Development of a Community Hydrologic

Information System

Jeffery S. Horsburgh

Utah State University

David G. Tarboton

Utah State University

Hydrologic Science

Hydrologic conditions(Fluxes, flows, concentrations)

Hydrologic Process Science(Equations, simulation models, prediction)

Hydrologic Information Science(Observations, data models, visualization

Hydrologic environment(Dynamic earth)

Physical laws and principles(Mass, momentum, energy, chemistry)

It is as important to represent hydrologic environments precisely with

data as it is to represent hydrologic processes with equations

Rainfall & SnowWater quantity

and quality

Remote sensing

Water Data Modeling

Meteorology

Soil water

• Provide access to multiple heterogeneous data sources simultaneously, regardless of semantic or structural differences between them

Objective

NWIS

NARR

NAWQANAM-12

request

request

request

request

request

requestrequest

request

request

return

return

return

return

return

returnreturn

return

return

What we are doing now …

Slide from Michael Piasecki, Drexel University

What we would like to do …..

NWIS

NAWQA

NARR

generic

request

GetValues

GetValues

GetValues

GetValues

GetValues

GetValuesGetValues

GetValues

GetValues ODM

Slide from Michael Piasecki, Drexel University

CU

AH

SI

HIS

CUAHSI Hydrologic Data Access System

A common data window for accessing, viewing and downloading hydrologic information

USGS NASANCDCEPA NWS Observatory Data

WaterOneFlow Web Services

Data access through web

services

Data storage through web

services

Dow

nlo

ads

Upl

oa

ds

Observatory data servers

CUAHSI HIS data servers

3rd party data servers

e.g. USGS, NCDC

GIS

Matlab

IDL

Splus, R

Excel

Programming (Fortran, C, VB)

Web services interface

Hydrologic Data Access System Website Portal and Map Viewer

Information input, display, query and output services

Preliminary data exploration and discovery. See what is available and perform exploratory analyses

HTML -XML WS

DL

- SO

AP

ODMODM

Web Services• A set of protocols that together provide a

mechanism for machine-to-machine communication over the Internet

• Advantages– Interoperability across operating systems and

programming languages (XML based)– Application developers interact with web

services similar to the way they interact with any other software library within a programming environment

NWISNWIS

ArcGISArcGIS

ExcelExcel

NCARNCAR

UnidataUnidata

NASANASAStoretStoret

NCDCNCDC

AmerifluxAmeriflux

MatlabMatlab

AccessAccess JavaJava

FortranFortran

Visual BasicVisual Basic

C/C++C/C++

Some operational services

CUAHSI Web ServicesCUAHSI Web Services

Data SourcesData Sources

ApplicationsApplications

Extract

Transform

Load

http://www.cuahsi.org/his.html

Local Data• No efficient online data delivery system

• Disparate file formats

• Different types, frequencies, etc.ODM with

Web ServicesODM with

Web Services

XMLXML

Data Mediation

Data Consumption and Analysis

ExcelFiles

ExcelFiles

AccessFiles

AccessFiles

TextFiles

TextFiles

Sensor Data

Sensor Data

Local Data SourcesWith Multiple Formats

ExcelFiles

ExcelFiles

AccessFiles

AccessFiles

TextFiles

TextFiles

Sensor Data

Sensor Data

Local Data SourcesWith Multiple Formats

Data Consumption and Analysis

CUAHSI Observations Data Model• A relational database at the

single observation level (atomic model)

• Stores observation data made at points

• Metadata for unambiguous interpretation

• Traceable heritage from raw measurements to usable information

• Standard format for data sharing

• Cross dimension retrieval and analysis

Streamflow

Flux TowerData

Precipitation& Climate

GroundwaterLevels

Water Quality

Soil Moisture

Data

ODM

ODM and HIS in The Little Bear River Test BedIntegration of Sensor Data With HIS

ObservationsDatabase

(ODM)

Base StationComputer(s)

Data ProcessingApplications In

tern

et

Telemetry Network

Environmental Sensors

Data discovery, visualization, analysis, and modeling

through Internet enabled applications

Programmer interaction through web services

Inte

rnet

Workgroup HIS Tools

Workgroup HISServer

Managing Data Within ODM - ODM Tools

• Load – import existing data directly to ODM

• Query and export – export data series and metadata

• Visualize – plot and summarize data series

• Edit – delete, modify, adjust, interpolate, average, etc.

CentralObservations

Database

Wet Chemistry Measurements

Sensors(Streamflow

Water QualityClimate)

Constituent Bayes Net

Exogenous Variables

(GIS, Land Use,Management)

C

BA

Sensor BayesNetwork

Telemetry Network

Nutrient Estimates

0

25

50

75

100

125

150

175

1980 1990 2000

Res

idue

Tot

al N

onfil

trab

le;

mg/

L

Date

C

BA

Little Bear River at Mendon Road (4905000)

y = 2.3761x

R2 = 0.6993

0

50

100

150

200

250

300

0 15 30 45 60 75

Turbidity (NTU)

TO

tal

Su

spen

ded

So

lid

s (m

g/L

)

Bayesian Networks to construct water quality measures from surrogate sensor signals to provide high frequency estimates of water quality and loading

Site specific correlationsbetween sensor signalsand other water quality variables

Sensors, data collection, and telemetry network

Bayesian Networks to control monitoring system, triggering sampling for storm events and base flow

CUAHSI HIS ODM – central storage and management of observations data

End result: high frequency estimates of nutrient concentrations and loadings

Little Bear River Integrated Monitoring System

Data Models: Structured data sets to facilitate data integrity and effective sharing and analysis.- Standards- Metadata- Unambiguous interpretation

Analysis: Tools to provide windows into the database to support visualization, queries, analysis, and data driven discovery. Models: Numerical implementations of hydrologic theory to integrate process understanding, test hypotheses and provide hydrologic forecasts.

ConclusionAdvancement of water science is critically

dependent on integration of water information

Databases Analysis

Models

ODM

Web Services