteristics of methane/air mixtures were investigated in a constant volume combustion chamber. Tested gas mixtures are 100% CH4, 05% H2 – 95% CH4, 10% H2 – 90% CH4 and 15% H2 – 85% CH4, and such mixtures were ignited using a passively Q-switched Nd:YAG laser ignitor which has a pulse energy of 12.3 mJ, pulse duration of 2.4 ns and wave length of 1064 nm. A Schlieren setup coupled with a high-speed camera enabled evaluating flame propagation behavior, while pressure curve analysis provided necessary data for characterization of combustion properties. Additionally, lean flammability limits of gas mixtures were also determined at the test conditions. The unique properties of hydrogen (such as low density, high reactivity, high diffusivity etc) widened lean flammability limit. Rate of pressure rise and measured pressure values increased with hydrogen addition, regardless of the air-fuel equivalence ratio (λ). Lastly, hydrogen addition uniformly affected flame propagation characteristics and flame luminosity. Combustion process became more stable with hydrogen addition.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2023The relationship between FDI, CO2 emissions, and energy consumption in Asia-Pacific economic cooperation countries
Balli, Esra; Sigeze, Ciler; Ugur, Mehmet Sedat; Çatık, Abdurrahman Nazif
This paper investigates the relationship between CO2 emissions, energy consumption, economic growth, and foreign direct investment for a sample of Asia-Pacific Economic Cooperation Countries (APEC) countries from 1981:Q1 to 2021:Q1 employing panel data methodology. We identify cross-sectional dependence and hence utilize the cross-sectional augmented Dickey-Fuller panel unit root test for appropriate estimation. The cointegration test developed by Westerlund (2008) reveals a long-run equilibrium between CO2 emissions, energy consumption, economic growth, and foreign direct investment. Long-run parameter estimates based on Common Correlated Effect Mean Group indicate that an increase in FDI inflows has a negative impact on air quality, supporting the pollution haven hypothesis. The cointegration test results also show that the impact of Gross Domestic Product (GDP) on CO2 emissions varies by country in the estimation sample. In contrast to the mixed evidence on the effects of other variables, the increase in energy consumption is positively and significantly affecting CO2 emissions in all APEC countries. Emirmahmutoglu and Kose Econ Model 28:870-876, (2011)’s panel causality test results show a bidirectional relationship between FDI and CO2 emissions in Japan. Furthermore, there is a bidirectional causal relationship between GDP and energy consumption in Australia, China, Japan, and Singapore. Overall, empirical evidence suggests that APEC countries should adhere to strict regulations and invest in environmental-friendly clean technologies to attract foreign direct investment.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2023Modeling the effect of meteorological variables on streamflow estimation: application of data mining techniques in mixed rainfall–snowmelt regime Munzur River, Türkiye
Katipoğlu, Okan Mert
Revealing the dynamic link between rainfall and runoff, which are the main components of the hydrological cycle, is significant for the planning and managing water resources, disaster risk management, and construction of water structures. This study used feed-forward neural network (FFNN), adaptive neuro-fuzzy inference system (ANFIS), and long short-term memory (LSTM) network to model the rainfall-runoff relationship. Various variations of lagged precipitation, temperature, relative humidity, and flows were presented as inputs, and the flow values of Munzur River were estimated as outputs. During the selection of input parameters, variables with high correlation to flow values were utilized. The model’s success was tested using several statistical indicators, including the coefficient of correlation (R), coefficient of determination (R2), and root mean square error (RMSE). When measuring values and model results are compared, FFNN and ANFIS models show accurate predictive results with high accuracy, while LSTM prediction results are not satisfactory. However, it was concluded that the FFNN model with the hyperbolic tangent sigmoid transfer function and Levenberg-Marquardt training algorithm made a slightly more accurate estimation. In addition, it was revealed that the best ANFIS-Sugeno model was obtained with a hybrid learning algorithm, Gaussmf membership function, and eight subsets. As a result of the analysis, it has been found that FFNN is superior to ANFIS in flow prediction. These results provide policymakers and planners with helpful information for developing flood and drought management strategies.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2023Evaluation of the RF-MEP Method for Merging Multiple Gridded Precipitation Products in the Chongqing City, China
Shi, Yongming; Chen, Cheng; Chen, Jun; Mohammadi, Babak; Cheraghalizadeh, Majid; Abdallah, Mohammed; Mert Katipoğlu, Okan; Li, Haotian; Duan, Zheng
Precipitation is a major component of the water cycle. Accurate and reliable estimation of precipitation is essential for various applications. Generally, there are three main types of precipitation products: satellite based, reanalysis, and ground measurements from rain gauge stations. Each type has its advantages and disadvantages. Recent efforts have been made to develop various merging methods to improve precipitation estimates by combining multiple precipitation products. This study evaluated for the first time the performance of the random forest-based merging procedure (RF-MEP) method in enhancing the accuracy of daily precipitation estimates in Chongqing city, China with a complex terrain and sparse observational data. The RF-MEP method was used to merge three widely used gridded precipitation products (CHIRPS, ERA5-Land, and GPM IMERG) with ground measurements from a limited number of rain gauge stations to produce the merged precipitation dataset. Eight stations (approximately 70% of the available stations) were used to train the RF-MEP approach, while four stations (30%) were used for independent testing. Various statistical metrics were employed to assess the performance of the merged precipitation dataset and the three existing precipitation products against the ground measurements. Our results demonstrated that the RF-MEP approach significantly enhances the accuracy of daily precipitation estimates, surpassing the performance of the individual precipitation products and two other merging methods (the simple linear regression model and the simple averaging). Among the three existing products, ERA5-Land exhibited the best performance in capturing daily precipitation, followed by GPM IMERG, while CHIRPS performed the worst. Regarding precipitation intensity, all three existing products and the RF-MEP merged dataset performed well in capturing light precipitation events with an intensity of less than 1 mm/day, which accounts for the majority (more than 70%) of occurrences. However, all datasets showed rather poor capability in capturing precipitation events beyond 1 mm/day, with the worst performance observed for extreme heavy precipitation events exceeding 50 mm/day. The RF-MEP approach significantly improves the detection ability for all precipitation intensities, except for the most extreme intensity (>50 mm/day), where only marginal improvement is observed. Analysis of the spatial pattern of precipitation estimates and the temporal bias of daily precipitation estimates further confirms the superior performance of the RF-MEP merged precipitation dataset over the three existing products.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2023Militarization of NATO countries sparks climate change? Investigating the moderating role of technological progress and financial development
Pata, Ugur Korkut; Destek, Mehmet Akif; Manga, Muge; Cengiz, Orhan
This study evaluates the effects of military expenditures (MEX) on environmental pollution, as well as the moderating role of factors such as financial development and technological progress for 15 NATO member countries under the environmental Kuznets curve (EKC) hypothesis. Using the CS-ARDL estimator, the study analyzes the effects of MEX, income, energy consumption, financial development, and technical progress on carbon emissions spanning the period from 1991 to 2018. Additionally, interaction terms are employed to regularize the moderating effects of financial development and technical advancement. The results show that income, energy consumption, and MEX all contribute to a rise in emissions. It is also found that the financial sector does not eradicate the detrimental ramifications of MEX on the environment, but that technological progress has a moderating effect. A 1% increase in the interaction of technological progress with the military sector reduces environmental degradation by 0.36, but a 1% augment in the interaction of the financial sector with the military sector increases carbon emissions by 0.41%. For this reason, it is imperative to evaluate and revise the financing of MEX of NATO countries from an environmental perspective for sustainable development. Furthermore, as long-run income elasticity in NATO countries is lower than the short-run one, the EKC hypothesis is valid. Based on the overall findings, the study suggests that NATO allies should incorporate the benefits of income growth and technological development into their environmental policies to offset the negative effects of MEX.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2023Performance based analysis for the Ankara-London route in terms of emissions and fuel consumption of different combinations of aircraft/engine: An IMPACT application
Ekici, Selcuk; Ayar, Murat; Kilic, Ugur; Karakoc, T. Hikmet
This study analyzes two types of aircraft offered to the industry by two different manufacturers on an identical route and trajectory for commercial aviation and the noxious emissions resulting from equipping these aircraft with the most frequently used engine combinations today. The research covers the most recent Base of Aircraft Data (BADA v4.2_1), the Aircraft Noise and Performance (ANP v2.3), and the ICAO Engine Emission Database (254-ICAO EDDB25/FOCA) based integrated aircraft noise and emissions modelling platform (IMPACT) developed by EUROCONTROL. The striking findings in fuel consumption and emissions of four different scenarios during identical flight operations are detailed. The research presents the application of a systematic aircraft-engine pair decision mechanism for investigators, scientists, airline operators, policy analysts and legislators, in accordance with a comprehensive computer simulation method that consistently acknowledges the fuel consumption and emissions analysis of aircraft-engine parings.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2023Mechanical, durability and microstructural characteristics of Portland pozzolan cement (PPC) produced with high volume pumice: Green, cleaner and sustainable cement development
Ulusu, Hayati; Yılmaz Aruntaş, Hüseyin; Burcu Gültekin, Arzuhan; Dayı, Mustafa; Çavuş, Murat; Kaplan, Gokhan
Nowadays, it is frequently preferred to use pozzolans instead of clinker to reduce the CO2 emissions that increase with cement production. Because in the future, the release of artificial pozzolans, such as fly ash and blast furnace slag, will decrease. Therefore, the demand for natural pozzolanic cement will increase. This study aimed to produce Portland Pozzolan Cement (PPC) by using pumice instead of clinker up to 40%. The Chemical, physical, mechanical, durability, microstructure, and carbon footprint characteristics of PPCs were investigated experimentally. As the pumice volume in the PPCs increased, the CaO/SiO2 ratio and specific gravity decreased. Due to the hygroscopic moisture of the pumice, its grindability has become difficult. While the 40 µm sieve residue of PPCs ranges from 0.8 to 1.7%, the sieve residue ratio generally increases as the pumice volume increases. The porous structure of pumice led to an increase in Blaine fineness as the replacement ratio increased. The Blaine fineness of PPCs containing 40% pumice rose by about 20% more than the reference cement. The consistency water of PCs varies between 29 and 36%. As the water consistency increased, the setting time of the pastes was prolonged. Initial setting times of PPCs are between 150 and 220 min. If the CaO/SiO2 ratio decreased with the pumice volume, the compression strength of the mortars decreased. While the 28-day compression strength of PPC containing 10% pumice was measured as 36.2 MPa, this value was measured as 21.6 MPa for PPC containing 40% pumice. As the pumice volume increased, the mortars' drying shrinkage and sulfate-induced expansion values decreased significantly. According to the sustainability analysis, the CO2 emissions of cement vary between 518 and 880 kg CO2/t. By using pumice instead of clinker, CO2 emissions of cement can be reduced. In SEM examinations, it was determined that pumice concentrated the microstructure. As a result, it has been determined that eco-friendly cement can be obtained by using 10% and 20% pumice in PPC production.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2023Monthly streamflow prediction in Amasya, Türkiye, using an integrated approach of a feedforward backpropagation neural network and discrete wavelet transform
Katipoğlu, Okan Mert
Due to climate change and increasing demand for water, effective planning of water resources is a current issue. Reliable and accurate streamflow prediction is of great importance in the planning of water resources. This study aimed to predict monthly streamflows in Amasya by combining a discrete wavelet transform and a feedforward backpropagation neural network (FFBPNN) model. Various meteorological variables were separated into sub signals with mother wavelets commonly used in hydrometeorological studies, such as Haar, Daubechies 2, Daubechies 4, Discrete Meyer, Coiflet 3, Coiflet 5, Symlet 3, and Symlet 5, and entered into the FFBBNN model to create a hybrid wavelet-based FFBBNN model. Inputs with a significant relationship with the output were entered into the model. Precipitation, temperature, and previous streamflow values covering 1960–2011 were used to create the model. During the modeling phase, 70% of the data were divided into training, 15% into validation, and 15% into testing. The performance of the model was compared using mean square error, correlation coefficient, and rank analysis. Coiflet 5 mother wavelet showed the best results. Moreover, it was proven that monthly streamflow can be successfully predicted using previous precipitation, temperature, and streamflow values and the Coiflet 5 mother wavelet with the FFBBNN hybrid model (MSE: 7.143, R: 0.921). In addition, all built wavelet FFBPNN models except the Symlet 3 mother wavelet performed better than the single FFBPNN model. The results of the study will assist planners, and decision makers in terms of providing sustainable and effective water resources and drought management.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2023Hydrological Drought Prediction Based on Hybrid Extreme Learning Machine: Wadi Mina Basin Case Study, Algeria
Achite, Mohammed; Katipoğlu, Okan Mert; Jehanzaib, Muhammad; Elshaboury, Nehal; Kartal, Veysi; Ali, Shoaib
Drought is one of the most severe climatic calamities, affecting many aspects of the environment and human existence. Effective planning and decision making in disaster-prone areas require accurate and reliable drought predictions globally. The selection of an effective forecasting model is still challenging due to the lack of information on model performance, even though data-driven models have been widely employed to anticipate droughts. Therefore, this study investigated the application of simple extreme learning machine (ELM) and wavelet-based ELM (W-ELM) algorithms in drought forecasting. Standardized runoff index was used to model hydrological drought at different timescales (1-, 3-, 6-, 9-, and 12-month) at five Wadi Mina Basin (Algeria) hydrological stations. A partial autocorrelation function was adopted to select lagged input combinations for drought prediction. The results suggested that both algorithms predict hydrological drought well. Still, the performance of W-ELM remained superior at most of the hydrological stations with an average coefficient of determination = 0.74, root mean square error = 0.36, and mean absolute error = 0.43. It was also observed that the performance of the models in predicting drought at the 12-month timescale was higher than at the 1-month timescale. The proposed hybrid approach combined ELM’s fast-learning ability and discrete wavelet transform’s ability to decompose into different frequency bands, producing promising outputs in hydrological droughts. The findings indicated that the W-ELM model can be used for reliable drought predictions in Algeria.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2023Implementation of hybrid wind speed prediction model based on different data mining and signal processing approaches
Katipoğlu, Okan Mert
Accurate estimation of wind speed (WS) data, which greatly influences meteorological parameters, plays a vital role in the safe operation and optimization of the power system and water resource management. The study’s main aim is to combine artificial intelligence and signal decomposition techniques to improve WS prediction accuracy. Feed-forward back propagation neural network (FFBNN), support vector machine (SVM) and Gaussian processes regression (GPR) models, discrete wavelet transform (DWT), and empirical mode decomposition (EMD) were used to forecast the WS values 1 month ahead in Burdur meteorology station. Statistical criteria such as Willmott’s index of agreement, mean bias error, mean squared error, determination coefficient, Taylor diagram and regression analysis, and graphical indicators were used to evaluate the prediction success of the models. As a result of the study, it was determined that both wavelet transform and EMD signal processing increased the WS prediction performance of the stand-alone ML model. The best performance was obtained with the hybrid EMD-Matern 5/2 kernel GPR with test (R2:0.802) and validation (R2:0.606). The most successful model structure was obtained using input variables with a delay of up to 3 months. The study’s results contribute to wind energy-related institutions in terms of practical use, planning, and management of wind energy.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2023Evaluation of Tree-Based Machine Learning and Deep Learning Techniques in Temperature-Based Potential Evapotranspiration Prediction
Akar, Funda; Katipoğlu, Okan Mert; Yeşilyurt, Sefa Nur; Han Taş, Mehmet Bilge
In this study, Extreme Gradient Boosting (XGBoost), Gradient Boosting Machine (GBM), Random Forest (RF), Bagged Trees (BT), and Custom Deep Learning methods were used to estimate the potential evapotranspiration (PET) values at Diyarbakir airport station in the Tigris basin. In establishing the models, the average temperature, maximum temperature, minimum temperature, maximum wind speed, relative humidity, average wind speed, and total precipitation values in the monthly time period were chosen as inputs, and PET values were used as output. The data set is divided into 70% training and 30% testing. 10-fold cross-validation to avoid overfitting problems. Training and test data were randomly selected. The prediction performances of the models were evaluated according to the statistical criteria of determination coefficient (R2), root mean square error (RMSE), mean absolute error (MAE), and rank analysis. The best PET estimates were obtained using the inputs of mean, min, maximum temperature, relative humidity, total precipitation, average, and maximum wind speed. It was also concluded that XGBoost was the highest performance. When the R2 values were examined, it was seen that the Deep Learning model had higher performance. But for RMSE and MAE, XGBoost did better. As a result of the rank analysis, it was seen that XGBoost got a higher score.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2023Comparison of the SPI and SPEI as drought assessment tools in a semi-arid region: case of the Wadi Mekerra basin (northwest of Algeria)
Berhail, Sabri; Katipoğlu, Okan Mert
The current research intends to compare the agreement level between the Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI), the former’s variant, at different timescales such as 1, 3, 6, 9, 12, and 24 months. This data was compiled from the Mekerra basin with the help of time series of rainfall and temperature data for 42 years from 1970 to 2011. The authors used Cohen’s kappa statistics and the Bland–Altman method to determine the test of agreement between SPI and SPEI. Furthermore, the innovative trend analysis (ITA) method was also employed to analyze the severe and extreme dry trends. The outcomes achieved from the Cohen’s kappa statistic revealed the presence of a significant level of agreement between the SPI and SPEI values across the timescales. Furthermore, the researchers observed a positive linear correlation (r > 0.75, p < 0.0001) between the ratings under study. The existence of a small mean difference between the Bland and Altman analyses confirmed the level of agreement between the analytical tools under consideration. In addition to these, the outcomes also infer that in case of the unavailability of the temperature data to conduct the SPEI. Therefore, it is acceptable to use the SPI as the current study found the presence of an acceptable degree of agreement between these two scales in the study location. The present study suggests utilizing various types of drought indices to evaluate the drought performance in a specific location or geographical area to make knowledge-driven decisions.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2023Spatiotemporal detection of abrupt change in trends of rainfall and dry and wet periods at different time scales: The case of the Medjerda basin in northeast Algeria
Berhail, Sabri; Katipoğlu, Okan Mert
This study investigates possible rainfall and drought trends using data from 38 rainfall stations in the Medjerda basin (northeast of Algeria) over 54 years (1965–2018). Drought-related data were calculated with the Standardized precipitation index (SPI). The Mann–Kendall test was used to find positive or negative precipitation trends. The magnitude of these trends was calculated using Sen’s slope method. According to the analysis, a decrease during the spring precipitation season was observed. Furthermore, the authors found the maximum increasing (decreasing) precipitation magnitude to be 2.14 mm/season (− 4.41 mm/season) in winter (spring). In addition, the magnitude of the precipitation trend per year ranged from − 6.26 to 2.54 mm/year, with an average reduction of 39% for the entire basin. From the outcomes of drought trend analysis, it can be inferred that for a short-time scale, the innovative trend analysis method exhibited a negative trend for the minimum and maximum SPI values. Drought severity was found to have increased during severe and extreme wet episodes, directly affecting Algeria’s frequently drought-affected agricultural regions, such as the Merdja plain and the irrigated perimeters of Sedrata and Zouabi. Considering the long-time scales, an increase was detected in drought severity and a decline during severe and extreme wet episodes. These findings show that the southeastern and central parts of the Medjerda basin’s long-term water resources have been severely affected, which negatively impacts the newly-constructed Ouldjet Mellegue dam in Tébessa province.
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