Abstract
Accurately quantifying spatiotemporal changes in surface water is essential for water resources management, nevertheless, the dynamics of Poyang Lake surface water areas with high spatiotemporal resolution, as well as its responses to climate change, still face considerable uncertainties. Using the time series of Sentinel-1 images with 6- or 12-day intervals, the Sentinel-1 water index (SWI), and SWI-based water extraction model (SWIM) from 2015 to 2020 were used to document and study the short-term characteristics of southwest Poyang Lake surface water. The results showed that the overall accuracy of surface water area was satisfactory with an average of 91.92%, and the surface water area ranged from 129.06 km2 on 2 March 2017 to 1042.57 km2 on 17 July 2016, with significant intra- and inter-month variability. Within the 6-day interval, the maximum change of lake area was 233.42 km2 (i.e., increasing from 474.70 km2 up to 708.12 km2). We found that the correlation coefficient between the water area and the 45-day accumulated precipitation reached to 0.75 (p < 0.001). Moreover, a prediction model was built to predict the water area based on climate records. These results highlight the significance of high spatiotemporal resolution mapping for surface water in the erratic southwest Poyang Lake under a changing climate. The automated water extraction algorithm proposed in this study has potential applications in delineating surface water dynamics at broad geographic scales.
Highlights
Lakes are among the most important terrestrial water resources
The period with the overall accuracy (89.93%) is 2 July 2019, which is because there are many commission error according to Figure 2l
Our study showed that the average overall accuracy in water classification attained 91.92% in southwest Poyang Lake using the Sentinel-1 water index (SWI)-based water extraction model
Summary
Lakes are among the most important terrestrial water resources. Information regarding lake surface waters is fundamental for supporting ecosystem services [1], especially wetlands [2] and biodiversity assessments [3], serving as a critical indicator to assess changes in local ecosystems at nearby lakes [4]. There are some existing water map products used to depict the extent of global water, such as the Joint Research Centre of the European Commission (JRC) global surface water map [6], global open permanent water bodies [7] and global raster water mask at 250 m resolution [8]. These products cannot quickly characterize variations in the surface water due to a lack of sufficient spatial and/or temporal resolutions [9]
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