A continuous simulation approach for the estimation of extreme flood inundation in coastal river reaches affected by meso- and macrotides

Considering the joint probability of occurrence of high sea levels and river discharges, as well as the interactions between these sources of flooding, is of major importance to produce realistic inundation maps in river reaches affected by the sea level. In this paper, we propose a continuous simulation method for the estimation of extreme inundation in coastal river reaches. The methodology combines the generation of synthetic long-term daily time series of river discharge and sea level, the downscaling of daily values to a time resolution of a few minutes, the computation of inundation levels with an unsteady high-resolution two-dimensional model and the use of interpolation techniques to reconstruct long-term time series of water surface from a limited number of characteristic cases. The method is especially suitable for small catchments with times of concentration of a few hours, since it considers the intradiurnal variation of river discharge and sea level. The methodology was applied to the coastal town of Betanzos (NW of Spain), located at a river confluence strongly affected by the sea level. Depending on the return period and on the control point considered, the results obtained with the proposed methodology show differences up to 50 cm when compared with the standard methodology used in this region for the elaboration of flood hazard maps in accordance with the requirements of the European Directives. These results indicate the need for adaption of the standard methodology in order to produce more realistic results and a more efficient evaluation of flood hazard mitigation measures.

[1]  T. Webster,et al.  Integrated River and Coastal Hydrodynamic Flood Risk Mapping of the LaHave River Estuary and Town of Bridgewater, Nova Scotia, Canada , 2014 .

[2]  P. Camus,et al.  A hybrid efficient method to downscale wave climate to coastal areas , 2011 .

[3]  Cecilia Svensson,et al.  Dependence between extreme sea surge, river flow and precipitation in eastern Britain , 2002 .

[4]  Jerónimo Puertas,et al.  Iber: herramienta de simulación numérica del flujo en ríos , 2014 .

[5]  Luis Cea,et al.  Modelización numérica de inundaciones fluviales , 2014 .

[6]  L. Cea,et al.  Bathymetric error estimation for the calibration and validation of estuarine hydrodynamic models , 2012 .

[7]  B. Gouldby,et al.  A simulation method for flood risk variables , 2007 .

[8]  M. Acreman Assessing the Joint Probability of Fluvial and Tidal Floods in the River Roding , 1994 .

[9]  G. H. Yu,et al.  A distribution free plotting position , 2001 .

[10]  L. A. Stone,et al.  Computer Aided Design of Experiments , 1969 .

[11]  A. Díez-Herrero,et al.  Quantification of flash flood economic risk using ultra-detailed stage–damage functions and 2-D hydraulic models , 2016 .

[12]  M. Larson,et al.  Implications of extreme waves and water levels in the southern Baltic Sea , 2008 .

[13]  B. Gouldby,et al.  Statistical simulation of flood variables: incorporating short‐term sequencing , 2008 .

[14]  Jean-Antoine Désidéri,et al.  Upwind schemes for the two-dimensional shallow water equations with variable depth using unstructured meshes , 1998 .

[15]  L. Hamm,et al.  An event-based approach for extreme joint probabilities of waves and sea levels , 2017 .

[16]  Voukouvalas Evangelos,et al.  Joint Probabilities of Storm Surge, Significant Wave Height and River Discharge Components of Coastal Flooding Events. Utilising statistical dependence methodologies & techniques. , 2016 .

[17]  Luis Cea,et al.  A simple and efficient unstructured finite volume scheme for solving the shallow water equations in overland flow applications , 2015 .

[18]  R. Franke Scattered data interpolation: tests of some methods , 1982 .

[19]  Peter Hawkes,et al.  Joint probability analysis for estimation of extremes , 2008 .

[20]  M. C. Davies,et al.  A morphogenic approach to world shorelines , 1964 .

[21]  Mohammad Taghi Dastorani,et al.  Application of ANN and ANFIS models on dryland precipitation prediction (case study: Yazd in Central Iran). , 2010 .

[23]  P. V. Overloop,et al.  A joint probability approach using a 1-D hydrodynamic model for estimating high water level frequencies in the Lower Rhine Delta , 2013 .

[24]  A. Casadio,et al.  Development of flood probability charts for urban drainage network in coastal areas through a simplified joint assessment approach , 2011 .

[25]  Nicholas J. Garrity,et al.  Evaluation of event and response approaches to estimate the 100-year coastal flood for pacific coast sheltered waters , 2007 .

[26]  Paula Camus,et al.  Analysis of clustering and selection algorithms for the study of multivariate wave climate , 2011 .

[27]  Andrés Díez-Herrero,et al.  Improvement of resilience of urban areas by integrating social perception in flash-flood risk management , 2016 .

[28]  Jerónimo Puertas,et al.  Validation of a 1D-2D dual drainage model under unsteady part-full and surcharged sewer conditions , 2017 .

[29]  Ben Gouldby,et al.  The joint probability of waves and water levels in coastal engineering design , 2002 .

[30]  Philip L. Roe,et al.  Discrete models for the numerical analysis of time-dependent multidimensional gas dynamics , 1986 .

[31]  J. L. Ayuso,et al.  Testing the relationship between instantaneous peak flow and mean daily flow in a Mediterranean Area Southeast Spain , 2008 .

[32]  Jerónimo Puertas,et al.  Global Sensitivity and GLUE-Based Uncertainty Analysis of a 2D-1D Dual Urban Drainage Model , 2016 .

[33]  Paula Camus,et al.  A global classification of coastal flood hazard climates associated with large-scale oceanographic forcing , 2017, Scientific Reports.

[34]  J. Vrijling,et al.  JOINT PROBABILITY DISTRIBUTIONS FOR WAVE HEIGHT, WIND SETUP AND WIND SPEED , 2005 .

[35]  P. Duarte,et al.  A modeling study on the hydrodynamics of a coastal embayment occupied by mussel farms (Ria de Ares-Betanzos, NW Iberian Peninsula) , 2014 .