Remote Sensing Inversion Study on Key Water Quality Parameters of Qinghai Lake
Journal: Architecture Engineering and Science DOI: 10.32629/aes.v6i2.3819
Abstract
To select a suitable remote sensing inversion model for the concentration of chlorophyll-a, a key water quality parameter of Qinghai Lake, this study based on Landsat 8 remote sensing image data and combined with the measured chlorophyll-a concentration data, constructed an inversion model for chlorophyll-a concentration in Qinghai Lake, and explored the spatial distribution pattern of chlorophyll-a concentration in Qinghai Lake in July 2024. The results show that the bands with higher correlation with the chlorophyll-a concentration of this water body are Landsat 8's B1, B6, and B7 bands; the band combination B6-B7 has a high correlation with the natural logarithm of chlorophyll-a concentration; the root mean square error (RMSE) of the chlorophyll-a concentration inversion model constructed is 0.162 μg/L, and the mean absolute error (MAE) is 14.36%, with high accuracy and good applicability; in July 2024, the chlorophyll-a concentration in Qinghai Lake showed a characteristic of lower concentrations at the river mouths such as the Buhai River and higher concentrations in areas such as the Erliangxian coast.
Keywords
chlorophyll-a concentration; eutrophication; Landsat 8 remote sensing imagery; Qinghai Lake
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[24]Li Nan. Absorption spectral decomposition of phytoplankton in the East China Sea considering population structure [D]. Nanjing University of Information Science and Technology, 2020.
[25]Miao Shiyu, Liu Yang, Li Chengyan, et al. Spatial and temporal distribution of Chl-a concentration in Qinghai Lake and its correlation with environmental factors [J]. Journal of Qinghai University, 2019, 38(03): 89-94+106.
[26]Shu Xiaozhou, Yin Qiu, Kuang Dingbo. Relationship between chlorophyll concentration and reflection spectral characteristics of algae in inland water [J]. Journal of Remote Sensing, 2000, (01):41-45.
[27]Sun Shaojie. Estimation and diurnal variation of chlorophyll-a concentration in Taihu Lake based on GOCI [D]. Nanjing University, 2013.
[28]Zhong Dan, Li Haojie, Fan Shuo, et al. Retrieval of chlorophyll-a concentration in nine plateau lakes in Yunnan Province based on MODIS data [J]. Chinese Journal of Ecology, 2017, 36(01): 277-286.
[29]Zhang Qin. Inversion and spatiotemporal variation of suspended sediment and chlorophyll-a concentrations in the Pearl River Estuary based on HY-1CCZI remote sensing image [D]. Guangzhou University, 2024.
[30]Cong Lu. Study on the correlation between Holocene lake evolution and eolian sediments on the Tibetan Plateau [D]. Qinghai Institute of Salt Lake Research, Chinese Academy of Sciences, 2021.
[31]Lanzhou Institute of Geology, Institute of Hydrobiology, Institute of Microbiology, Chinese Academy of Sciences, et al. Comprehensive survey report of Qinghai Lake [M]. Beijing: Science Press, 1979.
[32]Yuan Hong, Hao Lewei, Wang Qi, et al. Hydrodynamic characteristics of Qinghai Lake under prevailing risk control [J]. Yellow River, 2016, 38(03): 51-55. (in Chinese)
[33]Li S. T., Wang Q., Hao L. W., et al. (2018) (eds.). Hydrodynamic characteristics of Qinghai Lake and their response to sedimentary filling. Abstracts of the 15th National Conference on Palaeogeography and Sedimentology (pp.584). Key Laboratory of Petroleum Resources Research of Gansu Province/Key Laboratory of Petroleum Resources Research of Chinese Academy of Sciences; University of Chinese Academy ofSciences.
[34]Wang Lingling, Dai Huichao, CAI Qinghua. Numerical prediction and correlation of hydrodynamic factorsand chlorophyll-a distribution in Xiangxi River [J]. Journal of Applied Basic and Engineering Sciences, 2009, 17(05): 652-658.
[35]Zhang Yimin, Zhang Yongchun, Zhang Longjiang, et al. Effects of lake hydrodynamic dynamics on cyanobacteria growth [J]. China Environmental Science, 2007, (05): 707-711.
[36]Zhou Luhong, Gu Xiaohong, Zeng Qing-Fei, et al. Short-term prediction of chlorophyll-a concentration in different lakes of Taihu Lake using BP neural networks [J]. Chinese Journal of Water Ecology, 2012, 33(04): 1-6.
[37]Li Shuang Zhao. Distribution characteristics of chlorophyll in the Bohai Sea based on MODIS data and hydrodynamic model [D]. Tianjin University, 2017.
[38]Li Feipeng, Zhang Haiping, Chen Ling. Study on Spatial and temporal distribution of environmental factors and chlorophyll-a in small closed water bodies [J]. Environmental Science, 2013, 34(10): 3854-3861.
[2]Zhu G. W., Qin B. Q., Zhang Y. L., et al. Changes and influencing factors of chlorophyll-a and nutrientsalts in northern Taihu Lake from 2005 to 2017 [J]. Journal of Lake Science, 2018, 30 (2): 279-295.
[3]Ma Tengfei, Luo Hanjin, Li Zhimin, et al. Trend analysis of eutrophication of water source reservoir andconstruction of early warning model [J]. Environmental Science and Technology, 2019, 43 (05): 145-153. (in Chinese)
[4]Peppam, Vasilakosc, Kavroudakisd. Eutrophication Monitoring for Lake Pamvotis, Greece, Using Sentinel-2 Data [J]. Internationa lJournal of Geo-Information, 2020, 9 (3): 143.
[5]Liu Yu, Zhu Danyao. Inversion of chlorophyll-a concentration in Jingpo Lake based on Landsat8 OLI data [J]. Hubei Agricultural Sciences, 2019, 60(23): 157-162.
[6]Guo S. J, Wang X J, Han P. L, et al. Spatial and temporal characteristics of chlorophyll-a concentration and its influencing factors in Danjiangkou Reservoir [J]. Journal of Lake Sciences, 2021, 33(02): 366-376.
[7]Li, Y., Zhang, Y., Shi, K, et al. Spatiotemporal dynamics of chlorophyll-a in a large reservoir as derivedfrom Landsat8 OLI data: understanding its driving and restrictive factors. Environ. Sci. Pollut. Res. 25, 1359–1374 (2018).
[8]Allan, M. G., Hamilton, D. P., Hicks, B. J., & Brabyn, L. (2011). Landsat remote sensing of chlorophyll-a concentrations in central North Island lakes of New Zealand. International Journal of Remote Sensing, 32 (7), 2037–2055.
[9]Rodriguez-Lopez, Lien, et al. “Spatio-temporal analysis of chlorophyll in six Araucanian lakes of Central-South Chile from Landsat imagery.” Ecol. Informatics 65 (2021): 101431.
[10]Barraza-Moragaf, Alcayagah, Pizarroa. et al. Estimation of Chlorophyll-a Concentrations in Lanalhue Lake Using Sentinel-2 MSI Satellite Images. RemoteSensing. 2022; 14 (22): 5647.
[11]Li Suju, Wu Qian, Wang Xuejun, et al. Relationship between chlorophyll content and reflectance spectral characteristics of phytoplankton in Chaohu Lake [J]. Journal of Lake Sciences, 2002 (03): 228-234.
[12]Ma Ronghua, Dai Jinfang. Estimation of chlorophyll and suspended matter contents in Taihu Lake based on Landsat ETM and measured spectra [J]. Journal of Lake Science, 2005 (02): 97-103.
[13]Li Yongliu. Remote sensing retrieval of chlorophyll-a concentration in Karst Plateau lakes [D]. Guizhou Normal University, 2022.
[14]Xiang Yabo, Zhang Chunping, Wu Zhiguo, et al. Inversion of chlorophyll-a in sand lake based on Landsat8 data [J]. Land and Natural Resources Research, 2022, (01): 88-91.
[15]Liu Chong, Zhu Liping, Wang Junbo, et al. Remote sensing retrieval of lake transparency in the Tibetan Plateau based on MODIS [J]. Progress in Geography, 2017, 36(05): 597-609.
[16]Tao Xingyu, Liu Jinbao, Dun Yu Duoji, et al. Retrieval of chlorophyll-A concentration in typical lakes in Tibet based on MODIS [J]. China Environmental Monitoring, 2019, 39(1): 231-240. (in Chinese)
[17]Hao Meiyu, Zhu Huan, Xiong Xiong, et al. Distribution characteristics and genetic analysis of Chaetochetes in Qinghai Lake [J]. Chinese Journal of Hydrobiology, 2019, 44(05): 1152-1158.
[18]Chen Xue-min, Han Bing, Wang Lili, et al. Correlation analysis of total phosphorus, water temperature, salinity and chlorophyll-a in Qinghai Lake [J]. Journal of Agro-Environmental Science, 2013, 32(2): 333-337.
[19]Qin Boqiang, Shi Yafeng. Hydrological characteristics and causes of water level decline in Qinghai Lake [J]. Acta Geographica Sinica, 1992, (03): 267-273.
[20]Zhang Zhijun, Wang Ru, Yao Yue, et al. Inversion of suspended matter concentration in Qinghai Lake based on Zizian-1 02D hyperspectral satellite image [J]. Remote Sensing Technology and Application, 2019, 38(5): 1159-1166.
[21]Sun Shiju, Xu Hao, Wu Yan-Lan, et al. Inversion of chlorophyll-a concentration in Chaohu Lake and Nanfeihe River based on Sentinel-2 satellite remote sensing image [J]. Chinese Journal of Water Ecology, 2019, 44(5): 58-66.
[22]Bao Xishun, Sen De Rima, Li Chunsheng. Inversion of chlorophyll-a in Hasu sea based on high-resolution remote sensing images [J]. Inner Mongolia Water Resources, 2024, (2):23-24.
[23]Li Lei, Zhang Hongmei, Xiong Zhiling, et al. Inversion model of chlorophyll-a concentration in coastal waters based on ridge regression [J]. Jiangxi Water Resources Science and Technology, 2024, 50(4): 235-241.
[24]Li Nan. Absorption spectral decomposition of phytoplankton in the East China Sea considering population structure [D]. Nanjing University of Information Science and Technology, 2020.
[25]Miao Shiyu, Liu Yang, Li Chengyan, et al. Spatial and temporal distribution of Chl-a concentration in Qinghai Lake and its correlation with environmental factors [J]. Journal of Qinghai University, 2019, 38(03): 89-94+106.
[26]Shu Xiaozhou, Yin Qiu, Kuang Dingbo. Relationship between chlorophyll concentration and reflection spectral characteristics of algae in inland water [J]. Journal of Remote Sensing, 2000, (01):41-45.
[27]Sun Shaojie. Estimation and diurnal variation of chlorophyll-a concentration in Taihu Lake based on GOCI [D]. Nanjing University, 2013.
[28]Zhong Dan, Li Haojie, Fan Shuo, et al. Retrieval of chlorophyll-a concentration in nine plateau lakes in Yunnan Province based on MODIS data [J]. Chinese Journal of Ecology, 2017, 36(01): 277-286.
[29]Zhang Qin. Inversion and spatiotemporal variation of suspended sediment and chlorophyll-a concentrations in the Pearl River Estuary based on HY-1CCZI remote sensing image [D]. Guangzhou University, 2024.
[30]Cong Lu. Study on the correlation between Holocene lake evolution and eolian sediments on the Tibetan Plateau [D]. Qinghai Institute of Salt Lake Research, Chinese Academy of Sciences, 2021.
[31]Lanzhou Institute of Geology, Institute of Hydrobiology, Institute of Microbiology, Chinese Academy of Sciences, et al. Comprehensive survey report of Qinghai Lake [M]. Beijing: Science Press, 1979.
[32]Yuan Hong, Hao Lewei, Wang Qi, et al. Hydrodynamic characteristics of Qinghai Lake under prevailing risk control [J]. Yellow River, 2016, 38(03): 51-55. (in Chinese)
[33]Li S. T., Wang Q., Hao L. W., et al. (2018) (eds.). Hydrodynamic characteristics of Qinghai Lake and their response to sedimentary filling. Abstracts of the 15th National Conference on Palaeogeography and Sedimentology (pp.584). Key Laboratory of Petroleum Resources Research of Gansu Province/Key Laboratory of Petroleum Resources Research of Chinese Academy of Sciences; University of Chinese Academy ofSciences.
[34]Wang Lingling, Dai Huichao, CAI Qinghua. Numerical prediction and correlation of hydrodynamic factorsand chlorophyll-a distribution in Xiangxi River [J]. Journal of Applied Basic and Engineering Sciences, 2009, 17(05): 652-658.
[35]Zhang Yimin, Zhang Yongchun, Zhang Longjiang, et al. Effects of lake hydrodynamic dynamics on cyanobacteria growth [J]. China Environmental Science, 2007, (05): 707-711.
[36]Zhou Luhong, Gu Xiaohong, Zeng Qing-Fei, et al. Short-term prediction of chlorophyll-a concentration in different lakes of Taihu Lake using BP neural networks [J]. Chinese Journal of Water Ecology, 2012, 33(04): 1-6.
[37]Li Shuang Zhao. Distribution characteristics of chlorophyll in the Bohai Sea based on MODIS data and hydrodynamic model [D]. Tianjin University, 2017.
[38]Li Feipeng, Zhang Haiping, Chen Ling. Study on Spatial and temporal distribution of environmental factors and chlorophyll-a in small closed water bodies [J]. Environmental Science, 2013, 34(10): 3854-3861.
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