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Assessment of water quality parameters using temporal remote sensing spectral reflectance in arid environments, Saudi Arabia

Elhag Mohamed, Gitas Ioannis Zois, Othman Anas, Bahrawi Jarbou A., Gikas Petros

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URIhttp://purl.tuc.gr/dl/dias/50837AFB-B477-40F9-8E71-2B408B1A8179-
Identifierhttps://doi.org/10.3390/w11030556-
Identifierhttps://www.mdpi.com/2073-4441/11/3/556-
Languageen-
Extent14 pagesen
TitleAssessment of water quality parameters using temporal remote sensing spectral reflectance in arid environments, Saudi Arabiaen
CreatorElhag Mohameden
CreatorGitas Ioannis Zoisen
CreatorOthman Anasen
CreatorBahrawi Jarbou A.en
CreatorGikas Petrosen
CreatorΓκικας Πετροςel
PublisherMDPIen
Content SummaryRemote sensing applications in water resources management are quite essential in watershed characterization, particularly when mega basins are under investigation. Water quality parameters help in decision making regarding the further use of water based on its quality. Water quality parameters of chlorophyll a concentration, nitrate concentration, and water turbidity were used in the current study to estimate the water quality parameters in the dam lake of Wadi Baysh, Saudi Arabia. Water quality parameters were collected daily over 2 years (2017-2018) from the water treatment station located within the dam vicinity and were correspondingly tested against remotely sensed water quality parameters. Remote sensing data were collected from Sentinel-2 sensor, European Space Agency (ESA) on a satellite temporal resolution basis. Data were pre-processed then processed to estimate the maximum chlorophyll index (MCI), green normalized difference vegetation index (GNDVI) and normalized difference turbidity index (NDTI). Zonal statistics were used to improve the regression analysis between the spatial data estimated from the remote sensing images and the nonspatial data collected from the water treatment plant. Results showed different correlation coefficients between the ground truth collected data and the corresponding indices conducted from remote sensing data. Actual chlorophyll a concentration showed high correlation with estimated MCI mean values with an R2 of 0.96, actual nitrate concentration showed high correlation with the estimated GNDVI mean values with an R2 of 0.94, and the actual water turbidity measurements showed high correlation with the estimated NDTI mean values with an R2 of 0.94. The research findings support the use of remote sensing data of Sentinel-2 to estimate water quality parameters in arid environments.en
Type of ItemPeer-Reviewed Journal Publicationen
Type of ItemΔημοσίευση σε Περιοδικό με Κριτέςel
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2020-08-28-
Date of Publication2019-
SubjectGreen normalized difference vegetation index (GNDVI)en
SubjectMaximum chlorophyll index (MCI)en
SubjectNormalized difference turbidity index (NDTI)en
SubjectSentinel-2en
Bibliographic CitationM. Elhag, I. Gitas, A. Othman, J. Bahrawi and P. Gikas, "Assessment of water quality parameters using temporal remote sensing spectral reflectance in arid environments, Saudi Arabia," Water, vol. 11, no. 3, Mar. 2019. doi: 10.3390/w11030556en

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