Rainfall–Road Synergy and Landslide Risk Mapping in the Nepal Himalayas: A GIS–MCDA Framework with Level-4 Citizen Science Validation

Himalayan catchments face increasing landslide risk from the synergy of monsoon rainfall and unplanned road construction. Traditional top-down mapping often fails to capture localized hazards and socio-economic last mile vulnerabilities. This study developed hybrid framework integrating Geographic Information System (GIS) and Multi-criteria Decision Analysis (MCDA) in Melamchi Nepal. Moving beyond passive crowdsourcing, we implemented a level 4 extreme citizen science approach engaging 28 diverse stakeholders including farmers and individuals with disabilities as active co-analysts for hazard validation and risk interpretation. Primary spatial data were collected using KoboToolbox and validated through a multi-model protocol to mitigate GPS imprecision in high-relief terrain. A weighted linear combination model synthesized seven parameters, utilizing Euclidean distance as a standardized metric for adaptive capacity. Findings reveal that the synergy of rainfall and road construction triggered 58% of landslides, dominating regional geomorphic control. Furthermore, 42 vulnerability individuals reside in high-hazard zones with structurally fragile crude housing, highlighting critical risk accumulation areas. By bridging local temporal memory with scientific GIS-MCDA, the human centered approach transforms static record into dynamic tools for evacuation logic. This research provides a scalable blueprint for institutionalizing bottom-up inventories within Nepal’s DRRM act 2017 transitioning from reactive rescue to proactive, evidence-based resilience.