Measuring lake water level using multi-source remote sensing images combined with hydrological statistical data

Abstract

The Poyang Lake, as one of the most frequently flooded area, is the largest freshwater lake in China. It is very significant to monitor the water level and water regime accurately and in real-time during flooding. To provide an operational method to measure shape parameters, such as water level, water regime area, and water distribution of Poyang Lake using remote sensing images, we carried out the study. In the paper, using the hydrological statistical data of Poyang Lake through many years, we fit a mathematic model of water regime area varied with water level. Meanwhile, water regime distribution is extracted from Radarsat SAR and Terra Modis remote sensing images, and then its area can be calculated. Comparisons between model results and remote-sensing-image-based measuring results are carried out and the absolute error is less than 0.70%. Then we revise the fitted mathematic model using remotely sensed data and finally build a high precision (R 2>0.99) and practical mathematical model of water level versus water distribution of Poyang Lake main regime. It is a great contribution to the prevention, monitoring and mitigation of great flood disaster around the Poyang Lake district