Spatio-temporal analysis of water area variability in Poyang Lake (2012–2021) using remote sensing

With global warming and aggravation due to human activities, many regions of the world have suffered from frequent droughts and floods in recent decades. As the largest freshwater lake in China, and one of the ten ecological function reserves in China, Poyang Lake plays an important role in the local ecological environment. It is necessary to use long-term frequent satellite observations to investigate the Poyang Lake due to the significant seasonality of the lake’s area. This paper selects 20 periods of Landsat remote sensing images during the wet and dry seasons over 10 years from 2012 to 2021 as the data source. Threshold method is a commonly used method for water extraction, and different threshold methods have their advantages and disadvantages. Five water extraction methods were used: single-band threshold method, multi-band spectral relationship method, Normalized Difference Water Index (NDWI), Modified NDWI (MNDWI), and Modified Automatic Water Extraction Index (MAWEI), to extract water bodies from the Landsat 5 images dated February 15, 2004. The water area extracted by MAWEI had the smallest deviation from the actual measured area. It had the highest overall accuracy and Kappa coefficient. Additionally, it exhibited fewer instances of false positives and false negatives, and performed well in extracting small water bodies. Using the MAWEI method to perform water body extraction for Poyang Lake during the wet and dry seasons from 2012 to 2021 demonstrated significant interannual variability in the lake’s area, with a pronounced seasonal fluctuation. A comparison of the lake area between the first and last 5 years of this period revealed a shrinking trend in the lake’s extent. Moreover, the dynamic change in the lake area during the wet seasons was found to be less than that during the dry seasons, with an average dynamic change of 14.1% for the wet season and 16.4% for the dry season. Influenced by the floods in 2020, the water area reached its maximum. The driving factors behind the changes in the area of Poyang Lake were analyzed in conjunction with meteorological data. By calculating the Pearson coefficient, it was demonstrated that the correlation between lake area and precipitation is the strongest, followed by temperature, while there is no correlation with humidity. This research can provide valuable insights for policymakers and water resource managers.