Economic Incentives to Improve Water Quality in Agricultural Landscapes: Some New Variations on Old Ideas

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Economic Incentives to Improve Water Quality in
Agricultural Landscapes Some New Variations on
Old Ideas

• Catherine L. Kling
• Department of Economics
• Center for Agricultural and Rural Development
• Iowa State University
• AAEA, Denver, 2010

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Topics

• Introduction
• Water quality snapshot
• Current policy
• Policy abatement actions, point-based
• Tools evolutionary algorithms
• Case study Boone River Watershed

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Water Quality Lakes

• Lakes, Reservoirs, Ponds
• 42 assessed, 65 inadequate water quality to
  support uses
• Over 11 million acres are impaired
• Agriculture third highest source of impairment

A cyanobacteria bloom in a Midwestern lake.
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Water Quality Rivers Streams

• Rivers and Streams
• 26 assessed, 50 inadequate water quality to
  support designated uses
• Nearly ½ million stream miles are impaired
• Agriculture leading source of impairment
  (identified as cause of 22 unknown second
  highest)

Photos courtesy Iowa DNR
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Hypoxia Dead Zone

• Depleted oxygen creates zones incapable of
  supporting most life
• 400 worldwide
• Stressed marine and estuarine systems, mass
  mortality and dramatic changes in the structure
  of marine communities (Diaz and Rosenberg, 1995).
• In other words .

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Hypoxic Zone in the Gulf of Mexico
Nutrients and sediments from the Mississippi
River enrich the water making it brown. Over
400 hypoxic Areas worldwide (Diaz and
Rosenberg, 2008)
Image courtesy of Nancy Rabalais (Louisiana
Universities Marine Consortium) and can be found
on the Southern Regional Water Program web site.
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Frequency and Size 1985-Present
www.gulfhypoxia.net
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What abatement options exist?

• In field Management Practices
• Reduced (no) tillage
• Manure, fertilizer management/reduction
• Cover crops, rotation changes
• Land retirement

Panoramic view of gamma grass-big blue stem
planting http//www.fsa.usda.gov/Internet/FSA_Imag
e/ia_767_15.jpg
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What abatement options exist?

• Structural Practices
• Buffers
• Grassed Waterways
• Denitrification, controlled drainage
• Wetland restoration

Photo courtesy Missouri NRCS
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Efficacy and Cost of Practices

• Vary by
• Pollutant
• Field characteristics
• Land use in watershed
• Provision of other ecosystem services
• Ideally, all of these factors considered in
  efficient policy design

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Agricultural Water Pollution Characteristics

• Nonpoint (Segerson, Shortle and Dunn, etc.)
• Measurement costly to trace nutrients to source
• Randomness stochastic events (weather) have
  large effect on damages
• Spatial Aspect (Montgomery, Baumol and Oates)
• Location of release affects damages
• Damages are non-separable between fields

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Current Policy Milieu

• Clean Water Act, 1972
• States required to have water quality standards
  identifying goals for water
• Point sources required to obtain a discharge
  permit
• Nonpoint sources have no such obligations
• Total Maximum Daily Loads are not a standard
• Identify sources

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Programs to Support Policy

• Cost share programs - voluntary
• EPAs 319 program,
• Conservation Reserve Program,
• Environmental Quality Improvement Program,
• Conservation Security Program, and
• Wetlands Reserve Program
• Water Quality Trading
• Lack of standards on agriculture
• 475 of 700 watersheds agriculture contributes
  90 of N loads! (Ribaudo et al. 2008)

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Bottom Line

• Current policy approach
• Voluntary
• Property rights with polluters
• Fundamentally different than pollution control
  other sectors
• Nonpoint source nature
• Makes reversing property right seem hard
• Dont know how much externality generating
  activity is attributable to each source

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An Alternative ?

• Reverse property rights
• Focus on practices (abatement actions)
• Imperfect, but may still be welfare enhancing
• Example Abatement Action Permit System

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An Abatement Action Permit System (AAPS) Based on
Points

• Assign each practice/land use a point

• Set total points for watershed and allocate

• Allow trading

• Choose enforcement mechanism

• Adopt adaptive management

• Include innovation options

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Features

• Puts property rights to clean water in hands of
  society

• Addresses fairness early adopters rewarded

• Base on readily observable practices

• Not perfect, but a way to move forward?

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Soil and Water Assessment Tool

• Watershed-scale simulation model developed by
  USDA - Agricultural Research Service
• Predicts ambient (instream) water quality
  associated with a spatially explicit set of land
  use/conservation practices
• Gassman et al. (2007) identify over 250
  publications using SWAT

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SWAT Team
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Watershed

• 13 Fields, 4 land use/abatement options a, b, c,
  d
• SWAT simulates water quality under alternative
  land use, abatement activities

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Least Cost Problem

• What is the optimal placement of conservation
  practices?
• Brute force strategy
• Using water quality/hydrology model, analyze all
  the feasible scenarios, picking cost-efficient
  solutions
• But, if there are N abatement possibilities for
  each field and there are F fields, this implies a
  total of possible NF configurations to compare
• 30 fields, 2 options ? over 1 billion possible
  scenarios!

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Evolutionary Algorithm --- SPEA2

• Zitzler, Laumanns, and Thiele. SPEA2 Improving
  the Strength Pareto Evolutionary Algorithm,
  TIK-Report 103, May 2001, Errata added September,
  2001
• Other water quality applications Srivastava et
  al. (2002) Veith et al. (2003) Muleta and
  Nicklow (2005) Lant et al. (2005), Arabi et al.
  (2006)

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Strength Pareto Evolutionary Algorithm

• Search technique to approximate pareto optimal
  frontier
• Integrate Evolutionary Algorithm with water
  quality model
• Search for a frontier of cost-efficient nutrient
  pollution reductions

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Terminology
Individual specific assignment of practices
to fields Population set of individual
watershed configurations
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SPEA2 Applied to Optimal Watershed Design
Step I Generate initial population
Step II Run Swat and compute costs
Step III Identify best individuals
Step IV Evaluate stopping rule
Step V Choose parents
Step VI Create offspring
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Creating Offspring by Crossover

• Choose random position for cross
• Swap heads and tails
• Parents abababababab cdcdcdcdcdcd
• Children ababcdcdcdcd cdcdabababab
• Other variations multiple points, random points,
  etc.

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Mutation

• Randomly replace an abatement option with
  another
• Example
• Child1 ababcdcdcdcd
• might become ababacdcdcd
• Usually use a low mutation rate .003

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Boone River Watershed Iowa

• 586,000 acres
• tile drained, 90 corn and soybeans
• 128 CAFOs (480,000 head swine)

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Natural Environment Boone

• Some of the highest
• N loads in Iowa
• TNC priority area
• biodiversity
• Iowa DNR ProtectedWater Area

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Common Land Unit Boundaries

• 16,430 distinct CLUs
• Detailed data related to land use, farming
  practices,
• production costs,
• slope, soils,
• CSRs, etc.
• Weather station data

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The Land use/Abatement Set

• For each CLU
• Current practice
• Land retirement
• No tillage
• Reduced fertilizer (20)
• Cover crops
• Sensible combinations

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Evolutionary Algorithm Uniform Seeds
Description/ Uniform Seed Cost (1000) N Reduction P Reduction
Baseline 0    
Reduced Fertilizer 2,199 6 0
No till 2,589 28 44
NT, RF 4,788 34 45
Cover Crop 13,181 24 32
CCr,RF 15,380 29 32
CCr, NT 15,770 48 42
CCr,NT, RF 17,969 53 43
Land Retirement 110,294 82 92
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Gains from Optimal Placement
Practice Allocation () Practice Allocation () Practice Allocation () Practice Allocation () Practice Allocation ()
Cost (1000 dollars) N P NT NT, RF CC, RF CC NT RF Other
Cover Crops, Red. Fert 15,380 29 32     100    
Same N reductions 2,778 29 44 84 13 lt1 lt1 3
Same Cost 15,365 47 45 8 23 lt1 64 5
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Per acre average costs of abatement actions
needed to achieve equal percent reductions in N
and P
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Thanks for your attention! Much appreciation
to Todd Campbell, Phil Gassman, Manoj Jha, Becky
Olson, Sergey Rabotyagov, and Adriana Valcu for
superb research and presentation support and to
Marca, Silvia, Lyubov and loads of other
thoughtful people too numerous to mention for
insightful discussions. Financial support from
the U.S. Environmental Protection Agency under
their targeted watersheds grant program, the USDA
Conservation Effects Assessment Program, and
CSREES is very gratefully acknowleged.
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Cost Data
Mean Minimum Maximum
Corn Price1 3.08/bu
No Till2 4.09/ac --- ---
Reduced Fertilizer3 4.06/ac (3.6) 0 22
Land Retirement4 206/ac (24) 13 240
Cover Crops5 25/ac

1. Average corn price from 2004-2009.
2. IFIP data.
3. Corn yield response curves to nitrogen fertilizer
   (Sawyer et al.(2006) ) and corn price data used
   to estimate reduced profits
4. The cost of land retirement is estimated Iowa CSR
   and cash rental rates (Edwards and Smith, 2009).
   County level rents were converted into CLU level
   data by weighting county estimates by the share
   of CLU area located in a county.
5. Estimated Costs of Crop Production in Iowa 2008
   (FM-1712) and Estimating Farm Machinery Costs
   (PM-710), actual seed costs, and bulk generic
   glyphosate in 2008. No fertilizer applied for
   cover crop growth

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Least Cost for N and P Reductions
Target Decrease Cost Cost Reduction () Reduction () Watershed practices (counts of HRUs) Watershed practices (counts of HRUs) Watershed practices (counts of HRUs) Watershed practices (counts of HRUs) Watershed practices (counts of HRUs) Watershed practices (counts of HRUs) Watershed practices (counts of HRUs) Watershed practices (counts of HRUs) Watershed practices (counts of HRUs)
Target Decrease (1,000) (/acre) N P Baseline NT CC CC, NT RF NT, RF CC, RF CC, NT, RF Retire Land
10 1,158 2.19 11 21 1781 795 4 0 2 311 3 4 2
20 2,064 3.90 21 33 580 2310 4 2 1 1 2 0 2
30 3,389 6.41 30 44 1 2398 1 3 3 382 5 107 2
40 8,072 15.26 40 45 7 9 4 90 3 2173 5 608 3
50 20,815 39.36 50 50 5 10 5 11 12 966 11 1635 247
60 39,651 74.98 60 60 6 3 5 3 9 213 8 1828 827
70 79,194 149.75 70 81 4 61 2 369 2 417 5 3 2039
80 104,993 198.53 80 89 4 8 3 91 7 1 6 2 2780
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Fitness Assignment