Analyzing and Modeling the Spatial-Temporal Changes and the Impact of GLOTI Index on Precipitation in the Marmara Region of Türkiye

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung

Beitragende

  • Mehdi Aalijahan - , Marmara University (Autor:in)
  • Atilla Karataş - , Marmara University (Autor:in)
  • Anthony R. Lupo - , University of Missouri (Autor:in)
  • Bahtiyar Efe - , Samsun University (Autor:in)
  • Azra Khosravichenar - , Professur für Modellbasierte Landschaftsökologie, Universität Leipzig (Autor:in)

Abstract

Precipitation is a particularly important part of the Earth’s hydrological cycle and, therefore, is a necessary variable for maintaining natural balance. This study investigated past, present, and future changes in precipitation in the Marmara region, and examined the effects of global warming on this variable. The study period was from 1960 to 2020, and the climate data of 15 synoptic stations in the Marmara region were used for this purpose. To achieve the objectives of the study, linear and 6th order polynomial regression, ombrothermic and hythergraph diagrams, geostatistical models, Mann-Kendall test, Pearson correlation, standard Z-scores, and multi-layer perceptron artificial neural network models (MLP-ANN) were used to model and predict precipitation. The results of the linear regression analysis showed that of the 15 stations, 6 stations had an increasing trend, 6 stations had a trendless pattern, and 3 stations had a decreasing trend. In terms of periodic analysis, the main downward trend started in 1964 and continued until 1992, while the main periodic upward trend started in 1992 and continued until 2016. The synoptic stations in the Marmara region showed a lack of precipitation over six to seven months of the year, and the precipitation changes in the region were stronger than the temperature changes. In addition, the highest precipitation was observed on the southeast coast of the Black Sea, and the lowest precipitation was observed in the eastern parts of the region. Moreover, except for the Bilecik and Kocaeli stations, the changes in the long-term trend of precipitation at the other stations were significant. Among the 15 stations, only the Kocaeli and Sarıyer stations showed a positive correlation with global temperature during the annual period. In addition, the developed ANN model was accurate in simulating and predicting precipitation and showed an upward trend over the next seven years.

Details

OriginalspracheEnglisch
Aufsatznummer489
FachzeitschriftAtmosphere
Jahrgang14
Ausgabenummer3
PublikationsstatusVeröffentlicht - März 2023
Peer-Review-StatusJa

Schlagworte

Ziele für nachhaltige Entwicklung

ASJC Scopus Sachgebiete

Schlagwörter

  • global warming effect, GLOTI index, machine learning, Mann-Kendall test, Marmara region, MLP-ANN model, precipitation modeling, trend analysis