dsd-int 2015 - towards new hydrological forecasting systems in wales - andrew how

A NEW FLOOD FORECASTING SYSTEM FOR WALES:

CHALLENGES & OPPORTUNITIES

Andrew How Flood Forecasting Team Leader

Cyfoeth Naturiol Cymru / Natural Resources Wales

WALES Flood Risk Summary Overview

POPULATION

COASTAL

FLUVIAL

With steep, fast responding river catchments; large areas

of exposed coastline and a significant percentage of the population at risk of flooding – there are many challenges

to flood forecasting

POPULATION • 3 million people live in Wales • 1 in 8 people live in properties at risk from fluvial or coastal flooding. • Over half the population of Wales live near to, or on, the coast. • £8 billion worth of assets at risk.

FLUVIAL

Fast responding rivers.

Typical river response; from a normal to severe

event in less than 2 hours.

COASTAL • 1200km of coastline. • Sections of coastline exposed to large Atlantic swell waves and strong onshore winds • 2nd largest tidal range in the world with complex tide / surge interaction. • Large storm surge risk • Significant coastal communities.

• Where have we been?

• Where are we now?

• Where are we going?

• Where have we been?

Timeline of flood forecasting in Wales

pRE - 2004

Local dispersed service

Timeline of flood forecasting in Wales 2

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Timeline of flood forecasting in Wales

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Timeline of flood forecasting in Wales Centralised Coastal Forecasting

Centralised Fluvial Forecasting

New Coastal Forecasting Model

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Dockable windows

Expanded fluvial forecasting including boundary change

Improved interface

Timeline of flood forecasting in Wales

Model improvements

Ensemble forecasting

Improved data feeds

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+ + =

Timeline of flood forecasting in Wales

• No IT infrastructure

• No IT kit

• No established ways of working

Former EAWUsers

Former CCW Users

Former FCW UsersNRW

Office 365

Cloud Services

New organisation

• Building our own ICT

– World has changed – cloud

– Government Digital Services (GDS) “Cloud first or justify”

– Large System Integrators vs budgetary challenges

• Economic commitment

– Providing high quality skilled jobs in Wales

Early decisions

Former EAWUsers

Former CCW Users

Former FCW UsersNRW

Office 365

Cloud Services

Former EAWUsers

Former CCW Users

Former FCW UsersNRW

Office 365

Cloud Services

Former EAWUsers

Former CCW Users

Former FCW UsersNRW

Office 365

Cloud Services

Apprenticeship scheme

• First funded Microsoft Apprenticeship scheme in Wales

• 2 year apprenticeship with industry qualification

• Currently we have 9 apprentices

• Scheme has been adopted by other organisations

• Allows organic growth of our ICT Team

Early decisions

• Majority of applications run in cloud

• Many of our servers are cloud based

• We only pay when we are using them

• We can “spin up” a server in less than 5 minutes

• Applications are being simplified as they are migrated

MyNRW Azure VPN Connections Mobile Deployment

CRM Office 365Apprenticeship

SchemeStarLIMS

NRW Kit RolloutIntranet DMS Internet

Yammer Lync VOIP Telephony Mobile Apps

Applications

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Timeline of flood forecasting in Wales

Version upgrades

Expanded coverage

Improved and recalibrated models

Templates

Model schematics

Telemetry polling User permissions

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Timeline of flood forecasting in Wales

• Where have we been?

• Where are we now?

• Environment Agency replacing NFFS

• Natural Resources Wales establishing own capability

• Migrate existing NFFS for Wales

Wales’ forecasting system

Challenges

• Forecasting system which is hosted on infrastructure based in a separate organisation

• Forecasting system developed > 10 years ago

• New organisation with limited resources

• Limited timescales

• Managing existing system whilst developing the new system

Advantages

• Extensive configuration experience

• Established ways of working

• Open and flexible approach to IT

• Ability to utilise latest technological innovations

• Opportunity to learn from implementations of FEWS around the world

• Where have we been?

• Where are we now?

• Where are we going?

Not just a ‘lift and shift’ of the current setup

Methods of access

Reporting

Sharing data

Archiving

Basic functionality of supporting systems

Probabilistic forecasting

Dynamic assessment of risk

Establish our own capability

Way forward

Improved functionality

Not just a ‘lift and shift’ of the current setup

Methods of access

Reporting

Sharing data

Archiving

Basic functionality of supporting systems

Probabilistic forecasting

Sharing data

Dynamic assessment of risk

Way forward

Establish our own capability

Improved functionality

Sharing data

Sharing data

Basic functionality of supporting systems

Sharing data Basic functionality of supporting systems

Basic functionality of supporting systems

Basic functionality of supporting systems

Basic functionality of supporting systems Improved functionality

Improved functionality

Improved functionality

Improved functionality

Probabilistic forecasting

Improved functionality Probabilistic forecasting

Probabilistic forecasting

• Understanding of uncertainty • Better able to capture range of

risks • Increased processing / cloud

computing • Running all models with all

inputs

Probabilistic forecasting

Dynamic assessment of risk

Dynamic assessment of risk

Dynamic assessment of risk

• Real time updating of risk based on the latest forecast

• Dynamic colouring of flood risk areas

• Sharing data with professional partners

Methods of access

Dynamic assessment of risk Methods of access

Methods of access

App / web access Tailored to mobile working Access forecast meteorological / hydrological data Operational functionality

Full synch Ability to run standalone Full application

Minimal synch / no synch Ability to run models and assess output Operational functionality

Archiving

Archiving Methods of access

Archiving

• Currently using standard FEWS archive • We’ve done little development since implementation • Retrieving data is not always successful • Limited searchability and useability of data • Local working practice to manually archive Local Data Stores – noting any exceedances

• How do we automate this more effectively? • How do we combine archive with additional systems: telemetry data / historical data /

meteorological data? • How do we tailor this for: training / post event analysis / model calibration or verification

/ report generation?

Reporting

Archiving Reporting

Reporting

Reporting

• Where have we been?

• Where are we now?

• Where are we going?

Any questions?