Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Conference Object Assessment of Drought in Izmir District Using Standardized Precipitation Index(Springer Nature, 2025) Mersin, D.; Gulmez, A.; Safari, M.J.S.; Vaheddoost, B.; Tayfur, G.One of the main issues with agro-food and socio-economical security in the world is droughts. Regardless of cause or effect, the ever-changing climate is placing increasing strain on water resources pushing supply to its limits. Izmir, a growing city in Turkey, is endowed with variety of water resources, such as lakes, rivers, seashores, and groundwater reserves. Therefore, it is crucial for the planning and development of the area to examine past and foreseeable drought occurrences and their possible impact on water resources. In this regard, the study’s goal is to assess historical droughts in Izmir District. Data from three meteorological stations in Küçük Menderes basin, collected between 1973 and 2020, are utilized in this study. To establish the validity of the posterior drought analysis, the consistency and trend in the time series are first examined using the double mass curve, run test, and linear trend analysis. The next step is to assess the historical deficit related to meteorological, agricultural, and hydrological droughts using the SPI and moving mean (MA) operator. The temporal analysis of SPI reveals distinct drought patterns across the stations, with multiple moderate to extreme droughts occurring particularly between 1998 and 2010, highlighting significant spatial and temporal variability in drought severity and frequency. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.Conference Object Application of Artificial Neural Network for Predicting Peak Discharge From Breached Embankment Dam(International Association for Hydro-Environment Engineering and Research (IAHR), 2024) Okan, M.; Bor, A.; Tayfur, G.Estimation of peak discharge is a key parameter for risk assessment in case of dam failure, and has attracted great attention from researchers in recent years. Many formulas are available in the literature, but these cannot cover all experimental scenarios. Existing models are typically inadequate to address the complexities of dam breaches. This research attempted to predict the peak discharge in the breached embankments with an artificial neural network (ANN) model, which is effective in nonlinear problems, using datasets obtained from various dam breaches cited in the literature. The ANN model is useful in the preparation of emergency action plans since it enables prediction of peak discharge. Multilayer Perceptron (MLP) with Levenberg-Marquardt (LM) and Bayesian Regularization (BR) algorithms was used to predict peak discharges from breached embankments. The dataset was divided into three: 56% for training, 20% for validation and 24% for testing. Different scenarios were created using different input combinations. Performance evaluation was based on the root-mean squared error (RMSE), percent bias (PBIAS), determination of coefficient (R2), Nash-Sutcliffe efficiency (NSE) and RMSE-observations standard deviation ratio (RSR). A comparison of training algorithms revealed that LM showed the best performance when the best ANN was selected from 1000 networks. Volume of water above the breach bottom (Vw) had a greater effect on model performance than the depth of water above the breach bottom (Hw). The best performance was obtained when both Vw and Hw were used as input. © 2024 ISHS. All Rights Reserved.Erratum Correction To: Assessing the Spatial and Temporal Characteristics of Meteorological Drought in Afghanistan (Pure and Applied Geophysics, (2024), 10.1007/S00024-024-03578-x)(Birkhauser, 2025) Tayfur, G.; Hayat, E.; Safari, M.J.S.Correct affiliations of Mir Jafar Sadegh Safari should only include the following: Department of Geography and Environmental Studies, Toronto Metropolitan University, Toronto, Ontario, Canada Department of Civil Engineering, Yaşar University, Izmir, Turkey Department of Geography and Environmental Studies, Toronto Metropolitan University, Toronto, Ontario, Canada Department of Civil Engineering, Yaşar University, Izmir, Turkey The original article has been corrected. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.Article Citation - WoS: 3Citation - Scopus: 2Assessing the Spatial and Temporal Characteristics of Meteorological Drought in Afghanistan(Birkhauser, 2025) Tayfur, G.; Hayat, E.; Safari, M.J.S.Afghanistan is suffering from periodic events of drought, which has exacerbated in recent years due to extreme climate events in the region. Having an arid to semi-arid climate, the country faces significant challenges of water resources management, especially for irrigation as reliance on agriculture is cumbersome. This study is undertaken to characterize historical meteorological drought in Afghanistan to provide an insight on where and when meteorological drought events happened in different River Basins (RBs). The study mainly employs the gamma-Standardized Precipitation Index (gamma-SPI) to analyze historical meteorological droughts across Afghanistan from 1979 to 2019. Monthly precipitation data is obtained from the Ministry of Energy and Water (MEW) of Afghanistan, which is a combination of observed data from ground stations and gap-filled data by the MEW for the study period. Gridded gamma-SPI values are interpolated and mapped to visualize patterns of spatial drought across the entire country. The results indicate that countrywide extreme drought events occurred in 1999, 2000, 2001, 2010, 2016, 2017, and 2019, particularly affecting southern, western, and southwestern regions. Decreasing rainfall occurred in all five RBs, with the most considerable decline observed in the 1999–2008 period. The study reveals the increasing frequency and severity of meteorological droughts in Afghanistan. It also emphasizes on the vulnerability of agriculture and water sectors due to the drought events. The findings of the study suggest the need for better drought monitoring, preparedness, awareness, and adaptation of strategies to ensure water security and agricultural sustainability in the face of climate change. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.Article Citation - WoS: 1Citation - Scopus: 1Identification of Flood Hazard Zones in Afghanistan Using Gis and Multi-Criteria Decision Approach(Inderscience Publishers, 2024) Tani, H.; Tayfur, G.This study assessed Afghanistan’s potential flood hazard zones using the geographic information systems (GIS) and the analytical hierarchy process (AHP). Six different thematic layers were selected, and the AHP was applied to estimate the influence weights of each parameter. The final flood hazard zones map (FHZM) was reclassified into five zones. Sensitivity analysis was employed to create the flood hazard sensitivity map (FHSM) based on ‘effective weights’. It was found that the land use land cover (LULC) and rainfall are less sensitive compared to the other parameters. The FHZM and FHSM comparatively indicate the same regions regarding flood hazard levels. The methodology was tested against the recorded flood events in the region. The results showed that about 44% of the study area is under low and very low flood hazards, whereas 56% is subjected to high and very high. Low-lying areas are highly prone to flooding. Copyright © 2024 Inderscience Enterprises Ltd.Conference Object Overtopping Failure of a Homogeneous Earth-Fill Dam With Two Different Breach Sizes and Rough Downstream Conditions(Crc Press-balkema, 2024) Taskaya, E.; Buyuker, Z.; Ozturk, B.; Bombar, G.; Tayfur, G.In this experimental study, sediment movement as a result of the failure of homogeneous earth-fill dams was investigated for rough downstream conditions compared with two different breach sizes. The dam body with 2.02 m width, 10 cm crest width, 60 cm height, and 32 degrees upstream and downstream slope was constructed with material with a median grain diameter of D-50 = 0.441 mm in a rectangular reinforced concrete channel with a width of 2 m. In the top middle of the dam body for the overtopping scenario, a 5 cm and 25 cm deep breach was triggered for experiments. The roughness downstream of the dam was created by placing 13 concrete cubes of 10x10x10 cm at regular intervals. The most obvious difference between the experimental results is that the sediment thickness propagated along the downstream is in the experiment where the depth of the breach is high.Article Citation - WoS: 22Citation - Scopus: 26Fuzzy Logic for Rainfall-Runoff Modelling Considering Soil Moisture(Kluwer Academic Publishers, 2015) Tayfur, G.; Brocca, L.This study developed Mamdani-type fuzzy logic model to simulate daily discharge as a function of soil moisture measured at three different depths (10, 20 and 40 cm) and rainfall. The model was applied to 13 km2 size Colorso Basin in central Italy for a period from October 2002 to April 2004. For each variable of soil moisture, rainfall, and discharge, 9 fuzzy subsets were employed while 30 fuzzy rules, relating the input variables (soil moisture and rainfall) to the output variable (discharge), were optimized. The model employed the min inferencing, max composition, and the centroid method. The model application results revealed that Mamdani-type fuzzy logic model can be employed to incorporate soil moisture along with rainfall to simulate discharge. Using soil moisture measured at 40 cm soil depth along with rainfall produced better simulation of discharge with NS=0.68 and R= 0.82. The performance of the model was also tested against a conceptual rainfall- runoff model of MISDc (Modello Idrologico Semi-Distribuito in continuo). MISDc couples an event-specific component with a module for continuous time soil water balance for taking into account the variable antecedent wetness conditions. The MISDc model requires estimation of seven parameters and the measurements of the hydrometeorological variables such as rainfall and air temperature. The comparative study revealed that fuzzy model performs better in capturing runoff peak rates and overall trend of high and small flooding events. © Springer Science+Business Media Dordrecht 2015.