Using Lightning Data to Better Understand and Predict Flash Floods in the Mediterranean

One of the costliest natural hazards around the globe is flash floods, resulting from localized intense convective precipitation over short periods of time. Since intense convective rainfall (especially over the continents) is well correlated with lightning activity in these storms, a European Union FP6 FLASH project was realized from 2006 to 2010, focusing on using lightning observations to better understand and predict convective storms that result in flash floods. As part of the project, 23 case studies of flash floods in the Mediterranean region were examined. For the analysis of these storms, lightning data were used together with rainfall estimates in order to understand the storms?? development and electrification processes. In addition, these case studies were simulated using mesoscale meteorological models to better understand the local and synoptic conditions leading to such intense and damaging storms. As part of this project, tools for short-term predictions (nowcasts) of intense convection across the Mediterranean and Europe, and long-term forecasts (a few days) of the likelihood of intense convection, were developed and employed. The project also focused on educational outreach through a special Web site http://flashproject.org supplying real-time lightning observations, real-time experimental nowcasts, medium-range weather forecasts and educational materials. While flash floods and intense thunderstorms cannot be prevented, long-range regional lightning networks can supply valuable data, in real time, for warning the public, end-users and stakeholders of imminent intense rainfall and possible flash floods.     

Variability of the spatial structure of intense Mediterranean precipitation

Intense Mediterranean precipitation can generate devastating flash floods. A better understanding of the spatial structure of intense rainfall is critical to better identify catchments that will produce strong hydrological responses. We focus on two intense Mediterranean rain events of different types that occured in 2002. Radar and rain gauge measurements are combined to have a data set with a high spatial (1 × 1 km²) and temporal (5 min) resolution. Two thresholds are determined using the quantiles of the rain rate values, corresponding to the precipitating system at large and to the intense rain cells. A method based on indicator variograms associated with the thresholds is proposed in order to automatically quantify the spatial structure at each time step during the entire rain events. Therefore, its variability within intense rain events can be investigated. The spatial structure is found to be homogeneous over periods that can be related to the dynamics of the events. Moreover, a decreasing time resolution (i.e., increasing accumulation period) of the rain rate data will stretch the spatial structure because of the advection of rain cells by the wind. These quantitative characteristics of the spatial structure of intense Mediterranean rainfall will be useful to improve our understanding of the dynamics of flash floods.     

Radar for hydrology: Unfulfilled promise or unrecognized potential?

Hydrology requires accurate and reliable rainfall input. Because of the strong spatial and temporal variability of precipitation, estimation of spatially distributed rain rates is challenging. Despite the fact that weather radars provide high-resolution (but indirect) observations of precipitation, they are not used in hydrological applications as extensively as one could expect. The goal of the present review paper is to investigate this question and to provide a clear view of the opportunities (e.g., for flash floods, urban hydrology, rainfall spatial extremes) the limitations (e.g., complicated error structure, need for adjustment) and the challenges for the use of weather radar in hydrology (i.e., validation studies, precipitation forecasting, mountainous precipitation, error propagation in hydrological models).     

Sediment-charged flash floods on Montserrat: The influence of synchronous tephra fall and varying extent of vegetation damage

On 20th May 2006 the Soufrière Hills Volcano on the Caribbean island of Montserrat experienced a large dome collapse and intense rainfall generated flash floods. The floods had very high loads of volcanic debris derived both from this and previous eruptions and can thus be classified as lahars. The floods reached unusually high water levels and caused substantial geomorphic change in the Belham Valley. Detailed rainfall and geomorphological data, coupled with the precise timing of events and yewitness accounts have facilitated an assessment of the relative importance of rainfall volume and intensity, older volcanic debris, pre- and syn-flood tephra fall and the extent of pre-flood vegetation damage for the behavior of this and subsequent sediment-laden floods in this setting. The change in runoff behavior was controlled by preexisting vegetation damage and synchronous tephra fall and this was critically important in controlling the impact of these flash floods. Although rainfall intensity and volume have some control on flood occurrence they are not the critical control on flash flood impact on the geomorphology in the Belham Valley. A significant conclusion of this study is that the extreme nature of the flash floods was not caused by extreme rainfall (as is commonly believed to be the primary cause of flash floods) but rather it was the result of changed runoff behaviour caused by the widespread syn-flood tephra deposition and importantly the widespread vegetation damage by volcanic-associated acid rain in the preceding weeks.     

Development of a thresholds approach for real‐time flash flood prediction in complex geomorphological river basins

Flash floods represent one of the deadliest and costliest natural disasters worldwide. The hydrological analysis of a flash flood event contributes in the understanding of the runoff creation process. This study presents the analysis of some flash flood events that took place in a complex geomorphological Mediterranean River basin. The objective of the present work is to develop the thresholds for a real‐time flash flood forecasting model in a complex geomorphological watershed, based on high‐frequency data from strategically located hydrological and meteorological telemetric stations. These stations provide hourly real‐time data which were used to determine hydrological and meteorological parameters. The main characteristics of various hydrographs specified in this study were the runoff coefficients, lag time, time to peak, and the maximum potential retention. The estimation of these hydrometeorological parameters provides the necessary information in order to successfully manage flash floods events. Especially, the time to peak is the most significant hydrological parameter that affects the response time of an oncoming flash flood event. A study of the above parameters is essential for the specification of thresholds which are related to the geomorphological characteristics of the river basin, the rainfall accumulation of an event, the rainfall intensity, the threshold runoff through karstic area, the season during which the rainfall takes place and the time intervals between the rainstorms that affect the soil moisture conditions. All these factors are combined into a real‐time‐threshold flash flood prediction model. Historical flash flood events at the downstream are also used for the validation of the model. An application of the proposed model is presented for the Koiliaris River basin in Crete, Greece. Copyright © 2011 John Wiley & Sons, Ltd.     

RELATION BETWEEN PRECIPITATION AND INITIATION OF DEBRIS FLOWS IN THE JIANGJIA RAVINE,YUNNAN PROVINCE, SOUTHWEST CHINA

1 INTRODUCTION In the watershed of the Jiangjia Ravine, the frequency of occurrence of rainstorms which can mobilize debris flows is high, and there are abundant unconsolidated materials deposited in the upstream area, these resulted in frequent eruption …     

An exploratory study of spatial annual maximum of monthly precipitation in the northern region of Portugal

Adequately analyzing and modeling the extreme rainfall events is of great importance because of the effects that their magnitude and frequency can have on human life, agricultural productivity and economic aspects, among others. A single extreme event may affect several locations, and their spatial dependence has to be appropriately taken into account. Classical geostatistics is a well-developed field for dealing with location referenced data, but it is largely based on Gaussian processes and distributions, that are not appropriate for extremes. In this paper, an exploratory study of the annual maximum of monthly precipitation recorded in the northern area of Portugal from 1941 to 2006 at 32 locations is performed. The aim of this paper is to apply max-stable processes, a natural extension of multivariate extremes to the spatial set-up, to briefly describe the models considered and to estimate the required parameters to simulate prediction maps.     

Regional flood frequency and spatial patterns analysis in the Pearl River Delta region using L-moments approach

The Pearl River Delta (PRD) has one of the most complicated deltaic drainage systems with probably the highest density of crisscross-river network in the world. This article presents a regional flood frequency analysis and recognition of spatial patterns for flood-frequency variations in the PRD region using the well-known index flood L-moments approach together with some advanced statistical test and spatial analysis methods. Results indicate that: (1) the whole PRD region is definitely heterogeneous according to the heterogeneity test and can be divided into three homogeneous regions; (2) the spatial maps for annual maximum flood stage corresponding to different return periods in the PRD region suggest that the flood stage decreases gradually from the riverine system to the tide dominated costal areas; (3) from a regional perspective, the spatial patterns of flood-frequency variations demonstrate the most serious flood-risk in the coastal region because it is extremely prone to the emerging flood hazards, typhoons, storm surges and well-evidenced sea-level rising. Excessive rainfall in the upstream basins will lead to moderate floods in the upper and middle PRD region. The flood risks of rest parts are identified as the lowest in entire PRD. In order to obtain more reliable estimates, the stationarity and serial-independence are tested prior to frequency analysis. The characterization of the spatial patterns of flood-frequency variations is conducted to reveal the potential influences of climate change and intensified human activities. These findings will definitely contribute to formulating the regional development strategies for policymakers and stakeholders in water resource management against the menaces of frequently emerged floods and well-evidenced sea level rising.     

Probabilistic rainfall thresholds for flood forecasting: evaluating different methodologies for modelling rainfall spatial correlation (or dependence)

Rainfall threshold (RT) method is one of the evolving flood forecasting approaches. When the cumulative rainfall depth for a given initial soil moisture condition intersects the threshold rainfall curve, the peak discharge is expected to be equal or greater than the threshold discharge for flooding at the target site. Besides the total rainfall depth, spatial and temporal distribution of rainfall impacts the flood peak discharge and the time to peak. To revisit a previous study conducted by the authors, in which spatially independent rainfall pattern was assumed, the spatial distribution of rainfall was simulated following a Monte Carlo approach. The structure of the spatial dependence among sub‐watersheds' rainfalls was taken into account under three different scenarios, namely independent, bivariate copula (2copula) and multivariate Gaussian copula (MGC). For each set of generated random dimensionless rainfalls, the probabilistic RT curves were derived for dry moisture condition. Results were evaluated with both historical and simulated events. For the simulated events, threshold curves were assessed by means of categorical statistics, such as hit rate, false rate and critical success index (CSI). Results revealed that the best performance based on the CSI criterion corresponded to 50% curve in 2copula and MGC scenarios as well as 90% curve in the independent scenario. The recognition of 50% curve in 2copula and MGC scenarios is in agreement with our expectations that the mean probable curve should have the best performance. Moreover, the proposed inclusion of spatially dependent rainfall scenario improved the performance of RT curves by about 25% in comparison with the presumed spatially uniform rainfall scenario. Copyright © 2011 John Wiley & Sons, Ltd.     

An integrated approach of flash flood analysis in ungauged Mediterranean watersheds using post-flood surveys and unmanned aerial vehicles

This study analyzes the flash flood event of two ungauged ephemeral streams in Olympiada region (Chalkidiki, North Greece), which occurred at the 21–22 of November 2019. Aim of the study is to reconstruct the specific flash flood event, investigate the causes of flood generation mechanisms, evaluate the performance of SCS-CN hydrological and HEC-RAS hydraulic models, investigate the relation between extreme flash floods and human intervention, using the combination of ground and aerial observations obtained from the field survey and unmanned aerial vehicles (UAVs), respectively. The results of the specific discharge ranged between 9 and 11 m³ s⁻¹ km², values that are typical for flash flood events in Mediterranean region. The comparison between the observed and simulated values of flood extent showed sufficiently good performance of the hydraulic model (CSI = 82%). However, the statistical analysis of the observed and simulated flood depths displayed a flood depth overestimation by the applied model, despite that the values of the used statistic indexes are acceptable (RMSE = 0.35 m, SD = 0.53, NSE = 0.56, PBIAS = 11.26%). The model overestimation of flood depth was attributed to the DEM low resolution and quality. Ground and aerial observations depicted the alluvial fan activation, the alternation of flow paths and the huge sediment transport. Human intervention in main streams, urban sprawl, wet AMC and sediment transport were among the main factors that contributed to the flash flood generation. This integrated approach revealed the necessity of the constant evaluation and validation of hydrological and hydraulic models in small ungauged Mediterranean watersheds and ephemeral streams. The use of UAVs in combination with ground observations and hydraulic simulation could significantly contribute to the enhanced understanding of flash flood mechanisms, in the direction of flood risk mitigation, improvement of the planning efficiency of flood prevent measures, flood hazard estimation, evolution of flood warning systems and floodplain geomorphology analysis.     

Estimation of tail dependence coefficient in rainfall accumulation fields

Extreme rainfall events are of particular importance due to their severe impacts on the economy, the environment and the society. Characterization and quantification of extremes and their spatial dependence structure may lead to a better understanding of extreme events. An important concept in statistical modeling is the tail dependence coefficient (TDC) that describes the degree of association between concurrent rainfall extremes at different locations. Accurate knowledge of the spatial characteristics of the TDC can help improve on the existing models of the occurrence probability of extreme storms. In this study, efficient estimation of the TDC in rainfall is investigated using a dense network of rain gauges located in south Louisiana, USA. The inter-gauge distances in this network range from about 1 km to 9 km. Four different nonparametric TDC estimators are implemented on samples of the rain gauge data and their advantages and disadvantages are discussed. Three averaging time-scales are considered: 1 h, 2 h and 3 h. The results indicate that a significant tail dependency may exist that cannot be ignored for realistic modeling of multivariate rainfall fields. Presence of a strong dependence among extremes contradicts with the assumption of joint normality, commonly used in hydrologic applications.     

Modelling radar-rainfall estimation uncertainties using elliptical and Archimedean copulas with different marginal distributions

Abstract

Given that radar-based rainfall has been broadly applied in hydrological studies, quantitative modelling of its uncertainty is critically important, as the error of input rainfall is the main source of error in hydrological modelling. Using an ensemble of rainfall estimates is an elegant solution to characterize the uncertainty of radar-based rainfall and its spatial and temporal variability. This paper has fully formulated an ensemble generator for radar precipitation estimation based on the copula method. Each ensemble member is a probable realization that represents the unknown true rainfall field based on the distribution of radar rainfall (RR) error and its spatial error structure. An uncertainty model consisting of a deterministic component and a random error factor is presented based on the distribution of gauge rainfall conditioned on the radar rainfall (GR|RR). Two kinds of copulas (elliptical and Archimedean copulas) are introduced to generate random errors, which are imposed by the deterministic component. The elliptical copulas (e.g. Gaussian and t-copula) generate the random errors based on the multivariate distribution, typically of decomposition of the error correlation matrix using the LU decomposition algorithm. The Archimedean copulas (e.g. Clayton and Gumbel) utilize the conditional dependence between different radar pixels to obtain random errors. Based on those, a case application is carried out in the Brue catchment located in southwest England. The results show that the simulated uncertainty bands of rainfall encompass most of the reference raingauge measurements with good agreement between the simulated and observed spatial dependences. This indicates that the proposed scheme is a statistically reliable method in ensemble radar rainfall generation and is a useful tool for describing radar rainfall uncertainty.

Editor D. Koutsoyiannis; Associate editor S. Grimaldi     

A dependence modelling study of extreme rainfall in Madeira Island

The dependence between variables plays a central role in multivariate extremes. In this paper, spatial dependence of Madeira Island's rainfall data is addressed within an extreme value copula approach through an analysis of maximum annual data. The impact of altitude, slope orientation, distance between rain gauge stations and distance from the stations to the sea are investigated for two different periods of time. The results obtained highlight the influence of the island's complex topography on the spatial distribution of extreme rainfall in Madeira Island.     

The relationship between rainfall inputs and flood generation in south–east Spain

Rainfall and flood data are relatively sparse in semi‐arid areas; hence there have been relatively few investigations into the relationships between rainfall inputs and flood generation in these environments. Previous work has shown that flood properties are influenced by a combination of precipitation characteristics including amount, intensity, duration and spatial distribution. Therefore floods may be produced by high intensity, short duration storms, or longer duration, low intensity rainfall. Most of this research has been undertaken in small catchments in either hyper‐arid or relatively high rainfall Mediterranean climates. This paper presents results from a 6 year data record in south‐east Spain from research conducted in two basins, the Rambla Nogalte (171 km²) and the Rambla de Torrealvilla (200 km²). Data cover an area of approximately 500 km² and an annual average rainfall of 300 mm. At coarse temporal resolutions gauges spread over large areas record similar patterns of rainfall, although spells of rain show much more complexity; pulses of rain within storms can vary considerably in total rainfall, intensity and duration over the same area. The analysis for south‐east Spain shows that most storms occur over a period of less than 24 h, but that the number of rainfall events declines as the duration exceeds 8 h. This is at odds with data on floods for the study area suggesting that they are produced by storms lasting longer than 18 h. However, one flood event was produced by a very short (15 min) storm with high intensity rainfall. Most floods tended to occur in May/June or September, which coincides with wetter months of the year (September, October, December and May). Floods are also more highly related to the total rainfall occurring in a spell of rain, than to intensity. The complexity of storm rainfall increases with the storm total, which makes it difficult to generalize on the importance of rainfall intensity for flood generation. Copyright © 2007 John Wiley & Sons, Ltd.     

Radar rainfall estimation for flash flood forecasting in small urban watersheds

Radar rainfall estimation for flash flood forecasting in small, urban catchments is examined through analyses of radar, rain gage and discharge observations from the 14.3 km² Dead Run drainage basin in Baltimore County, Maryland. The flash flood forecasting problem pushes the envelope of rainfall estimation to time and space scales that are commensurate with the scales at which the fundamental governing laws of land surface processes are derived. Analyses of radar rainfall estimates are based on volume scan WSR-88D reflectivity observations for 36 storms during the period 2003–2005. Gage-radar analyses show large spatial variability of storm total rainfall over the 14.3 km² basin for flash flood producing storms. The ability to capture the detailed spatial variation of rainfall for flash flood producing storms by WSR-88D rainfall estimates varies markedly from event to event. As spatial scale decreases from the 14.3 km² scale of the Dead Run watershed to 1 km² (and the characteristic time scale of flash flood producing rainfall decreases from 1 h to 15 min) the predictability of flash flood response from WSR-88D rainfall estimates decreases sharply. Storm to storm variability of multiplicative bias in storm total rainfall estimates is a dominant element of the error structure of radar rainfall estimates, and it varies systematically over the warm season and with flood magnitude. Analyses of the 7 July 2004 and 28 June 2005 storms illustrate microphysical and dynamical controls on radar estimation error for extreme flash flood producing storms.     

Spatial risk assessment of typhoon cumulated rainfall: a case study in Taipei area

Typhoon is one of the most destructive disasters in Taiwan, which usually causes many floods and mudslides and prevents the electrical and water supply. Prior to its arrival, how to accurately forecast the path and rainfall of typhoon are important issues. In the past, a regression-based model was the most applied statistical method to evaluate the associated problems. However, it generally ignored the spatial dependence in the data, resulting in less accurate estimation and prediction, and the importance of particular explanatory variables may not be apparent. Therefore, in this paper we focus on assessing the spatial risk variations regarding the typhoon cumulated rainfall at Taipei with respect to typhoon locations by using the spatial hierarchical Bayesian model combined with the spatial conditional autoregressive model, where the model parameters are estimated by designing a family of stochastic algorithms based on a Markov chain Monte Carlo technique. The proposed method is applied to a real data set of Taiwan for illustration. Also, some important explanatory variables regarding the typhoon cumulated rainfall at Taipei are indicated as well.     

Flood modelling using the distributed event-based SCS-LR model in the Mediterranean Real Collobrier catchment

ABSTRACT

Event-based models are often used for flood prediction because they require fewer data than more complex models and account for a small number of parameters. We present the performance of such a model in simulating Mediterranean floods, with a focus on the initialization and on the impact of the rainfall uncertainties on the calibration of the model. The distributed event-based parsimonious Soil Conservation Service Lag-and-Route (SCS-LR) model was applied in the Real Collobrier catchment, France, which has a very high density of raingauges. The initial condition of the model was highly correlated with predictors, such as baseflow or soil water content. A reduction in the raingauge density can markedly change the calibration of the model. As the density of raingauges is generally low in most catchments, the uncertainties associated with rainfall measurement are thus expected either to mask the actual accuracy of the model, or to alter the model parameters.     

A review of advances in flash flood forecasting

Flash flooding is one of the most hazardous natural events, and it is frequently responsible for loss of life and severe damage to infrastructure and the environment. Research into the use of new modelling techniques and data types in flash flood forecasting has increased over the past decade, and this paper presents a review of recent advances that have emerged from this research. In particular, we focus on the use of quantitative precipitation estimates and forecasts, the use of remotely sensed data in hydrological modelling, developments in forecasting models and techniques, and uncertainty estimates. Over the past decade flash flood forecast lead‐time has expanded up to six hours due to improved rainfall forecasts. However the largest source of uncertainty of flash flood forecasts remains unknown future precipitation. An increased number of physically based hydrological models have been developed and used for flash flood forecasting and they have been found to give more plausible results when compared with the results of conceptual, statistical, and neural network models. Among the three methods for deciding flash flood occurrence discussed in this review, the rainfall comparison method (flash flood guidance) is most commonly used for flash flood forecasting as it is easily understood by the general public. Unfortunately, no existing model is capable of making reliable flash flood forecasts in urban watersheds even though the incidence of urban flash flooding is increasing due to increasing urbanisation. Copyright © 2011 John Wiley & Sons, Ltd.     

Hydraulic model tests for propagation of flow and sediment in floods due to breaking of a natural landslide dam during a mountainous torrent

During mountain torrents, large-magnitude floods may result from heavy rainfall and cause the breakage of landslide dams naturally formed by heavy rainfall, earthquakes, and so on. The characteristics of longitudinal spreading of clear water discharge and changes in flow depth must be clarified because the changes in peak depth have not yet been examined in steep-slope torrents and because there are few data on spreading of flash floods and related sedimentation in mountainous torrents. In the present study, experimental data were collected through hydraulic model tests over a rigid bed, and the spreading of water, fine sediment, bed load, and large boulders due to flooding are discussed assuming that flash flooding/debris flows occur in the upstream reach. The effects of changes in flow width, such as expansions and contractions in the flow width, as well as changes in meandering channels, sediment transportation, and spreading flow depth resulting from bores are examined using flume data for a steep-slope torrent. The data obtained in the present study reveal that fine sediment components are transported to the downstream reach if large-magnitude floods occur and that the spreading rate and peak lags of the fine sediment and water level indicate the occurrence of a flood in the upstream reach.     

Influence of rainfall and soil properties spatial aggregation on extreme flash flood response modelling: An evaluation based on the Sesia river basin,North Western Italy

High resolution radar rainfall fields and a distributed hydrologic model are used to evaluate the sensitivity of flood and flash flood simulations to spatial aggregation of rainfall and soil properties at catchment scales ranging from 75 to 983 km². Hydrologic modeling is based on a Hortonian infiltration model and a network-based representation of hillslope and channel flow. The investigation focuses on three extreme flood and flash flood events occurred on the Sesia river basin, North Western Italy, which are analysed by using four aggregation lengths ranging from 1 to 16 km. The influence of rainfall spatial aggregation is examined by using the flow distance as a spatial coordinate, hence emphasising the role of river network in the averaging of space–time rainfall. The effects of reduced and distorted rainfall spatial variability on peak discharge have been found particularly severe for the flash flood events, with peak errors up to 35% for rainfall aggregation of 16 km and at 983 km² catchment size. Effects are particularly remarkable when significant structured rainfall variability combines with relatively important infiltration volumes due to dry initial conditions, as this emphasises the non-linear character of the rainfall–runoff relationship. In general, these results confirm that the correct estimate of rainfall volume is not enough for the accurate reproduction of flash flood events characterised by large and structured rainfall spatial variability, even at catchment scales around 250 km². However, accurate rainfall volume estimation may suffice for less spatially variable flood events. Increasing the soil properties aggregation length exerts similar effects on peak discharge errors as increasing the rainfall aggregation length, for the cases considered here and after rescaling to preserve the rainfall volume. Moreover, peak discharge errors are roughly proportional to runoff volume errors, which indicates that the shape of the flood wave is influenced in a limited way by modifying the detail of the soil property spatial representation. Conversely, rainfall aggregation may exert a pronounced influence on the discharge peak by reshaping the spatial organisation of the runoff volumes and without a comparable impact on the runoff volumes.