Extreme Flooding, Policy Development, and Feedback Modelling Evan Davies and Slobodan Simonovic Civil and Environmental Engineering The University of Western Ontario London ON Canada Flood 2008 Conference

Presentation Outline Introduction Model Description Experimentation Conclusions

Introduction: Goals 1. Develop integrated model and apply to extreme flooding 2. Simulate long-term impacts of extreme flooding on socio-economic and natural systems 3. Stress importance of feedbacks Understanding  better policy Society Economy Environment Introduction Natural ChangeSocio-economic Change Extreme Flood

Rationale Floods are basically natural  Precipitation  Runoff Hazard is of human-origin  Settlement patterns  Land-use patterns  Flood defences Introduction

Feedbacks and Extreme Flooding In flooding, natural and anthropogenic systems interact  Realization underlies IFM Integrated Assessment approach  Feedback is crucial  Simulation modelling! Introduction

Model Structure Model components (8):  Carbon cycle  Climate  Water Quantity  Water Quality  Surface Flow  Population  Land Use  Economy Clearing and Burning Land Use Emissions + Carbon Climate Land Use + + Temperature Atmospheric CO 2 Water Stress Industrial Emissions − Surface Water Availability Water ConsumptionPopulationEconomy Surface Flow Temperature Consumption and Labour + +− GDP per capita + Water Quality Water Quantity Wastewater Treatment Wastewater Reuse Wastewater Treatment and Reuse − − + + − Carbon Absorption Atmospheric [CO 2 ] Temperature Change Water Use Wastewater treatment and reuse Water scarcity Renewable flow in changing climate Population growth = f(water scarcity) Biome coverage Human action GDP change Carbon tax Emissions Model Description

Model Characteristics Number of Model Elements:  740 named variables ‘Variables’: ~1600 (incl. arrays) Constants: ~470 (incl. arrays)  230 Stocks (many in arrays)  2300 total 600 equations (99 are critical) Thousands of feedbacks  Population: 4468 loops  Water stress: 2756 loops  Economic output: 203 loops  Industrial emissions: 47 loops Model Description

Work in Context Other models available:  Integrated Assessment Models IMAGE 2.0 (Alcamo et al., 1994) TARGETS (Rotmans and DeVries, 1997) World3 (Meadows et al., 2004)  Climate-Economy models DICE, RICE (Nordhaus and Boyer, 2000) ICAM-1 (Dowlatabadi and Morgan, 1993)  Water Use/Hydrological Models WaterGAP2 (Alcamo et al., 2003) WorldWater (Simonovic, 2002) Model Description

Simulating Flooding Floods affect:  Water quality  Infrastructure  Agriculture and crops  (Human health) But to different degrees… Experimental Approach

Experiments Run three experiments  Small flood  Medium flood  Large flood One year duration of direct effects Global Resolution Global Resolution Annual Cycle Annual Cycle Compare with Base Case Experimental Approach Capital Irrigated land Wastewater Treatment Water Reuse Agricultural Pollution Impose change on:

Results: Direct Effects After one year, changes in  Available surface water  Capital stock  Irrigated area  Wastewater treatment  Wastewater reuse  Water withdrawals Results

INDIRECT Effects The focus of the exercise… The flooding causes  No behavioural change  Long-lasting damage Results

Indirect Effects Feedback Feedback Effects  Even less-direct effects of flooding… Results Switch (1)(2)

Explanation (1) Why the water stress switch?  Reuse tops out  Agricultural withdrawals  Polluted surface water  Effective Withdrawal Results

Explanation (2) Why the population difference?  Water stress drives population growth Higher stress  lower growth Lower stress  higher growth Results

Conclusions feedback-based Developed feedback-based model  Physical and socio-economic sectors  Closed-loop structure Flood Experiments  Impose direct effects, simulate long-term  Long-term damage to Infrastructure, Water quality  Led to Higher water stress Lower population Illustrate IA modelling framework

Conclusions Cost of the approach:  Sacrifice resolution for completeness Benefits of the approach:  Connect Socio-economic and Physical Systems  Identify and understand causes  Analyze system behaviour

Publications Model structure, behaviour & applications Available from