A Reproducible Open-Data Workflow for Identifying Coastal Electrical Infrastructure Exposure to Flood and Coastal Hazards: A Comparative Application in Jamaica and Mozambique

Abstract Coastal power grids in small island developing states (SIDS) and low- and middle-income countries (LMICs) face escalating climate threats, yet analytical tools for assessing infrastructure exposure remain fragmented across disciplines, institutionally siloed, and difficult to transfer between national contexts. This paper presents a reproducible, open-data geospatial workflow implemented entirely in QGIS that identifies the exposure of coastal electrical infrastructure to flood and coastal hazards. The workflow integrates three methods: (1) blue spot detection adapted from road drainage engineering, (2) terrain-derived flood susceptibility classification, and (3) coastal proximity analysis through 1 km and 5 km buffer zones. The workflow is applied to Jamaica and Mozambique as contrasting cases, a Caribbean SIDS with near-universal electrification and an LMIC with approximately 36% electrification, using identical global open-data inputs. Jamaica's island geography concentrates coastal exposure (70% of plants within 5 km of the coast), while Mozambique's deltaic terrain dominates inland flood exposure (83% of transmission lines in high susceptibility zones). The contrasting patterns reflect genuine geographic differences: island geography concentrates generation coastally, while continental deltaic terrain amplifies inland flood exposure. The workflow operates without proprietary GIS software or commercial hazard data, and its outputs are structured as standardised exposure tables suitable for integration with downstream energy planning and investment appraisal tools.