1. Creating Hydrologic Information Systems David R. Maidment Utah State University 9 February 2004

2. ArcIMS Website http://emrcims.uwrl.usu.edu uses data stored in an ArcGIS geodatabase

3. Watershed Information System GIS map data on watersheds, lakes, gages, streams, dams,…. GIS surface data on terrain, land cover, precipitation Monitoring point information on streamflow, water quality, climate USGS gage

4. Real Time Weather Data

5. Nexrad Radar 06:09 PM MST Sun Feb 8th 2004

6. Nexrad Data from NOAAPort http://www.rap.ucar.edu/weather/radar/ About 3 minutes between measurement and local delivery of information NOAAPort

7. Unidata Weather Data Unidata is part of UCAR (Universities Corporation for Atmospheric Research) Unidata ingests data from NOAAPort and other sources Unidata streams weather data continuously to about 180 US universities Data received by a local data manager (LDM) USU has an LDM

8. Weather and Hydrology Weather Information –Continuous in space and time –Combines data and simulation models –Delivered in real time Hydrologic Information –Static spatial info, time series at points –Data and models are not connected –Mostly historical data Challenges for Hydrologic Information Systems How to better connect space and time? How to connect space, time and models? How to connect weather and hydrology?

9. Hydrologic Information System Modeling Geodatabase A hydrologic information system is a combination of geospatial and temporal hydrologic data and hydrologic models that supports hydrologic practice, science and education

10. Arc Hydro Arc Hydro is customized version of ArcGIS for water resources data GIS CRWR Water Resources

11. Arc Hydro — Hydrography

12. Arc Hydro — Hydrology

13. Flow Time Time Series HydrographyHydro Network Channel System Drainage System Arc Hydro Components

14. Arc Hydro Framework Data Model

15. National Hydrography Dataset, NHD Basins Waterbody (NHD) Arc Hydro Framework For South Florida Hydro Points

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

17. Nexrad data in Arc Hydro Attribute series Display as a temporal layer in ArcGIS Tracking Analyst

18. ArcGIS Tracking Analyst Tracking Analyst Demo Displays data in space and time Fecal Coliform in Galveston Bay 1995-2001

19. Attribute Series Time Series Map Features Map Attributes Attribute Series: A map attribute that is a time series for each feature

20. Time SeriesFeature Series Raster SeriesAttribute Series Time Variable Time and Space in GIS x y Value t1t1 t2t2 t3t3 Time t1t1 t2t2 t3t3 t3t3 t2t2 t1t1

21. Time Series and Temporal Geoprocessing Time SeriesFeature Series Raster SeriesAttribute Series Time Variable x y Value t1t1 t2t2 t3t3 Time t1t1 t2t2 t3t3 ArcGIS Temporal Geoprocessing t3t3 t2t2 t1t1 DHI Time Series Manager

22. 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 Time series downloaded from dbHydro and stored for all gages as Arc Hydro Attribute Series

23. Arc Hydro Attribute Series Feature Class (HydroID) Attribute Series Table (FeatureID) HydroID 2906 Map features have a time varying attribute

24. Raster Series Ponded Water Depth Kissimmee River June 1, 2003

25. Weather and Hydrology NetCDF describes atmospheric and water properties varying continuously in (x,y,z,t) GIS describes the physical landscape, –Vector GIS has spatially discrete features (point, line area) –Raster GIS is spatially continuous (in 2D) How do we connect the “water” with the “water environment”

26. TSDateTime FeatureID TSType TSValue Arc Hydro Attribute Series TSType Table Feature Class (point, line, area)

27. Time Space (x,y,z) Variables Value NetCDF Data Model (developed at Unidata for distributing weather data) Attributes Dimensions and Coordinates NetCDF describes a collection of variables whose values are stored at coordinate points in the (x,y,z,t) dimensions

28. NetCDF File for Weather Model Output of Relative Humidity (Rh) dimensions: lat = 5, lon = 10, time = unlimited; variables: lat:units= “degrees_north”; long:units= “degrees_east”; time:units= “hours since 1996-1-1”; data: lat = 20, 30, 40, 50, 60; long = -160, -140, -118, -96, -84, -52, -45, -35, -25, -15; time = 12; rh =.5,.2,.4,.2,.3,.2,.4,.5,.6,.7,.1,.3,.1,.1,.1.,.1,.5,.7,.8,.8,.1,.2,.2,.2,.2,.5,.7,.8,.9,.9,.1,.2,.3,.3,.3,.3,.7,.8,.9,.9.0,.1,.2,.4,.4,.4,.4,.7,.8,.9; rh (time, lat, lon);

29. Relative Humidity Points

30. Interpolate to Raster GeoTiff format, cell size = 0.5º

31. Zoom in to the United States

32. Average Rh in each State Determined using Spatial Analyst function Zonal Statistics with Rh as underlying raster and States as zones

33. Model Builder in Arc 9 Relative Humidity Analysis Model Model Builder Demo

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

35. Interface data models HMS RAS WRAP GIS Geo Database Arc Hydro data model Geographically Integrated Hydrologic Modeling Systems

36. Regional Storm Water Modeling Program and Master Plan for San Antonio City of San Antonio

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

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

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

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

41. 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

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

43. Nexrad Map to Flood Map in Arc 9 Model Builder FLO ODP LAIN MAP Flood map as output Model for flood flow Model for flood depth HMS Nexrad rainfall map as input

44. Hydrologic Information System Models Hydrologic simulation models Hydrologic data models Hydrologic workflow models All of these can be delivered through ArcIMS HMS Arc Hydro

45. Information Sources Analysis and Visualization Hydrologic Data Model CUAHSI Hydrologic Information System GIS Experiments Simulation Monitoring Climate models 2. Integrate data into a coherent structure 3. Do science 1. Assemble data from many sources Hypothesis testing Data Assimilation Remote sensing Statistics

46. CUAHSI Program Components

47. Institutions of participants in the CUAHSI HIS Proposal Hydrologic Information Partners

48. Created first for the Neuse basin and then for each of the following CUAHSI Observatory Planning basins Digital Watershed: An implementation of the CUAHSI Hydrologic Data Model for a particular region

49. 3D Control Volume of Neuse Basin Fluxes Extrude watershed boundary 15 km up into atmosphere and 1 km down into subsurface

50. Observatory Goal: Hydrologic Fluxes Improve predictive understanding of fluxes of –Water –Sediment –Nutrients –[Selected Contaminants] Across spatial scales, including catchment outlet Riverine fluxes, at a minimum, but also fluxes across other interfaces (PI-specified) Need for definition of “HydroElements”, at any location in hydrologic system

51. Riverine HydroElements Detailed bathymetry points of a river channel 3D HydroElement formed from cross-sections and profile lines

52. Conclusions New information era opening Rapid access and visual display of large quantities of data Better integration of data and modeling New disciplines: hydroinformatics and hydrologic information science Real time hydrology could support teaching USU is an important partner in this process!