Eutrophication and lakes dynamic conditions control the endogenous and terrestrial POC observed by remote sensing: Modeling and application

The sources of particulate organic carbon (POC) determine its conversion, thereby playing an important role in the carbon cycle of lakes. Accurate estimation of the sources and dynamic characteristics of POC is important for understanding the migration and transformation of organic carbon. However,...

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Autores principales:	Zhilong Zhao, Changchun Huang, Lize Meng, Lingfeng Lu, Yongfang Wu, Rong Fan, Shuaidong Li, Zhengwei Sui, Tao Huang, Chulong Huang, Hao Yang, Limin Zhang
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	POC source Carbon cycle Stable isotope Remote sensing Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/8a84ab02e054428980ec8b66e20dfc24
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spelling	oai:doaj.org-article:8a84ab02e054428980ec8b66e20dfc242021-12-01T04:55:35ZEutrophication and lakes dynamic conditions control the endogenous and terrestrial POC observed by remote sensing: Modeling and application1470-160X10.1016/j.ecolind.2021.107907https://doaj.org/article/8a84ab02e054428980ec8b66e20dfc242021-10-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X21005720https://doaj.org/toc/1470-160XThe sources of particulate organic carbon (POC) determine its conversion, thereby playing an important role in the carbon cycle of lakes. Accurate estimation of the sources and dynamic characteristics of POC is important for understanding the migration and transformation of organic carbon. However, the synchronous observation of POC sources with large areas through remote sensing is still challenging because of the complex composition of POC and the optical conditions of inland lakes. In this study, a three-band (1/ Rrs (689)–1/ Rrs (717)) × Rrs (697)) empirical algorithm of POC sources was constructed based on remote sensing reflectance (Rrs(λ)) and the proportion of endogenous POC estimated from the field-measured stable isotope (δ13CPOC) values. The validation and calibration results of the three-band algorithm showed robust performance, with MAPE and RMSE of estimated values and measured values of 10% and 0.07, respectively. The three-band algorithm had good simulation results for the Ocean and Land Color Instrument (OLCI), Moderate Imaging Spectroradiometer (MODIS), Geostationary Ocean Color Imager (GOCI), and Medium Resolution Imaging Spectrometer (MERIS) spectra. The POC sources estimated by the three-band algorithm suggest that the endogenous POC of Taihu Lake in August showed a decreasing trend from 2006 to 2019. The variation in terrestrial POC was slow and stable for both annual and monthly variations. The analysis of POC sources with total phosphorus (TP), total nitrogen (TN), water temperature, and wind speed indicated that terrestrial POC was closely related to wind speed (r = 0.33, P < 0.001), while endogenous POC was significantly associated with TP (r = 0.6, P < 0.001), TN (r = 0.56, P < 0.001), and water temperature (r = 0.49, P < 0.001). The use of remote sensing algorithms to evaluate POC from different sources is convenient and effective; furthermore, it helps to better understand the carbon cycle in lacustrine ecosystems.Zhilong ZhaoChangchun HuangLize MengLingfeng LuYongfang WuRong FanShuaidong LiZhengwei SuiTao HuangChulong HuangHao YangLimin ZhangElsevierarticlePOC sourceCarbon cycleStable isotopeRemote sensingEcologyQH540-549.5ENEcological Indicators, Vol 129, Iss , Pp 107907- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	POC source Carbon cycle Stable isotope Remote sensing Ecology QH540-549.5
spellingShingle	POC source Carbon cycle Stable isotope Remote sensing Ecology QH540-549.5 Zhilong Zhao Changchun Huang Lize Meng Lingfeng Lu Yongfang Wu Rong Fan Shuaidong Li Zhengwei Sui Tao Huang Chulong Huang Hao Yang Limin Zhang Eutrophication and lakes dynamic conditions control the endogenous and terrestrial POC observed by remote sensing: Modeling and application
description	The sources of particulate organic carbon (POC) determine its conversion, thereby playing an important role in the carbon cycle of lakes. Accurate estimation of the sources and dynamic characteristics of POC is important for understanding the migration and transformation of organic carbon. However, the synchronous observation of POC sources with large areas through remote sensing is still challenging because of the complex composition of POC and the optical conditions of inland lakes. In this study, a three-band (1/ Rrs (689)–1/ Rrs (717)) × Rrs (697)) empirical algorithm of POC sources was constructed based on remote sensing reflectance (Rrs(λ)) and the proportion of endogenous POC estimated from the field-measured stable isotope (δ13CPOC) values. The validation and calibration results of the three-band algorithm showed robust performance, with MAPE and RMSE of estimated values and measured values of 10% and 0.07, respectively. The three-band algorithm had good simulation results for the Ocean and Land Color Instrument (OLCI), Moderate Imaging Spectroradiometer (MODIS), Geostationary Ocean Color Imager (GOCI), and Medium Resolution Imaging Spectrometer (MERIS) spectra. The POC sources estimated by the three-band algorithm suggest that the endogenous POC of Taihu Lake in August showed a decreasing trend from 2006 to 2019. The variation in terrestrial POC was slow and stable for both annual and monthly variations. The analysis of POC sources with total phosphorus (TP), total nitrogen (TN), water temperature, and wind speed indicated that terrestrial POC was closely related to wind speed (r = 0.33, P < 0.001), while endogenous POC was significantly associated with TP (r = 0.6, P < 0.001), TN (r = 0.56, P < 0.001), and water temperature (r = 0.49, P < 0.001). The use of remote sensing algorithms to evaluate POC from different sources is convenient and effective; furthermore, it helps to better understand the carbon cycle in lacustrine ecosystems.
format	article
author	Zhilong Zhao Changchun Huang Lize Meng Lingfeng Lu Yongfang Wu Rong Fan Shuaidong Li Zhengwei Sui Tao Huang Chulong Huang Hao Yang Limin Zhang
author_facet	Zhilong Zhao Changchun Huang Lize Meng Lingfeng Lu Yongfang Wu Rong Fan Shuaidong Li Zhengwei Sui Tao Huang Chulong Huang Hao Yang Limin Zhang
author_sort	Zhilong Zhao
title	Eutrophication and lakes dynamic conditions control the endogenous and terrestrial POC observed by remote sensing: Modeling and application
title_short	Eutrophication and lakes dynamic conditions control the endogenous and terrestrial POC observed by remote sensing: Modeling and application
title_full	Eutrophication and lakes dynamic conditions control the endogenous and terrestrial POC observed by remote sensing: Modeling and application
title_fullStr	Eutrophication and lakes dynamic conditions control the endogenous and terrestrial POC observed by remote sensing: Modeling and application
title_full_unstemmed	Eutrophication and lakes dynamic conditions control the endogenous and terrestrial POC observed by remote sensing: Modeling and application
title_sort	eutrophication and lakes dynamic conditions control the endogenous and terrestrial poc observed by remote sensing: modeling and application
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/8a84ab02e054428980ec8b66e20dfc24
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Eutrophication and lakes dynamic conditions control the endogenous and terrestrial POC observed by remote sensing: Modeling and application

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