Effects of climate change on flood risks Workshop on “Flood management in a transboundary context”, 13-14.12.2011, Zagreb, Croatia

1. Effects of climate change on flood risks
Jacob Høst-Madsen
Director, consultancy

2. Climate change is here and will have impact

3. Water Stress Changes by 2025
80% of future
stress from
population
& development
not
climate change
Vorosmarty et al., 2000

5. Climate change adaptation: Many stakeholders
• Countries
• Ministries
• EU
• Insurance industry
• Local communities
• Water supply works
• Citizens
• Regions
• Health authorities
• Emergency units
• ……….

6. What is IWRM ?
A process which promotes co-ordinated development and management of water, land
and related resources in order to maximize the economic and social welfare in an
equitable manner without compromising the sustainability of the nature.
Securing basic water needs takes
50 l/cap/day
Securing our basic diet takes 2500
l/cap/day
Bio-fuels using up to 10-30,000 l
water per l bio-fuel!

7. Water governance and IWRM:
A never ending cycle!
Vision
Monitoring Situation analysis
Awareness
Participation
Commitment
Implementation Capacity Strategy
IWRM Plan

8. WR management issues
The basin as the basic
management unit
Opportunities for modelling

9. IWRM where?
IWRM processes focus on critical
water resources issues of any basin

10. New climate change guidelines from DHI
• Working with climate change: Water resources guidelines
• Working with climate change: Urban water guidelines
• Working with climate change: Marine water guidelines

11. The guidelines can provide answers to:
• Where and how to do screening and detail investigations?
• How to do adaptation and intelligent planning?
• How to do contingency planning?
• How to see adaptation planning as a continued effort?

12. Example: Guidelines for the analyses of the
impacts from climate changes on sewer systems
Purpose:
• Safeguard the future service level
• Identity new flood risk zones, due to climate changes
• Estimation of flood damanges
• Preparation of flood mitigation plans (climate adoptions)

13. The road towards informed decisions – according to the climate
guidelines
1. Will there be a problem ?
2. How big will it be ?
3. When will it arrive ?
4. What will it cost ?
5. How can damages be reduced ?

14. Informed decisions – Urban water
• Avoid contact with mixtures of rain water and
wastewater
• Protection of vital functions in society, i.e.
electricity, water, heating, communication and
hospitals,
• Economical estimates of damages to society
• Develop emergency plans

15. Flood damage reduction
• Reduction of the flood extent
• Reduction of the interaction with the flood
• Control of the surface runoff and subsequently
flooded areas
• Emergency plans and actions
• Flood warning and information systems

16. Example: Greve, Denmark

17. Example – Greve Denmark

18. The intelligent city

19. The football field: A new flood control storage - Denmark?

20. Intelligent planning - Porto Alegre - Brazil

21. Get the water out of the sewerage system

22. DHI Climate Change DSS
Powerful decision support for climate change
adaptation
Applications Features Benefits
• Analyses of impacts from different • Current and future climate information • Strong decision support
emission scenarios and different • Scenario data • Easy analysis from Global
global circulation models • Vulnerability information Circulation model to local impact
• Analysis of climate vulnerability, • Impacts information • Output tailored for stakeholders
undertainty, and downscaling • Adaptation impacts and decision makers
• View and display information • Analysis tools • Part of DHI Solution Software
concerning current and future climate • Data exchange
scenarios • Downscaling
• Uncertainty
• Comparison of adaptation measures
• Forum for decisions
• Presentation and analysis
• Database.

23. Downscaling & corrections
GCM projections:
Dynamical
Downscaling
RCM projections:
Statistical Downscaling Bias
Corrections
Weather generators,
….
Local Climate simulations:
Local Hydrological simulations:

24. Scenario 1 Scenario 2

25. Climate change tool In MIKE by DHI

26. Case: The Nile Basin Decision Support System

27. The Nile Basin DSS Project
Client : Nile Basin Initiative, Water Resources
Management Project, Addis Ababa, Ethiopia.
Lead Consultant : DHI
Sub-consultants:
• Riverside Technologies, USA
• Mott MacDonald, UK
• Tropics Consultants, Ethiopia.
• Funding : World Bank
• Project Period (May 2009 – May 2012)
• Project Scope (WP1 : IT Project)
– Software Requirement Analysis
– Software Architecture and Design
– Software Development and Testing
– Proof-of-concept
• WP2 (NB DSS Application within the Nile Basin)
– Software Testing
– Full scale application

28. Background (Nile Basin DSS)
• Key Treaties and Events
Various Bi-lateral Agreements
Sudan/Egypt and upstream riparians (no downstream
Impacts unless agreed with Sudan/Egypt)
High Aswan Dam (1955)
Capacity 111 BCM.
Nile Basin Treaty (1959):
55.5 BCM/yr for Egypt
18.5 BCM/yr for Sudan.
Nile Basin Initiative (NBI) Established (1999)
Under the NILE COM (Ministers of Water Affairs)
• promote cooperation and co-ordination in the Basin

29. Nile Basin water resources
management
Egypt, Sudan, Ethiopia, DR Congo, Uganda, Tanzania, Kenya, Burundi, Rwanda
Challenge
The 9 riparian countries of the Nile river basin, represented by the Nile Basin
Initiative, have agreed to develop the water resources of the 3 million km2 Nile
river basin in a cooperative manner; share socioeconomic benefits, and
promote regional peace and security. The development of shared and
accepted water resources management technologies is an important element
in achieving this common vision.
Solution
The Nile Basin decision support system (NB DSS) integrates climatological,
hydrological and environmental data with sophisticated water simulation
models, together with sector economic production models, cost-benefit and
multi-criteria analysis tools.
Value
The NB DSS provides accepted processes and tools for quantifying the
benefits of water and for sharing of information. It enables transparent and
objective prioritisation of investments and contributes to sustainable water
resources management in the Nile Basin.
“The Nile Basin decision support system will provide the basis for agreement on
and development of sustainable water resources projects in the Nile Basin.”
Dr. Abdulkarim H. Seid, DSS Lead Specialist
Water Resources Management Project, Nile Basin Initiative

30. Why a Nile Basin DSS?
Objective:
To enhance capacity to support basin wide
communication, information exchange, and identifying
trans-boundary opportunities for cooperative
development of the Nile Basin water resources.
The Nile Basin DSS is expected to be an agreed upon tool that will be
accepted and used by all riparian countries in the management of
the shared Nile water resources.

31. NBI Institutional Mandates
NBI-Secretariat
Objective: Achieving efficient trans-boundary management and
optimal use of Nile Basin water and water-related resources
Basin Development Planning related
– Coordination for Subsidiary Action Programs
– Support investment financing, mobilization of funding
resources
– Basin-wide river operations policies

32. The NB DSS / Institutions
• Regional level
– Regional Nile Basin DSS Center
(NBI, Addis Ababa)
• Sub Regional Level
– ENTRO (Eastern Nile)
– NELSAP (Nile Equatorial Lakes)
• National Level
– National DSS unit in each of the 9
countries (4 staff pr. Country).

33. NB DSS - Areas of Concern
(determined through stakeholder consultation)
Water resources development: main focus on interventions that alter
the time and space distribution of water in the basin; involve physical
structures.
Optimal water resources utilization: Main focus on those planning
decisions required to enhance utilization of available water resources,
mainly through non-structural interventions.
Energy development (hydropower): focuses on development of
hydropower potentials in the basin.
Rain-fed and irrigated agriculture: area focuses on assessing
current productivity and production levels of both rain-fed and irrigated
agriculture supporting efforts to increase food production through
relevant interventions, such as in the planning of irrigated agriculture.

34. NB DSS - Areas of Concern
(determined through stakeholder consultation)
Coping with floods: main focus in the first phase of the DSS shall be
to provide information on characteristics of flood prone areas, flow
generation, assessing impacts (or benefits) of storage reservoirs on
flood control, etc.
Coping with droughts: support drought management efforts,
including the planning for adaptation to climate change and variability.
Watershed and Sediment Management: evaluation of impacts of
alternative land use/cover on the hydrology of the river system, the
estimation of sediment yield, and reservoir sedimentation.
Navigation: focus to identify how navigation might be affected by
contemplated interventions and support efforts to minimize the adverse
impacts. In addition, navigation benefits shall be considered in the
planning and management of storage schemes.
Cross cutting issues: Climate change and water quality

35. The DSS Platform
Core
Users
Notification workgroups Time
series
GIS
Rules
Data broker
Uncertainty DIMS
Job scheduling
Database WEB
Publishing
Time series
GIS Scripting
Data Models
assimilation
Scenarios
Users Spreadsheets
Events & alarms
Meta data
Change log
Models
Workflows
Scenarios
On-line data
MCA/CBA
Real Time Linked
Optimisation
models
Ensembles Indicators
Modeling

36. Case: Sava

37. Development of Upper Sava Flood Forecasting
System
- Sava Basin -

38. Development of Upper Sava Flood Forecasting
System
- Slovenian Model -
Key Figures
10880 km2
Catchment
Automatic
forcasts
issued each
hour for the
next 6 days
Forecasting
at 40
Locations

39. Development of Upper Sava Flood Forecasting
System
- Model Development -
MIKE11 model includes:
- Modelling of 40 sub-basins
- Hydrodynamic modelling of Sava and 20 trib.
- Modelling of all important Structures
- Comprehensive model calibation/verification
Forecasting based on:
- Online data from Hydrometric network
- Input from meteorological models:
(INCA,Aladdin,ECWMF)
(Example from model calibration at one of the 40 forecasting locations)
- Real time modelling with MIKE 11 including
data assimilation at all forecasting locations

40. Development of Upper Sava Flood Forecasting
System
- Implementation Schedule -
2010 Month 6
Completion of MIKE 11 forecasting model
- Forecasting at 40 locations
2010 End of Year
Real Time operation – WEB dissemination
2011 -
Further Upgrading of Forecasting System
- Flood mapping in selected area
- Inflow forecasting
Provision for upgrade to entire Sava basin

41. Thanks for your attention
jhm@dhigroup.com