A Review of Flood Research: Trends, Methods, and Solutions

Abstract

Urban flooding has emerged as one of the most pressing challenges of the 21st century, intensified by climate change, extreme rainfall, and rapid urbanization. Over the past two decades, research on this issue has expanded considerably in both scale and scope, producing significant advances while also revealing persistent gaps. This review synthesizes and categorizes studies published between 2000 and 2023, with the aim of identifying key research trends, achievements, limitations, and future priorities. Five dominant trajectories are highlighted: (i) the growing application of multidimensional and hybrid hydrological–hydraulic models, (ii) the expanded use of GIS, remote sensing, and satellite data for flood mapping, (iii) the rise of artificial intelligence, machine learning, IoT, and Big Data in forecasting and early warning, (iv) the integration of climate-adaptive urban planning with green–gray infrastructure, and (v) increased attention to policy frameworks, governance, and social equity. Despite these advances, challenges remain, including the shortage of high-resolution data in many developing countries, the limited transfer of numerical models into practice, and the lack of integration between science, urban planning, and community participation. Building on these findings, the review proposes four strategic directions for future research: developing flexible simulation models using open data, applying AI/Big Data/IoT more effectively in early warning and risk management, embedding nature-based solutions in urban design, and strengthening international cooperation and cross-border data sharing. The study concludes that advancing urban flood research requires interdisciplinary collaboration that bridges science, policy, and practice, thereby contributing to the development of smarter, more sustainable, and climate-resilient cities.