Estimación de la erosión hídrica en la microcuenca del río Quevedo con el modelo Rusle
Water erosion is a global problem that causes soil loss and ecosystem degradation due to human activities. The annual soil loss of the upper Vinces river sub-basin is estimated using the Revised Universal Soil Loss Equation, remote sensing techniques and GIS. The factors considered are rainfall eros...
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| Format: | bachelorThesis |
| Language: | spa |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://repositorio.uteq.edu.ec/handle/43000/7013 |
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Add Tag | Summary: | Water erosion is a global problem that causes soil loss and ecosystem degradation due to human activities. The annual soil loss of the upper Vinces river sub-basin is estimated using the Revised Universal Soil Loss Equation, remote sensing techniques and GIS. The factors considered are rainfall erosivity, soil erodibility, length and slope, vegetation cover and conservation practices. The provinces of Los Ríos and Santo Domingo de los Tsáchilas register the highest amount of rainfall, causing landslides and floods. In terms of soil erodibility, two types were identified: Humic Andosols, categorized as 7 and 4, are rich in organic matter and important for agriculture, while Lithosols are more prone to erosion, while slope and length are important factors, with 65% of the micro-watershed having steep slopes and greater risk of erosion in the cantons of Sigchos, Pujilí, La Maná and Santo Domingo. Vegetation cover obtained 51% of moderate category, which corresponds to agricultural use, pastures and annual crops in land use. The results show a potential water erosion of 34% in the cantons of La Maná, Pujilí, Sigchos, Santo Domingo, and Valencia, which are considered without vegetation cover, and a current erosion of 1% in La Maná and Pujilí in the micro-watershed. An environmental management plan was developed to control and prevent erosion, which includes strategies such as reforestation, soil conservation, community training and a contingency plan for risk situations, with the objective of preventing emergencies in the community. This work demonstrates the effectiveness of the RUSLE model integrated with the GIS in estimating soil erosion. Keywords: GIS, Remote Sensing, Climate Change, Sedimentation, Runoff. |
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