A systematic review of geospatial and meteorological approaches to flood risk assessment and monitoring

Abstract

Abstract Increasing flood frequency, exposure and impacts associated with climate change, rapid urbanisation, and environmental change have intensified the need for robust flood risk assessment and monitoring frameworks. This systematic review synthesises advances in geospatial, hydrological, hydraulic, meteorological, and artificial intelligence (AI)-based approaches to assess their methodological development, operational applicability and emerging research priorities. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, 2,150 records were retrieved from Web of Science and Google Scholar. After duplicate removal, 1720 records were screened, 500 full-text articles were assessed for eligibility, and 190 studies published between 1985 and 2025 were included in the final thematic synthesis. Four principal methodological domains emerged from the reviewed evidence: geospatial technologies, hydrological and hydraulic modelling, meteorological approaches, and AI-enabled flood susceptibility, prediction and forecasting. Cross-cutting operational constraints included data availability and quality, inconsistent validation, computational requirements, model interpretability and transferability, interoperability and institutional readiness. Across individual study contexts, integrated geospatial-AI approaches frequently reported strong predictive capability and enhanced spatial analysis and decision support potential. However, substantial heterogeneity in datasets, spatial resolutions, validation procedures and performance metrics limits direct quantitative comparison across studies, particularly across contrasting hydroclimatic and data-constrained settings. This review advances the field through a comprehensive comparative synthesis of flood risk assessment methodologies and proposes a review-derived conceptual framework that explicitly connects methodological capability with validation, operational readiness and decision support. The findings identify key methodological advances, persistent implementation barriers and future priorities for developing more transparent, transferable, scalable and operationally robust flood risk assessment systems to support climate adaptation and disaster risk reduction.