SDG 13 · İklim Eylemi · SDG · Erzincan Binali Yıldırım Üniversitesi

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ArticleAçık Erişim2023/r/ebyu/12679
Performance Evaluation of Five Machine Learning Algorithms for Estimating Reference Evapotranspiration in an Arid Climate
Raza, Ali; Fahmeed, Romana; Syed, Neyha Rubab; Katipoğlu, Okan Mert; Zubair, Muhammad; Alshehri, Fahad; Elbeltagi, Ahmed
The Food and Agriculture Organization recommends that the Penman–Monteith Method contains Equation 56 (PMF) as a widely accepted standard for reference evapotranspiration (ETo) calculation. Despite this, the PMF cannot be employed when meteorological variables are constrained; therefore, alternative models for ETo estimation requiring fewer variables must be chosen, which means that they perform at least as well as, if not better than, the PMF in terms of accuracy and efficiency. This study evaluated five machine learning (ML) algorithms to estimate ETo and compared their results with the standardized PMF. For this purpose, ML models were trained using monthly time series climatic data. The created ML models underwent testing to determine ETo under varying meteorological input combinations. The results of ML models were compared to assess their accuracy and validate their performance using several statistical indicators, errors (root-mean-square (RMSE), mean absolute error (MAE)), model efficiency (NSE), and determination coefficient (R2). The process of evaluating ML models involved the utilization of radar charts, Smith graphs, heatmaps, and bullet charts. Based on our findings, satisfactory results have been obtained using RBFFNN based on M12 input combinations (mean temperature (Tmean), mean relative humidity (RHmean), sunshine hours (Sh)) for ETo estimation. The RBFFNN model exhibited the most precise estimation as RMSE obtained values of 0.30 and 0.22 during the training and testing phases, respectively. In addition, during training and testing, the MAE values for this model were recorded as 0.15 and 0.17, respectively. The highest R2 and NSE values were noted as 0.98 and 0.99 for the RBFNN during performance analysis, respectively. The scatter plots and spatial variations of the RBFNN and PMF in the studied region indicated that the RBFNN had the highest efficacy (R2, NSE) and lowest errors (RMSE, MAE) as compared with the other four ML models. Overall, our study highlights the potential of ML models for ETo estimation in the arid region (Jacobabad), providing vital insights for improving water resource management, helping climate change research, and optimizing irrigation scheduling for optimal agricultural water usage in the region.
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ArticleYalnız künye2023/r/ebyu/12649
Modeling of meteorological, agricultural, and hydrological droughts in semi-arid environments with various machine learning and discrete wavelet transform
Achite, Mohammed; Katipoglu, Okan Mert; Şenocak, Serkan; Elshaboury, Nehal; Bazrafshan, Ommolbanin; Dalkılıç, Hüseyin Yıldırım
Recent meteorological, hydrological, and agricultural droughts in the Mediterranean regions have raised concerns about the impact of climate change. In this study, the meteorological, agricultural, and hydrological droughts were modeled in the Wadi Ouahrane Basin using various machine learning (ML) models and standardized indices of rainfall, evapotranspiration, and runoff (SPI, SPEI, and SRI) at different times scales (1, 3, 6, 9, 12, and 24 months). The applied ML models were the linear support vector machine (SVM), quadratic SVM, cubic SVM, fine gaussian SVM, medium gaussian SVM, coarse Gaussian SVM, rational quadratic Gaussian process regression (GPR), squared exponential GPR, Matern 5/2 GPR, exponential GPR, bagged tree, and boosted tree. Moreover, the hybrid models acquired by combining these ML models with wavelet transform were evaluated. The performance of the models was analyzed using statistical criteria such as root mean square error, determination coefficient, and mean absolute error. As a result, wavelet-GPR models showed the most promising results in estimating SPI, SPEI, and SRI values. The values for SPI (R 2 of train: 0.393; and test: 0.351), SPEI (R 2 of train: 0.809; test: 0.746), and SRI (R 2 of train: 0.999; test: 0.808) indicate monthly time scale. Additionally, for the time periods of 3, 6, 9, 12, and 24 months, the predictions for SPI, SPEI, and SRI generally obtain R 2 of train 0.99 and test 0.95 values. Moreover, it was determined that wavelet-based ML models, established with inputs divided into three subcomponents with Daubechies mother wavelet, showed superior results than standalone ML models. The study results could guide decision-makers and planners in developing drought risk management and mitigation strategies.
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ArticleYalnız künye2023/r/ebyu/12523
Evaluation of the performance of data-driven approaches for filling monthly precipitation gaps in a semi-arid climate conditions
Katipoğlu, Okan Mert
Missing data cause problems in meteorological, hydrological, and climate analysis. The observation data should be complete and cover long periods to make the research more accurate and reliable. Artificial intelligence techniques have attracted interest for completing incomplete meteorological data in recent years. In this study the abilities of machine learning models, artificial neural networks, the nonlinear autoregressive with exogenous input (NARX) model, support vector regression, Gaussian processes regression, boosted tree, bagged tree (BAT), and linear regression to fill in missing precipitation data were investigated. In developing the machine learning model, 70% of the dataset was used for training, 15% for testing, and 15% for validation. The Bayburt, Tercan, and Zara precipitation stations, which are closest to the Erzincan station and have the highest correlation coefficients, were used to fill the data gaps. The accuracy of the constructed models was tested using various statistical criteria, such as root-mean-square error (RMSE), mean absolute error (MAE), Nash–Sutcliffe model efficiency coefficient (NSE), and determination coefficient (R2) and graphical approaches such as scattering, box plots, violin plots, and Taylor diagrams. Based on the comparison of model results, it was concluded that the BAT model with R2: 0.79 and NSE: 0.79 and error (RMSE: 11.42, and MAE: 7.93) was the most successful in the completion of missing monthly precipitation data. The contribution of this research is assist in the choice of the best and most accurate method for estimating precipitation data in semi-arid regions like Erzincan.
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ArticleAçık Erişim2023/r/ebyu/12470
Daily global solar radiation time series prediction using variational mode decomposition combined with multi-functional recurrent fuzzy neural network and quantile regression forests algorithm
Abdallah, Mohammed; Mohammadi, Babak; Nasiri, Hamid; Katipoğlu, Okan Mert; Abdalla, Modawy Adam Ali; Ebadzadeh, Mohammad Mehdi
Global solar radiation (GSR) prediction capability with a reliable model and high accuracy is crucial for comprehending hydrological and meteorological systems. It is vital for the production of renewable and clean energy. This research aims to evaluate the performance of combined variational mode decomposition (VMD) with a multi-functional recurrent fuzzy neural network (MFRFNN) and quantile regression forests (QRF) models for GSR prediction in daily scales. The hybrid VMD-MFRFNN and QRF models were compared with standalone MFRFNN, random forest (RF), extreme gradient boosting (XGB), and M5 tree (M5T) models across the Lund and Växjö meteorological stations in Sweden. The meteorological data from 2008 to 2017 were used to train the models, while the prediction accuracy was verified by using the data from 2018 to 2021 under five different input combinations. The various meteorological-based scenarios (including the input are air temperatures (Tmin, Tmax, T), wind speed (WS), relative humidity (RH), sunshine duration (SSH), and maximum possible sunshine duration (N)) were considered as input of predictor models. The current study resulted that the M5T model exhibited higher accuracy than RF and XGB models, while the QRF model showed equivalent performance with the M5T model at both study sites. The MFRFNN model outperformed QRF and M5T models across all input combinations at both study sites. The hybrid VMD-MFRFNN model showed the best performance when fewer input variables (Tmin, Tmax, T, WS at Lund station and Tmin, Tmax, T, WS, SSH, RH at Växjö station) were used for GSR prediction. We conclude that the MFRFNN model best predicts average daily GSR when combining all meteorological variables (Tmin, Tmax, T, WS, SSH, RH, N).
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ArticleAçık Erişim2023/r/ebyu/12415
Renewable Energy Consumption Convergence in G-7 Countries
Helmi, Mohamad Husam; Çatık, Abdurrahman Nazif; Coşkun, Nuran; Ballı, Esra; Sigeze, Çiler
This study examines the convergence of renewable energy consumption in G-7 countries. We employ LM unit root and RALS version of LM unit root tests with endogenously determined with structural one or two breaks. Despite the increase in renewable energy consumption in G-7 countries, it is important to identify whether renewable energy consumption converges across these countries to formulate appropriate policies to support sustainable energy consumption and reduce CO2 emissions. Our analysis indicated that Germany, Italy, and Canada exhibit evidence of convergence. However, after employing both the LM and RALS versions of the LM unit root tests, which consider level shifts with one or two breaks or trend shifts with one or two breaks, we found that there is no evidence of convergence for France, Japan, and the United Kingdom. Overall, our results highlight the importance of formulating country-specific policies to support renewable energy consumption and reduce CO2 emissions. Policymakers need to identify the drivers of renewable energy consumption and adopt appropriate measures to ensure that the countries can meet their climate goals while also ensuring energy security.
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ArticleAçık Erişim2023/r/ebyu/12394
Simulation of the Potential Impacts of Projected Climate and Land Use Change on Runoff under CMIP6 Scenarios
Haider, Saif; Masood, Muhammad Umer; Rashid, Muhammad; Alshehri, Fahad; Pande, Chaitanya B.; Katipoğlu, Okan Mert; Costache, Romulus
Assessing the impacts of climate change and land use/land cover changes on water resources within a catchment is essential because it helps us understand how these dynamic factors affect the quantity, quality, and availability of freshwater. This knowledge is crucial for making informed decisions about water management, conservation, and adaptation strategies, especially in regions facing increasing environmental uncertainties and challenges to water resource sustainability. In Pakistan’s Kunhar River Basin (KRB), this investigation explores the potential effects of shifting land use/land cover (LULC), and climate on stream flows. The SWAT (Soil and Water Assessment Tool), a semi-distributed hydrological model, and the most recent Coupled Model Intercomparison Project phase 6 (CMIP6) dataset from multiple global climate models (GCMs) were used to evaluate these effects. The temperature and precipitation data were downscaled using the CMhyd software; for both shared socioeconomic pathways (SSP2 and SSP5), the top-performing GCM out of four was required to produce downscaled precipitation and temperature predictions while taking future land use characteristics into account. The output from the chosen GCM indicated that by the conclusion of the 21st century, relative to the reference period (1985–2014), the study area’s average monthly precipitation, highest temperature, and lowest temperature will be increasing. Precipitation is anticipated to increase between 2015 and 2100 by 20.5% and 29.1% according to the SSP2 and SSP5 scenarios, respectively. This study’s findings, which emphasize the need for project planners and managers taking into account the effects of climate and land cover changes in their management techniques, show that climate change can have a significant impact on the changing seasons of flows in the Kunhar River basin.
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ArticleAçık Erişim2023/r/ebyu/12339
Time-varying impact of income and fossil fuel consumption on CO2 emissions in India
Ugur, Mehmet Sedat; Çatık, Abdurrahman Nazif; Sigeze, Ciler; Balli, Esra
This paper investigates the time-varying effects of fossil fuel consumption on CO2 emissions in India utilizing the time-varying cointegration test, allowing for multivariate long-run time-varying cointegration parameter developed by Bierens and Martins (2010) and the time-varying vector autoregressive (TVP-VAR) model developed by Primiceri (2005). The long-run time-varying coefficients reveal that GDP has a positive and increasing impact on CO2 emissions over time. Moreover, results confirm the polluting effects of all fossil fuels. Besides, the TVP-VAR model findings also demonstrate that changes in income and fossil fuel consumption have a positive and significant impact on environmental degradation. Coal is found to be the most polluting fuel, followed by oil consumption. Furthermore, the time-varying responses show that increased natural gas consumption has the least influence when compared to other fossil fuels on CO2 emissions.
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ArticleAçık Erişim2022/r/ebyu/20650
Ön Karışımlı Bir Yanma Odasında Farklı Kaya Gazlarının Deneysel Olarak İncelenmesi
Taştan, Murat; Çetintaş, Serdar
Dünyada küresel iklim değişikliliğinin negatif sonuçları gün geçtikçe artmıştır. Bu sebeple insanların daha az emisyon üreten yakıtlara yönelmesi gerektiği ortaya çıkmıştır. Sunulan çalışmanın amacı; kaya gazı bileşenlerinin emisyon özellikleri ve sıcaklık dağılımı üzerindeki etkisini belirlemektir. Bu çalışmada, farklı CH4/ C3H8 / CO2 /N2 içeriklerine sahip kaya gazı karışımlarının yanma ve emisyon davranışları deneysel olarak incelenmiştir. 4 kW ısıl güç ve 0,7 eşdeğerlik oranı ile dört farklı girdap değeri (0.2/0.6/1.0/1,4) kullanılarak emisyon ve sıcaklık ölçümleri incelenmiştir. Deneyde 6 farklı kaya gazı karışımı kullanılmıştır. Bu çalışma sonucunda kaya gazlarının içeriğine bağlı olarak emisyon değerlerinin büyük farklılıklar gösterdiği görülmüştür. Tüm kaya gazlarının metandan daha fazla NOx, CO ve CO2 değeri oluşturduğu gözlemlenmiştir. Kaya gazı karışımındaki C3H8 değeri NOx değerinde, eksenel sıcaklık dağılımında ve baca gazı sıcaklığında artışa neden olmuştur. CO2 oranındaki artışla CO değeri artarken NO, eksenel sıcaklık ve baca gazı sıcaklık değerleri azalmıştır.
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ArticleAçık Erişim2022/r/ebyu/20608
Dicle Havzasındaki Bazı İstasyonlara ait Potansiyel Evapotranspirasyon Verilerinin Trend Analizi
Katipoğlu, Okan Mert
Potansiyel evapotranspirasyon (PET) değerlerindeki eğilimlerin belirlenmesi, iklim değişikliği ve kuraklık yönetimi, tarımsal su kaynaklarının daha verimli yönetimi ve sulama planlamasının optimal tasarımı konuları açısından büyük öneme sahiptir. Bu çalışmada Dicle havzasında bulunan Batman, Cizre, Diyarbakır ve Hakkâri meteoroloji istasyonları için, 1964-2017 yılları arasında hesaplanan mevsimsel ve yıllık PET değerlerinin trend analizleri gerçekleştirilmiştir. Trendlerin belirlenmesinde Şen in Yenilikçi Trend Analizi (ITA) ve Mann-Kendall Mertebe Korelasyon (MKMK) metotları kullanılmıştır. PET değerlerinin hesaplanmasında sıklıkla kullanılan, basit ve az veri gerektiren Thornthwaite metodolojisi tercih edilmiştir. Araştırma sonunda ITA yöntemine göre, havzada seçilen istasyonların PET verilerinde genelde istatistik açıdan anlamlı artış trendleri hakimken, Diyarbakır istasyonu için ilkbahar ve kış mevsimlerinde istatistik açıdan anlamlı azalan trendler tespit edilmiştir. MKMK testine göre, kış mevsimi dışında istasyon konumlarında PET değerlerinde anlamlı artışlar vardır. Ayrıca ITA ve MKMK testleri büyük ölçüde örtüşmekle birlikte bazı istasyonlarda ITA ile tespit edilen artış trendleri MKMK testi ile saptanamamıştır. Elde edilen sonuçlar tarımsal su kaynaklarının planlanması ve verimli bir şekilde kullanılmasında, küresel ısınmanın etkileriyle mücadele etmek için adaptasyon ve azaltma stratejileri geliştirilmesinde karar vericilere önemli bilgi temin etmektedir.
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ArticleAçık Erişim2022/r/ebyu/20596
Evaluation of Irreversibility Analysis for Different Coal Types of a Thermal Power Plant
Uzun, Sinem
In this study, first law (energy conservation) and second law (exergy) analyzes of thermodynamics were performed for a thermal power plant. It is very important to perform energy and exergy analyzes in industrial plants. These analyzes can provide guidance on improving energy efficiency and recycling waste energy. In this study, energy and exergy analyzes were made for coals with different chemical contents in nine different countries. According to the results of the analysis, the highest first-law efficiency was found in Serbian coal (second type), as 53.61%. The second highest law efficiency was determined as 46.67% in Bangladesh coal (sixth type). Environmental Destruction Index (EDI) and Sustainability Index (SI) values were determined for all coal types. According to the results of the analysis, the highest EDI value was obtained as 4.00 at the temperature of 305 K for the 2nd coal type, and the highest SI value was obtained as 1.91 at the temperature of 293 K for the 6th coal type, according to the changing reference temperature values. According to this study, the highest second law efficiency was obtained from Bangladesh coal with a carbon (C) content of 77.84%.
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ArticleAçık Erişim2022/r/ebyu/20541
Determination of Carbon Footprint with IPCC Tier 1 and DEFRA Methods: The Case Study of Erzincan Binali Yıldırım University
Seyhan, Aslıhan Kurnuç; Çerçi, Muhammed
In this study, the carbon footprint of Erzincan Binali Yıldırım University for 2019 and 2020 was calculated first with the IPCC Tier 1 approach and then using the DEFRA conversion factors. The primary carbon footprint of EBYU has been calculated as 2753,2 tCO2e for 2019 and 2383,74 tCO2e for 2020, with the IPCC Methodology Tier 1 approach. Compared to 2019, there is a 13,42% decrease in the amount of emissions. With DEFRA conversion factors, 2314,53 tCO2e emissions for 2019 and 1826,54 tCO2e emissions for 2020 were calculated. Compared to 2019, there is a 21,08% decrease in the amount of emissions. This difference between the IPCC Tier 1 approach and DEFRA is due to the fact that the emission factors used in the IPCC Tier 1 approach calculations are general and DEFRA uses national data from the UK. It is thought that the decrease in carbon dioxide emissions is due to the mild climate in 2020 compared to 2019 and, as well as the doing online education in 2020 due to the Covid-19 pandemic process.
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ArticleAçık Erişim2022/r/ebyu/20399
Monthly stream flows estimation in the karasu river of euphrates basin with artificial neural networks approach
Katipoğlu, Okan Mert
This study aims to estimate streamflow values with artificial neural networks (ANN) using various meteorological parameters. In developing the ANN model, various combinations of precipitation, air temperatures, and potential evapotranspiration values were used as inputs, and streamflow values were obtained. Meteorological data is divided into 70% train, 15% test, and 15% validation. In the model's design, various training algorithms, network architecture, input combinations, and the number of iterations were tried, and the most suitable model was tested. Correlation coefficient (R), coefficient of determination (R2), absolute error (AE), and absolute relative error (ARE) coefficients were compared, and the most suitable model was selected. According to the analysis results, the optimal model was obtained using 2000 iterations, the architecture of the 4-4-1 model, and the Quasi-Newton algorithm. It was determined that the ANNs successfully modeled the rainfall-runoff relationship and produced reliable estimates. In addition, it was revealed that the inclusion of potential evapotranspiration values obtained by the Thornthwaite method into the model increases the model's success.
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ArticleAçık Erişim2022/r/ebyu/18402
IS THERE ANY RELATIONSHIP BETWEEN GEOPOLITICAL RISK AND CLIMATE CHANGE?
Cengiz, Orhan; Manga, Muge
Purpose: The aim of this study is to point out the impact of geopolitical risk on climate change. The CO2 emissions per capita is used as a proxy for climate change. Methodology: In this study, the data sample covers annual data from 1990 to 2015 for 12 selected Latin American and Asian countries. After standard preliminary tests (Cross-sectional dependence tests, CIPS unit root test, and slope homogeneity test), we employ the second-generation estimator - the AMG (Augmented Mean Group) method to explore the long-run relationship between geopolitical risk and CO2 emissions per capita. Results: The AMG findings document that a 1% rise in geopolitical risk escalates CO2 emissions per capita by 0.001%. In addition, economic growth and fossil energy consumption foster CO2 emissions per capita, whereas renewable energy contributes to decreasing CO2 emissions per capita. Conclusion: In recent years, scholars have attempted to explore the impact of geopolitical risk on environmental degradation. According to our results, in Latin American and Asian countries, decreasing geopolitical risk and conflict can impede environmental degradation. In the long run, a robust clean energy policy should be considered in case of geopolitical conflict by the government. Besides, the government should focus on renewable energy policy and substitute non-renewable energy resources with more technology-intensive resources.
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ArticleAçık Erişim2022/r/ebyu/18318
Energy and Exergy Analysis of Solar Collectors Having Different Tilt Angles: Case Study of Erzincan City
Kaba, Muhammet Yasin; Kurnuc Seyhan, Aslihan; Celen, Pinar; Celen, Ali
Solar collectors are frequently used in domestic water heating applications. In the design stage, the positioning of solar collector with suitable title angle is important in order to utilize from sun energy efficiently. In this study, the effect of tilt angle of a solar collector located to Erzincan city on monthly/daily average radiation values, water outlet temperature, energy and exergy efficiencies are theoretically investigated. It is seen that the maximum and minimum values of optimum tilt angles are 63 degrees ve 0 degrees for December and June, respectively. Tilt angles which are suggested for Erzincan (27.14 degrees) and calculated are compared for daily average hourly radiation values and it is seen that the maximum variation is 26% for January. In addition, energy and exergy efficiencies of solar collector are estimated and the maximum efficiencies are determined as 74.2% ve 9.7% for optimum tilt angles.
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ArticleYalnız künye2022/r/ebyu/13987
Investigating the potential of renewable energy in establishing global peace: Fresh evidence from top energy consumer countries
Destek, Mehmet Akif; Manga, Müge; Cengiz, Orhan; Destek, Gamze
Although the socio-economic determinants of terrorism are conducted by many researchers using different samples and time spans, the impact of renewable energy consumption on terrorism has been ignored for a long time. To bridge the gap, this paper aims to investigate the impact of renewable energy consumption on terrorism regarding economic growth, non-renewable energy consumption, and income inequality over the period straddling 1990 and 2019 for a panel of the USA, China, India, Iran, Germany, and Russia. We employ the CUP-FM and CUP-BC estimators to reveal the long-run relationship between variables. The empirical findings suggest that renewable energy consumption has a negative impact on terrorism. A 1% increase in renewable energy consumption decreases terrorism by 0.315% and 0.631%, according to the CUP-FM and CUP-BC estimators, respectively. Economic growth also has a negative impact on terrorism, whereas non-renewable energy consumption and income inequality positively affect terrorism. Our empirical findings highlighted that renewable energy consumption and economic growth are crucial for combating terrorism in these countries. Therefore, these countries need to improve comprehensive policies in terms of renewable energy consumption and simultaneously decrease non-renewable energy consumption and income inequality.
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ArticleYalnız künye2022/r/ebyu/13897
EXERGY ANALYSIS AND DETERMINATION OF IRREVERSIBILTY OF A THERMAL POWER PLANT
Ata, İsmail; Tanürün, H. Erdi; Uzun, Sinem; Bayrak, Sebile; Acır, Adem
The exergy analysis and determination of irreversibility İ of a thermal power plant with 210 MW are presented in this study. The first- (ηI) and second-law (ηII) efficiencies, losses, and İ are computed for each component in the plant. The highest energy loss (43.538%) occurs with heat transfer to cooling water of the condenser, whereas the second loss (14.138%) occurs in the boiler. The highest İ value in the cycle (86.87%) occurs in the boiler followed by the turbine (5.95%). The ηI and ηII efficiencies of the whole plant are 38.64% and 31.68%, respectively. In addition, effects of the efficiencies in the temperature range from 5°C to 30°C are investigated. The ηI efficiency of the whole plant does not change, whereas the ηII efficiency decreases with increasing reference temperatures. In addition, the ηII efficiency is associated with environmental impact and sustainability.
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ArticleYalnız künye2022/r/ebyu/13886
The omnidirectional runway with infinite heading as a futuristic runway concept for future free route airspace operations
Aydoğan, Emre; Demirel, Soner
Purpose: The purpose of this paper is to create and analyze the effectiveness of a new runway system, which is totally created for the future free route operations. Design/methodology/approach: This paper researches and analyses the new generated runway concept with the fast time simulation method. Fuel consumption and environmental effect of the new runway system are calculated based on simulation results. Findings: According to different traffic density analyses the Omnidirectional Runway with Infinite Heading (ORIH) reduced fuel consumption and CO2 emissions up to 46.97%. Also the total emissions of the ORIH concept, for the hydro carbon (HC), carbon monoxide (CO) and nitrogen oxides (NOx) pollutants were lower than the total emissions with the conventional runway up to 83.13, 74.36 and 51.49%, respectively. Practical implications: Free route airspaces bring many advantages to air traffic management and airline operations. Direct routes become available from airport to airport thanks to free route airspace concept. However, conventional single runway structure does not allow aircraft operations for every direction. The landing and take-off operations of a conventional airport with a single runway must be executed with only two heading direction. This limitation brings a bottleneck direct approach and departure route usage as convenient with free route airspace concept. This paper suggests and analyzes the omnidirectional runway with infinite heading (ORIH) as a solution for free route airspace. Originality/value: This paper suggests a new and futuristic runway design and operation for the free route operations. This paper has its originality from the suggested and newly created runway system.
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ArticleYalnız künye2022/r/ebyu/13866
Analyzing 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.
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ArticleAçık Erişim2022/r/ebyu/13824
Investigation of the effect of building-based assessment on flood hazard evaluation
Kurt, Zeynep Ö.; Kankal, Murat; Yüksek, Ömer
The aim of this study is to investigate the effect of building-based assessment on flood hazards. Değirmendere, which is one of the most important basins of the Eastern Black Sea Region of Turkey, was selected as the study area. Flood hazards for discharge values with different return periods of this region were found using; the damage percentages table recommended by the Huntington Civil Engineers Association (HCEA), the Van Eck and Kok depth-loss curves, and the equation obtained by Pistrika and Jonkman. The calculations were performed both for building-based and for the region-based and compared. Furthermore, the damage rates obtained for each building on a building-based were graded and shown on the map. It was determined that the damage on individual building-based estimation for Q1,000 calculated more than to the one on region-based 154% and 17% for the damage percentages table recommended by the HCEA, Van Eck and Kok depth-loss curves, respectively. Otherwise, it gave 11% less damage estimation for the equation obtained by Pistrika and Jonkman. Furthermore, it was concluded that the increase in damage from Q50 to Q100, from Q100 to Q500, and from Q500 to Q1,000 was between 16%-30% according to building-based damage estimation.
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ArticleYalnız künye2022/r/ebyu/13703
Combustion and emission characteristics of premixed biogas mixtures: An experimental study
Sivri, Ilker; Yilmaz, Harun; Cam, Omer; Yilmaz, Ilker
In this study, effects of fuel composition, swirl number and hydrogen addition on combustion and emission characteristics of various biogas mixtures were experimentally investigated. To this end, a laboratory scale combustor and a swirl stabilized premixed burner were designed and manufactured. Later on, this combusting apparatus was equipped with flow, control, safety and measurement tools, hence entire test system was constituted. Combustion and emission characteristics of tested biogas mixtures were determined by measuring temperature and species (CO2, CO, O2 and NO) distributions throughout the combustion chamber. Additionally, flame structures of tested biogas mixtures were evaluated by examining flame luminosity, visible flame length and flame thickness from instantaneous flame images. Results of this study showed that both radial and axial temperature distribution variations of tested biogas mixtures differently alter with hydrogen addition based on the gas composition. Although flame temperature increases with swirl number at burner outlet, it presents a non-monotonous dependence on swirl number outside the flame region because of the modified flow characteristics. This is also the case for emissions of CO2.
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