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Linking Spatial–Temporal Changes of Vegetation Cover with Hydroclimatological Variables in Terrestrial Environments with a Focus on the Lake Urmia Basin

Ehsan Foroumandi, Vahid Nourani, Dominika Dąbrowska and Sameh Ahmed Kantoush
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Ehsan Foroumandi: Center of Excellence in Hydroinformatics, Faculty of Civil Engineering, University of Tabriz, Tabriz 51666, Iran
Vahid Nourani: Center of Excellence in Hydroinformatics, Faculty of Civil Engineering, University of Tabriz, Tabriz 51666, Iran
Dominika Dąbrowska: Faculty of Natural Sciences, University of Silesia, 40-007 Katowice, Poland
Sameh Ahmed Kantoush: Water Resources Research Centre, Disaster Prevention Research Institute, Kyoto University, Kyoto 606-8501, Japan

Land, 2022, vol. 11, issue 1, 1-28

Abstract: Investigation of vegetation cover is crucial to the study of terrestrial ecological environments as it has a close relationship with hydroclimatological variables and plays a dominant role in preserving the characteristics of a region. In Iran, the current study selected the watersheds of two rivers, Nazloo-Chay and Aji-Chay, to systematically investigate the implications and causes of vegetation cover variations under changing environments. These two rivers are among the essential inflows to Lake Urmia, the second largest saline lake on Earth, and are located on the west and east sides of the lake, respectively. There has been a debate between the people living in the rivers’ watersheds about who is responsible for the decline in the level of Lake Urmia—does responsibility fall with those on the east side or with those on the west side? In this study, the normalized difference vegetation index (NDVI) was used as a remotely sensed index to study spatial–temporal pattern changes in vegetation. Moreover, the temperature, precipitation, and streamflow time series were gathered using ground measurements to explore the causes and implications of changing vegetation cover. Discrete wavelet transform was applied to separate the different components of the time series. The Mann–Kendall (MK) test was applied to the time series on monthly, seasonal, and annual time scales. The connections and relationship between the NDVI time series and temperature, precipitation, and streamflow time series and any underlying causes were investigated using wavelet transform coherence (WTC). Land use maps were generated for different years using a support vector machine (SVM) in the final stage. The results indicated that the most dominant monthly, seasonal, and annual hydrological periodicities across the watersheds are 8 months, 6 months, and 2 years, respectively. The increasing vegetation cover during stable hydro-environmental periods revealed unusual conditions in the Aji-Chay watershed and reflected agricultural expansion. The WTC graphs indicated sudden changes in mutual periodicities and time-lags with different patterns between variables, which indicates the increasing anthropogenic activities in both watersheds. However, this was more dominant in the Aji-Chay watershed. The land use maps and investigation of the averaged NDVI maps also denoted that the areas of cultivated land have increased by 30% in the Aji-Chay watershed, and crop types have been changed to the crops with a higher demand for water in both watersheds.

Keywords: vegetation cover; remote sensing; wavelet transform; support vector machine (SVM); land use map; Lake Urmia; Aji-Chay; Nazloo-Chay (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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