Jacob Høst-Madsen

Effects of climate change on flood risks

Director, consultancy

Climate change is here and will have impact

Water Stress Changes by 2025

Vorosmarty et al., 2000

80% of future

stress from

population

& development

not

climate change

Climate change adaptation: Many stakeholders

• Countries

• Ministries

• EU

• Insurance industry

• Local communities

• Water supply works

• Citizens

• Regions

• Health authorities

• Emergency units

• ……….

What is IWRM ?

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!

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.

Water governance and IWRM:

A never ending cycle!

Vision

Strategy

Situation analysis

Implementation

Monitoring

IWRM Plan

AwarenessParticipationCommitmentCapacity

WR management issues

The basin as the basic

management unit

Opportunities for modelling

IWRM where?

IWRM processes focus on critical

water resources issues of any basin

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

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?

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)

Example: Guidelines for the analyses of the

impacts from climate changes on sewer systems

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 ?

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

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

Example: Greve, Denmark

Example – Greve Denmark

The intelligent city

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

Intelligent planning - Porto Alegre - Brazil

Get the water out of the sewerage system

DHI Climate Change DSS Powerful decision support for climate change

adaptation

Applications

• Analyses of impacts from different

emission scenarios and different

global circulation models

• Analysis of climate vulnerability,

undertainty, and downscaling

• View and display information

concerning current and future climate

scenarios

Features

• Current and future climate information

• Scenario data

• Vulnerability information

• Impacts information

• Adaptation impacts

• Analysis tools

• Data exchange

• Downscaling

• Uncertainty

• Comparison of adaptation measures

• Forum for decisions

• Presentation and analysis

• Database.

Benefits

• Strong decision support

• Easy analysis from Global

Circulation model to local impact

• Output tailored for stakeholders

and decision makers

• Part of DHI Solution Software

Downscaling & corrections

GCM projections:

Dynamical

Downscaling

RCM projections:

Local Climate simulations:

Statistical Downscaling Bias

Corrections

Weather generators,

….

Local Hydrological simulations:

Scenario 1 Scenario 2

Climate change tool In MIKE by DHI

Case: The Nile Basin Decision Support System

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

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

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

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.

NBI Institutional Mandates

Basin Development Planning related

– Coordination for Subsidiary Action Programs

– Support investment financing, mobilization of funding

resources

– Basin-wide river operations policies

NBI-Secretariat

Objective: Achieving efficient trans-boundary management and

optimal use of Nile Basin water and water-related resources

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).

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.

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

NB DSS - Areas of Concern (determined through stakeholder consultation)

Real Time

Modeling

Core

Database

Time series

GIS

Models

Scenarios

Users

Meta data

Change log

The DSS Platform

On-line data

Workflows

Events & alarms

Rules

Notification

Data

assimilation

Job scheduling

Uncertainty

Users

workgroups Time

series GIS

Data broker

DIMS

WEB

Publishing

Scripting

Spreadsheets

Optimisation

Ensembles Indicators

Models

Scenarios

MCA/CBA

Linked

models

Case: Sava

Development of Upper Sava Flood Forecasting

System

- Sava Basin -

Key Figures

10880 km2 Catchment

Automatic forcasts issued each hour for the next 6 days

Forecasting at 40 Locations

Development of Upper Sava Flood Forecasting

System

- Slovenian Model -

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) - Real time modelling with MIKE 11 including data assimilation at all forecasting locations

(Example from model calibration at one of the 40 forecasting locations)

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

Thanks for your attention

jhm@dhigroup.com