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Activity report

MOLINES: Modelação da inundação em estuários. Da avaliação da

perigosidade à gestão crítica

PTDC/AAG-MAA/2811/2012

STORM SURGE MODELLING FOR WATER LEVEL AND INUNDATION

FORECASTING IN TAGUS ESTUARY

Kai Li

February 2015

Funding:

Table of Contents

1 Introduction ............................................................................................................................. 3

1.1 Framework....................................................................................................................... 3

1.2 Objectives ........................................................................................................................ 3

1.3 Structure of this report .................................................................................................... 3

2 Collection and processing of data for validation ..................................................................... 4

2.1 Data used ......................................................................................................................... 4

2.2 Data processing ............................................................................................................... 4

3 Development of the storm surge modelling system ............................................................... 7

3.1 Model assembly ............................................................................................................... 7

3.2 Model improvements and optimization .......................................................................... 8

3.3 Incorporation into the forecasting system ...................................................................... 8

4 Model calibration and validation ............................................................................................ 9

4.1 Wave validation ............................................................................................................... 9

4.2 Elevation validation ......................................................................................................... 9

5 Statistical study of elevation data ......................................................................................... 12

5.1 Elevation series gap identification and complementary ............................................... 12

5.2 Correlation study between surge and elevation gaps ................................................... 12

5.3 Correlation study between surge and river flow........................................................... 13

6 Publications ........................................................................................................................... 14

6.1 Journal papers ............................................................................................................... 14

6.2 Conference papers ........................................................................................................ 14

References ..................................................................................................................................... 15

ACTIVITY REPORT OF THE MOLINES PROJECT: STORM SURGE MODELLING, Kai LI, 2015

1 INTRODUCTION

1.1 Framework

This report describes the work performed by the Research Fellow Kai LI under the research grant of the project MOLINES - Modelação da inundação em estuários. Da avaliação da perigosidade à gestão crítica (PTDC/AAG-MAA/2811/2012), in the National Laboratory of Civil Engineering (LNEC). That activity took place between Jan 6, 2014 and Jan 6, 2015, supervised by Dr. André Fortunato of the Estuaries and Coastal Zones Division (NEC) of the Hydraulics and Environment Department (DHA) of LNEC.

1.2 Objectives

The objectives were:

Assessing and improving the Northeast Atlantic regional model for storm surge.

Collecting, analyzing, comparing and de-noising elevation data of tide gauges in Tagus estuary.

Establish an accurate current-wave coupled modelling system in Tagus for storm surge.

Validating the modeling system of the Tagus estuary for waves and elevations of year 2010 for the following research of 1941, 1996 and 2010 storm surge event.

1.3 Structure of this report

This report is organized into 5 sections beyond this introduction. Sections 2-5 describe the activity carried out and present the main results. Section 6 presents the list of articles and conference abstracts published during the period of 2014.


2 COLLECTION AND PROCESSING OF DATA FOR VALIDATION

2.1 Data used

To establish an all effects included in the storm surge modeling system in Tagus estuary for maximum realistic approach, multiple types of data from different sources were collected. The data used in the activity consists of six main categories: elevation, wave buoy, bathymetry, river flux, wave boundary and atmospheric data. They were used for the purposes of modelling and validation. The data used herein were provided or generated by previous work of Dr. André Fortunato, Dr. Paula Freire, Ms. Ana Rilo, Dr. Xavier Bertin and Dr. Guillaume Dodet with data from the Hawaii Sea Level Center (HSLC) and the British Oceanography Data Center (BODC) for complementary.

Figure 1. Elevation data in Cascais from different sources. Red: Fast delivery data from HSLC. Blue: research quality data from HSLC.

Green: data from local administration. Cyan: data from local administration after digital gauge installation (with high frequencies).

Magenta: data from local administration for year 2010 (with high frequencies).

2.2 Data processing

Some of the elevation data of recent years used in this activity were still in raw form without a complete quality control. Elevation data from different sources were carefully reviewed and compared to select the most reasonable and reliable (Figure 2). The elevation data were also processed with simple quality control and passed by a low-pass filter for study of tidal and surge signals.

River flux data of Almourol station were used in the activity. These data have different time steps in different periods and many gaps. The gaps were filled smoothly with climatology.


Figure 2. Predicted tide in Cascais in 2010-02-28. Red: predicted tide computed from research quality data of HSLC in previous years.

Blue: predicted tide computed from the tide gauge in Cascais. Green: predicted tide computed from fast delivery data of HSLC.

Atmospheric data were compared with observation to assess errors come from the atmospheric data (Figure 3 and Figure 4). NCEP and ECWMF reanalyses datasets were used in this activity.

Figure 3. Atmospheric pressures of mean sea level in station Geofísico. Red: pressure from observation. Blue: pressure from ECMWF

ERA20C dataset.


Figure 4. Wind magnitudes in station Geofísico. Red: wind magnitude from observation. Blue: wind magnitude from ECMWF ERA20C

dataset.


3 DEVELOPMENT OF THE STORM SURGE MODELLING SYSTEM

3.1 Model assembly

Within this activity, the model SCHISM/WWM was used in the simulation. SCHISM is a successor of SELFE (Zhang and Baptista, 2008). It is a semi-implicit finite element shallow water model, which targets cross-scale applications. SCHISM includes WWM as a module for spectral wave couplings (Roland et al., 2012).

The modelling work of this activity was composed of two essential parts: the regional model and the model of Tagus estuary (Figure 5). The unstructured triangular meshes were based on previous work and received numerous improvements in aspects of bathymetry, coastline fit and potential flooding area coverage particularly in the coastal region (Figure 6). Multiple sources of bathymetric data and interbath program of Dr. Andre Fortunato were used in the bathymetry input for both the regional and the Tagus estuary mesh as our best bathymetry knowledge in practice.

The regional model was computed with SCHISM only for 31 years (1980-2010). It was forced with atmospheric forcing from NCEP reanalysis, tidal potential from 11 constituents (SSA, MM, Mf, O1, K1, P1, Q1, M2, S2, N2, K2) and tidal elevations from 17 constituents at open boundaries (O1, K1, P1, Q1, M2, S2, N2, K2, 2N2, Mu2, Nu2, L2, M3, M4, MS4, MN4, M6) and Z0. The Tagus estuary model was computed with SCHISM and WWM III in full coupled mode for the 3 storm surge events in 1941, 1996 and 2010. It was forced with the same atmospheric forcing dataset with the regional model except 1941 (ECMWF reanalysis). The Tagus estuary model was fed with river flux and forced with elevation from the regional model and waves from a previous study with Wavewatch III in the ocean boundary. It also took advantage of bottom natural dependent manning coefficient.

Figure 5. Finite element mesh and bathymetry for regional model


Figure 6. Old and new meshes superimposed with satellite images near Cascais and Costa da Caparica: yellow: old mesh, red:

improved mesh

3.2 Model improvements and optimization

In this activity, the WWM model used was bumped to the newly developed WWM version 3 to take advantage of latest research results from WWM development, especially the improvement in computation speed. As SCHISM/WWM is a fast evolving modelling system, it may have compatibility issues depending on different computation environments, especially the latest version. The modelling system got various minor adjustment (some of them were essential) for the environment in LNEC.

The modelling system passed numerous sensitivity tests to get a balance between speed and accuracy. The good computational performance was very helpful for the following research and the implementation in forecasting system.

3.3 Incorporation into the forecasting system

As this modelling system will be used in a forecasting system, much knowledge can be shared with the other modelling system which uses SELFE or SCHISM. The modelling system got an opportunity of incorporation with the forecasting system in advance from the project of lagoon Aveiro. Cooperation with the other colleagues showed that the version used in the activity can be incorporated well into the forecasting system.


4 MODEL CALIBRATION AND VALIDATION

For this activity a set of flexible and well architected validation programs written in pure Python was developed. This enables the ability of validation the computation and comparison of different configurations for calibration on time.

Figure 7. Location of wave stations and tide gauges

4.1 Wave validation

The wave data used in this activity ranged from October 2010 to December 2013 with gaps. The period from November 2010 to December 2010 was chosen for validation. Validation results showed that WWM captured the waves very well.

4.2 Elevation validation

Elevation validation of regional model was based on statistical computation (Figure 8 and Figure 9) for the period from January 2010 to May 2010. The regional model predicted the elevation very well near Tagus estuary with a normalized error variance less than 1%. It also captured well the elevation peaks near Tagus estuary. This provided a change of accurate computation in the Tagus estuary model. Due to coarse grid resolution and lack of bathymetry data in the northern part of the regional domain, the error increased in other stations in the north. This was not an issue as they were out of the area of interest.


Figure 8. Normalized Error Variance for the elevation result of regional model

Figure 9. Peak Error of the elevation of regional model. Stem error range. Blue dot: error average.

For the Tagus estuary model the elevation results improved with wave coupled, in the complex situation of Xynthia period, the maximum peak under prediction reached 10 cm. This still need further work to improve it. In the tide gauge station of Seixal and VTS, due to the poor quality of elevation data and uncertainty of the reference level relation, the validation failed to get a trustable result.


Figure 10. Elevation validation of Tagus estuary model in Cascais.


5 STATISTICAL STUDY OF ELEVATION DATA

5.1 Elevation series gap identification and complementary

The observed elevation time series usually contain gaps (Figure 11). These gaps may have their own statistical features which can be further studied, but gaps can prevent accurate statistical studies based on the whole time series. Gap identification and complementary methods were developed in this activity. In this study, gaps can be identified from elevation series from a single source with uniform time steps. Any data records with larger time steps are identified as gaps. The properties of the gaps were collected for further study, especially the beginning time of the gaps which is corresponding to the equipment failure of tide gauges may due to extreme weather conditions. With the assistance of modelling work of this activity, gaps of elevation data were filled with predicted elevation from model. This provided a well-distributed elevation data in time domain for statistical study.

Figure 11. Gaps of elevation time series of Cascais between 1960 and 2003. The length of the red line indicate the length of the gaps

5.2 Correlation study between surge and elevation gaps

The correlation between elevation gaps and surge in Cascais was studied. The gaps are classified by the modelled surge value in the beginning of the gaps. A PDF graph (Figure 13) showed that elevation data gaps occur more frequently during extreme events.


Figure 13. Fraction of the beginning of data gaps in the Cascais for different ranges of low frequency surges. The surges were

obtained by filtering the results of water elevations obtained with the regional model described below with a Demerliac filter to

remove daily and higher frequencies. Results suggest that data gaps occur more frequently during extreme events.

5.3 Correlation study between surge and river flow

Correlation between surge and river flow was studied in this activity. The correlation between low frequency part of surge signal and river flux was calculated monthly (Figure 12). The high positive correlations in winter indicate the surges usually occur with higher river flow. The negative correlations in summer can be explained by the frequent river dam open event in summer.

Figure 22. Monthly correlation between the surge signal at Cascais (located in the Tagus estuary mouth) and the Tagus River flow iat

the Almourol station. Tidal and other high frequency signals were removed with a Demerliac filter from both (modeled) water levels

and (measured) river flows. The positive correlations in the winter indicate that high river flows and storm surges tend to occur

simultaneously.


6 PUBLICATIONS

6.1 Journal papers

Andre B. Fortunato, Kai Li, Xavier Bertin, Marta rodrigues, Belen Martin Miguez, Determining extreme sea levels along the Iberian Atlantic coast, submitted to Ocean Engineering

6.2 Conference papers

Fortunato, A.B., K. Li, X. Bertin, and M. Rodrigues. Determination of Extreme Sea Levels along the Portuguese Coast, 3as Jornadas de Engenharia Hidrográfica, 2014.

Rilo, A., A. Fortunato, P. Freire, K. Li, and A. Tavares. Suscetibilidade à Inundação de Margens Estuarinas. Aplicação à Baía Do Seixal (estuário Do Tejo, Portugal), 3as Jornadas de Engenharia Hidrográfica, 2014.

Guangzhou, February 2015

_________________________

Kai Li


REFERENCES

Zhang, Y.-L., Baptista, A.M., 2008. SELFE: A semi-implicit Eulerian-Lagrangian finite-element

model for cross-scale ocean circulation. Ocean Modelling, 21/3-4: 71-96.

Roland, A., Zhang, Y.J., Wang, H.V., Meng, Y., Teng, Y.-C., Maderich, V., Brovchenko, I., Dutour-

Sikiric, M. and Zanke, U. (2012). A fully coupled 3D wave-current interaction model on

unstructured grids, Journal of Geophysical Research, 117, C00J33, DOI:

10.1029/2012JC007952.

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