Flood Threshold Research Articles

A stochastic optimization model for patient evacuation from health care facilities during hurricanes

We propose a rigorous modeling and methodological effort that integrates statistical implementation of hydrology models in predicting inland and coastal flood scenarios due to hurricanes and a scenario-based stochastic integer programming model which suggests resource and staging area decisions in the first stage and the evacuation decisions in the second stage. This novel study combines physics-based flood prediction models and stochastic optimization for large-scale multi-facility coordination of hospital and nursing home evacuations before impending hurricanes. The optimization model considers scenario-dependent evacuation demand, transport vehicles with varying capacities, and both critical and non-critical patients. Utilizing Hurricane Harvey of 2017 as a case study and actual healthcare facility locations in southeast Texas, we explore various evacuation policies, demonstrating the impact of routing strategies, staging area decisions, flood thresholds, and receiving facility capacities on evacuation outcomes. One of the findings is that choosing staging area(s) and deploying evacuation vehicles optimally considering the uncertainty of the hurricane’s path at the time of decision making could have significant effect on the total cost of the operation and evacuation time experienced by the evacuees. We also show the non-negligible value of the scenario-based staging and routing solution conservatively calculated in relation to a single scenario solution using the concept of value of stochastic solution.

Establishing flood thresholds for sea level rise impact communication.

Sea level rise (SLR) affects coastal flood regimes and poses serious challenges to flood risk management, particularly on ungauged coasts. To address the challenge of monitoring SLR at local scales, we propose a high tide flood (HTF) thresholding system that leverages machine learning (ML) techniques to estimate SLR and HTF thresholds at a relatively fine spatial resolution (10 km) along the United States' coastlines. The proposed system, complementing conventional linear- and point-based estimations of HTF thresholds and SLR rates, can estimate these values at ungauged stretches of the coast. Trained and validated against National Oceanic and Atmospheric Administration (NOAA) gauge data, our system demonstrates promising skills with an average Kling-Gupta Efficiency (KGE) of 0.77. The results can raise community awareness about SLR impacts by documenting the chronic signal of HTF and providing useful information for adaptation planning. The findings encourage further application of ML in achieving spatially distributed thresholds.

Uncertainty propagation analysis for distributed hydrological forecasting using a neural network

AbstractThe last few decades have presented a significant increase in hydrological disasters, such as floods. In some countries, most of the environmental, socioeconomic, and biodiversity losses are caused by floods. Thus, flood forecasting is crucial to support an efficient disaster warning system. This work proposes a model for hydrological forecasting based on a neural network with a geographically aligned input named GeoNN. It employs weather radar data to obtain accumulated rainfall in each grid cell of the watershed and make 15‐ and 120‐min predictions of the outlet river level. An uncertainty propagation analysis was performed for GeoNN from a collection of test cases obtained by either using different schemes of the dataset partitioning or introducing different additive‐noise rates to the input data to provide a probability of flood occurrence and also an ensemble prediction. Both this probability and the ensemble were able to detect occurrences of river levels exceeding a given flood threshold.

Threshold-based flood early warning in an urbanizing catchment through multi-source data integration: Satellite and citizen science contribution

An effective flood early warning system is vital to take action to save lives and protect properties in urban areas which are increasingly prone to flooding. Despite substantial progress in flood early warning systems, limited available and accessible data often impede their advancement and reliability. Engaging communities affected by flooding can help address data and information gaps in flood early warning systems, facilitated by appropriate methods. This study developed and evaluated a flood threshold combination method to support a community-based flood early warning system in the Akaki catchment, home to Addis Ababa, the capital city of Ethiopia. Various flood threshold combinations were formulated, calibrated and validated by integrating multiple sources of data: rainfall, antecedent precipitation index estimates, Sentinel-1 Synthetic Aperture Radar satellite time series of flood extent, long-term simulated streamflow, citizen science data, river water level and three days lead-time numerical weather prediction rainfall forecast. During validation, the rainfall and river water level threshold combination outperformed other threshold combinations with probability of detection, false alarm ratio, and critical success index estimates of 0.74, 0.18 and 0.63, respectively. The flood threshold combination showed high detection performance for most flooding conditions. Flood forecasts with a 1-day lead-time exhibited a high likelihood in detecting historical severe flood events. The study provides a tested methodology for selecting suitable flood threshold-combinations, enhance the engagement of citizen scientists in a community–based flood early warning system in urban communities.

The Influence of Future Changes in Tidal Range, Storm Surge, and Mean Sea Level on the Emergence of Chronic Flooding

AbstractSea‐level rise is leading to increasingly frequent coastal floods globally. Recent research shows that changes in tidal properties and storm surge magnitudes can further exacerbate sea‐level rise‐related increases in flood frequencies. However, such non‐stationarity in tide and storm surge statistics are largely neglected in existing coastal flood projection methodologies. Here we develop a framework to explore the effect that different realizations of various sources of uncertainty have on projections of coastal flood frequencies, including changes in tidal range and storminess. Our projection methodology captures how observed flood rates depend on how storm surges coincide with tidal extremes. We show that higher flood rates and earlier emergence of chronic flooding are associated with larger sea‐level rise rates, lower flood thresholds, and increases in tidal range and skew surge magnitudes. Smaller sea‐level rise rates, higher flood thresholds and decreases in sea level variability lead to commensurately lower flood rates. Percentagewise, changes in tidal amplitudes generally have a much larger impact on flood frequencies than equivalent percentagewise changes in storm surge magnitudes. We explore several implications of these findings. Firstly, understanding future local changes in storm surges and tides is required to fully quantify future flood hazards. Secondly, existing hazard assessments may underestimate future flood rates as changes in tides are not considered. Finally, identifying the flood frequencies and severities relevant to local coastal managers is imperative to develop useable and policy‐relevant projections for decisionmakers.

Hydrologic Modelling for Flood Threshold and Hazard Prediction in the Black Volta River Basin, West Africa

Hydrologic Modelling for Flood Threshold and Hazard Prediction in the Black Volta River Basin, West Africa

THE TIDE IS HIGH: NEW INSIGHTS ON COASTAL FLOODING TRENDS AND FUTURES

Coastal flood frequencies are expected to increase around the world due to sea-level rise (SLR). This is largely related to the emergence of tidal flooding, where coastal flood thresholds are exceeded by astronomical tides alone. We will discuss the concept of tidal flooding and the observed trends from Australia and the United States. We then apply a new risk assessment framework (Hague et al. 2022) to identify which locations are most vulnerable to chronic flooding due to SLR this century. Finally, we discuss the implications of a global application of this framework for coastal engineering and management applications.

The Global Drivers of Chronic Coastal Flood Hazards Under Sea‐Level Rise

AbstractWe present the first global estimates of annual average exceedances of contemporary minor, moderate, and major flood levels under sea‐level rise (SLR). Applying established methods, we show that minor flooding will occur most days worldwide under 0.7 m global SLR. Moderate flooding occurs at the same frequency under 1.0 m SLR. Local and regional differences in flood threshold elevations, tidal ranges, and non‐tidal variability lead to differences in the SLR required for this chronic flooding to emerge. Lower flood thresholds, smaller tidal ranges, and larger extreme skew surges mean chronic flooding can emerge with less SLR. We discuss several implications of these findings for coastal flood hazard assessments. First, tide‐driven water level variability dominates weather‐driven water level variability when determining locations' propensities for frequent and chronic flooding under SLR. Second, centimeter‐accurate flood threshold information is necessary to accurately estimate present and future flood hazards. Third, locations with the most frequent floods at present may not be those that have the most frequent floods under SLR. We develop the Rapid Assessment Framework for Frequent Flood Transitions under SLR (RAFFFTS) to apply these findings to locations not previously considered in global coastal flood hazard studies. RAFFFTS can robustly identify potential future tidal flooding hotspots using only 1‐year observational records. We anticipate RAFFFTS will be a valuable tool for identifying locations at risk of chronic flooding under SLR, complementing existing tools for identifying changes in less frequent episodic floods.

Developing assessment flow for damage estimation of mud housing typology through a case study against coastal floods

Rising instances of prolonged inundation due to climate-aggravated high tide flooding are economically burdensome for resource-crunched developing nations that bear enormous damage due to loss of built infrastructure (housing in this case). Regardless of the loss, coastal flood impact on buildings is rarely given precedence. The mud building typology in India captures 34% of existing housing demand primarily within ruralIndia; for instance, 75% of the housing in Sagar Island uses mud as the dominant construction material, making it an ideal case for the proposed research. The multivariate nature of damage and empirical data constraint associated with mud buildings propels the development of two unconventional damage assessment approaches using multivariate-probabilistic technique. The proposed literature-based approach uses logical reasoning based on the available scientific evidence whereas the lab-based approach uses the insights from structural analysis of scaled model. The damage matrix created from both the approaches are used to analyse a common flood data (depth & duration) generated using 1000 Montecarlo simulations. The resultant Damage Stage values confirm the versatility of either approach over spatial (local to regional)—temporal (flood character and intensity) dimensions. The lab-based approach proved to be a better alternative considering the availability of continuous records on damage behaviour and precise information on the flood threshold of dominant building material, a crucial component of the multivariate damage assessment process.

Data From the Drain: A Sensor Framework That Captures Multiple Drivers of Chronic Coastal Floods

AbstractTide gauge water levels are commonly used as a proxy for flood incidence on land. These proxies are useful for projecting how sea‐level rise (SLR) will increase the frequency of coastal flooding. However, tide gauges do not account for land‐based sources of coastal flooding and therefore flood thresholds and the proxies derived from them likely underestimate the current and future frequency of coastal flooding. Here we present a new sensor framework for measuring the incidence of coastal floods that captures both subterranean and land‐based contributions to flooding. The low‐cost, open‐source sensor framework consists of a storm drain water level sensor, roadway camera, and wireless gateway that transmit data in real‐time. During 5 months of deployment in the Town of Beaufort, North Carolina, 24 flood events were recorded. Twenty‐five percent of those events were driven by land‐based sources—rainfall, combined with moderate high tides and reduced capacity in storm drains. Consequently, we find that flood frequency is higher than that suggested by proxies that rely exclusively on tide gauge water levels for determining flood incidence. This finding likely extends to other locations where stormwater networks are at a reduced drainage capacity due to SLR. Our results highlight the benefits of instrumenting stormwater networks directly to capture multiple drivers of coastal flooding. More accurate estimates of the frequency and drivers of floods in low‐lying coastal communities can enable the development of more effective long‐term adaptation strategies.

Climate related changes to flood regimes show an increasing rainfall influence

Climate change can result in changes to floods and flood regimes, but the relationship between floods and climate change is complex and poorly understood. The flood regime influences the nature, severity, and timing of flood events for any watershed. Flood regimes should be viewed as a continuum with completely nival (snowmelt-driven) watersheds at one end of the continuum and purely pluvial (rainfall-driven) watersheds at the other. Flood regimes are important for the operation of flood defenses and to better understand how changes in the flood regime can affect the magnitude of flood events. Data from 46 long term streamflow gauging stations from reference hydrologic networks (RHNs) in Canada (23) and the US (23), are examined to detect changes that have occurred, or are continuing to occur, in flood regimes from watersheds responding only to climate variations and changes. Peaks over Threshold (POT) flood events are used to investigate changes in the timing of flood events. Seasonality measures, using circular statistics, illustrate changes in the nature of the flood regime based on changes in the timing and regularity of flood threshold exceedences. A nival fraction is determined for each watershed and for each year based on a clustering of the flood events into two groups, representing nival and pluvial events. Changes to the flood regime over time, and based on annual temperature, are determined from logistic regression of the number of nival and pluvial events for each year. While strongly nival watersheds show no changes, roughly 15% of the stations exhibit significant changes that represent shifts towards the pluvial end of the flood regime continuum, which has implications for design flood estimation and the operation of flood control infrastructure.

The effect of tidal range and mean sea-level changes on coastal flood hazards at Lakes Entrance, south-east Australia

Despite being well-documented in other countries, the roles that anthropogenically induced changes and natural variability in tidal processes play in modulating coastal flood frequencies have not been investigated in Australia. Here we conduct a brief assessment of changes in tidal variability around Australia. We then apply a simple attribution framework to quantify the separate and joint effects of tidal range changes and increasing relative mean sea level on nuisance flood frequency at the location with the largest relative changes in tidal range, Lakes Entrance, Victoria. To understand how these changes in variability affect flood hazards, we consider a nuisance flood threshold based on recent coastal flood impact surveys. Results show that increases in the heights of high tides over recent years have exerted a large influence on coastal flood frequencies. These recent changes are potentially linked to changes in channel dredging regimes. We show that 93% of nuisance flood days since 2009 would not have occurred without these tidal range changes or the coincident increases in the mean sea level. We demonstrate the importance of considering tidal processes in estuarine coastal flood hazard assessments for future planning, even if these processes do not represent a substantial flood threat today. We discuss the implications of this study for future work on estuarine flood hazards and the benefits of considering impact-based thresholds in the assessment of such hazards.

A novel statistical approach to predict seasonal high tide flooding

Sea level rise is increasing the frequency of high tide flooding in coastal communities across the United States. Although the occurrence and severity of high-tide flooding will continue to increase, skillful prediction of high tide flooding on monthly-to-annual time horizons is lacking in most regions. Here, we present an approach to predict the daily likelihood of high tide flooding at coastal locations throughout the U.S. using a novel probabilistic modeling approach that relies on relative sea-level rise, tide predictions, and climatological non-tidal residuals as measured by NOAA tide gauges. A retrospective skill assessment using the climatological sea level information indicates that this approach is skillful at 61 out of 92 NOAA tide gauges where at least 10 high tide flood days occurred from 1997–2019. In this case, a flood day occurs when the observed water level exceeds the gauge-specific high tide flood threshold. For these 61 gauges, on average 35% of all floods are accurately predicted using this model, with over half of the floods accurately predicted at 18 gauges. The corresponding False-Alarm-Rate is less than 10% for all 61 gauges. Including mean sea level anomaly persistence at leads of 1 and 3 months further improves model skill in many locations, especially the U.S. Pacific Islands and West Coast. Model skill is shown to increase substantially with increasing sea level at nearly all locations as high tides more frequently exceed the high tide flooding threshold. Assuming an intermediate amount of relative sea level rise, the model will likely be skillful at 93 out of the 94 gauges projected to have regular flooding by 2040. These results demonstrate that this approach is viable to be incorporated into NOAA decision-support products to provide guidance on likely high tide flooding days. Further, the structure of the model will enable future incorporation of mean sea level anomaly predictions from numerical, statistical, andmachine learning forecast systems.

Flood Risk Assessment to Enable Improved Decision-Making for Climate Change Adaptation Strategies by Central and Local Governments

This study assessed the flood risk in the Republic of Korea, considering representative concentration pathway (RCP) climate change scenarios, after applying the concept of “risk” as proposed by the Intergovernmental Panel on Climate Change. For the hazard assessment, hazard indicators were constructed utilizing design rainfall standards, which represented the local flood protection capability, as a flood threshold. We constructed high-resolution spatial images from data of buildings, roads, agriculture areas, and the population that have suffered significant flood damage in the Republic of Korea. We also calculated flood exposure levels by analyzing the scales of the targets in low-lying areas. Environmental and anthropogenic conditions that can directly increase or decrease river flooding and urban flooding were set as indicators and utilized as proxy variables. As a result of the risk assessment, we found 43 risk areas in the historical period, accounting for 19% of the total administrative districts, 42 in the projected period under RCP 4.5 (18%), and 51 in the projected period under RCP 8.5 (22%). This study’s results can be utilized by the central government to determine flood risk priority areas in various administrative districts and by the local government to select priority areas to install flood reduction facilities.

Performance assessment of a four-pass serpentine proton exchange membrane fuel cell with non-humidified cathode and cell state estimation without special measurement

Proton exchange membrane fuel cells are promising electrochemical energy conversion devices especially important for mobile technologies, including the automotive industry thanks to their quick start-up, low operation temperature, and relatively higher energy density characteristics. However, cell performance depends on many parameters like reactant temperature and humidification ratio, cell operating temperature, reactant feeding pressure, and flow field. In this study, the performance of a 50 cm 2 active area four-pass serpentine flow field hydrogen-air proton exchange membrane (PEM) fuel cell experimentally investigated for various cell operating temperatures and reactant back pressures without humidification on the cathode side. Dehydration or flooding condition of the cell is showed to be determined with tafel slope, limiting current density and types of voltage losses without using a special measurement. The results show that flooding, which is called mild flooding, is possible to be seen even at high cell temperature in a non-humidified cathode fuel cell, in case of exceeding operating pressures. Behavior of cell parameters under mild flooding and ongoing severe flooding are different from each other. Pressure increase at above 45 °C operating temperature is seen to served higher power output. However, at low back pressure with escalated operating temperature doesn't result with a substantial increase on performance since less amount of water is produced as a product of reaction causing membrane dehydration at relatively low current density levels thus increasing ohmic loss. • Mild flooding in the sub layers can be masked by the peak power increased with high operating pressure. • The point where increase of i L and i 0 with pressure turns to decrease is the flood threshold. • Nernst based performance gain gets more apparent above 45 °C operating temperature. • Composite membranes are more resistant to dehydration at temperatures above 80 °C.

ميكانزمات واحتمالات نشأة الفيضانات المتطرفة بالمناطق الجافة (سهل تزنيت - المغرب)

يشهد تردد وعنف الظواهر الهيدرولوجية والمناخية المتطرفة التي تؤدي إلى حدوث فيضانات غامرة. يهدف هذا البحث إلى دراسة الخصوصيات والميكانزيمات المتحكمة في نشأة الفيضانات التي شهدها الحوض النهري لواد أودودو (إقليم تزنيت – المغرب الجنوب الغربي) وإجراء تحليل ترددي للأحداث الهيدرولوجية المتطرفة المرتبطة بالفيضانات من أجل تقدير فترة عودة حدوثها، فضلا عن تشخيص العوامل الطبيعية بمجال الدراسة وفهم الآليات الطبيعية وعلاقتها بنشأة الفيضانات، تعتمد الخطوات المنهجية مقاربتين: مقاربة تاريخية وأخرى إحصائية. تقوم الأولى على دراسة 8 حالات فيضانات عرفتها سافلة الحوض (المجال الحضري لمدينة تزنيت وجماعة أكلو)، وتحديد وتصنيف الأحياء والدواوير المهددة بالفيضانات من خلال الشهادات والمعاينات المباشرة للساكنة المجاورة. أما الثانية فركزت على تحليل ترددات الأحداث الهيدرومناخية القصوى (frequency analysis of hydroclimatic extreme events) لتصنيفها وتحديد خطورتها وفترة عودة وقوعها. يتضح من خلال تحليل النتائج المتحصل عليها، وجود ترابط دائم بين عتبات الفيضانات وقوة التساقطات المطرية وتركزها في الزمان والمكان، مما يعطيها سلوكا فجائيا شبيها بالفيضانات الصيفية والخريفية. مكنت هذه الدراسة من تحديد المناطق المهددة بالفيضانات وتصنيفها حسب درجة الخطورة، عبر العمل الكرطوغرافي بهدف توجيه تدخلات الفاعلين في الميدان. فقد مكن تحليل قيم الصبيب باستخدام نموذج تحليل الترددات واحتمالات حدوث الأحداث الهيدرومناخية الشديدة (فيضانات) وكذلك حساب قيم الصبيب اللحظي التي توافق فترات العودة من 2، 5، 10، 20، 50 و100 سنة. فالأحداث الهيدرولوجية ثنائية وخماسية الحول تتوافق مع تدفقات لصبيب لحظي من 120 إلى 331 متر3/ ثانية، في حين ان الحالات الاستثنائية والاستثنائية جدا، لها فترة عودة تزيد عن 50 و100 سنة وتتوافق مع تدفقات لصبيب لحظي من 912 إلى 1035 متر3/ ثانية.

Climate Change and Changes in Compound Coastal‐Riverine Flooding Hazard Along the U.S. Coasts

AbstractThe cooccurrence of coastal and riverine flooding leads to compound events with substantial impacts on people and property in low‐lying coastal areas. Climate change could increase the level of compound flood hazard through higher extreme sea levels and river flows. Here, a bivariate flood hazard assessment method is proposed to estimate compound coastal‐riverine frequency under current and future climate conditions. A copula‐based approach is used to estimate the joint return period (JRP) of compound floods by incorporating sea‐level rise (SLR) and changes in peak river flows into the marginal distributions of flood drivers. Specifically, the changes in JRP of compound major coastal‐riverine flooding defined based on simultaneous exceedances above major coastal and riverine thresholds, are explored by midcentury. Subsequently, the increase in the probability of occurrence of at least one compound major coastal‐riverine flooding for a given period of time is quantified. The proposed compound flood hazard assessment is conducted at 26 paired tidal‐riverine stations along the Contiguous United States coast with long‐term data and defined flood thresholds. We show that the northeast Atlantic and the western part of the Gulf coasts are experiencing the highest compound major coastal‐riverine flood probability under current conditions. However, future SLR scenarios show the highest frequency amplification along the southeast Atlantic coast. The impact of changes in peak river flows is found to be considerably less than that of SLR. Climate change impacts, especially SLR, may lead to more frequent compound events, which cannot be ignored for future adaptation responses in estuary regions.

Development and Evaluation of an ODE Representation of 3D Subsurface Tile Drainage Flow Using the HLM Flood Forecasting System

AbstractWe developed a new ordinary differential equation (ODE) to represent subsurface flows from a hillslope with artificial subsurface drainage (tiling) into an adjacent channel. Our ODE is based on a derived storage‐discharge relationship from high‐resolutions HYDRUS3D simulations that solve 3D partial differential Richards' equations for a hillslope (plot scale) with internal drainage surfaces, variable soil depth, hydraulic conductivity, and varying slope in the direction of flow. The ODE does not capture the hysteresis in the storage‐drainage relation that can only be captured using partial differential equations (PDEs), however the simplification does not have major impacts on the modeled flows. The nondimensional representation of the equation is consistent with, and provides an explanation for, the empirical equation used in classical hydrological models such as the ARNO (Arno River) and Variable Infiltration Capacity (VIC) model to simulate subsurface flows, which removes the need for parameter calibration. Our equation captures the features not captured by other ODE simplifications such as DRAINMOD. The ODE can be coupled to the Hillslope Link Model (HLM) flood forecasting system allowing real‐time regional simulation of streamflow fluctuations and floods over large domains. We show that (i) the new equation improves the capability to model watershed scale hydrograph recessions and to better capture the timing above flood thresholds for multiple spatial scales from 0.1 to 18,000 km2; (ii)using realistic values of slope combined with typical values of tile separation and soil depth provides good predictive power at gauged basin outlets; and (iii) parameters can be derived for particular situations using the 3D PDE framework.

Tide-only inundation: a metric to quantify the contribution of tides to coastal inundation under sea-level rise

Sea-level rise is causing coastal inundation events in estuaries, harbours, bays, and tidal rivers to happen more often as predictable daily high and low tides reach higher levels. This can lead to coastal inundation happening under benign weather conditions, as flood thresholds are exceeded due to tides alone without the influence of storm surges or other phenomena. As such, changes in frequency of this 'tide-only' inundation may be a useful metric to quantify the role that sea-level rise plays in modulating the risk of coastal inundation from high still water levels. Here we present a conceptual model for 'tide-only' inundation and propose a practical methodology to formulate tide-only inundation statistics: estimates, historical trends, and future projections. This enables this emerging natural hazard to be fully incorporated into new and existing coastal risk assessment frameworks and considered in coastal management and planning strategies at local and national levels. Further, it leads to a framework that can quantify the role that tides play in coastal flooding as sea levels rise.

Sea Level Rise Driving Increasingly Predictable Coastal Inundation in Sydney, Australia

AbstractAs global mean sea level continues to rise, thresholds corresponding to coastal inundation impacts are exceeded more frequently. This paper aims to relate sea level rise (SLR) observations and projections to their physical on‐the‐ground impacts. Using a large coastal city as an example, we show that in Sydney, Australia, frequencies of minor coastal inundation have increased from 1.6 to 7.8 days per year between 1914 and present day. We attribute over 80% of the observed coastal inundation events between 1970 and 2015 to the predominantly anthropogenic increases in global mean sea level. Further, we find that impact‐producing coastal inundation will occur weekly by 2050 under high‐ and medium‐emission/SLR scenarios and daily by 2100 under high emissions. The proportion of tide‐only coastal inundation events (i.e., where no storm surge is required to exceed flood thresholds) will increase with SLR, such that most coastal inundation events, including those considered historically severe, will become a predictable consequence of SLR and astronomical tides. These findings are important for coastal managers as frequency, severity, and predictability of inundation impacts can all now be related to the amount of SLR (e.g., a planning allowance or SLR projection). By incorporating known historical inundation events, this allows contextualization, visualization, and localization of global SLR and the changing nature of future coastal inundation risk.