Search Results (97)

Urban pluvial flooding (UPF) is an increasingly critical issue due to rapid urbanization and intensified precipitation driven by climate change that yet remains understudied in the Caribbean. This study analyzes the effects of UPF resulting from the transformation of a natural karstic landscape into an urbanized area considering a sub-watershed in Chetumal, Southern Mexican Caribbean, as a case study. Hydrographic numerical modeling was conducted using the IBER 2.5.1 software and the SCS-CN method to estimate surface runoff for a critical UPF event across three stages: (i) 1928—natural condition; (ii) 1998—semi-urbanized (78% coverage); and (iii) 2015—urbanized (88% coverage). Urbanization led to the orthogonalization of the drainage network, an increase in the sub-watershed area (20%) and mainstream length (33%), flow velocities rising 10–100 times, a 52% reduction in surface roughness, and a 32% decrease in the potential maximum soil retention before runoff occurs. In urbanized scenarios, 53.5% of flooded areas exceeded 0.5 m in depth, compared to 16.8% in non-urbanized conditions. Community-based knowledge supported flood extent estimates with 44.5% of respondents reporting floodwater levels exceeding 0.50 m, primarily in streets. Only 43.1% recalled past flood levels, indicating a loss of societal memory, although risk perception remained high among directly affected residents. The reported UPF effects perceived in the area mainly related to housing damage (30.2%), mobility disruption (25.5%), or health issues (12.9%). Although UPF events are frequent, insufficient drainage infrastructure, altered runoff patterns, and limited access to public shelters and communication increased vulnerability. Full article

Urban growth has intensified the generation of solid waste, particularly in densely populated and vulnerable neighborhoods, leading to environmental degradation and public health risks. This study presents a multidisciplinary methodology to estimate the mass of macroplastic litter mobilized from urban surfaces into nearby watercourses during storm events. Focusing on the Villa Páez neighborhood in Cordoba, Argentina—a data-scarce and flood-prone urban basin—the approach integrates socio-environmental surveys, field observations, Google Street View analysis, and hydrologic modeling using EPA SWMM 5.2. Macroplastic accumulation on streets was estimated based on observed waste density, and its transport under varying garbage collection intervals and rainfall intensities was simulated using a conceptual pollutant model. Results indicate that plastic mobilization increases substantially with storm intensity and accumulation duration, with the majority of macroplastic mass transported during high-return-period rainfall events. The study highlights the need for frequent waste collection, improved monitoring in vulnerable urban areas, and scenario-based modeling tools to support more effective waste and stormwater management. Full article

YouthMappers chapters, utilizing OpenStreetMap (OSM), play a pivotal role in tackling climate challenges through education and activism. This study investigates the influence of a booster grant project on enhancing Climate Activism and Education efforts through YouthMappers chapters in Sri Lanka. Through a geometric approach, the research integrates measurable survey data from OSM platform data from 223 YouthMappers chapter respondents at four (04) universities in Sri Lanka to evaluate five critical factors/dimensions: Capacity Building and Funding Support (CBFS), Climate Activism and Education (CAE), Community Engagement and Collaboration (CEC), Technical Skills and Resources (TSR), and Sustainability and Policy Integration (SPI). The Friedman test confirmed statistically significant differences across all factors’ variables (p < 0.001), highlighting strengths in technical competence and educational integration, with gaps identified in community engagement and sustainability. A Radial Basis Function (RBF) model revealed moderate predictive accuracy, excelling in variables like CAE and TSR but indicating higher error rates in SPI and CEC. Practical outcomes include flood risk maps, curriculum-integrated teaching schemes, and localized mapping workshops. These results underscore the booster grant’s role in enabling impactful, youth-led geospatial initiatives. However, challenges such as internet access, training gaps, and language barriers remain. This study recommends expanding student and community participation, refining training strategies, and integrating OSM into university curricula. These scalable interventions offer valuable insights for replication in other vulnerable regions, enhancing climate resilience through community-driven, data-informed youth engagement. Full article

One of the most significant factors shaping the formation of new urban structures is climate change—including global warming and the associated emerging issues—heatwaves, storms, hurricanes, floods, droughts, fires and others. In recent times, new threats have emerged, including war risks, radiation, pandemics and other potential factors, whose devastating consequences are no less severe than those of climate change. Concerning these and other potential threats, this work aims to develop a new, sustainable urban structure element—a territorial unit or complex to be used in creating a new city planning framework. The formation of this sustainable urban unit or complex is based on three fundamental sustainability principles—social, ecological and economic—the harmonious interaction of which can enable the creation of a safe, healthy and convenient urban environment for living, working and leisure. Such a structural urban complex would consist of a group of neighbourhoods with various building densities, enclosed by public transport streets that integrate the complex into the city’s overall spatial structure. To support the complex’s functioning, a structural element—a green core—is planned at its centre, serving as a space for residents’ recreation, protection from various threats and social interaction. Given that this technical, structural and urban territorial unit, in terms of its autonomous functionality, structure, composition, significance and other characteristics, is identical to a natural cell, it is proposed (based on the principles of bionics) to name this structural urban territorial unit an ‘urban cell’ or ‘urbocell’ for semantic clarity. Full article

Flood risk to rice production has previously been examined in terms of river basins or administrative units, incorporating data about the flood year, inundated area, precipitation, elevation, and impacts. However, there is limited knowledge about this topic, as most flood impact studies have focused on loss and damage to people and the economy. It remains important to identify how flood risk to rice production can be better identified within a long-term, community-based, analytical framework. In addition, flood risk studies in Sri Lanka tend to focus on single-year flood events within an administrative boundary, making it difficult to fully comprehend risks to rice production. This paper aims to fill these gaps by investigating long-term flood risk levels on rice production. With this aim, we collected and analyzed information about rice production, geospatial data, and 15-year precipitation records. Temporal-spatial maps were generated using Google Earth Engine JavaScript coding, Google Earth Pro, and OpenStreetMap. In addition, focus group discussions with farmers and key informant interviews were conducted to verify the accuracy of online information. The collected data were analyzed using descriptive statistics, GIS, and linear regression analysis methods. Regarding rice production impacts, we found that floods in the years 2006–2007, 2010–2011, and 2014–2015 had significant impacts on rice production with 20.5%, 75.8%, and 16.6% reductions, respectively. Flood risk maps identified low-, medium-, and high-risk areas based on 15-year flood events, elevation, proximity to water bodies, and 15-year flood-induced damage to rice fields. High risk areas were further studied through field discussions and interviews, showing the connection between past floods and poor water governance practices in terms of dam management. Our linear regression analysis found a marginal negative correlation between total seasonal rainfall and rice production. Full article

In conventional hydrology, a short-duration design rainstorm is typically used to estimate the design discharge in urban sewer systems. The reason for using a short duration is that engineers believe the time of concentration in urban watersheds is relatively small. The short-duration hyetograph is supposed to generate a flow hydrograph that accurately reflects the rainfall-runoff processes. In this study, we developed a street-sewer runoff model for an urban district of 2470 hectares. Detailed field flooding records were utilized to verify the stormwater model’s capability for inundation simulations. Subsequently, different rainfall series extracted from the recorded rainstorm data were used to investigate the causes of flooding corresponding to different durations of rainstorms. The results indicate that a 90 min main concentrated rainstorm causes small-scale flooding only; however, a 24 h rainfall series results in an extensive range of inundations. We further conducted similar short- and long-duration hyetograph tests in 16 urban drainage partitions (ranging from 2.3 to 193.5 hectares) to confirm the above findings. The results indicate that the maximum discharge in most partitions can only be found when the hyetograph duration exceeds 1080 min, which essentially contradicts previous engineering designs in urban watersheds in Taiwan. Full article

Green infrastructure (GI) plays a critical role in addressing urban fragmentation and flood vulnerability, especially in rapidly expanding cities where its optimal placement is essential to maximize social, ecological, and economic benefits. This study presents a multiscale methodology integrating spatial configuration and hydrological modeling to guide GI implementation in Ciudad Juárez, Mexico. The approach applies space syntax theory, fuzzy logic, and geospatial analysis across three spatial levels. At the city scale, the method evaluates street network integration and service accessibility to identify urban centers with potential for regeneration through GI. At the local scale, a 214-hectare area is analyzed using fuzzy multi-criteria decision analysis and Multiscale Geographically Weighted Regression (MGWR) to select the optimal locations for different nature-based solutions. At the microscale, spatiotemporal hydrological simulations of a 25-year return period rainfall event quantify the runoff and infiltration dynamics under different GI configurations, achieving infrastructure layouts that infiltrated over 1000 m³ of stormwater. This framework addresses the research gap on how connectivity and morphology can be combined to prioritize interventions based on flood risk data. The results offer a transferable strategy for integrating Sustainable Urban Drainage Systems (SUDSs) into complex data-scarce urban environments, supporting long-term urban resilience and multifunctional land-use planning. Full article

Introduction: Access to vaccines provided by the Brazilian National Immunization Program (NIP) to populations living in floodplains and hard-to-reach areas of the Amazon is complex and conditioned by the geographic characteristics of the region. The success of vaccination campaigns requires different strategies, technologies, and the involvement of professionals whose work goes beyond standard procedures and vaccination protocols. Objectives: To investigate the specificities of the immunization process of populations inhabiting floodplains and areas of difficult access in the municipality of Careiro da Várzea, in the state of Amazonas, Brazil. To analyze the theoretical and practical aspects of the National Immunization Program in the region. Methods: The case study included qualitative-descriptive techniques that combined data analysis, document analysis, and participant observation to reveal different socio-sanitary aspects of the immunization process of the Amazonian populations studied. The concepts of Street Level Bureaucracy and Social Technologies guided the analysis and description of the immunization process in the area studied. Results: The study described the geographic conditions, the social technologies used, and the individuals involved in the immunization process of the populations of communities and villages in flooded areas of the Amazon in Brazil. The high temperatures in the region create the need for thermal control in the storage of vaccines during their transfer to the communities and villages. The local coordination of the Imuniza SUS Program acts as a strategic mediator between the different bodies, ensuring the population’s access to vaccines, which means that the actions of government agents (Street Level Bureaucracy) are crucial to the functioning of the immunization program. Conclusions: The success of the immunization campaigns in the hard-to-reach flooded areas of the municipality is due to the existence of a virtuous cycle arising from the synergy between the different stakeholders that make up the immunization service; there is a clear relationship between the vaccination coverage rates achieved and the municipal administration’s commitment to public health. The immunization rates achieved in the municipality studied were compatible with the average established by the Brazilian Ministry of Health. This case study might enhance knowledge about health practices in this important world region. Full article

In recent years, the combined effects of rapid urbanization and climate change have led to frequent floods in urban areas. Rainstorm flood risk warning systems play a crucial role in urban flood prevention and mitigation. However, there has been limited research in China on nationwide urban flood risk warning systems based on rainfall predictions. This study constructs a two-level early warning system (EWS) at the national and urban levels using a two-dimensional hydrological–hydrodynamic model considering infiltration and urban drainage standards. A methodology for urban rainstorm flood risk warnings is proposed, leveraging short-term and high-resolution rainfall forecast data to provide flood risk warnings for 231 cities in central and eastern China. Taking Beijing as an example, a refined rainstorm flood warning technique targeting city, district, and street scales is developed. We validated the methodology with monitoring data from the “7.31” rainstorm event in 2023 in Beijing, demonstrating its applicability. It is expected that the findings of this study will serve as a valuable reference for the urban rainstorm flood risk warning system in China. Full article

With the acceleration of urbanization and due to the impact of climate warming, economic losses caused by urban waterlogging have become increasingly severe. To reduce urban waterlogging losses under the constraints of limited economic and time resources, it is essential to identify key waterlogging-prone areas for focused governance. Previous studies have often overlooked the spatial heterogeneity in the distribution of value and risk. Therefore, identifying the spatial distribution of land value and risk, and analyzing their spatial overlay effects, is crucial. This study constructs a “Waterlogging-Value-Loss” spatial analysis framework based on the hydrological and value attributes of land use. By developing a 1D–2D coupled hydrodynamic model, the study determines waterlogging risk distributions for different return periods. Combining these results with disaster loss curves, it evaluates land-use values and employs the bivariate local Moran’s I index to comprehensively assess waterlogging risk and land value, thereby identifying key areas. Finally, the SHAP method is used to quantify the contribution of water depth and value to waterlogging losses, and a Birch-K-means combined clustering algorithm is applied to identify dominant factors at the street scale. Using the central urban area of Beijing as a case study, the results reveal significant spatial heterogeneity in the distribution of urban waterlogging risks and values. Compared to traditional assessment methods that only consider waterlogging risk, the bivariate spatial correlation analysis method places greater emphasis on high-value areas, while reducing excessive attention to low-value, high-risk areas, significantly improving the accuracy of identifying key waterlogging-prone areas. Furthermore, the Birch-K-means combined clustering algorithm classifies streets into three types based on dominant factors of loss: water depth-dominated (W), value-dominated (V), and combined-dominated (WV). The study finds that as the return period increases, the dominant factors for 22.23% of streets change, with the proportion of W-type streets rising from 29% to 38%. This study provides a novel analytical framework that enhances the precision of urban flood prevention and disaster mitigation efforts. It helps decision-makers formulate more effective measures to prevent and reduce urban waterlogging disasters. Full article

Given the constraints of limited cultivated land resources, ensuring and enhancing crop productivity are crucial for food security. This study takes Chengdu as a case study. Using the cultivated land productivity (CLP) evaluation model, we calculated the cultivated land productivity index (CLPI) and analyzed its spatial distribution characteristics. The Geographical Detector model was employed to identify the main factors influencing CLP, and corresponding countermeasures and measures were proposed based on the limiting degrees of these factors. The findings reveal that Chengdu’s CLP index ranges from 1231 to 3053. Global spatial autocorrelation analysis indicates a spatial agglomeration pattern in Chengdu’s overall crop productivity distribution. The local spatial autocorrelation analysis demonstrates that township (street)-level crop productivity in Chengdu is primarily characterized by “high–high”, “low–low”, and “low–high” clusters. Key factors influencing the spatial differentiation of CLP in Chengdu include the agronomic management level, soil bulk density, irrigation guarantee rate, soil body configuration, field slope, and farmland flood control standard. Interaction detection shows that there are both double-factor and nonlinear enhancements among the factors. Specifically, the interaction between soil bulk density and the agronomic management level among other factors have the most explanatory power for the spatial differentiation of CLP. The CLP in Chengdu is highly restricted by its technical level, with the agronomic management level severely limiting CLP by more than 50%. These research results provide a theoretical reference for regional high-standard farmland construction and the protection and utilization of cultivated land resources. Full article

Many regions in Europe face increasing issues with flooding and droughts due to changing rainfall patterns caused by climate change. For example, higher rainfall intensities increase urban flooding. Nature-based solutions (NbS) are suggested as a key mitigation strategy for floods. This study aims to address and mitigate the challenges faced in Tivoli natural park in Ljubljana regarding high peak discharges and low-flow issues in the creek entering the sewer system. The study involves setting up, calibrating and validating a Hydrologic Engineering Centre–Hydrologic Modelling System (HEC-HMS) model using available data. This study analyses NbS, such as small ponds, green roofs and permeable paving, to reduce peak discharge. Runoff was reduced by an average of 32.4% with all NbS implemented and peak discharge by 20 L/s. Permeable parking performed best, with an average runoff reduction of 6.4%, compared to 4.8% for permeable streets and 5.9% for green roofs. The ponds reduced peak discharge, although their effectiveness varied between rainfall events. Rainfall events with higher volumes and durations tended to overwhelm the proposed solutions, reducing their effectiveness. The ability of HEC-HMS to model NbS is also discussed. The curve number (CN) parameter and impervious % alterations to simulate NbS provided quantitative data on changes in runoff and discharge. Full article

Constructing a precise and effective evaluation index system is crucial to flood disaster prevention and management in coastal areas. This study takes Lucheng District, Wenzhou City, Zhejiang Province, southeastern China, as a case study and constructs an evaluation index system comprising three criterion levels: disaster-causing factors, disaster-gestation environments, and disaster-bearing bodies. The weights of each evaluation index are determined by combining the Analytic Hierarchy Process (AHP) and the entropy method. The fuzzy matter-element model is utilized to assess the flood disaster risk in Lucheng District quantitatively. By calculating the correlation degree of each evaluation index, the comprehensive index of flood disaster risk for each street area is obtained, and the flood disaster risk of each street area is classified according to the risk level classification criteria. Furthermore, the distribution of flood disaster risks in Lucheng District under different daily precipitation conditions is analyzed. The results indicate that: (1) the study area falls into the medium-risk category, with relatively low flood risks; (2) varying precipitation conditions will affect the flood resilience of each street in Lucheng District, Wenzhou City. The flood disaster evaluation index system and calculation framework constructed in this study provide significant guidance for flood risk assessment in coastal plain cities. Full article

Previous studies have utilized machine learning algorithms that incorporate topographic and geological characteristics to model flood susceptibility, resulting in comprehensive flood maps. This study introduces an innovative integration of geospatial artificial intelligence for hazard mapping to assess flood risks on road networks within Portuguese municipalities. Additionally, it incorporates OpenStreetMap’s road network data to study vulnerability, offering a descriptive statistical interpretation. Through spatial overlay techniques, road segments are evaluated for flood risk based on their proximity to identified hazard zones. This method facilitates the detailed mapping of flood-impacted road networks, providing essential insights for infrastructure planning, emergency preparedness, and mitigation strategies. The study emphasizes the importance of integrating geospatial analysis tools with open data to enhance the resilience of critical infrastructure against natural hazards. The resulting maps are instrumental for understanding the impact of floods on transportation infrastructures and aiding informed decision-making for policymakers, the insurance industry, and road infrastructure asset managers. Full article

Urban waterlogging is a serious urban disaster, which brings huge losses to the social economy and environment of the city. As an important means of urban rainfall inundation analysis, numerical simulation plays an important role in promoting the risk assessment of urban waterlogging. Scientific and accurate assessment of waterlogging disaster losses is of scientific significance for the formulation of disaster prevention and mitigation measures and the guidance of post-disaster recovery and reconstruction. In this study, the SCS-CN hydrological model and GIS coupling numerical simulation method were used to simulate the inundation of urban waterlogging under four different rainfall return periods and to realize the visualization of the inundation range and waterlogging depth in Zhengzhou. At the same time, based on the numerical simulation results, the building is used as the basic assessment unit to construct a refined assessment framework for urban waterlogging risk at the street community level based on hazard, exposure, and vulnerability analysis. The refined risk assessment results have an important reference value for optimizing the working ideas of waterlogging control and providing a reference for local management departments to effectively deal with waterlogging disasters. Full article