using gis to visualize and analyze environmental time-series data as raster maps (richard koehler)
TRANSCRIPT
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Richard Koehler, PhD, PHNOAA/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
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Quote
The application of GIS
is limited only by the imagination
of those who use it.
Jack Dangermond
Co-founder,
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Time series in GIS
Two common approaches
1. Animate / time slider
Source: cuahsi.org
2. Line graphs
Source: esri
t5t4t3t2t1
Base map
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• Most statistics are simpleMean, 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 attributesData order not a factor
Configuration attributesData order is fundamental
Time series data analysis
– why not for temporal data?
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Data source: NOAA
Data source: USGS
Time series data displays
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Spaghetti plotKettle River near Laurier, WA
Data source: USGSDay of Water Year
Dis
char
ge (
ft3/s
)
Assumption:Lines lay within a single plane
Water Year: Oct 1 – Sept 30
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Display evolution
New assumption:Profiles stacked in multiple planes
!
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Tilt and rotate display
New perspective,“aerial”
Hidden axis
Spaghetti plot perspective,“ground”
Wire diagram
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Temporal map
• Dual timescale as X, Y
• Common framework
• Visualization options
• Allows data layering
Time-based coordinate system
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X = Short-term coordinate
Y = Long-term coordinate
2016
2015
2014
Y (year)
293 294 295 X (day)
Time grid
Framework
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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
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Streamflow exampleTraditional hydrograph
** Glen Canyon Dam
operational
What date is this event?
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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 key1 = Snowmelt runoff
Raster hydrograph
Colorado River at Lees Ferry, AZOct – 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
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Adopted by USGS
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Annual peak streamflow (ft3/s)
An outlier is an observation point that is distant from other observations.
Outliers
Outlier detectionIDOR
MTWA
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Outlier detection
Temporal outliers
+ Dworshakoperational
An outlier is an observation point that is distant from other observations.
IDOR
MTWA
Data source: USGS
Annual peak streamflow (ft3/s)
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“War time”Year-round DST
1942 to 1945
1973 Energy CrisisEarly 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
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Lookout Creek near Blue River, ORElev = 1,378 ftDrainage area =24.10 mi2
Western Cascade geologyLow soil permeability
McKenzie River at Outlet of Clear Lake, ORElev = 3,015 ft, Drainage area = 92.40 mi2
High Cascade geologyModerate/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
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McKenzie River Winter
Longer durationSummer
Higher baseflow
Lookout CreekWinter
Shorter durationSummer
Lower baseflow
Flow regime and geology
USFS - OSU study
Background map source: Google
Data source: USGS
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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: FeetTime Zone: Alaska DSTDatum: Mean Lower Low Water (MLLW)
3 months (129,600 pts)
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Bonneville Daily Count (2010 – 2014, 5 years)
Salmon migration
Source: Fish Passage Center
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Bonneville Daily Count (1938 – 2014, 76 years)
Salmon migration
Data source: USACE
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Traditional plots:
Puget Sound paralytic shellfish toxinsPuget 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)
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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
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8. Sea surface temp1,840 days
7. Salinity 2,513 days
6. Upwelling2,424 days
5. Tide range2,546 days
4. Wind2,662 days
3. Precipitation4,116 days
2. Air temp2,062 days
1. Streamflow1,716 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
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Summary
• Greater GIS versatilityPowerful “timescape” visualization
New opportunities for GIS
• Improve communicationEngage clients, funding sources, public
Enhance decision support information
• Increase ROI from GIS Leverage existing software
Expand products and servicesCompetitive advantage
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Acknowledgements
• Golden Software, LLCSupport and feedback for this innovative use of Surfer®
• USGSIncorporated raster hydrographs into the Water Watch website
• NOAAProvided data and feedback
• Northwest Power and Conservation Council (NWPCC)Sponsored data visualization workshop - May 2015
Selected workshop graphics used in this talk