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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

Author

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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
    Faculty of Civil and Environmental Engineering, Near East University, Near East Boulevard, 99138 Nicosia, via Mersin 10, Turkey)

  • 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)

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.

Suggested Citation

  • Ehsan Foroumandi & Vahid Nourani & Dominika Dąbrowska & Sameh Ahmed Kantoush, 2022. "Linking Spatial–Temporal Changes of Vegetation Cover with Hydroclimatological Variables in Terrestrial Environments with a Focus on the Lake Urmia Basin," Land, MDPI, vol. 11(1), pages 1-28, January.
  • Handle: RePEc:gam:jlands:v:11:y:2022:i:1:p:115-:d:722432
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    References listed on IDEAS

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    1. Hsin-Yu Chen & Chia-Chi Huang & Hsin-Fu Yeh, 2021. "Quantifying the Relative Contribution of the Climate Change and Human Activity on Runoff in the Choshui River Alluvial Fan, Taiwan," Land, MDPI, vol. 10(8), pages 1-14, August.
    2. Bhagawat Rimal & Lifu Zhang & Hamidreza Keshtkar & Xuejian Sun & Sushila Rijal, 2018. "Quantifying the Spatiotemporal Pattern of Urban Expansion and Hazard and Risk Area Identification in the Kaski District of Nepal," Land, MDPI, vol. 7(1), pages 1-22, March.
    3. Athos Agapiou, 2021. "Land Cover Mapping from Colorized CORONA Archived Greyscale Satellite Data and Feature Extraction Classification," Land, MDPI, vol. 10(8), pages 1-14, July.
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    Cited by:

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