Büyükyıldız, Meral
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Buyukyildiz, Meral Buyukyildiz, M. Büyükyıldız, M. Buyukyıldız, Meral
Job Title
Email Address
mbuyukyildiz@ktun.edu.tr
Main Affiliation
02.02. Department of Civil Engineering
Status
Current Staff
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ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
Research Topics
Domains
Physical Sciences
Fields
Environmental Science
Subfields
Global and Planetary ChangeWater Science and TechnologyEnvironmental Engineering
Specific Research Areas
Hydrology and Drought Analysis
Hydrology and Watershed Management Studies
Hydrological Forecasting Using AI
Climate variability and models
Flood Risk Assessment and Management
Sustainable Development Goals
1NO POVERTY
0
Research Products
2ZERO HUNGER
8
Research Products
3GOOD HEALTH AND WELL-BEING
0
Research Products
4QUALITY EDUCATION
0
Research Products
5GENDER EQUALITY
0
Research Products
6CLEAN WATER AND SANITATION
12
Research Products
7AFFORDABLE AND CLEAN ENERGY
1
Research Products
8DECENT WORK AND ECONOMIC GROWTH
1
Research Products
9INDUSTRY, INNOVATION AND INFRASTRUCTURE
2
Research Products
10REDUCED INEQUALITIES
0
Research Products
11SUSTAINABLE CITIES AND COMMUNITIES
7
Research Products
12RESPONSIBLE CONSUMPTION AND PRODUCTION
0
Research Products
13CLIMATE ACTION
18
Research Products
14LIFE BELOW WATER
1
Research Products
15LIFE ON LAND
1
Research Products
16PEACE, JUSTICE AND STRONG INSTITUTIONS
0
Research Products
17PARTNERSHIPS FOR THE GOALS
1
Research Products
Documents
19
Citations
463
h-index
10
This researcher does not have a WoS ID.
Publication Collaboration
| Affiliation Name | Count |
|---|---|
| Konya Technical University | 23 |
| Selçuk University | 4 |
| Necmettin Erbakan University | 2 |
| Istanbul Technical University | 2 |
| Shanghai Institute for Science of Science | 1 |
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Data obtained from OpenAlex
Scholarly Output
64
Articles
24
Views / Downloads
194/502
Supervised MSc Theses
6
Supervised PhD Theses
1
WoS Citation Count
177
Scopus Citation Count
176
Patents
0
Projects
0
WoS Citations per Publication
2.77
Scopus Citations per Publication
2.75
Open Access Source
42
Supervised Theses
7
| Journal | Count |
|---|---|
| Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi | 3 |
| Water Supply | 2 |
| European Journal of Science and Technology | 1 |
| Journal of Water and Climate Change | 1 |
| Konya Journal of Engineering Sciences | 1 |
Current Page: 1 / 5
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64 results
Scholarly Output Search Results
Now showing 1 - 10 of 64
Conference Object Assessment of Concentration, Erosivity and Seasonality of Precipitation Data for 1970-2019 Period of Karataş Gauging Station(2021) Köyceğiz, Cihangir; Büyükyıldız, MeralTemporal and spatial variations in precipitation as a result of the effects of climate change generally cause a flood, drought, soil erosion, etc. events to occur. For this reason, determining the precipitation variability in a region is quite important in protecting soil and water resources and in struggling soil erosion. This study aims to examine the monthly and annual variation of precipitation, annual and seasonal precipitation concentration (APCI and SPCI), annual and seasonal precipitation erosivity (AMFI) and SMFI, and seasonality of precipitation (SI) of the Karataş meteorological station in the Seyhan Basin for the period 1970-2019. In addition, the change of these parameters in the examined period was examined using the Mann-Kendall (MK) trend test. According to the results obtained, generally irregular and strong irregular precipitation distribution was obtained in the APCI values calculated for the Karataş station. According to SPCI analysis, SPCIWinter values are uniform and moderate, SPCISpring values are moderate, SPCISummer values are strongly irregular, and SPCIAutumn values have moderate precipitation distribution. According to the AMFI values calculated to examine the precipitation erosivity, it was determined that the precipitation generally constitutes a high (34%) and a quite high (40%) erosion risk. According to seasonal MFI analysis results, SMFIWinter values generally show a high and very high erosion risk, SMFISpring and SMFISummer values show no or very low erosion risk, and SMFIAutumn values show moderate, high and very high (about 62%) erosion risk. According to the SI analysis results of the 50-year study period, about half of the SI values represent significant seasonal precipitation with a long dry season. The Mann-Kendall trend results of monthly total precipitation, annual total precipitation, APCI, SPCI, AMFI, SMFI and SI values show that there are no significant trends for the 1970-2019 period.Article Citation - WoS: 2Citation - Scopus: 1Evaluation of Runoff Simulation Using the Global Brook90-R Model for Three Sub-Basins in Turkiye(MDPI, 2023-03-14) Ülker, Muhammet Cafer; Büyükyıldız, MeralThe use of physically based hydrological models in the observation of hydrological processes has some disadvantages as well as advantages. One of these disadvantages is the large supply of data pertaining to the study area that is required for the model to be run. However, the ability to run the Global BROOK90 R (GB90-R) model for any location and period has made a significant contribution to the science of hydrology. In this study, the GB90-R model was established in three different basins (carsamba, Karasu, and Korkun) in Turkiye with different drainage areas and climates, and the flow forecasting performance was comprehensively evaluated. In addition, the evaporation, ground moisture, and snowmelt outputs obtained were examined comparatively. According to the results, Karasu Basin, with the smallest drainage area, was the basin with the highest model success in flow estimation with NSE = 0.670, while Korkun Basin, with the largest drainage area, was the basin with the lowest model success with NSE = 0.337. It is thought that the increase in the drainage area is one of the important factors reducing the success of the model.Book Part Performance Analysis of Metaheuristic Optimization Algorithms for a Real Water Distribution Network(Eğitim Yayınevi, 2024) Yılmaz, Volkan; Büyükyıldız, Meral; Baykan, Ömer Kaan; Kamanlı, MehmetConference Object Temporal Trends of Annual and Seasonal Precipitation Concentration Index(2021) Köyceğiz, Cihangir; Büyükyıldız, MeralGlobal warming and climate change have significant effects on precipitation regimes. As a result, natural disasters such as drought and flood occur in our country as in many parts of the world. As a consequence of climate change, a significant portion of the total annual precipitation falling in an area can fall in just a few days, causing rainfall erosivity and flooding in the relevant areas. These climatic events cause loss of life and property in various regions, but also cause negative effects on agriculture and water resources. Climate change and global warming also cause a great decrease in water resources. The decrease in water resources reaches dimensions that prevent sustainable life as well as environmental impact. Global warming, which directly and indirectly affects water resources, increases the importance of water and water resources day by day. Precipitation, which is one of the meteorological events most affected by climate change, has the most important role in recharging water resources. In this study, monthly total precipitation data for the period 1970-2019 of Adana station (Station No: 17351) located in the Seyhan Basin were used. Firstly, the precipitation concentration index values of the precipitation data used were calculated on the seasonal and annual scales. In addition, the temporal trend of both monthly and annual precipitation and the calculated annual and seasonal precipitation concentration index values of the precipitation data in the examined period were examined. The temporal variation of monthly and annual precipitation values and annual and seasonal precipitation concentration index values were assigned using the Mann-Kendall trend method. The obtained trend analysis results were evaluated at the 95% significance level. The calculated annual precipitation concentration index values show 28% moderate, 56% irregular and 16% strong irregular precipitation distribution. While an insignificant increase was obtained in the annual precipitation concentration index values calculated in the examined time period, insignificant negative trends were obtained in the seasonal precipitation concentration index values of the four seasons.Conference Object Identifying the Meteorological Drought Characteristics of Sinop and Giresun Meteorological Stations With the Rainfall Anomaly Index(2023) Köyceğiz, Cihangir; Büyükyıldız, MeralDrought is one of the most important disasters that develop under different meteorological and environmental conditions, with the greatest impact on life and economy among other natural disasters. Various drought indices are used to determine more or less severe periods of climatic events. Rainfall Anomaly Index (RAI) is one of the widely used drought indices in the evaluation of meteorological droughts. In this study, it is aimed to examine the temporal characteristics of meteorological droughts of Sinop meteorological station in the Western Black Sea Basin and Giresun meteorological station in the Eastern Black Sea Basin for the period 1940-2021 (82 years) using RAI. According to the annual RAI values obtained for the studied period, both Sinop and Giresun stations have a rainy season with 32.93% and 32.94% in 27 years, respectively. In Sinop station, there is a dry season in 35 years with a rate of 42.69% and in Giresun station in 40 years with a rate of 48.78%. Sinop and Giresun stations are dominated by a near-normal season with 24.39% and 18.29% in 20 and 15 years, respectively. According to the RAI values obtained, the extremely dry year was experienced in 1986 with an RAI value of -5 for Sinop station and in 2010 with an RAI value of 4.27 for Giresun station.Article Citation - WoS: 48Citation - Scopus: 55Calibration of Swat and Two Data-Driven Models for a Data-Scarce Mountainous Headwater in Semi-Arid Konya Closed Basin(MDPI, 2019-01-16) Köyceğiz, Cihangir; Büyükyıldız, MeralHydrologic models are important tools for the successful management of water resources. In this study, a semi-distributed soil and water assessment tool (SWAT) model is used to simulate streamflow at the headwater of Caramba River, located at the Konya Closed Basin, Turkey. For that, first a sequential uncertainty fitting-2 (SUFI-2) algorithm is employed to calibrate the SWAT model. The SWAT model results are also compared with the results of the radial-based neural network (RBNN) and support vector machines (SVM). The SWAT model performed well at the calibration stage i.e., determination coefficient (R-2) = 0.787 and Nash-Sutcliffe efficiency coefficient (NSE) = 0.779, and relatively lower values at the validation stage i.e., R-2 = 0.508 and NSE = 0.502. Besides, the data-driven models were more successful than the SWAT model. Obviously, the physically-based SWAT model offers significant advantages such as performing a spatial analysis of the results, creating a streamflow model taking into account the environmental impacts. Also, we show that SWAT offers the ability to produce consistent solutions under varying scenarios whereas it requires a large number of inputs as compared to the data-driven models.Conference Object Characterizatıon and Temporal Variation Analysis of Precipitation in Mardin Province(2022) Köyceğiz, Cihangir; Büyükyıldız, MeralClimate change caused by the effect of global warming is increasing its impact all over the world day by day and poses serious threats to the ecosystem. With the effect of climate change, there are significant regional differences, especially in the precipitation parameter. Extreme increases and decreases in precipitation cause drought and flood events to occur more frequently. Various precipitation indices are used to examine the effect of climate change on precipitation, which is one of the most important parameters of the hydrological cycle. In this study, the variability of Mardin province precipitation, which is located within the borders of the Euphrates-Tigris Basin, which is one of the twenty-five river basins of Turkey and one of the most important transboundary basins of the Middle East, has been examined. For this purpose, precipitation data of the Mardin meteorological station numbered 17275, operated by the Turkish State Meteorological Service, in the 1941-2020 (80 years) period were used. The characterization of precipitation in Mardin province was evaluated by calculating Precipitation Concentration Index (PCI) and Rainfall Anomaly Index (RAI). According to the annual PCI values obtained for the examined period, it was determined that the precipitations in the province of Mardin, which is located in the drier lower part of the basin, generally have an irregular and strong irregular distribution. According to the RAI values obtained for the 80-year period, there is a rainy period in 30 years (37.5%), a dry period in 35 years (43.75%), and a near-normal period in 15 years (18.75%). Dry periods were observed more frequently in the last 30 years of the examined period.Conference Object Homogeneity and Trend Analysis of Some Meteorological Data of Karataş Station in Seyhan Basin(Niğde Ömer Halisdemir Üniversity, 2022) Yılmaz, Sümeyye; Büyükyıldız, Meral: In this study, maximum-minimum-average temperature, maximumminimum-average relative humidity and total-maximum precipitation data covering the years 1965-2016 belonging to Karataş meteorological observation station numbered 17981 in the Seyhan Basin, one of the important basins of Turkey, were used. These data were subjected to homogeneity tests (Pettit Test, Standard Normal Homogeneity Test, Buishand Rank Test, Von Neumann Rank Test) and trend analyzes (Mann Kendall, Sen Innovative Trend Test and Mann Kendall Rank Correlation Test). The results obtained by homogeneity and trend tests were evaluated at the 95% confidence level. According to the results of the 4 homogeneity tests used, Ptotal, Pmax and RHmax parameters are homogeneous and the other parameters are not homogeneous. According to the results obtained, there was a significant increase in Tmin and Tmean, and a significant decrease trend in RHmin and RHmax. The trends obtained in other parameters are not statistically significant.Master Thesis Fiziksel Tabanlı Global Brook90-r Hidrolojik Modelinin Türkiye'de Bazı Nehir Havzalarında Uygulanabilirliği: Akım Tahmin Çalışması(Konya Teknik Üniversitesi, 2022) Ülker, Muhammet Cafer; Büyükyıldız, MeralHidrolojik modellerin kullanımı havzalarda hidrolojik sürecin anlaşılması, hidrolik/hidrolojik değişenlerin tahmin edilmesi, su kaynakları üzerinde iklim değişikliği etkilerinin ortaya konulması, gelecek iklim projeksiyonlarının oluşturulması ve su yönetim stratejilerinin belirlenmesi açısından oldukça önemlidir. Bu çalışmada Türkiye'de ilk kez kullanılan fiziksel tabanlı Global BROOK90-R (GB90-R) hidrolojik modeli aylık akım miktarlarını tahmin etmek için Çarşamba Çayı, Karasu Çayı ve Körkün Çayı Havzalarına kurulmuştur. Modele girdi olarak meteorolojik (yağış, sıcaklık, rüzgar ve radyasyon) ve fiziksel (sayısal yükseklik haritası, arazi örtüsü ve toprak haritaları) veriler girilmiştir. Model, Çarşamba Çayı Havzası için 1977-2016, Karasu Çayı Havzası için 1979-2020 ve Körkün Çayı Havzası için 1992-2017 periyodunda çalıştırılmıştır. Her bir havza için elde edilen model sonuçlarının başarısı determinasyon katsayısı (R2), Nash-Sutcliffe verimlilik katsayısı (NSE), Kling-Gupta verimlilik katsayısı (KGE) ve bias yüzdesi (PBias) metrikleri kullanılarak değerlendirilmiştir. Elde edilen sonuçlara göre GB90-R modeli ile aylık akım tahmininde en yüksek başarı NSE=0.570 değeri ile Karasu Çayı Havzası için elde edilmiştir. Modelin aylık akım tahmininde Çarşamba Çayı Havzasında (NSE=0.521 değeri ile) elde ettiği başarı ise Karasu Çayı'nda elde edilen başarıya oldukça yakındır. GB90-R modeli ile aylık akım tahmininde en düşük performans NSE=0.337 değerine sahip Körkün Çayı Havzasında elde edilmiştir. Çalışmada ayrıca GB90-R modelinin akım dışındaki diğer çıktıları olan evaporasyon (EVPP), toprak nemi (SWATT) ve kar (SNOW) her üç havza için su bütçesi açısından değerlendirilmiştir. GB90-R modelinin en önemli avantajı, girdi olarak sadece havza konumunu talep ederken çıktı olarak detaylı hidrolojik parametreler sunmasıdır.Article Citation - WoS: 5Citation - Scopus: 5Performance of Data-Driven Models Based on Seasonal-Trend Decomposition for Streamflow Forecasting in Different Climate Regions of Türkiye(Pergamon-Elsevier Science Ltd, 2024-12-01) Yılmaz, Volkan; Koyceğiz, Cihangir; Buyukyıldız, MeralThis study examines the ability of different methods such as machine learning, ensemble models, and meta- heuristic algorithms to predict streamflow. For this purpose, five different methods were used: Artificial Neural Networks (ANN), Support Vector Machines (SVM), Adaptive Boosting, Particle Swarm Optimization (PSO), and BSPSO hybridized with Band Similarity (BS), a relatively new method. Additionally, the impact of seasonality and trend components obtained through Seasonal-Trend decomposition using LOESS (locally weighted regression and scatterplot smoothing) (STL) data decomposition technique on prediction success was investigated. Models were developed in three basins with three different climate characteristics: continental, temperate, and arid. The results showed higher prediction success in input structures including seasonality and trend components. While higher prediction successes were achieved at Karasu in the continental climate class and Kork & uuml;n in the temperate climate class, model performances were lower at K & uuml;& ccedil;& uuml;k Muhsine in the arid climate class. While the most successful modeling for K & uuml;& ccedil;& uuml;k Muhsine (NSE = 0.696) and Karasu stations (NSE = 0.811) was obtained with the BSPSO method, the SVM method produced the best results for Kork & uuml;n station (NSE = 0.818). Moreover, BSPSO models outperformed the prediction successes obtained by using PSO alone for each scenario at all three stations. The percentages of the BSPSO method improving the prediction success according to the NSE metric ranged from 3.53% to 17.40% at K & uuml;& ccedil;& uuml;k Muhsine, 0.49%-3.72% at Karasu, and 1.24%-7.24% at Kork & uuml;n. The competitive results achieved by the BSPSO approach compared to ANN and SVM in flow prediction constitute the innovative aspect of this study.