1. Airborne Survey and Remote Sensing Center of Nuclear Industry, Shijiazhuang 050002, China 2. Hebei Key Laboratory of Airborne Survey and Remote Sensing Technology, Shijiazhuang 050002, China
This study investigated the temperature distribution in the sea area around the Qinshan Nuclear Power Plant using Landsat thermal infrared remote sensing data. The results indicate a strong correlation between the inversion results of temperature and the measured data, suggesting reliable inversion results. Before the operation of the nuclear power plant, the surrounding sea area exhibited relatively uniform temperature, with no significant temperature difference except for natural warming. Furthermore, the temperature along the coast remained almost unchanged in the north-south direction and displayed slight temperature gradients in the east-west direction, with temperature variation not exceeding 0.6 ℃ within 10 km from the coast. After the operation of the nuclear power, the surrounding sea area showed temperature differentiation. The distribution characteristic of thermal discharge was closely related to tides and seasons. In the same season, the increased amplitude of the temperature during ebb tides generally exceeded that during flood tide. Under the same tidal condition, the increased amplitude of the temperature in summer typically exceeded that in winter. At a certain water intake of the first plant, the surface seawater manifested a temperature rise of over 1.0 ℃ during flood tide. Landsat data generally meet the demand for research on temperature distribution in the surrounding sea area of the Qinshan Nuclear Power Plant, and the distribution of thermal discharge under specific tidal conditions can be investigated using aerial remote sensing monitoring.
石海岗, 梁春利, 薛庆, 张恩, 章新益, 张建永, 张春雷, 程旭. 基于卫星遥感的秦山核电周边海域温度分布研究[J]. 自然资源遥感, 2025, 37(1): 152-160.
SHI Haigang, LIANG Chunli, XUE Qing, ZHANG En, ZHANG Xinyi, ZHANG Jianyong, ZHANG Chunlei, CHENG Xu. A study of temperature distribution in the sea area around Qinshan Nuclear Power Plant based on satellite remote sensing. Remote Sensing for Natural Resources, 2025, 37(1): 152-160.
Gao N, Han R, Zhao Y J, et al. Research on the optimization and modification about the water discharge channel of a coastal NPP based on mitigating the heat effects of its thermal effluent[J]. Water and Wastewater Engineering, 2022, 58(10):109-115.
Chen X Q, Shang Z R. The issue of thermal discharge in reviewing the environmental impacts report for nuclear power plant[J]. Nuclear Safety, 2007, 6(2):46-50.
Zhang J Y, Liang C L, Shi H G, et al. Application of thermal infrared remote sensing in monitoring heated water discharge of nuclear power plant[J]. Uranium Geology, 2021, 37 (3):534-540.
Wang H. Thermal discharge monitoring of Tianwan nuclear power plant based on satellite thermal infrared data[J]. Geospatial Information, 2022, 20(5):48-53.
Dong S F, Fan X, Shi H G, et al. Study on distribution of thermal discharge in Fuqing nuclear power plant based on Landsat8 and UAV[J]. Remote Sensing for Natural Resources, 2022, 34 (3):112-120.doi:10.6049/zrzyyg.2021258.
Thermal discharge enumerical simulation calculation and analysis report of Qinshan nuclear power plant expansion project (Fangjia-shan nuclear power project)[R].Zhejiang Institute of Hydraulics and Estuary, 2014.
[8]
Barsi J A, Barker J L, Schott J R. An atmospheric correction para-meter calculator for a single thermal band earth-sensing instrument[C]// IGARSS 2003—2003 IEEE International Geoscience and Remote Sensing Symposium. IEEE,2005: 3014-3016.
[9]
Barsi J A, Schott J R, Palluconi F D, et al. Validation of a web-based atmospheric correction tool for single thermal band instruments[C]. Earth Observing Systems X, 2005,5882: 1-6.
[10]
Jiménez-Muñoz J C, Sobrino J A. A generalized single-channel method for retrieving land surface temperature from remote sensing data[J]. Journal of Geophysical Research:Atmospheres, 2003, 108(D22):4688.
[11]
Qin Z H, Karnieli A, Berliner P. A mono-window algorithm for retrieving land surface temperature from Landsat TM data and its application to the Israel-Egypt border region[J]. International Journal of Remote Sensing, 2001, 22(18):3719-3746.
[12]
覃志豪, Zhang M H, Karnieli A, 等. 用陆地卫星TM6数据演算地表温度的单窗算法[J]. 地理学报, 2001, 56(4): 456-466.
doi: 10.11821/xb200104009
Qin Z H, Zhang M H, Karnieli A, et al. Mono-window algorithm for retrieving land surface temperature from Landsat TM6 data[J]. Acta Geographica Sinica, 2001, 56(4):456-466.
doi: 10.11821/xb200104009
Tu L P, Zhou B. A comparative study of algorithms for estimating land surface temperature from Landsat/TM data[J]. Bulletin of Science and Technology, 2007, 23(3):326-331.
Wang G L, Xiong X J. Distribution and variation of warm water discharge in the coastal area of Tianwan[J]. Advances in Marine Science, 2013, 31(1):69-74.
Zhu L, Wang Q, Wu C Q, et al. Principle and application of thermal discharge monitoring using remote sensing[M]. Beijing: China Environmental Science Press,2016:147-154.
Shi H G, Liang C L, Zhang J Y, et al. Remote sensing survey of the influence of coastline changes on the thermal discharge in the vi-cinity of Tianwan nuclear power station[J]. Remote Sensing for Land and Resources, 2020, 32(2):196-203.doi:10.6049/gtzyyg.2020.02.25.
Huang S H, Zhang Q Y, Yan J, et al. Impact of shoreline changes caused by Hangzhou Bay reclamation project on water environment[J]. Journal of North China University of Water Resources and Electric Power (Natural Science Edition), 2021, 42(2):32-41.
Wang L Y, Xing Z, Hou C, et al. The spatio-temporal change ana-lysis of mainland coastline in Hangzhou Bay from 1990 to 2017[J]. Marine Science Bulletin, 2020, 39(4):481-487.
He J H, Liang C L, Li M S. Temperature field airborne thermal remote sensing survey of the alongshore nuclear power station[J]. Remote Sensing for Land and Resources, 2010, 22(3):51-53.doi:10.6046/gtzyyg.2010.03.11.
Wang X, Wang X X, Su X, et al. Thermal discharge monitoring of nuclear power plant with aerial remote sensing technology using a UAV platform:Take Hongyanhe nuclear power plant,Liaoning Province,as example[J]. Remote Sensing for Land and Resources, 2018, 30(4):182-186.doi:10.6046/gtzyyg.2018.04.27.