Flood Risk Assessment Method Research Articles

Unraveling the interplay of human decisions and flood risk: An agent-based modeling approach

Flooding is a frequent and highly destructive natural disaster that requires effective flood management policies. This paper addresses the limitations of traditional flood risk assessment methods, focusing on the interplay between human decisions and flood risk using an integrated approach. Agent-Based Modeling (ABM) is employed to capture the social behavior of government, households, and farmers in three flood management scenarios. The study is conducted in the Fall River watershed, Idaho, USA, over a 30-year period. The results highlight the important influence of crop selection decisions on flood damage outcomes, with alfalfa emerging as the preferred crop due to its profitability and lower damage potential (around 67 % crop loss compared to more than 81 % for crops like corn, barley, and wheat). The levee scenario is identified as the most effective strategy, significantly reducing flood damage by more than 37 % and generating the highest average annual profit for farmers. The study emphasizes the need for comprehensive flood risk management strategies that address both frequent and rare flood occurrences in mitigating flood damage and promoting community resilience. By integrating human-flood interactions into flood risk assessment, this study offers valuable insights for Policymakers and stakeholders can utilize the research implications to develop effective strategies that mitigate damage and enhance community resilience.

A complete methodology to assess hydraulic risk in small ungauged catchments based on HEC-RAS 2D Rain-On-Grid simulations

This paper explores the use of the rain-on-grid (or direct rainfall) method for flood risk assessment at a basin scale. The method is particularly useful for rural catchments with small vertical variations and complex interactions with man-made obstacles and structures, which may be oversimplified by traditional hydrologically based estimations. The use of a hydrodynamic model solving mass and momentum conservation equations allows the simulation of runoff over the watershed at a basin scale. As a drawback, more detailed and spatially distributed data are needed, and the computational time is extended. On the other hand, a smaller number of parameters is needed compared to a hydrological model. Roughness and rainfall loss coefficients need to be calibrated only. The direct rainfall methodology was here implemented within the two-dimensional HEC-RAS model for the low-land rural, and ungauged, watershed of the Terdoppio River, Northern Italy. The resulting hydrographs at the closing section of the watershed were compared to synthetic design hydrographs evaluated through pure hydrological modelling, showing agreement on the peak discharge values for the low-probability scenarios, but not on the total volumes. The results in terms of water depth and flow velocity maps were used to create flood hazard maps using the Australian Institute for Disaster Resilience methodology. The Index of Proportional Risk model was then adopted to generate a basin-scale flood risk map, by combining flood hazard maps, damage functions for different building-use classes, and the value of reconstruction and content per unit area.

Projecting Flood Risk Dynamics for Effective Long‐Term Adaptation

AbstractFlood losses have steadily increased in the past and are expected to grow even further owing to climate and socioeconomic change. The reduction of flood vulnerability, for example, through adaptation, plays a key role in the mitigation of future flood risk. However, lacking knowledge about vulnerability dynamics, which arise from the interaction between floods and the ensuing response by society, limits the scope of current risk projections. We present a socio‐hydrological method for flood risk assessment that simulates the interaction between society and flooding continuously, including changes in vulnerability through collective (structural) and private (non structural) measures. Our probabilistic approach quantifies uncertainties and exploits empirical data to chart risk dynamics including how society copes with flooding. In a case study for the commercial sector in Dresden, Germany, we show that increased adaptation is necessary to counteract the expected four‐fold growth in flood risk due to transient hydroclimatic and socioeconomic boundary conditions. We further use our holistic approach to identify solutions for effective long‐term adaptation, demonstrating that integrated adaptation strategies (i.e., combined structural and non structural measures) can reduce the average risk by up to 60% at the study site. Ultimately, our case study highlights the benefit of the model for robust flood risk assessment as it can capture unintended, adverse feedbacks of adaptation measures such as the levee effect. Consequently, our socio‐hydrological method contributes to a more systemic and reliable flood risk assessment that can inform adaptation planning by exploring the possible system evolutions comprehensively including unlikely futures.

Flood risk assessment using an indicator based approach combined with flood risk maps and grid data

The increasing frequency of tropical cyclones, such as typhoons and localized heavy rainfall, increases the risk of flood damage in urban areas around the world. Countries implementing flood prevention projects use qualitative risk assessments, such as flood risk assessments, to support decision-making. However, existing flood risk assessment methods are not able to select and reflect only the damage targets that are directly exposed to flood risk. In addition, existing indexing methods are limited in improving the skewness of the raw data distribution, which distorts the calculated flood risk index. This study conducted a flood risk assessment based on an indicator-based approach using flood risk maps and grid data utilizing indicators (buildings, road area, etc.) from 2016 to 2019 for 44 cities and counties in the Gyeongsang-do Province. The flood risk assessment in this study consists of four items (Hazard, Exposure, Vulnerability, and Capacity) and nine indicators. Instead of using statistical data, we used the overlapped grids with the flood risk map for Exposure and Vulnerability indicators to reflect the flood risk exposed targets in the risk assessment. The limitations of existing indexing methods, such as min–max normalization, were improved by dividing the distribution into ten quantiles and scoring each quantile interval when indexing the indicators. Finally, entropy weights and Euclidean distance were applied to calculate the annual flood risk index of 44 cities and counties. The annual flood risk indices for local governments were arranged in descending order and then, the rankings of flood damage amount in 2019 were compared with the calculated index rankings. The sum and mean of absolute errors were 386 and 9.897, and the root mean square error was calculated as 11.930, which showed an improvement over the existing method. Using the calculated indices, it is possible to create Hazard vs. Capacity graph, Exposure vs. Vulnerability graph, or annual flood risk index graph. These graphs can be utilized to understand the level of exposure to flood risk of local governments and to assess the level of response through the Capacity index that contributes to damage reduction. It is believed that the flood risk assessment method presented in this study not only accurately identify the flood risk for local governments but can also be used to support decision-making processes to strengthen the government’s disaster prevention capabilities.

The Optimization of Water Storage Timing in Upper Yangtze Reservoirs Affected by Water Transfer Projects

To alleviate regional disparities in water resource distribution and consequent scarcity, China has initiated and planned a series of inter-basin water transfer projects using the Yangtze River Basin as the source. These projects are expected to divert approximately 33.4 billion cubic meters of water annually from the Yangtze River Basin. The implementation of these water transfer projects will inevitably alter the hydrological conditions in the upper reaches of the Yangtze River, impacting the reservoir storage strategies of cascading hydroelectric stations under current end-of-flood-season operational plans. This study quantitatively assesses the impact of water transfer projects on end-of-flood-season reservoir storage in cascading systems using the reservoir fullness ratio as an indicator. Employing reservoir storage analysis models, optimization techniques, and flood risk assessment methods, we simulated reservoir storage processes to evaluate associated flood risks and derive an optimized timing strategy for cascading reservoir storage. The results indicate that advancing the reservoir filling schedule by five days for both the Baihetan and Three Gorges dams can offset the adverse impacts of water transfer projects on reservoir storage efficiency. This adjustment restores the reservoir fullness ratio to levels observed in scenarios without water transfers while still meeting flood control requirements. After optimizing the timing of reservoir filling, the electricity generation capacity for the Baihetan and Three Gorges dams increased by 1.357 and 3.183 billion kWh, respectively, under non-transfer scenarios. In water transfer scenarios, the electricity generation for the Baihetan and Three Gorges dams increased by 1.48 and 2.759 billion kWh, respectively. By optimizing reservoir filling schedules, we not only improved the reservoir fullness ratio but also enhanced the electricity generation efficiency of the cascading systems, offering valuable insights for future reservoir operation optimization.

Urban flood risk assessment under rapid urbanization in Zhengzhou City, China

With accelerated urbanization and climate change, urban flooding is becoming more and more serious. Flood risk assessment is an important task for flood management, so it is crucial to map the spatial and temporal distribution of flood risk. This paper proposed an urban flood risk assessment method that takes into account the influences of hazard, vulnerability, and exposure, by constructing a multi-index urban flood risk assessment framework based on Geographic Information System (GIS). To determine the weight values of urban flood risk index factors, we used the analytic hierarchy process (AHP). Also, we plotted the temporal and spatial distribution maps of flood risk in Zhengzhou City in 2000, 2005, 2010, 2015, and 2020. The analysis results showed that, the proportion of very high and high flood risk zone in Zhengzhou City was 1.362%, 5.270%, 4.936%, 12.151%, and 24.236% in 2000, 2005, 2010, 2015, and 2020, respectively. It is observed that the area of high flood risk zones in Zhengzhou City showed a trend of increasing and expanding, of which Dengfeng City, Xinzheng City, Xinmi City, and Zhongmu County had the fastest growth rate and the most obvious increase. The flood risk of Zhengzhou City has been expanding with the development of urbanization. The method is adapted to Zhengzhou City and will have good adaptability in other research areas, and its risk assessment results can provide a scientific reference for urban flood management personnel. In the future, the accuracy of flood risk assessment can be further improved by promoting the accuracy of basic data and reasonably determining the weight values of index factors. The risk zoning map can better reflect the risk distribution and provide a scientific basis for early warning of flood prevention and drainage.

Simulation of dam-break flood and risk assessment: a case study of Chengbi River Dam in Baise, China

Abstract When a reservoir is damaged, it will bring destruction to people's lives and the regional economy. Flood simulation and risk assessment are two effective ways to mitigate flood risk. Flood risk is assessed by using flood hazard and vulnerability indices. However, one of the key concerns is how to quantify hazards and vulnerabilities more rationally. To this end, this study introduces a new quantitative method for flood risk assessment. Three schemes – full dam breach (S1), 1/2 dam breach (S2), and 1/3 dam breach (S3) – were proposed for flood simulation. HEC-RAS 2D was used to simulate the evolution process of dam-break floods. This study used a new quantification approach to calculate flood risk based on simulation results. The results show the following: (1) The inundation process is similar under the three schemes, but the degree differs. The greater the degree of dam break, the greater the inundation depth, maximum flow velocity, and inundation duration. (2) High-risk areas decrease with decreased dam break degree. Under the three schemes, the flood risk areas of Longjing Street account for 65.37, 71.41, and 66.22% of the total risk areas, respectively, which are the areas most affected by dam-break floods.

Development of convenient flood risk assessment method to community level: the case in the Deduru Oya basin in Sri Lanka

Purpose Floods have been identified as the most frequent and threatening disaster in Sri Lanka amidst an increasing trend of natural and man-made disasters in the world. Subject experts state that disaster risk management should be based on the results of risk assessments, but flood risk management in Sri Lanka is seemingly not based on community-level flood risk assessments. Accordingly, the purpose of this paper is to introduce a community-level flood risk assessment method to the local context of Sri Lanka. Design/methodology/approach The sample (n = 425) for the study was selected using the stratified random sampling method, and the Deduru Oya basin was selected as the study area. The risk assessment model introduced by Bollin et al. (2003) was used for the current study, but with some modifications. Accordingly, 16 variables were selected for the risk assessment. Descriptive data analysis methods were used in the study. Findings Community-level flood risk assessment method was introduced. Variable index, flood risk index and flood risk map were developed for the study area. The Grama Niladari Divisions (GNDs) were grouped into five categories from very high risk to very low risk. The GNDs named Wirakumandaluwa, Thimbilla, Deduru Oya, Bangadeniya and Elivitiya were ranked as the most flood-risk GNDs, respectively. Originality/value This paper produces a flood risk assessment method for the local context. Flood risk in the study area was assessed based on people’s perceptions. Accordingly, the flood risk index and flood risk map for the study area were developed based on the empirical data. GNDs were ranked based on the flood risk index.

The Effect of Flood Protection Works on Flood Risk

We pose the following research question: “what is the effect of flood protection works on flood risk?” To answer this question, we developed a flood risk assessment method that combines the typical hazard assessment via integrated hydrological and hydrodynamic calculations using HEC-HMS and 1D/2D HEC-RAS, respectively, and an original procedure for vulnerability assessment at the building level, which we applied in the town of Mandra in Attica, Greece. We performed calculations for 15 scenarios—combinations of return periods (T = 20, 50, 100, 150, and 200 y) and rain durations (t = 6, 12, and 18 h)—for the conditions of the year 2017, when there were no flood protection works, and today with these works in place. We identified the regions with high flood risk and concluded that the presence of the works caused a decrease in the inundation areas by 53–89%, along with reductions in the maximum water depths, the maximum flow velocities, and the average flood risk in Koropouli Street—the main street of Mandra, which suffered severe damage during the 2017 flood—by 38–62%, 18–52%, and 27–74%, respectively. The effect of the flood protection works increased with the increases in the return period and rain duration, while for the same return period the effect of the rain duration was more pronounced for the smaller return periods.

Flood risk assessment of urban cultural heritage based on PSR conceptual model with game theory and cloud model – A case study of Nanjing

Urban cultural heritage has rich historical, artistic, and scientific value. However, due to the increasing occurrence of extreme rainfall events globally, urban cultural heritage sites face increasing flood disaster risks. A flood risk assessment tool offers a scientific foundation for decision-making and is critical for understanding and managing flood risk for these heritage sites. There are several shortcomings in the previous literature, such as its failure to consider the emergency response capability of cultural heritage sites; nor does it reveal the uncertainty and nonlinear relations between assessment indexes and risk levels. To address these limitations of the previous research, this study builds a novel and easy-to-implement index-based flood risk assessment method based on the pressure-state-response conceptual model with game theory and cloud model (PSR-GT-CM). This study shows that the PSR-GT-CM is a feasible and effective method for flood risk assessment of urban cultural heritage sites. This method can be used to provide an accurate and efficient preliminary assessment of flood risk for urban cultural heritage sites with limited data and can be a useful reference for making decisions about the protection of cultural heritage sites and identifying cultural heritage sites that need a more detailed analysis. This method is illustrated through an application to 93 national-level protected cultural heritage sites in Nanjing, China.

Integrated flood risk assessment of river basins: Application in the Dadu river basin, China

Flood is the most common worldwide natural disaster with enormous impacts on human society and the ecosystem. Consequently, the research of flood risk assessment and zonation is critical. Its research scope is changeable, wherein the basin-scale research has become more and more important due to the increasing boom of cascade hydropower development in the river basin. The study proposed a basin-wide integrated flood risk assessment method combining index-based evaluation, Analytical Hierarchy Process (AHP) and Geographic Information System (GIS) technologies, which was implemented in the Dadu River basin, southwestern China to assess and zoning the basin flood risk. In the constructed risk assessment index system, we use extreme rainfall and dam breach to jointly describe the basin flood disaster-inducing factors and select flood control standard and flood routing coefficient as the sub-indicators of basic and specific coping capacity to characterize the flood intervention capacity of hydropower engineering. The results showed that, for the hazard, vulnerability and risk zonation maps with five classified levels, the southern of midstream and downstream of the basin are prone to frequent floods, while higher vulnerability levels mainly concentrate in the downstream but some parts scatter in the medium vulnerability zone. The high and very high risk zones account for 3% of the basin area and mainly concentrate in the southern basin, while 86% of the basin area is assigned as low and very low risk zones. The results of this work quantitatively express the spatial distribution characteristics of basin-wide flood hazard, vulnerability and risk, and provide a reference for practicing an integrated and efficient flood risk management, and disaster prevention and alleviation strategies.

Projection of Precipitation Extremes and Flood Risk in the China–Pakistan Economic Corridor

It is reported that the China–Pakistan Economic Corridor has been affected by extreme precipitation events. Since the 20th century, extreme weather events have occurred frequently, and the damage and loss caused by them have increased. In particular, the flood disaster caused by excessive extreme precipitation seriously hindered the development of the human society. Based on CRiteria Importance Through Intercriteria Correlation and square root of generalized cross-validation, this study used intensity–area–duration to analyze the trend of future extreme precipitation events, corrected the equidistance cumulative distribution function method deviation of different future scenario models (CESM2, CNRM-CM6-1, IPSL-CM6A-LR, and MIROC6) and evaluated the simulation ability of the revised model. The results showed that: 1) the deviation correction results of CNRM-CM6-1 in the Coupled Model Intercomparison Project Phase (CMIP) 6 could better simulate the precipitation data in the study area, and its single result could achieve the fitting effect of the CMIP5 multimodel ensemble average; 2) under CNRM-CM6-1, the frequency of extreme precipitation events under the three climate scenarios (SSP1-2.6, SSP3-7.0, and SSP5-8.5) presents interdecadal fluctuations of 3.215 times/10A, 1.215 times/10A, and 5.063 times/10A, respectively. The average impact area of extreme precipitation events would decrease in the next 30 years, while the total impact area and the extreme precipitation events in a small range would increase. Under the future scenario, the increase rate of extreme precipitation was highest in August, which increased the probability of extreme events; 3) in the next 30 years, the flood risk had an obvious expansion trend, which was mainly reflected in the expansion of the area of high-, medium-, and low-risk areas. The risk zoning results obtained by the two different flood risk assessment methods were different, but the overall risk trend was the same. This study provided more advanced research for regional flood risk, reasonable prediction for flood risk under future climate models, and useful information for flood disaster prediction in the study area and contributes to the formulation of local disaster prevention and reduction policies.

Research on the Vulnerability of the Community to Flood: A Case Study at the Downstream of Gianh River, Quang Binh Province

Flood is a frequent natural disaster which has a negative impact on the socio-economic activities of the community in the lower Gianh river area - one of the most vulnerability areas under the flood in the North Central Region, Vietnam. The aim of this paper is to assess the risk of flooding in the study area as well as point out the factors that increase the vulnerability of the local community. The study applies UNESCO-IHE vulnerability approach, combining the flood risk assessment method by MIKE FLOOD model and sociological investigation, with 90 household questionnaires (selected randomly and door-to-door interview). The main results include flood risk level maps (by analyzing inundation depth and flood flow velocities); data on community resilience to flood (resilience capacity and local people's perceptions on flood risks). These results are the basis for not only raising awareness about flood risks but also propose non-structural flood protection solutions for managers and local communities in the research areas.

An Optimized Weighted Naïve Bayes Method for Flood Risk Assessment.

Floods occur frequently and cause considerable damage to local environments. Effectively assessing the flood risk contributes to reducing loss caused by such disasters. In this study, the weighted naïve Bayes (WNB) method was selected to evaluate flood risk, and the entropy weight method was employed to compute the weights. A sampling and verifying model was employed to generate the most accurate conditional probability table (MACPT) to calculate the probability of flooding. When using the framework integrating WNB with the sampling and verifying model, previous studies could not obtain a WNB-based MACPT and the WNB classification accuracy, for lacking WNB functions that could be called directly. Facing this issue, in this study we developed WNB functions with the MATLAB platform to directly integrate with the sampling and verifying model to generate a WNB-based MACPT, contributing to the greater interpretability and extensibility of the model. Shantou and Jieyang cities in China were selected as the study area. The results demonstrate that: (1) a WNB-based MACPT can reflect the real spatial distribution of flood risk and (2) the WNB outperform the NB when integrated with the sampling and verifying model. The resulting gridded estimation reveal a detailed spatial pattern of flood risk, which can serve as a realistic reference for decision making related to floods. Furthermore, the proposed method uses less data, which would be helpful in developing countries where long-term intensive hydrologic monitoring is limited.

Flood Risk Assessment in Small Watershed Based on Catastrophe Theory

Flood system is a complex system affected by many control factors and has typical system characteristics, such as irreversibility, fuzzy characteristics, gray characteristics, etc. Catastrophe theory is a well developed singularity theory, which has been initially applied in some leaping disaster systems. However, in the field of flood risk management, the application of catastrophe theory is relatively few. In this paper, a small watershed in the mountainous area of southwest China is taken for an example. The catastrophe assessment theory is adopted to conduct flood risk assessment. By analyzing the characteristics of the flood system and selecting flood risk factors, the flood risk assessment index system is established and the catastrophe theory flood risk assessment model is conducted, thus conducting flood risk zoning and management according to the assessment result, which provides a new reliable method for flood risk assessment and offers foundation for disaster reduction department.

Method for fluvial and pluvial flood risk assessment in rural settlements

Flood risk assessments in the Global South have increased since the adoption of the United Nations Sendai Framework for Disaster Risk Reduction 2015–2030. However, they often fail to meet disaster risk reduction needs at the local scale, because they typically consider only one hazard (fluvial or pluvial floods). Furthermore, hazard and exposure are considered as stationary conditions, flood-prone assets are rarely identified, risk reduction measures are not identified in detail for specific locations, and the convenience of reducing or accepting risk is not evaluated. This paper describes a flood risk assessment method that is innovative in that it considers three hazard types (backwater, fluvial, and pluvial floods) and multiple risk scenarios; it uses orthophotos generated from images captured by an unmanned aerial vehicle and very high-resolution satellite images, and it involves communities in risk assessment. The method was applied to four rural settlements along the Sirba River, Niger. The assessment identifies the benefit of reducing risk in monetary terms, as well as the intangible benefits that reducing risk could generate, and it detects opportunities that flooding offers for rural development. The method can be replicated in all contexts where decision-making support is needed for flood risk assessment planning.•Risk analysis and evaluation is participatory.•Risk assessment is improved by combining local and technical knowledge.•Assets are identified using very-high-resolution satellite and drone images.

Urban flood risk assessment and analysis with a 3D visualization method coupling the PP-PSO algorithm and building data

Due to the influence of buildings on the distribution of flood and their economic and social attributes, 3D spatial information such as the size of buildings and the flooded ratio of buildings relative to their height has an increasing impact on urban flood risk. However, existing flood risk assessment methods mainly use data in 2D and analysis methods are mostly 2D. In this study, flood variation processes were analyzed in the form of 3D dynamic visualization by coupling an urban drainage model and a flood simulation model with 3D visualization methods. By further combining with 3D building models, the 3D spatial information of buildings related to flood was obtained. In order to study the influence of 3D information on flood risk and combine with other multi-source heterogeneous data for integrated analysis, a 3D visualization assessment and analysis method for flood risk, coupled with the projection pursuit-particle swarm optimization algorithm (PP–PSO) was established (3DVAAM-PP-PSO). A case study from Chaohu City, China, was used to demonstrate the method. The results showed that the PP-PSO algorithm can process high-dimensional information and obtain the objective weight of each index. The 3D information from the influenced buildings had an impact on the evaluation results, which needed to be considered. Through the 3D visualization analysis, the overall distribution of flood risk and that around the buildings were obtained in multi-perspectives. The flood risk during different rainfall return periods were analyzed intuitively and comparatively. This study furnishes a novel method for flood risk assessment and analysis by making the most of 3D spatial information.

Flood Risk Assessment Based on Fuzzy Synthetic Evaluation Method in the Beijing-Tianjin-Hebei Metropolitan Area, China

Flooding is one of the most devastating natural events and leads to enormous and recurring loss of life, properties, and resources around the globe. With climate change and accelerating urbanization, flood disasters in China have increasingly affected the sustainable development of metropolitan areas. Risk assessment is an essential step in flood management and disaster mitigation, which provide a quantitative measure of flood risk. However, the difficulty of flood risk zoning is dealing with the uncertainty of the evaluation process and the complicated non-linear relationship between indicators and risk levels. To address this issue, a fuzzy synthetic evaluation (FSE) method based on combined weight (CW) was utilized in this paper to generate flood risk maps at a grid-scale (1 × 1 km). For the case study in the Beijing-Tianjin-Hebei metropolitan area (BTH) in China, fourteen indicators were selected to construct the flood risk assessment model based on the FSE approach integrated with ArcGIS. The research demonstrates that moderate, high, and very high risk zones are distributed in the southeast fluvial plain of the BTH area, accounting for 31.36% of the total land area. Meanwhile, low and very-low risk zones occupy 68.64% of the total land area, and are primarily located in the high plateau and mountain regions in the northwest. We analyzed the risk level of each county and proposed risk mitigation measures based on field investigations. The verified risk assessment results were spatially consistent with the historical flood disaster records and loss positions, indicating the accuracy and reliability of the risk assessment map using the FSE approach. Compared with the IPCC (Intergovernmental Panel on Climate Change) TAR (Third Assessment Report) and AR5 (Fifth Assessment Report) methods, FSE has significant advantages in handling uncertainty, complexity, and the non-linear relationship between indices and risk grades. This study provides a novel quantitative method for flood risk assessment in metropolitan areas and practical implications for urban flood management.

A rapid flood risk assessment method for response operations and nonsubject‐matter‐expert community planning

AbstractFlood risk planning and emergency response at community levels rely on fast access to accurate inundation models that identify geographic areas, assets, and populations that may be flooded. However, limited flood modelling resources are available to support these events and activities. We present a computationally‐efficient flood model for facilitating rapid risk analysis across a wide range of scenarios and decision support to operational, crisis action, local flood‐fight, and community planning efforts. Our flood depth regression method converts publicly‐available river stage heights to flood depths, then downscales the depths from gage locations onto high resolution National Hydrography Dataset flowlines and estimates areas and depths of flooding by subtraction of the National Elevation Dataset from modelled water surface elevations. We demonstrate proof‐of‐principle analyses for historic 2009 Red River of the North flooding in the United States, achieving comprehensive mainstem flood estimation for the length of the river and depth accuracy of 1.4 ft (0.4 m) compared to gage observations, remote sensing, and higher‐resolution hydrologic models. We also demonstrate the utility of the method to inform planning and response decisions in preparation for flooding in a companion scenario for Yerington, Nevada, and call for further research and operationalization of riverine inundation mapping techniques.

Estimating snow water equivalent using unmanned aerial vehicles for determining snow-melt runoff

Although global warming decreases winter snow storage and snow-melt peak discharges in the majority of basins in warm regions, there exist specific catchments in cold regions where climate change increases the risk of snow-melt floods in winters and earlier-than-usual springs. The volume of water contained in a snowpack is quantified by snow water equivalent, the near-real-time estimation of which is essential to issue early warnings against snow-melt floods. We propose a new approach for rapid and high-resolution estimation of snow water equivalent for small mountainous basins, employing unmanned aerial vehicles known as drones. Numerical maps of snow water equivalent are automatically produced for subareas of a river basin by combining drone-based snow depth maps with snow density estimates. The reconstructions for subareas are extrapolated to the entire river basin using a zonal version of multiple linear regression. Validation is conducted on the example of the Kwisa river in southwestern Poland by balancing drone-based snow water equivalent with snow-melt runoff separated using a hydrologic model from discharges continuously measured during a thawing period. Differences between the drone-based and reconstructed snow-melt runoff are found to be of −11.2, +1.6 and +18.9%, providing evidence for the considerable worth skills of the new drone-based flood risk assessment method.