TY - JOUR
T1 - The influence of statistical uncertainty in the hydraulic boundary conditions on the probabilistically computed highwater level frequency curve in the Rhine Delta
AU - Zhong, Hua
AU - Van Gelder, Pieter
AU - Wang, Wen
AU - Wang, Gaoxu
AU - Liu, Yongzhi
AU - Niu, Shuai
PY - 2016
Y1 - 2016
N2 - 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.
AB - 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.
KW - High water level frequency
KW - Lower Rhine Delta
KW - Statistical uncertainty
KW - The bootstrap method
UR - http://www.scopus.com/inward/record.url?scp=84965133590&partnerID=8YFLogxK
UR - http://resolver.tudelft.nl/uuid:8e3bae84-604f-48d0-9468-f5f543aae588
U2 - 10.3390/w8040147
DO - 10.3390/w8040147
M3 - Article
AN - SCOPUS:84965133590
SN - 2073-4441
VL - 8
JO - Water
JF - Water
IS - 4
M1 - 147
ER -