Precision Restoration to Minimize Soil Loss in a Watershed in the Atlantic Forest Domain
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Le résumé fourni par la source
ABSTRACT The Turvo River Watershed, located in the Zona da Mata region of Minas Gerais and part of the Doce River Basin, faces serious problems of erosion and soil degradation, which compromise and reduce the quality of local water resources. Given this scenario, it is essential to implement environmental recovery strategies that prioritize the efficient allocation of vegetation zones, which serve as effective agents in reducing erosion caused by surface runoff in areas with exposed soil. The use of geotechnology tools, such as Geographic Information Systems (GIS) and the Unit Stream Power‐Based Erosion Deposition (USPED) model, helps identify areas most susceptible to sediment loss and deposition. Additionally, the application of Genetic Algorithms (GA) to maximize scenario simulations and optimize the placement of vegetation zones is crucial for minimizing erosion rates and achieving results more quickly and accurately. The results indicated that, among the simulated scenarios, erosion and deposition values remained mostly below 0.10 t ha −1 year −1 , characterizing low soil loss. The application of GA reduced erosion by up to 53.85% in the most efficient scenario and increased forest cover by approximately 66.5%, demonstrating its effectiveness in precision environmental restoration. This methodology proved to be useful and applicable to any watershed, serving as an effective tool for environmental management, erosion and sediment deposition studies, and monitoring of natural resources.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Precision Restoration to Minimize Soil Loss in a Watershed in the Atlantic Forest Domain
- Date Crossref
- 29/10/2025
- Éditeur
- Wiley
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Les institutions déclarées
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