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1. Bayesian modeling of flood control networks for failure cascade characterization and vulnerability assessment

   https://doi.org/10.1111/mice.12527  

   Dong, Shangjia ; Yu, Tianbo ; Farahmand, Hamed ; Mostafavi, Ali ( December 2019 , Computer-Aided Civil and Infrastructure Engineering)

   This paper presents a Bayesian network model to assess the vulnerability of the flood control infrastructure and to simulate failure cascade based on the topological structure of flood control networks along with hydrological information gathered from sensors. Two measures are proposed to characterize the flood control network vulnerability and failure cascade: (a) node failure probability (NFP), which determines the failure likelihood of each network component under each scenario of rainfall event, and (b) failure cascade susceptibility, which captures the susceptibility of a network component to failure due to failure of other links. The proposed model was tested in both single watershed and multiple watershed scenarios in Harris County, Texas using historical data from three different flooding events, including Hurricane Harvey in 2017. The proposed model was able to identify the most vulnerable flood control network segments prone to flooding in the face of extreme rainfall. The framework and results furnish a new tool and insights to help decision‐makers to prioritize infrastructure enhancement investments and actions. The proposed Bayesian network modeling framework also enables simulation of failure cascades in flood control infrastructures, and thus could be used for scenario planning as well as near‐real‐time inundation forecasting to inform emergency response planning and operation, and hence improve the flood resilience of urban areas.

    

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2. Investigating the Impact of Urban Layout Geometry on Urban Flooding

   A. Mustafa, M. Bruwier ( February 2019 , GEOProcessing 2019 : The Eleventh International Conference on Advanced Geographic Information Systems, Applications, and Services)

   In this paper, we use a procedural generation system to design urban layouts that passively reduce water depth during urban floods. The tool enables designing cities that passively lower flood depth everywhere or in chosen key areas. Our approach integrates a porosity-based hydraulic model and a parameterized urban generation system with an optimization engine so as to find the least cost modification to an initial urban layout. In order to investigate the relationship between urban layout design parameters and flood inundation depth, correlation coefficient method is used. This paper concludes that the most influential urban layout parameters are average road length and the mean parcel area. 

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3. Agricultural Innovations to Reduce the Health Impacts of Dams

   https://doi.org/10.3390/su13041869  

   Lund, Andrea J. ; Lopez-Carr, David ; Sokolow, Susanne H. ; Rohr, Jason R. ; De Leo, Giulio A. ( February 2021 , Sustainability)

   null (Ed.)

   Dams enable the production of food and renewable energy, making them a crucial tool for both economic development and climate change adaptation in low- and middle-income countries. However, dams may also disrupt traditional livelihood systems and increase the transmission of vector- and water-borne pathogens. These livelihood and health impacts diminish the benefits of dams to rural populations dependent on rivers, as hydrological and ecological alterations change flood regimes, reduce nutrient transport and lead to the loss of biodiversity. We propose four agricultural innovations for promoting equity, health, sustainable development, and climate resilience in dammed watersheds: (1) restoring migratory aquatic species, (2) removing submerged vegetation and transforming it into an agricultural resource, (3) restoring environmental flows and (4) integrating agriculture and aquaculture. As investment in dams accelerates in low- and middle-income countries, appropriately addressing their livelihood and health impacts can improve the sustainability of modern agriculture and economic development in a changing climate. 

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4. Policy diffusion in community-scale flood risk management.

   Noonan, D. S. ; Richardson, L. E. ; Sadiq, A. A. ( January 2018 , WIT transactions on engineering sciences)

   This study analyzes which communities adopted flood risk management practices during the past 25 years. In particular, we focus on community-scale flood management efforts undertaken voluntarily in towns and counties across the United States. In 1990, the US Federal Emergency Management Agency created the Community Rating System (CRS) to provide incentives to local governments to improve flood resilience. About 1,300 counties and cities voluntarily participate in the CRS, but most eligible communities do not participate. Here, we explore the factors shaping community CRS participation, such as flood risk, socio-economic characteristics, and economic resources, and we assess the competing phenomena of policy diffusion versus free riding. Previous models of community-scale flood mitigation activities have all considered each community’s decision as independent of one another. Yet one community’s flood management activities might directly or indirectly influence its neighbors’ mitigation efforts. Spillover effects or “contagion” may arise if neighboring communities learn from or seek to emulate or outcompete early adopting neighbors. Conversely, stricter regulation in one community may allow its neighbors to capitalize on looser regulation either by attracting more development or enjoying reduced “downstream” flood risks. This paper presents a conceptual model that allows for multiple forces affecting diffusion, such as copycatting and learning from neighboring communities, free-riding on neighbors’ efforts, and competing with neighbors to provide valuable amenities. We empirically test for these alternative diffusion pathways after controlling for the spatially correlated extant flood risks, building patterns, and demographics. The analysis integrates several large datasets to predict community flood risk management for all cities and counties in the US since 1990. Controls for local flood risk combined with a spatial lag regression model allow separate identification of alternative diffusion pathways. The results indicate strong evidence of copycatting and also suggest possible free-riding. 

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5. Flood Impacts on Critical Infrastructure in a Coastal Floodplain in Western Puerto Rico during Hurricane María

   https://doi.org/10.3390/hydrology8030104  

   Mejia Manrique, Said A. ; Harmsen, Eric W. ; Khanbilvardi, Reza M. ; González, Jorge E. ( September 2021 , Hydrology)

   null (Ed.)

   Flooding during extreme weather events damages critical infrastructure, property, and threatens lives. Hurricane María devastated Puerto Rico (PR) on 20 September 2017. Sixty-four deaths were directly attributable to the flooding. This paper describes the development of a hydrologic model using the Gridded Surface Subsurface Hydrologic Analysis (GSSHA), capable of simulating flood depth and extent for the Añasco coastal flood plain in Western PR. The purpose of the study was to develop a numerical model to simulate flooding from extreme weather events and to evaluate the impacts on critical infrastructure and communities; Hurricane María is used as a case study. GSSHA was calibrated for Irma, a Category 3 hurricane, which struck the northeastern corner of the island on 7 September 2017, two weeks before Hurricane María. The upper Añasco watershed was calibrated using United States Geological Survey (USGS) stream discharge data. The model was validated using a storm of similar magnitude on 11–13 December 2007. Owing to the damage sustained by PR’s WSR-88D weather radar during Hurricane María, rainfall was estimated in this study using the Weather Research Forecast (WRF) model. Flooding in the coastal floodplain during Hurricane María was simulated using three methods: (1) Use of observed discharge hydrograph from the upper watershed as an inflow boundary condition for the coastal floodplain area, along with the WRF rainfall in the coastal flood plain; (2) Use of WRF rainfall to simulate runoff in the upper watershed and coastal flood plain; and (3) Similar to approach (2), except the use of bias-corrected WRF rainfall. Flooding results were compared with forty-two values of flood depth obtained during face-to-face interviews with residents of the affected communities. Impacts on critical infrastructure (water, electric, and public schools) were evaluated, assuming any structure exposed to 20 cm or more of flooding would sustain damage. Calibration equations were also used to improve flood depth estimates. Our model included the influence of storm surge, which we found to have a minimal effect on flood depths within the study area. Water infrastructure was more severely impacted by flooding than electrical infrastructure. From these findings, we conclude that the model developed in this study can be used with sufficient accuracy to identify infrastructure affected by future flooding events. 

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