Assessment of The trophic state and Chlorophyll-a concentrations using Landsat OLI in Karaoun reservoir, Lebanon

Fadel, Ali; Faour, Ghaleb; Slim, Kamal

doi:10.22453/lsj-017.2.130145

Cited by 19 publications

(3 citation statements)

References 38 publications

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“…According to our study findings, the logchl-a predictive model based on spectral indices incorporated OLI bands 2 (blue), 3 (green), 4 (red), 5 (NIR) and 7 (swir2) with R equal to 0.58 [13,16,62,69] used similar bands for the estimation of chlorophyll-a in lakes and reservoirs and more particular vegetation indices and bands TM and ETM 1 (blue), 2 (green) and 4 (NIR). Reference [62] used the NDVI in Laguna Chascomús in relation to Chl-a estimation for its optical characteristics and because it is sensitive to the pigment absorption.…”

Section: Discussionmentioning

confidence: 72%

An Appraisal of the Potential of Landsat 8 in Estimating Chlorophyll-a, Ammonium Concentrations and Other Water Quality Indicators

et al. 2018

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In-situ monitoring of lake water quality in synergy with satellite remote sensing represents the latest scientific trend in many water quality monitoring programs worldwide. This study investigated the suitability of the Operational Land Imager (OLI) instrument onboard the Landsat 8 satellite platform in accurately estimating key water quality parameters such as chlorophyll-a and nutrient concentrations. As a case study the largest freshwater body of Greece (Trichonis Lake) was used. Two Landsat 8 images covering the study site were acquired on 30 October 2013 and 30 August 2014 respectively. Near concurrent in-situ observations from two water sampling campaigns were also acquired from 22 stations across the lake under study. In-situ measurements (nutrients and chlorophyll-a concentrations) were statistically correlated with various spectral band combinations derived from the Landsat imagery of year 2014. Subsequently, the most statistically promising predictive models were applied to the satellite image of 2013 and validation was conducted using in-situ data of 2013 as reference. Results showed a relatively variable statistical relationship between the in-situ and reflectances (R logchl-a: 0.58, R NH 4 + : 0.26, R chl-a: 0.44). Correlation coefficient (R) values reported of up to 0.7 for ammonium concentrations and also up to 0.5 and up to 0.4 for chl-a concentration and chl-a concentrations respectively. These results represent a higher accuracy of Landsat 8 in comparison to its predecessors in the Landsat satellites series, as evidenced in the literature. Our findings suggest that Landsat 8 has a promising capability in estimating water quality components in an oligotrophic freshwater body characterized by a complete absence of any quantitative, temporal and spatial variance, as is the case of Trichonis lake. Yet, even with the presence of a lot of ground information as was the case in our study, a quantitatively accurate estimation of water quality constituents in coastal/inland waters remains a great challenge. The launch of sophisticated spaceborne sensing systems, such as that of Landsat 8, can assist in improving our ability to estimate freshwater lake properties from space.

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Section: Discussionmentioning

confidence: 72%

An Appraisal of the Potential of Landsat 8 in Estimating Chlorophyll-a, Ammonium Concentrations and Other Water Quality Indicators

et al. 2018

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“…Performing the contextualization of SDG 6 will create the baseline for the continuous monitoring of measured indicators in the basin. Temsah, M., Tarhini, K., Fadel, A., & Slim, K. (2016) Weinthal, E, Sowers, J. (2020).…”

Section: Resultsmentioning

confidence: 99%

Sustaining the ecological functions of the Litani River Basin, Lebanon

Darwish

Shaban

Masih

et al. 2021

International Journal of River Basin Management

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Although Lebanon has the highest mean annual rainfall of all Middle Eastern countries, it is affected by water stress, negatively impacting agricultural food production, energy generation, and public health. The Bekaa Plain, where the Litani River Basin (LRB) is located, suffers serious water quality and quantity problems, which threaten agricultural productivity and public health. Most of the domestic and industrial water in the basin is left untreated. This study investigates prevailing water management issues in the basin. The analysis provides a critical reflection on the water quality and quantity indicators using Sustainable Development Goal 6 (SDG 6), to 'ensure availability and sustainable management of water and sanitation for all'. Results based on the author's observations and evidence from published reports and papers, since the early nineties, showed the existing management approaches are fall short to mitigate the negative impact of the environmental problems in the LRB, particularly low water quality (indicator 6.3) and inefficient water use (indicator 6.4). Progress on achieving sustainable water management (indicator 6.5) in the LRB is limited. Persistent environmental challenges remain due to weak governance, insufficient capacity, and law enforcement, which must be targeted by a public-private partnership.

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“…The most recent research depicting seasonal changes in the abundance and production of phytoplankton in the eastern-most oligotrophic coast of the Levantine Basin was conducted 20 to 30 years ago and was incomplete (Azov 1991). Monitoring the phytoplankton community can be done through classical field visits (Fadel 2014) and remote sensing imagery (Fadel et al 2016;Pinardi et al 2018;Sharaf et al 2019). Biogeochemical modeling has also been used to perceive the growing complexity with the increase in variables (Fadel et al 2017;Vinçon-Leite et al 2017).…”

Section: Introductionmentioning

confidence: 99%

On the use of validated ocean models to investigate the evolution of primary productivity in the Levantine Sea

Kanj

Fadel

2020

Limnological Review

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Marine ecosystems are vital natural resources that contribute to the global biogeochemical cycle, food, and energy production. In order to monitor and evaluate variations of different factors for decision making processes, validated ecosystem models were used in this study to analyze the evolution of different variables: temperature and salinity concentrations (from 1987 to 2014) and nitrate, phosphate, dissolved oxygen, chlorophyll concentrations, and phytoplankton biomass (from 1999 to 2014) in four sites (from 0 to 66 m depth) along the Levantine Sea: Lebanon, Turkey, Egypt and in the Open Sea. Principal component analysis and TRIX were then applied. Spatio-temporal analysis and PCA results showed that phytoplankton biomass is temporally affected by temperature and nutrients (in all stations) as well as salinity in some cases, in addition to its decrease with depth. TRIX analysis showed that all stations had higher primary productivity, in the first half of the year (January-May). Intense anthropogenic activities in Turkey and Egypt have altered the ecosystem’s stability and affected the phytoplankton biomass.

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Assessment of The trophic state and Chlorophyll-a concentrations using Landsat OLI in Karaoun reservoir, Lebanon

Cited by 19 publications

References 38 publications

An Appraisal of the Potential of Landsat 8 in Estimating Chlorophyll-a, Ammonium Concentrations and Other Water Quality Indicators

An Appraisal of the Potential of Landsat 8 in Estimating Chlorophyll-a, Ammonium Concentrations and Other Water Quality Indicators

Sustaining the ecological functions of the Litani River Basin, Lebanon

On the use of validated ocean models to investigate the evolution of primary productivity in the Levantine Sea

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