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A QGIS -plugin for gully erosion modeling.
- Source :
-
Earth Science Informatics . Dec2023, Vol. 16 Issue 4, p3269-3282. 14p. - Publication Year :
- 2023
-
Abstract
- Gully erosion affects the landscape and human life in many ways, including the destruction of agricultural land and infrastructures, altering the hydraulic potential of soils, as well as water availability. Due to climate change, more areas are expected to be affected by gully erosion in the future, threatening especially low-income agricultural regions. In the past decades, quantitative methods have been proposed to simulate and predict gully erosion at different scales. However, gully erosion is still underrepresented in modern GIS-based modeling and simulation approaches. Therefore, this study aims to develop a QGIS plugin using Python to assess gully erosion dynamics. We explain the preparation of the input data, the modeling procedure based on Sidorchuk's (Sidorchuk A (1999) Dynamic and static models of gully erosion. CATENA 37:401–414.) gully simulation model, and perform a detailed sensitivity analysis of model parameters. The plugin uses topographical data, soil characteristics and discharge information as gully model input. The plugin was tested on a gully network in KwaThunzi, KwaZulu-Natal, South Africa. The results and sensitivity analyses confirm Sidorchuck's earlier observations that the critical runoff velocity is a main controlling parameter in gully erosion evolution, alongside with the slope stability threshold and the soil erodibility coefficient. The implemented QGIS plugin simplifies the gully model setup, the input parameter preparation as well as the post-processing and visualization of modelling results. The results are provided in different data formats to be visualized with different 3D visualization software tools. This enables a comprehensive gully assessment and the derivation of respective coping and mitigation strategies. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 18650473
- Volume :
- 16
- Issue :
- 4
- Database :
- Academic Search Index
- Journal :
- Earth Science Informatics
- Publication Type :
- Academic Journal
- Accession number :
- 174096712
- Full Text :
- https://doi.org/10.1007/s12145-023-01092-7