Hydraulic Modelling for Real Time Flood Forecast Applications

Transcription

1 BHS/CIWEM SW Branch Meeting Hydraulic Modelling for Real Time Flood Forecast Applications Yiping Chen 20 June 2007

2 Introduction Hydraulic River Modelling: Washland (Floodplain) Modelling Techniques Integrated Flood Forecasting Approach Flood Forecasting Applications Forecast Uncertainties

3 Hydraulic River Modelling - Channel River = River cross-sections + distance between them Conservation of mass and momentum (St Venant Eqns) Variation of discharge and water level at each cross-section. Can predict impact on flood levels of loss or creation of floodplain volume Q Q t h Δx Q Attenuation Q Q t t

4 Hydraulic River Modelling Washland (1) Can be modelled as flood cells (2) Can be modelled by secondary flood channels Q (3) Can be modelled by extended cross-sections h Δx Q Washland Linked by lateral spills t Q

5 Washland Modelled as Flood Cells Channel Floodplain interactions: Floodplain areas obtained using LiDAR data Lateral spill unit used to link channel and floodplains Reservoir units used for over bank flows over floodplains Elevation maod

6 Washland Modelled as Secondary Channels Channel Floodplain interactions: Floodplain XSs obtained using LiDAR data Lateral spill unit used to link channel and floodplains Secondary Channels used for over bank flows over floodplains

7 Washland Modelled as Extended Cross-sections

8 Integrated Flood Forecasting Approach Rainfall Evaporation Hydrodynamic model Rainfall Runoff model Continuous water levels Continuous runoff hydrograph

9 Information Flow in Real Time FF System WEATHER FLUVIAL TIDAL REAL TIME DATA Weather radar images / actuals Meteosat satellite images Automatic weather stations Rain gauges / snow fall River / reservoir levels / gate settings etc Tidal levels / wave buoys Wind speed / direction Triggers/ alarms FORECASTS 5-day / heavy rainfall / severe weather forecasts 0-6 hour radar / NWP forecasts e.g. Nimrod/HYRAD River flow forecasting models / catchment wetness estimation MORECS MOSES Estuaries 5 day storm surge forecasts Storm Tide Forecasting Service / Astronomical Tide Predictions Onshore wave estimates and overtopping models Alarms Figure 2. Possible information flow in a real time flood warning and forecasting system Dissemination Floodcall AVM / sirens etc Emergency services Flood wardens Local authorities Utilities Flood defence staff River / reservoir control structures Environment Agency Other (Met Office etc) Archiving / post event analysis

10 Rainfall Runoff Processes RAINFALL POTENTIAL EVAPORATION MODEL PARAMETERS RUNOFF COMPONENTS EVAPORATION RECHARGE

11 PDM Schematic

12 PDM Parameters Parameter Description Function rainfac Surface flow Controls runoff volume, by scaling the rainfall input cmin Baseflow Minimum storage capacity cmax Baseflow Maximum storage capacity b Surface flow Exponent of Pareto distribution controlling spatial variability of store capacity be Baseflow Exponent in actual evaporation function k1 Surface flow Time constant for linear reservoir K2 Surface flow Time constant for linear reservoir kb Baseflow Baseflow time constant kg Baseflow Groundwater recharge time constant st Surface flow Soil tension storage capacity bg Baseflow Exponent of recharge capacity qconst Surface flow Flow constant to raise or lower flow levels tdly Baseflow Time delay applied to events

13 PDM Calibration Baseflow Calibration - Daily data Flow (m^3/s) /02/ /05/ /09/ /12/ /03/ /06/ /10/2003 Date Daily Flows TSCAL Baseflow Rainfall PDM Calibration October 2000, December 2000 and December 2002 events Flow (m3/s) Hours since event start Observed Baseflow Component TSCAL Rainfall Intensity

14 Real Time Flood Forecast Modelling Application Case Study 1 Eden

15 Introduction In January 2005, over 1800 properties flooded in Carlisle An event more than 1 metre higher than any other in the previous 200 years Existing Eden FF model has been in use for several years Floodplains modelled by extended XS and significantly under-estimated flows and levels during the January 2005 flood event Atkins built a separate Flood Defence strategy model in 2005 for the Carlisle area with more details, more up-to-date survey and more realistic representations of floodplains Atkins were commissioned in 2006 to improve the Eden/Carlisle flood forecasting model based on the FD strategy model

16 Eden Catchment (2335 km 2 ) Carlisle

17 Model Configuration DS Boundary Greenholme Sheepmount Linstock Low Crosby Durranhill Warwick Bridge Denton Holme Botcherby Bridge Great Corby Cummersdale Harraby Green Armathwaite (no model node) Gauged Inflow Forecasting Point River Eden River Eamont River Irthing River Petteril River Caldew Udford Eden Hall (no model node) Temple Sowerby

18 ISIS FF model Schematic

19 FF Model Schematic (1140 Nodes) Sheepmount Irthing Caldew Petteril Eden

20 Model Runtime Performance Flood Events (Simulation Duration) Maximum Outflow (m 3 /s) Total Model Runtime (second) Number Used for Each Timestep 300s 150s 75s <37.5s Feb 1990 (80 hr) Feb 1995 (80 hr) Jan 1999 (80 hr) Jan 2005 (150 hr) year design (80 hr) year +20% (80 hr) year +30% (80 hr)

21 Model Convergence Performance Jan 2005 Flood Event 1% Probability

22 Model Validation 15.0 January 1999 Validation Event - Sheepmount Stage (maod) Flow (m 3 sec -1 ) /01/ /01/ /01/ /01/ /01/ /01/ Gauged Stage FF Modelled Stage 1999 Gauged Flow FF Modelled Flow 0

23 Rating Comparison 15 Sheepmount Rating Stage (maod) EA Rating Spot Gaugings Jan-05 (Rating Extrapolate) Flood Forecast Model V41_MODEL (100yr) ,000 1,200 1,400 1,600 1,800 Flow (m3/s)

24 Real Time Flood Forecast Modelling Application Case Study 2 Rother/Tillingham/Brede

25 Rother/Tillingham/Brede Catchment

26 Rother FF Model Schematic Udiam

27 Model Calibration Level (maod) Modelled Udiam Level Recorded Level (maod) Modelled Udiam Level Recorded /10 26/10 31/ /11 10/11 Udiam Level 15/11 Modelled Recorded Oct Event /12 19/12 24/12 29/12 03/01 08/01 13/01 18/01 Dec 2000 Event Level (maod) /01 14/01 24/01 03/02 13/02 Jan 2002 Event

28 Raingauge Problem 80 Crowhurst - February Flow (m^3/s) Rainfall (mm) /01/01 14/01/01 19/01/01 24/01/01 29/01/01 03/02/01 08/02/01 13/02/01 18/02/01 23/02/01 Date Observed Q TBR Computed Q Revised Q Infilled Rainfall TBR Record

29 Tillingham/Brede FF Model Schematic

30 Modelling Problem Recorded Hundredhouse Bridge Level Modelled Level (maod) /12 11/12 16/12 21/12 26/12 31/12 Dec Jan 2002 Hundredhouse Bridge Level Recorded Modelled Level (maod) /01 14/01 24/01 03/02 13/02

31 Longsection Profile Node Label TILL1_09277 TILL1_09239 TILL1_09202 TILL1_09165 TILL1_09146 TILL1_09136 TILL1_09126 Elevation (m AD) TILL1_09074 TILL1_09022 TILL1_08971 TILL1_08919 TILL1_

32

33 Site Investigation

34 Additional Survey Locations

35 Additional Survey Locations

36 Revised Longsection Profile Node Label Elevation (m A TILL1_09277 TILL1_09202 TILL1_09126 TILL1_09114A TILL1_09101 TILL1_09088 TILL1_09075 TILL1_09023 TILL1_08919 TILL1_08818 TILL1_ Node Label TILL1_09277 TILL1_09239 TILL1_09202 TILL1_09165 TILL1_09146 TILL1_09136 TILL1_09126 TILL1_09074 TILL1_09022 TILL1_08971 TILL1_08919 TILL1_08818 Elevation (m AD)

37 Improved Modelling Results Recorded Hundredhouse Bridge Level Modelled Recorded Hundredhouse Bridge Level Modelled Level (maod) /12 11/12 16/12 21/12 26/12 31/12 Level (maod) Dec 1999 Hundredhouse Bridge Level 7.5 Recorded Modelled /12 11/12 16/12 21/12 26/12 31/12 Level (maod) 7.0 Hundredhouse Bridge Level 6.8 Recorded Modelled Level (maod) /01 14/01 24/01 03/02 13/02 Jan /01 14/01 24/01 03/02 13/02

38 Tillingham Tidal Sluice Control

39 Tillingham Sluice Modelling Results 5 4 Rye Harbour Level Recorded Level (maod) /10 27/10 Tillingham 01/11 Sluice Level 06/11 11/11 Modelled Recorded 3.5 Level (maod) /10 27/10 01/11 06/11 11/11

40 Key elements of modelling success Good representation of the catchment hydrology Good representation of the river hydraulics (cross-sections, roughness, etc) & hydraulic structures (operations) Good representation of the interactions between channel and floodplains Good stage flow rating Good model calibration / validation Flood forecasting model must be robust and stable

41 Sources of Uncertainties Factor Typical sources of uncertainty Meteorological Weather radar Meteorological conditions (e.g. bright band, orographic growth, anomalous propagation-anaprop, attenuation etc) Physical siting of the radar relative to the catchment (distance, local topography, obstacles etc) Rain gauges Exposure and altitude Sampling errors (interval, tipping bucket size etc) Performance in snowfall, high winds, heavy rainfall etc Quantitative Parameters/spatial and temporal resolution/representation of Precipitation atmospheric and land surface processes etc Forecasts Representation of storm growth/decay and advection processes etc (Nimrod/NWP) Representation of local factors (e.g. orographic growth) Fluvial River Flow Monitoring Rating curve accuracy, particularly at high flows Influence of sedimentation, vegetation and debris Coastal (including STFS and TRITON) Coastal Monitoring Density of wave monitoring network (sampling error) Combination of wave and still water level Shallow water effects Instrument error Errors in estimating mean sea level Model Boundary Conditions Choice of model type and structure Errors transferred from mesoscale models to boundaries of STFS offshore surge model Grid resolution inadequate representation of local bathymetric and topographic features that cause changes in local water levels Coupling of offshore and nearshore models Calibration Availability of sufficient extreme events for calibration Skill of person calibrating the model Operational Changes in characteristics since model was calibrated Events outside the range of the model calibration Instrument/telemetry downtime problems Real Time Updating procedures Detection Currently no formal updating used, however, potential to use upcoast error to correct for downcoast sites Component Catchment averaging procedures (raingauge inputs) Choice of model type and structure Typical sources of uncertainty Representation of physical processes (topography, elevation etc) Type of rainfall event (convective, frontal, orographic etc) Rain gauge density and distribution Instrumental problems at one or more of the rain gauges used Lumped, semi-distributed, distributed rainfall inputs Representation of catchment runoff processes River channel and floodplain representation Under/over parameterisation (parsimony) Flood defence loading/fragility (if represented) Gate operations Representation of ungauged inflows Representation of abstractions/discharges Model calibration Effectiveness of optimisation routines Choice of optimisation criteria Availability of sufficient high flow events for calibration Skill of person calibrating the model Operational Changes in catchment/channel characteristics since model was calibrated Events outside the range of the model calibration Model stability problems Representation of initial/antecedent conditions Representation of snowmelt (if applicable) Instrument/telemetry downtime problems (rainfall) Real Time Updating procedures Forecasting Appropriateness for the type of model used Sophistication of calibration software Quality of the high flow data used both for calibration and in real time Event specific problems (backwater, bypassing, debris etc) Instrument/telemetry downtime problems (flows)

42 Ensemble Forecasting Source KNMI

43 Snowfall February 7 th /8 th Source Met Office

44 Probabilistic Forecasting- Source Met Office

45 Thank you Questions?