Disappearing cities on US coasts.

The sea level along the US coastlines is projected to rise by 0.25-0.3 m by 2050, increasing the probability of more destructive flooding and inundation in major cities1-3. However, these impacts may be exacerbated by coastal subsidence-the sinking of coastal land areas4-a factor that is often underrepresented in coastal-management policies and long-term urban planning2,5. In this study, we combine high-resolution vertical land motion (that is, raising or lowering of land) and elevation datasets with projections of sea-level rise to quantify the potential inundated areas in 32 major US coastal cities. Here we show that, even when considering the current coastal-defence structures, further land area of between 1,006 and 1,389 km2 is threatened by relative sea-level rise by 2050, posing a threat to a population of 55,000-273,000 people and 31,000-171,000 properties. Our analysis shows that not accounting for spatially variable land subsidence within the cities may lead to inaccurate projections of expected exposure. These potential consequences show the scale of the adaptation challenge, which is not appreciated in most US coastal cities.

A reproducible and streamlined approach to geospatial modelling for the Community Rating System.

Building flood resilience has become a priority in the United States as flood risks continue to rise. The National Flood Insurance Program's Community Rating System (CRS) serves as an excellent framework for local-level resilience planning by incentivizing a wide range of flood management practices. Despite the short-term and long-term benefits, resource barriers and limited technical capacity constrain communities' ability to participate in the program. In this study, we develop a GIS-based decision support tool to facilitate communities' participation in CRS. Specifically, we focus on Open Space Preservation (OSP) in the floodplain, a high credit earning CRS activity that is also promising in terms of flood protection. Most communities already preserve lands in the floodplain, indicating a missed opportunity for policyholders across the United States to receive financial benefit. Furthermore, OSP aligns with a growing national interest in the use of natural infrastructure for flood protection. Implementing OSP, however, requires extensive GIS analysis. Many communities lack the technical capacity needed to fulfill the program requirements. To address this challenge, the tool identifies areas that are already preserved and calculates credit estimates, providing communities with an indication of the financial benefit they are eligible to receive. In addition, the tool implements a novel methodology for mapping unprotected open space areas in the floodplain that could be eligible for CRS credit if preserved. These maps, along with estimates of future crediting scenarios, help communities pursue additional OSP credits through flood resilient land-use planning. The tool was applied to communities in the Commonwealth of Virginia as a case study. Statewide, over 39,000 unclaimed OSP credits were identified, suggesting an opportunity for significant expansion of the CRS in Virginia. Across the country, communities can use the GIS tool to perform the necessary GIS work more quickly and easily, engage with stakeholders, and make a strong financial argument for proactive flood management practices.

Hydrological performance of rain gardens having Calendula officinalis plant with varied planting mixtures.

The rain gardens (RGs) have been one of the best management practices in cities to reduce the impact of urban flooding. However, very little is known about various design parameters of RGs, viz., the type of plantation, planting mixtures, and RG dimensions. This study pertains to examining the influence of planting mixtures on the variations of percolation rates of the RG with Calendula officinalis plant and without plants. Six types of planting mixtures in different experimental RGs have been tried. It has been observed that the percolation rate increases with a higher percentage of compost in the planting mixture for RGs with and without plants. The percolation rate is highest for the planting mixture having 25% compost. The runoff rate reduces with a higher percentage of compost in the planting mixture for RGs with C. officinalis and bare surfaces. No runoff is produced in RGs with plant having a compost of more than 20% in the planting mixture. The outcome of the study will be useful in deciding the composition of the planting mixture which will keep the RG plant healthy and at the same time improve the hydrological performance leading to lowering urban flooding magnitude.

Risk evaluation and mitigation against flood danger in an arid environment. A case study (El Bayadh region, Algeria).

Floods are among the most serious and devastating phenomena of natural disasters. Cities adjacent to flood-prone areas in the last decades have played a major role in increasing the potential adverse effects of flood damage. This research study aims to evaluate and mitigate the risks of flood events in the El Bayadh region, which suffers from poor infrastructure and drained networks. To achieve this, it is necessary to evaluate rainfall intensities and their limits for durations from 0.167 to 24 h with return periods from 2 to 1000 years. Eight different frequency analysis distributions were fit to the historical rainfall data series over 43 years (1970-2012) using hypothesis-based goodness tests and information-based criteria. The most appropriate distributions were used to develop the rainfall intensity-duration-frequency (IDF) and flood risk-duration-frequency (RDF) curves for the study area. The results show that high-intensity rainfall values last for short durations, while high flood risk values last for intermediate durations. The results of the flood RDF curves can provide useful information for policy makers to make the right decisions regarding the effectiveness of the region's protection structures against future flood risks.

The Great 2011 Thailand flood disaster revisited: Could it have been mitigated by different dam operations based on better weather forecasts?

This paper revisits the 2011 Great Flood in central Thailand to answer one of the hotly debated questions at the time "Could the operation decisions of the flood control structures substantially mitigate the flood impacts in the downstream areas?". Using a numerical modeling approach, we develop a hypothesis such that the two upstream dam reservoirs: Bhumibol and Sirikit had more accurately forecasted the typhoon-triggered abnormal rainfall volumes and released more water earlier to save the storage capacity via 17 different scenarios or alternative operation schemes. We subsequently quantify the potential improvements, or reduced flood impacts in the downstream catchments, solely by changing the operation schemes of these two dam reservoirs, with all other conditions remaining unchanged. We observed that changing the operation schemes could have reduced only the flood depth while offering very limited improvements in terms of inundated areas for the lower Chao Phraya River Basin. Among 17 scenarios simulated, the inundated areas could have been reduced at most by 3.68%. This result justifies the limited role of these mega structures in the upstream during the disaster on one hand, while pointing to the necessity of handling local rainfall differently on the other. The paper expands the discussion into how the government of Thailand has drawn the lessons from the 2011 flood to better prepare themselves against the lurking flood risk in 2021, also triggered by tropical cyclones. The highlighted initiatives, both technical and institutional, could have provided important references for the large river catchment managers in Southeast Asia and with implications of our method beyond the present application region.

An Integrated Artificial Intelligence of Things Environment for River Flood Prevention.

River floods are listed among the natural disasters that can directly influence different aspects of life, ranging from human lives, to economy, infrastructure, agriculture, etc. Organizations are investing heavily in research to find more efficient approaches to prevent them. The Artificial Intelligence of Things (AIoT) is a recent concept that combines the best of both Artificial Intelligence and Internet of Things, and has already demonstrated its capabilities in different fields. In this paper, we introduce an AIoT architecture where river flood sensors, in each region, can transmit their data via the LoRaWAN to their closest local broadcast center. The latter will relay the collected data via 4G/5G to a centralized cloud server that will analyze the data, predict the status of the rivers countrywide using an efficient Artificial Intelligence approach, and thus, help prevent eventual floods. This approach has proven its efficiency at every level. On the one hand, the LoRaWAN-based communication between sensor nodes and broadcast centers has provided a lower energy consumption and a wider range. On the other hand, the Artificial Intelligence-based data analysis has provided better river flood predictions.

Shelter from the storm.

A plan to wall off Houston and nearby industry from flooding caused by hurricanes will cost tens of billions of dollars. Will it be enough?

Effectiveness assessment of reservoir projects for flash flood control, water supply and irrigation in Wangmo Basin, China.

Most flash floods in countries around the world occur in poor rural mountainous areas and typically cause more casualties and economic losses due to monitoring challenges and early warning difficulties. In mountainous regions, reservoir projects are a very effective measure for mitigating the risk of flash floods and can also be used for water supplies and irrigation, but there is a lack of research on the comprehensive benefit assessments of reservoirs. In this paper, we simulate the inundation extents of flash floods for the Wangmo Basin in China, where flash floods frequently occur, under different return periods using the HEC-HMS (HEC-Hydrologic Modelling System) model and FLO-2D model and compare the resulting housing losses with and without reservoirs. The results indicate that using dam and reservoir operations for flood control in the Wangmo River Basin decreases the flooded housing area in the county centre by approximately 12.9 %-30.2 %, which results in housing losses reductions of 19.7 %-45.7 %.These dams and reservoirs will begin to make a profit during the 38th year of operation, and the average annual net benefit reaches 101.76 million RMB in 50 years, which is equivalent to 1.43 % of the GDP of Wangmo County; the net benefits of flood control, water supply and irrigation accounted for 0.4 %, 1.0 % and 0.03 %, respectively. Priority should be given to planning and building these water conservation measures to help these poor mountainous areas. The construction of dams and reservoirs can contribute to decreasing losses in poverty and disaster-prone regions. The effectiveness evaluation framework for dams and reservoirs presented in this study can be applied to other mountainous basins for flood control and local development.

The challenge of unprecedented floods and droughts in risk management.

Risk management has reduced vulnerability to floods and droughts globally1,2, yet their impacts are still increasing3. An improved understanding of the causes of changing impacts is therefore needed, but has been hampered by a lack of empirical data4,5. On the basis of a global dataset of 45 pairs of events that occurred within the same area, we show that risk management generally reduces the impacts of floods and droughts but faces difficulties in reducing the impacts of unprecedented events of a magnitude not previously experienced. If the second event was much more hazardous than the first, its impact was almost always higher. This is because management was not designed to deal with such extreme events: for example, they exceeded the design levels of levees and reservoirs. In two success stories, the impact of the second, more hazardous, event was lower, as a result of improved risk management governance and high investment in integrated management. The observed difficulty of managing unprecedented events is alarming, given that more extreme hydrological events are projected owing to climate change3.

Delta-scale solutions for human-scale needs.

Global studies inform river management needed for landscape sustainability.

Analysis of factors influencing levee safety using the DEMATEL method.

River embankments are the basic and the oldest measures of protecting areas potentially subjected to flooding, and at the same time pose a serious threat to their environment in the event of damage or failure. The technical condition of the levees and its regular evaluation is a key element of their safety. A general assessment of the technical condition of a levee is the result of many interacting factors and parameters that depend on each other to a varying degree. Therefore, it is necessary to consider the cause-and-effect links between the interrelationships of numerous parameters and sensors of significant impact. In this article the decision-making trial and evaluation laboratory (DEMATEL) method was applied to develop a cause-and-effect model for factors impacting the condition and safety of levees. Effective factors impacting the technical condition of a levee were identified; relationships between these factors were determined; a cause-and-effect model was developed based on identified factors; factors were categorized based on the dependence scale and influential indicators of each factors used in the DEMATEL method. The obtained results demonstrate that three following factors: hydrological factor, type and condition of soils in levee body and condition of levee areas (inter-levee and landside) play the most important role for levee safety. The results of this study can support traditional assessments of hydrotechnical structure or assist entities managing levees.

Improving flood hazard datasets using a low-complexity, probabilistic floodplain mapping approach.

As runoff patterns shift with a changing climate, it is critical to effectively communicate current and future flood risks, yet existing flood hazard maps are insufficient. Modifying, extending, or updating flood inundation extents is difficult, especially over large scales, because traditional floodplain mapping approaches are data and resource intensive. Low-complexity floodplain mapping techniques are promising alternatives, but their simplistic representation of process falls short of capturing inundation patterns in all situations or settings. To address these needs and deficiencies, we formalize and extend the functionality of the Height Above Nearest Drainage (i.e., HAND) floodplain mapping approach into the probHAND model by incorporating an uncertainty analysis. With publicly available datasets, the probHAND model can produce probabilistic floodplain maps for large areas relatively rapidly. We describe the modeling approach and then provide an example application in the Lake Champlain Basin, Vermont, USA. Uncertainties translate to on-the-ground changes to inundated areas, or floodplain widths, in the study area by an average of 40%. We found that the spatial extent of probable inundation captured the distribution of observed and modeled flood extents well, suggesting that low-complexity models may be sufficient for representing inundation extents in support of flood risk and conservation mapping applications, especially when uncertainties in parameter inputs and process simplifications are accounted for. To improve the accuracy of flood hazard datasets, we recommend investing limited resources in accurate topographic datasets and improved flood frequency analyses. Such investments will have the greatest impact on decreasing model output variability, therefore increasing the certainty of flood inundation extents.