Dynamic detection of water surface area of Ebinur Lake using multi-source satellite data (Landsat and Sentinel-1A) and its responses to changing environment

In arid and semi-arid climatic areas, lakes are extremely essential for fragile ecological environment and regional sustainable development. Ebinur Lake is an important component of the ecological barrier of Junggar Basin, Xinjiang Uyghur Autonomous Region (XUAR), China. Due to the tremendous changes in Ebinur Lake and surrounding marshes during the last decades, Ebinur Lake becomes a representative ecological degradation region in northwestern China. The detection of the intra-annual variations of water body and its responses to changing environment are critical for regional ecological security and rehabilitation of degraded ecosystem. To extract more accurate water information using Synthetic Aperture Radar (SAR) data and further fill the gap of inter-month dynamic monitoring of Ebinur Lake, a new SAR water index (modified Sentinel 1A water index, MSWI) was proposed based on the relationship between normalized difference water index (NDWI) imageries and Sentinel 1A data. The dynamic thresholds of classification were selected using Otsu method and the results showed that the classification results were acceptable with the optimal overall accuracy of 99.94% and kappa coefficient of 0.9971, respectively. We conduct a time series analysis of surface areas of Ebinur Lake using S1A data from February 9th, 2017 to February 4th, 2018. The maximum lake surface area was 965.29 km ² in April 22nd, 2017, while the minimum value was 750.37 km ² in September 1st, 2017, and the mean area was 831.51 km ² . The seasonal variations showed the stages of “sharp rising” – “significant decreasing” – “gradual stabilizing” in the study period. The water surface area was highly correlated with inflow water volume (correlation coefficient = 0.72, P < 0.001). The variation of Ebinur Lake's water surface area is crucial to monitor the resulting eco-environmental impacts under the changing environmental conditions in the arid and semi-arid areas.