Hazard Maps Research Articles

VERE Py-framework: Dual environment for physically-informed machine learning in seismic landslide hazard mapping driven by InSAR

VERE Py-framework: Dual environment for physically-informed machine learning in seismic landslide hazard mapping driven by InSAR

Integrating Hydrological Models for Improved Flash Flood Risk Assessment and Mitigation Strategies in Northeastern Thailand

This study focuses on assessing flash flood risks in Northeastern Thailand, particularly within the Lam Saphung, Phrom, and Chern River Basins, which are highly susceptible to flash floods and debris flows. Using the HEC-RAS hydraulic model integrated with GIS tools, the research analyzes historical and scenario-based flood events to evaluate the impact of land use changes and hydrological dynamics. The model was calibrated and validated with statistical metrics such as R2 values ranging from 0.745 to 0.994 and NSE values between 0.653 and 0.893, indicating strong agreement with the observed data. This study also identified high-risk areas, with up to 5.49% and 5.50% increases in flood-prone areas in the Phrom and Chern River Basins, respectively, from 2006 to 2019. Key findings highlight the critical role of proactive risk management and targeted mitigation strategies in enhancing community resilience. The integration of advanced hydraulic modeling with detailed datasets enables precise flood hazard mapping, including flood depths exceeding 1.5 m in certain areas and high-risk zones covering up to 105.2 km2 during severe flood events. These results provide actionable insights for emergency response and land use planning. This research significantly contributes to hydrological risk assessments by advancing modeling techniques and delivering practical recommendations for sustainable flood management. The outcomes are particularly relevant for stakeholders, including urban planners, emergency management officials, and policymakers, who aim to strengthen resilience in vulnerable regions. By addressing the complexities of flash flood risk assessments with robust quantitative evidence, this study not only enhances the understanding of flood dynamics, but also lays the groundwork for developing adaptive strategies to mitigate the adverse impacts of flash floods, safeguarding both communities and infrastructure in the region.

Global Research Trends in Performance-Based Structural Design: A Comprehensive Bibliometric Analysis

In the context of seismic hazard assessment and engineering design, a comprehensive understanding of local geological and geophysical factors is essential. However, previous studies have lacked crucial components such as local soil condition, ground response analysis, topographic influences, active fault characteristics, slip rates, groundwater behaviour, and slope considerations. To ensure the accuracy of the seismic hazard map of a country for the safe and cost-effective design of engineering structures in urban areas, a detailed analysis of these factors is imperative. Moreover, multidisciplinary investigations, such as logic-tree considerations, are needed to enhance seismic hazard maps. As a result, adopting a performance-based approach in structural design has become an essential priority. A performance-based approach allows engineers to design buildings to specified performance levels (IO, LS, CP) even without a reliable seismic hazard map. This approach is akin to a miracle for countries that do not have a reliable seismic hazard map. This study presents a systematic and comprehensive bibliometric analysis of the academic literature pertaining to performance-based design (PBD). By fostering collaborative efforts and expanding research networks, we aim to facilitate the development of coordinated initiatives within the field. Preferred journals, leading countries, leading organisations, and international institutions were identified utilizing the Scopus database. This study examined 3456 PBD-related publications spanning from 1969 to 2023 using VOSviewer version 1.6.19, a bibliometric mapping and visualization software tool. The analysis of co-citations revealed that performance-based design serves as the primary theoretical foundation for structural design and analysis. Furthermore, through a co-word analysis, we tracked the evolution of research topics within the PBD domain over time. This investigation uncovered noteworthy trends, including the steady growth of research output, the increasing prominence of the term “PBD”, and a focus on various types of performance-based analyses.

Earthquake induced liquefaction hazard analysis for Chittagong City using machine learning

Liquefaction hazard analysis is crucial in earthquake-prone regions as it magnifies structural damage. In this study, standard penetration test (SPT) and shear wave velocity ( V s ) data of Chittagong City have been used to assess the liquefaction resistance of soils using artificial neural network (ANN). For a scenario of 7.5 magnitude (Mw) earthquake in Chittagong City, estimating the liquefaction-resistance involves utilizing peak horizontal ground acceleration (PGA) values of 0.15 and 0.28 g. Then, liquefaction potential index (LPI) is determined to assess the severity of liquefaction. In most boreholes, the LPI values are generally higher, with slightly elevated values in SPT data compared to V s data. The current study suggests that the Valley Alluvium, Beach and Dune Sand may experience extreme liquefaction with LPI values ranges from 9.55 to 55.03 and 0 to 37.17 for SPT and V s respectively, under a PGA of 0.15 g. Furthermore, LPI values ranges from 25.55 to 71.45 and 9.55 to 54.39 for SPT and V s correspondingly. The liquefaction hazard map can be utilized to protect public safety, infrastructure, and to create a more resilient Chittagong City.

Flood inundation and hazard mapping using the HEC-RAS 2D model: a case study of Adoori River, Iran

Flood inundation and hazard mapping using the HEC-RAS 2D model: a case study of Adoori River, Iran

Sources and Trends of CO, O3, and Aerosols at the Mount Bachelor Observatory (2004–2022)

Understanding baseline O3 is important as it defines the fraction of O3 coming from global sources and not subject to local control. We report the occurrence and sources of high baseline ozone days, defined as a day where the daily maximum 8 h average (MDA8) exceeds 70 ppb, as observed at the Mount Bachelor Observatory (MBO, 2.8 km asl) in Central Oregon from 2004 to 2022. We used various indicators and enhancement ratios to categorize each high-O3 day: carbon monoxide (CO), aerosol scattering, the water vapor mixing ratio (WV), the aerosol scattering-to-CO ratio, backward trajectories, and the NOAA Hazard Mapping System Fire and Smoke maps. Using these, we identified four causes of high-O3 days at the MBO: Upper Troposphere/Lower Stratosphere intrusions (UTLS), Asian long-range transport (ALRT), a mixed UTLS/ALRT category, and events enhanced by wildfire emissions. Wildfire sources were further divided into two categories: smoke transported in the boundary layer to the MBO and smoke transported in the free troposphere from more distant fires. Over the 19-year period, 167 high-ozone days were identified, with an increasing fraction due to contributions from wildfire emissions and a decreasing fraction of ALRT events. We further evaluated trends in the O3 and CO data distributions by season. For O3, we found an overall increase in the mean and median values of 2.2 and 1.5 ppb, respectively, from the earliest part of the record (2004–2013) compared to the later part (2014–2022), but no significant linear trends in any season. For CO, we found a significant positive trend in the summer 95th percentiles, associated with increasing fires in the Western U.S., and a strong negative trend in the springtime values at all percentiles (1.6% yr−1 for 50th percentile). This decline was likely associated with decreasing emissions from East Asia. Overall, our findings are consistent with the positive trend in wildfires in the Western United States and the efforts in Asia to decrease emissions. This work demonstrates the changing influence of these two source categories on global background O3 and CO.

A Probabilistic Liquefaction Hazard Analysis: Case Studies from the Marmara Region

Earthquake induced soil liquefaction poses a significant threat to buildings and infrastructure, as evidenced by numerous catastrophic seismic events. Existing approaches of regional liquefaction hazard assessment predominantly rely on deterministic analysis methods. This paper presents a novel Probabilistic Liquefaction Hazard Analysis (PLHA) framework based on Monte-Carlo (MC) simulations to mitigate future seismic risks associated with liquefaction. The proposed procedure requires only publicly available data, offering accessibility and applicability in resource-constrained settings. A key feature of the procedure is its ability to deal with uncertainties in earthquake and soil parameters using distribution functions. Liquefaction potential is assessed through parameters such as Liquefaction Potential Index (LPI) and Liquefaction Severity (LS). The procedure is implemented in MATLAB as part of a broader probabilistic risk assessment framework for developing countries. The developed procedure is applied to the high risk city of Adapazari, Türkiye; an area lacking prior PLHA studies. Results are validated against observed liquefaction data from a simulated scenario event of the 1999 Kocaeli earthquake. Probabilistic liquefaction hazard maps are generated for the study area and the entire Marmara region in terms of LPI and LS. A novel aspect of this work is the integration of a time-dependent Probabilistic Seismic Hazard Analysis (PSHA) model into the PLHA framework. Results are compared with those predicted using the Poisson model for the Marmara region. Findings demonstrate that the developed PLHA procedure offers a robust and flexible tool for predicting seismic liquefaction hazards, providing valuable insights for loss estimation and risk mitigation planning.

Tomatoes Die: A Design Fiction for Grassroots Climate AI

This design fiction proposes a panel session in the near future having environment and climate advocates share their stories of using artificial intelligence (AI) in their work. This work explores how the development of an embodied river persona, a farming assistant app, and a community hazard mapping tool could pose challenges and aid successes to respective local communities. Our design fiction highlights issues of design and development challenges that local organizations might face in a varied AI development for the environment. We explore questions around incorporating traditional knowledge, ethical participatory design models, and challenges of implementing and sustaining tools. Our work demonstrates how design fiction might be used to imagine AI for the climate challenge that considers people, place, and community.

Liquefaction hazard mapping in DMDP area of Bangladesh: A comprehensive assessment using SCPT data and multiple severity indices

Liquefaction hazard mapping in DMDP area of Bangladesh: A comprehensive assessment using SCPT data and multiple severity indices

Using GIS and Analytical Hierarchy Process (AHP) for flood hazard assessment based on morphological and hydrological criteria, case of the Meknes region, Morocco

Flooding is one of the most significant natural disasters affecting North Africa. Its impact is increasingly intensified by climate change. Flood risk is a combination of natural and anthropogenic factors, highlighting the importance of understanding its spatial distribution in order to plan effective land management strategies. The main aim of this study is to identify and map areas at risk of flooding in the R'dom catchment area (Meknes, Morocco). This hazard is assessed by taking into account morphological criteria (slope, altitude, density of the hydrographic network, curvature) and hydrological criteria (drainage density, stream power index (SPI) and rainfall data). The methodology adopted is essentially based on a multicriteria analysis using analytical hierarchy process (AHP), with the use of GIS tools and satellite data. A flood hazard map was drawn up, with classification according to degree of susceptibility. The resulting map reveals that 26.3% of the study area is characterized by a high to very high flood hazard. Moderate flood risk accounts for 56.9% of the study area. These results underline the crucial need to implement effective flood mitigation strategies to protect communities from flooding.

Proposal of Conditional Seismic Hazard Maps for Site Consideration of Disaster Base Buildings

Proposal of Conditional Seismic Hazard Maps for Site Consideration of Disaster Base Buildings

Combining GIS and machine learning for enhanced tsunami risk management: A review of current approaches and unexplored future potential

This review article aims to discuss the current status and future potential of Geographic Information Systems (GIS) in map-based technology of tsunami risk management, especially in seismically active, well-known tsunami regions of the world. It presents GIS technologies for hazard mapping, risk assessment, and information generation for disaster-response operations. These are important tools for accurately mapping vulnerable areas by integrating real-time and historical data to develop accurate forecasts for possible tsunamis. Demographic and geographic data were also analyzed by GIS to determine the optimum route to develop evacuation strategies. A set of case studies demonstrates how GIS improves community resilience by supporting informed decision-making. In addition, suggestions are made for how future steeps as the integration of machine learning techniques as emerging tools for analyzing and classifying complex and vast datasets, which may enhance GIS applications in tsunami risk management to improve the accuracy and utility of these tools.

From land to sea: a new high-resolution bathymetry and topography of the Campi Flegrei area, Southern Italy

ABSTRACT Campi Flegrei is an active volcanic area located in the Campanian region (southern Italy). It is characterized by a caldera structure including a subaerial portion densely populated and a submarine area represented by the Gulf of Pozzuoli. Altimetry data acquired by Airborne Laser Scanning and seafloor depth data coming from several bathymetry surveys were used to show a Digital Elevation Model with a spatial resolution of 1 m for the topography of Campi Flegrei. This model, for the first time, reconstructs a topographic continuum from land to seafloor for a total extent of 138.32 km2. Thanks to the high spatial resolution, the model allowed to map and measure seafloor features such as landslides and terraces as well as Roman-epoch artefacts. Our results provide accurate reference topography for a more complete mapping and modelling of natural hazards that affect, directly or indirectly, the entire area of the Campi Flegrei caldera.

MULTIDIRECTIONAL USE OF UNMANNED AERIAL VEHICLES IN THE AREA OF SAFETY

The paper presents a wide range of possibilities for the use of drones in terms of human safety, theenvironment and technical facilities. In accordance with the concept of the paper, these areas aredivided into four main sources of hazards and in each of these cases the possibilities of using anunmanned aircraft are presented. Hazards caused by flooding, the environment, a fire and thoseoccurring on construction sites are subject to analysis. The main aim of the paper was to markareas of hazard using a grid superimposed on a map of an area by a specialised drone camera.Based on this information, it is possible to define a risk map of hazards to people and property.In the case of flooding, the depth of the river spillway was determined according to the width ofthe river channel, in this case affecting the safety of residents of a town. For the environmentalaspect, the surface area of a water table and its depth in the area of fields, meadows and pastureswere determined. This is also important from the agricultural point of view, including determiningthe extent of crop damage. In the case of a fire, the use of a drone enabled the assessment ofthe damaged surface of a building as a result of high temperatures, including the construction ofa situation plan related to the assessment of the building’s structure in the context of its continueduse. The final area is the safety of a construction site. Here, in turn, an important objective was tomap the occupational risks for those working there and, in particular, to identify the sources ofdangerous, harmful and nuisance factors. All of the diagrams presented confirmed the widespreaduse of UAVs in the diagnosis of occupational safety levels. With this technology, it is easier todiagnose sources of hazards and develop preventive measures.

Assessing Seismic Vulnerability and Pollution Risks of Wastewater Treatment Plants

Empirical studies are valuable for assessing soil and water pollution, as they can reduce costs and save time. The present study discusses previous research results using a questionnaire to gather experts’ judgments on technical issues and potential pollution related to the vulnerability of Wastewater Treatment Plants (WWTPs) in Greece. The questionnaire included 44 closed-type questions based on the Likert Scale. It was distributed to a representative sample of 116 operators over seven (7) months (April–November 2021). Geographical Information Systems (GISs) were employed to visualize the spatial distribution of the seismic vulnerability of WWTPs. The study outputs include eight (8) maps depicting the spatial distribution of seismic vulnerability, both with and considering soil–water pollution, by calculating the existence of seismic hazards and identifying potentially affected regions. Additionally, eight (8) tables support this analysis. The survey findings highlight the most vulnerable regions and WWTPs in the country. The results suggest that after excluding Zone III, the WWTPs of Zone II of the national Seismic Hazard Map (SHM) are estimated to be the most vulnerable. This study spatially visualizes the indicator of seismic vulnerability (ISV) and the seismic vulnerability index concerning potential soil–water pollution (ISV-REF), according to the SHM and regions. Most WWTPs have low ISV-REF, while maps illustrate the exceedance of that parameter, identifying the safest units and indicating that Zone I has the safest units according to the exceedance percentages. Integrating data on regions, ISV, ISV-REF, and their exceedance in GIS could lead to authorities’ and technicians’ decisions to implement quick measures. Researchers should also focus their studies more precisely, mitigating the seismic vulnerability of critical infrastructure, such as WWTPs.

Snow Avalanche Hazards and Avalanche-Prone Area Mapping in Tibet

Snow avalanche is one of the major natural hazards in the mountain region, yet it has received less attention compared to other mountain hazards, such as landslides, floods, and droughts. After a comprehensive overview of snow avalanche hazards in Tibet area, the spatial distribution and main driving factors of snow avalanche hazards in the high mountain region in Tibet were presented in the study first. Snow avalanche-prone areas in Tibet were then mapped based on the snow cover distribution and DEM data and were validated against in situ observations. Results show that there are the highest frequencies of avalanche occurrences in the southeastern Nyainqentanglha Mountains and the southern slope of the Himalayas. In the interior of plateau, avalanche development is constrained due to less precipitation and much flatter terrain. The perennially snow avalanche-prone areas in Tibet account for 1.6% of the total area of the plateau, while it reaches 2.9% and 4.9% of the total area of Tibet in winter and spring, respectively. Snow avalanche hazards and fatalities appear to be increasing trends under global climate warming due to more human activities at higher altitudes. In addition to the continuous implementation of engineering prevention and control measures in pivotal regions in southeastern Tibet, such as in the Sichuan–Tibet highway and railway sections, enhancing monitoring, early warning, and forecasting services are crucial to prevent and mitigate avalanche hazards in the Tibetan high mountain regions, which has significant implications for other global high mountain areas.

Characteristics and Comparative Assessment of Flash Flood Hazard Evaluation Techniques: Insights from Wadi Haily Basin, Eastern Red Sea Coast, Saudi Arabia

The Wadi Haily basin in southwest Saudi Arabia, which runs along the Red Sea coast, serves as an ideal natural laboratory for understanding flash flood dynamics in this region. However, limited morphometric and hydrological data are currently available in this area. This study aims to analyze key morphometric effective parameters to examine and assess flash flood risk potential within the basin. Using remote sensing, GIS, geological, and topographical datasets, this research combines advanced modeling and GIS tools to produce detailed flood hazard maps and risk assessments. This study examines 15 sub-basins of varying sizes, characterized by primary stream orders ranging from 4th to 8th. Based on morphometric analysis, the basins are categorized by flood susceptibility: four basins have a low flood risk, five exhibit moderate risk, and six are highly susceptible to flooding. Key findings indicate that the study area features a vast drainage area, high grid cell values of the drainage frequency, moderate drainage density, elongated basin shapes, low infiltration rates, and long overland flow distances, all suggesting a heightened flood hazard. Additional indicators include high values in gradient ratios, slopes, ruggedness numbers, relief ratios, and basin relief, reinforcing the basin’s flash flood vulnerability. This study provides a comprehensive morphological framework that can support strategic flood management and hazard mitigation planning for the Wadi Haily region.

Evaluation of Flood Hazards and Impacts on the Environment: A Case Study of Louisville, Kentucky, USA, Using Remote Sensing and Geographic Information Systems (GIS)

This study evaluates flood hazards and environmental impacts in Louisville, Kentucky, using remote sensing and Geographic Information Systems (GIS). A comprehensive flood risk assessment framework was developed utilizing various data, including: digital elevation model, land use/land cover, soil, boundary, stream network, precipitation, and road data. These data were used for delineation, discretization, parameterization, and simulation of flooding events-a flood hazard map identified high, medium, and low-risk areas, with infrastructure at risk evaluated. Notably, high-hazard regions are located near stream networks. The demographic analysis revealed that males reside predominantly in high and medium hazard areas, Ages 22-29 and 30-39 are concentrated in southwest high and medium-hazard regions; Younger populations (<5, 5-17, 18-21) and older adults (40-49, 50-64) reside in central and northwest medium and low-hazard areas. This study shows flood water distribution is influenced by bottlenecks and critical points during specific discharges, impacting local populations in the environment. Key findings inform flood risk management strategies, infrastructure planning, and emergency response initiatives, ultimately enhancing resilience in Louisville.

Analysis of Flood Hazards in Premiere Hills Housing and Surroundings Using the Weighted Overlay Method, Sungai Kunjang District, Samarinda City

This research was conducted in Sungai Kunjang District, Samarinda City, East Kalimantan Province. Based on the regional geology of Samarinda, this location is included in the stratigraphy of the Kutai Basin with the Balikpapan and Balang Island Formations. This research focuses on determining the flood hazard areas around the Premiere Hills housing complex. The research method used is weighted overlay using spatial analysis, which overlays several maps related to factors that influence vulnerability assessment. The analytical tool used is the Geographic Information System (GIS). Each parameter is given a weight by scoring each parameter, namely land use, elevation, river buffer, rainfall, soil type, and slope slope. An overlay is carried out to obtain the classes of flood hazards. Then, field verification is carried out to determine whether the areas on the flood hazard map match those in the field, especially in areas with a high level of flood hazard. In the analysis results obtained using the weighted overlay method, the research area has a relatively high level of flood danger, which can be seen on the hazard map, where the colour red dominates compared to areas that have a low or medium level of flood danger, which are marked with green and yellow on the map. Based on the analysis results of areas with high flood hazards, verification is carried out to see whether the areas with high flood hazards follow those in the field. It can be seen from this verification that three points are taken, which are areas where flooding often occurs, characterized by low elevation and have poor drainage channels that prevent water from flowing properly

Landslide Prediction Validation in Western North Carolina After Hurricane Helene

Hurricane Helene triggered 1792 landslides across western North Carolina and has caused damage to 79 bridges to date. Helene hit western North Carolina days after a low-pressure system dropped up to 254 mm of rain in some locations of western North Carolina (e.g., Asheville Regional Airport). The already waterlogged region experienced devastation as significant additional rainfall occurred during Helene, where some areas, like Asheville, North Carolina received an additional 356 mm of rain (National Weather Service, 2024). In this study, machine learning (ML)-generated multi-hazard landslide susceptibility maps are compared to the documented landslides from Helene. The landslide models use the North Carolina landslide database, soil survey, rainfall, USGS digital elevation model (DEM), and distance to rivers to create the landslide variables. From the DEM, aspect factors and slope are computed. Because recent research in western North Carolina suggests fault movement is destabilizing slopes, distance to fault was also incorporated as a predictor variable. Finally, soil types were used as a wildfire predictor variable. In total, 4794 landslides were used for model training. Random Forest and logistic regression machine learning algorithms were used to develop the landslide susceptibility map. Furthermore, landslide susceptibility was also examined with and without consideration of wildfires. Ultimately, this study indicates heavy rainfall and debris-laden floodwaters were critical in triggering both landslides and scour, posing a dual threat to bridge stability. Field investigations from Hurricane Helene revealed that bridge damage was concentrated at bridge abutments, with scour and sediment deposition exacerbating structural vulnerability. We evaluated the assumed flooding potential (AFP) of damaged bridges in the study area, finding that bridges with lower AFP values were particularly vulnerable to scour and submersion during flood events. Differentiating between landslide-induced and scour-induced damage is essential for accurately assessing risks to infrastructure. The findings emphasize the importance of comprehensive hazard mapping to guide infrastructure resilience planning in mountainous regions.