## 1 Introduction  
The Bohai Sea, located in north eastern China, is a semi-closed shallow sea, into which a large amount of sewage is discharged along the Gulf Coast. Environmental pollution of the Bohai Sea is becoming increasingly serious. The eutrophication of the water body is significantly intensified, resulting in frequent occurrence of red tides [1]. As an important part of marine environmental factors and water quality parameters, chlorophyll-a (Chla) has great significance for the marine ecological environment [2]. The detection of Chla concentration based on remote-sensing technology aims to calculate the Chla concentration using off-water reflectance [3] after atmospheric correction [4] and geometric correction of remote-sensingsatellite image data. In prior studies, different inversion models [5] are developed to retrieve Chla concentration according to the off-water emissivity. For the typical type II water body in the Bohai Sea, it is an urgent task to monitor the water color and quality change details of the sea [6]. Chla concentration can help us monitor the water quality and understand the characteristics of the coastal waters, as well as provide scientific basis for the management, and comprehensive utilization of the Bohai Sea [7; 8; 9]. It will be significant to find a more suitable Bohai Sea algorithm of Chla concentration inversion for the new sensor. The inversion algorithms for detecting Chla based on remote-sensing technology can be divided into two categories: empirical formula methods and model-based analytical methods [10]. At the beginning of 1990, [PERSON] calculated the Chla concentration based on the ratio of the red band and the infrared band [11]. Meanwhile, neural network and semi-analytical algorithms, as well as bio-optical models were also used to invert Chla concentration [12]. [PERSON] adopted [PERSON]'s method, corrected by using the phycoerythrin absorbance in 624 nm spectra, to improve the calculation accuracy of Chla [13]. In China, many prior studies analyzed the correlation [14; 15] between the normalized difference and the in situ Chla concentration, and found that the two show a significant negative correlation. The Chla in type II waters retrieved from the incineration algorithm shows that the average absolute error of the results is 1.081 [16]. Using satellite remote-sensing data, the detection of Chla concentration of type II water is greatly affected by suspended sediment, colored dissolved organic matter (CDOM), etc. [17]. A multi-factor algorithm was established previously by researchers for ocean water color hyperspectral information. The quantitative relationship between the common contributions of water color factors such as Chla, suspended sediment, and CDOM and the emissivity of water was developed based on high-resolution and hyperspectral remote-sensing fusion data [18]. At present, there are many empirical and semi-empirical algorithms for marine Chla inversion, and most of them use satellite data, such as Moderate-resolution Imaging Spectroradiometer (MODIS) data and Operational Land Imager (OLI) data [19; 20; 21; 22], from the near-polar solar synchronous orbit. In recent years, due to the influence of manmade and natural factors, the environment of China's coastal waters has undergone great changes, and the nutrient salt structure of some sea areas has changed, resulting in increasingly frequent red tide disasters [23]. Prior studies found that, in general, the annual variation of Chla concentration in the far coastal waters of Bohai bay is relatively low. Furthermore, the Chla concentration variation is characterized by a large range of continuous changes, and the seasonal variation in the near shore waters is obvious due to the influence of current conditions and precipitation [2]. Most important of all, the effect of tidal wave motion on Chla concentration distribution cannot be ignored. Tidal wave movement is the most important marine dynamic process in the Bohai Sea and plays an important role in controlling the marine environment [24].