Presentation on theme: "Presentation to Safe & SURE project team PhD student: Seith Mugume First supervisor: Professor David Butler Second supervisor: Dr. Diego Gomez 1 PhD Research."— Presentation transcript:
Presentation to Safe & SURE project team PhD student: Seith Mugume First supervisor: Professor David Butler Second supervisor: Dr. Diego Gomez 1 PhD Research Title: A resilience approach to urban flood risk management under future conditions in a developing country city
Presentation outline Background Scope of PhD research Traditional decision making approaches Resilience approach to decision making under uncertainty Concepts, frameworks and definitions of resilience Quantitative assessment of resilience Proposed research methodology Next steps 2
Global potential risk of urban flooding 3 Source: UN Multiple & uncertain drivers of future change Extreme rainfall events Nutrient and pollutant loading Urbanisation effects Land use change Socio-economic trends Transient shocks vs. Chronic stresses
Broad research areas Sustainability Resilience Threat MitigationSafety Impact- Level of service Consequence UWS Society Economy Environment Climate Population Regulation Water scarcity Urban flooding River pollution VulnerabilityAdaptation Refined Safe & SuRe concept Butler (2013)
Scope of PhD Thesis Investigate the use of resilience approach to study the impacts of future change on urban drainage system performance To evaluate appropriate response strategies to reduce pluvial flood risk in a developing country city 5 Pluvial flooding in the UK, Source: RAPIDS Project risk/rapids.html risk/rapids.html 2010 flooding in Dhaka, Bangladesh, Source: linked-to-climate-change/
Traditional decision making approaches in urban flood management 6 Increasing envelope of uncertainty Top-down (Cause-Effect) Impact models (e.g. urban flood models) Global and Regional Climate models Response options Emission scenarios Risk Assessment R = f(failure probability, consequence) Bottom-up (Vulnerability-Led) Develop adaptation response options Identify coping factors Response options Assess vulnerability (local scale) Based on Wilby & Dessai (2010)
Synthesis of global climate risk management Carter et al., Response policiesRisk quantification
A resilience approach to decision making under uncertainty 8 System Resilience Impact of disturbance Assess proximity to critical performance thresholds Investigate response & recovery Evaluate impact on level of service Evaluate response strategies How much disturbance can a system cope with ? versus What if future change occurs according to scenario x?
Key conceptual definitions 9
Characterisation and definitions of resilience 10 Stability within an attractor basin Remain within critical ecological thresholds System response Recovery Adaptive capacity Anticipation Coping capacity Recovery capacity Resilience Holling, 1973; Cumming et al., 2005; Wang and Blackmore, 2009; Blockley et al., 2012 and Cabinet Office, 2011 Ecological resilience Socio- ecological resilience Socio- technical resilience Infrastructure system resilience Institutional or organisational resilience Engineering resilience Maintain system structure and function Transitions management
Resilience against crossing critical performance thresholds 11 A measure of the capacity of a system to absorb disturbances and still persist with the same basic structure (Holling 1973, Walker et al 2004, Cumming et al 2005) Tendency to remain stable around an attractor basin Maintenance of system identity Attractor basins & thresholds (Walker et al 2004) Key resilience properties Resistance Persistence Stability Multiple static steady states
Resilience for response and recovery 12
System response curve Flood damage Flood depth 0 Failure consequence Exceedance Mens et al 2011, Butler 2013 Response vs disturbance What of response vs. time?
System performance curve 14 Adapted from: Wang & Blackmore (2009) & Butler (2013)
Categorising sub-properties of resilience 15
Quantitative assessment of resilience Working definition of resilience: The ability of an urban drainage system to maintain an acceptable level of functioning and to quickly recover from a shock or disturbance Resilience indicators 16
Resilience indicators 17 Examples of resilience indicators (de Bruijn, 2004) Amplitude: Measure of the impact on flood waves on system performance Graduality: A measure of a change in system response with respect to a change in the magnitude of flood waves Recovery rate: a measure of the rate at which the system returns to a normal or stable state after the flood event
Proposed resilience indicators for urban pluvial flooding 18 #Resilience property Resilience indicators 1Resistance threshold Duration of sewer surcharging 2Response timeDuration of manhole flooding Duration of surface/property flooding 3System response Flood depth Flooded area 5AmplitudeGraduality, G Expected annual damage (EAD) 4Recovery rateRecovery time Qualitative measures of adaptive capacity Urban drainage model simulations Qualitative study
Resilience based evaluation methods 19 Robust adaptation framework Real ‘In’ Options Adaptation Mainstreaming Adaptive Pathways Adaptive Policy Making
Quantifying resilience indicators Urban flood modelling o Rainfall run-off estimation o Part-full flow in sewers o Sewer surcharging o Surface flooding MIKEURBAN (Coupled 1D-2D model) 1D sewer flow modelling SWMM 5.0 MOUSE 2D surface flow modelling Qualitative study of acceptability thresholds Delphi technique Interview of key stakeholders 20 Example of network typology, land use and above and below ground networks (Barreto 2012)
6. Next steps 21 Identify set of resilience indicators to be used in case study Obtain data for a ‘test’ case study Urban drainage network Rainfall data Land use DEM Urban drainage model simulations using a ‘test’ case study Preliminary analysis of urban drainage network resilience
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