Machine Learning for Flood Resiliency—Current Status and Unexplored Directions - Uddameri, Venkatesh; Hernandez, E. Annette (Environments - MDPI, 2025)
A systems-oriented review of machine learning (ML) over the entire flood management spectrum, encompassing fluvial flood control, pluvial flood management, and resiliency-risk characterization was undertaken. Deep learners like long short-term memory (LSTM) networks perform well in predicting reservoir inflows and outflows. Convolution neural networks (CNNs) and other object identification algorithms are being explored in assessing levee and flood wall failures. The use of ML methods in pump station operations is limited due to lack of public-domain datasets. Reinforcement learning (RL) has shown promise in controlling low-impact development (LID) systems for pluvial flood management. Resiliency is defined in terms of the vulnerability of a community to floods. Multi-criteria decision making (MCDM) and unsupervised ML methods are used to capture vulnerability. Supervised learning is used to model flooding hazards. Conventional approaches perform better than deep learners and ensemble methods for modeling flood hazards due to paucity of data and large inter-model predictive variability. Advances in satellite-based, drone-facilitated data collection and Internet of Things (IoT)-based low-cost sensors offer new research avenues to explore. Transfer learning at ungauged basins holds promise but is largely unexplored. Explainable artificial intelligence (XAI) is seeing increased use and helps the transition of ML models from black-box forecasters to knowledge-enhancing predictors. © 2025 by the authors.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_5_Septembre_2025

Full-scale characterization of the effects of a bioretention system on water quality and quantity following the replacement of a mixed stormwater and combined sewer system - Le Cauchois, Pia; Doucet, Samuel; Bouattour, Ons; McQuaid, Natasha; Beral, Henry; Kõiv-Vainik, Margit; Bichai, Françoise; McCarthy, David; St-Laurent, Julien; Dagenais, Danielle; Bennekrela, Nesrine; Guerra, Juan; et al. (Blue-Green Systems, 2025)
ABSTRACT Urbanization is leading to more frequent flooding as cities have more impervious surfaces and runoff exceeds the capacity of combined sewer systems. In heavy rainfall, contaminated excess water is discharged into the natural environment, damaging ecosystems and threatening drinking water sources. To address these challenges aggravated by climate change, urban blue-green water management systems, such as bioretention cells, are increasingly being adopted. Bioretention cells use substrate and plants adapted to the climate to manage rainwater. They form shallow depressions, allowing infiltration, storage, and gradual evacuation of runoff. In 2018, the City of Trois-Rivières (Québec, Canada) installed 54 bioretention cells along a residential street, several of which were equipped with access points to monitor performance. Groundwater quality was monitored through the installation of piezometers to detect potential contamination. This large-scale project aimed to improve stormwater quality and reduce sewer flows. The studied bioretention cells reduced the flow and generally improved water quality entering the sewer system, as well as the quality of stormwater, with some exceptions. Higher outflow concentrations were observed for contaminants such as manganese and nitrate. The results of this initiative provide useful recommendations for similar projects for urban climate change adaptation.
Keywords: Infolettre_Ete_2025

The Impact of Flood Adaptation Measures on Affected Population’s Mental Health: A mixed method Scoping Review - El-Mousawi, Fatima; Ortiz, Ariel Mundo; Berkat, Rawda; Nasri, Bouchra (Cold Spring Harbor Laboratory, 2023)
AbstractThe frequency and severity of floods has increased in different regions of the world due to climate change. Although the impact of floods on human health has been extensively studied, the increase in the segments of the population that are likely to be impacted by floods in the future makes it necessary to examine how adaptation measures impact the mental health of individuals affected by these natural disasters. The goal of this scoping review is to document the existing studies on flood adaptation measures and their impact on the mental health of affected populations, in order to identify the best preventive strategies as well as limitations that deserve further exploration. This study employed the methodology of the PRISMA-ScR extension for scoping reviews to systematically search the databases Medline and Web of Science to identify studies that examined the impact of adaptation measures on the mental health of flood victims. The database queries resulted in a total of 857 records from both databases. Following two rounds of screening, 9 studies were included for full-text analysis. Most of the analyzed studies sought to identify the factors that drive resilience in flood victims, particularly in the context of social capital (6 studies), whereas the remaining studies analyzed the impact of external interventions on the mental health of flood victims, either from preventive or post-disaster measures (3 studies). There is a very limited number of studies that analyze the impact of adaptation measures on the mental health of populations and individuals affected by floods, which complicates the generalizability of their findings. There is a need for public health policies and guidelines for the development of flood adaptation measures that adequately consider a social component that can be used to support the mental health of flood victims.

Adaptation of Dual Drainage to Control Flooding and Enhance Combined Sewer Systems in Highly Urbanized Areas - Ossa Ossa, Juan Esteban; Duchesne, Sophie; Pelletier, Geneviève (2024)
Combined sewer surcharges in densely urbanized areas have become more frequent due to the expansion of impervious surfaces and intensified precipitation caused by climate change. These surcharges can generate system overflows, causing urban flooding and pollution of urban areas. This paper presents a novel methodology to mitigate sewer system surcharges and control surface water. In this methodology, flow control devices and urban landscape retrofitting are proposed as strategies to reduce water inflow into the sewer network and manage excess water on the surface during extreme rainfall events. For this purpose, a 1D/2D dual drainage model was developed for two case studies located in Montreal, Canada. Applying the proposed methodology to these two sites led to a reduction of the volume of wastewater overflows by 100% and 86%, and a decrease in the number of surface overflows by 100% and 71%, respectively, at the two sites for a 100-year return period 3-h Chicago design rainfall. It also controlled the extent of flooding, reduced the volume of uncontrolled surface floods by 78% and 80% and decreased flooded areas by 68% and 42%, respectively, at the two sites for the same design rainfall.

A data science approach to climate change risk assessment applied to pluvial flood occurrences for the United States and Canada - Bourget, Mathilde; Boudreault, Mathieu; Carozza, David A.; Boudreault, Jérémie; Raymond, Sébastien (ASTIN Bulletin: The Journal of the IAA, 2024)
There is mounting pressure on (re)insurers to quantify the impacts of climate change, notably on the frequency and severity of claims due to weather events such as flooding. This is however a very challenging task for (re)insurers as it requires modeling at the scale of a portfolio and at a high enough spatial resolution to incorporate local climate change effects. In this paper, we introduce a data science approach to climate change risk assessment of pluvial flooding for insurance portfolios over Canada and the United States (US). The underlying flood occurrence model quantifies the financial impacts of short-term (12–48 h) precipitation dynamics over the present (2010–2030) and future climate (2040–2060) by leveraging statistical/machine learning and regional climate models. The flood occurrence model is designed for applications that do not require street-level precision as is often the case for scenario and trend analyses. It is applied at the full scale of Canada and the US over 10–25 km grids. Our analyses show that climate change and urbanization will typically increase losses over Canada and the US, while impacts are strongly heterogeneous from one state or province to another, or even within a territory. Portfolio applications highlight the importance for a (re)insurer to differentiate between future changes in hazard and exposure, as the latter may magnify or attenuate the impacts of climate change on losses.

Forcing the Penman-Montheith Formulation with Humidity, Radiation, and Wind Speed Taken from Reanalyses, for Hydrologic Modeling - Ricard, Simon; Anctil, François (Water, 2019)
The Penman-Monteith reference evapotranspiration (ET0) formulation was forced with humidity, radiation, and wind speed (HRW) fields simulated by four reanalyses in order to simulate hydrologic processes over six mid-sized nivo-pluvial watersheds in southern Quebec, Canada. The resulting simulated hydrologic response is comparable to an empirical ET0 formulation based exclusively on air temperature. However, Penman-Montheith provides a sounder representation of the existing relations between evapotranspiration fluctuations and climate drivers. Correcting HRW fields significantly improves the hydrologic bias over the pluvial period (June to November). The latter did not translate into an increase of the hydrologic performance according to the Kling-Gupta Efficiency (KGE) metric. The suggested approach allows for the implementation of physically-based ET0 formulations where HRW observations are insufficient for the calibration and validation of hydrologic models and a potential reinforcement of the confidence affecting the projection of low flow regimes and water availability.

Tide-rainfall flood quotient: an incisive measure of comprehending a region’s response to storm-tide and pluvial flooding - Mohanty, Mohit Prakash; Sherly, Mazhuvanchery Avarachen; Ghosh, Subimal; Karmakar, Subhankar (Environmental Research Letters, 2020)
Abstract It is undeniable that coastal regions worldwide are facing unprecedented damages from catastrophic floods attributable to storm-tide (tidal) and extreme rainfall (pluvial). For flood-risk assessment, although recognizing compound impact of these drivers is a conventional practice, the marginal/individual impacts cannot be overlooked. In this letter, we propose a new measure, Tide-Rainfall Flood Quotient (TRFQ), to quantify the driver-specific flood potential of a coastal region arising from storm-tide or rainfall. A set of inundation and hazard maps are derived through a series of numerical and hydrodynamic flood model simulations comprising of design rainfall and design storm-tide. These experiments are demonstrated on three different geographically diverse flood-affected coastal regions in India. The new measure throws light on existing knowledge gaps on the propensity of coastal flooding induced by the marginal/individual contribution of storm-tide and rainfall. It shall prove useful in rationalizing long-term flood management strategies customizable for storm-tide and pluvial dominated global coastal regions.

Changes in cold region flood regimes inferred from long-record reference gauging stations - Burn, Donald H.; Whitfield, Paul H. (Water Resources Research, 2017)
Variability and nonstationarity in flood regimes of cold regions are examined using data from hydrometric reference streamflow gauging stations from 27 natural watersheds in Canada and adjacent areas of the United States. Choosing stations from reference networks with nearly 100 years of data allows for the investigation of changes that span several phases of some of the atmospheric drivers that may influence flood behavior. The reference hydrologic networks include only stations considered to have good quality data and were screened to avoid the influences of regulation, diversions, or land use change. Changes and variations in flood regimes are complex and require a multifaceted approach to properly characterize the types of changes that have occurred and are likely to occur in the future. Peaks over threshold (POT) data are extracted from daily flow data for each watershed, and changes to the magnitude, timing, frequency, volume, and duration of threshold exceedences are investigated. Seasonal statistics are used to explore changes in the nature of the flood regime based on changes in the timing of flood threshold exceedences. A variety of measures are developed to infer flood regime shifts including from a nival regime to a mixed regime and a mixed regime to a more pluvial-dominated regime. The flood regime at many of the watersheds demonstrates increased prominence of rainfall floods and decreased prevalence of snowmelt contributions to flood responses. While some individual stations show a relationship between flood variables and climate indices, these relationships are generally weak.
MAG ID: 2591956318

“Sickenin’ in the rain” – increased risk of gastrointestinal and respiratory infections after urban pluvial flooding in a population-based cross-sectional study in the Netherlands - Mulder, Annemieke Christine; Pijnacker, Roan; De Man, Heleen; Van De Kassteele, Jan; Van Pelt, Wilfrid; Mughini-Gras, Lapo; Franz, Eelco (BMC Infectious Diseases, 2019)
Keywords: Ouvrage_Collectif_Numéro1

Identification of changes in floods and flood regimes in Canada using a peaks over threshold approach - Burn, Donald H.; Whitfield, Paul H.; Sharif, Mohammed (Hydrological Processes, 2016)
Abstract Recent flood events in Canada have led to speculation that changes in flood behaviour are occurring; these changes have often been attributed to climate change. This paper examines flood data for a collection of 132 gauging stations in Canada. All of these watersheds are part of the Canadian Reference Hydrometric Basin Network (RHBN), a group of gauging stations specifically assembled to assist in the identification of the impacts of climate change. The RHBN stations are considered to have good quality data and were screened to avoid the influences of regulation, diversions, or land use change. Daily flow data for each watershed are used to derive a peaks over threshold (POT) dataset. Several measures of flood behaviour are examined based on the POT data, which afford a more in‐depth analysis of flood behaviour than can be obtained using annual maxima data. Analysis is conducted for four time periods ranging from 50 to 80 years in duration; the latter period results in a much smaller number of watersheds that have data for the period. The changes in flood responses of the watersheds are summarized by grouping the watersheds by size (small, medium, and large) and also by hydrologic regime (nival, mixed, and pluvial). The results provide important insights into the nature of the changes that are occurring in flood regimes of Canadian rivers, which include more flood exceedances, reduced maximum flood exceedance magnitudes for snowmelt events, and earlier flood events. Copyright © 2016 John Wiley & Sons, Ltd.
Keywords: Ouvrage_Collectif_Numéro1

Climate Change Impacts on Catchment Hydrology in Eastern Canada - Aygün, O.; Kinnard, C.; Campeau, S. (2019)
Snowmelt dominated regions are receiving increasing attention due to their noticeably rapid response to ongoing climate change, which raises concerns about the altered hydrological risks under climate change scenarios. This study aims to assess the climate change impacts on hydrology over two contrasted catchments in southern Québec: Acadie River and Montmorency River catchments. These river catchments represent two predominant landscapes of the St. Lawrence River watershed; an intensive farming landscape in the south shore lowlands and the forested landscape on the Canadian Shield on the north shore, respectively. In this study, a physically based hydrological model has been developed using the Cold Regions Hydrological Model (CRHM) for both of the catchments. The hydrological model outputs showed that we were able to simulate snow surveys and discharge measurements with a reasonable accuracy for both catchments. The acceptable performance of the model along with the strong physical basis of structure suggested that this model could be used for climate change sensitivity simulations. Based on the climate scenarios reviewed, a temperature increase up to 8°C and an increase in total precipitation up to 20% were analysed for both of the catchments. Both catchments were found to be sensitive to climate change, however the degree of sensitivity was found to be catchment specific. Snow processes in the Acadie River catchment were simulated to be more sensitive to warming than in the Montmorency River catchment. In case of 2°C warming, reduction in peak SWE was not be able to be compensated even by increased precipitation scenario. Given that, the Acadie River has already a mixed flow regime, even if 2°C warming is combined with an increase in precipitation, pluvial regime kept becoming more dominant, resulting in higher peaks of rain events. On the other hand, even 3°C of warming did not modify the flow regime of the Montmorency River. While there is shift towards earlier peak spring flows in both catchments, the shift was found to be more pronounced in the Acadie River. An earlier occurrence of snowmelt floods and an overall increase in winter streamflow during winter have been simulated for both catchments, which calls for renewed assessments of existing water supply and flood risk management strategies.
Conference Name: AGU Fall Meeting Abstracts ADS Bibcode: 2019AGUFM.C33B1572A
Keywords: Kinnard_Christophe

Resilience patterns of human mobility in response to extreme urban floods - Tang, Junqing; Zhao, Pengjun; Gong, Zhaoya; Zhao, Hongbo; Huang, Fengjue; Li, Jiaying; Chen, Zhihe; Yu, Ling; Chen, Jun (National Science Review, 2023)
ABSTRACT Large-scale disasters can disproportionately impact different population groups, causing prominent disparity and inequality, especially for the vulnerable and marginalized. Here, we investigate the resilience of human mobility under the disturbance of the unprecedented ‘720’ Zhengzhou flood in China in 2021 using records of 1.32 billion mobile phone signaling generated by 4.35 million people. We find that although pluvial floods can trigger mobility reductions, the overall structural dynamics of mobility networks remain relatively stable. We also find that the low levels of mobility resilience in female, adolescent and older adult groups are mainly due to their insufficient capabilities to maintain business-as-usual travel frequency during the flood. Most importantly, we reveal three types of counter-intuitive, yet widely existing, resilience patterns of human mobility (namely, ‘reverse bathtub’, ‘ever-increasing’ and ‘ever-decreasing’ patterns), and demonstrate a universal mechanism of disaster-avoidance response by further corroborating that those abnormal resilience patterns are not associated with people’s gender or age. In view of the common association between travel behaviors and travelers’ socio-demographic characteristics, our findings provide a caveat for scholars when disclosing disparities in human travel behaviors during flood-induced emergencies.

Assessing social vulnerability and identifying spatial hotspots of flood risk to inform socially just flood management policy. - Chakraborty, Liton; Thistlethwaite, Jason; Scott, Daniel; Henstra, Daniel; Minano, Andrea; Rus, Horatiu A. (Risk Analysis, 2022)
This study presents the first nationwide spatial assessment of flood risk to identify social vulnerability and flood exposure hotspots that support policies aimed at protecting high-risk populations and geographical regions of Canada. The study used a national-scale flood hazard dataset (pluvial, fluvial, and coastal) to estimate a 1-in-100-year flood exposure of all residential properties across 5721 census tracts. Residential flood exposure data were spatially integrated with a census-based multidimensional social vulnerability index (SoVI) that included demographic, racial/ethnic, and socioeconomic indicators influencing vulnerability. Using Bivariate Local Indicators of Spatial Association (BiLISA) cluster maps, the study identified geographic concentration of flood risk hotspots where high vulnerability coincided with high flood exposure. The results revealed considerable spatial variations in tract-level social vulnerability and flood exposure. Flood risk hotspots belonged to 410 census tracts, 21 census metropolitan areas, and eight provinces comprising about 1.7 million of the total population and 51% of half-a-million residential properties in Canada. Results identify populations and the geographic regions near the core and dense urban areas predominantly occupying those hotspots. Recognizing priority locations is critically important for government interventions and risk mitigation initiatives considering socio-physical aspects of vulnerability to flooding. Findings reinforce a better understanding of geographic flood-disadvantaged neighborhoods across Canada, where interventions are required to target preparedness, response, and recovery resources that foster socially just flood management strategies.
MAG ID: 4282937579

Flood exposure and social vulnerability in the United States - Tate, Eric; Rahman, Asif; Emrich, Christopher T.; Sampson, Christopher C. (Natural Hazards, 2021)
Human exposure to floods continues to increase, driven by changes in hydrology and land use. Adverse impacts amplify for socially vulnerable populations, who disproportionately inhabit flood-prone areas. This study explores the geography of flood exposure and social vulnerability in the conterminous United States based on spatial analysis of fluvial and pluvial flood extent, land cover, and social vulnerability. Using bivariate Local Indicators of Spatial Association, we map hotspots where high flood exposure and high social vulnerability converge and identify dominant indicators of social vulnerability within these places. The hotspots, home to approximately 19 million people, occur predominantly in rural areas and across the US South. Mobile homes and racial minorities are most overrepresented in hotspots compared to elsewhere. The results identify priority locations where interventions can mitigate both physical and social aspects of flood vulnerability. The variables that most distinguish the clusters are used to develop an indicator set of social vulnerability to flood exposure. Understanding who is most exposed to floods and where, can be used to tailor mitigation strategies to target those most in need.
MAG ID: 3119415889

Leveraging Hazard, Exposure, and Social Vulnerability Data to Assess Flood Risk to Indigenous Communities in Canada - Chakraborty, Liton; Thistlethwaite, Jason; Minano, Andrea; Henstra, Daniel; Scott, Daniel (International Journal of Disaster Risk Science, 2021)
Abstract This study integrates novel data on 100-year flood hazard extents, exposure of residential properties, and place-based social vulnerability to comprehensively assess and compare flood risk between Indigenous communities living on 985 reserve lands and other Canadian communities across 3701 census subdivisions. National-scale exposure of residential properties to fluvial, pluvial, and coastal flooding was estimated at the 100-year return period. A social vulnerability index (SVI) was developed and included 49 variables from the national census that represent demographic, social, economic, cultural, and infrastructure/community indicators of vulnerability. Geographic information system-based bivariate choropleth mapping of the composite SVI scores and of flood exposure of residential properties and population was completed to assess the spatial variation of flood risk. We found that about 81% of the 985 Indigenous land reserves had some flood exposure that impacted either population or residential properties. Our analysis indicates that residential property-level flood exposure is similar between non-Indigenous and Indigenous communities, but socioeconomic vulnerability is higher on reserve lands, which confirms that the overall risk of Indigenous communities is higher. Findings suggest the need for more local verification of flood risk in Indigenous communities to address uncertainty in national scale analysis.