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Water 2016, 8(4), 147; doi:10.3390/w8040147

The Influence of Statistical Uncertainty in the Hydraulic Boundary Conditions on the Probabilistically Computed High Water Level Frequency Curve in the Rhine Delta

1
Nanjing Hydraulic Research Institute, Nanjing 210029, China
2
State Key Laboratory of Hydrology–Water Resources and Hydraulic Engineering, Nanjing 210098, China
3
Safety and Security Science Group, Faculty of Technology, Policy and Management, Delft University of Technology, Delft 2628 BX, The Netherlands
4
College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China
*
Author to whom correspondence should be addressed.
Academic Editor: Y. Jun Xu
Received: 13 July 2015 / Revised: 15 February 2016 / Accepted: 29 February 2016 / Published: 13 April 2016

Abstract

The hydrodynamic characteristics of a delta or estuary are mainly governed by discharges of rivers and water level at the sea (or lake) boundaries. A joint probability approach is widely applied to quantify the high water level frequency in deltas. In the approach the relevant hydrodynamic loading variables, namely the astronomical tides, the wind induced storm surge and the river flows, are jointly investigated. The joint probability distribution is used to generate a large number of scenarios of boundary conditions which can drive a deterministic model to derive the water levels at locations of interest. The resulting water levels as well as their associated joint probabilities can be inverted to the high water level frequency curve. However, in the joint probability distribution, marginal distributions may contain large statistical uncertainties due to their relevant parameters being estimated from a limited length of data. In the case of the Rhine Delta, a nonparametric bootstrap method is applied to quantify the statistical uncertainties in three critical marginal distributions: wind induced storm surge peak level, wind induced storm surge duration and River Rhine discharge. The uncertainties are incorporated into the marginal distributions with a Monte Carlo integration method. Further the uncertainty-incorporated marginal distributions are used for the high water level frequency assessment. Compared to previous studies, water levels for given return periods are much higher. The uncertainty differs in each marginal distribution and its impact on the high water level frequency curve also varies. View Full-Text
Keywords: statistical uncertainty; the bootstrap method; high water level frequency; Lower Rhine Delta statistical uncertainty; the bootstrap method; high water level frequency; Lower Rhine Delta
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Zhong, H.; van Gelder, P.; Wang, W.; Wang, G.; Liu, Y.; Niu, S. The Influence of Statistical Uncertainty in the Hydraulic Boundary Conditions on the Probabilistically Computed High Water Level Frequency Curve in the Rhine Delta. Water 2016, 8, 147.

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