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Upper Colorado River Basin spatial analysis of water demand. Olga Wilhelmi olgaw@ucar.edu Kevin Sampson Jennifer Boehnert Kathleen Miller NCAR, Boulder. Upper Colorado River Basin Pilot Update Meeting February 24, 2011. Project goals . - PowerPoint PPT Presentation
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Upper Colorado River Basinspatial analysis of water demand
Olga Wilhelmi
olgaw@ucar.edu
Kevin Sampson
Jennifer Boehnert
Kathleen Miller
NCAR, Boulder
Upper Colorado River Basin Pilot Update MeetingFebruary 24, 2011
Project goals • Provide information that is useful
for managing current drought risks and for adapting to changing climate in the UCRB.
• Objectives: – Assess knowledge gaps in the UCRB
water demand data– Analyze spatial and temporal patterns
in water demand– Examine topological relationships
among water users and their respective sources
– Link spatial (and non-spatial) information on water demand to water supply for drought early warning
Water demand estimation Lack of standard definitions and consistent methodologies for
water demand estimation Academic and operational purposes Categories
• Surveys of empirical data• Agroclimatological modeling• Modeling of future water demand based on population growth
Diverse scales of data aggregations / different temporal records National
• USGS: regional and national water use trends (5-year intervals) • BOR: annual consumptive uses and loses
State• Colorado Water Conservation Board and Department of Water Resources collect and
model data on water use (Colorado Decision Support System (CDSS)– HydroBase (historic, real-time, call chronology)– Tools: StateCU, StateMod
Local• Water providers• The Upper Colorado River Basin Study (Hydrospehre, 2003)
Local scale water demand
Secondary markets of water (transfers, exchanges, rent)
Colorado HydroBase Water diversion water use? Decreed water right = primary use? Incomplete “call chronology”
March-8
7
March-8
8
March-8
9
March-9
0
March-9
1
March-9
2
March-9
3
March-9
4
March-9
5
March-9
6
March-9
7
March-9
8
March-9
9
March-0
0
March-0
1
March-0
2
March-0
3
March-0
4
March-0
5
March-0
6
March-0
7
March-0
8
March-0
9
March-1
00
10
20
30
40
50
Calls Per Month
Calls Per Month
Spatial patterns of water demand
GIS System for Analysis / Visualization Geodatabase Component
• Spatial / Non-spatial tables archived together Map Document (GIS) Component
• Analysis and display and manipulation of spatial / non-spatial data
Toolboxes • Models built explicitly for performing geoprocessing
operations on the database
Flexibility to work across scales scales for water administration vs scales for drought
planning and response
Resources to Lease / Buy
Growth (future demand)
Water Right Seniority
Other users Upstream/
Downstream
Competition (Seasonality of demand)
Conceptual design and data availability
UserX,Y Location
MainSource
Local Weather/Drought
Conditions
Secondary Sources
Data Available
Data unavailable
Surface water (streams and reservoirs)Groundwater
Administration No.Assoc. StructureStructure
X, Y LocationStream Mile
X, Y Structure LocationWater right seniority
Lease/Trade/BuyWater AugmentationQuota Increase
Water Provider
Delivery
NIDIS water demand data model Data Model is used to design the schema of a database: tables,
columns, relationships
Provides a template for water demand projects and for NIDIS geodatabase
Allows to exchange data in a similar format
HydroBase
U.S. Drought Monitor
GeodatabaseNHD Plus
Tools
NIDIS Analysis tools Linking diversion records to irrigated parcels Linking users to each other on the river network Demand summaries by geography or sector (use
type) Developing drought “early warning” tools (linking
supply and demand)
Tools executed in ArcGIS DesktopFlexibility of input datasets (test on Yampa
Basin)
Demand estimation
Use of historical diversion table (StructureAnnualAmt) to derive average historical monthly diversions to a subset of structures
Baseline for ‘demand’ Can be analyzed sector by
sector Spatial and temporal
components of demand
Demand estimation (cont.)
• Hydrobase ‘StructureAnnualAmt’ table gives historical diversions from each structure on a monthly basis.
• Units in AF• Values for Summit, Grand, and Eagle Counties.
1 2 3 4 5 6 7 8 9 10 11 120
200,000
400,000
600,000
800,000
1,000,000
1,200,000
1,400,000 TotalAUGCOMDOMEVPFEDFIRFISHUOINDIRRMINMUNOTHPWRRCHRECSNOSTKSTOWLDSeries22
IRR89%
MUN11%
Net Volume
IRRMUN
Net volume of water rights for Grand County, by primary decreed use.
Interview w/ division engineer
Alan Martellaro - Div. 5 Engineer & Judy Sappington, River Administrator October 21, 2010
Basin vulnerabilities Relation to “A-B Line”
Demand measures Standardizing irrigation deliveries by parcel size
Suggestion of case study areas (i.e., Troublesome creek)
River Administration
• Unique methods for Division 5
administration– Zones that determine subjectivity of senior calls
• “A-B Line” (red)• Separates main stem
calls from local calls• Drawn/redrawn based
on frequency of calls from particular users
Irrigated Agriculture
Irrigated parcel layer in CDSS GIS Layers
> 50,000 acres irrigated land in study area
Each parcel associated with a diversion structure
Diversions yield parcel ‘wetness’ (acre feet per acre)
Irrigated Parcels on Troublesome Creek
Supply/demand analysis tools are in development Drought impacts “early
warning” analysis Linking users to
sources of supply potential input factors
Administration area, A-B line
Seniority in water rights system
Relative seniority Supply measure?
Summary and next steps The NIDIS water demand data model was designed to
provide a quantitative spatial analysis framework for geometrically connecting the water users to the network of water delivery systems within the context of a basin or other administrative unit.
The combination of the spatial and non-spatial elements in a geodatabase allows analysis of water demand and potential drought impacts .
Next steps: Documentation and testing of scalability of the assessment tools
and methods for the entire Upper Colorado River Basin. Linking the water demand analysis with the current tools for
monitoring water supply in the Upper Colorado River Basin
Thank You!
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