Abstract:Abstract. Mediterranean catchments are regularly affected by fast and flash floods. Numerous hydrologic models have been developed, and allow modelling of these floods. However, these approaches often concern average-size basins of a few hundred km 2 . At larger scales (> 1000 km 2 ), coupling of hydrologic and hydraulic models appears to be an adapted solution. This study has as its first objective the evaluation of the performances of a coupling of models for flood hydrograph modelling. Secondly, the couplin… Show more
“…Consequently, such a relatively simple coupling strategy might affect model results, but the impacts of dynamic model feedback were assumed negligible when compared to the other sources of nontrivial uncertainty (e.g., the resolution and accuracy of the topographic data). Moreover, the use of dynamic coupling for the modeling of floodplain inundation dynamics at the large scale would require extremely large computational resources that hamper both the feasibility and transferability of the methodology to other study areas (Laganier et al, 2014;Lerat, 2009). Conversely, external unidirectional coupling has been successfully applied in a number of previous analyses (Bravo et al, 2012;Lian et al, 2007;Mejia & Reed, 2011), and it was hence considered a sensible approach for the purposes of this study.…”
Section: Coupled Modeling Approach and Data Analysismentioning
confidence: 99%
“…Instead of using observed rainfall records as model input, Nam et al (2014) used results from a numerical weather prediction model as input to the sequence of models for short-term flood inundation prediction. Laganier et al (2014), Nguyen et al (2016), and Mai and De Smedt (2017) showed that the coupled approach can adequately model flash floods and floodplain inundation. A coupled hydrologichydraulic modeling approach was recommended by Grimaldi et al (2013) for flood hazard modeling, by Felder et al (2017) for probable maximum flood risk estimation, and by Sindhu and Durga (2017) for flood damage mitigation.…”
Flood modeling at the regional to global scale is a key requirement for equitable emergency and land management. Coupled hydrological‐hydraulic models are at the core of flood forecasting and risk assessment models. Nevertheless, each model is subject to uncertainties from different sources (e.g., model structure, parameters, and inputs). Understanding how uncertainties propagate through the modeling cascade is essential to invest in data collection, increase flood modeling accuracy, and comprehensively communicate modeling results to end users. This study used a numerical experiment to quantify the propagation of errors when coupling hydrological and hydraulic models for multiyear flood event modeling in a large basin, with large morphological and hydrological variability. A coupled modeling chain consisting of the hydrological model Hydrologiska Byråns Vattenbalansavdelning and the hydraulic model LISFLOOD‐FP was used for the prediction of floodplain inundation in the Murray Darling Basin (Australia), from 2006 to 2012. The impacts of discrepancies between simulated and measured flow hydrographs on the predicted inundation patterns were analyzed by moving from small upstream catchments to large lowland catchments. The numerical experiment was able to identify areas requiring tailored modeling solutions or data collection. Moreover, this study highlighted the high sensitivity of inundation volume and extent prediction to uncertainties in flood peak values and explored challenges in time‐continuous modeling. Accurate flood peak predictions, knowledge of critical morphological features, and an event‐based modeling approach were outlined as pragmatic solutions for more accurate prediction of large‐scale spatiotemporal patterns of flood dynamics, particularly in the presence of low‐accuracy elevation data.
“…Consequently, such a relatively simple coupling strategy might affect model results, but the impacts of dynamic model feedback were assumed negligible when compared to the other sources of nontrivial uncertainty (e.g., the resolution and accuracy of the topographic data). Moreover, the use of dynamic coupling for the modeling of floodplain inundation dynamics at the large scale would require extremely large computational resources that hamper both the feasibility and transferability of the methodology to other study areas (Laganier et al, 2014;Lerat, 2009). Conversely, external unidirectional coupling has been successfully applied in a number of previous analyses (Bravo et al, 2012;Lian et al, 2007;Mejia & Reed, 2011), and it was hence considered a sensible approach for the purposes of this study.…”
Section: Coupled Modeling Approach and Data Analysismentioning
confidence: 99%
“…Instead of using observed rainfall records as model input, Nam et al (2014) used results from a numerical weather prediction model as input to the sequence of models for short-term flood inundation prediction. Laganier et al (2014), Nguyen et al (2016), and Mai and De Smedt (2017) showed that the coupled approach can adequately model flash floods and floodplain inundation. A coupled hydrologichydraulic modeling approach was recommended by Grimaldi et al (2013) for flood hazard modeling, by Felder et al (2017) for probable maximum flood risk estimation, and by Sindhu and Durga (2017) for flood damage mitigation.…”
Flood modeling at the regional to global scale is a key requirement for equitable emergency and land management. Coupled hydrological‐hydraulic models are at the core of flood forecasting and risk assessment models. Nevertheless, each model is subject to uncertainties from different sources (e.g., model structure, parameters, and inputs). Understanding how uncertainties propagate through the modeling cascade is essential to invest in data collection, increase flood modeling accuracy, and comprehensively communicate modeling results to end users. This study used a numerical experiment to quantify the propagation of errors when coupling hydrological and hydraulic models for multiyear flood event modeling in a large basin, with large morphological and hydrological variability. A coupled modeling chain consisting of the hydrological model Hydrologiska Byråns Vattenbalansavdelning and the hydraulic model LISFLOOD‐FP was used for the prediction of floodplain inundation in the Murray Darling Basin (Australia), from 2006 to 2012. The impacts of discrepancies between simulated and measured flow hydrographs on the predicted inundation patterns were analyzed by moving from small upstream catchments to large lowland catchments. The numerical experiment was able to identify areas requiring tailored modeling solutions or data collection. Moreover, this study highlighted the high sensitivity of inundation volume and extent prediction to uncertainties in flood peak values and explored challenges in time‐continuous modeling. Accurate flood peak predictions, knowledge of critical morphological features, and an event‐based modeling approach were outlined as pragmatic solutions for more accurate prediction of large‐scale spatiotemporal patterns of flood dynamics, particularly in the presence of low‐accuracy elevation data.
“…Douinot et al: Using a multi-hypothesis framework to improve the understanding of flash flood dynamics 1.2 Flash flood events: understanding flow processes Due to the challenges involved in forecasting flash floods, there has been considerable research done on the subject over the last 10 years. Examples include the HYDRATE (Hydrometeorological data resources and technologies for effective flash flood forecasting, 2006Gaume and Borga, 2013), which enabled the setting up of a comprehensive European database of flash flood flash events as well as the development of a reference methodology for the observation of post-flood events, the EXTRAFLO (EXTreme RAinfall andFLOod estimation, 2009-2013;Lang et al, 2014) to estimate extreme precipitation and floods for French catchments, the HYMEX project (HYdrological cycle in the Mediterranean EXperiment, 2010-2020; Drobinski et al, 2014) focusing on the meteorological cycle at the Mediterranean scale and particularly on the conditions that allow extreme events to develop, the FLASH project (Flooded Locations andSimulated Hydrographs, 2012-2017;Gourley et al, 2017) assessing the ability and the improvement of a flash flood forecasting framework in USA on the basis of real-time hydrological modelling with high-resolution forcing, or the FLOOD-SCALE project (Multi-scale hydrometeorological observation and modelling for flash floods understanding and simulation, 2012-2016Braud et al, 2014), based on a multiscale experimental approach to improve the observation of the hydrological processes that lead to flash floods.…”
Abstract. A method of multiple working hypotheses was applied to a range of catchments in the Mediterranean area to analyse different types of possible flow dynamics in soils during flash flood events. The distributed, process-oriented model, MARINE, was used to test several representations of subsurface flows, including flows at depth in fractured bedrock and flows through preferential pathways in macropores. Results showed the contrasting performances of the submitted models, revealing different hydrological behaviours among the catchment set. The benchmark study offered a characterisation of the catchments' reactivity through the description of the hydrograph formation. The quantification of the different flow processes (surface and intra-soil flows) was consistent with the scarce in situ observations, but it remains uncertain as a result of an equifinality issue. The spatial description of the simulated flows over the catchments, made available by the model, enabled the identification of counterbalancing effects between internal flow processes, including the compensation for the water transit time in the hillslopes and in the drainage network. New insights are finally proposed in the form of setting up strategic monitoring and calibration constraints.
“…The next step is to determine whether the discharge term is inflow or outflow fed back to the hydrodynamic model in the next time step. In this method, the current water level of the hydrologic model and hydrodynamic model have been used in velocity calculation at the mutual boundary, It does not consider present flow state (Bravo et al, 2012;Laganier et al, 2014). It is different from BCM using the lateral inflow conditions that velocity provided by hydrologic model will be added to the governing equations of hydrodynamic model directly, not considering present flow state.…”
Abstract. As one of the main natural disasters, flood disaster poses a great threat to township development and property security. Numerous hydrological models and hydrodynamic models have been developed and implemented for flood simulation, risk prediction and inundation assessment. In this study, a dynamic and bidirectional coupled hydrodynamic-hydrologic-hydrodynamic model (DBCM) is developed to predict and evaluate inundation impact in a catchment in mountain area. Based on characteristic theory, the proposed method is able to dynamically adapt and alternate the simulation domain of hydrologic model, and/or hydrodynamic model according to the local flow condition, and a key feature of the proposed model is the dynamic coupling splitting the hydrologic and hydrodynamic simulation domains. The proposed model shows good prediction accuracy and overcomes the shortage existing in previous unidirectional coupling model (UCM). Existing numerical examples and physical experiments were both used to validate the performance of DBCM. Compared to UCM, results from DBCM show good agreements with analytical and measured data which indicates that the proposed model effectively reproduces flood propagation process and accounts for surface flow interaction between non-inundation region and inundation region. Finally, DBCM is applied to predict the flood in the Longxi river basin, and the simulation results show the capability of DBCM in conducting flood event simulation in interested catchment which can support flood risk early warning and future management.
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