Verification of the Usability of Global River Inundation Model Output for Hazard Maps in Japan

A regression analysis was made on 277 acceleration response spectra computed from Japanese accelerograms by subdividing the data into discrete categories. Five magnitude and distance categories, and four ground condition categories were used. The maximum absolute acceleration amplitude is predicted as a product of three factors, each representing a weighting factor for magnitude, distance and ground condition category at each of the 18 response spectrum periods from 0·1 s to 4 s at a damping value of 5 per cent of critical. A method was then developed to evaluate seismic hazard in terms of acceleration response spectrum by using the prediction model and the seismicity data, and it was applied to obtain seismic macro‐zoning maps of Japan which are dependent on the natural period of a structure. The results of the analysis indicated that a single seismic zoning map may not be sufficient to cover a variety of structures with a wide range of periods because the expected spectral shape differs according to the seismicity of the area.

Climate-related extreme events impose a heavy toll on humankind, and many will likely become more frequent in the future. The compound (joint) occurrence of different climate-related hazards and impacts can further exacerbate the detrimental consequences for society. By analysing postprocessed data from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP), we provide a global mapping of future changes in the compound occurrence of six categories of hazards or impacts related to climate extremes. These are: river floods, droughts, heatwaves, wildfires, tropical cyclone-induced winds and crop failures. The use of impact model data provides a unique perspective on the compound occurrence of these hazards and impacts, beyond what can be obtained from Global Climate Model output. In line with the existing literature, we find sharp increases in the occurrence of many individual hazards and impacts, notably heatwaves and wildfires. Under a medium-high emission scenario, many regions worldwide transition from chiefly experiencing a given category of hazard or impact in isolation to routinely experiencing compound hazard or impact occurrences. A similarly striking change is projected for the future recurrence of compound hazards or impacts, with many locations experiencing specific compound occurrences at least once a year for several years, or even decades, in a row. Moreover, we show a nonlinearity in compound occurrences for different global warming levels, with higher warming giving a faster-than-linear increase in compound occurrences. In the absence of effective global climate mitigation actions, we may thus witness a qualitative regime shift from a world dominated by individual climate-related hazards and impacts to one where compound occurrences become the norm.

<p><strong>Abstract</strong></p><p>Flood inundation and hazard maps have played various crucial roles in terms of municipal hazard planning, timely flood control countermeasure operation, economic levee design, and developing flood forecasting or nowcasting systems. Given that the riparian areas prone to flood conventionally imposed special cares to justify applications of recently available flood inundation or hazard assessment numerical models on top of digital elevation models of dense spatial resolution such as LiDAR irrespective of their high costs. However, laborious and time & cost-consuming processes were required to proficiently produce inundation and hazard maps, which includes preparation of geometric and hydrologic data as input for the targeted numerical model, executing the model and post-processing, and inundation and subsequent hazard mapping. For example in Korea, field surveyed geometric dataset are provided in CAD format and should have to be manually converted into cross-sectional information compatible with HEC-RAS as a numerical model, where such dataset are not managed in centralized and standardized database. Then, flood inundation and hazard maps are generated one by one based on flood stage heights simulated from the HEC-RAS, where additional tools such as HEC-GeoRAS or manual drawing against DEM are usually applied. In order to efficiently and cost-effectively provide a series of flood inundation and hazard maps automatically with minimum practitioner involvement, this study demonstrates a set of open-source based tools that automated flood and hazard mapping processes as follows: a) parse CAD files containing geometric surveys like cross-sections and store them into server-based Arc River database approachable through website; b) retrieve geometric information using RiverML from Arc River and implicitly make them compatible with HEC-RAS input format; c) execute the HEC-RAS with some designated boundary conditions and various flood discharge; d) parse HEC-RAS output in binary format and draw flood inundation and hazard map on a given DEM through a developed add-on in QGIS using Python. We found that the proposed entire autonomous processes substantially enhanced efficiency and accuracy for flood mapping. The spatial accuracy of flood inundation and hazard map after applying above processes were validated throughout comparison with an inundation trace map acquired from typhoon Nari, 2007, in Hancheon basin located in Jeju Island, Korea, where a series of inundation and hazard maps were comprehensively investigated to track the burst of flood in the extreme flood events.</p><p> </p><p><strong>Acknowledgment</strong></p><p>This work was supported by the US Geological Survey Cooperative Grant Agreement #G19AC00257 and by the Korea Agency for Infrastructure Technology Advancement (KAIA) grant funded by the Ministry of Land, Infrastructure and Transport (21AWMP- B121092-06).</p>

Bottom-up multilevel flood hazard mapping by integrated inundation modelling in data scarce cities

Global warming is changing the magnitude and frequency of extreme precipitation events. This requires updating local rainfall intensity-duration-frequency (IDF) curves and flood hazard maps according to the future climate scenarios. This is, however, far from straightforward, given our limited ability to model the effects of climate change on the temporal and spatial variability of rainfall at small scales. In this study, we develop a robust method to update local IDF relations for sub-daily rainfall extremes using Global Climate Model (GCM) data, and we apply it to a coastal town in NW Spain. First, the relationship between large-scale atmospheric circulation, described by means of Lamb Circulation Type classification (LCT), and rainfall events with potential for flood generation is analyzed. A broad ensemble set of GCM runs is used to identify frequency changes in LCTs, and to assess the occurrence of flood generating events in the future. In a parallel way, we use this Weather Type (WT) classification and climate-flood linkages to downscale rainfall from GCMs, and to determine the IDF curves for the future climate scenarios. A hydrological-hydraulic modeling chain is then used to quantify the changes in flood maps induced by the IDF changes. The results point to a future increase in rainfall intensity for all rainfall durations, which consequently results in an increased flood hazard in the urban area. While acknowledging the uncertainty in the GCM projections, the results show the need to update IDF standards and flood hazard maps to reflect potential changes in future extreme rainfall intensities.

The Noto Hanto earthquake struck one of the lowest earthquake probability regions on the national seismic hazard map of Japan. To contribute to future updates of the hazard map, we examined the predictability of the 2007 earthquake on the basis of geological data that were available before it occurred. Sonic prospecting profiles of active faulting and the absence of an onshore fault could have limited the potential rupture length to 12–15 km, similar to the 2007 source. Empirical relationships between magnitude and fault length would have given usMj= 6.6–6.8 andMw= 6.3–6.4. The emergence of one marine terrace, which inclines to the south and reaches an altitude of approximately 50 m, can be dated to 120–130 ka and yields an uplift rate of approximately 0.4 mm/year.Mw-displacement empirical relationships and examples of recent blind fault events that have occurred at various locations around the world suggest that the conceivable maximum coseismic uplift of such shocks is 40–70 cm. Together with the uplift rate, we would have obtained an average recurrence interval of 1000–2000 years and, consequently, a 1.5–3.0% time-independent (Poisson) probability for 30 years. In addition, the significant inclination of the marine terraces—3.2 per mille (0.32%)—is better explained by the accumulation of frequent southward tilting as large as that of the 2007 type event with approximately 1600-year intervals, without any significant contributions from other seismic sources. We therefore conclude that the Noto Hanto earthquake source would have been better evaluated and identified if we had taken into account not only major active faults but also the active tectonics of moderate-size faults and their associated scale and rate.

This paper explores a method to combine the time and space continuity of a large-scale inundation model with discontinuous satellite microwave observations, for high-resolution flood hazard mapping. The assumption behind this approach is that hydraulic variables computed from continuous spatially-distributed hydrodynamic modeling and observed as discrete satellite-derived flood extents are correlated in time, so that probabilities can be transferred from the model series to the observations. A prerequisite is, therefore, the existence of a significant correlation between a modeled variable (i.e., flood extent or volume) and the synchronously-observed flood extent. If this is the case, the availability of model simulations over a long time period allows for a robust estimate of non-exceedance probabilities that can be attributed to corresponding synchronously-available satellite observations. The generated flood hazard map has a spatial resolution equal to that of the satellite images, which is higher than that of currently available large scale inundation models. The method was applied on the Severn River (UK), using the outputs of a global inundation model provided by the European Centre for Medium-range Weather Forecasts and a large collection of ENVISAT ASAR imagery. A comparison between the hazard map obtained with the proposed method and with a more traditional numerical modeling approach supports the hypothesis that combining model results and satellite observations could provide advantages for high-resolution flood hazard mapping, provided that a sufficient number of remote sensing images is available and that a time correlation is present between variables derived from a global model and obtained from satellite observations.

River floods are common natural disasters that cause serious economic damage worldwide. In addition to direct economic damage, such as the destruction of physical assets, floods with long‐lasting inundation cause direct and indirect economic losses within and outside the affected area. Direct economic losses include loss of opportunity, due to interruption of business activities, and the costs associated with emergency measures such as cleaning, while indirect economic losses affect sectors within the trade and supply network. Few studies have explicitly estimated direct and indirect economic losses in several sectors, due to the difficulty of modeling inundation depth and period at finer scales. Here we developed a global modeling framework to estimate the direct and indirect economic losses associated with floods using a computable general equilibrium model and a global river and inundation model, which can simulate the flood extent, depth, and period. Application of the method to the 2011 Thailand flood demonstrated that the estimated economic losses due to business interruption in the industry and service sectors totaled $14.7 billion, which was about two thirds of the estimated direct economic damage caused by the flood ($22.0 billion). The estimated indirect economic losses reduced the gross domestic product of Thailand by 4.81% in 2011, without considering transboundary effects, and will cause more than 0.5% reduction in gross domestic product even in 2030, resulting in $55.3 billion of total losses from 2011 to 2030. Comprehensive estimation of direct and indirect economic losses facilitates understanding of various types of flood‐related economic risks during and after a flood.

The impacts of flooding are expected to rise due to population increases, economic growth and climate change. Hence, understanding the physical and spatiotemporal characteristics of risk drivers (hazard, exposure and vulnerability) is required to develop effective flood mitigation measures. Here, the long-term trend in flood vulnerability was analysed globally, calculated from the ratio of the reported flood loss or damage to the modelled flood exposure using a global river and inundation model. A previous study showed decreasing global flood vulnerability over a shorter period using different disaster data. The long-term analysis demonstrated for the first time that flood vulnerability to economic losses in upper-middle, lower-middle and low-income countries shows an inverted U-shape, as a result of the balance between economic growth and various historical socioeconomic efforts to reduce damage, leading to non-significant upward or downward trends. We also show that the flood-exposed population is affected by historical changes in population distribution, with changes in flood vulnerability of up to 48.9%. Both increasing and decreasing trends in flood vulnerability were observed in different countries, implying that population growth scenarios considering spatial distribution changes could affect flood risk projections.

Classical approaches to flood hazard are obtained by the concatenation of a recurrence model for the events (i.e., an extreme river discharge) and an inundation model that propagates the discharge into a flood extent. The classical approach, however, uses “best‐fit” models that do not include uncertainty from incomplete knowledge or limited data availability. The inclusion of these, so called epistemic uncertainties, can significantly impact flood hazard estimates and the corresponding decision‐making process. We propose a simulation approach to robustly account for uncertainty in model's parameters, while developing a useful probabilistic output of flood hazard for further risk assessments via the Bayesian predictive posterior distribution of water depths. A Peaks‐Over‐Threshold Bayesian analysis is performed for future events simulation, and a pseudo‐likelihood probabilistic approach for the calibration of the inundation model is used to compute uncertain water depths. The annual probability averaged over all possible models’ parameters is used to develop hazard maps that account for epistemic uncertainties. Results are compared to traditional hazard maps, showing that not including epistemic uncertainties can underestimate the hazard and lead to non‐conservative designs, and that this trend increases with return period. Results also show that the influence of the uncertainty in the future occurrence of discharge events is predominant over the inundation simulator uncertainties for the case study.

Two‐dimensional shallow water models are widely used tools for flood inundation mapping. However, even if High Performance Computing techniques have greatly decreased the computational time needed to run a 2D inundation model, this approach remains unsuitable for applications that require results in a very short time or a large number of model runs. In this paper we test a non‐parametric regression model based on least squares support vector machines as a computationally efficient surrogate of the 2D shallow water equations for flood inundation mapping. The methodology is initially applied to a synthetic case study consisting of a straight river reach flowing towards the sea. A coastal urban area is then used as a real test case. Discharge in three streams and tide levels are used as predictor variables to estimate the spatial distribution of maximum water depth and velocity in the study area. The suitability of this regression model for the spatial prediction of flood hazard is evaluated. The results show the potential of the proposed regression technique for fast and accurate computation of flood extent and hazard maps.

Urban underground spaces are rapidly expanding, but their low elevation, limited drainage capacity, and strong enclosure make them highly vulnerable to pluvial flooding. To elucidate how inundation dynamics in 3D underground spaces under extreme rainfall translate into actionable risk indicators (e.g., depth thresholds and arrival time), we propose and cross-validate a rainfall-informed capacity–depth–damage (C–D–D) curve method and a physics-based computational fluid dynamics (CFD) inundation model. The first approach is a rainfall-informed C–D–D curves method that rapidly maps net inflow to depth evolution and warning indicators (e.g., threshold depth and arrival time). The second approach is a 3D-geometry-resolved CFD inundation model that simulates spatially distributed depths/flows under prescribed inflow and drainage/outlet conditions, providing high-fidelity validation and hazard maps. A GeoSLAM handheld 3D Laser Scanning system was used to reconstruct as-built, modeling-ready 3D geometry of the underground space, addressing the common limitation of idealized layouts in prior evacuation-time assessments and enabling geometry-specific inundation and warning-threshold predictions. Using an underground parking garage in Tongzhou District, Beijing as a case study, we evaluated flood dynamics and risks under rainfall scenarios with annual exceedance probabilities of 1%, 2%, and 5%. Results show that stronger rainfall significantly advances critical water-depth thresholds and compresses evacuation windows; for example, under P = 1%, the 0.2 m alert occurs 1.5 h earlier than under P = 2% and 5.3 h earlier than under P = 5%. The two methods exhibit strong consistency in threshold timing (typically within 0–1 h), while CFD resolves spatial heterogeneity and identifies medium-to-high risk zones earlier in the intrusion stage. This integrated framework supports rapid early warning, evacuation-window assessment, entrance protection, and drainage-capacity design. Novelty lies in (i) integrating handheld 3D Laser Scanning with a “curve-first, CFD-refine” dual-model workflow; (ii) cross-validating fast C–D–D-based warning thresholds against geometry-resolved CFD dynamics; and (iii) delivering actionable time-to-threshold warnings and spatial risk maps for emergency planning.

Devastating floods are observed every year globally from upstream mountainous to coastal regions. Increasing flood frequency and impacts affect both major rivers and their tributaries. Nonetheless, at the small-scale, the lack of distributed topographic and hydrologic data determines tributaries to be often missing in inundation modeling and mapping studies. Advances in Unmanned Aerial Vehicle (UAV) technologies and Digital Elevation Models (DEM)-based hydrologic modeling can address this crucial knowledge gap. UAVs provide very high resolution and accurate DEMs with low surveying cost and time, as compared to DEMs obtained by Light Detection and Ranging (LiDAR), satellite, or GPS field campaigns. In this work, we selected a LiDAR DEM as a benchmark for comparing the performances of a UAV and a nation-scale high-resolution DEM (TINITALY) in representing floodplain topography for flood simulations. The different DEMs were processed to provide inputs to a hydrologic-hydraulic modeling chain, including the DEM-based EBA4SUB (Event-Based Approach for Small and Ungauged Basins) hydrologic modeling framework for design hydrograph estimation in ungauged basins; the 2D hydraulic model FLO-2D for flood wave routing and hazard mapping. The results of this research provided quantitative analyses, demonstrating the consistent performances of the UAV-derived DEM in supporting affordable distributed flood extension and depth simulations.

Background:How should we address the natural hazards? This question has been a longstanding issue in Japanese society. After the Great East Earthquake in 2011, Education for Disaster Prevention (EDP) has been especially positioned in various school subjects and has become one of the important learning themes for Social Studies including geography, history and civics areas, aiming to build a sustainable society and its citizens. At the same time, a lot of symposiums or teacher education programmes regarding natural hazards and EDP have been held in geographical societies in Japan.Purpose:This research examines the characteristics of EDP in primary and secondary Social Studies in Japan, and the outreach for supporting EDP in school education by geography societies.Methods:This research analyses the contents of the Course of Study for primary and secondary Social Studies revised in 2017/2018, and outreach by geography societies.Results & Discussion:‘Self-help,’ ‘mutual assistance’ and ‘public support’ are the important ideas for disaster prevention in Japan, these ideas are positioned in the primary and secondary Social Studies curriculum. For example, students read a (hazard)map in their local area and make a decision on how they should evacuate in the hazardous events, to develop the idea‘self-help.’ Lessons such as this are well-seen in the primary and secondary geography classes. On the other hand, lessons introducing the idea ‘public support’ are often positioned in civics. Lessons of this type tend to help students understand the various levels of government’s roles in natural hazards and develop their competency to propose disaster prevention measures for local society as citizens.In Japanese geography societies, research on natural hazards and EDP has been conducted for a long time. Its outcomes have been opened to the public, such as workshops for teachers and public symposiums, etc. In addition, fieldwork programmes in disaster areas are conducted by some geography societies.

Evaluation of tsunami inundation in the plain of Martil (north Morocco): Comparison of four inundation estimation methods