David g tarboton utah state university dtarb@usu edu www engineering usu edu dtarb
Download
1 / 37

David G Tarboton Utah State University [email protected] engineeringu/dtarb - PowerPoint PPT Presentation


  • 108 Views
  • Uploaded on

Hydrologic modeling to quantify watershed functioning and predict the sensitivity to change A discussion of ideas towards an integrated Water Sustainability and Climate Project. David G Tarboton Utah State University [email protected] www.engineering.usu.edu/dtarb. Outline. Some philosophy

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about ' David G Tarboton Utah State University [email protected] engineeringu/dtarb' - deiter


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
David g tarboton utah state university dtarb@usu edu www engineering usu edu dtarb

Hydrologic modeling to quantify watershed functioning and predict the sensitivity to change A discussion of ideas towards an integrated Water Sustainability and Climate Project

David G Tarboton

Utah State University

[email protected]

www.engineering.usu.edu/dtarb


Outline
Outline predict the sensitivity to change

  • Some philosophy

    • Question driven

    • Appropriate simplification

  • An example

  • A framework for thinking about water balance and change

  • Concluding thoughts


My research focus
My Research Focus predict the sensitivity to change

Advancing the capability for hydrologic prediction by developing models that take advantage of new information and process understanding enabled by new technology.

  • Hydrologic Information System

  • Terrain Analysis Using Digital Elevation Models

  • Climate Change Impacts on Hydrology and Stream Ecology

  • Snow melt modeling

  • Modeling the impacts of land cover change on streamflow

  • The Great Salt Lake

  • Trends in Streamflow


The questions that we ask as scientists shape everything that follows. They can lead us to see the world in new ways, or mundane ones. They can spur the development of new approaches, or the recyclingof established ones. They can focus our attention in useful directions, or leave us wandering aimlessly.


WATERS Network: that follows. How can we protect ecosystems and better manage and predict water availability and quality for future generations, given changes to the water cycle caused by human activities and climate trends?

http://www.watersnet.org/docs/WATERS_Network_SciencePlan_2009May15.pdf


Protect ecosystems and better manage and that follows. predict water availability and quality

Grand Challenges

Engineering: Integration of built environment water system

Social Sciences: People, institutions, and their water decisions

Hydrologic Sciences: Closing the water balance

WATERS Network science questions

How is fresh water availability changing, and how can we understand and predict these changes?

How can we engineer water infrastructure to be reliable, resilient and sustainable?

How will human behavior, policy design and institutional decisions affect and be affected by changes in water?

Resources needed to answer these questions and transform water science to address the Grand Challenges

Measurement of stores, fluxes, flow paths and residence times

Synoptic scale surveys of human behaviors and decisions

Water quality data for water throughout natural and built environment

Observatories, Experimental Facilities, Cyberinfrastructure

http://www.watersnet.org/docs/WATERS_Network_SciencePlan_2009May15.pdf


  • From the Preface: that follows.

  • I explore and evaluate the biophysical relationship between ambient climate and the form and function of the associated vegetation

  • Land surface atmosphere boundary conditions are “interactive”

  • Theoretical generation of these atmospheric boundary conditions which are necessarily highly idealized

  • Monteith (1981) “progress can be made only if the number of variables is held to a minimum”

  • Many details neglected

  • XXX may find approach naïve and be offended

  • YYY may welcome the reduction of an intricate multidisciplinary problem to a small set of simple, albeit approximate rules

  • In multidisciplinary endeavors, all the rich scientific detail of each contributing field can’t be retained in their joining, lest the resulting complexity negate the utility of the result


We need to strike a tractable balance in the representation of process complexity (from different disciplines)

  • Building an integrated model (and associated data/information system):

    • is a way to encode and encapsulate knowledge and test hypotheses

    • is a way to formalize communication across disciplines

    • is a journey in research

    • is a process of discovery

    • should involve frequent iteration and adaption


Example a distributed catchment scale water resources planning model
Example: A distributed catchment-scale water resources planning model

The Water Resources Inventory Area 1 (WRIA 1) Nooksack hydrologic model for decision support


Integrated model of Hydrologic, Water Management and Consumption processes at each “catchment”

  • Competition for water resources among users

  • Human activities can alter water balance having effects on stream ecosystems and water quality

  • Simulation modeling used to quantify the likely impacts of water management choices


Rainfall – Runoff Transformation Consumption processes at each “catchment”

  • Enhanced TOPMODEL (Beven and Kirkby, 1979 and later) applied to each subwatershed model element.

  • Kinematic wave routing of

  • subwatershed inputs through

  • stream channel network.

  • Vegetation based

  • interception component.

  • Modified soil zone

  • Infiltration excess

  • GIS parameterization


Consumption processes at each “catchment”q1 ,, q2 , &yf

f & K

Soil derived parameters

Zone Code Polygon Layer

Depth weighted average

Soil Grid Layers

Joined to Polygon Layer

Exponential decrease with depth

Soil parameter look up by zone code

Table of Soil Hydraulic Properties – Clapp Hornberger 1978


Historic (pre-settlement) Consumption processes at each “catchment”

Vegetation derived parameters

Existing


Distributed energy balance snowmelt model
Distributed Energy Balance Snowmelt Model Consumption processes at each “catchment”

Luce, C. H. and D. G. Tarboton, (2004), "The Application of Depletion Curves for Parameterization of Subgrid Variability of Snow," Hydrological Processes, 18: 1409-1422, DOI: 10.1002/hyp.1420.


Area subject to artificial drainage
Area subject to artificial drainage Consumption processes at each “catchment”


Water management
Water Management Consumption processes at each “catchment”

  • Uses

  • Irrigation

    • Soil moisture demand driven

  • Non Irrigation

    • Per capita driven

  • Diversions

  • Sources

  • Reservoir

  • Groundwater

  • Stream

  • Withdrawal limited by availability and right priority

Agriculture

Urban

Stream

Reservoir

Groundwater


Precipitation input and interpolation
Precipitation Input and Interpolation Consumption processes at each “catchment”


Streamflow gauges used in calibration
Streamflow gauges used in calibration Consumption processes at each “catchment”


Calibration
Calibration Consumption processes at each “catchment”


The impact on streamflow of present land use Consumption processes at each “catchment”

Figure 4. Ratio of simulated existing streamflow with no water management to simulated historic streamflow, 30 year average over the years 1961-2005 at each node of the WRIA 1 surface water quantity model.


The impact on streamflow of present water management and use Consumption processes at each “catchment”

Figure 19. Ratio of simulated streamflow under existing conditions to simulated streamflow under existing conditions without water management.


Figure 24. Streamflow at ProjnodeID=164, Drainage 87, Deer Creek.

Figure 25. Existing conditions simulation of user withdrawals from Deer Creek Drainage (Drainage 87)


Existing and Full Build Out scenario simulations of Lake Whatcom active storage.

Discharge from Lake Whatcom (Node 246).


Figure 35. Simulated Historic, Existing and Full Build Out Bertrand Creek Streamflow (ProjNodeID=515)



Impact on water balance
Impact on Water Balance Bertrand Creek

Deer Creek cumulative water balance components simulated under Historic and Existing conditions without water management.


Impact of a trans basin diversion
Impact of a trans-basin diversion Bertrand Creek

Streamflow at ProjnodeID=185, Drainage 109, location of Middle Fork Diversion

Streamflow at ProjnodeID=519, Drainage 163, location where Middle Fork Diversion discharges into Anderson Creek.


The impact on streamflow of future development
The impact on streamflow of future development Bertrand Creek

Ratio of mean streamflow simulated under Full Buildout conditions to mean streamflow simulated under existing conditions.


We need to understand the overall functioning of coupled natural and human system water systems
We need to understand the overall functioning of coupled natural and human system water systems


A general framework for thinking about the overall water balance and change impacts s p q e p q e

E=R natural and human system water systems

Energy limited upper bound

E=P

Water limited upper bound

Q/P

Humid

Arid

Energy Limited

Water Limited

A general framework for thinking about the overall water balance and change impactsS=P-Q-E  P=Q+E

E/P

1

Evaporative Fraction

R/P

Dryness (Available Energy /Precip)

Following Budyko, M. I., (1974), Climate and Life, Academic, San Diego, 508 p.


Retention or Residence time natural and human system water systems

E/P

E = R : energy limited upper bound

large

medium

small

E = P : water limited upper bound

1

Evapotranspiration fraction

R/P

arid

humid

energy limited

water limited

Dryness (available energy /precip)

Budyko [1974] partitioning of input water P into the evapotranspiration fraction, E/P, the residual of which is discharge Q. Dryness or aridity is quantified in terms of R/P. As dryness increases, the evapotranspiration fraction increases. For the same R/P the evaporative fraction is greater when retention is greater as retained water has more opportunity to evaporate or transpire.


Milly budyko model framework for predictions and hypothesis testing
Milly/Budyko Model – Framework for predictions and hypothesis testing

Q/P

Increasing variability in soil capacity or areas of imperviousness

Increasing Retention/Soil capacity

Increasing variability in P – both seasonally and with storm events

Precise observations of Precipitation, Runoff, Soil Moisture, Energy Balance, Water Storage required to discriminate among these hypotheses

Milly, P.C.D. and K.A. Dunne, 2002, Macroscale water fluxes 2: water and energy

supply control of their interannual variability, Water Resour. Res., 38(10).


Uncalibrated runoff ratio
Uncalibrated Runoff Ratio hypothesis testing

Low

  • Explains 88% of geographic variance

  • Remaining 12% difference is consistent with uncertainty in model input and observed runoff

High

Milly, P. C. D., (1994), "Climate, Soil Water Storage, and the Average Annual Water Balance," Water Resources Research, 30(7): 2143-2156.


Some suggestions for working together to solve regional water problems
Some suggestions for working together to solve regional water problems

  • Pick a place. Synergy from multiple studies in a common location.

  • Compelling Science.

  • Societal importance.

  • Shared data systems.

  • Long term commitment.


B water problems

E

A

R

R

Bear

BEAR R

W

E

B

E

R

R

O

J

R

Weber

D

A

N

West Desert

R

Jordan/Provo

Solar Radiation

Development, Growth, Water Resources Management

Air Temperature

GSL System

Precipitation

Air Humidity

Mountain Snow pack

Land Cover Land Use

Lake Evaporation

GSL Level,

Volume, &

Area

Streamflow

Surface Salinity & Temperature

Watershed Evapotranspiration

Pumping

Soil Moisture

And

Groundwater

GSL Salt Load


Summary thoughts on stimulating interdisciplinary water science collaboration
Summary thoughts on stimulating interdisciplinary water science collaboration

  • Communication

  • Enabling Technology

    • Putting data in the system should make an individual researchers job easier

    • Enhance sharing by enabling analysis otherwise not available

  • Maps and Geographic Information Systems are important for synthesis

  • Advancement of water science is critically dependent on integration of waterinformation


ad