Remote Sensing Monitoring of the Bottom Topography in a Shallow Reservoir and the Spatiotemporal Changes of Submerged Aquatic Vegetation under Water Depth Fluctuations

Abstract

Monitoring the growth and distribution of submerged aquatic vegetation (SAV) is crucial to the protection and restoration of the ecosystem of inland reservoirs. Considering the high sensitivity of SAV to water depth fluctuations in Guanting Reservoir, China, in this study, we realized the reconstruction of bottom topography by combining changing water level with a long time series remote sensing technology and explored the spatiotemporal succession law of SAV by analyzing the effect of water depth on the spatiotemporal distribution of SAV. Results of water depth spatial distribution in Guanting Reservoir were obtained by using water and land boundary lines to construct underwater terrain contours. The accuracy of estimated water depth data from remote sensing images was verified with measured water depth data, and the average relative error of water depth estimation results was about 0.25 m. The experimental results show that (1) the SWIR bands of Landsat images could avoid the interference of aquatic vegetation and realize the separation of land and water; and (2) after separating water area from land, an SWIR1_NIR index was used to effectively map SAV distribution in the reservoir. The results also indicate that the distribution of SAV in the reservoir is suitable for the water depth range of 0-2 m. Water depth fluctuations cause changes in the spatial distribution of suitable water depth. It is the main reason for the change of SAV distribution area in the reservoir during the past 20 years.