Water Resources Research · 2019 · 118 citations · 97 references
Natural ResourcesEarth SciencesHydrologyCatchment HydrologyFlood HydrologyHydrologic ModelingFlood ForecastingFlood Inundation ModelingFloodplain HydraulicsFloodplain HydrologyHydraulic ModelingHydrological ModelingCoupled Hydraulic ModelingEvent-based Flood ModelingFlood Inundation DynamicsFlood Inundation Uncertainty AnalysisFlood ModelingHydraulic Flood ModelingHydraulic Modeling For FloodsHydrological Variability
Flood modeling at regional to global scales is essential for emergency and land management, yet coupled hydrological‑hydraulic models—central to forecasting—suffer from uncertainties in 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 coupling Hydrologiska Byråns Vattenbalansavdelning and LISFLOOD‑FP to predict floodplain inundation in the Murray Darling Basin from 2006‑2012, analyzing how discrepancies between simulated and measured flow hydrographs affect inundation patterns across catchment scales. The experiment identified areas needing tailored modeling or data collection, highlighted high sensitivity of inundation volume and extent to flood peak uncertainties, and proposed accurate peak predictions, knowledge of critical morphological features, and event‑based modeling as pragmatic solutions for better large‑scale flood dynamics prediction, especially with low‑accuracy elevation data.
Abstract 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.
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