An Overall Evaluation of Water Transparency in Lake Malawi from MERIS Data

Vundo, Augusto and Matsushita, Bunkei and Jiang, Dalin and Gondwe, Mangaliso and Hamzah, Rossi and Setiawan, Fajar and Fukushima, Takehiko (2019) An Overall Evaluation of Water Transparency in Lake Malawi from MERIS Data. Remote Sensing, 11 (3). p. 279. ISSN 2072-4292

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Abstract

Lake Malawi is an important water resource in Africa. However, there is no routine monitoring of water quality in the lake due to financial and institutional constraints in the surrounding countries. A combination of satellite data and a semi-analytical algorithm can provide an alternative for routine monitoring of water quality, especially in developing countries. In this study, we first compared the performance of two semi-analytical algorithms, Doron11 and Lee15, which can estimate Secchi disk depth (SD) from satellite data in Lake Malawi. Our results showed that even though the SD estimations from the two algorithms were very highly correlated, the Lee15 outperformed the Doron11 in Lake Malawi with high estimation accuracy (RMSE = 1.17 m, MAPE = 18.7%, R = 0.66, p < 0.05). We then evaluated water transparency in Lake Malawi using the SD values estimated from nine years of Medium Resolution Imaging Spectrometer (MERIS) data (2003–2011) with the Lee15 algorithm. Results showed that Lake Malawi maintained four water transparency levels throughout the study period (i.e., level 1: SD > 12 m; level 2: SD between 6–12 m; level 3: SD between 3–6 m; level 4: SD between 1.5–3 m). The level 1 and 2 water areas tended to shift or trade places depending on year or season. In contrast, level 3 and 4 water areas were relatively stable and constantly distributed along the southwestern and southern lakeshores. In general, Lake Malawi is dominated by waters with SD values larger than 6 m (>95%). This study represents the first overall and comprehensive analysis of water transparency status and spatiotemporal variation in Lake Malawi.

Item Type: Article
Uncontrolled Keywords: Secchi Disk Depth; Semi-analytical algorithm; remote sensing; spatiotemporal variation
Subjects: Natural Resources & Earth Sciences
Depositing User: Maria Regina Karunia
Date Deposited: 11 Mar 2026 03:11
Last Modified: 11 Mar 2026 03:11
URI: https://karya.brin.go.id/id/eprint/58036

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