NRCS Farm Irrigation Rating Index - PowerPoint PPT Presentation

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NRCS Farm Irrigation Rating Index

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NRCS Farm Irrigation Rating Index History and Use By Clare Prestwich Irrigation Engineer NRCS National Water and Climate Center * * * * * * Comparison of the two ... – PowerPoint PPT presentation

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Title: NRCS Farm Irrigation Rating Index


1
NRCS Farm Irrigation Rating Index
  • History and Use
  • By
  • Clare Prestwich
  • Irrigation Engineer
  • NRCS National Water and Climate Center

2
The Need
  • A uniform and objective evaluation method for
    planning irrigation water conservation
  • Method of documenting present water use as well
    as the effects of changes made by improving both
    irrigation system and management
  • Reduce the need for difficult and time consuming
    complete seasonal field evaluations

3
The Process
  • Multidisciplinary team was formed from several
    western states and a national committee
  • Basic data and procedures originated as a result
    of a west wide water conservation emphasis
    program during the 1980s

4
The Results
  • Farm Irrigation Rating Index (FIRI)
  • Assist Offices
  • Plan water management improvements
  • Estimate water conserved by improved management
  • Estimate the runoff and deep percolation
  • Provide a tool for follow up and document
    accomplishment in water management

5
What it is not
  • Replacement for on site evaluations
  • A finite farm or field application efficiency, or
    specific deep percolation and runoff amounts

6
What it is
  • A procedure for comparing improvements or changes
  • Year to year
  • Field, Farm and project level
  • Relative rating
  • A season long evaluation not a single event
  • Composed of three elements
  • Management
  • System
  • Potential efficiency

7
Management
  • Water management is the human element. Decisions
    scientifically based, knowledge to operate the
    system, and maintenance performed.
  • The management element is defined by 6 factors
  • Water measurement
  • Soil moisture monitoring and scheduling
  • Irrigation skill
  • Maintenance
  • Water delivery constraint
  • Soil Condition

8
System Element
  • Factors selected according to irrigation type
  • System element is defined by nine factors
  • Water distribution control
  • Conveyance efficiency
  • Land leveling
  • Climatic
  • Sprinkler design
  • Wind
  • Tail water reuse
  • Emitter clogging
  • Trickle design

9
Potential Efficiency Element
  • A measure of the optimum application efficiency
    for the method of irrigation being used
  • Values based on full canopy cover and systems are
    well designed and maintained.

10
Default Potential Efficiencies
11
Management Factors
Water Measurement Factor
Irrigation Skill and Action Factor
Soil Moisture/Scheduling Factor
12
Water Delivery Factor
Maintenance Factor
Soil Condition Factor
13
System Factors for all Systems
Water Distribution Control Factor
Conveyance Efficiency Factor
14
(No Transcript)
15
Sprinkler System Factors
Climate Factor
Sprinkler Design Factor
Wind Factor
16
Surface System Factors
Land Leveling Factor
Tail water reuse factor
17
(No Transcript)
18
Micro System Factors
Climate Factor
Trickle Design Factor
Emitter Clogging Factor
Wind Factor
19
Rating Index
20
Very easy to put into a program
21
Or spreadsheet
22
FIRI use
  • Use extensively during the 1994 Irrigation
    induced erosion survey
  • Project ranking and comparison for NRCS programs
    (e.g. EQIP, CSP)

23
Example
  • Pasture irrigated by uncontrolled flood with
    3000ft of earth ditch on sandy loam soil. Water
    delivered on a18 day rotation limited rate

24
Present condition
  • Potential Efficiency - 50
  • Management
  • No water measurement .9
  • Schedules based on Plant indicators .94
  • Irrigation Skill Lacks full attention
  • Maintenance good .98
  • Water Delivery fix rotation limited rate .85
  • Soil Condition conservation tillage .98

25
Present Condition
  • System
  • Control at - Farm delivery .94
  • Conveyance 3000ft earth ditch .91
  • Unleveled fields - .82
  • No tail water reuse -1.0
  • MGT .9 x .94 x .96 x .98 x .85 x .98 .663
  • SYS .94 x .91 x .82 x 1 .701
  • FIRI 50 x 0.663 x 0.701 23.3

26
Future
  • Operator wants to change to a graded furrow
    system with land leveled fields and tail water
    reuse. Ditch replaced with gated pipe

27
Future Condition
  • Potential Efficiency change to graded furrow 50
    to 75
  • Management changes
  • Add measuring device .90 to .96
  • Scheduling - no change .94
  • Irrigation skill - follows plan .96 to 1
  • Maintenance - no change .98
  • Delivery - no change .85
  • Soil tillage - no change .98

28
Future Condition
  • System
  • Control change to each set .94 to 1
  • Conveyance change to gated pipe .91 to .99
  • Land change to laser level .82 to 1
  • Add tail water reuse change 1 to 1.08
  • MGT .96 x .94 x 1 x .98 x .85 x .98 .737
  • SYS 1 x .99 x 1 x 1.08 1.069
  • FIRI 75 x 0.737 x 1.069 59.1

29
Compute the water conserved
  • Water conserved with seasonal net irrigation of 2
    ac-feet/ac

30
Guide lines for deep percolation and runoff
31
Problems
  • Management Section has greatest weight
  • More subjective to the person doing rating
  • NRCS required to report water saved or conserved
  • FIRI rating taken as actually efficiency
  • More water saved than available
  • Most states restrict water rights to 4 to 5
    ac-ft/ac
  • From our example
  • 8.6-3.4 5.2 ac-ft/ac saved

32
Possible changes
  • Update Potential Efficiencies
  • Add systems like LESA, MESA, SDI, etc.
  • Update Management factors to reflex current
    Technology
  • Soil moisture/scheduling Flow measurement, etc.
  • Change computation method from straight
    multiplication to a statistical method.

33
  • Original method
  • PE x f1 x f2.x Fn
  • Proposed method
  • PE x (1-sqrt((1-f1)2(1-f2)2.(1-fn)2))
  • The multiplication approach essentially assumes a
    worst case scenario where each influence has full
    weight regardless of the other factors
  • The Statistical approach recognizes that if one
    condition is poor, that the influence of another
    variable is not as great as it would be if it
    were the only problem.

34
Comparison of the two methods
35
Value of FIRI
  • Still an Effective tool
  • Quick, uniform and provides reasonable
    comparisons
  • Users need to be realistic
  • Better input gives better comparison
  • Not meant for black box use
  • Still a relative value
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