Silver Creek Watershed Dynamic Stream Temperature Modeling

Silver Creek Watershed
Dynamic Stream Temperature Modeling and Visualization
March 10, 2015
Stephen Blake
Maria Loinaz
Michael Butts
Agenda
• Introduction:
• Tools and Approach:
Application for Stream Temperature and Ecohydrology
Model Descriptions: MSHE and ECOLab
Adaptation to Realtime Data and Process Visualization/Dissemination
• Q/A Discussion
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Stream Temperature Forcings
Approaches to Groundwater Contribution
Increasing Complexity - Spatial Detail - Level of Effort
Statistical
Approach
In channel data
collection
Regional spatial
correlations
Remote sensing
uses
No ability to
provide
management/
alternatives
Deterministic,
Ignore GW
Focus on
surface only
GW Q = 0
Deterministic,
static GW
GW conduction
Q
0
T
0
Streambed/GW
conduction
Integrated
SW/GW Model
GW advection
and conduction
Q
0
Aquifer T
Includes
SW/GW
management
Fully Dynamic
Heat Transport
Complex and
data intensive
Prohibitive at
watershed
scale
Typically not
inclusive of
management
capabilities
Integrated Surface and Groundwater
flow-temperature model
Model Components and Approach
Precipitation and snow:
• Uses input time series data of precipitation and air temperature to calculate rainfall and snow.
• Snow dynamics are calculated using a degree-day method (temperature-index method)
• Inputs and model can be implemented for real-time use
Unsaturated zone (UZ) and evapotranspiration (ET): calculates actual evapotranspiration,
infiltration rate, and moisture content of the soils.
• Two-Layer Water Balance Method for regional application
• Richards equation approach for local areas
The saturated zone (SZ): uses a finite difference solution of 3D Darcy equation for aquifer flow
• Independent, flexible spatial discretization (vert. and hor.)
• Drainage flow connection to river network
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Model Components and Procedures (continued)
The irrigation module distributes water to crop cells
• from both the canals and the groundwater according to the crop water
• demand, (calculated by the model or user specified), and water availability
Surface water flow model finite difference Saint Venant Equations. It calculates water levels
and discharges for alternating gridpoints along the length of the streams
Exchange flows between the groundwater in MIKE SHE and the MIKE 11 streams
• occur in the direction of the head gradient
• controlled by specified leakage coefficients for the streambeds
Catchment modeling: NAM model in MIKE 11
Lumped model for upper basins and channel tributary areas
(not within MIKE SHE model domain)
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Study Area 1: Wood River Valley and Silver Creek
Hydrology
Low preciptation and high ET
Intensive irrigation
Stream temperature
Impacts of hydrology and
sediment accumulation
Climate change
Ecology - fish habitat
Low flows
Temperature
Oxygen, nutrients
Fish declines and kills
Additional factors that affect stream temperature
Stream-scale factors:
Geomorphology
Gradient / sinuosity
Channel geometry (width-to-depth)
Bank Vegetation
Shading
Bank stability
Microclimate
Hydrology
from Boyd, M., and Kasper, B. 2003
Factors that affect stream temperature
Stream scale factors +
Catchment diffuse sources
Groundwater flows
Tributary flows
Agricultural and urban runoff
Need for an integrated approach
Integrated Hydrologic Model
1D surface water flow
sw-gw exchange
3D Groundwater flow
Model Grid (300m cell)
Streams and Canals
Land Use
Soils
Topography
High
Low
Thickness of Confined Aquifer
High
Low
DHI, 2009
Stream Temperature Model
Head budget solved in ECOLab,
linked to surface and groundwater
flow and channel energy transport
for each time step
1D heat transport equation:
T
t
1
A
( QT )
x
1
A
x
DA
T
x
H
C pd
T = temperature ( C)
V = water volume (m3)
H = heat (Joules)
Cp = heat capacity (J/m3 C)
Q = flow (m3/s)
A = cross-sectional area (m2)
D = longitudinal dispersion (m2/s)
d = water depth (m)
H = net heat flux (J/m2 s)
Net heat flux =
solar + atmospheric + net sensible
– backwater radiation – evaporation
+ net groundwater + runoff
What is ECO Lab?
• Open process module built for
ecological modelling
• Equation solver for coupled ordinary
differential equations integrated with
hydrodynamic models
• Easy: Process descriptions based on
ECO Lab Templates.
• Flexible: User can specify own
expressions in ECO Lab Templates
• Generic: ECO Lab templates are
independent of model dimension
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Hydrodynamic
modelling
Advection-Dispersion
modelling
ECO Lab
Water Quality
Information
ECOLab elements
• State Variables
The information of “interest”, i.e. biomass, concentration
• Constants
(time invariant) parameter, e.g. rates, stoichiometric relationships
• Forcing
(external) Factors influencing the calculations, e.g. temperature, flow
• Auxiliary Variables
Intermediate calculations, outputs
• Process
Describing the change rate of state variables
• Derived outputs
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Pure output items (based on the data values at the end of a time step)
The template editor
ECOLab template:
•
All process descriptions, variable definitions etc. (the “model”) are stored in a
separate file.
•
This “template” can be linked into hydraulic/hydrodynamic/groundwater engines
•
The same model can be used in 1D, 2D or 3D models!
•
Parameterisation is done in the setup
The template process definitions are compiled at runtime (VM approach)
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The template editor
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ECOLab Template
Integrated Surface/Groundwater Heat Balance
ECOLab Stream Temperature template:
1400 lines Structured text file (40kb)
Start with existing template
Edit to suit local process needs and
constants
Edit via GUI or external editor
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Stream vegetation
The stream orientation and the vegetation parameters for shading calculations are specified for all the
streams using a stream segment discretization of 500 meters.
Model Calibration
Flow/temperature gage located at Silver Creek, downstream of tributaries
10
simulated
measured
Flow (m 3 /s)
8
6
4
2
0
4/07
6/07
9/07
12/07
3/08
6/08
month/year
9/08
12/08
3/09
25
9/09
25
simulated
measured
daily average
hourly output
Temperature (°C)
20
Temperature (°C)
6/09
15
10
20
15
10
simulated
measured
5
0
4/07
5
6/07
9/07
12/07
3/08
6/08
month/year
9/08
12/08
3/09
6/09
9/09
1/6/08
16/6/08
1/7/08
day/month/year
16/7/08
31/7/08
Model scenarios
1.
2.
3.
4.
5.
Restoration of stream morphology
Restoration of stream bank vegetation
Water use: e.g., irrigation water savings
(10% reductions)
Land use changes:
1. agriculture land to non-irrigated grass
2. crop change: alfalfa to barley
Climate change:
1960-1990 vs. 2003-2009
2.5
Climate factors
2
1.5
1
0.5
0
-0.5
-1
-1.5
Precipitation (-)
Temperature (°C)
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Spatial distribution of temperature
Heat contribution of Silver Creek sources
Heat source fraction of total incoming heat
1.0
atmospheric
groundwater
Patton Creek = 1%
drainage
temperature
Cain Creek = 9%
25
0.8
20
0.6
15
0.4
10
0.2
5
0.0
0
1.0
Chaney Creek = 4%
Mud Creek = 13%
Loving Creek = 16%
25
0.8
20
0.6
15
0.4
10
0.2
5
0.0
0
1.0
Grove Creek = 43%
Thompson Creek = 2%
Wilson Creek = 6%
25
0.8
20
0.6
15
0.4
10
0.2
5
0.0
1 2 3 4 5 6 7 8 9 101112
0
1 2 3 4 5 6 7 8 9 10 11 12
month
1 2 3 4 5 6 7 8 9 10 11 12
Temperature (°C)
solar
Buhler Drain = 6%
Temperature change, stream-scale scenarios
average change in vegetation height (m)
6.0
4.0
2.0
0.0
-2.0
-4.0
-6.0
-8.0
1
2
3
4
5
6
stream #
7
8
9
10 11
Water/land use scenarios:
water table elevation increase
Water/land use scenarios:
maximum temperature decrease
Adaptation to Real-time Data and Process Visualization/Dissemination
• Data and Model Integration Framework and Data sources
• Remote Sensing Applications
• Web based Visualization and Dissemination
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Real-time Scenario Implementation of Stream Temperature Methods
Real-time Sensor Feeds
• SCADA controls
• Met Data / Forecast
• HYDSTRA
• Telemetry
Remote Sensing Inputs
Snowcover and ET
Model Runs &
Visualization
Automate Reporting
Web Dissemination
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Met Data
Global solar radiation
Diffuse solar radiation
Air temperature
Relative humidity
Wind speed
Remote Sensing
to verify and improve
spatial ET components
Natural
colours
Evapotranspiration
Vegetation
greenness
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Analysis of spatial changes over time
Baseline snowcover processing
Download of
HDF-EOS files
from NASA
servers
Subsetting and
geometric
adjustments
Data
conversion and
quality flag
implementation
Export grids
and statistics to
hydrologic
model
Fractional Snow Cover Field Coded Integer Values
Value
Description
0-100
200
201
211
225
237
239
250
254
255
Fractional snow
Missing data
No decision
Night
Land
iInand water
Ocean
Cloud
Detector saturated
Fill
Customised Solution:
Web Interface to interact and run the model
Groundwater & Surface water modelling
(MIKE SHE reference model)
•
•
•
•
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Web-based interface for model access
Realtime Information management system
Planning tool for alternatives analysis
Scenario comparison
Customised Solution: Web Interface for Scenario Comparisonel
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References
Integrated flow and temperature modeling at the catchment scale
Maria C. Loinaz, Hasse Kampp Davidsen, Michael Butts, Peter Bauer-Gottwein
Journal of Hydrology 495 (2013) 238–251
Other Publications available
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Thank you!
Further Information and Contacts
DHI US Contact details:
Stephen Blake: [email protected]
mail:
[email protected]
www:
www.dhigroup.com
www.mikebydhi.com
user forum: fttp://forum.mikebydhi.com
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