Impact Of Floods Research Articles

Impact of floods on food security in rural Afghanistan

Floods, affecting roughly one million Afghans annually and causing substantial economic losses, is one of the most frequent disasters. This study examines the impacts of floods on household food security in rural Afghanistan, where 80 % of the population relies on subsistence farming and consists of 80 % of the food-insecure population. Based on the 2022 Data in Emergency Monitoring Round 5 dataset, a two-stage least squares with an instrumental variable is applied to analyze the relationship, considering district altitude and unconditional aid. Our findings reveal the negative impacts of floods, i.e., flood exposure decreases the Food Consumption Score (FCS) by 7.1 points and the Household Dietary Diversity Score (HDDS) by 0.14 points. Additionally, flood exposure increases the Household Hunger Scale (HHS) by 0.77 points and significantly raises the probability of moderate and severe food insecurity by 11 % and 20 %, respectively. Food aid offers a lifeline, boosting FCS by 1.54 points and reducing HHS by 0.42 points while mitigating food insecurity risks. High-altitude areas experience greater vulnerability, with higher hunger levels and lower dietary diversity compared to lowlands. Our research suggests prioritizing preventative strategies like area-based policies and flood preparedness plans over solely relying on post-disaster relief initiatives. Additionally, accounting for topographical variations, at least at the district level, is crucial for future food security studies in Afghanistan and similar contexts. These findings hold significant implications for achieving UN Sustainable Development Goals 2 (Zero Hunger) and 13 (Climate Action).

Multi-crowdsourced data fusion for modeling link-level traffic resilience to adverse weather events

Climate change leads to more frequent and intense weather events, posing escalating risks to road traffic. Crowdsourced data present new opportunities to monitor and investigate road traffic changes during adverse weather. This study utilizes two types of crowdsourced data: passively collected location data (PCLD) from mobile devices and actively collected user reports (ACUR) from the WAZE app, to examine the impact of floods, winter storms, and fog on road traffic. Three metrics derived from PCLD—speed change, event duration, and area under the curve (AUC)—along with an additional metric from ACUR, user-perceived severity, are utilized to assess link-level traffic resilience. All metrics are correlated with road characteristics such as functional class, number of lanes, divider types, road geometry, and historical traffic, to analyze underlying relationships and make forecasting. Using the Dallas–Fort Worth (DFW) metroplex in 2022 as a case, the study finds that overall, winter storms have the most substantial impact on road traffic, followed by floods and fog. Travel demand metrics, such as POI visits and traffic volume, experience a more significant decrease than traffic speed. The impact of weather also varies by road characteristics, with higher-class roads with greater volume and higher speed experiencing more substantial changes. Road geometry, such as minimal altitude and slopes, also significantly influences road traffic resilience under floods but not during winter storms. Moreover, the study reveals that ACUR may not accurately reflect the actual impact during extreme weather events, as few users are able to travel outside to actively act as “sensors”. In sum, this study evaluates a set of crowdsourced data for assessing link-level traffic resilience, designs various resilience metrics, and examines how they vary across road attributes and weather events, which are essential for guiding disaster preparedness, response, and recovery in road transportation systems.

A simple method to assess flood regulation supply in urban lawns

Floods have an important impact on life and loss of goods. Urban green spaces are crucial to mitigating flood impact. However, their capacity to prevent floods depends on their condition, especially in areas highly affected by human activities such as lawns. Here, we developed a simple method to assess flood regulation using soil penetration resistance as a proxy and tested it on an urban lawn in Vilnius (Lithuania) in winter. We developed an experimental design using an app for collecting data and working with it in a GIS environment. To understand their spatial relations, geostatistical (e.g., semi-variogram model and ordinary kriging mapping) and spatial statistics ((Moran's global autocorrelation index and Cluster and Outlier Analysis (Anselin Local Moran's I)) tools were applied. The preliminary results from the tested method showed that the lawn studied has different capacities to retain floods due to the management practices. Nevertheless, it is essential to be applied in different soil moisture conditions since flood regulation (soil penetration resistance) can be variable throughout the year.•A novel method was developed to estimate flood regulation using soil penetration resistance as a proxy;•An urban lawn was used to test the method and identify areas with low and high capacity for flood regulation;•The method quickly assesses lawn flood retention capacity in different environments.

Impact of Flooding and Drought Risks on the Cost of Bond Financing for Water Utilities.

The global water cycle has experienced significant changes due to the interplay of climate shifts and human activities, resulting in more frequent and severe droughts and floods. These shifts have started to impact the operational efficiency of water treatment and delivery systems. This, in turn, has implications for the economic performance of these assets and the climate-impacted cost of their financing through the issuing of municipal bonds. Analyzing a decade of water bond data (2009-2019), this study offers empirical evidence for the impact of flood and drought risks on bond investor demand to offset water risks. The results reveal that bond markets factored in coastal flood risks between 2013 and 2019, adjusting by 3-6 basis points (bps) per risk score unit, and riverine flood risks from 2009 to 2013, with a 5-11 basis points increase per risk score unit. These effects were primarily driven by bonds issued in the Pacific Coast and Great Plains regions, respectively. In contrast, the pricing of drought risks in the bond market followed a more nuanced pattern. Additionally, we show the channeling effects of water consumption and investor perceptions of climate change on water risk pricing in the bond market. These findings have significant implications for water risk management in the public sector as regions with heightened water risk exposure are perceived as riskier by market participants, leading to a higher cost of capital for municipalities and water agencies.

UPDAPS-Flood: a mechanistic-empirical flexible pavement analysis tool to evaluate the effect of flooding events on flexible pavement performance

ABSTRACT Flooding can cause considerable damage to flexible pavements and negatively affects their performance over time. This study aims to evaluate the flooding effects on the flexible pavement performance and the potential resiliency of the pavement network through a mechanistic-empirical (ME) pavement analysis approach. The Unified Pavement Distress Analysis and Prediction System (UPDAPS) programme, which includes ME analysis models, was used to develop the UPDAPS-Flood programme. A total of 7,655 flexible pavement sections were extracted from the Highway Pavement Management System (HPMS) database in three United States regions. Finally, the resiliency of the pavement network to flood events was quantified using the loss of pavement service life based on the international roughness index (IRI). The results showed that flooding has the highest impact on rutting performance, followed by IRI and fatigue cracking. It has been found that a proper drainage system can reduce the flooding impact by a factor of two. The predicted pavement performance was found to be very sensitive to the coefficients of the rutting model, which brings the need for further studies to re-calibrate the rutting prediction model at higher moisture content levels.

A MAP-based approach to identify the social vulnerability to flood hazard in states adjacent to Mexican Gulf

The impact of floods can significantly differ based on the local circumstances. The severity of the impact caused by a natural flood in one area compared to another depends on the distinct vulnerability factors present within the affected community, encompassing cultural, social, and economic aspects. Understanding a society's capacity to anticipate, adapt to, endure, and recover from the effects of natural floods relies on evaluating its social vulnerability, which is closely connected with potential risks and community resilience. This study adopts a framework that can analyze the interaction between natural hazards and social factors and is flexible to be applied to different geographic locations. This framework encompasses flood hazards and social vulnerability within the scope of flood risk reduction. This paper explores how social vulnerability can be integrated into the analysis of flood risks within the states adjacent to the Mexican Gulf. Initially, social components are selected and applied to measure and map the Social Vulnerability Index (SVI). Next, a MAP-based methodology is adopted to identify the spatial variability of social vulnerability concerning flood hazards. Then, a risk matrix is developed and the classifications on SVI map are aligned with those on a flood hazard map; provided by the Federal Emergency Management Agency (FEMA). This led to the development of a qualitative social vulnerability exposure map to flood hazards, emphasizing regions marked by high levels of both flood risk and social vulnerability. The findings of this study highlight the importance of integrating social vulnerability into flood risk mitigation policies and emergency management, and planning.

The Gaps Between Institutional and Practical Disaster Risk Management Measures on Coastal Flood Risks in South Korea’s Coastal Communities

Global warming and climate change significantly increase the frequency of coastal floods caused by sea level rise (SLR) as a permanent factor and hydrometeorological hazards as tentative factors. The combined risks will affect coastal communities. South Korea is gradually facing SLR risks, mainly in its southern coastal regions; however, disaster risk reduction (DRR) in coastal regions remains fragmented. This study aimed to investigate the status of DRR for coastal communities in South Korea by looking at government practices and testimonies from residents. This study reviewed DRR-related regulations and documents and collected data from interviews with local government officials, field visits, and informal conversations with residents in six coastal communities. The findings show that the coastal communities were less resilient to coastal floods than to other hazards, such as typhoons and heavy rains, and the potential consequences could be expanded due to demographic challenges, fragmented institutional systems, and low risk awareness. Moreover, this study emphasized the necessity of an integrated approach to reducing the impact of coastal floods caused by both SLR and other factors. It also highlighted the importance of coastal community engagement in local DRR activities through increasing risk awareness and adapting to environmental change based on appropriate risk information disclosure by the government. The impacts of coastal floods triggered by SLR and other hazard factors can be reduced by aligning practical regulatory measures with adaptive strategies and enhancing the disaster resilience of coastal communities.

Assessing the Impact and Coping Measures of Urban Flash Floods in Quetta during Monsoon 2022

The research study was carried out to assess the impact and coping measures of flash floods in Quetta City during Monsoon 2022. A combination of both qualitative and quantitative research method was used as part of “After-Only” research design. Primary data sources included survey of the affected areas in Quetta City and interviews of officials from various departments. Secondary data sources involved records from relevant departments, newspapers, journals and internet. Random sampling technique was adopted during the survey and thematic analysis of total sample size of 390 was carried out. .The findings have revealed that unchecked urbanization and construction in waterways amplified the damaged caused by flash floods in Quetta in 2022. The empirical evidences and survey conducted of affected areas pointed out lack of implementation of available regulatory measures. In order to mitigate the effect of any future flash flood, existing regulatory mechanism in required to be implemented in true letter and spirit which should include reclaiming of encroached waterways, planning for rehabilitation of affected households to suitable location and detailed urban planning to cater for expansion of Quetta City.

Utilization of Sentinel-1 Imagery for Mapping the Distribution of Floods in the Putussibau Kota Subdistrict and Surrounding Areas

Floods are a disaster that often occurs in the Putussibau Kota sub-district, West Kalimantan, because of its location where the Kapuas River passes. However, flood disaster mitigation efforts in this area are often hampered by the lack of information on flood distribution maps and impact predictions. This research utilizes the change detection and thresholding (CDAT) method applied to Sentinel-1 SAR data to map the distribution of floods in the Putussibau Kota sub-district and its surroundings, as well as analyze its impact on infrastructure and population. Next, the impact of the flood is calculated using an overlay technique between the flood map and the exposure map. The research results show that the flood distribution map for the August 2021 event had an accuracy of 0.76 and a kappa coefficient of 0.52. Next, the results of the flood impact evaluation showed that 37 km of roads, 2,700 buildings, and 11,700 people were affected by this incident. This analysis can be used to assist local governments in future flood mitigation efforts.

When resilience isn’t enough: natural disaster as an under-researched barrier

Natural disasters significantly impact the study plans of higher education students. This study explores the impact of catastrophic floods in the Australian city of Townsville in January 2019 on three enabling students enrolled in Skills for Tertiary Education Preparatory Studies (STEPS) at CQUniversity Australia (CQU). STEPS is a foundation course aimed at widening participation in line with the Australian government objectives to have more Australians complete a tertiary qualification. Students who successfully complete STEPS can gain direct entry to most higher education undergraduate courses. The aim of the study was to develop an understanding of the impacts of the Townsville floods on each participant along with an evaluation of the support offered by the University during the disaster. While the participants in this study showed extraordinary resilience and capacity for recovery throughout the disaster, all three participants withdrew from the STEPS course. While some educators may believe that students withdraw due to low resilience, this research suggests that resilience theory may not be a good fit in the context of natural disasters. Instead, a theory that considers the student and their community context is needed, such as the ecological theory by Bronfenbrenner (as cited in Paquette & Ryan, 2001). When extraordinary events occur, specific forms of institutional support are needed, such as Withdrawal Without Academic Penalty (WWAPs) and Leave of Absence with an acknowledgment of assessments passed to maintain enrolment. Such measures are likely to increase retention of students in widening participation initiatives.

Flood occurrence and impact models for socioeconomic applications over Canada and the United States

Flood occurrence and impact models for socioeconomic applications over Canada and the United States

Vulnerability, Resilience and Adaptation of Lagos Coastal Communities to Flooding

Lagos has been identified as one of the 50 cities most vulnerable to extreme sea levels. The state also ranked 30th among 136 port cities in terms of population exposure to flooding under a past climate scenario (2005) and 15th under a future climate scenario (2070s). The state faces significant environmental strains as a result of its geo-economic status. Some of the problems are wetland loss, pollution, population pressure, restricted access to drinkable water, and flooding. All these factors have contributed to the instability of Lagos ecosystems, but the impact of flooding is particularly significant because Lagos is surrounded by aquatic ecosystems and its low elevation and topography increase its susceptibility to flooding. The method adopted in this review involved the use of PICO (Population, Intervention, Control, and Outcomes) criteria to synthesize the research questions and objectives. Thereafter, PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines was employed for the study selection criteria, search strategies and data extraction methods. A broad search strategy involving databases (Google scholar, Science Direct), pertinent keywords and search filters was used to identify relevant articles and minimize selection bias. After the search, PICO criteria was again used to select the studies to be considered in the review. The selected text were downloaded and the essential scientific information were extracted and analyzed in the study. The impacts of flooding are numerous. Flooding is a key factors that has prevented Africa’s growing urban population from escaping poverty, and it also impedes the achievement of some SDGs. This is because many African cities lack the resources and infrastructures needed to withstand extreme weather conditions. Surviving in flood-prone cities like Lagos is a daunting task because flood affects livelihood, human health, and can even cause death. Specifically, the 2020 flood incidence in Nigeria affected about 40% of the local government areas, and 97% of the states, displacing over 120,000 persons and killing 68 persons aside from properties and farmlands destroyed. Women and children are the most vulnerable. The adoption of advanced flood risk management strategies could help in flood containment and management in the state.

Brief communication: Storm Daniel flood impact in Greece in 2023: mapping crop and livestock exposure from synthetic-aperture radar (SAR)

Abstract. For this brief communication, we analyzed the crop area and number of livestock exposed to flooding from the historic precipitation caused by Storm Daniel in central Greece on 3–8 September 2023. We derived from the near-real-time RAdar Produced Inundation Diary (RAPID) system an inundated area totaling 1150 km2, located mainly in the Thessalian plain. By overlaying a land cover map on the RAPID inundation map, we found that ∼ 820 km2 (70 %) of the inundated area was agricultural land. A detailed distribution map of crop type and animal farms revealed that the crop most affected by the flooding was cotton; the inundated area of more than 282 km2 comprised ∼ 30 % of the total area planted with cotton in central Greece. In terms of livestock, we estimated more than 14 000 ornithoids and 21 500 sheep and goats were affected. Consequences for agriculture and animal husbandry in Greece are expected to be severe.

Factors Affecting Survival of Common Sandpiper (Actitis hypoleucos) Nests along the Semi-Natural Vistula River in Poland.

Predation is an important factor limiting bird populations and is usually the main factor influencing nest survival. In riverine habitats, flooding poses an additional significant challenge. Our study aimed to elucidate the influence of nest location and incubation timing on the survival of common sandpiper nests in a large, semi-natural, lowland river. The survey was carried out in central Poland on the Vistula River, in 2014-2015, 2021, and 2023, along two river sections 2 km and 10 km in length. The nest survival rate was 27%, which is twice as low as that reported on small upland rivers, with flooding being an additional factor causing losses on the Vistula River. Our research showed that mammalian and avian predation accounted for 51% of losses and flooding for 49% of losses. The negative impact of floods on nest survival decreased as the breeding season progressed between May and July, while the chances of being depredated increased during the same period. Nests placed under shrubs were less likely predated than nests located in grass. Moreover, locating the nest in proximity to water increased nesting survival and in fact, more nests found in our study were situated close to the water's edge.

The Impacts of Floods on Crop Production in Kilosa District, Tanzania

Floods pose a major threat to agricultural production in Kilosa District, Tanzania, with the Mkondoa River being a primary source of flooding. This study aimed to assess the impacts of floods on crop production in Kilosa District. A cross-sectional research design was employed, involving a household survey of 120 respondents, focus group discussions and key informant interview with various stakeholders. The results show that floods have had significant negative impacts on crop production in the district. Over 80% of the population in Kilosa depend on agriculture, and this sector is affected by floods. Respondents reported substantial losses in crop yields and damage to farmland due to recurring flood events. The study also identified several initiatives conducted by the local community, organizations and the government to reduce the impact of floods. However, more effort is needed to minimize the impact on crop damage. The insights from this assessment can inform policymakers and development practitioners in designing and implementing effective flood management strategies for Kilosa District

Fluxes, Mechanisms, Influencing Factors, and Bibliometric Analysis of Tree Stem Methane Emissions: A Review

Methane (CH4) emissions exert large effects on the global climate. Tree stems are vital sources of emissions in ecosystem CH4 budgets. This paper reviewed the number of publications, journals, authors, keywords, research hotspots, and challenges. A total of 990 articles from 2006 to 2022 were collected based on the Web of Science database. The intellectual base was analyzed using CiteSpace 6.3.1 and VOSviewer 1.6.20 softwares. The results illustrated a growing trend in the study of tree stem methane emissions. The United States was the most research-active country; however, the most active institution was the Chinese Academy of Sciences in China. The research on stem methane emission by Vincent Gauci, Katerina Machacova, Zhi-Ping Wang, Kazuhiko Terazawa, Kristofer R. Covey, and Sunitha R. Pangala has had a significant impact. Current research indicates that stem CH4 emissions significantly vary among different tree species and are influenced by leaf type, forest type, tree height, whether the trees are alive or dead, and other environmental conditions (such as soil water content, air temperature, CO2 fluxes, and specific density). Soil CH4 fluxes and production by methanogens in heartwood were the primary sources of tree stem methane. Some pectin or cellulose from trees may also be converted into methane. Moreover, methane can be produced and released during the decomposition of deadwood by basidiomycetes. Furthermore, there are some trends and challenges for the future: (1) distinguishing and quantifying emissions from various sources; (2) accurately assessing the impact of floods on methane emissions is crucial, as the water level is the main factor affecting CH4 emissions; and (3) addressing the limited understanding of the microbial mechanisms of methane production in different tree species and investigating how microbial communities affect the production and emission of methane is vital. These advances will contribute to the accurate assessment of methane emissions from global ecosystems.

Integration of UH SUH, HEC-RAS, and GIS in Flood Mitigation with Flood Forecasting and Early Warning System for Gilireng Watershed, Indonesia

A flood forecasting and early warning system is critical for rivers that have a large flood potential, one of which is the Gilireng watershed, which floods every year and causes many losses in Wajo Regency, Indonesia. This research also introduces an integration model between UH SUH and HEC-RAS in flood impact analysis, as a reference for flood forecasting and early warning systems in anticipating the timing and occurrence of floods, as well as GIS in the spatial modeling of flood-prone areas. Broadly speaking, this research is divided into four stages, namely, a flood hydrological analysis using UH SUH, flood hydraulic tracing using a 2D HEC-RAS numerical model, the spatial modeling of flood-prone areas using GIS, and the preparation of flood forecasting and early warning systems. The results of the analysis of the flood forecasting and early warning systems obtained the flood travel time and critical time at the observation point, the total time required from the upstream observation point to level 3 at Gilireng Dam for 1 h 35 min, Mamminasae Bridge for 4 h 35 min, and Akkotengeng Bridge for 8 h 40 min. This is enough time for people living in flood-prone areas to evacuate to the 15 recommended evacuation centers.

Flood susceptibility assessment of Jhelum River Basin: A comparative study of TOPSIS, VIKOR and EDAS methods

Floods are frequent natural hazards that cause widespread destruction, particularly in low-elevated areas. This study focuses on identifying flood susceptible zones in the Kashmir Valley, known for historical flooding attributed to the overflow of the Jhelum River. Various Multi-Criteria Decision Making (MCDM) techniques, including Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Vise Kriterijumska Optimizacijai Compromission Resenje (VIKOR), and Evaluation Based on Distance from Average Solution (EDAS), were employed in this research. A total of 17 multidimensional factors were considered, and multicollinearity tests revealed no correlation among these factors. The results of the MCDM models indicate that areas along the Jhelum River are classified under very high flood susceptible zone. Specifically, Srinagar city is consistently classified under very high flood susceptible zone by all three models. Approximately 4.27 %, 9.67 %, and 5.39 % of the total area were identified as very high susceptible areas by TOPSIS, VIKOR, and EDAS, respectively. The models exhibited robust performance, as evidenced by the Area Under the Curve of the Receiver Operating Characteristics curve (AUC-ROC). Notably, VIKOR demonstrated excellent performance among the three models in generating flood susceptible maps. The favorable outcomes of these models underscore their potential application in similar regions facing comparable challenges. This study carries significant implications for policymakers, administrators, and local authorities involved in flood management within the Kashmir Valley. The insights provided can inform proactive measures and strategies to mitigate the impact of floods and enhance the overall resilience of the region.

SAR-based dynamic information retrieving of the Beijing-Tianjin-Hebei flood-inundation happened in July 2023, North China

Climate change-induced rainfalls have elevated the likelihood of flood occurrences, disrupting severely the normal functioning of people. Especially in the geographically unique Beijing-Tianjin-Hebei (BTH) plain in north China, an unanticipated sudden and long-duration flood-inundation happened in the summer of 2023 (referred to as the ‘23.7’ BTH flood). To address the dynamic information and recreate the flood evolution, we constructed a flood retrieving and analysis procedure to elucidate the development process and its impacts. First, accurately extract the temporal inundation extent of floods. Subsequently, we implemented the selected knowledge-driven algorithm to retrieve the dynamic information of flood evolution, including inundation extent, water depth, and shortest inundation duration. Furthermore, hazard-bearing bodies like cultivated land, population, and buildings were analyzed to improve our understanding of the flood impact. We uncovered that the ‘23.7’ BTH flood had caused extensive inundation and notably affected the Daqing River System, where the flood breached the river bank and submerged both buildings (0.96 km2) and cultivated land (241.46 km2), and led to prolonged inundation in the Baiyangdian area, which persisted for up to 30 days. This disastrous event highlights the great requirements to boost upstream flood storage capacity and enhance preparedness and rapid response capabilities for abnormal floods.

A High‐Performance Coupled Human And Natural Systems (CHANS) Model for Flood Risk Assessment and Reduction

AbstractIn recent years, flood risk in urban areas has been rapidly increasing due to unsustainable urban development, changes of hydrological processes and frequent occurrence of extreme weather events. Flood risk assessment should realistically take into account the complex interactions between human and natural systems to better inform risk management and improve resilience. In this study, we propose a novel Coupled Human And Natural Systems (CHANS) modeling framework to capture the intricate interactive human behaviors and flooding process at a high spatial resolution. The new CHANS modeling framework integrates a high‐performance hydrodynamic model with an agent‐based model to simulate the complex responses of individual households to the evolving flood conditions, leveraging the computing power of graphics processing units (GPUs) to achieve real‐time simulation. The framework is applied to reproduce the 2015 Desmond flood in the 2,500 km2 Eden Catchment in England, demonstrating its ability to predict interactive flood‐human dynamics and assess flood impact at the household‐level. The study also further explores the effectiveness of different flood risk management strategies, including the provision of early warning and distribution of sandbags, in mitigating flood impact. The new CHANS model potentially provides a useful tool for understanding short‐term human behaviors and their impact on flood risk during a flood event, which is important for the development of effective disaster risk management plans.