2014 mike by dhi uk symposium user group meeting - presentations and papers - 13 may 2014

2014 MIKE BY DHI UK SYMPOSIUM
COOMBE ABBEY HOTEL, WARWICKSHIRE, UK
13 MAY 2014
16TH ANNUAL MIKE BY DHI UK USER GROUP MEETING
PRESENTATIONS & PAPERS

CONTENTS
1. INTRODUCTION
ERLAND RASMUSSEN (EXECUTIVE VICE PRESIDENT, MIKE BY DHI)
2. RELEASE 2014 NEWS & VIEWS IN THE MARINE AREA
POUL KRONBORG (BUSINESS AREA MANAGER, COAST AND SEA, MIKE BY DHI)
3. RELEASE 2014 NEWS & VIEWS IN THE URBAN, WATER RESOURCES AND GROUNDWATER AREAS
TORBEN S. JENSEN (BUSINESS AREA MANAGER, WATER RESOURCES, MIKE BY DHI)
4. MODELLING EXTREME WATER LEVELS IN THE SWAN AND CANNING RIVERS, PERTH, WA
ALAN FORSTER (URS)
5. CATCHMENT FLOOD RISK ASSESSMENT AND MANAGEMENT (CFRAM) STUDIES IN IRELAND
STEPHEN PATTERSON (RPS)
6. USING MIKE 21 FOR THE ESTIMATION OF JAPAN TYPHOON RISK
JUERGEN GRIESER (RMS)
7. DEVELOPING USEFUL ESTUARINE SEDIMENT TRANSPORT MODELS: IMPROVING MODEL OUTPUTS BY
IMPROVING MODEL INPUTS
KEVIN BLACK (PARTRAC)
8. REAL TIME FLOOD FORECASTING IN THE ENVIRONMENT AGENCY
CLIFFORD WILLIAMS (ENVIRONMENT AGENCY)
9. FROM HAZARD TO IMPACT: THE CORFU FLOOD DAMAGE ASSESSMENT TOOL
ALBERT CHEN (UNIVERSITY OF EXETER)
10. JUST HOW SEVERE WAS THE 2013/14 WINTER AND HOW DID THE MET OFFICE WAVE MODEL PERFORM?
ADAM LEONARD-WILLIAMS (MET OFFICE)
11. INTEGRATED CATCHMENT AND ESTUARY MODELLING
ANN SAUNDERS (INTERTEK)
12. RIVERINE WATER QUALITY MODELLING, WITH FOCUS ON NUTRIENTS USING MIKE 11 ECO LAB
VERA JONES (ATKINS)
13. TEACHING WITH MIKE BY DHI
BJÖRN ELSÄßER (QUEEN’S UNIVERSITY BELFAST)

INTRODUCTION
ERLAND RASMUSSEN (DHI)

© DHI
The Start of the MIKE by DHI Era
MOUSE

© DHI
Solutions
MIKE by DHI
MIKE CUSTOMISED by DHI
THE ACADEMY by DHI
We make our knowledge globally accessible
Through our local teams and unique software
The Future

RELEASE 2014 NEWS & VIEWS IN THE
MARINE AREA
POUL KRONBORG (DHI)

Marine News and Views
in version 2014
© DHI #1
Poul Kronborg
Business Area Manager, Coast & Sea
MIKE by DHI

Agenda
© DHI
• Performance improvements: Use of GPU’s
• Scour Calculation Tool
• New source feature (Near-field integration)
• New dike features (overtopping)
• MIKE Animator enhancements (solids and particle visualization)
• Mesh Generation improvements
• Software Development Kit
• De-commissioning of MIKE 21 NSW and the old PA/SA-module
• Introducing online WaterData
Marine MIKE software: New developments in version 2014

Performance Improvements 1: A short history
• OpenMP parallelization:
• Release 2005: MIKE 21 SW
• Release 2008: MIKE 21 FM
MIKE 3 FM
• Release 2009: MIKE 21 BW
MIKE 21 ‘Classic’
MIKE 3 ‘ Classic’
6 December, 2012© DHI #3
• MPI parallelization:
MIKE 21 FM
MIKE 3 FM
• Porting of engines to Linux:
MIKE 21 FM
MIKE 3 FM
And now in version 2014: Use of GPU’s

Performance Improvements 2: Use of GPU’s
© DHI
Use of Graphical Processor Unit’s
(GPU’s) in MIKE 21 HD FM
• MPI-parallelization is undertaken by utilising the
calculation power of the GPU
• Data transfer between the GPU and the CPU is
automatic, a standard input file is used
• In version 2014 only the HD-module can use this
facility, but also the HD-part of simulations with
more modules involved (e.g. HD+AD) will use it.
Add-on modules are parallelized with a shared
memory approach, OpenMP
• The speed-up of the HD-simulation will be very
significant (test results show a speed-up factor of
up to 110)
Test example, HD Speed up factor

Performance Improvements 3: Launch
The GPU-card is activated by the user
when launching a simulation:

Scour Calculator
© DHI
This new productivity tool facilitates evaluations of scour-risk
around a mono-pile for MIKE 21 users.
The implementation in version 2014 is the first step of this
development:
• Version 2014: Based on known scour formulae
• Following version: Based on tables of development
rates, derived from CFD experiments

Scour Calculator
Illustration of
calculated scour hole
development

Scour Calculator

First step in integrated near-field/far-field simulation: New source
feature
© DHI
As the first step in integrated near-field/far-field simulation, a new
jet source has been added to the list of source types.
When this type is selected a steady jet is calculated and the vertical
position of the source position becomes dynamic.
The method outlined by Jirka (2004) is used.

First step in integrated near-field/far-field simulation: New source
feature

New dikestructure features: overtopping
© DHI
The dike structure was introduced in MIKE 21 and MIKE 3
FM in version 2012:
• Simulate dikes, embankments, flow obstructions
• Defines local features not resolved in bathymetry
• Location defined by geo-referenced polyline
• Geometry can vary in time and space
• Flow over Dikes calculated by Weir equation
New: The dike structure has now also been introduced in
MIKE 21 ‘Classic’.
Dike Structure
Dikes structure definition: MIKE 21 FM

New dikestructure features: overtopping
© DHI #12
As an enhancement of the dike structure introduced in
release 2012, two additional types of dike discharge have
been implemented in the FM versions:
• Specify the overtopping discharge
• Calculate the overtopping discharge from a user-
specified table
This gives a range of possibilities for including
overtopping in the modelling

MIKE Animator enhancements
© DHI
With version 2012 we launched a completely re-engineered version
of MIKE Animator, with a number of new facilities, for example
efficient handling of MIKE 3-files. New enhancements are:
• Inclusion of solids (for example buildings, ships or other floating
objects).
• Support for particles (Particle Tracking module and ABM-module)
• Support for MIKE SHE result-files

Example: MIKE Animator enhancements

Improved mesh-generation facilities
© DHI
From version 2014 the complete MIKE Zero interface will support
64 bits. Amongst other improvements, this will influence the
generation of meshes:
• Fully 64 bit mesh generator process
• No software-based size limitations, both with respect to number
of mesh-elements and number of scatter points
And further:
• New tool for creating Flexible Meshes from gridded meshes
• Import facilities calculation meshes from ADCIRC/SMS/Tuflow

Improved mesh-generation

Software Development Kit
© DHI
• The Software Development Kit (SDK) makes it possible to create
or modify MbD-files outside MbD’s editors and tools.
• A 2012-version already exist that makes it possible to read, write
and edit DFS-files (for example output-files) from any .NET
environment (for example C# or IronPython)
• Version 2014 of the SDK will make it possible to access PFS-
files

De-commmisioning and a name change
© DHI
• MIKE 21 NSW will be de-commisioned from version 2014, given
that it has been replaced completely by MIKE 21 SW.
• The old PA/SA-modules is completely replaced in functionality
by the PT (Particle Tracking) module and the new oil spill
module, MIKE 21 SA and MIKE 3 SA, that have been introduced
during the latest releases. The PA/SA-modules will therefore be
de-commissioned.
• In order to avoid frequent misunderstandings we will rename the
SA-modules (MIKE 21 SA and MIKE 3 SA) to OS, standing for
Oil Spill. The new names will be MIKE 21 OS and MIKE 3 OS.

Introducing: waterdata.dhigroup.com
• Easy data access is one of the keys to fast and safe project execution
• We have worked with easy data access before, f.ex with the inclusion of Global Tidal data and with
MIKE C-Map
• We now introduce DHI’s new data portal (at waterdata.dhigroup.com), where a large quantity of
relevant data can be found.
• Easy data access is one of the keys to fast and safe
project execution
• We have worked with easy data access before, f.ex
with the inclusion of Global Tidal data,MIKE C-Map
and Global Circulation Models (Climate Change)
• We now introduce DHI’s new data portal (at
waterdata.dhigroup.com), where a large quantity of
relevant data can be found.

• For MIKE users, version 2014 includes a DHI
WaterData Client that assist the user with
identification and download of relevant data
• MIKE users will also have free or discounted access
to data

• Examples of data that can be found on the portal:
• Global Wave Data from DHI based on CFRS 1979-2012
• Global Wind Data (CFSR) 1979-2012
• PERGOS Middle East Gulf Hindcast Database
• South China Sea Waves
• CCMP Cross-Calibrated, Multi-Platform Ocean Wind Velocity Product
• Aquarius Monthly Sea Surface Salinity
• MODIS Monthly Sea Surface Temperature
• .....and more is coming

Marine MIKE software: New developments in version 2014
© DHI
Resuming:
• Performance improvements: Use of GPU’s
• Scour Calculation Tool
• New source feature (Near-field integration)
• New dike features (overtopping)
• MIKE Animator enhancements (solids and particle visualization)
• Mesh Generation improvements
• Software Development Kit
• De-commissioning of MIKE 21 NSW and the old PA/SA-module
• DHI Data Portal

Thank you
Sign up for our newsletter (available in English, Spanish and Potuguese) at www.mikebydhi.com

RELEASE 2014 NEWS & VIEWS IN THE URBAN,
WATER RESOURCES AND GROUNDWATER AREAS
TORBEN S. JENSEN (DHI)

2014 MIKE by DHI UK Symposium
Release 2014 News and views
Urban and Water resources SW
Torben S. Jensen
Business Area Manager, Water Resources

WEST
Wastewater treatment is essential to control the environmental impacts
of human behavior.
Continuously changing flow and composition makes it challenging
to meet the severe discharge limits.
Modelling and simulation of
Waste Water Treatment Plants

MIKE URBAN
Water distribution
Water distribution modeling under steady state,
extended period and water hammer flow conditions
including water quality and real-time control
Collection system
Waste water and storm water simulations with rainfall-runoff,
pollution transport and sediment transport including
advanced real-time control
© DHI #4
Release 2014

MIKE URBAN developments – Recent releases
• ArcGIS 10.1 (ESRI)
• Usability tools
• Plotting and reporting
• Optimization
 Engine
 GUI:
 Open editors with 200.000 pipes in 3-4 seconds
 Faster refresh of map
© DHI #5
Handling of 200.000 pipes

Roadmap for the next major releases
© DHI #6

MIKE URBAN – specific application areas
URBAN FLOODING
• Specialised Urban Component in a True Integrated Flood modelling package
MIKE FLOOD, fully dynamic coupling:
RIVER – URBAN – OVERLAND
PIPE SYSTEM - GROUNDWATER INTERACTION (Leakage etc)
• Unique combination of pipe flow model and Groundwater/Catchment model
MIKE URBAN – MIKE SHE
© DHI #7

MIKE Zero
© DHI #9
MIKE Zero – a 64-bit application!
• GUI Editors and Tools are all now 64-bit applications
• Simulation Engines already made 64-bit applications in previous releases
• Overcomes previous Windows OS restriction on memory allocation
• Allows to utilize large amount of data:
• E.g. large scatter data set for Flexible Mesh generation

MIKE 21 FM GPU
© DHI #10
The fastest MIKE 21 ever!
• MIKE 21 can now utilize GPU for simulations (Graphical Processing Unit)
• GPU option is available for MIKE 21 FM HD and MIKE FLOOD FM HD
• GPU option allows coupled simulations in MIKE FLOOD (1D + 2D GPU)
• Speed-up factors are impressive!
• The speed-up factor depends on the model setup.
• Larger models with less flood-and-dry tend to scale better
• The MIKE 21 GPU is linkable
• Behaves like MIKE 21 FM HD as part of MIKE FLOOD and linked with other M21-modules
• Your PC needs to be equipped with a top-end NVIDIA graphics card (priced around US$ 1,000)

MIKE HYDRO
The common framework for Water Resources products
© DHI #11

MIKE HYDRO
© DHI #12
Release 2014 includes:
• MIKE HYDRO Basin
• Feature complete package for River Basin
water resources management projects
• Full-featured successor of MIKE BASIN in Release 2014
• MIKE HYDRO River,
• River modelling with MIKE HYDRO
• First release of successor to ‘classic’ MIKE 11 GUI
• Phase I: Subset of ‘classic’ MIKE 11 GUI features

MIKE HYDRO Basin
© DHI #13
In summary:
• Map-centric, New and Intuitive Graphical User Interface
• Robust & stable MIKE BASIN engine
• New features added (WQ / ECO Lab, Global Ranking)
• Including rainfall runoff models
• Tailored simulations through macro/programming access to engine (COM/.Net interface)
• Replaces MIKE BASIN entirely with Release 2014!
• Targeting River Basin Management and Planning

Rivers and Flooding
© DHI #14
MIKE HYDRO River: First release of River module in MIKE HYDRO
Phase I of River module developments:
A. Subset of MIKE 11 functionality included:
• Hydrodynamic modelling
• GUI-Features from Network, Simulation and HD Parameter Editors ported to MIKE HYDRO
B. MIKE HYDRO River <-> MIKE 11 Classic setup converter
• Import existing MIKE 11 models into MIKE HYDRO River
• Export MIKE HYDRO River model to MIKE 11 ‘Classic’ setup files

Rivers and Flooding
© DHI #15
Looking ahead:
Phase II of MIKE HYDRO River :
• Phase II targeted our next major release
• Full-featured replacement of MIKE 11 ‘Classic’ GUI
• Supplementing Release 2014:
• Additional features
• MIKE 11 Add-on modules

Rivers and Flooding
MIKE 11 GIS functionality in MIKE HYDRO River
Features:
• Loading of DEM (ascii-grid file or dfs2 file).
• River tracing and Catchment delineation tool
• Generate Cross-sections from DEM
• Cross sections from survey points
• Use alignment lines (shapefiles) to :
• Trim or Extend existing cross sections
• Set markers from alignment lines (Marker 1 and 3)
Trim sections
in tributary
Alignment lines

Rivers and Flooding
© DHI #17
MIKE FLOOD: Graphical Editing of lateral Links in Couple editor
New in MIKE FLOOD Couple editor:
• Graphical Editing of links (new toolbar)
• Editing of existing, lateral links
• Editing available for links in both Classic and FM
x

Rivers and Flooding
© DHI #18
MIKE FLOOD: Dikes structure option in all 2D Overland flow models
Dikes structures now available in all MIKE 21 engines:
• MIKE 21 FM (Flexible Mesh, Release in version 2012)
• MIKE 21 ‘Classic’ (Rectilinear grid) NEW!
• MIKE 21 C (Curvelinear grid) NEW!
Dike Structure
Dike structures:
• Simulate dikes, embankments, flow obstructions
• Defines local features not resolved in bathymetry
• Location defined by geo-referenced polyline
• Geometry can vary in time and space
• Flow over Dikes calculated by Weir equation
Dikes structure definition: MIKE 21 FM

Rivers and Flooding
© DHI #19
MIKE FLOOD FM: Mesh conversion tool (MIKE Zero toolbox)
• Seamless Grid to Mesh conversion (.dfs2 to .mesh quadrangular)
• Converts dfs2 and external formats
Easy transformation from MIKE FLOOD ‘Classic’ to FM!
dfs2-file Mesh-file

MIKE FLOOD – 2D FM modelling
Christchurch M21-model
 4.2 million elements
 Squared elements (10mx10m)
 Rainfall event of 21 hour duration
Single, central peak representing 100
year design storm
 FM-GPU simulation
• Double precision
• First order scheme
• Sim-time = 3.5 hour (approx)
• 3-4 times faster than 16-core GPU

Additional details and Q/A
© DHI #21
Join the training session tomorrow:
• Focus on Flood modelling
• Productivity tools
• 3-way coupling
• MIKE HYDRO River
• …
• …
• …

Rivers and Flooding
© DHI #23
MIKE HYDRO River – The Graphical User Interface:
River model
toolbar icons
Cross
sections plot
Graphical
River Network
editor
Structures
plot
River model
tree view items

MODELLING EXTREME WATER LEVELS IN THE
SWAN AND CANNING RIVERS, PERTH, WA
ALAN FORSTER (URS)

Presentation Title
Assessment of Swan and Canning River Tidal and Storm Surge
Water Levels
13 May 2014
Acknowledgements
Australian Government Funding
Commonwealth: Natural Disaster Resilience Program
State: Department of Water
Data Sources
WA Department of Transport: Coastal Data Centre
WA Department of Water
URS Perth
Hydraulic Modelling Team

Swan and Canning Rivers Tidal and Storm Surge Water Levels
2
Outline
1. Objective
2. Background
3. The Solution
4. Results
5. Challenges

3
1. Objective
•Provide quantitative information that the Department of Water could use
to provide planning policy advice with respect to future flood levels in
the Swan and Canning River System.
•Achieved through a strategic level study of the Swan and Canning Rivers
to understand the role of:
-River flows
-Marine surges
-Wind and
-Sea level rise
-On the water level in the
river system

4
2. Background: Location
Darlingscarp‘Thehills’
Fremantle
Swan River
Canning River
Perth CBD

5
Mill Point 1926

6

7

8
Photographs from Brearly, 2005, “Ernest Hodgkin’s Swanland:
Estuaries and Lagoons of South-western Australia”, UWA Press.

9
2. Background: Water Level Forcing
Meadow Street
Existing tidal limit

3. The Solution: MIKE21HD(FM)
10
MeadowStreet
BarrackStreet
Fremantle

3. The Solution: MIKE 21HD (FM)
11
Meadow Street
Barrack Street
Fremantle

12
3. The Solution: MIKE21 SW and Overtopping Analysis

3. The Solution: MIKE21 SW and Overtopping Analysis
13
(72 km/hr)

4. Results: Flood Maps
14

4. Results: Maximum Speed
15

4. Results: Long Sections
16

17
4. Results: Wave overtopping
Overtopping Rates (litres / sec / m)

5. Challenges: Client’s Brief and Expectations
•Client requested
- Wave setup
•Client Assembled ‘all’ input data
- Water level and flow (hydrology) data
- Bathymetry data
• LiDAR
• Bathymetric surveys
• River cross-sections (1980’s)
- No allowance for additional survey works
- Aerial photographs
18

5. Challenges: Bathymetry
•Highly vegetated river valleys with no cross-section or reliable LiDAR
data
•Very shallow (<0.2m) difficult to distinguish a ‘main’ channel
19

5. Challenges: Bathymetry
•Datum not consistent-despite assurances
•Not all data sets had been reduced to AHD (despite assurances to the
contrary)
•Cross-sections were from 1980’s and excluded more recent land
development
•Cross-sections were sparse and missed bed features such as banks
and paleo-channels
•Bathymetric survey only covered narrow navigable channel in middle
reaches of the rivers
•Priority areas and breaklines in mesh generator cannot be used
together
20

5. Challenges: Hydrology
21

5. Challenges: Calibration
22

5. Challenges: Calibration
23

5. Challenges: Development
•Attempt 1: MIKE Flood
- Coupled model u/s of Meadow Street/MIKE21HD d/s
- Calibrated for all but high fluvial flow
- Unstable along coupling for rising flows
•Attempt 2: MIKE11 linked to MIKE21 HD(FM)
- Very poor calibration at Meadow Street for high fluvial flow
- Unsure if the model would reproduce tidal limit for sea level rise
scenarios
•Attempt 3: MIKE 21 HD (FM)
- Model A: Quadrangular mesh for channel
- Model B: Triangular mesh for channel
• Stable throughout model
• Best overall calibration
24

6. Conclusion
•Project was a success for the DoW
•MIKE21HD (FM) model delivered to the DoW
•Issues with bathymetry highlighted and overcome
•Established hydrology challenged and up for review
•Identified:
- River flooding the largest risk but
- Sea level rise will have significant impact on long-
term development
25

Questions?
26

CATCHMENT FLOOD RISK ASSESSMENT AND
MANAGEMENT (CFRAM) STUDIES IN IRELAND

Catchment Flood Risk Assessment &
Management (CFRAM) Studies in Ireland
MIKE by DHI UK User Group Meeting
13th May 2014
Stephen Patterson
Associate ‐ RPS

Overview
• Background to CFRAMS
• RPS Involvement
• MIKE
– Fluvial & Coastal
– Hydrology
• Problems & Solutions
• Current Status & Programme

CFRAMS Context
• Development from
EU Floods Directive
and National Flood
Policy Review
• Series of studies to
cover RoI – 6
CFRAM Studies
across 7 River Basin
Districts (Ireland is
divided into 8 River
Basin Districts)
North Western
Neagh Bann
Eastern
South
Eastern

CFRAMS Objectives
• Complete a Preliminary Flood Risk Assessment
• Identify, assess and map the existing and potential future flood
hazard and risk within the Study Area
• Identify viable structural and non-structural options and measures
for flood risk management
• Prepare a set of Flood Risk Management Plans (FRMP) for the
Study Area

Model Extents
• AFA: Area for Further Assessment
• Level of detail:
• Detailed assessment for High Priority
Watercourses (HPW)
• Broad scale for Medium Priority Watercourses
(MPW)
CFRAMS Area HPW (km) MPW (km) Totals (km) No. Of AFA's
East 44 611.1 192.3 803.4
South East 38 501 427 928
NWNB 39 394.9 290.8 685.7
TOTAL 121 1507 910.1 2417.1
East
South East
North West
Neagh Bann

Fluvial & Coastal Models - Overview
• Model Conceptualisation
– Mostly 1 AFA per model
• Choice of software
– MIKE plus ICM and ISIS
• Version of Software
– MIKE 2011 for Classic Grid (5 m)
– MIKE 2012 for Flexible Mesh
• Buildings blocked from mesh
– Engineers Australia, February 2012
• Floodplain Resistance
– CORINE Dataset

Modelling Team
• Internal Modelling Plan
– Folder Structure
– Naming Convention
– Model Log Sheet
– Live Database of Model Details (including current status)
– Modelling approach & assumptions
– Calibration Approach
– Programme
– Licences
– Modelling PC’s
– Archiving
– Modellers role and deliverables
• Internal Modelling Workshops
• Further assistance Not forgetting Mr Steve Flood !

Modelling Team
Hydrology Team
Mapping Team
Generation of Cross-Section
DB Structures
MIKE 11 Construction
MIKE 21 & MIKE FLOOD
Construction
MIKE FLOOD Calibration and
Verification
Technicians
(Using Civil 3D)
Junior / Senior
Modellers
Senior Modellers
Senior ModellersHydrology Team

Hydrology – MIKE NAM
• Hydrometric records
generally poor in study area
• Rainfall records date since
1940’s in some areas
• Radar data adjusted against
available rain gauge data
• Produced hourly gridded
time series of rainfall data
• Provide quality spatio-
temporal rainfall input for
the hydrological rainfall-
runoff analysis.

0
10
20
30
40
50
60
70
6/20/2007 12:00 6/21/2007 0:00 6/21/2007 12:00 6/22/2007 0:00 6/22/2007 12:00 6/23/2007 0:00 6/23/2007 12:00 6/24/2007 0:00 6/24/2007 12:00
Hourlyprecipitation(mm)
Date
Weighted (mm)
Radar (mm)
Total sum P_weighted = 32.80 (mm);
Total sum P_radar = 96.54 (mm)
Clear case why Radar data
is important to capture
spatio-temporal variability

• Significant improvements:
– Spatial distribution of rainfall
– Peak discharges
– Timing of peak discharges
• Provides hydrograph shape and an extended AMAX series
• ArcGIS scripts automate estimation of NAM model parameters:
– Based on look-up decision trees & available GIS layers
– Autocalibration used for gauged catchments
– Second phase calibration involving manual adjustment
– Mass balance check

Problems & Solutions
• Software versions
• Volume of work
• Heavily culverted models
• Peak discharge extraction
• Model simulation times
• Mass Balance Calculation
• HD Maps dfs2 shift
• Skewed weirs
• Links for narrow watercourses (GIS)

Current Status & Programme
• Draft Flood Extent Maps complete
• Draft final models & maps (end of September 2014)
• Client, Local Authority & Public Consultation (end of 2014)
• Final Model & Maps (early 2015)
• Flood Risk Management Plans (late 2015)

Further Information
www.cfram.ie

USING MIKE 21 FOR THE ESTIMATION OF JAPAN
TYPHOON RISK

1
Confidential©2013 Risk Management Solutions, Inc.
USING MIKE 21 FOR THE ESTIMATION OF
JAPAN TYPHOON RISK
Juergen Grieser
Director, Model Development
And Kimberly Roberts, Qun Zhao, Ashley Astorquia,
Jamie Rodney, John Maskell, and Nicolas Bruneau

2
Hazard
HOW DOES RMS MODEL FINANCIAL RISK?
Vulnerability
Transforms hazard into loss
ratio
Exposure
Exposure:
• Economic Exposure
• Industry Exposure
• Client Portfolios
• Storm
• Flood
• Terrorism
• Pandemics
Event set:
• Frequency
• Severity
• Footprints Hazard
LR

3
JAPAN TYPHOON SURGE
Complex coastline
Complex bathymetry

4
Tokyo Bay
> 4 MILLION PEOPLE LIVE IN AREAS BELOW SEA LEVEL
Ise Bay Osaka Bay
Tokyo Bay
Area: 116 km2
Population below sea level:
1.76 million
Ise Bay
Area: 336 km2
.9 million
Osaka Bay
Area: 124 km2
1.38 million

5
HOW CAN WE MODEL SURGE HAZARD?
We have a stochastic event set comprising 100,000 years
of synthetic storms, i.e. ~450,000 typhoons.
Each storm has a track and attributed wind fields.
But we cannot run MIKE 21 to calculate waves and surge
for all these storms and all possible tidal conditions.

6
STRATEGY
MIKE
Wave
MIKE
Surge
Parametric
Nearshore Model
MIKE Tides
Inundation Model
Track Selection
Waves
Track Selection
Surge
+
Parametric
Defence Model

7
TRACK
SELECTION

8
A simple parametric model
and
TRACK
SELECTION
 surge:

9
The simplest surge model:
TRACK
SELECTION
Wind Speed squared
Fetch
Nearshore Water Depth
Air Pressure Deficit
Calibration per gate with
MIKE runs of severe storms.

10
MIKE MESHES

11
Wave Mesh
MIKE MESHES
Surge Mesh
Surges get enhanced by shallow water.
Waves get limited by shallow water.

12
Calibrated with observed tides.
Domain size,
Local grid resolution,
Bottom friction parameter.
SURGE MESH
CALIBRATION

13
Calibrate CD with 11 key storms and
Verify with 400+ observed further storms since 1951.SURGE MESH
CALIBRATION

14
We underestimate surge at exposed sea fronts.
According to literature this is mainly due to wave setup not regarded in the surge
model.
SURGE MESH
CALIBRATION

15
TIDES

16
QQ plots for 24 starting hours.
TIDE-SURGE
INTERACTION:
VERA 1959
Ise BayOsaka Bay

17
TIDE-SURGE
INTERACTION:
VERA 1959
Ariake Sea Seto Inland Sea
QQ plots for 24 starting hours.

19
PARAMETRIC
NEARSHORE
MODEL

20
• The shallow water near the defence alters the wave spectrum.
• We need to know the highest waves at the defence.
• The nearshore model parameterizes wave setup and breaking
near the defences based on the EurOtop manual and
parameterizations by Jentsje van der Meer.
NEARSHORE
MODEL

21
WAVE SETUP DURING HISTORICAL STORM 3616

22
WAVE SETUP – MUROTOMISAKI (3616)

23
Wave Height Distribution
Wave Period
Wave Length
Wave Direction
Breaking Wave Height
Kind of Breaking
WAVES AT
DEFENCES

25
Location
Toe Height
Crest Height
Steepness
Material
Tetrapods
DEFENSES

26
5m DTM Defence database
DEFENCES Where are they?
Example Tokyo:

27
DEFENCES
8.2
8.6
5m DTM
5m DTM +
Defences
Doing this for 6000km is quite an effort.
Combine this Information

28
The Three Failure ProcessesDEFENCES
Wave Overtopping Surge Overflowing Breaching
Weir equationEurOtop Manual Together with our
consultant Prof. Jentsje
van der Meer

29
Debris Impact
Happened during Vera (1959)
NON-MODELLED DEFENCE BREACHING
Ship Impact
Happened during Muroto I
(1934)
Gate Failure
Many gates  high failure
potential

30
INUNDATION

31
Methodology:
In-house shallow water model over land.
Run on regular rectangular grid.
Extremely fast due to GPUs.
INUNDATION
Bath‐tubbing:
If water level higher than defence (or
ground elevation if undefended) then
flood it.

32
Inflow
TOKYO BAY
TEST CASE
Approx. 2s of GPU
time needed to run a
21.75hr inundation
event on 50m
resolution 899x2040
(aggregated from
5m).

33
Thanks for your
attention
THE END

DEVELOPING USEFUL ESTUARINE SEDIMENT
TRANSPORT MODELS: IMPROVING MODEL
OUTPUTS BY IMPROVING MODEL INPUTS

Developing Useful Estuarine Sediment Transport
Models: Improving Model Outputs by Improving
Model Inputs
Kevin Black
Partrac Ltd
DHI Symposium, Coventry, 13-14th May, 2014

A Judicious, Data-Led Approach for Improving
Estuarine Sediment Transport Models
Kevin Black
Partrac Ltd
DHI Symposium, Coventry, 13-14th May, 2014

Typical Sediment Management Applications
• Dredging impact
o Dispersion of dredge plumes
• Morphological assessment
o Stabilty of intertidal mudflats
• Longshore drift rate assessment
• Beach recharge efficacy
• Storm impact
o Riverine sediment influx
o Dispersion of river plumes
• Siltation severity in port environments
• Scour evaluation
• Suspended sediment transport/sediment flux assessment
• Construction activity impact
• Contaminated sediment management

Reality Check
• ALL models are an approximation to reality
• Our capability to predict water movements is pretty good
• Our capability to predict sediment movement is not as good
o Sandy sediments better than for muddy sediment
Conclusions of the EU SEDMOC Project
Davies et al., 2001 “It has long been known that predictors of coastal sediment
transport suffer from large inaccuracies, but this study indicated that the situation
was initially even worse than we thought”.
o Muddy sediments are complex materials, time dependent and comparatively
poorly understood
o Most models do not include biology

Factors Impacting Model Quality
1. Fancy mathematics
2. ALL models need to use the most up-to-date algorithms
3. ALL models need quality input data
4. ALL models to be calibrated
- the process of comparing model predictions with actual data, and ‘tuning’ the model
5. ALL models need to be verified (validated)
- the process of comparing model predictions with an entirely independent dataset

Calibration and Verification
1 Calibration

SedTrans Models - The Bottom Boundary
• Bathymetry
11
Sediment-hydraulic input parameters
– Flow velocity (stress)
– Size, Density (bed, suspended)
– Critical entrainment stress
– Erosion rate coefficients
– Critical depositional stress
– Settling velocity (suspended sediments)
– Bed roughness / hydraulic roughness
– (Sub-) surface structure
Sensitivity in model: moderate to high, since for most sediment types these input cannot be
estimated but must be measured

Measuring Boundary Layer Inputs using Benthic Flume
Technology

Internal paddles ADV flow sensor 3 vertical OBS turbidity sensors

Model Input Parameters Provided
• , .
• .
• .
•
•
•
•
Example Data

Needs
In situ instrument (net deposition) or unbiased sediment traps (gross deposition)
Measure to mm scale, 24/7
Sedimentation in estuaries frequently occurs on a scale below the resolution of
single/multi-beam survey (~0.10 m). Specialist sensors are required to measure
deposition at lower scales, and to record changes through time.
Model Verification: Comparing Model Predictions of
Deposition with Real Data

 direct, real world study of contaminant
movement
 Text
 Text
 snapshot only
animation
Title
Particle Tracking (a simple concept)
Cartoon courtesy of Bairds

Concluding Remarks
• Accept all models are, and will only ever be, approximations to reality
• Accept there may be a limit to the accuracy of SedTans models in particula
Nevertheless:
• Collect field data using state-of-the-art instrumentation and methods to opt
the model calibrations
• Verify the model extensively (using state-of-the-art instrumentation and met
to provide confidence to the model user and to sediment managers

“It has long been known that predictors of coastal
sediment transport suffer from large inaccuracies, but
this study indicated that the situation was initially even
worse than we thought”

REAL TIME FLOOD FORECASTING IN THE
ENVIRONMENT AGENCY

Real time Flood
Forecasting at the
Environment Agency
Cliff Williams
National Modelling and Forecasting Service
13 May 2014

Why Flood Forecasting?
The winter of 2013 to 2014 was the wettest on
record with over 7,800 homes and nearly
3,000 commercial properties flooded.
The most serious tidal surge in over 60 years
was experienced on December 5 2013. 2,400
properties were affected along the East Coast
of England.

Emergency
responders
Public
Radar
& satellite
data
National Flood
Forecasting
System
(NFFS)
Weather Forecasting Flood Forecasting Flood Warning
Media
Met’
data
Rain & radar
forecasts
Rain & radar
forecasts
Tide & surgeTide & surge
Flood
Forecasting
Centre (1)
Forecasting
centres (7)
River, Coast &
rain gauge data
Area
Incident
Rooms
(16)
+

Key Data and Products
From the Met Office:
‘Best Data’ products
UK Weather Radar Network (joint MO/EA)
SMD, wind forecast etc

From the FFC:
Hydromet Guidance
Forecast Met Data (FMD)
Heavy Rainfall Alerts (HRA)
UKCMF tidal alerts

UKCMF:
Astronomical tide data (yearly)
CS3 surge model (CS3)
CS3 surge ensembles (24 members, +120 hours)
Tide gauge network
Wave forecasts (Wave Watch III model)
Observed waves (WaveNet)

Other Data:
National telemetry network (Q, H and P)

Best Data Short-range
Source purely UKV. 2km grid
36 hour forecast, 4 times a day:
0300, 0900, 1500, 2100 GMT
Delivered approx. 2.5 hours later.
Products:
N5: rain-rate (15 min intervals)
N6: rain-accumulation (15 min intervals)
N7: screen temperature (hourly intervals)
.

Best Data Medium-range
5 day forecast
UKPP constructs data on a 2km grid.
Radar data first 3 hours – UKV – Euro4
4 times daily, based on Euro4 runtimes:
0000 & 1200 GMT (120 hour forecasts)
0600 & 1800 GMT (60 hour forecasts)
Products:
N8: rain-rate (hourly intervals)
N9: rain-accumulation (hourly intervals)
N10: screen temperature (hourly intervals)

NFFS System Configuration
14
Toltec
Online
NFFS
Merlin
Online NFFS
Primary
Hyrad
Telemetry
MO Data
DDS
(Dual sited)
Exported
NFFS
Data
Telemetry
Exported NFFS
Forecast for use
in Telemetry
Toltec
Online
Webservice
Merlin
Online
Webservice
DDS

Model run times and forecast length
Fluvial forecasts:
Every 6 hours (or more)
+36 hours (or more)
Tidal forecasts:
every 6 hours
+36 hours
Tidal ensemble forecasts:
every 12 hours
+120 hours
Historical fluvial forecast:
once a day at 0500, T0=2100 on the previous day.
15

NFFS data hierarchy
Rain gauge
Radar
actuals
Observed Forecast
Short range model forecast
Radar based forecast

Mike 11 fluvial forecasting models
Ancholme
Bedford Ouse
Blackwater
Burton Coggles
Gipping
Irnham
Louth (NAM to ISIS)
Market Harborough
Surfleet

Bedford Ouse – Mike 11 model

Bedford Ouse – Catchment Averaging
19

Bedford Ouse – Catchment Averaging
20

Bedford Ouse – NAM generated flows
21

Bedford Ouse model calibration

Forecasting Systems and Tools used in
Coastal Events
Deterministic Forecasting
Probabilistic Forecasting
Quantification of forecast uncertainty
Longer lead times (5 days)
Can provide Best, Worse Case and Most Likely
Scenario information.

Deterministic Coastal Forecasting

Surge Ensembles: Mon 2 Dec. PM

FROM HAZARD TO IMPACT: THE CORFU FLOOD
DAMAGE ASSESSMENT TOOL

Albert S. Chen
FROM HAZARD TO IMPACT
The CORFU flood damage assessment tool
2014 MIKE by DHI UK Symposium

Outline
• The CORFU Project
• Flood damage assessment tool
• Demo
• Conclusions

The CORFU project
• Collaborative Research on Flood Resilience in Urban
Areas
• Funded by European Commission FP7
• Overall aims:
– Assess flood impacts for different futures or scenarios
– Develop and evaluate state-of-the-art flood resilience
measures and strategies
– Facilitate mutual learning between European & Asian
cities through joint investigation to help create flood
resilient cities

Introduction
Drivers and pressures
Flood hazard assessment
Vulnerability / impact
assessment
Responses and resilience
strategies

Introduction
Tangible Intangible
Direct
Physical damage to assets
• Buildings
• Contents
• Infrastructure
Loss of life
Injuries
Diseases
Loss of ecological goods
Indirect
Loss of industrial
production
Traffic disruption
Emergency costs
Inconvenience of post‐
flood recovery
Increased vulnerability of
survivors

Introduction
Barcelona
Beijing
Dhaka
Hamburg
Mumbai
Nice
Taipei

Flood damage assessment
Damage
Depth
Depth‐Damage
Curves (DDC)
Land uses

Hazard-vulnerability function
Damage Hazard information Vulnerability
Building content/
construction damage
Flood depth
(and duration)
Financial loss
Building construction
damage
Flood velocity
(and duration)
Building resistance
Pedestrian safety Flood depth Human physical resistance
Pedestrian safety Flood velocity Human physical resistance
Driving safety Flood depth Vehicle resistance
Driving safety Flood velocity Vehicle resistance
Human body health Contamination concentration
(and duration)
Human body resistance

Health-impact assessment
Health Impact
Contamination
Contamination‐
Health Impact
Curves
Demographic
data
Mortality
Depth
Depth‐Mortality
Curves (DDC)
Demographic
data

Model development
• Standard GIS data format adopted
• Integrated with DHI MIKE software
• Python scripts and Geoprocessing functions within ESRI
ArcGIS software
• Minimum manual input to calculate the flood damage
• Transportable to other GIS software packages/platforms
• Separate executable programs for additional functions

Resolution issue
0 2010
m
±
Legend
Buildings
Others
Commercial Activity
Education & Research
Governmental Services
Mixed Use
Manufacturing and Processing Activity
Residential

Input
• Buildings
– Unique index for each
building
– Major land use type/
Combination of land use
• Flood depth
– Raster grid (MIKE Urban)
– Depth inside building
(Irregular polygons for
Barcelona case)

Depth-damage curves (DDC)
The Benefits of Flood and Coastal Risk Management: A Handbook of Assessment
Techniques‐2010 (Multi‐Coloured Manual), Middlesex University, UK

Output
• Damage/EAD for individual
buildings
• Same output format for
various input data types

Conclusions
• GIS-based tool for flood damage assessment
• Capable utilising hydraulic modelling results
directly
• Evaluate the flood damage & EAD efficiently
• Possible further applications
– future flood damage using urban growth model data
– different hazard-vulnerability analyses and other
future scenarios

Acknowledgements
• Research on the CORFU (Collaborative research on flood
resilience in urban areas) project was funded by the
European Commission through Framework Programme 7,
Grant Number 244047.
• The authors appreciate the Institute of Water Modelling
(IWM) for the provision of case study data and William
Veerbeek for the UGM modelling results.

Thank you and questions?
Further information: http://corfu7.eu
Contact: a.s.chen@ex.ac.uk

JUST HOW SEVERE WAS THE 2013/14 WINTER
AND HOW DID THE MET OFFICE WAVE MODEL
PERFORM?

© Crown copyright Met Office
Just how bad was the winter?
An assessment of the Met Office wave model data and a long term
comparison
Adam Leonard-Williams, Senior Metocean Scientist, DHI User Group Meeting 12th May 2014

Contents
This presentation covers the following areas
• Introduction
• Locations and data sets
• Model vs. obs for the winter
• Long term comparison using the hindcast
• Impact on EVA
• Questions and answers

Introduction

It was miserable…
• Wettest winter is UK & Wales series
since 1766.
• 2 spells exceptionally stormy weather
mid Dec – early Jan & late Jan – mid
Feb.
•At least 12 major winter storms,
stormiest period of winter weather for at
least 20 years.

It was miserable…
5th Dec 19th Dec 24th Dec 27th Dec 31st Dec
3rd Jan 6th Jan 26th Jan
4th Feb 8th Feb 12th Feb 14th Feb1st Feb

It was miserable…
Barometric pressure
Number gust
events
940 mb 940 mb

Further reading, wider
context
“A global perspective on the recent storms and floods in the UK”
Met Office & CEH February 2014
http://www.metoffice.gov.uk/media/pdf/1/2/Recent_Storms_Briefing_Fina
l_SLR_20140211.pdf
• Major perturbations to the pacific and North Atlantic jet streams
• Driven, in part, by persistent rainfall over indonesia and tropical West
Pacific.
• North Atlantic jet stream unusually strong, linked to exceptional wind
patterns in stratosphere with intense polar vortex.
• As yet no definitive answer on possible contribution of climate change
to the recent storminess. This is in part due to the highly variable
nature of UK weather and climate.

A focus on the waves

The science has improved since
1607, meanwhile the journalism….

4th Jan 7th Jan 27th Jan
1st Feb 5th Feb 9th Feb
Global model output

Motivations for investigation
• Did we model the
storm peaks ok?
• How did the winter
compare with previous
ones?
• Geographical
variation?
• Any impacts to think
about?
• Interest from industry

Locations and Datasets
K5
K4
Brittany
E1 & Porthleven
Magnus
Buchan
Clipper
Observations datasets
Porthleven obs
Porthleven
model point

Model dataset
• Hindcast run from 1980 to end February 2014 (3 hourly 1980-2000, hourly 2001
to present)
• WaveWatch III Global 50km driving European 8km
• ERA-interim atmospherics (75km up to 2011), then Met Office global operational
data at 25km.
Locations and Datasets

Model vs. Observations

obs hindcast 1980/81 – 2012/13 DJF
mean and 97.5th %ile
76% > mean, 8% > 97.5th %ile
79% > mean, 14% > 97.5th %ile
71% > mean, 13% > 97.5th %ile
75% > mean, 14% > 97.5th %ile

obs hindcast 1980/81 – 2012/13 DJF
mean and 97.5th %ile
72% > mean, 9% > 97.5th %ile
72% > mean, 8% > 97.5th %ile
53% > mean, 4% > 97.5th %ile
58% > mean, 9% > 97.5th %ile

Scatter plots for Dec 2013 – Feb 2014

Long term comparisons using the
hindcast

Long term comparisons
• Use the hindcast to compare
this winter (DJF) against the
previous 33.
• Compare: mean hs, 97.5th
%ile hs and number of storm
events

DJF Mean Hs DJF 97.5th %ile Hs

Number of event that exceed 97.5%ile (DJF)

Overview
•Highest mean
97.5th %ile and no.
storms
• ~70-80% time hs
> mean
•Highest mean
97.5th %ile and no.
storms
• ~72% time hs >
mean
•3 previous years
with higher mean
•4 previous years
with higher 97.5th
%ile
• 9 previous years
with at least as
many storm events
•57% time hs >
mean
•7 previous years with
higher mean
•11 previous years
with higher 97.5th %ile
• 1 previous years with
at least as many storm
events
•53% time hs > mean

Impact on EVA

Impact on EVA
• Small case study at E1 – EVA on data before and then
including this winter.
• Fitted GEV to winter maximums 80/81 to 12/13
• Fitted GPD to time series data 1980 to 2013
• Fitted GEV to all winter maximums
• Fitted GPD to all time series data

Impact on EVA
• Diff of ~3m at
1000-yr rp for
GEV
• Diff of ~4m at
1000 rp for
GPD

Impact on EVA
R Diagnostic plots for GEV analysis
1980/81 – 2012/13 1980/81 – 2013/14
Note change in slope!

Questions & answers

Zoomed in on January 26th to February 16th

INTEGRATED CATCHMENT AND ESTUARY
MODELLING

www.intertek.com1
Integrated Catchment
and Estuary Modelling
An approach for modelling bacteria

www.intertek.com2
Aims
• To understand bathing water and
shellfish water quality
• To understand contributions from
the catchment and from the
assets
• Water company
• Domestic
• Business
• Agricultural / diffuse
• To provide a basis for the design
of solutions which will address
the real problems

www.intertek.com3
Historical Water Quality – Bathing Water

www.intertek.com4
Historical Water Quality – Shellfish Water

www.intertek.com5
The Catchment
• Water company assets
• 15 continuous
• 45 intermittent
• Domestic off-sewer
• 31 active consents
• 38 exemptions
• Businesses off sewer
• 42 active consents
• 5 exemptions
• Agricultural diffuse
• 19 watercourses
• 500,000 sheep and cattle

www.intertek.com6
Modelling the catchment
• Point source assets
• River model: Catchment-Impact
– model travel time and decay
to the estuary model
• Agricultural sources
• Hydrology and bacteria washoff
model to simulate – depostion,
decay, washoff, partition and
transport to the river system

www.intertek.com7
Modelling the estuary
200 metre regional model 50 metre local model

www.intertek.com8
Hydrology Calibration
• Model based on revised FEH
method
• Calibrate and validate against
measured flow data
• Check against flow statistics
0
5
10
15
20
01/04/2000 16/04/2000 01/05/2000 16/05/2000 31/05/2000 15/06/2000 30/06/2000
Flow(m3/s)
Modelled Observed
0
0.2
0.4
0.6
0.8
1
1.2
5% 10% 15% 20% 25% 30% 35% 40% 45% 50% 55% 60% 65% 70% 75% 80% 85% 90% 95%
Flow (m3/s)
Comparison of modelled and observed log‐normal distribution percentiles
Observed
Modelled

www.intertek.com9
Bacteria Washoff Calibration
• Model based on SWAT method
but with much finer timestep
• Calibrate and validate against
sampling data
• Check against statistics

www.intertek.com10
Integrating the models
• Network model – 10 years output
• River model – 10 years output for
upstream point sources
• Washoff model -10 years output –
varying sheep and cattle
population for each year
• Estuary model – unit impact
approach for flexibility

www.intertek.com11
Validating the overall model
• Validate against bathing
water sampling data
• May show ‘missing’ load
• Talk to operations
• Contamination survey
• Sampling data
• Validated model can be used
with confidence to design
solutions
0
10
20
30
40
50
60
70
80
90
100
1
2
3
6
10
18
32
56
100
178
316
562
1,000
1,778
3,162
5,623
10,000
17,783
31,623
56,234
100,000
concentration (no/dl)
%cumulativeexceeden
Model predictions BWsampling Model predictions fitted BWsamplingfitted

www.intertek.com12
Model Output
• Bathing waters – results at a
point
• Shellfish waters – results as
contours

www.intertek.com13
Source apportionment
• Source apportionment allows
schemes to be designed to
address the asset which is
causing the problem
• The impact of diffuse
(agricultural) runoff is clearly
shown. It may not be
possible to solve the
problem without addressing
runoff.

www.intertek.com14
What next?
• Noro-virus
• Much longer decay rate
• Active and inactivated forms
• Only produced by humans
• Real-time predictions
• Provide warnings to bathers
• Provide warning to shell-
fishermen
• Variable decay rate 0
10
20
30
40
50
0 1 2 3 4 5 6 7 8
Concentration (nv/100ml)
Days
SW38
SW6
SW34
SW39
SW33
SW27
Standard

RIVERINE WATER QUALITY MODELLING, WITH
FOCUS ON NUTRIENTS USING MIKE 11 ECO LAB
VERA JONES (ATKINS)

River water quality modelling using
Mike 11 Ecolab
DHI User Group meeting
13th May 2014
Presentation by:
Vera Jones

3
Impacts on water quality
•Water quality is often a key concern when assessing the
environmental impact of new developments, due to for
example:
New wastewater
discharges
New trade discharges
Changes flow/dilution

4
•EC Water Framework Directive (WFD) has put a renewed focus on
water quality - target for water bodies to achieve Good Status, a number
of new environmental quality standards and principle of ‘no
deterioration’.
Legislative considerations
•Priority Substances Directive. Latest
edition was published in August 2013 and
will be revised every 3 years.
•Urban Wastewater Treatment Directive:
Urban Pollution Manual*.
•Bathing Water Directive – also revised
recently. Standards defining the quality of
bathing waters, focusing on bacterial
counts.
*FWR (2012). Urban Pollution Management Manual
http://www.fwr.org/UPM3/

Assessing water quality impacts
5

6
Range of options available:
Monitoring and visual
assessment of results
Simple mass balance
calculations
Assessing water quality impacts
Steady State models –
SIMCAT, QUAL-2K
Hydrodynamic models -
Mike 11 Ecolab.

Issues to
•Over the past years we have worked on several
hydrodynamic water quality models using Mike 11 Ecolab,
with a focus on dissolved oxygen and nutrient modelling.
Our hydrodynamic water quality modelling capability
•Hydrodynamic water quality models provide higher level of
detail on temporal and spatial resolution which is often
needed to assess the water quality impacts of:
oNew water resources schemes
oContinuous and intermittent discharges
Key tool to optimise water companies’ strategic
investments.

Effect of shading due to marginal vegetation
•Results in less light in the water column and less surface water cooling
Modification of standard equation to take into account localised
marginal vegetation
Variation in water clarity along a tidal river
•Significant variation in tidal rivers, both temporally and spatially.
Development of a series of equations to simulate variations in water
clarity based on changing water levels or salinity along the river
Taking into account the impacts of
periodic algal blooms
•Phytoplankton populations shrink and
expand during the year
Modification to the photosynthesis and
respiration equations to include a time-
varying chlorophyll determinand
Adapting models to fit each project requirements

Catchment understanding at the start of the project
Several wastewater treatment works
Storm discharges from
combined sewer
overflows
High nutrient load

Model
description
•Parameters
modelled:
Dissolved Oxygen
Temperature
Ammonia
Nitrate
Ortho-phosphate
Particulate
phosphorus
Biochemical Oxygen
Demand
•Summer 2011 survey
•Input from sewer model
(MWH): ammonia and
BOD
31 rural sub-
catchments
7 wastewater
treatment works
6 private discharges
~120 combined
sewer overflows – DAS
modelling by MWH
p
Ammonia
Ortho-phosphate

Calibration & Validation: example

10-year runs –
stochastic
‘baseline’
Methodology for assessment
Results extracted and processed for every model node:
•Water Framework Directive standards
•99th percentile standards*
•Fundamental Intermittent Standards (FIS)*
Two years selected for further
scenario testing : ‘poor’ and
‘average’ water quality
Urban
Wastewater
Treatment
Directive
*FWR (2012). Urban Pollution Management Manual
http://www.fwr.org/UPM3/

Methodology for assessment
•Programme developed for processing results at every
node against the relevant standards.
High
Good
Moderate
Poor
Bad
For all results analyses: Good or High
Status is required.
10-year model scenario runs=100 million data points per
run; data processing tool developed to convert results to
easy-to-read maps

Scenario testing: analysis against WFD standards
Ortho-phosphate 2024 -
baseline
Ortho-phosphate 2024 – no waste
water treatment works scenario
Works are a key cause of failure to
meet the Water Framework Directive
standards
High
Good
Moderate
Poor
Bad

Scenario testing: analysis against 99th percentile standards
BOD 2024 - baseline BOD 2024 – no waste water
treatment works scenario
However, works also dilute intermittent
untreated combined sewer overflow inputs.
High
Good
Moderate
Poor
Bad
Currently assisting our client to explore best strategic
options for this system, including advanced treatment at
wastewater treatment works.

18
•Water quality often a key concern when new developments
or schemes are planned.
•Water Framework Directive
has put a renewed focus on
impacts on water quality.
•An important tool to help us
assess impacts on water quality
is hydrodynamic modelling –
power of quantitative
assessment and scenario
testing.
Overview & Conclusion
•Key success factors:
Adapting model to suit requirements of each project
Developing tools to process results efficiently – clarity of
results presentation to clients/regulators.

TEACHING WITH MIKE BY DHI

Teaching & Research with
MIKE by DHI @
Queen’s University Belfast
Dr Björn Elsäßer Dipl. Ing. CEng
13th May 2014

School of Planning, Architecture and Civil Engineering
• Established 1845 as Queen’s College,
• More than 17,000 students and 3,500 staff,
• Part of Russell Group of Universities,
• SPACE has 60 staff and 160 students starting
each year
About Queen’s University Belfast

Marine Renewable Energy @ QUB -
Wave Energy

Marine Renewable Energy @ QUB -
Tidal Energy

MIKE in class
Coastal Engineering & Tidal Energy module
• Demonstration of shoaling, refraction and
diffraction using Mike 21 BW
• Building of a complete tidal model of the
Severn Estuary

• Easy analysis of data without
knowledge of any programming
language
MIKE in class
Tidal Analysis & Prediction Toolbox
• Knowledge &
understanding of student
can be tested !

MIKE in class
Wave hindcast model as 3rd year project

• Importance of southern Atlantic
wave climate on NA
• Good performance of SW model
relative to assimilated data
From student project to PhD project
The North Atlantic Wave model

Sewage outfall impacts in Belfast Lough
Belfast Lough historically eutrophic
£43 m investment in 2006 to improve water
treatment
New wastewater treatment works completed
in 2008
Minimal tertiary treatment prior to discharge
Designed discharge capacity of 900 l/s
Daniel Pritchard Hydrodynamic models as ecological tools
Belfast
Portaferry
Treatment
Works
Outfall

The ‘Briggs Rock Seaweed Culture Project’
≈ 30 % of N
≈ 1.5 % of P
Possible…
but not experimentally tractable!

Outfall Impacts: Approach
Water samples from the treatment plant
In situ water samples
Seaweed bulk stable isotope samples
Hydrodynamic model development and validation
Simplified plume and processed-based macroalgal
models (Eulerian transport)

Outfall impacts: Results
Initial dilution is very high
High spatial variability
The model predicts the magnitude of the
nutrient input the right order of magnitude…
… but under predicts on Spring Tides
Pritchard et al. In review. Marine Pollution Bulletin

Outfall impacts: Results
Stable isotopes
Significant, but small differences
between sites

School of Planning, Architecture and Civil EngineeringLouise O’Boyle
Wave Energy Converter
• Designed to extract energy from waves
• Also interact with local wave climate
Wave Energy Converter Arrays
• Multiple devices deployed in close proximity
• One WEC may positively or negatively influence energy available
for other WEC’s
• Increased scale - increases potential for changes to coastal
processes, sediment transport and ecology.
Changes to Wave Field
• Quantifying changes in wave field numerically facilitates
environmental impact assessments and design of optimum wave
farm layout
• Experimental results required for numerical model validation
Wave Fields around Wave Energy Converter Arrays.
Wave Fields around Wave Energy Converter Arrays

School of Planning, Architecture and Civil EngineeringLouise O’Boyle Wave Fields around Wave Energy Converter Arrays.
Potential interaction of a WEC on the surrounding
wave field.
Wave
Scattering
Reflection Diffraction
Wave
Radiation
In order for a device to extract
energy it destructively interfere with
incident waves: wave radiation
How will Wave Farm Interact?

School of Planning, Architecture and Civil EngineeringLouise O’Boyle 8/ 21
Experimental Approach
• Experimentally map the wave climate around WEC array
• Use different model types for each interaction effect
• Each tested individually and in 4 array layouts
• Results used for numerical model validation

Results – Wave Disturbance (mm)
Terminator Array Configuration
Attenuator Array Configuration
Wavelength = device spacingWavelength > device spacing Wavelength < device spacing
Sample Results

MIKE 21 Boussinesq Waves
• Phase resolving – depth averaged
MIKE 21 Spectral Waves
• Phase Averaged
Model Area – Portaferry Wave Basin
• Experiments carried out at Portaferry Wave Basin
• Maximum correlation with experimental data required
• WEC arrays simulated in models of wave basin
• Numerical models validated at wave basin scale
• Subsequently extended to full scale
Surfaceelevation(mm)
Time (s)
Frequency (Hz)
SpectralDendity
Numerical Representation of WECs

WEC representation in MIKE 21 SW Model
• WEC represented using ‘Structures’ tool in SW model
• Definition of frequency and directionally dependent
• Reflection coefficient - Kr
• Transmission coefficient - Kt
• Absorption coefficient – Ka = √(1 – Kr
2 – Kt
2)
• Energy balence is altered accordingly at each cell containing a structure.
Fully Reflective Absorbing Obstacle Oscillating Water Column
Kr = 1
Kt = 0
Ka = 0
e.g. Kr = 0
Kt = 0.8
Ka = 0.2
(related to absorption)
Kr = reflected + (Krad /√2)
Kt = transmitted + (Krad /√2)
Ka = Krad
(related to power capture)
Acting over
what
diameter?
Frequency &
directionally
dependant

WEC presentation in MIKE 21 BW Model
• WEC represented by assigning porosity values to each cell within the
footprint of the device.
• Fully reflective obstacles – porosity = 0, equivalent to ‘land value’
• Absorbing obstacles - porosity = 0.4 or variable porosity
- characteristic unit diameter = 0.01 (laminar)
• Real WEC represented using internal generation lines to simulate the
radiated wave
Louise O’Boyle Wave Fields around Wave Energy Converter Arrays.

• BW model results based on surface elevation (Boussinesq eqn.)
• SW model results based on wave energy (Action Balance eqn.)
• Therefore it is proposed that a better parameter for cross validation of
models is change in energy content
Comparison of results for single OWC at damping level 3
Comparison of Results

Comparison of Array Configuration and Damping Level
• SW model has been validated and can be used to investigate effects of
array layout and damping levels on the wave field

Horse-mussel larvae in Strangford Lough
Strangford Lough heavily dredged
for queen scallops in the late
1970’s and early 1980’s
Massive decline in Modiolus
modiolus biogenic reefs
Cultch site
Strangford
Lough
Strangford
Narrows
52 days of simulation
True Lagrangian transport
Full hydrodynamic background
Continuous release, 6 sites, 200
particles per timestep

Horse-mussel larvae: Results
Elsäßer et al. 2013. Identifying optimal sites for natural recovery and restoration of impacted biogenic habitats in a special
area of conservation using hydrodynamic and habitat suitability modelling. Journal of Sea Research, 77: 11--21.

What is to come:
• LINC -

Conclusions
• Easy user interface allows engineering students to
get into hydraulic modelling quickly
• Excellent research tool – mean to an end!
• Enables colaborative work, where focus is on the
science not on the process
• Improvements to code or additions can be
implemented

For more details see:
• http://www.qub.ac.uk/research-centres/eerc/
• http://tiny.cc/BjoernElsaesser
• https://github.com/dpritchard
• http://dx.doi.org/10.1016/j.seares.2012.12.006
• http://dx.doi.org/10.1016/j.marpolbul.2013.09.046
• http://dx.doi.org/10.1007/978-94-017-8002-5_12

ACKNOWLEDGEMENTS
ALAN FORSTER (URS)
YIPING CHEN (HYDER CONSULTING)
SHIRIN COSTA (MOTT MACDONALD)
AMBRE TREHIN & ZHONG PENG (FUGRO GEOS)
VERA JONES (ATKINS)
JAMES TOMLINSON (ATKINS)
THANKS TO ALL DHI STAFF (PARTICULARLY ERLAND
RASMUSSEN, POUL KRONBORG AND TORBEN S. JENSEN WHO
PRESENTED ON THE DAY) AND SPECIAL THANKS TO DORA
TRYGGVADOTTIR AND MARK BRITTON
MANY THANKS TO EVERYONE WHO ATTENDED AND
PARTICIPATED IN THE EVENT

DHI Water Environments (UK) Ltd
Ocean Village Innovation Centre
Ocean Way
Southampton
SO14 3JZ
United Kingdom
Telephone +44 (0)2380 381961
mikebydhi.uk@dhigroup.com
www.dhi-uk.info/ugm
www.dhigroup.com
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needs and challenges. Our training courses are offered as standard and/or as tailored training.
MIKE by DHI courses focus on practical skills, hands-on exercises and on teaching you how to
get the most out of your software.
Thematic courses allow you to apply concepts, applications and decision support principles to
the entire business process within current areas such as aquaculture & agriculture, energy,
climate change, flooding, coast & marine, surface & groundwater, urban water, industry,
environment & ecosystems, product safety & environmental risk, etc.
MIKE CUSTOMISED by DHI courses enable you to understand the power of the MIKE
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Our trainers are experienced professionals, many of whom are recognised international
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2014 mike by dhi uk symposium user group meeting - presentations and papers - 13 may 2014

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2014 mike by dhi uk symposium user group meeting - presentations and papers - 13 may 2014