The core insight of the study is that flood resilience cannot be assessed by hydrology alone. A city’s vulnerability to flooding depends not only on where water will go during an extreme event, but also on which facilities matter most when disaster strikes. Hospitals, emergency service centers, utilities and administrative hubs form the backbone of a city’s response capacity, and when these facilities are disrupted, the consequences ripple far beyond the flooded footprint. Operational efficiency drops, public dissatisfaction rises, and the continuity of essential services is impaired precisely when citizens depend on them most. The researchers therefore framed their investigation around a two-part question: where will the water go, and what will it hit that the city cannot afford to lose?

To answer the first half of that question, the team turned to HEC-RAS, the Hydrologic Engineering Center’s River Analysis System, a widely used one-dimensional hydraulic modeling platform developed by the US Army Corps of Engineers. The researchers investigated the hydrological conditions of Hamedan City and its surrounding areas, then simulated river behavior under multiple flood scenarios defined by different return periods. Return periods, expressed in years, describe the average interval between flood events of a given magnitude; a 100-year flood, for example, has roughly a one percent chance of occurring in any single year. By running the model across this spectrum of scenarios, the team captured how inundation extents and water depths change as floods grow rarer and more severe.

The hydraulic output from HEC-RAS was then integrated with a Geographic Information System, or GIS, to delineate flood-prone areas across the city. This integration is where the technical power of the approach emerges. Hydraulic models produce spatially distributed estimates of water surface elevations along river reaches, and when those elevations are draped over high-resolution terrain data within a GIS environment, they generate precise floodplain boundaries. Planners can overlay any layer of urban information, from land parcels to road networks to building footprints, onto these boundaries to see exactly what lies within the inundation zone. The resulting maps translate abstract hydraulic computations into actionable spatial intelligence for zoning and emergency planning.

In parallel, the team built a vulnerability classification system for urban assets. They established a set of criteria and sub-criteria designed to capture the multiple dimensions along which urban facilities can be evaluated, ranging from operational characteristics to economic significance. To determine the relative importance of these factors, the researchers designed a structured questionnaire and distributed it to selected experts, whose judgments were then aggregated. The arithmetic mean of the expert responses fed into the Analytic Hierarchy Process, a well-established multi-criteria decision-making method, implemented in the Expert Choice software. AHP works by decomposing a complex decision into a hierarchy of criteria and alternatives, deriving weights through pairwise comparisons, and producing a ranked prioritization that is transparent and reproducible.

The AHP results revealed a clear hierarchy of concerns. The quantitative level of operation, a measure of how intensively and measurably a facility functions, received the greatest weight among all evaluated indicators, signaling that experts view operational capacity as the dominant factor in urban vulnerability. At the other end of the scale, economic value was assigned the lowest weight, suggesting that the sheer monetary worth of a facility matters less to resilience than its functional role during a crisis. This finding carries practical weight for municipal decision-makers: protecting a modest but operationally critical service center may deliver more resilience per unit of investment than safeguarding a high-value property with limited emergency significance.

With critical urban centers identified and prioritized through the AHP framework, and flood-prone zones delineated through the HEC-RAS and GIS pipeline, the final analytical step was a spatial overlay. By intersecting the layer of prioritized urban facilities with the mapped flood extents in the GIS environment, the researchers identified and enumerated the vulnerable centers, those critical assets that fall within areas likely to be inundated under the modeled scenarios. This intersection transforms two separate analyses into a single, decision-ready product: a ranked list of the facilities whose flooding would inflict the greatest damage on the city’s capacity to function and respond.

The framework’s architecture is deliberately transferable. The authors note that the approach can potentially be applied to other urban areas, provided that appropriate local data are available and that the hydraulic component undergoes site-specific calibration and validation. That caveat is important. Hydraulic models are only as reliable as the terrain data, flow measurements and roughness coefficients that feed them, and a model calibrated for Hamedan’s river channels and topography cannot simply be transplanted elsewhere without adjustment. The vulnerability weighting, too, depends on expert panels whose composition and judgments will vary between cities, meaning that the specific rankings are context-dependent even if the methodology is universal.

The study is also candid about its boundaries. The assessment rests on current hydrological conditions and conventional flood return periods; explicit future climate projections are not incorporated into the modeling. This is a meaningful limitation in an era when climate change is altering precipitation patterns and intensifying extreme rainfall events in many regions, including arid and semi-arid landscapes like western Iran. The authors recommend that future studies integrate climate projections and scenario-based precipitation changes to evaluate how urban flood risk evolves under future climate conditions. Such an extension would allow planners to stress-test their resilience strategies against the wetter extremes that a changing climate may deliver, rather than against the historical record alone.

For Hamedan, the practical implications are immediate. The identification of vulnerable critical centers gives municipal authorities a concrete starting point for protective investment, whether through physical flood defenses, facility hardening, relocation of the most exposed assets, or revised zoning that restricts new critical infrastructure from flood-prone land. For the broader field of urban flood management, the study demonstrates how hydraulic simulation, geospatial analysis and structured expert judgment can be woven into a single coherent workflow. As cities worldwide grapple with the compounding pressures of growth and climate volatility, frameworks of this kind, which ask not just where the water will flow but what the city can least afford to lose, are likely to become an increasingly standard part of the flood resilience toolkit.

Subject of Research: GIS-integrated HEC-RAS flood simulation and AHP-based vulnerability assessment of critical urban centers in Hamedan City

Article Title: Enhancing Flood Resilience: a GIS-Integrated Approach to River Flow Modelling and Urban Zoning using HEC-RAS Simulation

Article References: Naseri, A., Estelaji, F., Yari, M. H., Asl, B. R., Zahedi, R., & Abedi, B. (2026). Enhancing Flood Resilience: a GIS-Integrated Approach to River Flow Modelling and Urban Zoning using HEC-RAS Simulation. Water Resources Management, 40(12), Article 528. https://doi.org/10.1007/s11269-026-04893-9

Image Credits: AI Generated

DOI: 10.1007/s11269-026-04893-9

Keywords: flood resilience, HEC-RAS, GIS, AHP, urban zoning, Hamedan, hydraulic modeling, flood vulnerability, river flow simulation, urban planning, Water Resources Management, multi-criteria decision making

The research, led by Hai Sun of the Ocean University of China together with colleagues at Qingdao University of Technology, Clemson University, and Western Sydney University, tackles one of the most persistent blind spots in flood management: the pathways linking land-use patterns to hydrological responses. Urbanization reshapes basin hydrology by replacing soils and vegetation with impervious surfaces such as roads, rooftops, and parking lots. These surfaces prevent infiltration, accelerate runoff generation, and amplify flood peaks, sending more water into rivers faster and overwhelming channels and drainage systems. Green infrastructure — permeable pavements, rain gardens, wetlands, and vegetated storage areas — counteracts this by improving infiltration, storage, and surface roughness. But until now, planners have lacked a rigorous, basin-scale framework for measuring how these benefits vary across space and under different storm conditions.

To close that gap, the team constructed three urban expansion scenarios for the year 2044 in the Poyang Lake Basin: a no-green-infrastructure baseline, a storage-oriented green infrastructure scenario, and a permeability-oriented scenario. The Poyang Lake Basin, China’s largest freshwater lake system and a critical node in the Yangtze River’s hydrology, is a natural laboratory for this question. Its low-lying floodplains, dense tributary network, and rapidly expanding urban platforms make it acutely sensitive to changes in land cover.

Land-use changes under each scenario were simulated using a cellular automaton–Markov (CA–Markov) model, a technique that combines transition probabilities derived from historical land-change data with spatial neighborhood constraints to project how urban footprints evolve. This allowed the researchers to generate realistic maps of where impervious surfaces would spread by 2044 and where green infrastructure would be deployed under each strategy. The hydrological consequences were then evaluated through a coupled one-dimensional and two-dimensional modeling framework, chaining HEC-HMS, a rainfall-runoff model, to HEC-RAS, a river hydraulics and flood inundation model. The coupling is significant: it enables a continuous simulation chain from land-use evolution to runoff generation to flood dynamics, rather than treating each link in isolation.

The baseline results are sobering. Under unconstrained urban expansion, impervious surface coverage in the basin rises from 3.93 percent to 7.37 percent — nearly a doubling of sealed ground. Correspondingly, the basin-averaged curve number, a standard parameter in the Soil Conservation Service runoff method that encapsulates how readily a landscape converts rainfall into runoff, increases from 68 to 72. That seemingly modest shift carries heavy consequences: the researchers calculate an approximately 18 percent decrease in potential maximum retention, the landscape’s capacity to absorb and store rainfall before it becomes floodwater. In plain terms, by mid-century the basin could surrender nearly a fifth of its natural buffering capacity to concrete and asphalt.

Green infrastructure partially blunts this trajectory, but the two strategies do so very differently. Permeability-oriented green infrastructure — designed to restore infiltration across the urban surface — achieves the strongest reduction in impervious coverage, limiting the rise to 6.68 percent, and effectively reverses the degradation of infiltration and storage capacity captured by the curve number. Storage-oriented green infrastructure, which concentrates water retention in discrete facilities, shows only limited improvement in these landscape-scale parameters. The reason is structural: storage works locally, behind berms and inside basins, while permeability works everywhere, beneath every street and rooftop it touches.

Those parameter-level differences propagate directly into flood behavior. Under small to moderate rainfall events, permeability-oriented green infrastructure reduces peak discharge by 6.2 percent and total runoff volume by 3.54 percent, and — critically — it maintains its effectiveness even under extreme conditions, because infiltration capacity does not fill up the way a storage basin does. Storage-oriented measures, by contrast, remain constrained by finite capacity: once a retention facility fills, additional rainfall passes through unattenuated. Yet the picture is not one-sided. The analysis reveals clear spatial heterogeneity: in areas with sufficient storage capacity, storage-based strategies actually outperform infiltration-based measures during large rainfall events, when rainfall intensity outpaces the soil’s ability to absorb water and detention volume becomes the deciding factor. The catch is that this advantage is limited by spatial and capacity constraints at the basin scale — there is simply not enough suitable land and storage volume to deploy it everywhere.

The two-dimensional hydraulic component of the framework sharpens this spatial story further. Permeability-oriented green infrastructure reduces the extent of high-depth and high-velocity flood hotspots, with the strongest benefits concentrated along river corridors and urban platforms — precisely the locations where people and assets cluster. This leads the authors to a practical siting logic built around the curve number itself: boost permeability and roughness on the slopes, maintain them through the channels, and add storage capacity at confluences where flows converge and backwater effects amplify. In other words, read the landscape’s hydrological fingerprints and match the intervention to the terrain.

The study’s most consequential recommendation is that no single strategy suffices. Because green infrastructure performance varies with location, terrain, and storm magnitude, the authors argue for differentiated strategies aimed at residual high-risk areas: infiltration-dominated measures for moderate rainfall, enhanced storage and conveyance capacity for extreme events, and spatially targeted deployment that combines infiltration and storage synergies in low-lying zones, storage-control combinations along flow corridors, and strict land-use regulation in high-risk areas. This is a departure from the one-size-fits-all deployments that have characterized much green infrastructure planning, including China’s high-profile sponge city program, and it provides theoretical support and decision-making guidance for coordinated planning and refined flood risk management at the basin scale.

The timing could hardly be more urgent. Recent global research has documented rapid urban growth inside flood zones since 1985 and projected substantial increases in future fluvial flood risk across China’s major urban agglomerations, with the Global South bearing disproportionately higher exposure. As climate change intensifies extreme rainfall and cities continue to seal their surfaces, the Poyang Lake findings offer a template that travels: simulate the land, couple it to the water, and let the spatial heterogeneity of performance — not generic best practice — dictate where every permeable meter and every storage basin goes. The difference, this research suggests, may be measured not just in percentage points of peak discharge, but in neighborhoods that stay dry.

Subject of Research: Spatial variability in the flood mitigation performance of green infrastructure under future urban expansion in the Poyang Lake Basin

Article Title: Spatial heterogeneity of green infrastructure performance in flood mitigation under urban expansion

Article References: Sun, H., Wang, H., Chu, Y., Yao, W., Fan, C., Chu, Z., & Liang, B. (2026). Spatial heterogeneity of green infrastructure performance in flood mitigation under urban expansion. Natural Hazards, 122(19), Article 637. https://doi.org/10.1007/s11069-026-08312-5

Image Credits: AI Generated

DOI: 10.1007/s11069-026-08312-5

Keywords: green infrastructure, flood mitigation, urban expansion, Poyang Lake Basin, CA-Markov model, HEC-HMS, HEC-RAS, curve number, impervious surfaces, runoff reduction, spatial heterogeneity, flood risk management