Vasilis Bellos | National Technical University of Athens (original) (raw)
Papers by Vasilis Bellos
Water, 2022
We propose a novel probabilistic approach to flood hazard assessment, aiming to address the major... more We propose a novel probabilistic approach to flood hazard assessment, aiming to address the major shortcomings of everyday deterministic engineering practices in a computationally efficient manner. In this context, the principal sources of uncertainty are defined across the overall modeling procedure, namely, the statistical uncertainty of inferring annual rainfall maxima through distribution models that are fitted to empirical data, and the inherently stochastic nature of the underlying hydrometeorological and hydrodynamic processes. Our work focuses on three key facets, i.e., the temporal profile of storm events, the dependence of flood generation mechanisms on antecedent soil moisture conditions, and the dependence of runoff propagation over the terrain and the stream network on the intensity of the flood event. These are addressed through the implementation of a series of cascade modules, based on publicly available and open-source software. Moreover, the hydrodynamic processes ...
Habitat Suitability Curves (HSCs) were developed for two freshwater fish species, namely Salmo pe... more Habitat Suitability Curves (HSCs) were developed for two freshwater fish species, namely Salmo pelagonicus and Barbus balcanicus, using microhabitat data obtained at a mountainous stream, in upper Axios River, Greece, for habitat evaluation on the micro scale. Twelve riverine HSCs associating two size classes with three microhabitat parameters (water depth, velocity and substrate) were developed and used. For the hydraulic simulation of the stream, the well-known, one-dimensional HEC-RAS software was implemented. The Weighted Usable Area (WUA) was estimated by combining habitat suitability indices with the output of the hydraulic model, to evaluate the relationship between streamflow and fish habitat availability. For the calibration of the model, water depth and flow velocity measurements were performed on April 2016. In the framework of the calibration phase, an algorithm was developed, to automate this process and to implement a sophisticated optimisation method. For the upstream...
Water Resources Management, 2018
Urban drainage modelling typically requires development of highly detailed simulators due to the ... more Urban drainage modelling typically requires development of highly detailed simulators due to the nature of various underlying surface and drainage processes, which makes them computationally too expensive. Application of such simulators is still challenging in activities such as real-time control (RTC), uncertainty quantification analysis or model calibration in which numerous simulations are required. The focus of this paper is to present a rather simple hybrid surrogate modelling (or emulation) strategy to simplify and accelerate a detailed urban drainage simulator (UDS). The proposed surrogate modelling strategy includes: a) identification of the variables to be emulated; b) development of a simplified conceptual model in which every component contributing to the variables identified in step (a) is replaced by a function; c) definition of these functions, either based on knowledge about the mechanisms of the simulator, or based on the data produced by the simulator; and finally, d) validation of the results produced by the surrogate model in comparison with the original detailed simulator. Herein, a detailed InfoWorks ICM simulator was selected for surrogate modelling. The case study area was a small urban drainage network in Luxembourg. An emulator was developed to map the rainfall time series, as input, to a storage tank volume and combined sewer overflow (CSO) in the case study network. The results showed that the introduced strategy provides a reliable method to simplify the simulator and reduce its run time significantly. For the specific case study, the emulator was approximately 1300 times faster than the original detailed simulator. For quantification of the emulation error, an ensemble of 500 rainfall scenarios with 1 month duration was generated by application of a multivariate autoregressive model for conditional simulation of rainfall time series. The results produced by the emulator were compared to the ones produced by the simulator. Finally, as an indicator of the emulation error, distributions of Nash-Sutcliffe efficiency (NSE) between the emulator and simulator results for prediction of storage tank volume and CSO flow time series were presented.
Water Research, 2018
This paper aims to stimulate discussion based on the experiences derived from the QUICS project (... more This paper aims to stimulate discussion based on the experiences derived from the QUICS project (Quantifying Uncertainty in Integrated Catchment Studies). First it briefly discusses the current state of knowledge on uncertainties in sub-models of integrated catchment models and the existing frameworks for analysing uncertainty. Furthermore, it compares the relative approaches of both building and calibrating fully integrated models or linking separate sub-models. It also discusses the implications of model linkage on overall uncertainty and how to define an acceptable level of model complexity. This discussion includes, whether we should shift our attention from uncertainties due to linkage, when using linked models, to uncertainties in model structure by necessary simplification or by using more parameters. This discussion attempts to address the question as to whether there is an increase in uncertainty by linking these models or if a compensation effect could take place and that overall uncertainty in key water quality parameters actually decreases. Finally, challenges in the application of uncertainty analysis in integrated catchment water quality modelling, as encountered in this project, are discussed and recommendations for future research areas are highlighted.
Water Research, 2018
This paper aims to stimulate discussion based on the experiences derived from the QUICS project (... more This paper aims to stimulate discussion based on the experiences derived from the QUICS project (Quantifying Uncertainty in Integrated Catchment Studies). First it briefly discusses the current state of knowledge on uncertainties in sub-models of integrated catchment models and the existing frameworks for analysing uncertainty. Furthermore, it compares the relative approaches of both building and calibrating fully integrated models or linking separate sub-models. It also discusses the implications of model linkage on overall uncertainty and how to define an acceptable level of model complexity. This discussion includes, whether we should shift our attention from uncertainties due to linkage, when using linked models, to uncertainties in model structure by necessary simplification or by using more parameters. This discussion attempts to address the question as to whether there is an increase in uncertainty by linking these models or if a compensation effect could take place and that overall uncertainty in key water quality parameters actually decreases. Finally, challenges in the application of uncertainty analysis in integrated catchment water quality modelling, as encountered in this project, are discussed and recommendations for future research areas are highlighted.
Water, 2017
A methodology is presented which can be used in the evaluation of parametric uncertainty in urban... more A methodology is presented which can be used in the evaluation of parametric uncertainty in urban flooding simulation. Due to the fact that such simulations are time consuming, the following methodology is proposed: (a) simplification of the description of the physical process; (b) derivation of a training data set; (c) development of a data-driven surrogate model; (d) use of a forward uncertainty propagation scheme. The simplification comprises the following steps: (a) unit hydrograph derivation using a 2D hydrodynamic model; (b) calculation of the losses in order to determine the effective rainfall depth; (c) flood event simulation using the principle of the proportionality and superposition. The above methodology was implemented in an urban catchment located in the city of Athens, Greece. The model used for the first step of the simplification was FLOW-R2D, whereas the well-known SWMM software (US Environmental Protection Agency, Washington, DC, USA) was used for the second step of the simplification. For the training data set derivation, an ensemble of 100 Unit Hydrographs was derived with the FLOW-R2D model. The parameters which were modified in order to produce this ensemble were the Manning coefficients in the two friction zones (residential and urban open space areas). The surrogate model used to replicate the unit hydrograph derivation, using the Manning coefficients as an input, was based on the Polynomial Chaos Expansion technique. It was found that, although the uncertainties in the derived results have to be taken into account, the proposed methodology can be a fast and efficient way to cope with dynamic flood simulation in an urban catchment.
Water Research, 2018
This work presents a method to emulate the flow dynamics of physically based hydrodynamic simulat... more This work presents a method to emulate the flow dynamics of physically based hydrodynamic simulators under variations of time-dependent rainfall and parametric scenarios. Although surrogate modelling is often employed to deal with the computational burden of this type of simulators, common techniques used for model emulation as polynomial expansions or Gaussian processes cannot deal with large parameter space dimensionality. This restricts their applicability to a reduced number of static parameters under a fixed rainfall process. The technique presented combines the use of a modified Unit Hydrograph (UH) scheme and a polynomial chaos expansion (PCE) to emulate flow from physically based hydrodynamic models. The novel element of the proposed methodology is that the emulator compensates for the errors induced by the assumptions of proportionality and superposition of the UH theory when dealing with non-linear model structures, whereas it approximates properly the behaviour of a physically based simulator to new (spatially-uniform) rainfall time-series and parametric scenarios. The computational time is significantly reduced, which makes the practical use of the model feasible (e.g. real time control, flood warning schemes, hydraulic structures design, parametric inference etc.). The applicability of this methodology is demonstrated in three case studies, through the emulation of a simplified non-linear tank-in-series routing structure and of the 2D Shallow Water Equations (2D-SWE) solution (FLOW-R2D) in two computational domains. Results indicate that the proposed emulator can approximate with a high degree of accuracy the behaviour of the original models under a wide range of rainfall inputs and parametric values.
Water Resour Manage, 2014
Floods in built-up areas are among the most catastrophic natural hazards mainly due to the high v... more Floods in built-up areas are among the most catastrophic natural hazards mainly due to the high value properties existing in these areas. The most vulnerable areas are the riverine areas with mild terrain which are often encountered in the coastal zone. Due to the mild terrain and the complicated topography caused by buildings, roads and infrastructure, a two-dimensional modelling is required for a realistic simulation of the flood evolvement. In this paper the flood simulation is performed by a recently devised fully dynamic numerical model, the FLOW-R2D, which is based on the two-dimensional Shallow Water Equations solved by the Finite Difference Method and the McCormack numerical scheme. The performance of the model is tested for three alternative representations of the resistance caused by buildings, namely, the reflection boundary, the local elevation rise, and the local increase of the Manning roughness coefficient. The model was run for three different hydrographs and produced time series of water depths and flow velocities in the entire computational domain of the inundated area for each hydrograph. The results of the model for the three alternative building representations and different building alignments were compared with the experimental data available from experiments reported in recent papers. Based on the comparison between numerical and experimental results it was concluded that the reflection boundary method proved to be the most successful building representation for the application of FLOW-R2D. Finally, the data requirements and the required density of the digital terrain model were discussed in relation to the building representation methods.
Water Resources Management, 2014
In this paper, a new powerful numerical hydrodynamic in-house model is presented and tested. The ... more In this paper, a new powerful numerical hydrodynamic in-house model is presented and tested. The model simulates flood routing in two dimensions. It is based on the solution of Shallow Water Equations using the Finite Difference Method according to the explicit McCormack numerical scheme which has shock capturing capability. The innovation of the proposed model lies in the modification of McCormack scheme by incorporating artificial viscosity through a diffusion factor in order to avoid oscillations as proposed by various researchers. Additionally, a threshold of water depth is introduced in order to distinguish the wet and dry cells of the computational domain. The model is capable of producing maps for the inundation extent, water depths and depth-averaged water velocities. Finally, the paper presents extensive testing of the model by comparison with analytical solution, experimental results and with the output of another software package in real world flood simulation studies.
Hydrology
Machine learning has been employed successfully as a tool virtually in every scientific and techn... more Machine learning has been employed successfully as a tool virtually in every scientific and technological field. In hydrology, machine learning models first appeared as simple feed-forward networks that were used for short-term forecasting, and have evolved into complex models that can take into account even the static features of catchments, imitating the hydrological experience. Recent studies have found machine learning models to be robust and efficient, frequently outperforming the standard hydrological models (both conceptual and physically based). However, and despite some recent efforts, the results of the machine learning models require significant effort to interpret and derive inferences. Furthermore, all successful applications of machine learning in hydrology are based on networks of fairly complex topology that require significant computational power and CPU time to train. For these reasons, the value of the standard hydrological models remains indisputable. In this stu...
In this dataset, the water depth time series in 21 gauges of Sumacarcel town are derived by the F... more In this dataset, the water depth time series in 21 gauges of Sumacarcel town are derived by the FLOW-R2D model, assuming 240 different combinations of three input paramaters: a) input flow to the computatioal domain (upstream boundaries) (Q) b) the Manning coefficient of the computational domain (n) c) effective slope (required at the upstream boundaries) (S) The sampling for the three parameters is made by Latin Hypercube technique, assuming for each parameter the following interval: a) 10000-20000 m^3/s b) 0.03-0.21 s/m^(1/3) c) 0.0001 - 0.02 The dataset consists of the following: 1) input_data.csv file, in which the 240 combinations of the three input parameters is provided (Scenario 100 - 399) 2) runs_tous folder, in which files 100.cv-399.csv. Water depth time series are recorded in 21 gauges. The first column is time (in seconds), and the water dpeths are in meters. Papers relative to this dataset: 1) Description of the case study: Alcrudo F and Mulet J (2007). Description o...
This report describes a brief overview of current predictions of the effect of climate change on ... more This report describes a brief overview of current predictions of the effect of climate change on precipitation. Although there is great regional variation on the predictions, there is a general consensus that there may be an increase in the occurrence of extreme events. The current climate change predictions are generally made over large regions, and not urban scales. Downscaled predictions do exist, but they are generally still daily or hourly, and over several km 2 resolution. The wash-off of sediment from urban areas is a process that varies over small areas (e.g. streets, gardens, roofs, hence 10s and 100s meters) and over periods of minutes. Hence currently existing downscaled predictions of climate change are as yet not usable for prediction of effects of climate change on urban sediment wash-off. Furthermore, questions remain in general about the relation between spatial and temporal variability of rainfall at urban scales (sub-km and minutes), sampling errors and uncertainty due to other sources, and uncertainty this may cause in simulating runoff and wash-off from urban areas. Hence, to aid the study of potential effects of climate chance and localised high rainfall intensity peaks on urban sediment wash-off, this report described the effects of small scale rainfall variability on uncertainty in wash-off. A new dataset of uniquely high resolution rainfall (9 paired gauges over 200x400m at 1 minute resolution) was utilised, as well as an innovative set of laboratory wash-off experiments. The propagation of different sources of uncertainty, including rainfall uncertainty, in improved sediment wash-off modelling was investigated Key findings were that: for a 400x200 m area, at 2 min temporal averaging interval the average coefficient of variation in the prediction of peak AARI is 6.6 % and the maximum coefficient of variation is 13 % and they are reduced to 1.5 % and 3.6 % respectively at 30 min averaging interval; and the maximum uncertainty in the prediction of peak wash-off load due to rainfall uncertainty within an 8-ha catchment was found to be ~15%.
Urban drainage modelling typically requires development of highly detailed and complex models due... more Urban drainage modelling typically requires development of highly detailed and complex models due to the nature of the underlying drainage processes. This makes activities such as model calibration, uncertainty quantification analysis and usage in real-time control (RTC) challenging and computationally expensive. The focus of this paper is to develop a surrogate model to simplify and accelerate a complex model, and make it available for RTC in future studies. Hence, only the output of the model which is relevant for RTC is considered. Surrogate models may lead to larger uncertainties in the model predictions but can significantly decrease simulation runtime. Therefore, quantification of this uncertainty is addressed here as well. We use the detailed InfoWorks ICM software as the simulator for surrogate modelling. The case study area is within the Haute-Sûre catchment in Luxembourg. First, we ran the InfoWorks ICM model to produce a dataset of inputs and outputs of the simulator. Sec...
Hydrology
Dam break studies consist of two submodels: (a) the dam breach submodel which derives the flood h... more Dam break studies consist of two submodels: (a) the dam breach submodel which derives the flood hydrograph and (b) the hydrodynamic submodel which, using the flood hydrograph, derives the flood peaks and maximum water depths in the downstream reaches of the river. In this paper, a thorough investigation of the uncertainty observed in the output of the hydrodynamic model, due to the seven dam breach parameters, is performed in a real-world case study (Papadiana Dam, located at Tavronitis River in Crete, Greece). Three levels of uncertainty are examined (flow peak of the flood hydrograph at the dam location, flow peaks and maximum water depths downstream along the river) with two methods: (a) a Morris-based sensitivity analysis for investigating the influence of each parameter on the final results; (b) a Monte Carlo-based forward uncertainty analysis for defining the distribution of uncertainty band and its statistical characteristics. Among others, it is found that uncertainty of the...
Water Resources Management
This study seeks to test the predictive performance of a hydraulic model using as reference the f... more This study seeks to test the predictive performance of a hydraulic model using as reference the flood extent extracted through Sentinel-1 imagery. A precipitation event which took place between the 22nd and 28th of February 2018 in Pineios river basin, Central Greece, was analyzed. A threshold technique was performed to delineate the inundation extent from the satellite image, whereas both HEC-HMS and HEC-RAS software were coupled to simulate the examined storm event. To assess model response, the flooded area derived through the modeling approach was compared against that derived from the satellite image processing, using an area-based measure of fit. Furthermore, an uncertainty analysis on the parameters of the hydrologic model was elaborated to investigate their impact on the results of the hydraulic model. The sensitivity of the latter to the value of the roughness coefficient as well as to changes in the spatial resolution of the utilized topography was also examined. Considering as a perfect response of the model its complete coincidence with the satellite image product, it was found that the hydraulic model performance ranged between 61.04%-65.49%, depending on the selected upstream flow hydrograph, topography and roughness coefficient. The upstream flow conditions proved to play a more critical role, while roughness coefficient and topography were found to cause slighter changes in model response.
Journal of Hydraulic Engineering
Water, 2022
We propose a novel probabilistic approach to flood hazard assessment, aiming to address the major... more We propose a novel probabilistic approach to flood hazard assessment, aiming to address the major shortcomings of everyday deterministic engineering practices in a computationally efficient manner. In this context, the principal sources of uncertainty are defined across the overall modeling procedure, namely, the statistical uncertainty of inferring annual rainfall maxima through distribution models that are fitted to empirical data, and the inherently stochastic nature of the underlying hydrometeorological and hydrodynamic processes. Our work focuses on three key facets, i.e., the temporal profile of storm events, the dependence of flood generation mechanisms on antecedent soil moisture conditions, and the dependence of runoff propagation over the terrain and the stream network on the intensity of the flood event. These are addressed through the implementation of a series of cascade modules, based on publicly available and open-source software. Moreover, the hydrodynamic processes ...
Habitat Suitability Curves (HSCs) were developed for two freshwater fish species, namely Salmo pe... more Habitat Suitability Curves (HSCs) were developed for two freshwater fish species, namely Salmo pelagonicus and Barbus balcanicus, using microhabitat data obtained at a mountainous stream, in upper Axios River, Greece, for habitat evaluation on the micro scale. Twelve riverine HSCs associating two size classes with three microhabitat parameters (water depth, velocity and substrate) were developed and used. For the hydraulic simulation of the stream, the well-known, one-dimensional HEC-RAS software was implemented. The Weighted Usable Area (WUA) was estimated by combining habitat suitability indices with the output of the hydraulic model, to evaluate the relationship between streamflow and fish habitat availability. For the calibration of the model, water depth and flow velocity measurements were performed on April 2016. In the framework of the calibration phase, an algorithm was developed, to automate this process and to implement a sophisticated optimisation method. For the upstream...
Water Resources Management, 2018
Urban drainage modelling typically requires development of highly detailed simulators due to the ... more Urban drainage modelling typically requires development of highly detailed simulators due to the nature of various underlying surface and drainage processes, which makes them computationally too expensive. Application of such simulators is still challenging in activities such as real-time control (RTC), uncertainty quantification analysis or model calibration in which numerous simulations are required. The focus of this paper is to present a rather simple hybrid surrogate modelling (or emulation) strategy to simplify and accelerate a detailed urban drainage simulator (UDS). The proposed surrogate modelling strategy includes: a) identification of the variables to be emulated; b) development of a simplified conceptual model in which every component contributing to the variables identified in step (a) is replaced by a function; c) definition of these functions, either based on knowledge about the mechanisms of the simulator, or based on the data produced by the simulator; and finally, d) validation of the results produced by the surrogate model in comparison with the original detailed simulator. Herein, a detailed InfoWorks ICM simulator was selected for surrogate modelling. The case study area was a small urban drainage network in Luxembourg. An emulator was developed to map the rainfall time series, as input, to a storage tank volume and combined sewer overflow (CSO) in the case study network. The results showed that the introduced strategy provides a reliable method to simplify the simulator and reduce its run time significantly. For the specific case study, the emulator was approximately 1300 times faster than the original detailed simulator. For quantification of the emulation error, an ensemble of 500 rainfall scenarios with 1 month duration was generated by application of a multivariate autoregressive model for conditional simulation of rainfall time series. The results produced by the emulator were compared to the ones produced by the simulator. Finally, as an indicator of the emulation error, distributions of Nash-Sutcliffe efficiency (NSE) between the emulator and simulator results for prediction of storage tank volume and CSO flow time series were presented.
Water Research, 2018
This paper aims to stimulate discussion based on the experiences derived from the QUICS project (... more This paper aims to stimulate discussion based on the experiences derived from the QUICS project (Quantifying Uncertainty in Integrated Catchment Studies). First it briefly discusses the current state of knowledge on uncertainties in sub-models of integrated catchment models and the existing frameworks for analysing uncertainty. Furthermore, it compares the relative approaches of both building and calibrating fully integrated models or linking separate sub-models. It also discusses the implications of model linkage on overall uncertainty and how to define an acceptable level of model complexity. This discussion includes, whether we should shift our attention from uncertainties due to linkage, when using linked models, to uncertainties in model structure by necessary simplification or by using more parameters. This discussion attempts to address the question as to whether there is an increase in uncertainty by linking these models or if a compensation effect could take place and that overall uncertainty in key water quality parameters actually decreases. Finally, challenges in the application of uncertainty analysis in integrated catchment water quality modelling, as encountered in this project, are discussed and recommendations for future research areas are highlighted.
Water Research, 2018
This paper aims to stimulate discussion based on the experiences derived from the QUICS project (... more This paper aims to stimulate discussion based on the experiences derived from the QUICS project (Quantifying Uncertainty in Integrated Catchment Studies). First it briefly discusses the current state of knowledge on uncertainties in sub-models of integrated catchment models and the existing frameworks for analysing uncertainty. Furthermore, it compares the relative approaches of both building and calibrating fully integrated models or linking separate sub-models. It also discusses the implications of model linkage on overall uncertainty and how to define an acceptable level of model complexity. This discussion includes, whether we should shift our attention from uncertainties due to linkage, when using linked models, to uncertainties in model structure by necessary simplification or by using more parameters. This discussion attempts to address the question as to whether there is an increase in uncertainty by linking these models or if a compensation effect could take place and that overall uncertainty in key water quality parameters actually decreases. Finally, challenges in the application of uncertainty analysis in integrated catchment water quality modelling, as encountered in this project, are discussed and recommendations for future research areas are highlighted.
Water, 2017
A methodology is presented which can be used in the evaluation of parametric uncertainty in urban... more A methodology is presented which can be used in the evaluation of parametric uncertainty in urban flooding simulation. Due to the fact that such simulations are time consuming, the following methodology is proposed: (a) simplification of the description of the physical process; (b) derivation of a training data set; (c) development of a data-driven surrogate model; (d) use of a forward uncertainty propagation scheme. The simplification comprises the following steps: (a) unit hydrograph derivation using a 2D hydrodynamic model; (b) calculation of the losses in order to determine the effective rainfall depth; (c) flood event simulation using the principle of the proportionality and superposition. The above methodology was implemented in an urban catchment located in the city of Athens, Greece. The model used for the first step of the simplification was FLOW-R2D, whereas the well-known SWMM software (US Environmental Protection Agency, Washington, DC, USA) was used for the second step of the simplification. For the training data set derivation, an ensemble of 100 Unit Hydrographs was derived with the FLOW-R2D model. The parameters which were modified in order to produce this ensemble were the Manning coefficients in the two friction zones (residential and urban open space areas). The surrogate model used to replicate the unit hydrograph derivation, using the Manning coefficients as an input, was based on the Polynomial Chaos Expansion technique. It was found that, although the uncertainties in the derived results have to be taken into account, the proposed methodology can be a fast and efficient way to cope with dynamic flood simulation in an urban catchment.
Water Research, 2018
This work presents a method to emulate the flow dynamics of physically based hydrodynamic simulat... more This work presents a method to emulate the flow dynamics of physically based hydrodynamic simulators under variations of time-dependent rainfall and parametric scenarios. Although surrogate modelling is often employed to deal with the computational burden of this type of simulators, common techniques used for model emulation as polynomial expansions or Gaussian processes cannot deal with large parameter space dimensionality. This restricts their applicability to a reduced number of static parameters under a fixed rainfall process. The technique presented combines the use of a modified Unit Hydrograph (UH) scheme and a polynomial chaos expansion (PCE) to emulate flow from physically based hydrodynamic models. The novel element of the proposed methodology is that the emulator compensates for the errors induced by the assumptions of proportionality and superposition of the UH theory when dealing with non-linear model structures, whereas it approximates properly the behaviour of a physically based simulator to new (spatially-uniform) rainfall time-series and parametric scenarios. The computational time is significantly reduced, which makes the practical use of the model feasible (e.g. real time control, flood warning schemes, hydraulic structures design, parametric inference etc.). The applicability of this methodology is demonstrated in three case studies, through the emulation of a simplified non-linear tank-in-series routing structure and of the 2D Shallow Water Equations (2D-SWE) solution (FLOW-R2D) in two computational domains. Results indicate that the proposed emulator can approximate with a high degree of accuracy the behaviour of the original models under a wide range of rainfall inputs and parametric values.
Water Resour Manage, 2014
Floods in built-up areas are among the most catastrophic natural hazards mainly due to the high v... more Floods in built-up areas are among the most catastrophic natural hazards mainly due to the high value properties existing in these areas. The most vulnerable areas are the riverine areas with mild terrain which are often encountered in the coastal zone. Due to the mild terrain and the complicated topography caused by buildings, roads and infrastructure, a two-dimensional modelling is required for a realistic simulation of the flood evolvement. In this paper the flood simulation is performed by a recently devised fully dynamic numerical model, the FLOW-R2D, which is based on the two-dimensional Shallow Water Equations solved by the Finite Difference Method and the McCormack numerical scheme. The performance of the model is tested for three alternative representations of the resistance caused by buildings, namely, the reflection boundary, the local elevation rise, and the local increase of the Manning roughness coefficient. The model was run for three different hydrographs and produced time series of water depths and flow velocities in the entire computational domain of the inundated area for each hydrograph. The results of the model for the three alternative building representations and different building alignments were compared with the experimental data available from experiments reported in recent papers. Based on the comparison between numerical and experimental results it was concluded that the reflection boundary method proved to be the most successful building representation for the application of FLOW-R2D. Finally, the data requirements and the required density of the digital terrain model were discussed in relation to the building representation methods.
Water Resources Management, 2014
In this paper, a new powerful numerical hydrodynamic in-house model is presented and tested. The ... more In this paper, a new powerful numerical hydrodynamic in-house model is presented and tested. The model simulates flood routing in two dimensions. It is based on the solution of Shallow Water Equations using the Finite Difference Method according to the explicit McCormack numerical scheme which has shock capturing capability. The innovation of the proposed model lies in the modification of McCormack scheme by incorporating artificial viscosity through a diffusion factor in order to avoid oscillations as proposed by various researchers. Additionally, a threshold of water depth is introduced in order to distinguish the wet and dry cells of the computational domain. The model is capable of producing maps for the inundation extent, water depths and depth-averaged water velocities. Finally, the paper presents extensive testing of the model by comparison with analytical solution, experimental results and with the output of another software package in real world flood simulation studies.
Hydrology
Machine learning has been employed successfully as a tool virtually in every scientific and techn... more Machine learning has been employed successfully as a tool virtually in every scientific and technological field. In hydrology, machine learning models first appeared as simple feed-forward networks that were used for short-term forecasting, and have evolved into complex models that can take into account even the static features of catchments, imitating the hydrological experience. Recent studies have found machine learning models to be robust and efficient, frequently outperforming the standard hydrological models (both conceptual and physically based). However, and despite some recent efforts, the results of the machine learning models require significant effort to interpret and derive inferences. Furthermore, all successful applications of machine learning in hydrology are based on networks of fairly complex topology that require significant computational power and CPU time to train. For these reasons, the value of the standard hydrological models remains indisputable. In this stu...
In this dataset, the water depth time series in 21 gauges of Sumacarcel town are derived by the F... more In this dataset, the water depth time series in 21 gauges of Sumacarcel town are derived by the FLOW-R2D model, assuming 240 different combinations of three input paramaters: a) input flow to the computatioal domain (upstream boundaries) (Q) b) the Manning coefficient of the computational domain (n) c) effective slope (required at the upstream boundaries) (S) The sampling for the three parameters is made by Latin Hypercube technique, assuming for each parameter the following interval: a) 10000-20000 m^3/s b) 0.03-0.21 s/m^(1/3) c) 0.0001 - 0.02 The dataset consists of the following: 1) input_data.csv file, in which the 240 combinations of the three input parameters is provided (Scenario 100 - 399) 2) runs_tous folder, in which files 100.cv-399.csv. Water depth time series are recorded in 21 gauges. The first column is time (in seconds), and the water dpeths are in meters. Papers relative to this dataset: 1) Description of the case study: Alcrudo F and Mulet J (2007). Description o...
This report describes a brief overview of current predictions of the effect of climate change on ... more This report describes a brief overview of current predictions of the effect of climate change on precipitation. Although there is great regional variation on the predictions, there is a general consensus that there may be an increase in the occurrence of extreme events. The current climate change predictions are generally made over large regions, and not urban scales. Downscaled predictions do exist, but they are generally still daily or hourly, and over several km 2 resolution. The wash-off of sediment from urban areas is a process that varies over small areas (e.g. streets, gardens, roofs, hence 10s and 100s meters) and over periods of minutes. Hence currently existing downscaled predictions of climate change are as yet not usable for prediction of effects of climate change on urban sediment wash-off. Furthermore, questions remain in general about the relation between spatial and temporal variability of rainfall at urban scales (sub-km and minutes), sampling errors and uncertainty due to other sources, and uncertainty this may cause in simulating runoff and wash-off from urban areas. Hence, to aid the study of potential effects of climate chance and localised high rainfall intensity peaks on urban sediment wash-off, this report described the effects of small scale rainfall variability on uncertainty in wash-off. A new dataset of uniquely high resolution rainfall (9 paired gauges over 200x400m at 1 minute resolution) was utilised, as well as an innovative set of laboratory wash-off experiments. The propagation of different sources of uncertainty, including rainfall uncertainty, in improved sediment wash-off modelling was investigated Key findings were that: for a 400x200 m area, at 2 min temporal averaging interval the average coefficient of variation in the prediction of peak AARI is 6.6 % and the maximum coefficient of variation is 13 % and they are reduced to 1.5 % and 3.6 % respectively at 30 min averaging interval; and the maximum uncertainty in the prediction of peak wash-off load due to rainfall uncertainty within an 8-ha catchment was found to be ~15%.
Urban drainage modelling typically requires development of highly detailed and complex models due... more Urban drainage modelling typically requires development of highly detailed and complex models due to the nature of the underlying drainage processes. This makes activities such as model calibration, uncertainty quantification analysis and usage in real-time control (RTC) challenging and computationally expensive. The focus of this paper is to develop a surrogate model to simplify and accelerate a complex model, and make it available for RTC in future studies. Hence, only the output of the model which is relevant for RTC is considered. Surrogate models may lead to larger uncertainties in the model predictions but can significantly decrease simulation runtime. Therefore, quantification of this uncertainty is addressed here as well. We use the detailed InfoWorks ICM software as the simulator for surrogate modelling. The case study area is within the Haute-Sûre catchment in Luxembourg. First, we ran the InfoWorks ICM model to produce a dataset of inputs and outputs of the simulator. Sec...
Hydrology
Dam break studies consist of two submodels: (a) the dam breach submodel which derives the flood h... more Dam break studies consist of two submodels: (a) the dam breach submodel which derives the flood hydrograph and (b) the hydrodynamic submodel which, using the flood hydrograph, derives the flood peaks and maximum water depths in the downstream reaches of the river. In this paper, a thorough investigation of the uncertainty observed in the output of the hydrodynamic model, due to the seven dam breach parameters, is performed in a real-world case study (Papadiana Dam, located at Tavronitis River in Crete, Greece). Three levels of uncertainty are examined (flow peak of the flood hydrograph at the dam location, flow peaks and maximum water depths downstream along the river) with two methods: (a) a Morris-based sensitivity analysis for investigating the influence of each parameter on the final results; (b) a Monte Carlo-based forward uncertainty analysis for defining the distribution of uncertainty band and its statistical characteristics. Among others, it is found that uncertainty of the...
Water Resources Management
This study seeks to test the predictive performance of a hydraulic model using as reference the f... more This study seeks to test the predictive performance of a hydraulic model using as reference the flood extent extracted through Sentinel-1 imagery. A precipitation event which took place between the 22nd and 28th of February 2018 in Pineios river basin, Central Greece, was analyzed. A threshold technique was performed to delineate the inundation extent from the satellite image, whereas both HEC-HMS and HEC-RAS software were coupled to simulate the examined storm event. To assess model response, the flooded area derived through the modeling approach was compared against that derived from the satellite image processing, using an area-based measure of fit. Furthermore, an uncertainty analysis on the parameters of the hydrologic model was elaborated to investigate their impact on the results of the hydraulic model. The sensitivity of the latter to the value of the roughness coefficient as well as to changes in the spatial resolution of the utilized topography was also examined. Considering as a perfect response of the model its complete coincidence with the satellite image product, it was found that the hydraulic model performance ranged between 61.04%-65.49%, depending on the selected upstream flow hydrograph, topography and roughness coefficient. The upstream flow conditions proved to play a more critical role, while roughness coefficient and topography were found to cause slighter changes in model response.
Journal of Hydraulic Engineering