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- MakaleYalnız künye2026Scopus SJRQ2The Trend of Monthly Mean Streamflow Values and Regimes in the Susurluk Basin (Türkiye) with Mountain and Semi-Arid Climates
Yıldız, Mehmet Berkant; Toğrul, Burçe; Kankal, Murat; Akçay, Fatma; Şan, Murat; Nacar, Sinan
This study diagnoses monthly trends in streamflow magnitude and regime for the Susurluk Basin (Türkiye), which spans semi-arid and mountainous sub-climates. Monthly records from 1990 to 2019 were analyzed at 14 stream gauges and nine precipitation stations. Trends are assessed with the Mann–Kendall (MK) test alongside recent graphical approaches, Improved Visualization for Innovative Trend Analyses (IV-ITA) to resolve value class-based (low/high) behavior, and Innovative Polygon Trend Analysis (IPTA) with the Star Concept to quantify intra-annual transitions. Before the trend analyses, the stations were tested to determine whether their values were homogeneous, and any inhomogeneous stations were excluded from the study. The consistency between the trends of nine precipitation stations and the streamflow data in the basin was analyzed. Across the basin, the average streamflow increased by approximately 40–60% between January and March at many measurement points. However, it then decreased by around 80% in April, albeit at a more moderate rate in December. This suggests significant rebalancing occurred during the December–April period, when most of the annual streamflow occurs. IV-ITA exhibits broadly similar trends for both low and high streamflow classes, with notable exceptions in January–February. Precipitation–streamflow trend directions are largely consistent in the high-flow season (December–April), supporting the notion that climatic control influences the detected shifts. To contextualize these signals, basin-wide land-use/land-cover shifts (1990–2018), notably urban growth, forest expansion, and cropland reconfiguration, provide process context, indicating that a larger fraction of rainfall is routed as fast surface runoff while infiltration and base streamflow recharge decline, alongside seasonally modified water demand. Collectively, the MK+IV-ITA+IPTA framework reveals class-specific and intra-annual dynamics that are obscured by monolithic tests alone and provides decision-relevant evidence for allocation, drought–flood risk, and operations in an intensively managed basin.
AtıfScopus2OpenAlex2İncele - MakaleYalnız künye2023Scopus SJRQ1Trend analysis of precipitation using innovative approaches in northwestern Turkey
Körük, Ali Emre; Kankal, Murat; Yıldız, Mehmet Berkant; Akçay, Fatma; Şan, Murat; Nacar, Sinan
Precipitation is highly sensitive to climate change, and monitoring its trends over time is essential for understanding the effects of global warming on the Earth's water cycle. This study investigates the effects of climate change on monthly precipitation in the Susurluk Basin located in northwestern Turkey, using innovative trend analysis methods. Innovative Polygon Trend Analysis (IPTA) using star graphics and Improved Visualization for Innovative Trend Analysis (IV-ITA) techniques were used to analyze precipitation data from nine stations in the basin over 50 years (1970–2019), and the findings were compared to classical Mann-Kendall (MK) results. According to the trend analysis results, the MK method detected significant trends in only two months in the decreasing direction. In these decreasing trends observed at Simav and Keles stations in November, z values were calculated as −2.38 and −2.05, respectively. IPTA method detected increasing trends in 54 months and decreasing trends in 40 months; this means there is a change of more than 5% between two half series. The IV-ITA method indicated an increase of more than 40% in the low values for January, March, August, and September. In addition, there was an increasing trend of more than 40% in the high values observed in September at all stations. It was observed that mean precipitation heights increased from September to December and then decreased throughout the basin. It is predicted that decreases in precipitation during dry seasons may put intense pressure on agricultural water use and affect water quality. In addition, the increase in precipitation in spring months may increase flood events. It was determined that graphical innovative trend analysis methods are more effective in trend identification than MK, and these methods' results have much higher visual inspection and linguistic interpretation possibilities. Innovative methods allow for more flexible and in-depth analysis using different statistical parameters.
AtıfScopus40WoS34OpenAlex43İncele - MakaleYalnız künye2023Scopus SJRQ2Annual Trends of Precipitation and Temperature in the Northwestern Part of Turkey Using Innovative Approaches: A Holistic and Partial Study
Akçay, Fatma; Şan, Murat; Nacar, Sinan; Kankal, Murat
Trend analysis benefits collecting and analyzing reliable data in climate change studies. In this context, long-term temperature and precipitation data analysis, two variables sensitive to climate change, is essential. This study aims to holistically and partially determine the annual trends of precipitation and temperature time series for 1970–2019 at nine selected stations in the Susurluk Basin, Turkey. The innovative trend significance test (ITST), innovative crossing trend analysis (ICTA) method, and Mann-Kendall (MK) test were used to determine holistic trends. Also, partial trends were determined using successive average methodology (SAM). For the precipitation variable, while an increasing trend was determined for the ITST, there was mostly no trend for the other methods. While a strong increasing trend was detected for the temperature according to the ITST and MK methods, no trend was observed in any station according to the ICTA method. According to the SAM results, the maximum trend durations for the peak and trough change points were 4.9 (10.3) and 5.3 (8.4) years, respectively, for precipitation (temperature). The strong temperature trends in the basin will likely continue, requiring precautions against extreme events such as drought.
AtıfScopus16WoS13OpenAlex18İncele