Sürdürülebilir Kalkınma Amaçları
Yazarlar
- Şan, Murat(4)
- Kankal, Murat(3)
- Nacar, Sinan(2)
- Acar, Emine(1)
- Akçay, Fatma(1)
- Bayram, Adem(1)
- Okkan, Umut(1)
Yayınlar
- MakaleYalnız künye2026Scopus SJRQ2Analysis of the Changes in River Water Quality and Quantity with Innovative Trend Methods
Şan, Murat; Nacar, Sinan; Bayram, Adem; Kankal, Murat
This study aims to investigate trends and changes in water quality (WQ) and quantity parameters under low-medium-high groups and seasonal trends employing innovative methods. The data were collected from three monitoring stations in the Broad River Basin (USA). The data spanning the years 1987–2020, on water temperature (WT), dissolved oxygen (DO), discharge (Q), and electrical conductivity (EC) parameters, were used for analysis. A combination of innovative trend analysis with binary segmentation (ITABS) was proposed for objective group separation for the purpose of group trend analysis, allowing for the capture of changes in both location and shape parameters. Recently proposed innovative polygon trend Wilcoxon significance test (IPTWST) and innovative polygon trend analysis (IPTA) were also used to examine seasonal trends for the first time, providing a graphical and qualitative analysis of seasonal behavior. The seasonal Mann-Kendall test was also used to compare them. The ITABS method grouped WQ parameters into more than one group, except for the DO parameter. Especially from EC and Q parameters, it is concluded that the trends in groups do not always contribute to the overall trend or at the same rate. Group trends, therefore, should not be ignored for water resources management. According to IPTA and IPTWST, although there is no clear trend in certain seasons, it is evident that seasonal trends exist, and the Q and EC parameters have a more complex structure. The IPTWST method has the advantage of being able to graphically show the inter-seasonal behavior, although it is identical to the seasonal Mann-Kendall method.
AtıfScopus1WoS1OpenAlex1İncele - MakaleAçık Erişim2025Scopus SJRQ1Combined innovative trend analysis methods for seasonal trend testing
Şan, Murat
While holistic trend identification is essential, it does not consider the periodic, e.g., monthly, trend characteristics needed to identify seasonal trend behavior. Furthermore, identifying seasonal trends can help manage or regulate water resources systems and irrigation and agricultural operations. In this study, the innovative trend significance test (ITST), the revised ITST, and the Wilcoxon signed-rank test, which are non-parametric methods, are proposed as alternative seasonal trend tests by combining them with the innovative polygon trend analysis (IPTA), which provides visual and linguistic examinations of seasonal behaviors. Groundwater level data from the Chilgrove House (United Kingdom), flow data from the Danube River Basin (Romania), precipitation and temperature data from Türkiye were used to compare the proposed methods with the seasonal Mann-Kendall (SMK) method. For temperature and groundwater level data, all methods showed an increasing trend at different confidence intervals, but for other data, trends emerged according to the characteristics of the methods. So, some of the proposed methods are more rigid than the SMK in trend detection, while others are more sensitive. In addition to the advantage of its applications to seasonal trend behaviors, the proposed significance tests are combined with the IPTA method and comparable alternative methods to the SMK. So, seasons with a clear increase or decrease can be seen visually in the proposed combined methods contrary to the SMK method. Thus, both seasonal trend behaviors and inter-seasonal transitions can be examined graphically, and seasonal significance testing can be applied. According to the characteristics of these combined methods, they can be used not only for seasonal trend tests, just like the SMK method, but also for regional trend tests using stations data instead of seasons.
AtıfScopus28WoS25OpenAlex30İncele - MakaleAçık Erişim2024Scopus SJRQ1Trends and amount changes of temperature and precipitation under future projections in high–low groups and intra-period for the Eastern Black Sea, the Wettest Basin in Türkiye
Nacar, Sinan; Şan, Murat; Kankal, Murat; Okkan, Umut
This study investigates the possible effects of climate change on temperature and precipitation variables in the Eastern Black Sea Basin, Türkiye’s wettest and flood-prone region. The outputs of three GCMs under historical, RCP4.5, and RCP8.5 scenarios were downscaled to regional scale using the multivariate adaptive regression splines method. The future monthly temperature and precipitation for 12 stations in the basin were projected for three periods: the 2030s (2021–2050), 2060s (2051–2080), and 2090s (2081–2100). In addition to relative changes, high and low groups and intra-period trends were analyzed for the first time using innovative methods. For the pessimistic scenario, an increase of 3.5 °C in the interior and 3.0 °C in the coastal areas of the basin is projected. For the optimistic scenario, these values are expected to be 2.5 and 2.0 °C, respectively. A decrease in precipitation is projected for the interior region, and a significant increase is expected for the eastern and coastal areas of the basin, especially in spring. This result indicates that floods will occur frequently coastal areas of the basin in the coming periods. Also, although the monotonic trends of temperatures during periods are higher than precipitation in interior regions, these regions may have more uncertainty as their trends are in different directions of low and high groups of different scenarios and GCMs and contribute to all trends, especially precipitation.
AtıfScopus15WoS15OpenAlex13İncele - MakaleAçık Erişim2022Scopus SJRQ1Innovative polygon trend analyses with star graph for rainfall and temperature data in agricultural regions of Turkey
Acar, Emine; Kankal, Murat; Akçay, Fatma; Şan, Murat
Agriculture is affected by climate change, such as extreme increases or decreases rainfall and temperature patterns. It is possible to research that effect by using trend analysis methodologies. This paper investigates trends of monthly total rainfall and mean temperature data of nine selected stations from agricultural regions of Turkey between 1969 and 2020. To the end, the classical Mann–Kendall, Innovative Trend Significance Test (ITST), and Innovative Polygon Trend Analysis (IPTA) with Star Graph methods providing the opportunity to examine seasonal behavior were used for trend analysis. The analysis reveals that about 96% of all monthly rainfall in the Mann-Kendall test has no trend. However, nearly all stations tend to decrease (increase) in November (September) in both innovative approaches. For temperature, it is seen that increasing trend or no trend dominated in general. There were increasing trends in the innovative approaches throughout the year except for April. Temperatures have increased significantly throughout the year in all regions over the last decades. With the help of IPTA, it was also concluded that the seasonal internal variability of rainfall over the entire time and in the last 30 years is quite complex and persists in all agricultural regions. The results show that irregular changes in rainfall and rising temperatures in all stations negatively affected crop yield and/or required more irrigation. In addition, according to the results obtained by comparing trend methods, innovative approaches are very insistent on determining of trend and provide additional information through a visual review of trend behaviors.
AtıfScopus22WoS22OpenAlex26İncele