Dti Sam Project. Development of a risk based procedure and supporting tools for urban drainage. SAM Project partners - research

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1 Dti Sam Project SAM : System-based analysis and management of urban flood risks Development of a risk based procedure and supporting tools for urban drainage Dr Yannick Cesses Project Objective Research to develop a risk based procedure for drainage analysis and management Aiming to overcome some of the limitations of current methods Follow the trend already set by River and Coastal defence Partners 12 partners across the drainage industry Value 1,573,000 (DTI Funding 50%) Duration 3+ years (March 2006 June 2009) IAHR UK Section 16/09/2010 SAM Project partners - research SAM Project partners industry partners

2 Predict ed O bs erved Drainage engineering evolution The risk method for drainage analysis Health Disease Odour Level of service 30 year flooding protection 100 year flooding protection Environment awareness & protection Sewerage separation SUDS < Integrated drainage > Risk based approach Consequences Cost / Social / environment Current tools Current limitations to drainage engineering Wallingford Procedure (1981) (Wassp, Wallrus, HydroWorks, Infoworks) Focused on system performance Analysis of system performance based on design storms Matrix of Return Period and Duration events 1. We know rainfall does not fall uniformly all over a large catchment and flooding arrives at different times so how can we do properly integrated drainage assessment? Verification Plot Ryde Catchment Event D, Site People don t care who s flood water has caused the damage to their property Discharge (m/s) Time (minutes)

3 SAM research topic areas Spatial time series rainfall (2D) Stochastic rainfall generators and data Newcastle University & Imperial College base and tools for spatial rainfall events Assess the difference between using 2D rainfall and uniform rainfall on urban drainage systems Develop a risk based procedure RFSM (rapid flood spreading tool) SAM-UMC (integration of for multiple runs) Risk shell for multiple runs and analysis Solutions development using risk based optimisation Generation of 2D rainfall Imperial College & University of Newcastle Stochastic models 2D time series rainfall 2 approaches Newcastle: data minimising approach, high and low resolution data (nested grids spatially and temporally) Imperial: high resolution data (fixed grid) Calibrated to radar data only 4 years of Nimrod data Prototype useable tools Imperial College Newcastle Management Event analysis, selection and export tool Rainfall Files CellID Time depth 1 1 st Jan : st Jan : st Jan : st Jan : st Jan :20 3 Rainfall Database Rainfall Processing Tool Event analysis and selection Review summary statistics to support selection Monthly / seasonal / annual rainfall totals, no. of wet days, annual maximum rainfall depth Identify localised intense events Identify all events that meet user-defined criteria (e.g. threshold intensity) in any cell within the study area/catchment Identify events over larger areas Amount of Data > 200G Identify all events that meet user-defined criteria (e.g. threshold intensity) over a study area or entire catchment

4 Network flood volume analysis and results FEH 95% upper bound FEH Result: scattering ellipses (2 correlated dependent variables) FEH Uniform rainfall: 10% difference Uniform Spatial rainfall: 40% difference Rainfall deviation Flood volume analysis 1D / 2D deviation Flood volume deviation Flood volume deviation *100% Flood volume deviation in function of the size of the catchment Area in ha System Loads System States System Loads System States Fully operational Single asset failure Structural Single asset failure Blockage System States 5000 nodes Multiple system failure Blockage + structural Dry Time 100 years Frequent rainfall Extreme rainfall System States Fully operational Single asset failure Structural Single asset failure Blockage Multiple system failure Blockage + structural Dry If Foul If Foul If Foul Time Frequent rainfall Extreme rainfall 20,000

5 Rapid Flood Spreading Rapid Flood Spreading RFSM Developed specifically for probabilistic analysis Simple overland flooding tool Rapid NAFRA (National Flood Risk Assessment) Multiple loading events and defence system states, national-scale ling Decision Support Framework (MDSF) Flood risk analysis software product being developed for use by the UK Environment Agency staff, catchment scale Development under DTI SAM Application to the urban environment and below-ground drainage systems state Flood routing calc state Flood routing calc Ground Ground

6 state Flood routing calc state Flood routing calc Ground Ground state Flood routing calc Flood volumes state Flood routing calc Flood volumes Ground Ground

7 state Flood routing calc Flood volumes Flood depths state Flood routing calc Flood volumes Flood depths Ground Ground Risk based tools structure state Flood routing calc Flood volumes Flood depths Flood damages Rainfall Events InfoworksCS s Ground SAM-UMC SAM-UMC

8 Design rainfall - Time series - No Define Return Period (Start at 1 or 2 years) No flooding Define a duration (Start at 30min) calculation All critical durations and return periods run? Yes convergence at control nodes \ all nodes? = marginal increase (1-5%) Yes for network & Impact Zones No 8 hrs Bottom end 5 hrs 2 hrs 30 min Return Period Top of system Extend rainfall series No Evaluate extreme event threshold Process rainfall series Run each event Extreme events Normal events Dry event calculation convergence at control nodes \ all nodes? = marginal deviation (1-5%) Yes for network & Impact Zones AVG D avg Run ID categories at each node Sub-division of information for Weather 300 System state Dry weather Frequent event Extreme event Fully functional NO DAMAGE NO DAMAGE DAMAGE Collapse(s) and/or Blockage(s) DAMAGE (IF FOUL PIPE) DAMAGE DAMAGE at each node ( ) Node ID Structural Blockage Hydraulic ( ) Progressive 1.00E E E E E E E E E E E RP (years)

9 Attribution of of (annualised) Risk Expected Annual () calculated for each Impact Zone Integration of all possible events to find an annualised value of Likelihood x Consequence Critical duration of each node is used for each return period Probability P 1 P 10 P 20 of (annualised) Risk Impact zones and Assets Expected Annual () calculated for each Impact Zone & manhole Integration of all possible events to find an annualised value of Likelihood x Consequence Critical duration of each node is used for each return period Impact zone manhole Probability P 1 P 10 P 20

10 a function of pipe length Flood frequency (level of service) frequency is still probably a fundamental measure An value could be from massive damage from very rare events, or damage from relatively frequent events. Optimisation is a measure of performance of the existing system and does not tell us how to manage or to improve it. Solutions development for IZs and Assets does not solve any flooding problems, it just provides a measure of performance (current or future). Option 1 Traditional technique use engineering judgement Base decisions on reducing (or zero) flooding at selected Impact Zones Then re-evaluate, assess cost-benefit Option 2 Optimisation use GA technique for evaluating specific objective function Maximise reduction for given investment Minimise investment for specified reduction (network, nodes or Impact zones).

11 Solutions Risk based Optimisation Solutions development Advantages Efficient search for possible solutions Freedom to consider a range of possible changes to network Disadvantages Need to limit number of options to make run-times manageable requires pre-processing of the model Careful selection of search criteria Capital cost ( ) 4,000, ,500, ,000, ,500, ,000, ,500, ,000, , Generation 1,200, ,000, , , , , ( ) Conclusion DTI SAM is a radical new approach to analysis of system performance & asset management. Extendable to all aspects of drainage (environmental impact etc.) subject to ability to use appropriate cost functions as a measure of impact) Where do we go from here? Discussion on the appropriateness of using Is the same value of appropriate for foul and surface water flooding? Is an area with the same value of as another, that suffers from frequent rainfall compared to rare events, of more or less importance to provide a solution? Weighting is effectively provided to frequent events Is fair? (Equity is a primary measure of Sustainability)

12 on flooding could extend to cover: Property damage, Infrastructure damage, Flood incidence costs, Social trauma and health, Mortality National productivity impact And then also: Environmental impact Pollution, Biodiversity, Carbon?? discussion Prognosis for the future DTI SAM is a radical new approach to analysis of system performance & asset management in line with the new SRM. Future take-up of the method requires: Support from Policy makers and Regulators (OFWAT, Environment Agency, Defra) Is this a way of measuring Sustainability or Resilience?? Perhaps is not a universally appropriate indicator