Chlorophyll-a concentrations inversion based on the modified Quasi-Analytical Algorithm and Sentinel-3 OLCI in Daihai Lake, China

The Quasi-Analytical Algorithm (QAA) is effective in retrieving water inherent optical properties (IOPs) from remote sensing spectral reflectance and has wider applications in studies of the open ocean and coastal waters than of inland waters. This research aimed to modify the QAA model based on measured field spectral reflectance and absorption coefficients to render it applicable to studies of Daihai Lake, China. The improvements mainly included the reference wavelength selection, the power index of the particle backscattering coefficient and the exponential slope of the absorption coefficient of the colored detrital matter estimation. The average relative error between the inversed and measured absorption coefficients was less than 20%. A linear model was established between the phytoplankton absorption coefficient at a wavelength of 674 nm (aph(674)) and the chlorophyll-a (Chl-a) concentration, with a determination coefficient of 0.88. Additionally, the modified Quasi-Analytical Algorithm (MQAA) model was applied to the Ocean and Land Color Instrument (OLCI) data aboard the Sentinel-3 satellite. Finally, a spatial distribution map for the Chl-a concentrations in Daihai Lake on August 10, 2017 was drawn and the mid-eutrophication area was found to occur in the north and border.

External Groundwater Alleviates the Degradation of Closed Lakes in Semi-Arid Regions of China

There are a large number of lakes with beaded distribution in the semi-arid areas of the Inner Mongolian Plateau, and some of them have degraded or even disappeared during the past three decades. We studied the reasons of the disappearance of these lakes by determining the way of replenishment of these lakes and the impact of the natural-social environment of the basin, with the aim of saving these gradually disappearing lakes. Based on remote sensing image and hydrological analysis, this paper studied the recharge of Daihai Lake and Huangqihai Lake. The deep learning method was used to establish the time-series of lake evolution. The same method was combined with the innovative woodland and farmland extraction method to set up the time-series of ground classification composition in the basins. Using relevant survey data, combined with soil water infiltration test, water chemical, and isotopic signature analysis of various water bodies, we found that the Daihai Lake area is the largest in dry season and the smallest in rainy season and the other lake is not satisfied with this phenomenon. In addition, we calculated the specific recharge and consumption of the study basin. These experiments indicated that the exogenous groundwater is recharged directly through the faults at the bottom of Daihai Lake, while the exogenous groundwater is recharged in Huangqihai Lake through rivers indirectly. Large-scale exploitation of groundwater for agricultural irrigation and industrial production is the main cause of lake degradation. Reducing the extraction of groundwater for agricultural irrigation is an important measure to restore lake ecology.