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    Analyzing land use and climate change impacts of Suğla water storage in Turkey
    (Springer Wien, 2024) Ciftci, Hasan Cagatay; Gumus, Kutalmis; Gumus, Munevver Gizem
    Large water masses affect the land use of their surroundings and change the regional climate. Many methods are used to determine changes in regional climate and land use. This study aims to investigate the impact of the Su & gbreve;la water storage site in Turkey on land use and climate before and after 2006, the year the site became operational. The effects of the Su & gbreve;la water storage site on the climate and land use of the region were investigated using trend analyses, Autoregressive Integrated Moving Averages (ARIMA) models, and remote sensing techniques. For these purposes, increasing or decreasing trends in the meteorological time series covering the years 1960-2020 obtained from four meteorological stations in this region were determined by trend analysis. ARIMA models, a time series estimation and forecasting method, were used to make predictions for the next 10-year period (2020-2030) for meteorological data. With remote sensing techniques, changes in land use were determined using Landsat satellite images from 1984, 1990, 2000, 2006, 2010, 2020 and 2022. As a result of the study, increasing and decreasing trends were detected in trend analysis and ARIMA forecasts at all stations. It was observed that the water bodies have increased by 1% since 2006, when the site started to hold water, and there has been a significant increase from forest and semi-natural areas to agricultural areas. These results show that the land use around the Su & gbreve;la water storage area has changed significantly, with agricultural areas expanding.
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    Forecasting future scenarios of coastline changes in Turkiye's Seyhan Basin: a comparative analysis of statistical methods and Kalman Filtering (2033-2043)
    (Springer Heidelberg, 2024) Gumus, Munevver Gizem
    Complex changes in coastlines are increasing with climate, sea level, and human impacts. Remote Sensing (RS) and Geographic Information Systems (GIS) provide critical information to rapidly and precisely monitor environmental changes in coastal areas and to understand and respond to environmental, economic, and social impacts. This study aimed to determine the temporal changes in the coastline of the Seyhan Basin, Turkiye, using Landsat satellite images from 1985 to 2023 on the Google Earth Engine (GEE) platform. The approximately 50 km of coastline was divided into three regions and analyzed using various statistical techniques with the Digital Shoreline Analysis System (DSAS) tool. In Zone 1, the maximum coastal accretion was 1382.39 m (Net Shoreline Movement, NSM) and 1430.63 m (Shoreline Change Envelope, SCE), while the maximum retreat was -76.43 m (NSM). Zone 2 showed low retreat and accretion rates, with maximum retreat at -2.39 m/year (End Point Rate, EPR) and -2.45 m/year (Linear Regression Rate, LRR), and maximum accretion at 0.99 m/year (EPR) and 0.89 m/year (LRR). Significant changes were observed at the mouth of the Seyhan delta in Zone 3. According to the NSM method, the maximum accretion was 1337.72 m, and maximum retreat was 1301.4 m; the SCE method showed a maximum retreat of 1453.65 m. EPR and LRR methods also indicated high retreat and accretion rates. Statistical differences between the methods were assessed using the Kruskal-Wallis H test and ANOVA test. Generally, NSM and EPR methods provided similar results, while other methods varied by region. Additionally, the Kalman filtering model was used to predict the coastline for 2033 and 2043, identifying areas vulnerable to future changes. Comparisons were made to determine the performance of Kalman filtering. In the 10-year and 20-year future forecasts for determining the coastline for the years 2033 and 2043 with the Kalman filtering model, it was determined that the excessive prediction time negatively affected the performance in determining the coastal boundary changes.