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Richard Koehler, PhD, PH
NOAA/National Weather Service
National Hydrologic and Geospatial
Sciences Training Coordinator
Using GIS to Visualize and Analyze
Environmental Time-Series Data
as Raster Maps
GIS Colorado Fall Meeting October 21, 2016
Source: nrcs.gov Source: noaa.govSource: usbr.gov
Quote
The application of GIS
is limited only by the imagination
of those who use it.
Jack Dangermond
Co-founder,
Time series in GIS
Two common approaches
1. Animate / time slider
Source: cuahsi.org
2. Line graphs
Source: esri
t5
t4
t3
t2
t1
Base map
• Most statistics are simple
Mean, median, variance, standard deviation, min, max
• Multiple streamflow metrics exist (170+)
• Need time-scale analysis to find patterns
• Visualization overlooked as an analysis method
• GIS - technology for data analysis, configuration and
visualization for spatial data
Magnitude 55%
Frequency 8%
Duration 26%
Timing 6%
Flow change 5%
Composition attributes
Data order not a factor
Configuration attributes
Data order is fundamental
Time series data analysis
– why not for temporal data?
Data source: NOAA
Data source: USGS
Time series data displays
Spaghetti plot
Kettle River near Laurier, WA
Data source: USGS
Day of Water Year
Discharge(ft3/s)
Assumption:
Lines lay within
a single plane
Water Year:
Oct 1 – Sept 30
Display evolution
New assumption:
Profiles stacked in
multiple planes
!
Tilt and rotate display
New perspective,
“aerial”
Hidden
axis
Spaghetti plot perspective,
“ground”
Wire diagram
Temporal map
• Dual timescale as X, Y
• Common framework
• Visualization options
• Allows data layering
Time-based coordinate system
X = Short-term coordinate
Y = Long-term coordinate
2016
2015
2014
Y (year)
293 294 295 X (day)
Time grid
Framework
Visualization and analysis
X = Short-term coordinate
Y = Long-term coordinate
Z = Value (raster cell color)
2016
2015
2014
Y (year)
293 294 295 X (day)
Z (value)
  
  
  
Time as raster
Streamflow example
Traditional hydrograph
*
* Glen Canyon Dam
operational
What date is
this event?
2
2 = Drought
3
3 = Low winter flow
4
4 = Storm flow
5
5 = Higher autumn flow
6
6 = Diversion tunnels closed
7
7 = El Niño runoff
8
8 = Artificial floods
9
9 = Sunday flow
10
10 = Christmas
11
11 = Monthly change
1
Pattern key
1 = Snowmelt runoff
Raster hydrograph
Colorado River at Lees Ferry, AZ
Oct – Sept (water year), 1921 to 2014
*
• First day
of month
Glen Canyon
Dam online
*
12
12 = Policy change
What date is
this event?
‘96
Data source: USGS
Adopted by USGS
Annual peak streamflow (ft3/s)
An outlier is an
observation point
that is distant from
other observations.
Outliers
Outlier detection
IDOR
MTWA
Outlier detection
Temporal
outliers
+ Dworshak
operational
An outlier is an
observation point
that is distant from
other observations.
IDOR
MTWA
Data source: USGS
Annual peak streamflow (ft3/s)
“War time”
Year-round DST
1942 to 1945
1973 Energy Crisis
Early DST
1974 and 1975
Congress changes
when DST begins
Switch
to DST
CAN
MT
ID WY
Data Source: USACE
Fort Peck Reservoir computed daily inflow
Days with no data can provide information
Data quality
Missing
Lookout Creek near Blue River, OR
Elev = 1,378 ft
Drainage area =24.10 mi2
Western Cascade geology
Low soil permeability
McKenzie River at Outlet of Clear Lake, OR
Elev = 3,015 ft,
Drainage area = 92.40 mi2
High Cascade geology
Moderate/High soil permeability
Source: Grant et al., 2010. Streamflow response to climate warming in mountain regions:
Integrating the effects of snowpack and groundwater dynamics.
http://www.fs.fed.us/psw/cirmount/meetings/mtnclim/2010/talks/pdf/Grant_Talk2010.pdf
Flow regime and geology (Oregon)
USFS - OSU study
Background map source: Google
McKenzie River
Winter
Longer duration
Summer
Higher baseflow
Lookout Creek
Winter
Shorter duration
Summer
Lower baseflow
Flow regime and geology
USFS - OSU study
Background map source: Google
Data source: USGS
Ocean tides (1 minute values)
Data source: NOAA
Traditional
1 day (1,440 pts) 1 week (10,080 pts)
1 month (43,200 pts) 3 months (129,600 pts)
Hawk Inlet, AK
Apr-Jun 2016 predicted tides
Sunrise,
Sunset
…
Raster
Units: Feet
Time Zone: Alaska DST
Datum: Mean Lower Low Water (MLLW)
3 months (129,600 pts)
Bonneville Daily Count (2010 – 2014, 5 years)
Salmon migration
Source: Fish Passage Center
Bonneville Daily Count (1938 – 2014, 76 years)
Salmon migration
Data source: USACE
Traditional plots:
Puget Sound paralytic shellfish toxins
Puget Sound
“Red tide” analysis
Source: Moore, S.K., et al., 2009. Recent trends in paralytic shellfish toxins in Puget Sound, relationships to climate,
and capacity for prediction of toxic events. Harmful Algae 8, 463–477 doi:410.1016/ j.hal.2008.1010.1003.
Time series datasets:
Environmental factors
1. Streamflow (m3s-1)
2. Air temp (C)
3. Precipitation (cm)
4. Wind speed (ms-1)
5. Tidal height difference (m)
6. Upwelling (m3s-1100 m-1)
7. Sea surface salinity (psu)
8. Sea surface temp (C)
Observed streamflow
1,716 days or
36% of days were in
“criterion windows”
Criterion: Flow ≤ 350 m3s-1
Met = 1 Not met = 0
Missing
Apply a binary filter
Identify threshold days
8. Sea surface temp
1,840 days
7. Salinity
2,513 days
6. Upwelling
2,424 days
5. Tide range
2,546 days
4. Wind
2,662 days
3. Precipitation
4,116 days
2. Air temp
2,062 days
1. Streamflow
1,716 days
Multi-layer analysis
Only 126 days
meet all 8 criteria
1 - Apply criterion to each layer 2 – Produce a summary layer
J F M A M J J A S O N D
Summary
• Greater GIS versatility
Powerful “timescape” visualization
New opportunities for GIS
• Improve communication
Engage clients, funding sources, public
Enhance decision support information
• Increase ROI from GIS
Leverage existing software
Expand products and services
Competitive advantage
Acknowledgements
• Golden Software, LLC
Support and feedback for this innovative use of Surfer®
• USGS
Incorporated raster hydrographs into the Water Watch website
• NOAA
Provided data and feedback
• Northwest Power and Conservation Council (NWPCC)
Sponsored data visualization workshop - May 2015
Selected workshop graphics used in this talk
Questions?
Richard Koehler, PhD, PH
richard.koehler@noaa.gov

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Using GIS to Visualize and Analyze Environmental Time-Series Data as Raster Maps (Richard Koehler)

  • 1. Richard Koehler, PhD, PH NOAA/National Weather Service National Hydrologic and Geospatial Sciences Training Coordinator Using GIS to Visualize and Analyze Environmental Time-Series Data as Raster Maps GIS Colorado Fall Meeting October 21, 2016 Source: nrcs.gov Source: noaa.govSource: usbr.gov
  • 2. Quote The application of GIS is limited only by the imagination of those who use it. Jack Dangermond Co-founder,
  • 3. Time series in GIS Two common approaches 1. Animate / time slider Source: cuahsi.org 2. Line graphs Source: esri t5 t4 t3 t2 t1 Base map
  • 4. • Most statistics are simple Mean, median, variance, standard deviation, min, max • Multiple streamflow metrics exist (170+) • Need time-scale analysis to find patterns • Visualization overlooked as an analysis method • GIS - technology for data analysis, configuration and visualization for spatial data Magnitude 55% Frequency 8% Duration 26% Timing 6% Flow change 5% Composition attributes Data order not a factor Configuration attributes Data order is fundamental Time series data analysis – why not for temporal data?
  • 5. Data source: NOAA Data source: USGS Time series data displays
  • 6. Spaghetti plot Kettle River near Laurier, WA Data source: USGS Day of Water Year Discharge(ft3/s) Assumption: Lines lay within a single plane Water Year: Oct 1 – Sept 30
  • 7. Display evolution New assumption: Profiles stacked in multiple planes !
  • 8. Tilt and rotate display New perspective, “aerial” Hidden axis Spaghetti plot perspective, “ground” Wire diagram
  • 9. Temporal map • Dual timescale as X, Y • Common framework • Visualization options • Allows data layering Time-based coordinate system
  • 10. X = Short-term coordinate Y = Long-term coordinate 2016 2015 2014 Y (year) 293 294 295 X (day) Time grid Framework
  • 11. Visualization and analysis X = Short-term coordinate Y = Long-term coordinate Z = Value (raster cell color) 2016 2015 2014 Y (year) 293 294 295 X (day) Z (value)          Time as raster
  • 12. Streamflow example Traditional hydrograph * * Glen Canyon Dam operational What date is this event?
  • 13. 2 2 = Drought 3 3 = Low winter flow 4 4 = Storm flow 5 5 = Higher autumn flow 6 6 = Diversion tunnels closed 7 7 = El Niño runoff 8 8 = Artificial floods 9 9 = Sunday flow 10 10 = Christmas 11 11 = Monthly change 1 Pattern key 1 = Snowmelt runoff Raster hydrograph Colorado River at Lees Ferry, AZ Oct – Sept (water year), 1921 to 2014 * • First day of month Glen Canyon Dam online * 12 12 = Policy change What date is this event? ‘96 Data source: USGS
  • 15. Annual peak streamflow (ft3/s) An outlier is an observation point that is distant from other observations. Outliers Outlier detection IDOR MTWA
  • 16. Outlier detection Temporal outliers + Dworshak operational An outlier is an observation point that is distant from other observations. IDOR MTWA Data source: USGS Annual peak streamflow (ft3/s)
  • 17. “War time” Year-round DST 1942 to 1945 1973 Energy Crisis Early DST 1974 and 1975 Congress changes when DST begins Switch to DST CAN MT ID WY Data Source: USACE Fort Peck Reservoir computed daily inflow Days with no data can provide information Data quality Missing
  • 18. Lookout Creek near Blue River, OR Elev = 1,378 ft Drainage area =24.10 mi2 Western Cascade geology Low soil permeability McKenzie River at Outlet of Clear Lake, OR Elev = 3,015 ft, Drainage area = 92.40 mi2 High Cascade geology Moderate/High soil permeability Source: Grant et al., 2010. Streamflow response to climate warming in mountain regions: Integrating the effects of snowpack and groundwater dynamics. http://www.fs.fed.us/psw/cirmount/meetings/mtnclim/2010/talks/pdf/Grant_Talk2010.pdf Flow regime and geology (Oregon) USFS - OSU study Background map source: Google
  • 19. McKenzie River Winter Longer duration Summer Higher baseflow Lookout Creek Winter Shorter duration Summer Lower baseflow Flow regime and geology USFS - OSU study Background map source: Google Data source: USGS
  • 20. Ocean tides (1 minute values) Data source: NOAA Traditional 1 day (1,440 pts) 1 week (10,080 pts) 1 month (43,200 pts) 3 months (129,600 pts) Hawk Inlet, AK Apr-Jun 2016 predicted tides Sunrise, Sunset … Raster Units: Feet Time Zone: Alaska DST Datum: Mean Lower Low Water (MLLW) 3 months (129,600 pts)
  • 21. Bonneville Daily Count (2010 – 2014, 5 years) Salmon migration Source: Fish Passage Center
  • 22. Bonneville Daily Count (1938 – 2014, 76 years) Salmon migration Data source: USACE
  • 23. Traditional plots: Puget Sound paralytic shellfish toxins Puget Sound “Red tide” analysis Source: Moore, S.K., et al., 2009. Recent trends in paralytic shellfish toxins in Puget Sound, relationships to climate, and capacity for prediction of toxic events. Harmful Algae 8, 463–477 doi:410.1016/ j.hal.2008.1010.1003. Time series datasets: Environmental factors 1. Streamflow (m3s-1) 2. Air temp (C) 3. Precipitation (cm) 4. Wind speed (ms-1) 5. Tidal height difference (m) 6. Upwelling (m3s-1100 m-1) 7. Sea surface salinity (psu) 8. Sea surface temp (C)
  • 24. Observed streamflow 1,716 days or 36% of days were in “criterion windows” Criterion: Flow ≤ 350 m3s-1 Met = 1 Not met = 0 Missing Apply a binary filter Identify threshold days
  • 25. 8. Sea surface temp 1,840 days 7. Salinity 2,513 days 6. Upwelling 2,424 days 5. Tide range 2,546 days 4. Wind 2,662 days 3. Precipitation 4,116 days 2. Air temp 2,062 days 1. Streamflow 1,716 days Multi-layer analysis Only 126 days meet all 8 criteria 1 - Apply criterion to each layer 2 – Produce a summary layer J F M A M J J A S O N D
  • 26. Summary • Greater GIS versatility Powerful “timescape” visualization New opportunities for GIS • Improve communication Engage clients, funding sources, public Enhance decision support information • Increase ROI from GIS Leverage existing software Expand products and services Competitive advantage
  • 27. Acknowledgements • Golden Software, LLC Support and feedback for this innovative use of Surfer® • USGS Incorporated raster hydrographs into the Water Watch website • NOAA Provided data and feedback • Northwest Power and Conservation Council (NWPCC) Sponsored data visualization workshop - May 2015 Selected workshop graphics used in this talk
  • 28. Questions? Richard Koehler, PhD, PH richard.koehler@noaa.gov