Emergency Management Research Articles

Assessment and Examination of Emergency Management Capabilities in Chinese Rural Areas from a Machine Learning Perspective

The Chinese government’s rural rejuvenation program depends on improving the national Rural Emergency Management Capability (REMC). To increase the resilience of Chinese rural areas against external dangers, REMC and its driving elements must be effectively categorized and evaluated. This study examines the variations in REMC levels and driving factors across different cities and regions, revealing the spatial distribution patterns and underlying mechanisms. To improve REMC in Chinese rural areas, this research employs the Projection Pursuit Method to assess REMC in 280 cities from 2006 to 2020. Additionally, we identify 22 driving factors and use the Random Forest algorithm from machine learning to analyze their impact on REMC. The analysis is conducted at both national and city levels to compare the influence of various driving factors in different regions. The findings show that China’s REMC levels have improved over time, driven by economic growth and the formation of urban clusters. Notably, some underdeveloped regions demonstrate higher REMC levels than more developed areas. The four most significant driving factors identified are rural road density, rural Internet penetration, per capita investment in fixed assets, and the density of township health centers. At the city level, rural Internet penetration and the e-commerce turnover of agricultural products have particularly strong driving effects. Moreover, the importance of driving factors varies across regions due to local conditions. This study offers valuable insights for the Chinese government to enhance REMC through region-specific strategies tailored to local circumstances.

Certificate program "Readiness, response and management of emergency situations" as a component in the formation of competencies for public health specialists

In the field of public health, the acquiring of relevant knowledge, skills and competencies for managing emergencies as well as the problem of effective response to them, and how to mitigate their consequences within the healthcare system are the crucial issues. The research employs bibliosemantic, informational, analytical, medical, statistical, sociological methods, method of content analysis, as well as surveys of practitioners from the Center for Disease Control and Prevention and the Public Health Center of Ukraine. The minimum sample size comprises 326 individuals, which was calculated using the statistical package G*Power; a total of 369 respondents participated in the survey. The statistical processing of the materials was carried out using the licensed program Microsoft Excel 2016. In addition, the inclusion criteria for respondents concerned the individuals who participated in rapid response groups (both primary and reserve). The exclusion criteria encompassed specialists who were on leave for various reasons, such as maternity or health-related issues, in addition to individuals who opted not to engage in the survey. When developing the requisite competencies, it is imperative to allocate appropriate consideration to the practical aspect, as evidenced by the information gathered through the survey. Thus, 47% of respondents believe that this aspect needs improvement. Furthermore, within the array of challenges linked to the attainment of requisite competencies, specialists from rapid response groups have delineated the subsequent factors: psychological and emotional stress, a perceived threat to personal safety (19%), inadequate levels of professional training (18.4%), health-related concerns (11.7%), and deficiencies in material and technical support (26.8%). Consequently, upon analysis of the acquired data, the imperative to initiate the subsequent modifications to the accredited program "Readiness, Response and Emergency Management" has been ascertained, namely: to enhance practical training methodologies, to underscore holistic competencies, to implement psychological training protocols, and to instruct on the operation with modern technical equipment.

Leadership Styles in Crisis Management: Lessons from Covid-19

The COVID-19 pandemic highlighted the critical importance of effective leadership in navigating complex crises. This paper investigates the role of leadership styles in crisis management, with a specific focus on lessons learned from the COVID-19 pandemic. By reviewing existing leadership theories, including transformational, transactional, and situational leadership, this study identifies adaptive and change-focused leadership as particularly relevant during crises. The research analyzes the phases of crisis management preparation, response, recovery, and mitigation—and examines how various leadership approaches influenced outcomes during the pandemic. Using COVID-19 as a case study, the findings underscore the need for agility, flexibility, and systemic thinking in leadership. The paper concludes with practical lessons for future crises, emphasizing the value of situational awareness, emotional intelligence, community engagement, and collaborative strategies. These insights provide a framework for improving leadership effectiveness in managing large-scale emergencies. Keywords: Crisis management, Leadership styles, COVID-19 pandemic, Situational leadership, Adaptive leadership.

Bridging incremental to transformative hazard management strategies on the Tule River Indian Reservation

Abstract Compounding hazards are becoming more common due to global environmental change. To build societal resilience, there is a need to focus on how people are made vulnerable by our social, political, and economic systems that turn hazards into disasters. Incremental adaptation, often piecemeal and hazard-specific actions, will be insufficient for keeping pace with the rapid global environmental changes already underway. Instead, transformative adaptation is necessary for meeting this need, although the pathways for how to create transformative as opposed to incremental change through individual action and social systems are challenging. These challenges for climate adaptation are on display in rural American Indian Tribal Nations, including the Tule River Indian Reservation, the site of this co-produced research. The Reservation is rural and isolated, and many of the 2000 members manage chronic health conditions like diabetes alongside increasing wildfire and wildfire smoke, extreme heat, drought, and flooding hazards. We ask: how do emergency managers and health practitioners on the Reservation characterize hazards and the vulnerabilities of the people they serve, and how do these understandings determine viable pathways for adaptation to support community health? We interviewed 16 practitioners with expertise in emergency management and health care services on the Tule River Indian Reservation. Using a grounded theory approach to analyze practitioner interviews, our article makes two major contributions. First, we identify a conceptual framework by which practitioners connect people to each other and to place, from place to compounding hazards, and from vulnerabilities to hazard management strategies. Second, our conceptual framework illustrates the incremental-transformative adaptation tension. Most adaptation strategies under consideration or implemented are incremental in nature and hazard-specific. Yet, we demonstrate how action at earlier points in the framework could promise transformative adaptation, addressing the disconnection between people, place, and infrastructure in ways that incremental adaptation actions cannot.

A Study on ESG Evaluation Indicators Through Chemical Accident Data Analysis and Double Materiality Assessment

This study focuses on identifying key factors that companies should prioritize to prevent chemical accidents from an ESG (Environmental, Social, and Governance) perspective. ESG provides insight into corporate sustainability by comprehensively considering both external impacts and internal risks. To achieve this, this study applied a scoring approach based on double materiality, assessing both internal and external impacts. The assessment process involved data collection, categorization of accident causes, score calculation, and prioritization of safety management items. Data from chemical accident statistics revealed that mechanical integrity, human factors, and preventive maintenance were the primary causes across all three countries. Internal impacts were evaluated by accident severity and frequency, while external impacts considered casualties and management priorities. Internal impact results showed mechanical integrity as critical in the U.S., preventive maintenance in the U.K., and human factors in Republic of Korea. For external impacts, human factors were most critical in Republic of Korea. To prioritize safety management elements for chemical accident prevention from an ESG perspective, this study categorized them into three tiers. Tier 1 represents the most critical elements requiring urgent attention, while Tier 3 includes the least critical elements. This tier classification is intended not as an absolute ranking but as a general reference for identifying overall trends in safety management priorities. Tier 1 included the U.K.’s preventive maintenance and human factors across all countries, with Republic of Korea’s human factors being the most vulnerable. Tier 2 revealed operating procedures and human factors as critical, with U.S. emergency preparedness and U.K. design highlighted. Tier 3, with impact scores below 1, was safest. These findings effectively identified safety management priorities to enhance accident prevention.

The Dual Role of Anxiety in Crisis Response: Emotional Intensification and Prosocial Behavior During the COVID-19 Pandemic

The COVID-19 pandemic has profoundly impacted mental health, intensifying negative emotions and challenging collective psychological resilience. This study examines the complex psychological interplay between social media engagement, emotional responses, and behavioral outcomes during crises. Using an online survey (N = 500) conducted during the COVID-19 pandemic, the findings reveal that heightened social media use for social interaction is associated with amplified emotional responses—particularly anxiety, anger, and sadness. Among these, anxiety demonstrated a dual role, acting as both a psychological stressor and a motivator for cooperative and prosocial behaviors, such as supporting government policies, volunteering, and donating. In contrast, anger and sadness were not associated with similar behavioral outcomes. These findings highlight the nuanced psychological impact of anxiety during crises, emphasizing its potential to drive adaptive responses amidst heightened emotional distress. This study contributes to a deeper understanding of how emotional and psychological processes, particularly anxiety, influence public behavior during crises, providing insights for mental health interventions and policy strategies.

Need for judicious selection of runoff inputs in a global flood model

Abstract Numerous flood hazard assessment and risk management studies depend on hydrodynamic flood models, which require detailed inputs. However, these models face challenges when assessing flood hazards and risks at national scales due to the unavailability of input data and high computational demands. Recent advancements in global flood models (GFMs) have emerged as promising solutions. These widely adopted GFMs, capable of producing flood characteristics, require runoff input typically derived from land surface models (LSMs) or global hydrological models (GHMs), which are prone to inherit cascading uncertainties. Moreover, the utilization of a single runoff input into a GFM can produce biased and misinterpreted flood hazards due to underestimation or overestimation of GFM outputs. To highlight these implications, the present study examines GFM simulations forced with eight state-of-the-art model runoff datasets, including LSMs, GHMs, and reanalysis observations, uncovering unsafe inter-model flood depth variation (IMDV). Focusing on the flood-prone Mahanadi River Basin (MRB) of India, the study observes that IMDV surpasses the self-help range of humans (0.2 m) for 65% of the MRB region, and exceeds human and vehicle safety thresholds (2 m) for 15% of the region, based on four past flood events from the Dartmouth Flood Observatory. These regions exhibiting high IMDV overlap with densely populated areas, potentially affecting 1.66–3.65 million people. Thus, the injudicious use of runoff in GFM for flood disaster planning can lead to inaccurate flood hazard and risk assessments, significantly affecting populous regions. An alternative approach is recommended, advocating for the use of multiple simulations incorporating diverse runoff datasets. This approach would generate conservative and optimistic flood scenarios, leveraging each model’s strengths. Such comprehensive hazard scenarios would enhance flood management and decision-making for policymakers by addressing the uncertainty and providing possible impacts through risk assessments.

Before Helene’s Landfall: Analysis of Disaster Risk Perceptions and Preparedness Assessment in the Southeastern United States in 2023

Hurricane Helene’s catastrophic impact on the Southeastern United States highlighted the critical importance of disaster preparedness. This study analyzes data from FEMA’s 2023 National Household Survey to examine pre-Helene disaster risk perception and preparedness levels among residents of six Southeastern states: Florida, Georgia, North Carolina, South Carolina, Tennessee, and Virginia. Our aim was to assess baseline preparedness and gain insights that could inform future disaster planning. The analysis revealed significant inter-state variations in risk perceptions, with Florida residents showing the highest awareness (84% believing a disaster was likely or very likely) and Virginia residents the lowest (63%). Perceived primary threats varied geographically, with hurricanes dominating concerns in coastal states (78% in Florida) and tornadoes in inland areas (68% in Georgia). Despite these differences, concerns about losing access to essential services during disasters were consistent across all states, with over 60% of residents extremely concerned about energy and food/shelter disruptions. While self-reported confidence in disaster preparedness was high across all states, there was a notable discrepancy between this confidence and residents’ estimated ability to manage without power or water. For instance, only 47% of Florida residents believed they could manage without power for more than one week despite their high-risk perception. Home or renters’ insurance coverage ranged from 65% in Florida to 77% in South Carolina. Hazard-specific insurance varied widely, with hurricane insurance coverage at 53% in Florida compared to about 12% in Tennessee. Our findings provide timely insights into the state of disaster preparedness in the wake of Helene, emphasizing more need for tailored, region-specific approaches to disaster preparedness and risk communication. The discrepancies between perceived and actual preparedness highlighted by this study can inform more effective strategies for enhancing community resilience in the face of increasing extreme weather events driven by climate change.

ANALISIS RISIKO TERHADAP PERILAKU YANG MEMBAHAYAKAN PADA PENGEMUDI DUMP TRUCK DALAM PENGANGKUTAN BATUBARA DI PT BAHANA BUMI MANDIRI KABUPATEN LAHAT PROVINSI SUMATERA SELATAN

PT Bahana Bumi Mandiri is an experienced logistics and contractor transportation provider company since 2016 located in South Sumatera. One of the accident prevention programs at PT Bahana Bumi Mandiri’s operations is to emphasize the importance of communication with dump truck drivers, and one form of implementing this programis to ensure that the unit is on the dump truck driver when operating. The aim of this research is to find out the risk of dangerous behavior of dump truck drivers when transporting coal and to find out efforts to improve or solve the risk and behavior that have been caused by dump truck drivers when transporting coal. The standard used at PT Bahana Bumi Mandiri is P2H (Daily Inspection and Checking). The implementation of safe driving at PT Bahana Bumi Mandiri is still relatively minimal so it is necessary to add safety driving to reduce potential dangers that could occur. However, it is necessary to know first the attitude of dump truck drivers by asking question in the form of a questionnaire so the data is processed so that the results can be known. If the need for safe driving in mines is not implemented more fully, it can increase the risk of accidents or incidents in the work emvironment.

Evaluation of Chatbots in the Emergency Management of Avulsion Injuries.

This study assessed the accuracy and consistency of responses provided by six Artificial Intelligence (AI) applications, ChatGPT version 3.5 (OpenAI), ChatGPT version 4 (OpenAI), ChatGPT version 4.0 (OpenAI), Perplexity (Perplexity.AI), Gemini (Google), and Copilot (Bing), to questions related to emergency management of avulsed teeth. Two pediatric dentists developed 18 true or false questions regarding dental avulsion and asked public chatbots for 3 days. The responses were recorded and compared with the correct answers. The SPSS program was used to calculate the obtained accuracies and their consistency. ChatGPT 4.0 achieved the highest accuracy rate of 95.6% over the entire time frame, while Perplexity (Perplexity.AI) had the lowest accuracy rate of 67.2%. ChatGPT version 4.0 (OpenAI) was the only AI that achieved perfect agreement with real answers, except at noon on day 1. ChatGPT version 3.5 (OpenAI) was the AI that showed the weakest agreement (6 times). With the exception of ChatGPT's paid version, 4.0, AI chatbots do not seem ready for use as the main resource in managing avulsed teeth during emergencies. It might prove beneficial to incorporate the International Association of Dental Traumatology (IADT) guidelines in chatbot databases, enhancing their accuracy and consistency.

Research on optimization of emergency supplies customs clearance strategy from the perspective of public health security based on Chinese trade data

BackgroundThis study is significant for improving the accuracy of Customs’ cross-border supervision of emergency supplies and ensuring the timely clearance of these essential goods.MethodsTo ensure both the convenience and security of Customs oversight regarding emergency supplies, this study first systematically collects and organizes representative data on the import and export trade of these supplies. Proposed an enhanced Recency Frequency Monetary (RFM) cluster analysis model, building on the principles of k-means clustering. Subsequently, the model is employed to cluster the import and export trade data of emergency supplies. Finally, the paper offers optimization suggestions for customs clearance supervision based on the analysis results.ResultsThe study primarily focuses on the collection and organization of import and export trade data across six major categories of representative emergency supplies. By employing K-means clustering techniques, the research develops an improved RFM cluster analysis model, referred to as TR-TF-TV, and subsequently proposes strategies for customs supervision of emergency supplies. By integrating K-means clustering techniques, this study develops an advanced RFM cluster analysis model, referred to as TR-TF-TV. It subsequently proposes customs supervision strategies for emergency supplies. These strategies include a clustering analysis of trade data to ensure safe and efficient customs clearance, the preservation of integrity and stability within the emergency supplies supply chain, the enhancement of the national emergency management system, and the improvement of response capabilities to public health emergencies.ConclusionThis analysis of trade data concerning the import and export of emergency supplies, based on the enhanced RFM clustering model, represents an exploratory initiative in original model design. Recognizing the inherent limitations associated with the model’s index design and data sample selection, we intend to refine these elements in future research, aiming to improve and validate the model to further optimize related countermeasures.

When Does Corporate Social Responsibility Backfire? Intentional Crises and the Insurance Value of CSR

ABSTRACTDrawing on attribution theory and expectancy violation theory, this study investigates the effect of corporate social responsibility (CSR) on stock market reactions in the context of intentional crises, during which stakeholders are likely to attribute crisis responsibility to the focal firm. Using a sample of Chinese listed firms from 2012 to 2022, we find that in the context of an intentional crisis, the stock market reacts more negatively to firms with higher prior CSR performance. Two contingency factors (i.e., media attention and state ownership) strengthen this negative relationship. This study contributes to the CSR literature by broadening knowledge of the insurance‐like effects of CSR and by identifying a “boomerang effect” of CSR in the context of intentional crises.

Defining Our Mission: A Content Analysis of U.S. Emergency Management Agency Mission Statements

Abstract The identity and mission of emergency management is a topic of frequent discussion among researchers and practitioners. However, the extent to which there is consensus across emergency management agencies about what their missions are is unclear. This study seeks to answer that question through a content analysis of the mission statements from 226 emergency management agencies representing all levels of government in the United States (i.e. federal, state, territorial, tribal, and local). Mission statements are a tool organizations use to indicate both externally and internally their raison d’etre. This study found there is consensus regarding emergency management agencies’ concern with “all-hazards” and the use of phases to organize their work. There were differences found in how agencies accounted for their constituencies, partner agencies, role identity, and goals. Despite some differences, this study found that overall agency mission statements across levels of government in the US align, suggesting consensus in the field of the mission of emergency management.

Using artificial intelligence to optimize anti-seizure treatment and EEG-guided decisions in severe brain injury.

Electroencephalography (EEG) is invaluable in the management of acute neurological emergencies. Characteristic EEG changes have been identified in diverse neurologic conditions including stroke, trauma, and anoxia, and the increased utilization of continuous EEG (cEEG) has identified potentially harmful activity even in patients without overt clinical signs or neurologic diagnoses. Manual annotation by expert neurophysiologists is a major resource limitation in investigating the prognostic and therapeutic implications of these EEG patterns and in expanding EEG use to a broader set of patients who are likely to benefit. Artificial intelligence (AI) has already demonstrated clinical success in guiding cEEG allocation for patients at risk for seizures, and its potential uses in neurocritical care are expanding alongside improvements in AI itself. We review both current clinical uses of AI for EEG-guided management as well as ongoing research directions in automated seizure and ischemia detection, neurologic prognostication, and guidance of medical and surgical treatment.

Reinforced NEAT Algorithms for Autonomous Rover Navigation in Multi-Room Dynamic Scenario

This paper demonstrates the performance of autonomous rovers utilizing NeuroEvolution of Augmenting Topologies (NEAT) in multi-room scenarios and explores their potential applications in wildfire management and search and rescue missions. Simulations in three- and four-room scenarios were conducted over 100 to 10,000 generations, comparing standard learning with transfer learning from a pre-trained single-room model. The task required rovers to visit all rooms before returning to the starting point. Performance metrics included fitness score, successful room visits, and return rates. The results revealed significant improvements in rover performance across generations for both scenarios, with transfer learning providing substantial advantages, particularly in early generations. Transfer learning achieved 32 successful returns after 10,000 generations for the three-room scenario compared to 34 with standard learning. In the four-room scenario, transfer learning achieved 32 successful returns. Heatmap analyses highlighted efficient navigation strategies, particularly around starting points and target zones. This study highlights NEAT’s adaptability to complex navigation problems, showcasing the utility of transfer learning. Additionally, it proposes the integration of NEAT with UAV systems and collaborative robotic frameworks for fire suppression, fuel characterization, and dynamic fire boundary detection, further strengthening its role in real-world emergency management.

Fighting with blunted tools? The politics of contemporary inflation management in southern Europe

This article compares the responses of the governments and social partners in Italy and Spain to the inflation crisis of 2021–2023. Faced with a common exogenous shock and sharing a comparable institutional setting in the labour market, the two countries’ responses to the inflation crisis differed substantially with regard to the policy mode of crisis response and the types of policy intervention. First, social partners’ involvement was far more significant in Spain, where peak-level agreements were signed setting a three-year trajectory for negotiated wage increases. In contrast, Italian governments proceeded unilaterally, with no attempts at collective bargaining coordination. Secondly, while the Italian government disbursed more fiscal resources through targeted compensatory measures, the Spanish government relied primarily on energy price controls and minimum wage revaluation, with lower overall fiscal expenditure. Finally, the distribution of inflation costs across population groups differed, with inflation in Spain being lower and having less regressive distributional effects than in Italy. We attribute the differing policy responses to the different partisan compositions and ideological orientations of the two governments.

Impact of the COVID-19 pandemic on alcohol consumption in young adults: A systematic review.

The COVID-19 pandemic caused unprecedented restrictions, leading to differences in the frequency and patterns of alcohol consumption, especially among young adults. This systematic review aims to investigate the overall evidence concerning changes in alcohol consumption in this period. Systematic review. Adhering to PRISMA and SWiM guidelines, this study's review protocol is registered in PROSPERO (CRD42023464591). The studies research was carried out in PubMed, Scopus, and Web of Science. Inclusion criteria involved observational studies focusing on participants aged 18 to 35, exploring alcohol consumption during at least the first wave of COVID-19, and publications in English or Spanish. A total of 28 studies conducted in different countries were included, European (18), North American (9), and Latin American (1). Although in many studies the overall prevalence of alcohol use was reduced, it was mainly among occasional users, in which the main motivation was the lack of social contact. It was exposed that participants with a high risk of problematic use increased their alcohol consumption, showing associated factors such as poor mental health, depressive symptoms, stress, and coping motivations. Males generally exhibited a higher risk of problem use and risky behaviours than females. During COVID-19, youth alcohol consumption decreased overall, especially among social drinkers, but increased among high-risk users due to factors like distress and loneliness. Similar trends during other disasters emphasize the importance of addressing high-risk drinking in disaster planning. Also, preventing high-risk drinking from adolescence and youth could be helpful in reducing the global burden and impact of alcohol consumption.

Research on leakage and diffusion behavior of hydrogen doped natural gas in integrated pipeline corridors based on data drive

With the wide application of hydrogen-doped natural gas (HBNG) in end users, laying pipelines in urban, comprehensive pipe corridors has become increasingly common. However, the leakage and diffusion of hydrogen-doped natural gas in confined or semi-confined spaces (e.g., utility corridors) can pose a severe safety hazard, as methane and hydrogen gas mixtures have a higher risk of explosion. Therefore, studying hydrogen-doped natural gas’s leakage and diffusion behavior in the comprehensive pipe gallery is essential to ensure its safe operation. This paper establishes a numerical model to study the diffusion law of hydrogen-doped natural gas leakage, and the concentration distribution under different conditions is analyzed. The evolution of the leakage and diffusion of hydrogen-doped natural gas under different hydrogen doping ratios, wind speeds, inlet and outlet spacing, and leakage port sizes were simulated, and the effects of these factors on gas diffusion and explosion hazard volume were discussed. In addition, the backpropagation neural network (BPNN) combined with the global optimization capability of genetic algorithm and the nonlinear mapping capability of neural network is used in this paper to provide a reliable technical means for the accurate prediction of explosion risk volume, which has important application value in the safety design of pipeline corridor and accident prevention and control. The results show that the diffusion range of gas in the pipe corridor increases significantly with the increase of hydrogen mixing ratio. When the hydrogen mixing ratio decreases from 20% to 0, the explosion volume of CH4 decreases by 12.25%. The explosion volume of H2 is close to 0. At the same time, the greater the distance between inlet and outlet, the wider the spread of the dangerous area, when the distance between inlet and outlet is reduced from 200 m to 100 m, the explosion volume of CH4 is reduced by 99.92%, and the explosion volume of H2 is reduced by 100%. In the case of emergency, the reasonable design of Distance between inlet and outlet and air flow configuration can help to quickly discharge harmful gases, ensure the safe evacuation and equipment maintenance in the pipe corridor, and have guiding significance for the ventilation design of the pipe corridor.

Community Efforts to Care for Animals During Climate Disasters: Experiences and Recommendations from an Australian Bushfire Affected Region

Abstract Formal disaster prevention, preparation, risk management, and response remain highly anthropocentric, with non-human animals afforded minimal attention, resourcing, and support. This article reports on informal community efforts to care for non-human animals during and after the 2019/2020 “Black Summer” bushfires in Australia, when over three billion animals were killed, injured, or displaced. We conducted 56 in-depth interviews with community members, government officials, and experts, and ran four full day workshops with community members to investigate: how communities sought to protect and care for domesticated, farmed, and wild animals; the factors that facilitated and impeded their efforts; and the changes they believed would lead to better outcomes for animals in disasters in the future. Key findings are that: human communities understood and treated non-human animals as part of their communities; humans went to extraordinary lengths to care for and rescue animals; these efforts were largely invisible to, and unsupported—even condemned—by formal emergency management agencies. We conclude that human-centric emergency and disaster management policies are at odds with community values and behaviors. We argue that disaster management must evolve to accommodate and support the realities of community-based rather than individual-based approaches, and must simultaneously expand to consider communities as multispecies.

Delineating urban flooding when incorporating community stormwater knowledge

Abstract Accurately delineating both pluvial and fluvial flood risk is critical to protecting vulnerable populations in urban environments. Although there are currently models and frameworks to estimate stormwater runoff and predict urban flooding, there are often minimal observations to validate results due to the quick retreat of floodwaters from affected areas. In this research, we compare and contrast different methodologies for capturing flood extent in order to highlight the challenges inherent in current methods for urban flooding delineation. This research focuses on two Philadelphia neighborhoods, Manayunk and Eastwick, that face frequent flooding. Overall, Philadelphia, PA is a city with a large proportion of vulnerable populations and is plagued by flooding, with expectations that flood risk will increase as climate change progresses. An array of data, including remotely sensed satellite imagery after major flooding events, Federal Emergency Management Agency’s Special Flood Hazard Areas, First Street Foundation’s Flood Factor, road closures, National Flood Insurance Program claims, and community surveys, were compared for the study areas. Here we show how stakeholder surveys can illuminate the weight of firsthand and communal knowledge on local understandings of stormwater and flood risk. These surveys highlighted different impacts of flooding, depending on the most persistent flood type, pluvial or fluvial, in each area, not present in large datasets. Given the complexity of flooding, there is no single method to fully encompass the impacts on both human well-being and the environment. Through the co-creation of flood risk knowledge, community members are empowered and play a critical role in fostering resilience in their neighborhoods. Community stormwater knowledge is a powerful tool that can be used as a complement to hydrologic flood delineation techniques to overcome common limitations in urban landscapes.