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<p>Inland reservoirs in sub-Saharan Africa are increasingly threatened by nutrient enrichment, sediment loading, and organic pollution. Yet, limited resources, sparse sampling networks, and high analytical costs constrain routine water-quality monitoring. Although satellite remote sensing offers a promising alternative for large-scale and repeated assessment, applications that simultaneously evaluate multiple chemical and physical parameters in African reservoirs remain scarce, and the water-quality status of Ngezi Dam in Zimbabwe has received little scientific attention. This study aimed to develop and validate a multi-parameter remote-sensing framework for mapping surface-water quality in Ngezi Dam and identifying spatial pollution patterns. Landsat-8 Collection 2 Level-2 imagery processed in Google Earth Engine was integrated with laboratory-analysed field samples collected across the reservoir, and empirical and band-ratio models were applied to estimate turbidity, total suspended solids, total dissolved solids, chemical oxygen demand, total nitrogen, and total phosphorus, with model performance evaluated using coefficients of determination. The results revealed pronounced spatial heterogeneity, with elevated nutrient and organic-pollution indicators concentrated in the reservoir head and selected nearshore zones, suggesting emerging pollution hotspots. Validation showed moderate to strong agreement between satellite-derived and observed values (R2 = 0.57–0.76). These findings demonstrate that Landsat-based remote sensing, when calibrated with limited field data, provides a cost-effective and scalable approach for multi-parameter water-quality monitoring in data-scarce environments and can support reservoir management, early detection of eutrophication risks, and long-term aquatic ecosystem conservation in Ngezi Dam and comparable African water bodies.</p>

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A remote sensing-based approach to monitor water quality in the Ngezi Dam, Zimbabwe

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月28日

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  • Honour Chinoitezvi,
  • Mercy Sai,
  • Courage Mutema

摘要

Inland reservoirs in sub-Saharan Africa are increasingly threatened by nutrient enrichment, sediment loading, and organic pollution. Yet, limited resources, sparse sampling networks, and high analytical costs constrain routine water-quality monitoring. Although satellite remote sensing offers a promising alternative for large-scale and repeated assessment, applications that simultaneously evaluate multiple chemical and physical parameters in African reservoirs remain scarce, and the water-quality status of Ngezi Dam in Zimbabwe has received little scientific attention. This study aimed to develop and validate a multi-parameter remote-sensing framework for mapping surface-water quality in Ngezi Dam and identifying spatial pollution patterns. Landsat-8 Collection 2 Level-2 imagery processed in Google Earth Engine was integrated with laboratory-analysed field samples collected across the reservoir, and empirical and band-ratio models were applied to estimate turbidity, total suspended solids, total dissolved solids, chemical oxygen demand, total nitrogen, and total phosphorus, with model performance evaluated using coefficients of determination. The results revealed pronounced spatial heterogeneity, with elevated nutrient and organic-pollution indicators concentrated in the reservoir head and selected nearshore zones, suggesting emerging pollution hotspots. Validation showed moderate to strong agreement between satellite-derived and observed values (R2 = 0.57–0.76). These findings demonstrate that Landsat-based remote sensing, when calibrated with limited field data, provides a cost-effective and scalable approach for multi-parameter water-quality monitoring in data-scarce environments and can support reservoir management, early detection of eutrophication risks, and long-term aquatic ecosystem conservation in Ngezi Dam and comparable African water bodies.