Gulf Hypoxia and Water Quality in the Upper

Mississippi River Basin

Catherine L. Kling

Iowa State University

“Least Cost Control of Agricultural Nutrient Contributions to the Gulf of Mexico

Hypoxic Zone,” Sergey Rabotyagov, Todd Campbell, Manoj Jha, Hongli Feng, Philip

W. Gassman, Lyubov Kurkalova, Silvia Secchi, and Catherine L. Kling.

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Overview Water quality related to water quantity, floods,

climate, hydrology, and land use, which are all related economics and policy

Gulf hypoxia and water quality in UMRB

Modeling system for Upper Mississippi River Basin

Water quality and hydrology

Economics/land use models

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Gulf Hypoxia

• Over 400 hypoxic areas worldwide, combined

affected area of 245,000 km2 (Diaz and

Rosenberg, 2008)

•Naturally occurring, but significantly enhanced

by anthropogenic sources of nutrients

•43% N and 41 % P reaching hypoxic zone

originates from UMRB (USGS)

•Gulf of Mexico effects still poorly documented,

brown shrimp fishery effects, recreational fishing

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2008 Hypoxic Zone

2nd largest on record, ~ size of New Jersey

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189,000 square miles in seven states,

dominated by agriculture: 67% of total area,

> 1200 stream segments and lakes on EPAs impaired waters list,

Upper Mississippi River Basin

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How to Address?

Enormous number of farm fields/decision makers

Each : one or more land use/conservation practices

Retire land (e.g., CRP), Reduce tillage, Terraces, Contouring, Grassed Waterways, Reduce fertilizer, better timing, etc.

Costs and effectiveness vary across locations

Other complications:

Biofuels,

Climate change

Other environmental concerns

UMRB Modeling System

Designed to support policy design and to understand

consequences of land use change

Components: SWAT model linked with land use

economic model, loads of data

Evaluation policies by running scenarios Posit changes in prices or policies (taxes, cap and trade, etc.)

Predict changes in land use (shift crop choices, implement conservation practices, retire land from production)

Evaluate water quality effects of a configuration of conservation practices

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SWAT

Physically based and continuous watershed based hydrology and water quality model, daily time step

Developed to predict impacts of land management practices on watershed hydrology and water quality

Watershed divided into sub watersheds, then HRUs, mass balances performed at HRU level, loadings routed through main channels, reservoirs to the watershed outlet

Extensively used world wide; over 250 peer reviewed publications

Key Data Sources

Land use data: 1997 NRI database, 114,000 survey points in

UMRB (non-GIS),Comprehensive cropping history

(rotation),Other land use data

Topography: 30m DEM, USGS Seamless Data Distribution

System,

Climate data: Illinois Water Survey, 535 stations across UMRB

Fertilizer rates and tillage data, 1990-95 Cropping Practice

Survey, ARMS, CTIC

Soil data, derived from USDA Soils5 Data

Economics cost data, crop budgets, state conservation program

costs, land retirement (2007 rental rates)

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UMRB Watershed Model

7070

7120

7090

7030

71007080

7140

7040

7130

7010

7020

7050

7110

7060

Sub Basin

NRI points

Average size NRI “point”

(Acres) HRU Count

7030 4113 1,199 27

7060 5930 922 105

7050 3847 1,581 52

7110 5883 1,088 118

7040 6495 1,056 119

7120 7661 905 151

7090 7167 971 183

7070 5141 1,480 49

7100 8375 1,097 283

7020 7797 1,380 373

7140 7776 1,397 203

7130 9745 1,171 433

7010 8954 1,415 139

7080 14965 975 495

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Using Integrated Models to provide

information on Gulf Hypoxia

1. Hypoxia Action Plan has a goal of reducing the size of the zone to 5,000 km2 by 2015

2. What would be least costly way to achieve this?

Using water quality model, analyze all the feasible scenarios, picking cost-efficient solutions

But, if there are N conservation practices possible for adoption on 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

Genetic Algorithm provides approximate solution

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One possible watershed

configuration

a

d b

a b

c

a

d

a

b

a a

a

13 Fields

4 conservation practices

413= >67 million possible configurations

Genetic Algorithm lingo

Field = gene

Practice options =allele set

watershed configuration = individual (described

by set of genes)

Population = set of configurations

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Algorithm flow diagram

Individual = watershed configuration

= specific assignment of practices

to fields

Population = set of watershed configurations

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Pareto frontier: UMRB

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Tradeoffs of NPS control costs and

water quality benefits

Phosphorus loadings at the outlet vs. costs

In this case, nitrate reduction constraint is binding up to a 50% reduction in P

This suggests an asymmetry in the control of the two nutrients in the UMRB

Empirical cost curve for phosphorus reductions

0

200

400

600

800

1000

1200

1400

1600

1800

0 20 40 60 80 100 120

P loadings, % of baseline

Co

st,

% o

f b

aseli

ne

Unconstrained cost curve

Binding constraint on 30% Nreduction

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Tradeoffs of NPS control costs and

water quality benefits Nitrate loadings at the outlet vs. costs

Thus, if a policy seeks to reduce N by more than 20%, more than 30% reductions in P follow

Empirical cost curve for nitrate reductions

0

200

400

600

800

1000

1200

1400

1600

1800

2000

0 20 40 60 80 100 120

Nitrates, % of baseline

Co

st,

% o

f b

aseli

ne

Unconstrained cost curve

Binding constraint on 30% Preduction

Nitrate-N loading

that yields 30%

nitrate-N and

36% P loading

reduction

Annual additional cost: $ 1.4 billionost)

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USDA payments for farms in Iowa

($million, From EWG)

Year Conservation

Payments

Disaster

Payments

Commodity

Payments

Total USDA

Payments

2000 $169.25 $15.63 $2,118.23 $2,303.10

2001 $208.16 $20.26 $1,742.67 $1,971.09

2002 $223.19 $18.00 $498.03 $739.22

2003 $219.12 $65.30 $761.06 $1,045.48

2004 $221.21 $1.30 $1,030.59 $1,253.10

2005 $219.22 $85.00 $1,936.61 $2,240.83

Next Steps

Compare cost savings to alternative decision

rules

Look at sensitivity of costs to climate change by

incorporating regional climate model predictions

into modeling framework

Investigate policy design: how do we design

incentives to achieve improvements in water

quality at low cost?

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