## 2 Data and Methods
### Data and Preprocessing  
(1) Landsat Imagery  
The United States Geological Survey (USGS) released the Landsat Collection 2 Level-2 (C2L2) scientific product in November 2020 ([[https://earthexplorer.usgs.gov/](https://earthexplorer.usgs.gov/)]([https://earthexplorer.usgs.gov/](https://earthexplorer.usgs.gov/)), accessed on 2 January 2022), containing long-time series (August 1982-Present) as well as high-spatial-resolution and high-temporal-resolution data imaged across a large swath of landscapes (185 km), which allows for long-term thermal discharge monitoring with fine-scale grading. USGS-released Landsat C2L2 scientific products were used in this study, and 139 scenes of high-quality data, acquired between 2013 and 2024, covering the study area were selected. \begin{table}
\begin{tabular}{c c c c c} \hline
**Power Unit** & **Reactor Type** & **Gross Capacity** & **First Criticality Date** & **Commercial Operation Date** \\ \hline No. 1 & PWR & 1253 MW & 8 August 2018 & 22 October 2018 \\ No. 2 & PWR & 1253 MW & 29 September 2018 & 9 January 2019 \\ \hline \end{tabular}
\end{table} 
Table 1: Operational parameters of HYNPP units. Figure 1: Geographic location of the study area and division of EFZs. (**a**) Geolocation of HNP; (**b**) EFZ distribution; (**c**) Intake and outlet locations of HNP. By linear stretching Equation (1), \(SST\) values are determined from the Landsat C2L2 surface temperature data. \[SST=ST\times Scale+Offset-273.15 \tag{1}\]  
where \(SST\) is the surface temperature of the water body after linear stretching, in \({}^{\circ}\)C, \(ST\) is the DN value of the C2L2 dataset surface temperature band, and \(Scale\) and \(Offset\) are the scaling and offset factors for linear stretching, respectively, where \(Scale=0.00341802\), and \(Offset=149.0\). The SST data underwent quality control using several techniques to ensure accuracy and reliability. First, singular value rejection identified and removed anomalous SST values deviating significantly from expected patterns. Values outside the valid SST range of 293-61,440, as defined in the science product guide [33], were also excluded to retain only physically plausible measurements. Second, cloud-contaminated pixels were removed using the Level-2 pixel quality band (ProductID_QA_PIXEL) within each C2L2 dataset. This band uses binary representation to provide information on cloud cover and other quality indicators, ensuring retention of only valid, cloud-free SST data. Third, to enhance dataset robustness, SST data from nearshore intertidal and foreshore areas were excluded. These areas are susceptible to inaccuracies due to land proximity and shallow water influences [26]. Furthermore, during summer, shallow bathymmetric conditions can cause higher temperatures in submerged areas, potentially mimicking coastal thermal plumes and leading to data misinterpretation. EFZs data  
The EFZ data of the sea area near HYNPP utilized in this study were obtained from the Environmental Functional Zone Planning of Nearshore Sea Areas in Shandong Province ([[http://lyc.sdeein.gov.cn/dtx/201605/20160529_716079.html](http://lyc.sdeein.gov.cn/dtx/201605/20160529_716079.html)]([http://lyc.sdeein.gov.cn/dtx/201605/20160529_716079.html](http://lyc.sdeein.gov.cn/dtx/201605/20160529_716079.html)), accessed on 20 May 2024), which was approved by the People's Government of Shandong Province, China, in May 2016. The data were used to determine the environmental functions of the sea area near HYNPP. The planning stipulates Type I to Type IV EFZs, which implement the corresponding sea water quality standards [32], respectively, and no water quality objectives are set for the thermal mixing zone, but it should not affect the water quality of the adjacent EFZs.