A physically-based parsimonious hydrological model for flash floods in Mediterranean catchments

A spatially distributed hydrological model, dedicated to flood simulation, is developed on the basis of physical process representation (infiltration, overland flow, channel routing). Estimation of model parameters requires data concerning topography, soil properties, vegetation and land use. Four parameters are calibrated for the entire catchment using one flood event. Model sensitivity to individual parameters is assessed using Monte-Carlo simulations. Results of this sensitivity analysis with a criterion based on the Nash efficiency coefficient and the error of peak time and runoff are used to calibrate the model. This procedure is tested on the Gardon d'Anduze catchment, located in the Mediterranean zone of southern France. A first validation is conducted using three flood events with different hydrometeorological characteristics. This sensitivity analysis along with validation tests illustrates the predictive capability of the model and points out the possible improvements on the model's structure and parameterization for flash flood forecasting, especially in ungauged basins. Concerning the model structure, results show that water transfer through the subsurface zone also contributes to the hydrograph response to an extreme event, especially during the recession period. Maps of soil saturation emphasize the impact of rainfall and soil properties variability on these dynamics. Adding a subsurface flow component in the simulation also greatly impacts the spatial distribution of soil saturation and shows the importance of the drainage network. Measures of such distributed variables would help discriminating between different possible model structures

The use of distributed hydrological models for the Gard 2002 flash flood event: Analysis of associated hydrological processes

Summary This paper presents a detailed analysis of the September 8-9, 2002 flash flood event in the Gard region (southern France) using two distributed hydrological models: CVN built within the LIQUID® hydrological platform and MARINE. The models differ in terms of spatial discretization, infiltration and water redistribution representation, and river flow transfer. MARINE can also account for subsurface lateral flow. Both models are set up using the same available information, namely a DEM and a pedology map. They are forced with high resolution radar rainfall data over a set of 18 sub-catchments ranging from 2.5 to 99 km2 and are run without calibration. To begin with, models simulations are assessed against post field estimates of the time of peak and the maximum peak discharge showing a fair agreement for both models. The results are then discussed in terms of flow dynamics, runoff coefficients and soil saturation dynamics. The contribution of the subsurface lateral flow is also quantified using the MARINE model. This analysis highlights that rainfall remains the first controlling factor of flash flood dynamics. High rainfall peak intensities are very influential of the maximum peak discharge for both models, but especially for the CVN model which has a simplified overland flow transfer. The river bed roughness also influences the peak intensity and time. Soil spatial representation is shown to have a significant role on runoff coefficients and on the spatial variability of saturation dynamics. Simulated soil saturation is found to be strongly related with soil depth and initial storage deficit maps, due to a full saturation of most of the area at the end of the event. When activated, the signature of subsurface lateral flow is also visible in the spatial patterns of soil saturation with higher values concentrating along the river network. However, the data currently available do not allow the assessment of both patterns. The paper concludes with a set of recommendations for enhancing field observations in order to progress in process understanding and gather a larger set of data to improve the realism of distributed models

Analysis of flash flood processes dynamics in a Mediterranean catchment using a distributed hydrological model

The present study aims at analyzing the hydrological processes involved in flash flood generation. It focuses on small catchments located in the Mediterranean region (Southern France) and often affected by extreme events (Gaume et al., 2009; Ruin et al., 2008). The model used in this study is a spatially distributed rainfall-runoff model dedicated to extreme event simulation and developed on the basis of physical process representation. It is structured into three modules, which represent the soil component, the overland flow component and flow through the drainage network. Infiltration is described using the Green and Ampt model and the soils are assumed vertically homogeneous. Lateral subsurface flow is based on the Darcy's law for a confined aquifer. Surface runoff calculation is divided into two parts: overland flow and flow along the drainage network. Both are simulated using the 1D kinematic wave approximation of the Saint-Venant equations with the Manning friction law. In the drainage network, the friction difference between main channel and floodplain is taken into account. Determination of model parameters requires terrain measurement data, usually issued from DEM, soil survey and vegetation or land-use. Four parameters are calibrated for the entire catchment using discharge measurements. Model sensitivity to individual parameters is assessed using Monte-Carlo simulations, the model is then calibrated using these results to estimate the parameters with a data assimilation process called the adjoint state method (Bessière et al., 2008; Castaings et al., 2009). Flood events with different hydrometeorological characteristics are studied to compare the location of saturated areas, infiltration and runoff dynamics as well as importance of the subsurface flow. A better understanding of these processes is indeed necessary especially to improve the model efficiency when the simulation parameters cannot be calibrated and must therefore be transposed from gauged basins to ungauged basins

A physically-based parsimonious hydrological model for flash floods in Mediterranean catchments

International audienceA spatially distributed hydrological model, dedicated to flood simulation, is developed on the basis of physical process representation (infiltration, overland flow, channel routing). Estimation of model parameters requires data concerning topography, soil properties, vegetation and land use. Four parameters are calibrated for the entire catchment using one flood event. Model sensitivity to individual parameters is assessed using Monte-Carlo simulations. Results of this sensitivity analysis with a criterion based on the Nash efficiency coefficient and the error of peak time and runoff are used to calibrate the model. This procedure is tested on the Gardon d'Anduze catchment, located in the Mediterranean zone of southern France. A first validation is conducted using three flood events with different hydrometeorological characteristics. This sensitivity analysis along with validation tests illustrates the predictive capability of the model and points out the possible improvements on the model's structure and parameterization for flash flood forecasting, especially in ungauged basins. Concerning the model structure, results show that water transfer through the subsurface zone also contributes to the hydrograph response to an extreme event, especially during the recession period. Maps of soil saturation emphasize the impact of rainfall and soil properties variability on these dynamics. Adding a subsurface flow component in the simulation also greatly impacts the spatial distribution of soil saturation and shows the importance of the drainage network. Measures of such distributed variables would help discriminating between different possible model structures

A regional distributed hydrological modelling approach for flash-flood understanding and experimental design

Flash floods represent the most destructive natural hazard in the Mediterranean region, causing around one billion Euros worth of damage in France over the last two decades. Flash floods are associated with extreme and rare rainfall events and usually occur in ungauged river basins. Amongst them, small-ungauged catchments are recognized as the most vulnerable to storm driven flash floods. In order to limit the damages to the population, there is a need to improve our understanding and the simulation tools for these events. In order to provide information over a whole region, hydrological models applicable at this scale, and able to take into account the spatial variability of rainfall and catchment characteristics, must be proposed. This paper presents such a regional distributed approach applied to the 8-9 September 2002 extreme event which affected the Gard region in the south-east of France. In order to identify the variables and catchment characteristics which require improved knowledge, two distributed hydrological models were set up on a set of catchments, with sizes ranging from 2.5 to 99 km2. The models differ in terms of spatial discretization and process representation. They were forced using radar data with a 1 km2 spatial resolution and 5 min time step. The model parameters were specified using the available information, namely a digital terrain model and a soil data base. The latter provides information about soil texture, soil porosity and soil depths. Soil hydraulic properties were defined using pedo-transfer functions. Data from a post-flood field survey of maximum peak discharge were used to assess the quality of the simulations. A reasonable agreement between modeled and observed values was obtained. Sensitivity studies were then performed to assess the respective impact of rainfall estimation and soil variability on the simulated discharge. The analysis shows that rainfall remains the first controlling factor of flash flood dynamics and that high resolution spatial and temporal data are required in order to properly simulate peak discharge and flow dynamics for a range of scales. The river bed roughness also influences the peak intensity and time. Soil spatial representation is shown to have a significant role on runoff coefficients and on the spatial variability of saturation dynamics. For some catchments, the impact of soil properties on the simulated discharges was of the same order of magnitude as the impact of the rainfall estimation. The results were very similar for the two distributed models, despite their difference in structure. They show that the poor knowledge of soil properties, mainly soil depth, initial soil water content and saturated hydraulic conductivity is detrimental to robust estimation of discharge. A better knowledge of these variables is therefore recommended; in particular soil depth is required. Post field estimation of peak discharge were very valuable for the regional assessment of the methodology, but must be complemented with data of the whole hydrographs to reduce the uncertainty in flow dynamics and runoff production. Effort towards improved quantitative rainfall estimation using a network of radars must also be continued. The results of the study are used in the design of the future HyMeX experiment, aiming at improving the Mediterranean water balance and the knowledge of extreme events. A strategy based on gauged nested catchments is set up. Detailed measurements of the water balance (discharge, soil moisture, evapotranspiration) are proposed on small catchments of about 1 km2 in order to improve the process understanding. An intermediate scale is defined for catchments of about 100 km2 with distributed hydrometry, based on Large Scale Image Velocimetry to tackle the change of scale problem. Finally, operational data are used at larger scale of about 1000 km2. These data will also be useful to propose improved modelling tools applicable on ungauged catchments

Use of regional distributed hydrological modelling approaches for the design of catchment experimental set up within HyMeX

Flash floods represent the most destructive natural hazard in the Mediterranean region, causing around one billion Euros worth of damage in France over the last two decades. Flash floods are associated with extreme and rare rainfall events and usually occur in ungauged river basins. Amongst them, small-ungauged catchments are recognized as the most vulnerable to storm driven flash floods. In order to limit the damages to the population, there is a need to improve our understanding and the simulation tools for these events. In order to provide information over a whole region, hydrological models applicable at this scale, and able to take into account the spatial variability of rainfall and catchment characteristics, must be proposed. This paper presents such a regional distributed approach applied to the 8-9 September 2002 extreme event which affected the Gard region in the south-east of France. In order to identify the variables and catchment characteristics which require improved knowledge, two distributed hydrological models were set up on a set of catchments, with sizes ranging from 2.5 to 99 km2. The models differ in terms of spatial discretization and process representation. They were forced using radar data with a 1 km2 spatial resolution and 5 min time step. The model parameters were specified using the available information, namely a digital terrain model and a soil data base. The latter provides information about soil texture, soil porosity and soil depths. Soil hydraulic properties were defined using pedo-transfer functions. Data from a post-flood field survey of maximum peak discharge were used to as sess the quality of the simulations. A reasonable agreement between modeled and observed values was obtained. Sensitivity studies were then performed to asses the respective impact of rainfall estimation and soil variability on the simulated discharge. The analysis shows that rainfall remains the first controlling factor of flash flood dynamics and that high resolution spatial and temporal data are required in order to properly simulate peak discharge and flow dynamics for a range of scales. The river bed roughness also influences the peak intensity and time. Soil spatial representation is shown to have a significant role on runoff coefficients and on the spatial variability of saturation dynamics. For some catchments, the impact of soil properties on the simulated discharges was of the same order of magnitude as the impact of the rainfall estimation. The results were very similar for the two distributed models, despite their difference in structure. They show that the poor knowledge of soil properties, mainly soil depth, initial soil water content and saturated hydraulic conductivity is detrimental to robust estimation of discharge. A better knowledge of these variables is therefore recommended. In particular soil depth is required. Post field estimation of peak discharge were very valuable for the regional assessment of the methodology, but must be complemented with data of the whole hydrographs to reduce the uncertainty in flow dynamics and runoff production. Effort towards improved quantitative rainfall estimation using a network of radars must also be continued. The results of the study are used in the design of the future HyMeX experiment, aiming at improving the Mediterranean water balance and the knowledge of extreme events. A strategy based on gauged nested catchments is set up. Detailed measurements of the water balance (discharge, soil moisture, evapotranspiration) are proposed on small catchments of about 1 km2 in order to improve the process understanding. An intermediate scale is defined for catchments of about 100 km2 with distributed hydrometry, based on Large Scale Image Velocimetry to tackle the change of scale problem. Finally, operational data are used at larger scale of about 1000 km2. These data will also be useful to propose improved modelling tools applicable on ungauged catchments. The modelling approach is currently enriched to provide continuous simulations in order to study the sensitivity of the hydrological response to initial conditions. These results will be used to determine where observations of soil moisture offer the best potential for improving our understandin