Spatio-temporal analysis of climate and irrigated vegetation cover changes and their role in lake water level depletion using a pixel-based approach and canonical correlation analysis

Soghra Andaryani; Vahid Nourani; Hassan Abbasnejad; Julian Koch; Simon Stisen; Björn Klöve; Ali Torabi Haghighi

doi:10.1016/j.scitotenv.2023.162326

Spatio-temporal analysis of climate and irrigated vegetation cover changes and their role in lake water level depletion using a pixel-based approach and canonical correlation analysis

Sci Total Environ. 2023 May 15:873:162326. doi: 10.1016/j.scitotenv.2023.162326. Epub 2023 Feb 25.

Authors

Soghra Andaryani¹, Vahid Nourani², Hassan Abbasnejad³, Julian Koch⁴, Simon Stisen⁴, Björn Klöve⁵, Ali Torabi Haghighi⁵

Affiliations

¹ Center of Excellence in Hydroinformatics and Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran; Geological Survey of Denmark and Greenland, GEUS, Øster Voldgade 10, 1350 Copenhagen K, Denmark. Electronic address: s.andaryani@gmail.com.
² Center of Excellence in Hydroinformatics and Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran; Near East University, Faculty of Civil and Environmental Engineering, Near East Boulevard, 99138, via Mersin 10, Turkey.
³ Geological Survey & Mineral Exploration, Tabriz, Iran.
⁴ Geological Survey of Denmark and Greenland, GEUS, Øster Voldgade 10, 1350 Copenhagen K, Denmark.
⁵ Water, Energy and Environmental Engineering Research Unit, University of Oulu, 90570 Oulu, Finland.

PMID: 36842572
DOI: 10.1016/j.scitotenv.2023.162326

Abstract

Lake Urmia, located in northwest Iran, was among the world's largest hypersaline lakes but has now experienced a 7 m decrease in water level, from 1278 m to 1271 over 1996 to 2019. There is doubt as to whether the pixel-based analysis (PBA) approach's answer to the lake's drying is a natural process or a result of human intervention. Here, a non-parametric Mann-Kendall trend test was applied to a 21-year record (2000-2020) of satellite data products, i.e., temperature, precipitation, snow cover, and irrigated vegetation cover (IVC). The Google Earth Engine (GEE) cloud-computing platform utilized over 10 sub-basins in three provinces surrounding Lake Urmia to obtain and calculate pixel-based monthly and seasonal scales for the products. Canonical correlation analysis was employed in order to understand the correlation between variables and lake water level (LWL). The trend analysis results show significant increases in temperature (from 1 to 2 °C during 2000-2020) over May-September, i.e., in 87 %-25 % of the basin. However, precipitation has seen an insignificant decrease (from 3 to 9 mm during 2000-2019) in the rainy months (April and May). Snow cover has also decreased and, when compared with precipitation, shows a change in precipitation patterns from snow to rain. IVC has increased significantly in all sub-basins, especially the southern parts of the lake, with the West province making the largest contribution to the development of IVC. According to the PBA, this analysis underpins the very high contribution of IVC to the drying of the lake in more detail, although the contribution of climate change in this matter is also apparent. The development of IVC leads to increased water consumption through evapotranspiration and excess evaporation caused by the storage of water for irrigation. Due to the decreased runoff caused by consumption exceeding the basin's capacity, the lake cannot be fed sufficiently.

Keywords: Canonical correlation analysis; Google Earth Engine; Irrigated vegetation cover/climate trends; Lake Urmia; Pixel-based analysis approach.