CE%20394K.2%20Surface%20Water%20Hydrology

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CE 394K.2 Surface Water Hydrology

• Lecture 1 Introduction to the course
• Readings for today
• Applied Hydrology, Chapter 1

Once more unto the breach, dear friends, once
more Or close the wall up with our English
dead! In peace theres nothing so becomes a
man As modest stillness and humility But when
the blast of war blows in our ears, Then imitate
the action of the tiger.. King Henry V before
the battle of Agincourt, 1415 Shakespeare, King
Henry the Fifth, Act III, Scene I
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How is new knowledge discovered?
After completing this Handbook in 1993, I asked
myself the question how is new knowledge
discovered in hydrology? I concluded that there
are three ways

• By deduction from existing knowledge
• By experiment in a laboratory
• By observation of the natural environment

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Deduction Newton

• Deduction is the classical path of mathematical
  physics
• Given a set of axioms
• Then by a logical process
• Derive a new principle or equation
• In hydrology, the St Venant equations for open
  channel flow and Richards equation for
  unsaturated flow in soils were derived in this
  way.

Three laws of motion and law of gravitation
(1687)
http//en.wikipedia.org/wiki/Isaac_Newton
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Experiment Pasteur

• Experiment is the classical path of laboratory
  science a simplified view of the natural world
  replicated under controlled conditions
• In hydrology, Darcys law for flow in a porous
  medium was found this way.

Pasteur showed that microorganisms cause disease
discovered vaccination Foundations of
scientific medicine
http//en.wikipedia.org/wiki/Louis_Pasteur
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Observation Darwin

• Observation direct viewing and characterization
  of patterns and phenomena in the natural
  environment
• In hydrology, Horton discovered stream scaling
  laws by interpretation of stream maps

Published Nov 24, 1859 Most accessible book of
great scientific imagination ever written
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Conclusion for Hydrology

• Deduction and experiment are important, but
  hydrology is primarily an observational science
• discharge, water quality, groundwater,
  measurement data collected to support this (USGS)

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Hydrologic Science and Engineering

• In science, we observe conditions and infer
  processes
• In engineering, we simulate processes and predict
  conditions
• Both require characterizing the surrounding
  environment

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Hydrologic Science
It is as important to represent hydrologic
environments precisely with data as it is to
represent hydrologic processes with equations
Physical laws and principles (Mass, momentum,
energy, chemistry)
Hydrologic Process Science (Equations, simulation
models, prediction)
Hydrologic conditions (Fluxes, flows,
concentrations)
Hydrologic Information Science (Observations,
data models, visualization
Hydrologic environment (Physical earth)
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Water Data
Water quantity and quality
Rainfall Snow
Soil water
Modeling
Meteorology
Remote sensing
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Water Data Web Sites
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NWISWeb site output
agency_cd Agency Code site_no USGS
station number dv_dt date of daily mean
streamflow dv_va daily mean streamflow
value, in cubic-feet per-second dv_cd
daily mean streamflow value qualification
code Sites in this file include USGS
02087500 NEUSE RIVER NEAR CLAYTON,
NC agency_cd site_no dv_dt dv_va dv_cd USGS 0208
7500 2003-09-01 1190 USGS 02087500 2003-09-02 649
USGS 02087500 2003-09-03 525 USGS 02087500 2003
-09-04 486 USGS 02087500 2003-09-05 733 USGS 020
87500 2003-09-06 585 USGS 02087500 2003-09-07 485
USGS 02087500 2003-09-08 463 USGS 02087500 2003
-09-09 673 USGS 02087500 2003-09-10 517 USGS 020
87500 2003-09-11 454
Time series of streamflow at a gaging station
USGS has committed to supporting
CUAHSIs GetValues function
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Observation Stations
Map for the US
Ameriflux Towers (NASA DOE)
NOAA Automated Surface Observing System
USGS National Water Information System
NOAA Climate Reference Network
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Water Quality Measurement Sites in EPA Storet
Substantial variation in data availability from
states
Data from Bora Beran, Drexel University
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Water Quality Measurement Sites from Texas
Commission for Environmental Quality (TCEQ)
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Geographic Integration of Storet and TCEQ Data in
HIS
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Observations Catalog
Specifies what variables are measured at each
site, over what time interval, and how many
observations of each variable are available
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CUAHSI Hydrologic Data Access System
(being built using HIS Server in collaboration
with ESRI)
NASA
NCDC
EPA
NWS
Observatory Data
USGS
A common data window for accessing, viewing and
downloading hydrologic information

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HIS Server

• Supports data discovery, delivery and publication
• Data discovery how do I find the data I want?
• Map interface and observations catalogs
• Metadata based Search
• Data delivery how do I acquire the data I want?
• Use web services or retrieve from local database
• Data Publication how do I publish my
  observation data?
• Use Observations Data Model

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HIS Server and Analyst
HIS Server
HIS Analyst
Implemented at San Diego Supercomputer Center and
at academic departments and research centers
Implemented by individual hydrologic scientists
using their own analysis environments
Web Services
Flexible any operating system, model,
programming language or application
Sustainable industrial strength technology
http//www.cuahsi.org/his/webservices.html
Details of HIS Analyst are here
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Point Observations Information Model
http//www.cuahsi.org/his/webservices.html
USGS
Data Source
Network
Streamflow gages
Sites
Neuse River near Clayton, NC
Variables
Discharge, stage (Daily or instantaneous)
Values
Value, Time, Qualifier
206 cfs, 13 August 2006

• A data source operates an observation network
• A network is a set of observation sites
• A site is a point location where one or more
  variables are measured
• A variable is a property describing the flow or
  quality of water
• A value is an observation of a variable at a
  particular time
• A qualifier is a symbol that provides
  additional information about the value

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Data Sources
NASA
Storet
Ameriflux
Unidata
NCDC
Extract
NWIS
NCAR
Transform
CUAHSI Web Services
Excel
Visual Basic
ArcGIS
C/C
Load
Matlab
Fortran
Access
Java
Applications
Some operational services
http//www.cuahsi.org/his/
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CUAHSI Web Services
Web Application Data Portal

• Your application
• Excel, ArcGIS, Matlab
• Fortran, C/C, Visual Basic
• Hydrologic model
• .

• Your operating system
• Windows, Unix, Linux, Mac

Internet
Simple Object Access Protocol
Web Services Library
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Series and Fields
Features
Series ordered sequence of numbers
Point, line, area, volume Discrete space
representation
Time series indexed by time Frequency series
indexed by frequency
Surfaces
Fields multidimensional arrays
Scalar fields single value at each
location Vector fields magnitude and direction
Random fields probability distribution
Continuous space representation
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North American Regional Reanalysis of Climate
Precipitation
Evaporation
Variation during the day, July 2003
NetCDF format
mm / 3 hours
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Data Cube What, Where, When
When
A data value
Where
What
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Continuous Space-Time Data Model -- NetCDF
Time, T
Coordinate dimensions X
D
Space, L
Variable dimensions Y
Variables, V
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Discrete Space-Time Data Model
Time, TSDateTime
TSValue
Space, FeatureID
Variables, TSTypeID
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Hydrologic Statistics
Time Series Analysis
Geostatistics
Multivariate analysis
How do we understand space-time correlation
fields of many variables?
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• Project sponsored by the European Commission to
  promote integration of water models within the
  Water Framework Directive
• Software standards for model linking
• Uses model core as an engine
• http//www.openMI.org

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OpenMI Links Data and Simulation Models
Simple River Model
Trigger (identifies what value should be
calculated)
CUAHSI Observations Data Model as an OpenMI
component
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Typical model architecture
Model application

• Application
• User interface engine
• Engine
• Simulates a process flow in a channel
• Accepts input
• Provides output
• Model
• An engine set up to represent a particular
  location e.g. a reach of the Thames

Write
Input data
Run
Read
Engine
Write
Output data
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Linking modelled quantities
Accepts Provides
Upstream Inflow (m3/s) Outflow (m3/s)
Lateral inflow (m3/s)
Abstractions (m3/s)
Discharges (m3/s)
Accepts Provides
Rainfall (mm) Runoff (m3/s)
Temperature (Deg C)
Evaporation (mm)
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Data transfer at run time
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Models for the processes
Rainfall(database)
RR (Sobek-Rainfall -Runoff)
River (InfoWorks RS)
Sewer (Mouse)
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Data exchange
Rainfall(database)
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RR (Sobek-Rainfall -Runoff)
2 RR.GetValues
1 Trigger.GetValues
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River (InfoWorks-RS)
call
Sewer (Mouse)
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data
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Water OneFlow

• Like Geospatial OneStop, we need a Water
  OneFlow a common window for water data and
  models
• Advancement of water science is critically
  dependent on integration of water information