Application of multi-criteria decision-making on low-impact development practice selection for the Kinyerezi River sub-catchments in Dar es Salaam, Tanzania.

The impermeable areas in catchments are proportional to peak flows that result in floods in river reaches where the flow-carrying capacity is inadequate. The high rate of urbanization witnessed in the Kinyerezi River catchment in Dar es Salaam city has been noted to contribute to floods and siltation in the Msimbazi River. The Low-Impact Development (LID) practices that includes bio-retention (BR) ponds, rain barrels (RBs), green roofs (GRs), etc. can be utilized to mitigate portion of the surface runoff. This study aims to propose suitable LID practices and their sizes for mitigating runoff floods in the Kinyerezi River catchment using the Multi-Criteria Decision-Making (MCDM) approach. The results indicated that the BR and RBs were ranked high in capturing the surface runoff while the sediment control fences were observed to be the best in reducing sediments flowing into the BR. The proposed BR ponds were greater than 800 m2 with 1.2 m depth while RB sizes for Kinyerezi and Kisungu secondary schools and Kinyerezi and Kifuru primary schools were 2,730; 2,748; 1,385; and 1,020 m3, respectively. The BR ponds and RBs are capable of promoting water-demanding economic activities such as horticulture, gardening, car washing while reducing the school expenses and runoff generation.

Analysing the outbreaks of leptospirosis after floods in Kerala, India.

A growing number of studies have linked the incidence of leptospirosis with the occurrence of flood events. Nevertheless, the interaction between flood and leptospirosis has not been extensively studied to understand the influence of flood attributes in inducing new cases. This study reviews leptospirosis cases in relation to multiple flood occurrences in Kerala, India. Leptospirosis data were obtained for three years: 2017 (non-flood year) and two years with flooding-2018 (heavy flooding) and 2019 (moderate flooding). We considered the severity of flood events using the discharge, duration and extent of each flooding event and compared them with the leptospirosis cases. The distribution of cases regarding flood discharge and duration was assessed through descriptive and spatiotemporal analyses, respectively. Furthermore, cluster analyses and spatial regression were completed to ascertain the relationship between flood extent and the postflood cases. This study found that postflood cases of leptospirosis can be associated with flood events in space and time. The total cases in both 2018 and 2019 increased in the post-flood phase, with the increase in 2018 being more evident. Unlike the 2019 flood, the flood of 2018 is a significant spatial indicator for postflood cases. Our study shows that flooding leads to an increase in leptospirosis cases, and there is stronger evidence for increased leptospirosis cases after a heavy flood event than after a moderate flooding event. Flood duration may be the most important factor in determining the increase in leptospirosis infections.

Mortality Associated with Priority Diseases in Flood-Affected Areas Using District Health Information System (DHIS2) During September-December 2022: Pakistan Experience.

OBJECTIVES: To quantify the burden of communicable diseases and characterize the most reported infections during public health emergency of floods in Pakistan. METHODS: The study's design is a descriptive trend analysis. The study utilized the disease data reported to District Health Information System (DHIS2) for the 12 most frequently reported priority diseases under the Integrated Disease Surveillance and Response (IDSR) system in Pakistan. RESULTS: In total, there were 1,532,963 suspected cases during August to December 2022 in flood-affected districts (n = 75) across Pakistan; Sindh Province reported the highest number of cases (n = 692,673) from 23 districts, followed by Khyber Pakhtunkhwa (KP) (n = 568,682) from 17 districts, Balochistan (n = 167,215) from 32 districts, and Punjab (n = 104,393) from 3 districts. High positivity was reported for malaria (79,622/201,901; 39.4%), followed by acute diarrhea (non-cholera) (23/62; 37.1%), hepatitis A and E (47/252; 18.7%), and dengue (603/3245; 18.6%). The crude mortality rate was 11.9 per 10 000 population (1824/1,532,963 [deaths/cases]). CONCLUSION: The study identified acute respiratory infection, acute diarrhea, malaria, and skin diseases as the most prevalent diseases. This suggests that preparedness efforts and interventions targeting these diseases should be prioritized in future flood response plans. The study highlights the importance of strengthening the IDSR as a Disease Early Warning System through the implementation of the DHIS2.

Floods and cause-specific mortality in the UK: a nested case-control study.

BACKGROUND: Floods are the most frequent weather-related disaster, causing significant health impacts worldwide. Limited studies have examined the long-term consequences of flooding exposure. METHODS: Flood data were retrieved from the Dartmouth Flood Observatory and linked with health data from 499,487 UK Biobank participants. To calculate the annual cumulative flooding exposure, we multiplied the duration and severity of each flood event and then summed these values for each year. We conducted a nested case-control analysis to evaluate the long-term effect of flooding exposure on all-cause and cause-specific mortality. Each case was matched with eight controls. Flooding exposure was modelled using a distributed lag non-linear model to capture its nonlinear and lagged effects. RESULTS: The risk of all-cause mortality increased by 6.7% (odds ratio (OR): 1.067, 95% confidence interval (CI): 1.063-1.071) for every unit increase in flood index after confounders had been controlled for. The mortality risk from neurological and mental diseases was negligible in the current year, but strongest in the lag years 3 and 4. By contrast, the risk of mortality from suicide was the strongest in the current year (OR: 1.018, 95% CI: 1.008-1.028), and attenuated to lag year 5. Participants with higher levels of education and household income had a higher estimated risk of death from most causes whereas the risk of suicide-related mortality was higher among participants who were obese, had lower household income, engaged in less physical activity, were non-moderate alcohol consumers, and those living in more deprived areas. CONCLUSIONS: Long-term exposure to floods is associated with an increased risk of mortality. The health consequences of flooding exposure would vary across different periods after the event, with different profiles of vulnerable populations identified for different causes of death. These findings contribute to a better understanding of the long-term impacts of flooding exposure.

Evaluation of urban flood susceptibility through integrated Bivariate statistics and Geospatial technology.

Flood disasters are frequent natural disasters that occur annually during the monsoon season and significantly impact urban areas. This area is characterized by impermeable concrete surfaces, which increase runoff and are particularly susceptible to flooding. Therefore, this study aims to adopt Bi-variate statistical methods such as frequency ratio (FR) and weight of evidence (WOE) to map flood susceptibility in an urbanized watershed. The study area encompasses an urbanized watershed surrounding the Chennai Metropolitan area in southern India. The essential parameters considered for flood susceptibility zonation include geomorphology, soil, land use/land cover (LU/LC), rainfall, drainage, slope, aspect, Topographic Wetness Index (TWI), and Normalized Difference Vegetation Index (NDVI). The flood susceptibility map was derived using 70% of randomly selected flood areas from the flood inventory database, and the other 30% was used for validation using the area under curve (AUC) method. The AUC method produced a frequency ratio of 0.806 and a weight of evidence value of 0.865 contributing to the zonation of the three classes. The study further investigates the impact of urbanization on flood susceptibility and is further classified into high, moderate, and low flood risk zones. With the abrupt change in climatic scenarios, there is an increase in the risk of flash floods. The results of this study can be used by policymakers and planners in developing a preparedness system to mitigate economic, human, and property losses due to floods in any urbanized watershed.

Combining multisensor images and social network data to assess the area flooded by a hurricane event.

In this study, multisensor remote sensing datasets were used to characterize the land use and land covers (LULC) flooded by Hurricane Willa which made landfall on October 24, 2018. The landscape characterization was done using an unsupervised K-means algorithm of a cloud-free Sentinel-2 MultiSpectral Instrument (MSI) image, acquired during the dry season before Hurricane Willa. A flood map was derived using the histogram thresholding technique over a Synthetic Aperture Radar (SAR) Sentinel-1 C-band and combined with a flood map derived from a Sentinel-2 MSI image. Both, the Sentinel-1 and Sentinel-2 images were obtained after Willa landfall. While the LULC map reached an accuracy of 92%, validated using data collected during field surveys, the flood map achieved 90% overall accuracy, validated using locations extracted from social network data, that were manually georeferenced. The agriculture class was the dominant land use (about 2,624 km2), followed by deciduous forest (1,591 km2) and sub-perennial forest (1,317 km2). About 1,608 km2 represents the permanent wetlands (mangrove, salt marsh, lagoon and estuaries, and littoral classes), but only 489 km2 of this area belongs to aquatic surfaces (lagoons and estuaries). The flooded area was 1,225 km2, with the agricultural class as the most impacted (735 km2). Our analysis detected the saltmarsh class occupied 541 km2in the LULC map, and around 328 km2 were flooded during Hurricane Willa. Since the water flow receded relatively quickly, obtaining representative imagery to assess the flood event was a challenge. Still, the high overall accuracies obtained in this study allow us to assume that the outputs are reliable and can be used in the implementation of effective strategies for the protection, restoration, and management of wetlands. In addition, they will improve the capacity of local governments and residents of Marismas Nacionales to make informed decisions for the protection of vulnerable areas to the different threats derived from climate change.

Health Consequences Management in a Multi-Hazard Context: A Systematic Review of the Coincidence of Flood and the COVID-19 Pandemic.

OBJECTIVES: The co-occurring flood and coronavirus disease (COVID-19) increase the consequences for health and life. This study examined the strategies to manage the health consequences of the co-occurring flood and COVID-19, with a specific focus on these 2 challenges. METHODS: This review included all the studies published in peer-reviewed journals between January 1980 and June 2021. Several electronic databases were searched, including Scopus, Web of Science, and PubMed. Mixed Methods Appraisal Tools (MMT), version 2018, assessed the articles retrieved through a comprehensive and systematic literature search. Descriptive and thematic analyses were carried out to derive strategies for managing the health consequences of the simultaneous flood and COVID-19. RESULTS: Among 4271 identified articles, 10 were eligible for inclusion. In total, 199 strategies were identified in this review for managing the multi-hazard health consequences of flooding and COVID-19, which were classified into 9 categories and 25 subcategories. The categories included policy making and decision making, coordination, risk communication, logistics, planning, preparedness measures, response measures, social and humanitarian support, and actions of local communities and non-governmental organizations. CONCLUSIONS: Managing a multi-hazard and reducing its health consequences requires various actions. Flood management must be needed, and flood-affected people and their health should be protected.

Machine learning-based potential loss assessment of maize and rice production due to flash flood in Himachal Pradesh, India.

Flash floods in mountainous regions like the Himalayas are considered to be common natural calamities. Their consequences often are more dangerous than any flood event in the plains. These hazards not only put human lives at threat but also cause economic deflation due to the loss of lands, properties, and agricultural production. Hence, assessing the impact of such hazards in the existing agricultural system is of utmost importance to understand the probable crop loss. In this paper, we studied the efficiency of the remotely sensed microwave data to map the croplands affected by the flash flood that occurred in July 2023 in Himachal Pradesh, a mountainous state in the Indian Himalayan Region. The Una, Hamirpur, Kangra, and Sirmaur districts were identified as the most affected areas, with about 9%, 6%, 5.74%, and 3.61% of the respective districts' total geographical area under flood. Further, four machine learning algorithms (random forest, support vector regressor, k-nearest neighbor, and extreme gradient boosting) were evaluated to forecast maize and rice crop production and potential loss during the Kharif season in 2023. A regression algorithm with ten predictor variables consisting of the cropland area, two vegetation indices, and seven climatic parameters was applied to forecast the maize and rice production in the state. Amongst the four algorithms, random forest showed outstanding performance compared to others. The random forest regressor estimated the production of maize and rice with R2 more than 0.8 in most districts. The mean absolute error and the root mean squared error obtained from the random forest regressor were also minimal compared to the others. The maximum production loss of maize is estimated for Solan (54.13%), followed by Una (11.06%), and of rice in Kangra (19.1%), Una (18.8%) and Kinnaur (18.5%) districts. This indicated the utility of the proposed approach for a quick in-season forecast on crop production loss due to climatic hazards.

Dispersal and connectivity in increasingly extreme climatic conditions.

While climate change has been shown to impact several life-history traits of wild-living animal populations, little is known about its effects on dispersal and connectivity. Here, we capitalize on the highly variable flooding regime of the Okavango Delta to investigate the impacts of changing environmental conditions on the dispersal and connectivity of the endangered African wild dog (Lycaon pictus). Based on remote sensed flood extents observed over 20 years, we derive two extreme flood scenarios: a minimum and a maximum flood extent, representative of very dry and very wet environmental periods. These conditions are akin to those anticipated under increased climatic variability, as it is expected under climate change. Using a movement model parameterized with GPS data from dispersing individuals, we simulate 12,000 individual dispersal trajectories across the ecosystem under both scenarios and investigate patterns of connectivity. Across the entire ecosystem, surface water coverage during maximum flood extent reduces dispersal success (i.e., the propensity of individuals to disperse between adjacent subpopulations) by 12% and increases dispersal durations by 17%. Locally, however, dispersal success diminishes by as much as 78%. Depending on the flood extent, alternative dispersal corridors emerge, some of which in the immediate vicinity of human-dominated landscapes. Notably, under maximum flood extent, the number of dispersing trajectories moving into human-dominated landscapes decreases by 41% at the Okavango Delta's inflow, but increases by 126% at the Delta's distal end. This may drive the amplification of human-wildlife conflict. While predicting the impacts of climate change on environmental conditions on the ground remains challenging, our results highlight that environmental change may have significant consequences for dispersal patterns and connectivity, and ultimately, population viability. Acknowledging and anticipating such impacts will be key to effective conservation strategies and to preserve vital dispersal corridors in light of climate change and other human-related landscape alterations.

Health Disparities in the Aftermath of Flood Events: A Review of Physical and Mental Health Outcomes with Methodological Considerations in the USA.

PURPOSE OF REVIEW: This review applies an environmental justice perspective to synthesize knowledge of flood-related health disparities across demographic groups in the USA. The primary aim is to examine differential impacts on physical and mental health outcomes while also assessing methodological considerations such as flood exposure metrics, baseline health metrics, and community engagement. RECENT FINDINGS: In our review (n = 27), 65% and 72% of studies identified racial, ethnic, or socio-economic disparities in physical and mental health outcomes post-flooding, respectively. The majority of racial/ethnic disparities were based on Black race, while most socio-economic disparities were based on lower household income. Forty-two percent of studies lacked flood exposure metrics, but often identified disparities. Common flood exposure metrics included self-reported flooding, flood risk models, and satellite-based observations. Seventy percent of studies lacked baseline health measurements or suitable alternatives, and only 19% incorporated community engagement into their research design. The literature consistently finds that both physical and mental health burdens following flooding are unequally shared across racial, ethnic, and socio-economic groups. These findings emphasize the need for disaster risk reduction policies that address underlying vulnerabilities to flooding, unequal exposure to flooding, and progressive funding for recovery efforts. Findings also underscore the importance of methodological enhancements to facilitate precise assessments of flood exposure and health outcomes.

Flooding in semi-unformal urban areas in North Africa: Environmental and psychosocial drivers.

Urban flooding is recognized as a nature-driven disaster shaped by inherent factors such as climate, morphology, and hydrology, affecting vulnerability and flood exposure. While these factors play a paramount role, significant psychosocial intricate drivers are acknowledged, though they are challenging for prediction and assessment. This study delves into these drivers in a specific context, aiming to draw conclusions that extend beyond. It undertakes a comprehensive approach, integrating cloud-based Radar flood detection, analysis of flood causation patterns, and geostatistical analysis of a social survey based on cross-synthesis, contingency analysis, and structural equation modeling. In particular, we characterize the case of the coastal city of Tetouan in Morocco, which is representative in its environmental and socioeconomic settings to most cities in North Africa. It unraveled the nuanced interplay of psychosocial, economic, and territorial dynamics influencing flood exposure. The findings reveal how watershed location molds unique environmental exposures, steering nuanced, emotional, and behavioral responses among residents. Gender and education differentials reveal diverse perceptions and awareness of flood risks. Psychosocial intricacies come to the forefront, portraying education, income, and awareness as crucial mediators influencing cognitive and affective responses. Elevated education, increased income, and heightened awareness correlate with heightened perception and coping strategies. Findings reveal that risk perception significantly and differently influences risk acceptance, coping, and aversion through an array of identified key factors influencing coping strategies, mediating elements in flood damage relationships, and underscoring the pivotal role of perception in shaping responses to risk. Moreover, it found that lower risk acceptance leads to higher coping and aversion, and the latter positively affects coping, indicating that acceptance reduces the motivation to avoid the risk and decreases the willingness to adopt coping strategies to reduce the exposure. The outcomes carry critical implications for comprehending individual and collective social behaviors, informing strategies, and mitigating flood risk that apply at a wider context. It accentuates the inadequacy of relying solely on structural engineering for risk management, citing spatial constraints, misinformation, and lapses in prior-risk memory as compounding exposure challenges. This recognition catalyzes action, advocating tailored awareness campaigns, educational initiatives, and capacity-building programs, spotlighting the need for heightened individual profiles to enhance social understanding, engagement, and resilience. We anticipate profound insights, fostering a richer comprehension of urban flooding complexities and informing adaptive strategies on a broader scale.

Investigation of innovative designs of high-velocity channels for damping kinetic energy of flows.

In our contemporary world, demanding sustainable resource management, the study focuses on innovative fast flow channel designs. It investigates their efficacy in reducing flow kinetic energy, aiming to optimize water and energy management and diminish flood risks. Employing diverse methodologies, it analyzes and develops these designs, proving their substantial impact on stream energy management. These innovations not only enhance energy efficiency but also mitigate risks associated with excess kinetic energy, promoting safer stream management. This research significantly contributes to fluid dynamics and engineering, deepening the understanding of kinetic energy control in flows and offering potential solutions for water supply, environmental sustainability, and infrastructure safety challenges.

Enhancing solids deposit prediction in gully pots with explainable hybrid models: A review.

Urban flooding has made it necessary to gain a better understanding of how well gully pots perform when overwhelmed by solids deposition due to various climatic and anthropogenic variables. This study investigates solids deposition in gully pots through the review of eight models, comprising four deterministic models, two hybrid models, a statistical model, and a conceptual model, representing a wide spectrum of solid depositional processes. Traditional models understand and manage the impact of climatic and anthropogenic variables on solid deposition but they are prone to uncertainties due to inadequate handling of complex and non-linear variables, restricted applicability, inflexibility and data bias. Hybrid models which integrate traditional models with data-driven approaches have proved to improve predictions and guarantee the development of uncertainty-proof models. Despite their effectiveness, hybrid models lack explainability. Hence, this study presents the significance of eXplainable Artificial Intelligence (XAI) tools in addressing the challenges associated with hybrid models. Finally, crossovers between various models and a representative workflow for the approach to solids deposition modelling in gully pots is suggested. The paper concludes that the application of explainable hybrid modeling can serve as a valuable tool for gully pot management as it can address key limitations present in existing models.

Seasonal impact of constructed wetlands on nitrogen and phosphorus in sediments of flood control lakes with pollution assessment.

The primary drivers of eutrophication in lakes following the reduction of external nutrient inputs are the release of N and P from sediments. Constructed wetlands play a pivotal role in ameliorating N, P, and other biogenic element levels. However, the presence of large vegetation in these wetlands also substantially contributes to nutrient accumulation in sediments, a phenomenon influenced by seasonal variations. In this study, a typical constructed wetland was selected as the research site. The research aimed to analyze the forms of N and P in sediments during both summer and winter. Simultaneously, a comprehensive pollution assessment and analysis were conducted within the study area. The findings indicate that elevated summer temperatures, together with the presence of wetland vegetation, promote the release of N through the nitrification process. Additionally, seasonal variations exert a significant impact on the distribution of P storage. Furthermore, the role of constructed wetlands in the absorption and release of N and P is primarily controlled by the influence of organic matter on nitrate-nitrogen, nitrite-nitrogen, and available phosphorus, and is also subject to seasonal fluctuations. In summary, under the comprehensive influence of constructed wetlands, vegetation types, and seasons, sediments within the lake generally exhibit a state of mild or moderate pollution. Therefore, targeted measures should be adopted to optimally adjust vegetation types, and human intervention is necessary, involving timely sediment harvesting during the summer to reduce N and P loads, and enhancing sediment adsorption and retention capacity for N and P during the winter.

Effects of microplastics on microbial community structure and wheatgrass traits in Pb-contaminated riparian sediments under flood-drainage-planting conditions.

The coexistence of microplastics (MPs) and heavy metals in sediments has caused a potential threat to sediment biota. However, differences in the effects of MPs and heavy metals on microbes and plants in sediments under different sediment conditions remain unclear. Hence, we investigated the influence of polyethylene (PE) and polylactic acid (PLA) MPs on microbial community structure, Pb bioavailability, and wheatgrass traits under sequential incubation of sediments (i.e., flood, drainage, and planting stages). Results showed that the sediment enzyme activities presented a dose-dependent effect of MPs. Besides, 10 % PLA MPs significantly increased the F1 fractions in three stages by 11.13 %, 30.10 %, and 17.26 %, respectively, thus resulting in higher Pb mobility and biotoxicity. MPs altered sediment bacterial composition and structures, and bacterial community differences were evident in different incubation stages. Moreover, the co-exposure of PLA MPs and Pb significantly decreased the shoot length and total biomass of wheatgrass and correspondingly activated the antioxidant enzyme activity. Further correlation analysis demonstrated that community structure induced by MPs was mainly driven by sediment enzyme activity. This study contributes to elucidating the combined effects of MPs and heavy metals on sediment ecosystems under different sediment conditions.

Vegetation dieback in the Mississippi River Delta triggered by acute drought and chronic relative sea-level rise.

Vegetation dieback and recovery may be dependent on the interplay between infrequent acute disturbances and underlying chronic stresses. Coastal wetlands are vulnerable to the chronic stress of sea-level rise, which may affect their susceptibility to acute disturbance events. Here, we show that a large-scale vegetation dieback in the Mississippi River Delta was precipitated by salt-water incursion during an extreme drought in the summer of 2012 and was most severe in areas exposed to greater flooding. Using 16 years of data (2007-2022) from a coastwide network of monitoring stations, we show that the impacts of the dieback lasted five years and that recovery was only partial in areas exposed to greater inundation. Dieback marshes experienced an increase in percent time flooded from 43% in 2007 to 75% in 2022 and a decline in vegetation cover and species richness over the same period. Thus, while drought-induced high salinities and soil saturation triggered a significant dieback event, the chronic increase in inundation is causing a longer-term decline in cover, more widespread losses, and reduced capacity to recover from acute stressors. Overall, our findings point to the importance of mitigating the underlying stresses to foster resilience to both acute and persistent causes of vegetation loss.

Exploring optimal deep tunnel sewer systems to enhance urban pluvial flood resilience in the gangnam region, South Korea.

Urban pluvial flooding is becoming a global concern, exacerbated by urbanization and climate change, especially in rapidly developing areas where existing sewer systems lag behind growth. In order to minimize a system's functional failures during extreme rainfalls, localized engineering solutions are required for urban areas chronically suffering from pluvial floods. This study critically evaluates the Deep Tunnel Sewer System (DTSS) as a robust grey infrastructure solution for enhancing urban flood resilience, with a case study in the Gangnam region of Seoul, South Korea. To do so, we integrated a one-dimensional sewer model with a rapid flood spreading model to identify optimal routes and conduit diameters for the DTSS, focusing on four flood-related metrics: the total flood volume, the flood duration, the peak flooding rate, and the number of flooded nodes. Results indicate that, had the DTSS been in place, it could have reduced historical flood volumes over the last decade by 50.1-99.3%, depending on the DTSS route. Regarding the conduit diameter, an 8 m diameter was found to be optimal for minimizing all flood-related metrics. Our research also developed the Intensity-Duration-Frequency (IDF) surfaces in three dimensions, providing a correlation between simulated flood-related metrics and design rainfall characteristics to distinguish the effect of DTSS on flood risk reduction. Our findings demonstrate how highly engineered solutions can enhance urban flood resilience, but they may still face challenges during extreme heavy rainfalls with a 80-year frequency or above. This study contributes to rational decision-making and emergency management in the face of increasing urban pluvial flood risks.

Multi-hazard assessment of climate-related hazards for European coastal cities.

The assessment of risk posed by climate change in coastal cities encompasses multiple climate-related hazards. Sea-level rise, coastal flooding and coastal erosion are important hazards, but they are not the only ones. The varying availability and quality of data across cities hinders the ability to conduct holistic and standardized multi-hazard assessments. Indeed, there are far fewer studies on multiple hazards than on single hazards. Also, the comparability of existing methodologies becomes challenging, making it difficult to establish a cohesive understanding of the overall vulnerability and resilience of coastal cities. The use of indicators allows for a standardized and systematic evaluation of baseline hazards across different cities. The methodology developed in this work establishes a framework to assess a wide variety of climate-related hazards across diverse coastal cities, including sea-level rise, coastal flooding, coastal erosion, heavy rainfall, land flooding, droughts, extreme temperatures, heatwaves, cold spells, strong winds and landslides. Indicators are produced and results are compared and mapped for ten European coastal cities. The indicators are meticulously designed to be applicable across different geographical contexts in Europe. In this manner, the proposed approach allows interventions to be prioritized based on the severity and urgency of the specific risks faced by each city.

Coupling simulation of pipeline nodes - Storage tank linkage in urban high-density built-up areas using optimization model.

Climate change and urbanization contribute to the increased frequency of short-duration intense rainstorms. Traditional solutions often involve multiple scenarios for cost-effectiveness comparison, neglecting the rationality of placement conditions. The effective coupling and coordination of the location, number, size, and cost of storage tanks are crucial to addressing this issue. A three-phase approach is proposed to enhance the dynamic link between drainage pipeline and storage tanks in urban high-density built-up areas, integrating Python language, SWMM, the Elitist Non-Dominated Sorting Genetic Algorithm (NSGA-III), and the Analytic Hierarchy Process (AHP) methods. In the first stage, each node within the pipeline network is considered as a potential storage tank location. In the second stage, factors such as the length and diameter of the upstream connecting pipeline, as well as the suitability of the storage tank location, are assessed. In the third stage, the length and diameter of the downstream connecting pipeline node are evaluated. The results show that the 90 overflow nodes (overflow time >0.5h) have been cleared using the three-phase approach with a 50a (duration = 3h) return period as the rainfall scenario, which meets the flooding limitations. After the completion of the three-phase method configuration, the total overflow and SS loads were reduced by 96.45% and 49.30%, respectively, compared to the status quo conditions. These two indicators have decreased by 48.16 and 9.05%, respectively, compared to the first phase (the traditional method of only replacing all overflow nodes with storage tanks). The proposed framework enables decision-makers to evaluate the acceptability and reliability of the optimal management plan, taking into account their preferences and uncertainties.