Flash Flood Risk Research Articles

Evaluation of Convection-Permitting Precipitation Forecast Products Using WRF, NMMB, and FV3 for the 2016–17 NOAA Hydrometeorology Testbed Flash Flood and Intense Rainfall Experiments

Abstract During the summers of 2016 and 2017, the Center for Analysis and Prediction of Storms (CAPS) ran real-time storm-scale ensemble forecasts (SSEFs) in support of the Hydrometeorology Testbed (HMT) Flash Flood and Intense Rainfall (FFaIR) experiment. These forecasts, using WRF-ARW and Nonhydrostatic Mesoscale Model on the B-grid (NMMB) in 2016, and WRF-ARW and GFDL Finite Volume Cubed-Sphere Dynamical Core (FV3) in 2017, covered the contiguous United States at 3-km horizontal grid spacing, and supported the generation and evaluation of precipitation forecast products, including ensemble probabilistic products. Forecasts of 3-h precipitation accumulation are evaluated. Overall, the SSEF produces skillful 3-h accumulated precipitation forecasts, with ARW members generally outperforming NMMB members and the single FV3 member run in 2017 outperforming ARW members; these differences are significant at some forecast hours. Statistically significant differences exist in the performance, in terms of bias and ETS, among subensembles of members sharing common microphysics and PBL schemes. Year-to-year consistency is higher for PBL subensembles than for microphysical subensembles. Probability-matched (PM) ensemble mean forecasts outperform individual members, while the simple ensemble mean exhibits substantial bias. A newly developed localized probability-matched (LPM) ensemble mean product was produced in 2017; compared to the simple ensemble mean and the conventional PM mean, the LPM mean exhibits improved retention of small-scale structures, evident in both 2D forecast fields and variance spectra. Probabilistic forecasts of precipitation exceeding flash flood guidance (FFG) or thresholds associated with recurrence intervals (RI) ranging from 10 to 100 years show utility in predicting regions of flooding threat, but generally overpredict the occurrence of such events; however, they may still be useful in subjective flash flood risk assessment.

A Study on Climate-Driven Flash Flood Risks in the Boise River Watershed, Idaho

We conducted a study on climate-driven flash flood risk in the Boise River Watershed using flood frequency analysis and climate-driven hydrological simulations over the next few decades. Three different distribution families, including the Gumbel Extreme Value Type I (GEV), the 3-parameter log-normal (LN3) and log-Pearson type III (LP3) are used to explore the likelihood of potential flash flood based on the 3-day running total streamflow sequences (3D flows). Climate-driven ensemble streamflows are also generated to evaluate how future climate variability affects local hydrology associated with potential flash flood risks. The result indicates that future climate change and variability may contribute to potential flash floods in the study area, but incorporating embedded-uncertainties inherited from climate models into water resource planning would be still challenging because grand investments are necessary to mitigate such risks within institutional and community consensus. Nonetheless, this study will provide useful insights for water managers to plan out sustainable water resources management under an uncertain and changing climate.

Fuzzy Risk Assessment of Flash Floods Using a Cloud-Based Information Diffusion Approach

The assessment of flash flood risks is the basis on which flash flood prevention measures and early-warning systems can be proposed and reasonably implemented. However, inadequate monitoring of flash flood data which mainly occurs in remote areas restricts quantitative risk assessment. This study aimed to address the problems of limited data availability. A new model that integrating the Cloud-based Information Diffusion (CID) model and Analytic Hierarchy Process (AHP) approach is developed to assess flash flood risks. The proposed method improves the information diffusion function by introducing cloud model, while converting single-valued observations with incomplete information into fuzzy set-valued samples. The new approach can perform comprehensive risk assessment tasks with various indexes that are composed of incomplete information. Another advantage of this approach is that it can illustrate fuzzy uncertainty, fuzziness, and randomness of risk indexes by coupling with the cloud model, the risk magnitude is quantified with membership degree. A mountainous watershed in Southern China named Yangshan County was selected as the study area. Compared with information diffusion (ID) and entropy-based information diffusion (EID), the assessment results of the three models are, in general, consistent with one another, and agree with the reported values. According to the principle of maximum membership degree, Yangshan County is determined as a high-risk region when confronting with flash flood hazards. This model provides a feasible and effective method on fuzzy risk assessment of flash flooding, and is expected to be applied in other multi-criteria decision with limited available information or small sample problems.

Flash flood susceptibility modelling using geomorphometric approach in the Ushairy Basin, eastern Hindu Kush

This study focuses on flash flood susceptibility modelling using geomorphometric ranking approach in the Ushairy Basin. In the study area, flash floods are highly unpredictable and the worst hydrometeorological disaster. An advanced spaceborne thermal emission and reflection radiometer global digital elevation model was used as input data in a geographic information system environment to delineate the target basin. A total of 17 sub-basins were delimited using a threshold of $$4 \hbox {km}^{2}$$ . The attribute information of each sub-basin was analysed to compute the geomorphometric parameters by applying Hortonian and Strahler geomorphological models. The results were analysed and categorised into five classes using statistical techniques, and the rank score was assigned to each class of all parameters depending on their relation with flash flood risk. In this study, 16 parameters were analysed to quantify the geomorphometric number of each sub-basin depicting the degree of flash flood susceptibility. The geomorphometric number of each sub-basin was linked to the geo-database for spatial visualisation. The analysis reveals that extremely high, very high, high and moderate sub-basins susceptible to flash floods were spread over an area of 55%, 8.5%, 23.7%, and 11.5%, respectively. It was found that out of total settlements, 53% are located in the extremely highly and very highly susceptible sub-basins. In the study area, the upper reaches are characterised by snow-covered peaks, steep slopes and high drainage densities ( $${>}1.7 \hbox { km/km}^{2})$$ . The analysis further indicated that the flash flood susceptibility increases with the increase in area, relief and relief ratio of the sub-basins. Model accuracy was assessed using primary data regarding past flood damages and human fatalities. Similarly, socio-demographic conditions of each sub-basin were also compared and linked to the extent of flash flood susceptibility. This study may assist the district government and district disaster management authority of Dir upper to initiate flood risk reduction strategies in highly susceptible zones of the Ushairy Basin.

Gridded Flash Flood Risk Index Coupling Statistical Approaches and TOPLATS Land Surface Model for Mountainous Areas

This study presents the development of a statistical flash flood risk index model, which is currently operating in research mode for flash flood risk forecasting in ungauged mountainous areas. The grid-based statistical flash flood risk index, with temporal and spatial resolutions of 1 h and 1 km, respectively, has been developed to simulate the flash flood risk index leading to flash flood casualties using hourly rainfall, surface flow, and soil water content in the previous 6 h. The statistical index model employs factor analysis and multi-linear regression to analyze its gridded hydrological components that are obtained from the TOPMODEL-based Land Atmosphere Transfer Scheme (TOPLATS). The performance of the developed index model has been evaluated in estimating flash flooding in ungauged mountain valleys and small streams. Numerical results show that the approach simulated 38 flash flood catastrophes in the Seoul Capital Region with 71% accuracy; therefore, this approach is potentially adequate for flash flood risk forecasting.

Risk assessment and sensitivity analysis of flash floods in ungauged basins using coupled hydrologic and hydrodynamic models

Flash floods are among the most devastating natural hazards but the analyses of flash floods are hindered by the lack of hydro-meteorological data. In particular, data issues are critical in ungauged basins. This paper presents an investigation of flash flood modeling using coupled hydrological and hydrodynamic models. Specifically, the TOPography-based hydrological MODEL (TOPMODEL) is employed to obtain the flood hydrograph and the coupled 1D-2D hydrodynamic model MIKEFLOOD is used to simulate floodplain inundation. The methods are tested in the Pajiang River, a mountainous basin in South China. The results show that the TOPMODEL effectively simulates the flood hydrograph and the Nash–Sutcliffe coefficients of the flow rate are larger than 0.80 for both calibration and validation. Also, MIKEFLOOD effectively simulates the flood inundation extent and flooding depth and the BIAS for simulated water level is −0.004 m. Further, using socioeconomic and historical flood disaster datasets, areas with high flash flood risk are identified. A flash flood risk assessment shows a clear trend of change in the flood hazard and the spatial heterogeneity of the flood vulnerability is significant. A sensitivity analysis of the flood vulnerability to the socioeconomic indicators indicates that cultivated land is the most sensitive indicators, and the population and the construction areas have similar influences. Overall, the coupled hydrological and hydrodynamic models prove effective and can be used in practical applications for flash flood risk mapping.

Flash Flood Risk Analysis Based on Machine Learning Techniques in the Yunnan Province, China

Flash flood, one of the most devastating weather-related hazards in the world, has become more and more frequent in past decades. For the purpose of flood mitigation, it is necessary to understand the distribution of flash flood risk. In this study, artificial intelligence (Least squares support vector machine: LSSVM) and classical canonical method (Logistic regression: LR) are used to assess the flash flood risk in the Yunnan Province based on historical flash flood records and 13 meteorological, topographical, hydrological and anthropological factors. Results indicate that: (1) the LSSVM with Radial basis function (RBF) Kernel works the best (Accuracy = 0.79) and the LR is the worst (Accuracy = 0.75) in testing; (2) flash flood risk distribution identified by the LSSVM in Yunnan province is near normal distribution; (3) the high-risk areas are mainly concentrated in the central and southeastern regions, where with a large curve number; and (4) the impact factors contributing the flash flood risk map from higher to low are: Curve number > Digital elevation > Slope > River density > Flash Flood preventions > Topographic Wetness Index > annual maximum 24 h precipitation > annual maximum 3 h precipitation.

Algorithm of conversion of meteorological model parameters

This article is focused on the forecasting severe storms with the Algorithm of Storm Prediction as a new forecasting tool for the prediction of the convective precipitation, severe storm phenomena and the risk of flash floods. The first chapter contains information about two applications on which basis are computed forecast ouptuts of this algorithm. Further, this chapter is also objected on more detailed descripition of the second application known as the Algorithm of conversion of meteorological model parameters . Predictive outputs generated by this algorithm are verified on 63 storm events, which is occurred in the territory of the Zlín Region in 2015-2017. The results chapter solves the comparison of the success rate of the manually and computed-processed outputs calculated in the Algorithm of Storm Prediction. Primarily, these outputs will be used for increasing efectivity of preventive measures against flash floods not only by the Fire Rescue Service, but also by flood authorities and crisis management bodies.

Flash flood risk assessment in urban arid environment: case study of Taibah and Islamic universities’ campuses, Medina, Kingdom of Saudi Arabia

Flooding impacts can be reduced through application of suitable hydrological and hydraulic tools to define flood zones in a specific area. This article proposes a risk matrix technique which is applied on a case study of Taibah and Islamic universities catchment in Medina, Kingdom of Saudi Arabia (KSA). The analysis is based on integration of the hydrologic model hydraulic models to delineate the flood inundation zones. A flood risk matrix is developed based on the flood occurrence probability and the associated inundation depth. The risk matrix criterion is classified according to the degree of risks as high, moderate and low. The case study has indicted low to moderate risk for flood frequencies of 5 years return periods and moderate to high risk may exist for flood with rerun period of 50 and 100 years. The results are projected on a two-dimensional satellite images that shows the geographical locations exposed to flooding. A quantitative summary of the results have been presented graphically to estimate the magnitude of the inundation areas that can assess the degree of damage and its economic aspects. The developed flood risk matrix tool is a quantitative tool to assess the damage which is crucial for decision makers.

Establishing an early warning system for flash floods in Hoang Su Phi District, Ha Giang Province, Vietnam

Hoang Su Phi is a mountainous district in Ha Giang province, Vietnam. When the rainy season arrives in these parts, flash floods (besides landslides), frequently occur in many areas, seriously affecting the socio‐economic condition of the district. Therefore, in this paper, we have developed an early warning system for flash floods, established based on a geomorphological and hydrological approach. The basic principle underlying this system is the fact that flash floods will often occur where there is high potential risk with sufficient rainfall. In the model, eight parameters of the basin were used to build a potential flash flood map. Using the spatial processing module in an open source software, early predictions from automatic weather stations were interpolated and processed online to produce a potential risk map. Depending on the threshold of precipitation values, the results determined locations where flash flood may occur at various flash flood risk indices (FFRI). The system may be applied to support provision of early flash flood warning up to 1−6 days in advance in the district, allowing the local government ample time to make appropriate decisions on the prevention and/or mitigation of damages caused by flash flood hazards.

Impact of land use changes on flash flood prediction using a sub-daily SWAT model in five Mediterranean ungauged watersheds (SE Spain)

Flash floods cause severe natural disasters over the world generating property and infrastructures damages, poverty and loss of human life, among others. Mediterranean coastal watersheds are specially sensible to flash floods effects due to their typical drainage basin features (steep slopes, short concentration times, complex orography, etc.) and the high rainfall intensity typical of convective systems. In the present study, the temporal evolution of the hydrological answer in five Mediterranean (SE Spain) ravine basins with sizes from 10.2 km2 to 200.9 km2 were analysed. A sub-daily SWAT model was used at watershed scale to capture the complex hydrological dynamics. Five land use scenarios corresponding to no-urbanization (baseline), 1990, 2000, 2006 and 2012 were evaluated using GIS-based tools. Additionally, statistical significant differences among the studied scenarios were checked employing the Kruskal-Wallis and post-hoc tests based on Mann-Whitney test with BH correction.Our results show that flash flood risks have increased in the studied catchments due to changes in land uses, particularly affected by a large urban growth. Observed changes in soil uses have been important since the sixties of the last century, because of a high demographic and touristic pressure and specially the urban area has enhanced considerably during the last 22 years. Currently, some of these catchments present around 70% of their surface occupied by urban land uses with high population density producing curve number surpasses 85 and 90 levels. The hydrological response of the studied basins changed to higher flow rate peaks and shorter concentration times. Some discharges increased significantly from the baseline land use scenario (≈50 m3/s, 190 m3/s, 380 m3/s) to the most urbanised scenario (≈235 m3/s, 385 m3/s, 940 m3/s), respectively. These findings provide to urban planning policy makers very useful information in the face of flash flood effects, which have cost even human lifes in the studied ravine basins during last years.

The Anthropogenic Geomorphology of the New Suburbs, East of Greater Cairo, Egypt

The Greater Cairo (GC) is one of the largest urban clusters in the world. Basiclly, it contains three interlocked cities including Cairo City (the capital). In the last two decades, many new suburbs were constructed to the east of the old Cairo City. The current study investigates recent urbanization of the new suburbs and its impacts on natural landscape-geomorphology. A series of optical satellite images are utilized to quantify land-cover changes from 2000 to 2017. Detailed field studies were carried out. These field studies allow checking remotely sensed data and observing human-induced landforms. The human activities (urban growth) alter the native geomorphology, mainly drainage basins (wadis). Two applied case studies have been carried out. These applied case studies probe the flash flood risk in the New Cairo City and the New Adminstrative Capital, and demonstrate the land subsidence in Madinty suburb.

Two‐dimensional hydrodynamic modelling for urban flood risk assessment using unmanned aerial vehicle imagery: A case study of Kirsehir, Turkey

This study is an assessment of flash flood risk in the downstream part of an intermittent stream which lost its natural bed due to intense human interventions, with the example of Hastane Brook in the province of Kirsehir (Turkey). The effects of flooding events with high, medium, and low probability of occurrence are investigated on a street‐by‐street basis with a two‐dimensional (2D) hydrodynamic model constructed in HEC‐RAS 5.0 software. Due to the lack of records of past flood events required for model calibration, it is aimed to utilise high‐quality data as much as possible in model development. Therefore, to more accurately simulate the movement of water and thereby to advise adequate measures for reducing the most likely flood effects, the required high‐resolution terrain and land use data are produced by processing the aerial images acquired by the unmanned aerial vehicle (UAV) flights over the flood risk zone. The estimation of flood hydrographs is only based on the synthetic unit hydrograph methods due to the absence of representative stream gauging stations inside or near the region. The resultant flood hazard maps are cautionary in terms of demonstrating the effects of possible floods that are unexpected to come from such an intermittent stream basin.

Enhancing flash flood risk perception and awareness of mitigation actions through risk communication: A pre-post survey design

Flood risk management is gradually shifting from a risk-based approach to an integrated one that, among other elements, considers risk communication (RC) as a means of boosting resilience. Regardless of the above, few scientists have tackled up to now the integration of RC into flood risk management. In this connection, this particular study seeks to check out the potential of a risk dialogue approach (based on an ad hoc RC strategy) to change attitudes and behaviours in relation to flash flood risk. Via a pre-post survey design, we evaluated risk perception and awareness regarding a Civil Protection Plan (CPP) implemented locally (i.e., in the municipality of Navaluenga, central Spain). For this particular objective, a questionnaire survey was created, and 201 adults (representing more than 10% of the population census) were interviewed twice in a one-year period. Before the second survey, an RC strategy was created. The RC strategy comprised briefings, quiz answers, storytelling, a contest of videos and photographs about past floods, and an intergenerational workshop. A t-test for paired sample analyses and a general linear model (GLM) repeated measures ANOVA were applied to identify changes in risk perception and awareness. Our results indicate that the RC strategy did increase flood risk perception in Navaluenga in the long term (lifetime). Also, it increased the level of awareness of the various features that comprise the CPP, enabling people to be more competent in facing a flash flood. Some cognitive biases detected in the perceptual process of human beings may shed some light on the results obtained. The implementation of well-thought-out RC strategies can play a role in improving resilience, particularly in geographic areas such as the Iberian Peninsula, in which climate change scenarios indicate a likely increase in the severity and frequency of flooding.

Assessment of flash flood vulnerability zonation through Geospatial technique in high altitude Himalayan watershed, Himachal Pradesh India

Himachal Pradesh is in the western part of the Indian Himalaya which is environmentally fragile and susceptible to natural disasters. Flash flood disaster is a major problem in the state due to its diverse topography combined with meteorological and morphological conditions. In the present study, detailed terrain information was used to identify the causes of natural disaster. Remote Sensing data such as Landsat 8 satellite data and ASTER (DEM) coupled with geological and geomorphological data were utilized in a Geographical Information System (GIS) environment for the estimation of flash flood risk in 20 sub-watersheds of Beas valley. Morphometric analysis was used to estimate the flash flood risk levels of sub-watersheds. Drainage characteristics, slope, and wetness index were analyzed by a set of parameters relevant to flash flood risks. All the sub-watersheds were assigned with a rank according to the compound value analyzed for all the given parameters. After analysis of compound values, it was observed that an area of 555 km2 which is 47% of the total area was in very high priority and very highly susceptible to the flash flood occurrences. In the entire watershed, more than 90% of the total area was found to be highly vulnerable to flash floods. Such zonations using RS/GIS can assist policymakers in taking appropriate and timely measures for the reduction of flash floods. This can initiate appropriate corrective measures and reduce the risk of heavy loss of life and property.

Role of rainfall intensity and urban sprawl in the 2014 flash flood in Genoa City, Bisagno catchment (Liguria, Italy)

Flash floods are typical for the Mediterranean region, however they have been recurring at increasing frequency over the past few decades especially over the Italian Peninsula. The region of Genoa has recently moved into the international spotlight due to frequent and disastrous flash floods of the Bisagno River and its tributaries as a result of intense autumn rainfall and dense floodplain urbanization. The last flood events even caused loss in human lives, with 6 casualties in 2011 and 1 in 2014. However, it has not yet been investigated whether the increase in these flash flood events is due to a change in rainfall regime or due to urban expansion in areas prone to flash floods. This study investigates the meteorological conditions and the ground effects of the Bisagno River flash flood of October 9th, 2014 in the city of Genoa. Application of a Standard Anomaly Index and a Cluster Analysis reveals a positive trend in intense and short-duration rainfall recorded in the Bisagno Valley for the period of 1945–2016. Urban sprawl in the catchment, assessed through a multi-temporal cartographic and photographic comparison, highlights the progressive and total consumption of land in the floodplain. In the river basin surrounding Genoa the risk of flash floods has increased, both due to a change in rainfall regime and associated increase in discharge but also due to increased vulnerability caused by progressive urban expansion and land use change, including in particular transformations of the Bisagno riverbed. The results obtained demonstrate the need for urgent action to mitigate flood risk by introducing, amongst other measures, a citizen observatory for early warning of flash floods.

Increasing Flash Floods in a Drying Climate over Southwest China

In a globally warming world, subtropical regions are generally expected to become drier while the tropics and mid–high latitudes become wetter. In line with this, Southwest China, close to 25°N, is expected to become increasingly prone to drought if annual mean precipitation decreases. However, despite this trend, changes in the temporal distribution of moisture supply might actually result in increased extreme rainfall in the region, whose climate is characterized by distinct dry and wet seasons. Using hourly and daily gauge observations, rainfall intensity changes since 1971 are examined for a network of 142 locations in the region. From the analysis, dry season changes are negligible but wet season changes exhibit a significantly strong downward trend [−2.4% (10 yr)−1], particularly during the past 15 years [−17.7% (10 yr)−1]. However, the intensity of events during the wettest of 5% hours appears to steadily increase during the whole period [1.4% (10 yr)−1], tying in with government statistical reports of recent droughts and flooding. If the opposing trends are a consequence of a warming climate, it is reasonable to expect the contradictory trend to continue with an enhanced risk of flash flooding in coming decades in the region concerned.

Cold Injury and Flash Flood Damage in Boro Rice Cultivation in Bangladesh: A Review

Increasing population with decreasing resources and increasing climate vulnerability appeared as the great challenges to sustain food security of Bangladesh. Cold stress adversely affects growth and productivity of rice (Oryza sativa L.). Systematic studies have been carried out to improve understanding on rice cold tolerance. Two adverse conditions, such as low temperature stress at reproductive stages and flash flood at maturity affect the Boro rice in the haor areas of Bangladesh. Any deviation of these two phenomena is enough to cause disaster in haor areas. Here, we summarized different types of cold injury, rice cold injury scenario and cold tolerant rice varieties/genotypes available in different countries. Moreover, we discussed on rice cold tolerant barrier and flash flood risk in Boro rice cultivation at haor areas of Bangladesh. Based on the authors’ own research and available data, the concept of overcoming cold and flash flood damage was proposed. According to this concept there were distinguished possible ways how to improve cold tolerance and flash flood problem in Boro rice cultivation in BangladeshBangladesh Rice j. 2017, 21(1): 13-25

Building socio-hydrological resilient cities against flash floods: Key challenges and a practical plan for arid regions

The objective of this research is to improve the understanding and recognition of the management challenges to flash flooding hazards and the potential adaptive measures within the arid urban areas through a socio-hydrological framework. Considering the capital of Sudan, Khartoum, as an example of urban arid areas with increasing flash flood risk, the analysis was founded on expert views and opinions collected from a range of different flood management actors following the 2013 and 2014 flash flood events. The qualitative research methods included participant observation, expert interviews and focus groups. The main themes of management challenges recorded included weak institutional capacity, bad governance, limited resources, and poor urban planning. These four themes, in turn, included different types of challenges, among which lack of: civil society engagement and coordination of actors, political will, data and tools, and effective urban development strategy shared the highest number of comments from the professional actors in each theme, respectively. These findings presented a management perspective to the lessons previously established and learned from an impact assessment. Accordingly, the amalgamation of all the lessons learned from the flood research findings enabled a suitable Master Flash Flood Management Plan (MaFFMaP) to be proposed as a final product. This plan would operate within an Integrated Flash Flood Management (IFFM) framework. The facets of the MaFFMaP include steps toward improving the quantity and quality of data resources regarding this hazard, aspects for use of these new datasets within a mixed-measure (structural and non-structural) approach from the authorities, and programmes for building community and civil society capacity through improving awareness and engagement. Furthermore, it is intended that this plan would be a replicable design, which could therefore be adopted and implemented in the wider context of the urban arid regions.

Modified Pervious Concrete Containing Recycled Asphalt Pavement and Waste Tire Rubber

Portland Cement Pervious Concrete (PCPC) can reduce the risk of flash flood by letting the storm runoff to sip through the voids available in the PCPC hence infiltrate into the soil. This unique ability of pervious concrete offers advantages to the environment, public agencies, and building owners by controlling rainwater on site and addressing storm water runoff issues. Thus, this study was conducted to substantiate the usage of inorganic, cheap and reusable material namely Recycled or reclaimed asphalt pavement (RAP) and Fine Crumb Rubber (FCR) in pervious concrete. The primary objective of this study is to compare the compressive strength, density and the surface infiltration rate of pervious concrete containing waste tire rubber with pervious concrete that is made up by using natural aggregate without any enhancement. Standard pervious concrete will consist of natural coarse aggregates and cement. In this study, RAP will be replacing the natural coarse aggregates, the same size with the previous research. The modified pervious concrete will also be mixed with a certain percentage of FCR, replacing certain percentage of the coarse aggregate. The results of this study indicate that using recycled material could achieve similar performance as using natural aggregate, hence may reduce the construction cost.