Abstract
BackgroundThe improper land utilization has brought tremendous pressure on the surface water of the Aral Sea Region in the past decades. It was seriously hindered for construction of the Green Silk Road Economic Belt by the fragile environment. Therefore, it is of great necessity for environmental protection and social development to monitor the change of surface water in the Aral Sea Region.MethodsIn this study, LandTrendr algorithm was used on Landsat time-series data to characterize the change in farmland on the Google Earth Engine platform. Based on multi-source data, the water area changes of the Aral Sea were extracted based on the Google Earth Engine, and the mean method was utilized to extract the changes in water level and water storage. Finally, a water-farmland coupling degree model was utilized to evaluate the impact of farmland changes on the surface water in the Aral Sea Region.ResultsAs a result, the change of farmland is as follows: the farmland area of the Aral Sea Region has abandoned 3,129 km2 from 1987 to 2019, with overall accuracy of 85.3%. The farmland change had increased the drainage downstream of the Amu Darya River and the Syr Darya River. It has led area of the Aral Sea to decrease each year continuously. The area of the Aral Sea shrank by 1,606.36 km2 per year from 1987 to 2019. Furthermore, Aral Sea’s water level decreased by 0.13 m per year from 2003 to 2009. The amount of water storage in the Aral Sea Region also showed a downward trend from 2002 to 2016. There was a high-quality coupling coordination 0.903 relationship between surface water and farmland. It will increase the burden of water for people’s normal daily life by the water loss resources caused by abandoned farmland. This study emphasized threat of unreasonable farmland management to surface water of the Aral Sea Region. The findings contributed for decision makers to formulating effective reasonable policies to protect surface water and use land of the Aral Sea Region. Meanwhile, the application of coupling degree model can provide a new method for studying the connection of independent systems in the farmland, water, environment and more.
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