Satellite-observed significant improvement in nearshore transparency of the Bohai Sea during pollution control

The Bohai Sea(BS)is the unique semi-closed inland sea of China,characterized by degraded water quality due to significant terrestrial pollution input.In order to improve its water quality,a dedicated action named“Uphill Battles for Integrated Bohai Sea Management”(UBIBSM,2018–2020)was implemented by the Chinese government.To evaluate the action effectiveness toward water quality improvement,variability of the satelliteobserved water transparency(Secchi disk depth,Z_(SD))was explored,with special emphasis on the nearshore waters(within 20 km from the coastline)prone to terrestrial influence.(1)Compared to the status before the action began(2011–2017),majority(87.3%)of the nearshore waters turned clear during the action implementation period(2018–2020),characterized by the elevated Z_(SD)by 11.6%±12.1%.(2)Nevertheless,the improvement was not spatially uniform,with higher Z_(SD)improvement in provinces of Hebei,Liaoning,and Shandong(13.2%±16.5%,13.2%±11.6%,10.8%±10.2%,respectively)followed by Tianjin(6.2%±4.7%).(3)Bayesian trend analysis found the abrupt Z_(SD)improvement in April 2018,which coincided with the initiation of UBIBSM,implying the water quality response to pollution control.More importantly,the independent statistics of land-based pollutant discharge also indicated that the significant reduction of terrestrial pollutant input during the UBIBSM action was the main driver of observed Z_(SD)improvement.(4)Compared with previous pollution control actions in the BS,UBIBSM was found to be the most successful one during the past 20 years,in terms of transparency improvement over nearshore waters.The presented results proved the UBIBSM-achieved remarkable water quality improvement,taking the advantage of long-term consistent and objective data record from satellite ocean color observation.

Shipborne oceanic high-spectral-resolution lidar for accurate estimation of seawater depth-resolved optical properties

Lidar techniques present a distinctive ability to resolve vertical structure of optical properties within the upper water column at both day-and night-time.However,accuracy challenges remain for existing lidar instruments due to the ill-posed nature of elastic backscatter lidar retrievals and multiple scattering.Here we demonstrate the high performance of,to the best of our knowledge,the first shipborne oceanic high-spectral-resolution lidar(HSRL)and illustrate a multiple scattering correction algorithm to rigorously address the above challenges in estimating the depth-resolved diffuse attenuation coefficient Kd and the particulate backscattering coefficient bbp at 532 nm.HSRL data were collected during day-and night-time within the coastal areas of East China Sea and South China Sea,which are connected by the Taiwan Strait.Results include vertical profiles from open ocean waters to moderate turbid waters and first lidar continuous observation of diel vertical distribution of thin layers at a fixed station.The root-mean-square relative differences between the HSRL and coincident in situ measurements are 5.6%and 9.1%for Kd and bbp,respectively,corresponding to an improvement of 2.7-13.5 and 4.9-44.1 times,respectively,with respect to elastic backscatter lidar methods.Shipborne oceanic HSRLs with high performance are expected to be of paramount importance for the construction of 3D map of ocean ecosystem.

Unprecedent green macroalgae bloom:mechanism and implication to disaster prediction and prevention

Green macroalgae bloom(GMB),with the dominant species of Ulva prolifera,has regularly occurred since 2007 along the China coast.Although disaster prevention and control achieved favorable results in 2020,the satellite-observed GMB annual maximum coverage(AMC)rebounded sharply in 2021 to an unprecedented level.The reasons for this rebound and the significant interannual variability over past 15 years are still open questions.Here,by using long-term time-series(2007-2022)optical and Synthetic Aperture Radar satellite observations(1000+scenes),meteorological data and water quality statistics,the mechanism analysis was performed by exploring effects from natural factors and human activities.Two key determinants for AMC are successfully identified from numerous potential factors which are the macroalgae distribution in a key area(the Subei Shoal)during a critical period(from April to May 20)and the nutrient availability.Furthermore,by using these two parameters,a novel model for AMC prediction(R^(2)=0.87,p<0.01)is proposed and independently validated,which can reasonably explain the significant interannual variability(2014-2021)and agree well with the latest observation in 2022(percentage difference 12%).Finally,suggestions are proposed for future disaster prevention and alleviation.This work may aid future bloom prediction and management measure optimization.