1. Arc Hydro and Time Series
Presented by David R. Maidment
At ESRI, Redlands CA
15 January 2004

2. Hydrologic Information System
Analysis, Modeling,
Decision Making
Arc Hydro
Geodatabase

3. Arc Hydro Components Drainage System Hydro Network Time Series
Flow
Time
Time Series
Channel System
Hydrography

4. Time Series Data indexed by time
A time series is a sequence of (time, value) pairs
Represents a single type of information e.g. streamflow
Many existing time series databases are not linked to GIS
Flow
Time

5. Time and Space in GIS Time Series Feature Series Attribute Series
Variable t3
Value t2 t1
Time
Attribute Series
Raster Series
Value t3 t1 t2 t2 t1 t3 y x

6. Time Series and Temporal Geoprocessing
DHI Time Series Manager
Time Series
Feature Series
Time
Variable t3
Value t2 t1
Time
Attribute Series
Raster Series
Value t3 t3 t2 t1 t2 t1 y x
ArcGIS Temporal Geoprocessing

7. Time Series A sequence of {time, value} pairs
Exists independently of GIS
May be associated with 0, 1 or many spatial features
Displayed using graphs
Measured at gages
Generated by simulation models
Time Series
Time
Variable
Value
Time

8. Attribute Series A sequence of {featureID, time, value} triplets
Features have time series
Feature classes have attribute series
Attribute series is a feature attribute that varies through time
Features have fixed shape
Time Series
Attribute Series t3 t2 t1
Feature Attributes

9. Arc Hydro Attribute Series Object
TSDateTime
TSValue
FeatureID
TSType

10. Arc Hydro Attribute Series
Feature Class (HydroID)
Attribute Series Table (FeatureID)

11. Attribute Series Typing
TSType
Attribute Series 1 *
Type
Units
Regular ….
FeatureID
Type
Time
Value
Map time series e.g. Nexrad
Collections of values recorded at various locations and times e.g. water quality samples
This is current Arc Hydro time series structure

12. Raster Series A sequence of {time, raster} pairs
Stored in a time-indexed raster catalog
Shares same time series type classification as other forms of time series
Produced by time-indexed geoprocessing operations
Raster Series
Value t3 t2 t1 y x

13. Feature Series A sequence of {shape, time, value} triplets
Feature geometry varies through time
Features may vary in shape and location in space
Produced by observation or by classification of phenomena in raster series
Feature Series t3 t2 t1

14. Time Series Types
Need to classify time series into Types so that functions can be applied appropriately
All series should share the same typing system
Many aspects of typing numerical data from physical time series
GIS data have categorical, ordinal, interval and ratio types

15. Arc Hydro Case Studies GoldSim linked to Arc Hydro
Tracking Analyst for displaying Arc Hydro attribute series data
MaptoMap: From Nexrad rain map to a flood plain map using Model Builder, Arc Hydro and the HEC models
Temporal Geoprocessing for Hydroperiod at the South Florida Water Management District
Then Michael Blongewicz will present the
DHI Time Series Manager

16. GoldSim

17. Step 1: Initiate the Model

18. Step 2: Specify Time Horizon and Number of Time Steps

19. Step 3: Use Monte Carlo Analysis?

20. Step 4: Add Model Elements

21. Arc Hydro Attribute Series
Feature Class (HydroID)
Attribute Series Table (FeatureID)

22. Arc Hydro TSType Table Arc Hydro has 6 Time Series DataTypes Units of
measure
Regular or
Irregular
Time
interval
Type Of
Time
Series
Info
Recorded or
Generated
Type
Index
Variable
Name
Arc Hydro has 6 Time Series DataTypes
Instantaneous
Cumulative
Incremental
Average
Maximum
Minimum

23. Type of Time Series
Gold Sim Types
Arc Hydro Type
1. Instantaneous

24. GoldSim Demo

25. Arc Hydro Case Studies GoldSim linked to Arc Hydro
Tracking Analyst for displaying Arc Hydro attribute series data
MaptoMap: From Nexrad rain map to a flood plain map using Model Builder, Arc Hydro and the HEC models
Temporal Geoprocessing for Hydroperiod at the South Florida Water Management District
Then Michael Blongewicz will present the
DHI Time Series Manager

26. Tracking Analyst Data Structures
Simple Event
One table
Contains at least date/time of observation
Complex Event
Two tables
Object can be stationary or dynamic (depending on whether geometry and time are on same table)

27. Simple Events (1 Table) ID Time Geometry Value 1 T1 X1,Y1 0.1 2 T2
0.3 T3
X3,Y3
0.7 T4
X4,Y4
0.4 3 T5
X5,Y5
0.5 T6
X6,Y6
0.2 4 T7
X7,Y7 T8
X8,Y8
0.8 T9
X9,Y9
Unique Identifier
for objects being
tracked through
time
Observation
Time of observation (in order)
Geometry of observation

28. Complex Event (static version)ID
Time
Value 1 T1
0.1 2 T2
0.3 T3
0.7 T4
0.4 3 T5
0.5 T6
0.2 4 T7 T8
0.8 T9 ID
Geometry 1
X1,Y1 2
X2,Y2 3
X3,Y3 4
X4,Y4
This is an Attribute Series
The object maintains its geometry (i.e. it is stationary and has fixed shape)

29. Complex Event (dynamic version)ID
Geometry
Time
Value 1
X1,Y1 T1
0.1 2
X2,Y2 T2
0.3
X3,Y3 T3
0.7
X4,Y4 T4
0.4 3
X5,Y5 T5
0.5
X6,Y6 T6
0.2 4
X7,Y7 T7
X8,Y8 T8
0.8
X9,Y9 T9 ID
Gage Number 1
1001 2
1002 3
1003 4
1004
This is a Feature Series
The object’s geometry can vary with time (i.e. shape can change or relocate)

30. Concept of Temporal Layer
Take the attribute series table, and join the feature class to that table
Shape is then attached to all attribute series records (one shape for many records)
This is a “Time Centric” view. Bring space to time rather than time to space

31. Irregularly recorded water quality data form an Attribute Series
A point feature class defines the spatial framework
Many variables defined at each point
Time of measurement is irregular
May be derived from a Laboratory Information Management System
Field samples
Laboratory
Database

32. Fecal Coliform in Galveston Bay (Irregularly measured data, 1995-2001)
Coliform Units per 100 ml
Tracking Analyst Demo

33. Tracking Analyst Demo

34. Nexrad over South Florida
Real-time radar rainfall data calibrated to raingages
Received each 15 minutes
2 km grid
Stored by SFWMD in Arc Hydro time series format

35. Nexrad data as Attribute Series
Display as a temporal
layer in Tracking Analyst

36. Nexrad Animation (produced with Tracking Analyst)
Tracking Analyst animations need a time stamp displayed on them
Tracking Analyst needs to be able to display Raster Series
It would be nice to have a “animate raster series” tool in Spatial Analyst

37. Arc Hydro Case Studies GoldSim linked to Arc Hydro
Tracking Analyst for displaying Arc Hydro attribute series data
MaptoMap: From Nexrad rain map to a flood plain map using Model Builder, Arc Hydro and the HEC models
Temporal Geoprocessing for Hydroperiod at the South Florida Water Management District
Then Michael Blongewicz will present the
DHI Time Series Manager

38. GIS Preprocessors for Hydrologic Models
Interface
Model 1
Database
Model 2
Model 3

39. Connecting Arc Hydro and Hydrologic Models
GIS
Interface data models
HMS
Geo
Database
Arc Hydro
data model
RAS
WRAP

40. Regional Storm Water Modeling Program and Master Plan for San Antonio
City of
San Antonio
Good morning.
It’s my pleasure to share with you an example of regional cooperation within Bexar County.

41. San Antonio Regional Watershed Modeling System
Geospatial Data:
City, County
SARA, other
“Bring the models
together”
Modeling
System
Rainfall Data:
Rain gages
Nexrad
Calibration Data:
Flows
Water Quality
Floodplain
Management
Capital
Improvement
Planning
Water quality
planning
Integrated
Regional Water
Resources planning
Flood
Forecasting

42. Regional Watershed Modeling System Case Study
Salado Creek
watershed
Components:
Arc Hydro Geodatabase
for whole watershed
HEC-HMS hydrology model
HEC-RAS hydraulic model
for Rosillo Creek
Bexar County
Rosillo Creek watershed

43. Arc Hydro and HEC-HMS HEC-HMS Hydrologic Model Arc Hydro Schematic
Network
Calculates
Flows

44. Arc Hydro and HEC-RAS HEC-RAS Hydraulic Calculates Water Surface
Model
Calculates
Water Surface
Elevations
Arc Hydro
Channel
Cross Sections

45. HEC Data Storage System (DSS) (binary data file system shared by HEC models)
Model features define the spatial framework
One or a few variables modeled
Values for each time interval
One time series may be associated with many features
Many modeling scenarios
Time series
catalog
Many time series

46. Flow Change Points Models communicate with
one another through Arc Hydro
at designated points

47. Nexrad Map to Flood Map in Arc 9 Model Builder
FLOODPLAIN MAP
Flood map
as output
Model for
flood flow
HMS
Model
for flood
depth
Nexrad rainfall map as input

48. Map to Map Demo

49. Arc Hydro Case Studies GoldSim linked to Arc Hydro
Tracking Analyst for displaying Arc Hydro attribute series data
MaptoMap: From Nexrad rain map to a flood plain map using Model Builder, Arc Hydro and the HEC models
Temporal Geoprocessing for Hydroperiod at the South Florida Water Management District
Then Michael Blongewicz will present the
DHI Time Series Manager

50. Arc Hydro for South Florida Water Management District (SFWMD)
Hydroperiod
Estimation
Operations Decision
Support System
Existing Arc Hydro
Framework
Enhanced
Arc Hydro Framework
for South Florida
Regional Simulation
Model
Flood
Hydrology &
Hydraulics

51. Arc Hydro Framework Data Model
The Arc Hydro framework is built on a Hydro Network made up of HydroEdges (stream lines) and HydroJunctions (points of interest on the lines). The watersheds, waterbodies and hydropoints are connected to the hydronetwork using relationships with the hydro junctions (blue lines in the diagram).

52. Arc Hydro Framework For South Florida
Basins
Waterbody
(NHD)
The Arc Hydro Framework is a simplified version of the full Arc Hydro data model designed for an entry level user who just wants to put together a basic data set for streams, watersheds, waterbodies and hydro points like stream gages and water quality monitoring points
Hydro Points
Hydro Network
(NHD)

53. Flood Inundation Region
HydroPeriod
Flood Inundation Region 1
Depth Class
Land Category
dbHydro 1 1
Feature Series
Time Series
MonitoringPoint
Attribute Series
Raster Series
1..*
Extended Arc Hydro Framework

54. Hydroperiod Tool TimeSeries Framework
Feature Series
Time
Variable 1 3
Attribute Series
Raster Series y t x 2 4

55. Component Transfer Mechanism
Visual Basic program to load DBHydro catalog data into Arc Hydro TimeSeries format
ArcGIS Spatial Interpolation to create water surface raster from TimeSeries stage values
Raster to Polygon Tool to create daily ponded depth class polygons from daily ponded depth class rasters
Spatial Analyst Zonal Statistics to calculate statistics over selected zones 1 2 3 4

56. Time series from gages in Kissimmee Flood Plain
21 gages measuring water surface elevation
Data telemetered to central site using SCADA system
Edited and compiled daily stage data stored in corporate time series database called dbHydro
Each time series for each gage in dbHydro has a unique dbkey (e.g. ahrty, tyghj, ecdfw, ….)

57. Compile Gage Time Series into an Attribute Series table

58. Hydraulic head Land surface h Mean sea level (datum)
Hydraulic head is the water surface elevation in a standpipe
anywhere in a water system, measured in feet above mean sea
level

59. Map of hydraulic head Z Hydraulic head, h h(x, y) x y X Y
A map of hydraulic head specifies the continuous spatial
distribution of hydraulic head at an instant of time

60. Time sequence of hydraulic head mapsz t3 t2 t1
Hydraulic head, h x y

61. Attribute Series to Raster Series

62. Inundation d h L Depth of inundation = d IF (h - L) > 0 then

63. Inundation Time Series
d(x,y,t) = h(x,y,t) – LT(x,y) h
(x,y,t)
LT(x,y)
d(x,y,t) t
Time
DEMO: DHI Time Series

64. Ponded Water Depth
Kissimmee River
June 1, 2003

65. Show Generate Rasters Model

66. Hydroperiod Tool TimeSeries Framework
Feature Series
Time
Variable 1 3
Attribute Series
Raster Series y t x 2 4

67. Depth Classification
Depth
Class 11 5
9-10 4
7-8 3
5-6 2
3-4 1
1-2 -1

68. Feature Series of Ponded Depth

69. Show Classify Depths Model

70. Attribute Series for Habitat Zones

71. Show Zonal Stats Model

72. Issues
Is the {time series, attribute series, raster series, feature series} an appropriate language for describing time variation of spatial features?
What plans does ESRI have to design ArcGIS time series and do they fit with what is proposed here?
Need to refine and standardize the time series typing system