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Novel methods for monitoring low chlorophyll-a concentrations in the large, oligotrophic Lake Malawi/Nyasa/Niassa.
Makwinja, Rodgers; Inagaki, Yoshihiko; Tesfamichael, Solomon G; Curtis, Christopher J.
Affiliation
  • Makwinja R; Department of Geography, Environmental Management and Energy Studies, University of Johannesburg, PO Box 524, Auckland Park, 2600, South Africa. Electronic address: rmakwinja@uj.ac.za.
  • Inagaki Y; Department of Civil and Environmental Engineering, Waseda University, Shinjuku, Tokyo, 169-8555, Japan.
  • Tesfamichael SG; Department of Geography, Environmental Management and Energy Studies, University of Johannesburg, PO Box 524, Auckland Park, 2600, South Africa.
  • Curtis CJ; Department of Geography, Environmental Management and Energy Studies, University of Johannesburg, PO Box 524, Auckland Park, 2600, South Africa.
J Environ Manage ; 364: 121462, 2024 Jul.
Article in En | MEDLINE | ID: mdl-38878578
ABSTRACT
The use of remote sensing for monitoring chlorophyll-a (chla) and modelling eutrophication has advanced over the last decades. Although the application of the technology has proven successful in ocean ecosystems, there is a need to monitor chla concentrations in large, nutrient-poor inland water bodies. The main objective of this study was to explore the utility of publicly available remotely sensed Sentinel-2 (S2) imagery to quantify chla concentrations in the nutrient-deficient Lake Malawi/Niassa/Nyasa (LMNN). A secondary objective was to compare the S2 derived chla with the Global Change Observation Mission-Climate (GCOM-C) chla product that provides uninterrupted data throughout the year. In situ chla data (n = 76) from upper, middle and lower sections of LMNN served as a reference to produce remote sensing-based quantification. The line-height approach method built on color index, was applied for chla concentrations below 0.25 mg/m3. Moderate Resolution Imaging Spectroradiometer 3-band Ocean Color (MODIS-OC3) - was adopted when chla concentration exceeded 0.35 mg/m3. The MODIS-OC3 algorithm had generic model coefficients that were calibrated for each in situ sample by using GCOM-C Level 3 chla product. A weighted sum of the two algorithms was applied for chla concentrations that fell between 0.25 and 0.35 mg/m3. The above methods were then applied to the S2 data to estimate chla at each pixel. S2 showed a promising accuracy in distinguishing chla levels (MSE = 0.18) although the chla range in the lake was relatively narrow, particularly using the locally calibrated coefficients of the OC3 algorithm. Chla distribution maps produced from the S2 data revealed limited spatial variation across the LMNN with higher concentrations identified in the coastal areas. S2-derived chla and GCOM-C chla comparison showed fairly good similarity between the two datasets (MSE = 0.205). Accepting this similarity, monthly chla dynamics of the lake was profiled using the temporally reliable GCOM-C data that showed oligotrophic conditions (1.7 mg/m3 to 3.2 mg/m3) in most parts of the lake throughout the year. The study's findings advance the potential for both remote sensing approaches to provide vital information at the required spatial and temporal resolution for evidence-based policymaking and proactive environmental management in an otherwise very data deficient region.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Lakes / Environmental Monitoring / Chlorophyll A Country/Region as subject: Africa Language: En Journal: J Environ Manage Year: 2024 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Lakes / Environmental Monitoring / Chlorophyll A Country/Region as subject: Africa Language: En Journal: J Environ Manage Year: 2024 Document type: Article