Simulation Of Flood Events Research Articles

Modeling an evaluation framework for adding IoT water-level sensors based on ANN-derived 2D inundation simulations

ABSTRACT This study aims to develop a smart model for evaluating the spatial density of added IoT sensors (called AIOT grids) to optimize their amount and placements, named SM_ESD_AIOT model; the proposed SM_ESD_AIOT model mainly collaborates cluster analysis with Akaike information criterion (AIC) based on the resulting 2D inundation simulations from the ANN-derived model in comparison with those from the physically based hydrodynamic (SOBEK) model under various sets of AIOT-based sensor networks. Miaoli City in northern Taiwan is selected as the study with the three practical IoT sensors; also, the 1,939 electrical poles are treated as the potential AIOT grids grouped under 5, 10, 15, and 20 clusters. Using a simulated rainfall-induced flood event of 51 h, the five AIOT-based sets, consisting of five added and three practical IoT sensors, could be selected as the optimal one with the minimum AIC (around 1.45). Also, on average, the 2D inundation simulation indices from the optimal five AIOT-based sensor networks are 0.7 better than the results from the three IoT sensors (about 0.495). As a result, the proposed SM_ESD_AIOT is shown to efficiently optimize the amount and placements of the AIOT sensors to enhance the reliability and accuracy of 2D inundation simulation.

Flood risk assessment using machine learning, hydrodynamic modelling, and the analytic hierarchy process

ABSTRACT The objective of this study was to develop a theoretical framework based on machine learning, the hydrodynamic model, and the analytic hierarchy process (AHP) to assess the risk of flooding downstream of the Ba River in the Phu Yen. The framework was made up of three main factors: flood risk, flood exposure, and flood vulnerability. Hazard was calculated from flood depth, flood velocity, and flood susceptibility, of which depth and velocity were calculated using the hydrodynamic model, and flood susceptibility was built using machine learning, namely, support vector machines, decision trees, AdaBoost, and CatBoost. Flood exposure was constructed by combining population density, distance to the river, and land use/land cover. Flood vulnerability was constructed by combining poverty level and road density. The indices of each factor were integrated using the AHP. The results showed that the hydraulic model was successful in simulating flood events in 1993 and 2020, with Nash–Sutcliffe efficiency values of 0.95 and 0.79, respectively. All machine learning models performed well, with area under curve (AUC) values of more than 0.90; among them, AdaBoost was most accurate, with an AUC value of 0.99.

Impacts of spatiotemporal resolutions of precipitation on flood event simulation based on multimodel structures – a case study over the Xiang River basin in China

Abstract. Accurate flood event simulation and prediction, enabled by effective models and reliable data, are critical for mitigating the potential risk of flood disaster. This study aims to investigate the impacts of spatiotemporal resolutions of precipitation on flood event simulation in a large-scale catchment of China. We use high-spatiotemporal-resolution Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG) products and a gauge-based product as precipitation forcing for hydrologic simulation. Three hydrological models (HBV, SWAT and DHSVM) and a data-driven model (long short-term memory (LSTM) network) are utilized for flood event simulation. Two calibration strategies are carried out, one of which targets matching of the flood events, with peak discharge exceeding 8600 m3 s−1 between January 2015 and December 2017, and the other one is the conventional strategy for matching the entire streamflow time series. The results indicate that the event-based calibration strategy improves the performance of flood event simulation compared with a conventional calibration strategy, except for DHSVM. Both hydrological models and LSTM yield better flood event simulation at a finer temporal resolution, especially in flood peak simulation. Furthermore, SWAT and DHSVM are less sensitive to the spatial resolutions of IMERG, while the performance of LSTM obtains improvement when degrading the spatial resolution of IMERG-L. Generally, LSTM outperforms the hydrological models in most flood events, which implies the usefulness of the deep learning algorithms for flood event simulation.

Hydrologic Evaluation of the Global Precipitation Measurement Mission over the U.S.: Effect of Spatial and Temporal Scales

This research focuses on the effects of spatio-temporal resolutions of global satellite precipitation on simulated flood events characteristics. The analysis is carried out by spatially, temporally, and spatiotemporally upscaling fine-scale precipitation forcings from the ground-radar-based Multi-Radar Multi-Sensor system (MRMS) to the resolution of the Integrated Multi-satellitE Retrievals for GPM (IMERG) satellite precipitation product. These upscaled products were then run through the Ensemble Framework for Flash Flood Forecasting hydrologic modeling framework over the U.S. to assess how the different spatial and temporal resolutions impact the simulated outputs of flood event magnitude, duration, and timing. It was found that the quantitative uncertainties generated by the IMERG Early (IMERG-E) simulations overpowered those associated with resolution across all flood characteristics. When compared to native MRMS simulations, however, the upscaled precipitation estimates tended to underestimate peak discharges and event durations, associated with distinct negative water balance errors. It was also found that the upscaled precipitation simulations exhibited a scaling effect with regards to error contribution of peak discharge, with higher contributions at smaller basin sizes and decreasing contributions as basin sizes increased. Looking at how upscaling can affect the modeled output desired allows for improved understanding of which resolutions lead to the greatest changes in simulation accuracy, increasing the potential global use and utility of current or future satellite products, especially in regions where high-resolution ground radars are sparse.

Hydrological Simulation Study in Gansu Province of China Based on Flash Flood Analysis

The calibration and validation of hydrological model simulation performance and model applicability evaluation in Gansu Province is the foundation of the application of the flash flood early warning and forecasting platform in Gansu Province. It is difficult to perform the simulation for Gansu Province due to the fact that it covers a wide range, from north to south, with multiple climate types and diverse landforms. The China Flash Flood Hydrological Model (CNFF) was implemented in this study. A total of 11 model clusters and 289 distributed hydrological models were divided based on hydrology, climate, and land-use factors, among others. A spatiotemporally mixed runoff method and the Event-Specific Geomorphological Instantaneous Unit Hydrograph (GIUH) were applied based on large-scale fast parallel computation. To improve model calibration and validation efficiency, the RSA method (Regionalized Sensitivity Analysis) was used for CNFF model parameter sensitivity analysis, which could reduce the number of model parameters that need to be adjusted during the calibration period. Based on the model sensitivity analysis results, the CNFF was established in Gansu Province to simulate flood events in eight representative watersheds. The average NSE, REQ, and ET were 0.76 and 0.73, 9.1% and 12.6%, and 1.2 h and 1.7 h, respectively, in the calibration and validation period. In general, the CNFF model shows a good performance in multiple temporal and spatial scales, thus providing a scientific basis for flash flood early warning and analysis in Gansu Province.

A two-dimensional hydrodynamic urban flood model based on equivalent drainage of manholes

Abstract Numerical simulations of urban flood events are of great significance in flood control and disaster reduction. An important part of these numerical investigations concerns drainage, which is crucial to the accuracy of the simulation results. To overcome the difficulty of obtaining underground pipe network data and improve the traditional equivalent drainage simulation method, an equivalent drainage model based on manholes is proposed, to simulate urban flooding based on a two-dimensional hydrodynamic model. The new model is applied to a classic case and the simulation results are compared with those from the MIKE URBAN model to verify the simulation accuracy of the proposed formulation. The submerged areas given by the two models are compared under different rainfall conditions, with an average relative error of 6%. The differences in water depths at various nodes are statistically analyzed, and the average Nash–Sutcliffe efficiency and average root mean square error are found to be 96% and 0.03 m, respectively. The results of this research provide effective urban flood simulation in areas lacking pipe network data and have important significance for promoting the practical application of refined numerical simulations of urban flooding.

Construction of a semi-distributed hydrological model considering the combination of saturation-excess and infiltration-excess runoff space under complex substratum

Study regionTypical basin in humid areas in the Huaihe River Study focusAccurate flood forecasting is essential for making timely decisions regarding flood control and disaster reduction. The theory of watershed runoff generation and convergence serves as a crucial foundation for flood forecasting, while the calculation of runoff is necessary to simulate flood discharge. Identifying watershed runoff generation mechanisms has been a challenging task, particularly under complex underlying surface conditions. To improve the accuracy of flood simulation, this study examines the underlying surface information in the watershed, such as particle composition and content, soil bulk density, geological slope, land use, and other spatial attributes, aiming to analyze the mechanisms of runoff generation. In the study of sub-watersheds, various combinations of runoff generation mechanisms are identified to determine the patterns of runoff. Subsequently, a semi-distributed hydrological model is developed, which incorporates both saturation-excess and infiltration-excess runoff, utilizing the information obtained from the underlying surface. The model is validated using rainfall-runoff data from 14 events at the Xiagushan watershed. New hydrological insights for the regionThe analysis of the fundamental physical conditions of the underlying surface of the watershed revealed that 69.70% of the area is prone to saturation-excess runoff, with an additional 30.30% of the area being susceptible to infiltration-excess runoff. The model considers the spatial distribution of runoff patterns by incorporating complex underlying surface information and demonstrates high accuracy in simulating flood events (NSE= 0.87, Epeak = 12.08%, Wpeak = 13.16%, Tpeak = 0.14 h, R2 = 0.90). The model is straightforward, practical, and exhibits promising potential in terms of timeliness and applicability, thus lending itself well to further application in other watersheds, contributing to the scientific foundation of flood warning and forecasting efforts.

Estimation of channel and flood plain roughness using HEC-RAS model: A case study of the Veseočica River, Bosnia and Herzegovina

Modeling flow in open channels is essential for determining channel capacity and predicting flood events. The key segment for creating flood hazard and risk maps is a high-quality hydraulic model of the flow in the main bed with its tributaries. Several software packages have been developed for hydrodynamic simulations of flood events. In addition to the geometric characteristics of the watercourse, the equations of a one-dimensional flow model include a parameter that connects all influences that provide resistance to the flow of water. Determining the roughness of a natural channel is one of the most demanding procedures for the development of hydraulic models. Therefore, it is necessary to calibrate and validate the Manning coefficients of the channel roughness using simulation models. In the present study, the estimation of channel and floodplain roughness for the Veseočica River in Bosnia and Herzegovina was performed using the HEC-RAS hydrodynamic model. After calibration and verification of the model, flood hazard maps were created for flood waves with return periods of 20, 100, and 500 years. ArcGIS and HEC-GeoRAS software tools were used to create the flood risk maps.

Reliability of Runoff Hydrograph Model for Extreme Rainfall Events using HEC-RAS 2D Flow Hydrodynamics Rain-On-Grid

Hydrological modeling is a valuable tool for analyzing water resources and predicting the impacts of extreme rainfall events, particularly for flood risk mitigation. Accurate results from hydrological models rely heavily on detailed input of watershed characteristics, including morphometric factors, land cover, and slope. In the face of the increasing frequency and severity of floods due to climate change, hydrological modeling has become an essential tool for disaster risk mitigation and management. HEC-RAS is a widely used software for river flow modeling and floodplain analysis. HEC-RAS 2D with the rain-on-grid meteorological model is a powerful tool for simulating flood events in complex river systems. The rain-on-grid method enables the simulation of spatially distributed rainfall events and their impact on runoff, which is crucial for modeling extreme runoff hydrographs. Previous studies have demonstrated the accuracy and effectiveness of HEC-RAS 2D with rain-on-grid in modeling extreme runoff hydrographs. This study aims to validate the reliability of HEC-RAS 2D hydrodynamics in simulating unsteady flow with meteorological data will be examined within a laboratory-scale physical model of the watershed. Additionally, the performance of HEC-RAS 2D will be evaluated in a observed watershed, specifically the Bangga watershed in Central Sulawesi to assess the performance of the HEC-RAS 2D Hydrodynamics model. The runoff hydrograph reliability model using HEC-RAS 2D rain-on-grid yielded close results when compared to a laboratory-scale physical model with a rainfall simulator and HEC-RAS 2D simulation using meteorological input data. The error in Time of Peak (Tp) and Peak Discharge (Qp) between the physical and numerical models was 7% and 3.5%, respectively. Additionally, in the HEC-RAS 2D simulation, a Manning roughness coefficient value of 0.04 closely matched the results of the physical model, while there was some variability when comparing HEC-RAS 2D results with measured data in Bangga watershed of Central Sulawesi. However, the numerical model exhibited relatively approaching result with the HEC-HMS SCS hydrograph model.

Assessing the compound flood risk in coastal areas: Framework formulation and demonstration

Storm surge and river runoff can result in compound flooding in coastal areas. The impact of these events can be more significant than that generated by each component individually. This paper describes a framework for characterizing flooding during compound events and quantifying the relative importance of surge and river flows in controlling inundation depth (ID). For the analysis, we considered 1051 simulations of historical flood events covering about 40 years in Connecticut (CT), USA, and several simulated storms associated with synthetic climate scenarios. We simulated river discharge time series for each event using a physically based distributed hydrological model and retrieved the storm surge from tidal stations. These time series are used as upstream and downstream boundary conditions in 2D hydrodynamic simulation. We focused the analysis on seven locations along the coast of Connecticut covered by LiDAR-derived 1 m DEM. To capture the variability of inundation characteristics over the full-scale gradient from river to coast, we introduced a new topographic index, D-Index, that distinguishes topologic variabilities. Results from this study highlight that there is a correlation of ID to different drivers in distinct categories of the D-Index, which can correctly label the main source of hazard, either coast, river, or compound. We identified thresholds of standard deviation (σ) of the D-Index to identify areas where ID strongly correlates with either flow peak and volume, surge peak, or a combination of both. The study also shows that it is possible to use the results obtained from the 1 m analysis to generalize the findings for the entire CT coast to derive zones dominated by surge, river flow, or the compound effect of the two. This study can help coastal communities better understand the risk of the compound impacts of coastal storms, which is essential for increasing climate resilience.

Signatures-and-sensitivity-based multi-criteria variational calibration for distributed hydrological modeling applied to Mediterranean floods

Classical calibration methods in hydrology typically rely on a single cost function computed on long-term streamflow series. Even when hydrological models achieve acceptable scores in NSE and KGE, imbalances can still arise between overall model performance and its ability to simulate flood events, particularly flash floods. Multi-scale signatures, which refer to hydrological signatures computed at different temporal and/or spatial scales, and distributed flood modeling, which accounts for spatial variability in input variables and model parameters, are important concepts in hydrological modeling. In this study, the potential of using multi-scale signatures is explored to enhance multi-criteria calibration methods for spatially distributed flood modeling, which remains considerable challenges. We present a novel signatures and sensitivity-based calibration approach implemented into a variational data assimilation algorithm capable to deal with high dimensional spatially distributed hydrological optimization problems. It is tested on 141 flash flood pronecatchments mostly located in the French Mediterranean region. Our approach involves computing several signatures, including flood event signatures, using an automated flood segmentation algorithm. We select suitable signatures for constraining the model based on their global sensitivity with the input parameters through global signature-based sensitivity analysis (GSSA). We then perform two multi-criteria calibration strategies using the selected signatures, including a single-objective optimization approach, which transforms the multi-criteria problem into a single-objective function, and a multi-objective optimization approach, which uses a simple additive weighting method to select an optimal solution from the Pareto set. Our results show significant improvements in both calibration and temporal validation metrics, especially for flood signatures, demonstrating the robustness and delicacy of our signatures-based calibration framework for enhancing flash flood forecasting systems.

Hydrodynamic modeling of ephemeral flow in the Iishana channel systems of the Cuvelai Basin—Northern Namibia

AbstractThe transboundary region of the Iishana system in the western Cuvelai Basin, between southern Angola and northern Namibia, is frequently affected by floods at irregular intervals. As a result, the predominantly rural, subsistence farming population has experienced crop failures, human, and economic losses. To date, very little is known about the generation of floods, flood concentration, and stormwater drainage dynamics in this region. In this study, 2D‐hydrodynamic modeling was applied to reconstruct one of the latest major flood events during the rainy season from November 2008 to March 2009 in order to study the runoff behavior and interconnectivity of the Iishana system. The model focused on the eastern part of the Iishana system, which was most affected by floods and flood damage due to the high population density in and around Oshakati, the regional capital. Two main streams were identified noteworthy because they merge and subsequently affect Oshakati. Regarding the simulated flood event water depths vary from 0.1 m to 14 m, with an average of 0.2 m, while water depths above 5 m were attributed to borrow pits. The inundation area ranged up to 1860 km2 and the amount of water left after the rainy season on March 25th, 2009, was determined between 0.116 and 0.547 km3, depending on the amount of evapotranspiration considered in the model. Thus, in the Angolan part of the Iishana system, significantly larger quantities of water are available for longer periods of time during the subsequent dry season, whereas the system in Namibia stores less water, resulting in a shorter water retention period.

Simulating flood events at the Twin Ports of Duluth-Superior using a linked hydrologic-hydrodynamic framework

Generally, ports in the North American Great Lakes are not supported with navigational guidance (water level, water temperature, currents, ice) by NOAA’s Great Lakes Operational Forecast System (GLOFS). To examine the benefit of extending model coverage to this critical infrastructure, a linked hydrologic-hydrodynamic framework was developed for the Twin Ports of Duluth-Superior in western Lake Superior, and tested over three case studies of flooding due to storm surge and/or river flooding. Streamflow from 22 National Water Model (NWM) simulated and 3 gauged inflows within the domain was injected into a hydrodynamic model built on the Finite Volume Community Ocean Model (FVCOM), with a wet-dry grid that covered the harbor and surrounding floodplain. Model results from flood simulations compared well against time-series of water level and streamflow at gauges within the harbor, with root mean square error (RMSE) and bias values small relative to the typical fluctuations. Inclusion of NWM-simulated tributaries improved the accuracy of modeled water levels in the harbor, and increased simulated current speeds in navigational channels by up to 0.5 ms−1. Modeled inundation extent in the floodplain closely matched flood extent surveys conducted in response to a record flood event in 2012, demonstrating the capability of the modeling framework to provide flood guidance in the complex coastal setting.

2D Numerical Simulation of Floods in Ebro River and Analysis of Boundary Conditions to Model the Mequinenza Reservoir Dam

The computational simulation of rivers is a useful tool that can be applied in a wide range of situations from providing real time alerts to the design of future mitigation plans. However, for all the applications, there are two important requirements when modeling river behavior: accuracy and reasonable computational times. This target has led to recent developments in numerical models based on the full two-dimensional (2D) shallow water equations (SWE). This work presents a GPU accelerated 2D SW model for the simulation of flood events in real time. It is based on a well-balanced explicit first-order finite volume scheme able to run over dry beds without the numerical instabilities that are likely to occur when used in complex topography. The model is applied to reproduce a real event in the reach of the Ebro River (Spain) with a downstream reservoir, in which a study of the most appropriate boundary condition (BC) for modeling of the dam is assessed (time-dependent level condition and weir condition). The whole creation of the model is detailed in terms of mesh optimization and validation. The simulation results are compared with field data over the flood duration (up to 20 days), allowing an analysis of the performance and time saved by different GPU devices and with the different BCs. The high values of fit between observed and simulated results, as well as the computational times achieved, are encouraging to propose the use of the model as a forecasting system.

Intercomparison of global reanalysis precipitation for flood risk modelling

Abstract. Reanalysis datasets are increasingly used to drive flood models, especially for continental and global analysis and in areas of data scarcity. However, the consequence of this for risk estimation has not been fully explored. We investigate the implications of four reanalysis products (ERA-5, CFSR, MERRA-2 and JRA-55) on simulations of historic flood events in five basins in England. These results are compared to a benchmark national gauge-based product (CEH-GEAR1hr). The benchmark demonstrated better accuracy than reanalysis products when compared with observations of water depth and flood extent. All reanalysis products predicted fewer buildings would be inundated by the events than the national dataset. JRA-55 was the worst by a significant margin, underestimating by 40 % compared with 14 %–18 % for the other reanalysis products. CFSR estimated building inundation the most accurately, while ERA-5 demonstrated the lowest error in terms of river stage (29.4 %) and floodplain depth (28.6 %). Accuracy varied geographically, and no product performed best across all basins. Global reanalysis products provide a useful resource for flood modelling where no other data are available, but they should be used with caution due to the underestimation of impacts shown here. Until a more systematic international strategy for the collection of rainfall and flood impact data ensures more complete global coverage for validation, multiple reanalysis products should be used concurrently to capture the range of uncertainties.

Simulation of overland flow in the Domica cave area flood events using the r.sim.water module

The flash floods are very important hydrometeorological situations affecting the Domica cave area. The flash floods depend on several factors such as the amount of precipitation, land cover, phenological phase of the vegetation, or soil infiltration rate. This paper focuses on the simulation of flood events occurring in the winter and summer seasons on the Silická plateau. The main aim of the paper is the evaluation of the effects of model parameterisation and interpretation of spatial aspects of the overland flow during the flood events. GRASS GIS software, specifically its r.sim.water module was used for hydro-logical modelling of the surface runoff. The simulation included a detailed digital eleva-tion model calculated from airborne laser scanning data and land cover derived from a detailed orthoimagery map. The infiltration rate parameter and the Manning’s roughness coefficient were estimated based on land cover classes. The simulation produced water depth maps describing flood events. The results showed that during the winter season in 2016, a smaller rainfall intensity was necessary for flood occurrence and that this phenomenon is primarily caused by frozen soil, through which no water is being infiltrated. The simulation of summer flood event in 2017 shows similar results of runoff accumulation but with higher rainfall intensity and infiltration rate. The flash flood event in 2021 turned out to be differ-ent, with such extreme rainfall intensity that even higher infiltration rate was insufficient in slowing the surface runoff. The results also proved the suitability of the chosen method for small-scale high-resolution hydrological simulations. URL: https://www.gcass.science.upjs.sk/

Urban Flood Loss Estimation and Evacuation Design Based on a 500-Year Extreme Flood Event in Syracuse City

To understand the potential risk of flooding in Syracuse City, New York State, USA, this research attempted to accomplish the flood hazard assessment for a simulated 500-year flood event in the downstream floodplain of Onondaga Creek within Syracuse. Based on the commonly used category of flood damages, the flood damage of Syracuse was divided into loss of buildings and loss of population. The results showed that the city’s center would have the highest damage rate for buildings and a total of 1139 buildings would be inundated, of which 326 buildings would be severely damaged by more than 80%. Furthermore, about 7390 people would be directly affected by the flood event, among which approximately 900 people might lose their lives. Communities near Onondaga Creek were assigned designated evacuation shelters based on the accessibility and distance to the shelters. The shortest available evacuation routes were calculated. More shelters should be provided in the central downtown area, with its large population, and distributed along the western bank of Onondaga Creek. This research offered a first approximate flood loss estimation that might lead to more attention and studies concerning a potential flood hazard in the future. It also provided science-based guidelines for city authorities to refer to in practical flood hazard mitigation.

Hydrological and Hydraulic Modeling Applied to Flash Flood Events in a Small Urban Stream

In flood area mapping studies, hydrological-hydraulic modeling has been successfully applied around the world. However, the object of study of most of the research developed in Brazil is medium to large channels that use topographical and hydrometeorological data of coarse spatial and temporal resolution. Thus, the aim of this study is to investigate coupled modeling in a small urban channel, using high-resolution data, in the simulation of flood events in a small urban channel, located in Campo Grande, Mato Grosso do Sul. In this study, we used the HEC-HMS and HEC-RAS programs, where topographic information, land use, land cover, and observed data from rain gauges, water level, and flow sensors from 2015 to 2018 were used as input data. To calibrate and validate the hydrological model, four events were used that occurred during the monitoring period, while in the hydraulic model we chose a historical event that caused great disturbances. We then generated flood scenarios with representative synthetic rainfall for a basin, with return times of 5, 10, 50, and 100 years. We observed a good fit in the calibration and validation of the HEC-HMS, with values of R2 = 0.93, RMSE = 1.29, and NSE = 0.92. In HEC-RAS, we obtained values of R2 = 0.93, RMSE = 1.29, and NSE = 0.92 for the calibration, and in the validation, real images of the event prove the computed flood spot sources. We observed that rain with a return time of less than five years provides areas of flooding in several regions of the channel, and in critical channeled sections, the elevation and speed of the flow reach 5 m and 3 m·s−1, respectively. Our results indicate that the channel already has a natural tendency towards flooding in certain stretches, which become more compromised due to land use and coverage and local conditions. We conclude that the high-resolution coupled modeling generated information that represents local conditions as well, showing how potential failures of drainage in extreme scenarios are possible, thus enabling the planning of adaptations and protection measures against floods.

Spatially coherent statistical simulation of widespread flooding events under climate change

Abstract Simulating rare widespread hydrological events can be difficult even with the use of modelled data such as the UKCP18 12 km regional climate projections. To generate larger event sets for application in catastrophe modelling, two statistical approaches are highlighted and applied to widespread GB-generated flooding events using a grid-based hydrological model and UKCP18 regional projections. An Empirical Copula method was applied on a national scale, generating over 600,000 events across two time-slices (1980–2010 and 2050–2080). This was compared to model-generated events and showed good matching across time-slices and ensemble members, although lacked some ability to describe the least-rare events. The Empirical Copula was also compared to an implementation of a conditional exceedance model. This model was much more computationally intensive so was restricted to Northwest England but offered the ability to be tuned more finely through choices of marginal distributions. Analysing over 11,000 events, it also matched well with the Empirical Copula and model-generated events but under-represented the smallest events. Both approaches require a broad dataset to draw from but showed reasonable efficacy. For simple statistics, the Empirical Copula shows the potential to be a powerful tool in exploring spatial structure over large regions or at a fine spatial resolution.

Modelling flooding due to runoff from spoil heaps during heavy rainfall

ABSTRACT Flash floods generated by runoff from abandoned spoil heaps have posed great risks to neighbouring areas but there has been little study on the process, so it is difficult to evaluate the effectiveness of runoff retention or detention measures. These events are likely to become more frequent in a future climate change scenario. To provide a means by which interested parties can study such events, including methods of mitigation, a computer modelling approach is proposed using free open-source software. Unlike conventional tools that solve the shallow water equations, the software tool uses a cellular automata approach to reduce the computational overhead. It is also easy to use so it is suitable for use by practitioners who are not hydrology experts. The method is illustrated by modelling a historical flood in the UK involving spoil heap runoff. Good correlation was observed between the characteristics of the actual and simulated flood event.