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AWRA Spring Specialty AWRA Conference Spring Specialty on GIS Conference and Water on Resources GIS and Water VIII Resources May 13, 2014 Using a Temporal Information System

1 AWRA Spring Specialty AWRA Conference Spring Specialty on GIS Conference and Water on Resources GIS and Water VIII Resources May 13, 2014 Using a Temporal Information System for Visualization and Analysis of Hydrologic Time-Series Data Application and Case Study Results Image source: Richard Koehler, PhD, PH Visual Data Analytics, LLC

for Visualization and Analysis of Hydrologic Time-Series Data Application and Case

2 Discovery consists of looking at the same thing as everyone else and thinking something different. Albert Szent-Györgyi Nobel Laureate (Discoverer of Vitamin C)

3 GIS and time-series Landscape + line graphs Timescape! Temporal maps X = Day, Y = Year, Z = Value

4 Traditional hydrograph Colorado River at Lees Ferry, AZ 92 years of daily data (33,700 values) Glen Canyon Dam *

5 Raster hydrograph Colorado River at Lees Ferry, AZ 92 years of daily data (33,700 values) * * Glen Canyon Dam

6 Raster hydrograph Colorado River at Lees Ferry, AZ 92 years of daily data (33,700 values) Temporal patterns * 1. Snowmelt runoff 2. Drought 3. Storm 4. Vegetation signal 5. Tunnels closed 6. El Nino 7. Artificial flood 8. Sundays 9. Christmas 10. Monthly change 2 4 * Glen Canyon Dam

Drought 3. Storm 4. Vegetation signal 5. Tunnels closed 6. El Nino 7.

7 Raster hydrographs adopted by the USGS

8 Application: QA/QC CAN MT Fort Peck computed daily inflow (~72 yrs, 26,300 values) ID WY Switch to DST, systematic error Missing

9 Application: Multi-site comparison Drought index Wetter Drier Oregon

10 Inter-comparisons Value color Temporal persistence Spatial extent Year Month

11 Annual Max Daily Mean Flow Red River of the North at Fargo, ND Symbol size flow Flow (cfs) Year Max = 29, Min =

12 Case study 1 Colorado River Water Availability Study (CRWAS) How can climate simulations for water resources be re-purposed? Topics Hydrometeorology Climate change Water supply Consumptive use Decision support Reservoir management Instream flows Data visualization Elements a. Sites = 845 Diversions, Reservoirs, Stream gages, ISF reaches, Natural Flow Nodes, b. Parameters = 26 Demand, CU, Loss, Flow, c. Climate scenarios = 11 Historic, 2040 & 2070 simulations

Topics Hydrometeorology Climate change Water supply Consumptive use Decision support Reservoir management Instream

13 Current data display Elements a. Sites 1 b. Parameters 1 c. Scenarios 11 a. Colorado River nr CO-UT state line b. Upstream Inflow c. All climate scenarios

14 Proposed data display Elements a. Sites 1 b. Parameters 1 c. Scenarios 1 a. Colorado River nr CO-UT state line b. Upstream Inflow c. Historic climate scenario

15 Proposed data display Elements a. Sites 1 b. Parameters 1 c. Scenarios 1 a. Colorado River nr CO-UT state line b. Upstream Inflow c G climate scenario

16 New product display Elements a. Sites 1 b. Parameters 1 c. Scenarios 2 a. Colorado River nr CO-UT state line b. Upstream Inflow (new) c. (2070 G) (Historic)

17 Potential new products Elements a. Sites multiple b. Parameters multiple c. Scenarios multiple 1. Temporal signature 2. Up and downstream - or - basin to basin comparison 3. Dual parameter comparison 4. Scenario difference comparison (as shown earlier) 5. More complex intercomparisons

Temporal signature 2. Up and downstream - or - basin to basin comparison 3.

18 Case study 2 Paralytic shellfish toxins in Puget Sound* How can multiple environmental time-series be integrated into a single summary plot? Topics Water quality Habitat monitoring Hydrometeorology Oceanography Public health Economics Climate change Decision support Ecological forecasting and trends Data visualization CAN WA * Moore, S.K., et al., Recent trends in paralytic shellfish toxins in Puget Sound, relationships to climate, and capacity for prediction of toxic events. Harmful Algae 8, doi: / j.hal

Ecological forecasting and trends Data visualization CAN WA * Moore, S.K., et al., 2009.

19 Background information Criteria driven approach for shellfish toxicity Time-series datasets: Traditional plots: Environmental factors 1. Sea surface temp ( C) 2. Sea surface salinity (psu) 3. Air temp ( C) 4. Precipitation (cm) 5. Streamflow (m 3 s -1 ) 6. Tidal height difference (m) 7. Upwelling (m 3 s m -1 ) 8. Wind speed (ms -1 )

Sea surface salinity (psu) 3. Air temp ( C) 4. Precipitation (cm) 5.

20 Threshold example Observed streamflow Criterion: Flow 350 m 3 s -1 Met = 1, Not met = 0 Flow (m 3 s -1 ) Missing 1,716 days Event Windows

21 Calendar Year Case study results 1,840 days 2,513 days Apply specific criterion to specific layer If layers = 8 for any day; Then event window present Potential Event Windows 2,424 days 2,546 days 127 days 2,662 days 1,716 days 2,062 days 4,116 days Day of Year Missing

22 Benefits of temporal maps Natural way to view large datasets Quickly review and interpret Develop new types of products Cost effective and time efficient method Result = Competitive advantage

Questions? Visual Data Analytics, LLC Richard Koehler, PhD, PH rick@vizualtime.

23 Questions? Visual Data Analytics, LLC Richard Koehler, PhD, PH Consulting, partnering, workshops Visit our website for more information.

Introduction to Raster Graphics and Applications

Data Visualization Workshop May 7, 2015 Introduction to Raster Graphics and Applications Richard Koehler, PhD, PH NOAA, Boulder, CO richard.koehler@noaa.gov Source: usgs.gov Source: nrcs.gov Source: noaa.gov