Estimation of Chlorophyll-A Concentration in Choghakhor wetland using remote sensing and in-situ measurements

Document Type : Animal environment

Authors

Department of environmental science, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran

Abstract

 The usage of water resources requires an understanding of water quality, since water resources are the ultimate recipients of pollution from human activities. The main objectives of this study were to investigate the water quality in Choghakhor wetland located in Chaharmahal and Bakhtiari Province using field surveys and to measure the chlorophyll A, using satellite images and to calculate the correlation between the amount of chlorophyll A derived from satellite images and field measurements. For this purpose, water quality of wetland was evaluated using laboratory methods and chlorophyll A was measures using NDCI index and laboratory method. Parameters measured using laboratory methods were DO, EC, PH, TDS, TSS, chlorophyll A, nitrates, water depth, water temperature and the ambient temperature. Sampling was done in 4 stations in the wetland and all tests were carried out within 24 hours after sampling in the laboratory. Statistical analysis of data was done by two-way ANOVA and mean comparison was performed based on Duncan's multiple range test at significance level of 5 percent. Chlorophyll A concentration was measured using NDCI index in ArcGIS 10.3 software. The amount of chlorophyll A derived from satellite images were correlated against the amount of chlorophyll A derived from water sampling and results showed a good correlation (R2 =0.92) between the data obtained from remote sensing and data driven from field survey. This showed that satellite imagery could be used as a useful tool to estimate the amount of chlorophyll A.

Keywords

References

  1. Ayeni, A.O. and Adesalu, T.A., 2018. Validating chlorophyll-a concentrations in the Lagos Lagoon using remote sensing extraction and laboratory fluorometric methods. MethodsX. Vol. 5, pp: 1204-1212.
  2. Abdelmalik, K.W., 2018. Role of statistical remote sensing for Inland water quality parameters prediction. The Egyptian Journal of Remote Sensing and Space Sciences. Vol. 21, No. 2, pp: 193-200.
  3. Chawira, M.; Dube, T. and Gumindoga, W., 2013. Remote sensing based water quality monitoring in Chivero and Manyame lakes of Zimbabwe. Physics and Chemistry of the Earth. Vol. 66, pp: 38-44.
  4. Haji Gholizadeh, M.;Melesse, A.M. and Reddi, L., 2016. A Comprehensive Review on Water Quality Parameters Estimation Using Remote Sensing Techniques. Sensors. Vol. 16, No. 8, pp: 1-43.
  5. Howarth, R.W., 1988. Nutrient limitation of net primary production in marine ecosystems. Annual Review of Ecology and Systematics. Vol. 19, pp: 89-110.
  6. Li, X.; Manman, C. and Anderson, B.C., 2009. Design and performance of a water quality treatment wetland in a public park in Shanghai, China. Ecological Engineering. Vol. 35, pp: 18-24.
  7. Mohamed, M.F., 2015. Satellite data and real time stations to improve water quality of Lake Manzalah. Water Science. Vol. 29, pp: 68-76.
  8. Masocha, M.; Murwira, A.; Magadza, C.H.D.; Hirji, R. and Dube, T., 2017. Remote sensing of surface water quality in relation to catchment condition in Zimbabwe. Physics and Chemistry of the Earth. Vol. 100, pp: 13-18.
  9. Mishra, S. and Mishra, R., 2012. Normalized difference chlorophyll index: A novel model for remote estimation of chlorophyll-a concentration in turbid productive waters. Remote Sensing of Environment. Vol. 117, pp: 394-406.
  10. Mushtaq, F. and Nee Lala, M.G., 2016. Remote Estimation of Water Quality Parameters of Himalayan Lake (Kashmir) using Landsat 8 OLI Imagery. Geocarto International. Vol. 32, pp: 274-285.
  11. Nemati varnosfaderany, M.; Mirghaffary, N.; Ebrahimi, E. and Saffianian, A., 2008. Water quality assessment in an arid region using a water quality index. Water Science and Technology. Vol. 60, No. 9, pp: 2319-2327.
  12. Subiyanto, S.; Ramadhanis, Z. and Hafidh Baktiar, A., 2018. Integration of remote sensing technology using Sentinel-2A Satellite images for fertilization and water pollution analysis in Estuaries Inlet of Semarang Eastern Flood Canal. E3S Web of Conferences. Vol. 31, pp: 1-6.
  13. Watanabe, F.; Alcântara, E.; Rodrigues, T.; Rotta, L.; Bernardo, N. and Imai N., 2017. Remote sensing of the chlorophyll-a based on OLI/Landsat-8 and MSI/Sentinel-2A (Barra Bonita reservoir, Brazil). Annals of the Brazilian Academy of Sciences. Vol. 31, pp: 1-14.

 

Journal of Animal Environment
Volume 12, Issue 3
June 2020
Pages 475-486

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