13th INTERNATIONAL BILTEK CONGRESS ON CURRENT DEVELOPMENTS IN SCIENCE, TECHNOLOGY AND SOCIAL SCIENCES, Paris, Fransa, 18 - 21 Aralık 2025, ss.14-15, (Özet Bildiri)
Climate change, which is constantly reshaping itself
based on trends in meteorological and hydrological variables, brings with it
numerous problems. These include irregularities in precipitation patterns,
depletion of groundwater and surface water resources, and/or unexpected
locational and temporal variations in these resources, disruption of ecological
balance, floods, desertification, drought, erosion, and fires. To predict the
potential risks and magnitudes that may arise from climate change and to develop
solutions to potential problems, it is crucial to define and interpret climate
variable trends in detail. Conventional Mann-Kendall (MK) and Sen's slope (SS)
trend analysis methods can only test the direction and magnitude of monotonic
trends to a limited extent under certain statistical assumptions. However, the
Innovative Trend Analysis (ITA) method and its numerous derivatives enable the
detailed determination of both monotonic and non-monotonic trends. Recently
proposed Frequency ITA (F-ITA) and Frequency Differential Length ITA (FDL-ITA)
approaches can also identify the frequencies and probabilities of additional
trend patterns. In this way, changes in the frequency of trend-related events,
in other words, regime changes, events that classical approaches cannot detect
and that the ITA methodology cannot measure, can be evaluated using objective
numerical criteria. In this study, average temperature and maximum temperature
trends measured at selected Cihanbeyli, Beyşehir, Karaman ve Niğde stations in the
Konya Closed Basin, one of Türkiye's major basins, were analyzed and interpreted using
classical and innovative methodologies. Furthermore, regime changes resulting
from climate change were analyzed and interpreted using a synthesis of the
recently presented F-ITA and FDL-ITA methodologies. The results showed an
increasing trend in both maximum and average temperatures across traditional
and innovative trend approaches, ensuring more effective climate change
adaptation and mitigation strategies. The maximum SS was at Cihanbeyli station
with SS 0.6 ̊ C/10 years and an increasing trend at a 99% confidence level for
the monthly maximum temperature.