Lecture 15: Flood Mitigation and Forecast Modeling

Transcription

1 Lecture 15: Flood Mitigation and Forecast Modeling Key Questions 1. What is a 100-year flood inundation map? 2. What is a levee and a setback levee? 3. How are land acquisition, insurance, emergency response used to mitigate a flood 4. How is streamflow forecasting used to mitigate a flood? 5. What is the difference between weather and climate? 6. What has caused the climate to change in the last 100 years? 7. How will future climate impact snow and streamflow in the Nooksack basin? Niigata Japan, 1964 liquefaction Nooksack River

2 100-year Floodplain Map

3 Mitigation: 100 Year Flood Map

4 Mitigation: Structural Techniques 1. Levees are engineered embankments designed to contain the river

5 Mitigation: Structural Techniques Levees are designed to contain floods along most of the lower Nooksack (floods that range from 5 to 100 year return periods) levee

6 Mitigation: Setbacks Levees The Soldiers Home Setback Levee on the Puyallup River near Orting.

7 Mitigation: Structural Techniques 2. Dams can store and slowly release water storage capacity Δ = monitored release

8 Mitigation: Land Acquisition

9 Mitigation: Nooksack River

10 Mitigation: Insurance

11 Mitigation: Emergency Response

12 Mitigation: Forecast Modeling

13 Modeling the effects of climate change forecasts on streamflow in the Nooksack River basin

14 Climate versus Weather Weather: short-term, local variations in atmospheric conditions (one monthly average represents weather) Average January temperatures at the Clearbrook weather station.

15 Climate versus Weather Climate: long-term average weather conditions (30 years or longer) (collection of monthly values represents climate) What does the trend line indicate? Average January temperatures at the Clearbrook weather station.

16 Reconstructed temperatures for the past 2000 years

17 Measured temperatures for the past 200 years

18 97% of active, publishing climatologists think human activities have changed the climate n = 3146

19 Greenhouse Gases

20 Greenhouse Effect: CO 2 and other greenhouse gases trap radiated heat from the Earth and increase the temperature

21 Anthropogenic (human) causes for increased CO 2 Burning of fossil fuels Deforestation CO 2 source trees are a CO 2 sink

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23 South Cascade Glacier One of three benchmark Glaciers that have been established in a USGS glacier monitoring program

24 South Cascade Glacier One of three benchmark Glaciers that have been established in a USGS glacier monitoring program

25 Mote et al. (2008) Averaged sea level at stable tide gauge sites

26 Futuristic CO 2 Emission Scenarios

27 General Circulation Models (GCM) Emission Scenarios About 40 institutions world wide run GMCs

28 Modeled Temperature Predictions based on different CO 2 emission scenarios

29 GCM: NASA s GISS model

30 Modeling the effects of climate change forecasts on streamflow in the Nooksack River basin

31 Goal of Research To predict impact of climate change on snowpack and streamflow in the Nooksack River basin

32 The Nooksack River is a snow dominated basin that is sensitive to temperature changes spring peak due to snowmelt Discharge at North Cedarville, WA Water Year 2009 (Oct 2008 Sept 2009)

33 no snowpack so rain falls on exposed bedrock and thin, wet soils and produces a high peak snow pack Hydrograph Hydrograph Hydrograph Hydrograph more volume but less peaked Time Time

34 Approach Spatial characteristics of the Nooksack River basin Predicted climate data DHSVM Hydrology model Predict Future: Snow Water Equivalent (SWE) Streamflow Peak Flows Data processing

35 Methods 1. Hydrologic Model Set-up, Calibration, & Validation 2. Downscaling & Validation of Climate Change Forecasts 3. Hydrologic Modeling

36 Methods: DHSVM Distributed Hydrology Soil Vegetation Model DHSVM calculates a water and energy budget on each grid cell for each time step inputs - outputs = change in storage

37 The DHSVM also predicts snow accumulation and melt

38 Methods: DHSVM Spatial Input DEM Watershed Boundary Stream Network Soil Thickness Soil Type Landcover

39 Methods: DHSVM Meteorological Input Temperature Precipitation Wind Speed Relative Humidity Shortwave Radiation Longwave Radiation North Shore Weather Station, Lake Whatcom

40 DHSVM: Streamflow Calibration Calibration adjustment of model parameters to mimic an observed dataset Photo: USGS USGS Stream gauge at Cedarville

41 DHSVM: Calibration Nooksack River, WY Initial Simulation Daily Mean Streamflow (cfs) Cedarville - observed Cedarville - simulated 1Jan2006 2Jul2006 1Jan2007 2Jul2007 Date Nooksack River, WY After Calibration Daily Mean Streamflow (cfs) Cedarville - observed Cedarville - simulated 1Jan2006 2Jul2006 1Jan2007 2Jul2007 Date

42 DHSVM: Calibration & Validation Validation comparison of simulated data with observed data for a time period not included in the calibration Nooksack River, WY Daily Mean Streamflow (cfs) Cedarville - observed Cedarville - simulated calibration validation 1Jan2006 1Jan2007 1Jan2008 1Jan2009 Date

43 DHSVM: SWE Calibration Calibration adjustment of model parameters to mimic an observed dataset Snotel Stations Photo: NRCS

44 DHSVM: Calibration & Validation Wells Creek Snotel (NF), WY Daily Mean SWE (m) observed simulated 1Jan2006 1Jan2007 1Jan2008 1Jan2009 Date Middle Fork Snotel, WY Daily Mean SWE (m) observed simulated 1Jan2006 1Jan2007 1Jan2008 1Jan2009 Date

45 Methods 1. Hydrologic Model Set-up, Calibration, & Validation 2. Downscaling & Validation of Climate Change Forecasts 3. Hydrologic Modeling

46 Emissions Scenarios IPCC 2001

47 Methods: Climate Change Forecasts Three General Circulation Models (GCMs) : 1. IPSL_CM4_A2 Institut Pierre Simon Laplace (with A2) 2. Echam5_A2 Max Planck Institute for Meteorology (with A2) 3. GISS_ER_B1 Goddard Institute for Space Studies (with B1) 2040s Changes in Temperature and Precipitation Mote and others, 2005

48 Methods: GCM Downscaling GCM scale of 100s km regional scale of 10s km local station CIG, 2010 Monthly time scale

49 Methods: GCM Downscaling Empirical Cumulative Distribution Functions (ecdf) April Mean Temperature April ecdf Frequency Non-Exceedance Probability Abbotsford, Mean Temperature (C) Mean Temperature (C)

50 Methods: GCM Downscaling April ecdfs Shift 50-year historical time series based on 31-year forecast period Non-Exceedance Probability Abbotsford, s GISS Forecast, Mean Temperature (C) Result: 50-year forecast Non-Exceedance Probability Abbotsford, GISS Forecast, Combined 2050s Forecast April ecdfs Mean Temperature (C)

51 Methods: GCM Downscaling Each forecast is based on the Abbotsford time series Monthly Mean Temperature, Temperature (C) Abbotsford GISS_B Forecast Month

52 Methods: GCM Downscaling Each forecast is based on the Abbotsford time series Monthly Mean Temperature, Temperature (C) Abbotsford GISS_B Forecast Month

53 Methods: Validation of Downscaling outlier 25 th 75 th percentiles median Monthly Mean Temperature, minimum Temperature (C) Abbotsford GISS_B1 Echam_A2 IPSL_A Month

54 Methods: Local Forecasts Monthly Mean Temperature Abbotsford GISS_B1 ECHAM_A2 IPSL_A Month Temperature (C)

55 Methods: Local Forecasts Total Monthly Precipitation Abbotsford GISS_B1 ECHAM_A2 IPSL_A Month Precipitation (mm)

56 Methods: Processing of Forecasts 1. Apply monthly ΔT to daily Abbotsford data 2. Disaggregate daily data to a 3-hour time step 3. Derive other 3-hour meteorological input from temperature and precipitation Shortwave Radiation Longwave Radiation Windspeed Relative Humidity

57 Methods 1. Hydrologic Model Set-up, Calibration, & Validation 2. Downscaling & Validation of Climate Change Forecasts 3. Hydrologic Modeling

58 Approach Spatial characteristics of the Nooksack River basin Predicted climate data DHSVM Hydrology model Predict Future: Snow Water Equivalent (SWE) Streamflow Peak Flows Data processing

59 Results: SWE Monthly Mean SWE at MF Snotel - GISS_B1 SWE(m) Month Monthly Mean SWE at MF Snotel - IPSL_A2 SWE(m) Month

60 Results: SWE Monthly Mean SWE at MF Snotel - GISS_B1 SWE (m) Month Monthly Mean SWE at MF Snotel - IPSL_A2 SWE (m) Month

61 Results: Streamflow Monthly Median Streamflow - GISS_B1 Streamflow (cfs) Month Monthly Median Streamflow - IPSL_A2 Streamflow (cfs) Month

62 Results: Streamflow Monthly Median Streamflow - GISS_B1 Streamflow (cfs) Month Monthly Median Streamflow - IPSL_A2 Streamflow (cfs) Month

63 Results: Peak Flow Events Annual Peak Flows (WY ) - GISS_B1 Streamflow (cfs) 0e+00 4e+04 8e+04 Ferndale-observed Cedarville-simulated Annual Peak Flows (WY ) - IPSL_A2 Streamflow (cfs) 0e+00 4e+04 8e+04 Ferndale-observed Cedarville-simulated

64 Results: Peak Flow Events Simulated Peaks Above 30,000 cfs Frequency GISS_B1 Echam_A2 IPSL_A Forecast Period IPSL_A IPSL_A IPSL_A IPSL_A Frequency Frequency Frequency Frequency Month Month Month Month

65 Temperature or Precipitation? Monthly Mean Temperature Predicted increases in temperature and precipitation More agreement on temperature trends Temperature (C) Abbotsford GISS_B1 ECHAM_A2 IPSL_A2 Previous regional studies indicate that temperature is the driving factor in changes to SWE (Hamlet et al., 2005, Mote et al., 2005, Mote et al., 2008) Precipitation (mm) Month Total Monthly Precipitation Abbotsford GISS_B1 ECHAM_A2 IPSL_A Month

66 Conclusions SWE will decrease Timing of peak SWE and of the spring melt peak in the hydrograph will move earlier in the year Winter streamflow will increase, summer streamflow will decrease Peak flow events will increase in magnitude and frequency Extent of change depends on temperature change Photo: John Scurlock

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