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Journal of Experimental Agriculture International

Journal of Experimental Agriculture International, ISSN: 2457-0591, ISSN: 2231-0606 (Past),Vol.: 19, Issue.: 1


Monitoring Water Quality in a Reservoir of the Semi-arid Region Using Remote Sensing


Janaina Castro De Mendonça1*, Fernando Bezerra Lopes1, Eunice Maia de Andrade1, Francisco Josivan de Oliveira Lima2 and Fernanda Helena Oliveira da Silva1

1Departamento de Engenharia Agrícola, Universidade Federal do Ceará, Campus do PICI Bloco 804, Fortaleza – CE, Caixa Postal 12.168 CEP.: 60450-760, Brasil.

2Fundação Cearense de Meteorologia, Avenida Rui Barbosa, 1246 – Aldeota, Fortaleza – CE, CEP.: 60115-221, Brasil.


Article Information
(1) Moreira Martine Ramon Felipe, Associate Professor, Departamento de Enxeñaría Química, Universidade de Santiago de Compostela, Spain.
(1) Suheyla Yerel Kandemir, Bilecik Seyh Edebali University, Turkey.
(2) Erivaldo Antonio Da Silva, São Paulo State University, Brazil.
Complete Peer review History: http://www.sciencedomain.org/review-history/22168




Aims: The aim of this study was to analyse the use of remote sensing as an alternative in monitoring water quality, and to analyse models that estimate the concentrations of chlorophyll-a (Chl-a) in a reservoir in the semi-arid region.

Place and Duration of Study: Field campaigns were carried out at the Pereira de Miranda reservoir, Pentecoste, in the State of Ceará (CE), at five sampling points, from December 2014 to December 2015.

Methodology: Limnological and spectral data were used, which were collected using a spectroradiometer. The limnological attributes of Chl-a and suspended sediments were analysed in the laboratory, and used to evaluate the spectral responses. Four three-band models were analysed for estimating the concentrations of Chl-a.

Results: The models of Lopes [11] and Gitelson et al. [15] gave the best performance, with respective satisfactory results for R2 of 0.75 and 0.79, MAE errors of 6.74 (μg.L-1) and 6.51 (μg.L-1), an NSE of 0.74 for both models, and RMSE of 9.01 (μg.L-1) and 8.93 (μg.L-1). From these results, the models were selected and applied in the campaigns of April and September 2015.

Conclusion: The use of remote sensing is therefore viable in estimating concentrations of Chl-a, collaborating to the development of research and in water resource management at lower cost.


Keywords :

Limnological attributes; Chlorophyll-a; bio-optical models.


Full Article - PDF    Page 1-12    Article Metrics


DOI : 10.9734/JEAI/2017/37913

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