Assessing Landslide Risk and Mitigation Strategies in Agricultural Communities near the Andes

Thesis Abstract

Landslides present a significant and recurrent geohazard affecting agricultural communities situated near the steep slopes of the Andes, resulting in extensive economic losses, displacement of populations, and adverse environmental impacts. Despite the increasing frequency and severity of landslides driven by climate variability and land use changes, there remains limited comprehensive assessment of landslide risk levels and the effectiveness of existing mitigation strategies within these vulnerable rural populations. This study aims to evaluate landslide risk and identify sustainable mitigation measures applicable to agricultural communities near the Andes, with specific objectives to map landslide susceptibility zones, analyze socio-economic factors influencing risk perception and adaptive capacity, and assess the implementation and efficacy of current mitigation strategies. Employing a mixed-methods research design, the study integrates quantitative spatial analysis with qualitative socio-cultural inquiry. The quantitative component involves a detailed landslide susceptibility assessment utilizing Geographic Information Systems (GIS) and remote sensing data, alongside Multinomial Logistic Regression to model the influence of terrain, land cover, rainfall patterns, and land use on landslide occurrence. The qualitative component explores community perceptions, indigenous knowledge, and the perceived effectiveness of mitigation strategies through semi-structured interviews and focus group discussions with 250 farmers and local authorities across five selected villages. Instrument validity was ensured through expert validation and pilot testing, and data triangulation enhances reliability. Thematic analysis is employed to interpret qualitative data, while quantitative data are analyzed using descriptive statistics and regression models, with significance tested at p<0.05. Expected findings include a detailed landslide susceptibility map identifying high-risk zones correlated with specific topographical and climatic conditions. Socio-economic analysis is anticipated to reveal key knowledge deficits and barriers to effective risk mitigation, including land tenure issues and limited access to technical resources. Insights into community perceptions could highlight gaps between scientific risk assessments and local indigenous knowledge, informing culturally sensitive engagement strategies. The regression analysis is expected to demonstrate a significant relationship between land management practices and landslide occurrence, underscoring the importance of integrated land use planning. The contribution of this research lies in its comprehensive risk assessment model tailored to local contexts, providing a platform for targeted mitigation planning. The study advances understanding of how socio-cultural factors influence risk perception and the adoption of mitigation strategies within rural Andean communities. It also informs policy recommendations for integrating scientific and indigenous knowledge systems in community-based disaster risk reduction initiatives. The main conclusion emphasizes that sustainable landslide mitigation in these communities requires an integrated approach that combines scientifically derived susceptibility assessments with locally relevant mitigation practices and community engagement. It advocates for policies that enhance land management, promote community participation in risk reduction, and improve access to early warning systems and technical support. The study further recommends expanding adaptive capacity through capacity-building programs, strengthening land use regulations, and fostering multi-stakeholder collaboration to ensure resilient and sustainable agricultural livelihoods in landslide-prone regions. This research adds valuable insights into the intersection of geoscience, socio-economic factors, and indigenous knowledge in disaster risk management, providing a replicable framework for similar studies in other mountainous, rural settings globally.