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<p>The Soubré hydropower plant (HPP), the largest in&#xa0;Côte d’Ivoire&#xa0;in terms of installed capacity, has&#xa0;faced aquatic plants proliferation in its reservoir lake&#xa0;since its recent commissioning in 2017. This study applies the DKPR (accessibility to the aquatic environment, D; hydrological functioning of soil and subsoil, K; physiography, P; and rainfall erosivity, R) method to assess Soubré lake’s vulnerability to pollution while evaluating the impact of image type and classification method on the&#xa0;final vulnerability map. The data included geological, pedological, rainfall&#xa0;data (1961–2022), a Digital Elevation Model (DEM), and 2023 Landsat 9 and Sentinel 2 satellite images.&#xa0;Image classification was performed using Maximum Likelihood (ML) and Random Forest (RF), with their performance assessed using Kappa coefficient (Kc) and Overall Accuracy (OA). The influence&#xa0;of the Land Use (LU) map on&#xa0;the K criterion and final maps was&#xa0;also&#xa0;examined. The results showed good performance of both ML and RF algorithms, with Kc and OA &gt; 0.6 except&#xa0;for ML’s Kc with Sentinel 2. LU map has no significant impact on the K criterion and the final vulnerability map. Regardless of the LU map, four vulnerability classes (low, moderate, high, and very high) were observed on&#xa0;the final map, with moderate vulnerability being dominant. Around 30% to 40% of the study area was&#xa0;highly or very highly vulnerable, particularly along the watercourse. These findings highlight the need for proactive monitoring, pollution control, and sustainable lake management strategies.</p>

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Application of the DKPR Method to Tropical Conditions Using an Integrated Approach to Assess the Vulnerability of Soubré Lake (Southwest, Côte d’Ivoire)

  • 期刊论文

  • 发表日期：

    2025年4月15日

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  • Yaraba Tuo,
  • Franck Hervé Akaffou,
  • Jules Mangoua Oi Mangoua,
  • Bérenger Koffi,
  • Wawogninlin Brice Coulibaly,
  • Yao Emile Desmond Konan,
  • Brou Dibi

摘要

The Soubré hydropower plant (HPP), the largest in Côte d’Ivoire in terms of installed capacity, has faced aquatic plants proliferation in its reservoir lake since its recent commissioning in 2017. This study applies the DKPR (accessibility to the aquatic environment, D; hydrological functioning of soil and subsoil, K; physiography, P; and rainfall erosivity, R) method to assess Soubré lake’s vulnerability to pollution while evaluating the impact of image type and classification method on the final vulnerability map. The data included geological, pedological, rainfall data (1961–2022), a Digital Elevation Model (DEM), and 2023 Landsat 9 and Sentinel 2 satellite images. Image classification was performed using Maximum Likelihood (ML) and Random Forest (RF), with their performance assessed using Kappa coefficient (Kc) and Overall Accuracy (OA). The influence of the Land Use (LU) map on the K criterion and final maps was also examined. The results showed good performance of both ML and RF algorithms, with Kc and OA > 0.6 except for ML’s Kc with Sentinel 2. LU map has no significant impact on the K criterion and the final vulnerability map. Regardless of the LU map, four vulnerability classes (low, moderate, high, and very high) were observed on the final map, with moderate vulnerability being dominant. Around 30% to 40% of the study area was highly or very highly vulnerable, particularly along the watercourse. These findings highlight the need for proactive monitoring, pollution control, and sustainable lake management strategies.