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Articles

An assessment of chlorophyll-a concentration spatio-temporal variation using Landsat satellite data, in a small tropical reservoir

, , , , &
Pages 1130-1143 | Received 19 Nov 2014, Accepted 11 Feb 2015, Published online: 27 Mar 2015
 

Abstract

Traditional approaches to monitoring aquatic systems are often limited by the need for data collection which often is time-consuming, expensive and non-continuous. The aim of the study was to map the spatio-temporal chlorophyll-a concentration changes in Malilangwe Reservoir, Zimbabwe as an indicator of phytoplankton biomass and trophic state when the reservoir was full (year 2000) and at its lowest capacity (year 2011), using readily available Landsat multispectral images. Medium-spatial resolution (30 m) Landsat multispectral Thematic Mapper TM 5 and ETM+ images for May to December 1999–2000 and 2010–2011 were used to derive chlorophyll-a concentrations. In situ measured chlorophyll-a and total suspended solids (TSS) concentrations for 2011 were employed to validate the Landsat chlorophyll-a and TSS estimates. The study results indicate that Landsat-derived chlorophyll-a and TSS estimates were comparable with field measurements. There was a considerable wet vs. dry season differences in total chlorophyll-a concentration, Secchi disc depth, TSS and turbidity within the reservoir. Using Permutational multivariate analyses of variance (PERMANOVA) analysis, there were significant differences (p < 0.0001) for chlorophyll-a concentration among sites, months and years whereas TSS was significant during the study months (p < 0.05). A strong positive significant correlation among both predicted TSS vs. chlorophyll-a and measured vs. predicted chlorophyll-a and TSS concentrations as well as an inverse relationship between reservoir chlorophyll-a concentrations and water level were found (p < 0.001 in all cases). In conclusion, total chlorophyll-a concentration in Malilangwe Reservoir was successfully derived from Landsat remote sensing data suggesting that the Landsat sensor is suitable for real-time monitoring over relatively short timescales and for small reservoirs. Satellite data can allow for surveying of chlorophyll-a concentration in aquatic ecosystems, thus, providing invaluable data in data scarce (limited on site ground measurements) environments.

Acknowledgements

This work was financially supported by the German Academic Exchange Service (DAAD – A/10/02914) and Malilangwe Trust Postgraduate Research Grant to Tatenda Dalu. Special thanks goes to Clemence Chakuya and Patrick Mutizamhepo (University of Zimbabwe); Philemon Chivambu, Pandeni Chitimela, and Pamushana Lodge Tour Guides (Malilangwe Wildlife Reserve), for their assistance during fieldwork. Our appreciation goes to Elizabeth Munyoro of the Department of Biological Sciences, University of Zimbabwe for all her support during the study. We would also like thank NASA for providing Landsat images of the area under study.

Additional information

Funding

This work was financially supported by the German Academic Exchange Service (DAAD – A/10/02914) and Malilangwe Trust Postgraduate Research Grant to Tatenda Dalu.

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