# Environmental Assessment ~~~ Modeling ~~~ Water Resources 

# Phase III/IV Modeling Water Quality Impacts of Corn Production

for Ethanol in the Upper Mississippi River Basin

Prepared by

AQUA TERRA Consultants

Mountain View, CA 94043

Decatur, GA 30030

With

Texas A & M University

Spatial Sciences Laboratory (TAMU-SSL)

College Station, TX 77843

Under Work Assignments 3-32 and 3-33

of US EPA Contract No. EP-C-06-029

Submitted to

Dr. David Wells,

US EPA Office of Water

Washington, DC 20460

January 20, 2010

# CONTENTS

Page

Figures

............................................................................................................................... iii

Tables

.............................................................................................................................. .. iv

1.0 Introduction and Scenario Development .................................................................. 1

1.1 Background and Objectives. ................................................................................ 1

1.2 Scenario Analyses for Ethanol Production in the UMRB...................................... 2

2.0 Model Results .............................................................................................................. 4

2.1 Baseline Setup and Calibration............................................................................ 4

2.2 Future Scenario Development.............................................................................. 5

2.3 Scenario Results .................................................................................................. 7

2.4 Summary Analyses of Current Model Results...................................................... 12

3.0 References ................................................................................................................... 14

Appendices .................................................................................................................... 15

Appendix A – Detailed Modeling Results ....................................................................

A Q U A T E R R A C o n s u l t a n t s 

# ii

# FIGURES

Figure 1.1 Upper Mississippi River Basin with 8-digit HUCs ........................................... 1

TABLES

Table 1.1 Summary of corn yield, corn area, and ethanol produced for UMRB scenarios 3

Table 2.1 Comparison of average annual total nitrogen loads for AEO 2007 Scenario

...... 7

Table 2.2 Comparison of average annual total nitrogen loads for RFS1 Scenario ............. 8

Table 2.3 Comparison of average annual total nitrogen loads for 2022 Control Case

Volume Scenario ................................................................................................. 8

Table 2.4 Comparison of average annual total phosphorous loads for AEO 2007

Scenario .............................................................................................................. 8

Table 2.5 Comparison of average annual total phosphorous loads for RFS1 Scenario

...... 9

Table 2.6 Comparison of average annual total phosphorous loads for 2022 Control Case

Volume Scenario ................................................................................................. 9

Table 2.7 Comparison of average annual sediment outflow and streamflow for AEO

2007 Scenario ..................................................................................................... 9

Table 2.8 Comparison of average annual sediment outflow and streamflow for RFS1

Scenario .............................................................................................................. 10

Table 2.9 Comparison of average annual sediment outflow and streamflow for Corn

Stover Scenario................................................................................................... 10

Table 2.10 Comparison of 2007 AEO and 2022 Control Volume Case scenarios’ corn

areas and ethanol goals (% difference between scenarios in parentheses) ....... 10

Table 2.11 Comparison of 2007 AEO and 2022 Control Volume Case scenarios’ average

annual nitrogen loads (% difference between scenarios in parentheses) ........... 11

Table 2.12 Comparison of 2007 AEO and 2022 Control Volume Case scenarios’ average

annual phosphorous loads (% difference between scenarios in parentheses)

... 11

Table 2.13 Comparison of 2007 AEO and 2022 Control Volume Case scenarios’ average

annual sediment outflow (% difference between scenarios in parentheses)....... 11

A Q U A T E R R A C o n s u l t a n t s 

# iii

# SECTION 1.0

INTRODUCTION

1.1 BACKGROUND AND OBJECTIVES

The production of biofuels has become an important industry in the US and has seen a dramatic

expansion in production capacity, with continued plans for future expansion. In 2006, the U.S.

produced approximately 4.9 billion gallons of ethanol, mostly from corn kernels. Of the potential

crops for biofuel production, corn has the highest rates of application of fertilizers and

pesticides, leading to the concern that higher corn production could result in an increased

loading of nutrients, pesticides, and sediment to waterways, including major rivers and

estuaries.

Given this potential for problems associated with corn-based ethanol production, the focus of

this study is to model and assess the potential impacts on surface waters resulting from the

expected increase in corn production in the Upper Mississippi River Basin (UMRB) (see Figure

1.1). The UMRB was selected because it repres ents many potential issues associated with

ethanol production, including its connection to major water quality concerns such as the hypoxia

problems identified in the Gulf of Mexico.

Figure 1.1 : Upper Mississippi River Basin with 8-digit HUCs (Hydrologic Unit Codes)

This report is a continuation of work begun under previous Work Assignments (2-32 and 2-33).

Those efforts (Phases I and II) involved the initial setup of the SWAT model for the UMRB and

A Q U A T E R R A C o n s u l t a n t s 

# 1

# the running of scenarios based on anticipated future ethanol goals. This portion of the current

effort (Phases III and IV) involved running three additional sets of scenarios to further

investigate possible ethanol production futures. Details of the model setup are included in the

final report from Phases I and II (US EPA, 2008).

1.2 SCENARIO ANALYSES FOR ETHANOL PRODUCTION IN THE UMRB

In order to assess alternative potential future conditions within the UMRB, such as alternative

levels of increased corn production, we first established a SWAT model of a baseline scenario

for ‘current’ conditions, to which the results of ‘future’ condition model runs can be compared. In

developing the baseline scenario, it was necessary to select a target year, or window of years,

that represent the conditions on the watershed. As in the previous study the year 2005 was

selected as the mid-point of the target period for baseline conditions, with one update. The year

2007 was selected as the target year in determining the baseline corn yield value. As with most

models of this scale, it was not possible to hav e all of the data sources come from the exact

same time period. It is a common modeling practice to combine the best available data sources

for model development in an attempt to characterize the baseline condition within a short time

window or period.

The SWAT model was applied (i.e. calibrated) to the UMRB using weather data from the period

of 1960 to 2001, and flow and water quality data from 13 USGS gages on the mainstem of the

Mississippi River, spatially distributed from the upper reaches in Minnesota and Wisconsin to

the UMRB outlet below Grafton, Illinois.

The SWAT model was setup on 131 sub-watersheds (8-digit Hydrologic Unit Code (HUC)) for

the entire UMRB using the 2001 National Land Cover Data (NLCD) and Cropland Data Layer

(CDL, 2004-06) as the land use coverage for the baseline scenario; the USDA-NRCS

STATSGO provided the soils data for the entire analyses. In addition, information from the

Conservation Tillage Information Center (CTIC) and USDA Census of Agriculture 2002/1997

was used to identify the cropping rotation and management practices for the agricultural land

areas by these same 131 sub-watersheds. Based on the management information at this level,

each sub-watershed was assigned appropriate management and tillage practices. As noted

above, the model was setup to run using 1960-2001 weather data, a 42-year time period,

available from NRCS climatic data center, which is a derivative of NOAA-NWS-NCDC datasets.

In addition the weather data has been spatially interpolated to assign one distinct weather

station to each sub-basin.

The simulation of processes modeled by SWAT is carried out within the Hydrologic Response

Unit (HRU). HRUs represent unique combinations of land use, soil characteristics, and

management within each sub-basin being modeled. The UMRB model contains a total of

16,416 HRUs with the number of HRUs per 8-digit HUC ranging from 57 to 216.

The 42-year SWAT model runs were performed and the results analyzed to establish runoff,

sediment, nitrogen, and phosphorous loadings from each of the 131 8-digit HUC subwatersheds and the larger 4-digit sub-basins, along with the total outflow from the UMRB and at

the various USGS gage sites distributed along the Mississippi River mainstem. These results

provided the baseline scenario model values to which the future alternatives are compared.

Once the SWAT baseline model is run and baseline results are tabulated, SWAT can be used to

analyze a wide range of various scenarios through changes in land use or cropping conditions

(e.g. increase corn production, increased yields), management practices, nutrient inputs (e.g.

increased fertilizer applications), etc.

A Q U A T E R R A C o n s u l t a n t s 

# 2

# In this study, SWAT model runs were performed for conditions corresponding to the years 2010,

2015, 2020, and 2022 for three different scenarios, each of which contained a unique set of

national ethanol goals. These national goals were adjusted for the UMRB based on a 42.3%

ratio of ethanol production capacity within the UMRB compared to national capacity. This ratio

was determined by overlaying a coverage of nationwide ethanol plants with a coverage of the

study area. Production from ethanol plants within the study area were totaled and then divided

by the nationwide production. Both current production and planned expansion were included in

the totals. Ethanol location and production information was taken from the Renewable Fuels

Association’s (RFA) table of Ethanol Biorefinery Locations

( http://www.ethanolrfa.org/industry/locations/ ) (Renewable Fuels Association, 2008). The

resulting UMRB ethanol production goals were converted into the corresponding required corn

production acreage, i.e. the extent of corn acreage needed within the UMRB to meet those

ethanol production goals.

The three scenarios analyzed in this effort were:

• Annual Energy Outlook (AEO) 2007 Reference Case – national ethanol goals of 10.49

BGY in 2010, 11.1 BGY in 2015, 11.83 BGY in 2020, and 12.29 BGY in 2022

• Renewable Fuel Standard (RFS) 1 – constant national ethanol goal of 7.05 BGY starting

in 2012

• 2022 Control Case Volume – national ethanol goals of 11.24 BGY in 2010, 14.79 BGY in

2015, and 15.0 BGY for 2016 and beyond (adjustments to corn stover removal were not

implemented until 2022 for this scenario and thus were not included in these model runs)

The baseline average corn yield for the UMRB was established at 140.7bu/ac for the previous

study. Using the same 1.23% annual yield increase as the previous study (USDA, 2008), this

translated to a corn yield of 144.2 bu/ac for the updated baseline of 2007. Applying the assumed

yield increase resulted in 3.7%, 10.3%, 17.2%, and 20.1% increases in yields, respectively, for

the four target years – 2010, 2015, 2020, 2022. The SWAT model was executed for the

available input climate record, 1960-2001, with the model run under conditions of the adjusted

corn production and yields noted above. Separate model runs were performed for each of the

four projection years, and the model results we re analyzed to provide loadings for comparison

with the baseline loadings. A summary of yield and ethanol production for the model runs in

each scenario and each target year is shown in Table 1.1.

Table 1.1 : Summary of corn yield, corn area, and ethanol produced for UMRB scenarios

AEO 2007

Reference Case RFS1 2022 Control

Case Volume Model

Run Average

Yield,

bu/ac Corn

Area,

million ac Ethanol

Goal,

BGY Corn

Area,

million ac Ethanol

Goal,

BGY Corn

Area,

million ac Ethanol

Goal,

BGY

Baseline 144.2 23.65 3.04 23.65

- 23.65

-

2010 149.6 26.83 4.44 23.65

- 27.61 4.75

2015 159.0 26.78 4.70 22.78 2.98 30.40 6.26

2020 169.0 26.80 5.00 22.35 2.98 29.73 6.35

2022 173.2 26.96 5.20 22.20 2.98 29.40 6.35

A Q U A T E R R A C o n s u l t a n t s 

# 3

# SECTION 2.0

MODEL RESULTS

In order to assess the potential impacts of increased corn production, due to projected

increased demands for ethanol, the SWAT model was applied to the UMRB to first establish

that the model can reasonably represent the flow, sediment and nutrient loads within and

leaving this large regional river basin. This baseline condition was defi ned to represent UMRB

conditions corresponding to the approximate time frame of 2003-2006. Then the model was

exercised with changed conditions to reflect alternative future scenarios, for the ethanol

demands expected for the time horizons of 2010, 2015, 2020, and 2022. The differences

between the baseline and the other time horizons reflect the impacts that might be expected

due to the growing demands for ethanol as a biofuel.

This section first describes the baseline conditions and initial calibration efforts, followed by the

details of the model scenario changes for the adjusted ethanol production targets for time

horizons noted above.

2.1 BASELINE SETUP AND CALIBRATION

The main objective of this study was to produce datasets (i.e., flow, sediment, nitrogen,

phosphorous) for the UMRB that can be used to study the impact of increased biofuel

production, specifically ethanol, and possibly other scenarios (e.g. climate change, nutrient

management and other best management practices) on water quantity and quality. A model that

mimics important physical, chemical, and biotic processes within the watershed, and is based

on extensive and spatially explicit datasets, provi des a sound basis for using the model as a tool

to investigate the likely impacts of changed conditions. Even though the model results may not

produce statistics (i.e., modeled vs observed) that are generally considered good or very good

in terms of agreement with observations, the model can still be a viable and valuable tool for

assessing potential relative impacts of changes on the watershed.

As described in section 1.2, while developing the baseline scenario, it was necessary to select a

target year, or window of years, that represent the conditions on the watershed. For this study

the year 2005 was selected as the mid-point of the target period for baseline conditions. As with

most models of this scale, it was not possible to have all of the data sources come from the

exact same time period. It is a common modeling practice to combine the best available data

sources for model development in an attempt to characterize the baseline condition within a

short time window or period. As described in the Phase I/II report (US EPA, 2008), the majority

of the data sources were derived from the years 2000 through 2006. In reality, the baseline

scenario represents watershed conditions within a two to three year period centered on the

target year of 2005.

To make this effort more current, the year 2007, rather than 2005 (used in Phases I/II), was

selected as the year for establishing baseline corn production. Using the same baseline

parameter set that produced an area-weighted average of 140.7 bu/ac in 2005, the same

assumed annual yield increase (1.23%) was applied to establish a 2007 baseline yield of 144.2

bu/ac. Another assumption that was updated was the fraction of baseline corn contributing to

ethanol production. Where Phases I/II assumed that 12% of existing corn contributed to ethanol

production, a value of 33% was used for Phases III/IV, based on current estimates (U.S.

Department of Agriculture, 2009).

A Q U A T E R R A C o n s u l t a n t s 

# 4

# Detailed comparisons of the SWAT UMRB model with observed data are found in the phase I/II

report. As with the initial study, calibration was limited to crop yield and uptake values to ensure

that yield levels under current and projected future conditions were an accurate reflection of

planned ethanol production targets for each scenario. Given the model’s setup, it is readily

extendible to study various scenarios such as biofuel potential expansion of corn or switch grass

production acreages or combined climate change effects on biofuel in this large area.

2.2 FUTURE SCENARIO DEVELOPMENT

Once the SWAT baseline model is run and baseline results tabulated, SWAT can then be used

to analyze a wide range of various scenarios through changes in land use or cropping

conditions (e.g. increase corn production, increased yields), management practices (e.g.

BMPs), nutrient inputs (e.g. increased fertilizer applications), etc.

In this study, SWAT scenario analyses were performed for the years 2010, 2015, 2020, and

2022 with three distinct national corn ethanol production goals. These national goals were

adjusted for the UMRB based on a 42.3% ratio of ethanol production capacity within the UMRB

compared to national capacity. As noted above, this fraction was determined by overlaying a

coverage of nationwide ethanol plants with a coverage of the study area. Production from

ethanol plants within the study area were totaled and then divided by the nationwide production.

Both current production and planned expansion were included in the totals. Ethanol location

and production information was taken from Rene wable Fuel Association’s table of Ethanol

Biorefinery Locations ( http://www.ethanolrfa.org/industry/locations/ ) in April 2008.

The resulting UMRB ethanol production goals for the three scenarios are shown in Table 1.1.

Using an assumed average of 2.7 gallons per bushel (G/bu) of corn and a moisture content of

20% when converting corn grain mass to bushels, the resulting UMRB goals were converted

into the corresponding required corn production acreage (i.e. the extent of corn acreage needed

to meet those ethanol production goals).

In addition, a 1.23% annual yield increase was imposed, based on USDA projections, to

account for assumed advances in crop science, resulting in 3.7%, 10.3%, 17.2%, and 20.1%

increases in yields, respectively, for the four target years – 2010, 2015, 2020, 2022. This

produced the following future yield averages for the target years:

o 2010 – 149.6 bu/ac

o 2015 – 159.0 bu/ac

o 2020 – 169.0 bu/ac

o 2022 – 173.2 bu/ac

In computing the amount of corn acres needed for each scenario, it was assumed that the

fraction of baseline scenario corn (23.65 million acres) used for ethanol remained constant at

33%, as does the conversion factor of 2.7G/bu corn. It is also assumed that 100% of new corn

in the future scenarios is used for ethanol production.

To account for future corn acreage increases, it was necessary to develop a standard

methodology for updating the model to reflect such changes. Given the scale and complexity of

the model, the methodology required the number of HRUs in each sub-basin to remain

constant. Thus, to generate increased corn ac reage, the area terms of selected HRUs were

modified to “shift” acreage from allowable land uses (see below) into corn. The approach used

in developing the future scenarios was as follows:

• Allow the following land use conversions:

A Q U A T E R R A C o n s u l t a n t s 

# 5

# o Conservation Reserve Program acres Æ continuous corn and corn/soybean

rotations

o corn/soybean rotations Æ continuous corn

o hay and other row crops Æ continuous corn and corn/soybean rotations

• All land uses available for conversion were checked to see if there was a matching corn

HRU (i.e., same soil and slope class) to which they can be converted.

• The total amount of potential corn area from these matching HRUs was determined

(24.7 million acres for the above conversions).

• The ratio of new corn needed to potential new corn was calculated for the current

scenario (e.g. 3.18 million acres/24.7 million acres for AEO in 2010 = 12.9%).

• For each HRU that can be converted to corn, the above ratio (e.g. 12.9%) was then

applied to the area terms of the matching HRUs to create the new corn area needed.

A number of issues were discovered as this procedure was developed. Originally it was

assumed that all corn conversions would be to continuous corn. However, many sub-basins did

not contain any continuous corn (particularly in Northern areas). This required a decision – is

the new corn demand met by converting only corn/soybean rotations (there is enough of this to

meet all scenario demands) and thus not increase corn area in many sub-basins or should hay

and other row crops be allowed to be converted to corn/soybean rotations so that those subbasins without continuous corn will see an increase in corn area. This methodology chose the

later option.

Additionally, this methodology meant there was variability across sub-basins in the percentage

of HRUs converted since a sub-basin’s make- up (i.e. soils, slopes, land uses) impacted how

well its corn HRUs matched other HRUs for conversion. Thus, there was variability across subbasins in the percent corn area increase while still achieving the needed percent increase

across the UMRB.

Given a baseline average yield of 144.3 bu/ac and applying the assumptions described here,

the corn areas changes required for the future scenarios were established as shown in Table

1.1. One notable result of the assumed yield increases was that for the RFS1 scenario, with its

constant and moderate future ethanol goals, less corn acreage was needed in future target

years (see Table 1.1). To meet this need, land use conversions from continuous corn to corn in

rotation were made using the same methodology described above.

A Q U A T E R R A C o n s u l t a n t s 

# 6

# 2.3 SCENARIO RESULTS

In discussing the results it is useful to review the three scenarios that were run:

• Annual Energy Outlook (AEO) 2007 Reference Case – national ethanol goals of 10.49

BGY in 2010, 11.1 BGY in 2015, 11.83 BGY in 2020, and 12.29 BGY in 2022

• Renewable Fuel Standard (RFS) 1 – constant national ethanol goal of 7.05 BGY starting

in 2012

• 2022 Control Case Volume – national ethanol goals of 11.24 BGY in 2010, 14.79 BGY in

2015, and 15.0 BGY for 2016 and beyond (adjustments to corn stover removal were not

implemented until 2022 for this scenario and thus were not included in these model runs)

Each of the national ethanol goals was adjusted for the UMRB based on the percent of

biorefineries found in the UMRB (42.3%, see Section 1.2). The SWAT model was executed for

the available input climate record, 1960-2001, with the model run under conditions of the

adjusted corn production and yields noted in Table 1.1. Separate model runs were performed

for each of the four projection years for the three different scenarios. The model results were

analyzed to provide projected loadings for comparison with the baseline loadings.

In viewing these results note that the “Unit Land Load” is the rate at which the nutrient entered

the waterways and the “Total Land Load” is the total amount of nutrient that entered the

waterways. The “Total Outflow” is the total amount of nutrient that left the UMRB, with the

difference between it and the “Total Land Load” being used to determine the percentage of

nutrient “Removed by Assimilation”. Load and outflow values are from all land uses, not just

corn areas. The “Corn Area Increase” and “Outflow Change” percentages represent the change

from baseline conditions for each year.

Tables 2.1 – 2.3 show average annual total nitrogen loads for baseline and future projections for

the three scenarios. Both the AEO 2007 and 2022 Control Case Volume scenarios included

significant corn area increases, with the UMRB SWAT model responding in the same manner

as in the Phase I/II study. In these cases, the total nitrogen load increases through the first

(2010) or second (2015) target years, but decreases from those levels in the later years (2020 –

2022). As discussed in the Phase I/II report, the decrease in nitrogen loads can be attributed to

the increased yield production of future scenarios, resulting in greater plant uptake of nutrients.

Additionally, less corn acreage was needed for later model years due to the increased yield

values. These factors also explain the results for the RFS1 scenario, where decreasing corn

areas resulted in lower loadings than Baseline for all target years.

Table 2.1 : Comparison of average annual total nitrogen loads for AEO 2007 Scenario

Scenario Corn

Area,

million ac Unit Land

Load,

lbs/ac Total Land

Load,

million lbs Total

Outflow,

million lbs Removed by

Assimilation,

% Corn Area

Increase, % Outflow

Change, %

Baseline 23.65 15.55 1,889 1,423 24.7

2010 26.83 15.91 1,933 1,462 24.4 13 2.72

2015 26.78 15.73 1,911 1,445 24.4 13 1.51

2020 26.80 15.53 1,887 1,425 24.5 13 0.14

2022 26.96 15.44 1,887 1,417 24.5 14 -0.42

A Q U A T E R R A C o n s u l t a n t s 

# 7

# Table 2.2 : Comparison of average annual total nitrogen loads for RFS1 Scenario

Scenario Corn

Area,

million ac Unit Land

Load,

lbs/ac Total Land

Load,

million lbs Total

Outflow,

million lbs Removed by

Assimilation,

% Corn Area

Increase, % Outflow

Change, %

Baseline 23.65 15.55 1,889 1,423 24.7

2010 23.65 15.46 1,878 1,414 24.7 0 -0.63

2015 22.78 15.12 1,838 1,382 24.8 -3.7 -2.91

2020 22.35 14.86 1,806 1,357 24.9 -5.5 -4.68

2022 22.20 14.76 1,794 1,347 24.9 -6.1 -5.37

Table 2.3 : Comparison of average annual total nitrogen loads for 2022 Control Case Volume

Scenario

Scenario Corn

Area,

million ac Unit Land

Load,

lbs/ac Total Land

Load,

million lbs Outflow,

million lbs Removed by

Assimilation,

% Corn Area

Increase, % Outflow

Change, %

Baseline 23.65 15.55 1,889 1,423 24.7

2010 27.61 16.00 1,944 1,467 24.5 17 3.05

2015 30.40 16.01 1,946 1,469 24.5 29 3.20

2020 29.73 15.73 1,912 1,442 24.6 26 1.31

2022 29.40 15.61 1,897 1,430 24.6 24 0.44

Tables 2.4 – 2.6 show average annual total phosphorous loads for baseline and future

projections for the three scenarios. These results followed a similar pattern as those for

nitrogen. This is due to the same issues as shown for nitrogen (increase in plant uptake and

decrease in corn area over time) applied to the phosphorous loads.

Table 2.4 : Comparison of average annual total phosphorous loads for AEO 2007 Scenario

Scenario Corn

Area,

million ac Unit Land

Load,

lbs/ac Total Land

Load,

million lbs Outflow,

million lbs Removed by

Assimilation,

% Corn Area

Increase, % Outflow

Change, %

Baseline 23.65 1.450 176.2 130.6 25.9

2010 26.83 1.475 179.3 134.6 24.9 13 3.09

2015 26.78 1.466 178.2 133.7 25.0 13 2.38

2020 26.80 1.456 177.0 132.7 25.0 13 1.64

2022 26.96 1.453 176.5 132.4 25.0 14 1.36

A Q U A T E R R A C o n s u l t a n t s 

# 8

# Table 2.5 : Comparison of average annual total phosphorous loads for RFS1 Scenario

Scenario Corn

Area,

million ac Unit Land

Load,

lbs/ac Total Land

Load,

million lbs Outflow,

million lbs Removed by

Assimilation,

% Corn Area

Increase, % Outflow

Change, %

Baseline 23.65 1.450 176.2 130.6 25.9

2010 23.65 1.445 175.6 130.1 25.9 0 -0.39

2015 22.78 1.427 173.5 128.4 26.0 -3.7 -1.70

2020 22.35 1.412 171.6 126.9 26.0 -5.5 -2.83

2022 22.20 1.406 170.8 126.3 26.1 -6.1 -3.28

Table 2.6 : Comparison of average annual total phosphorous loads for 2022 Control Case Volume

Scenario

Scenario Corn

Area,

million ac Unit Land

Load,

lbs/ac Total Land

Load,

million lbs Outflow,

million lbs Removed by

Assimilation,

% Corn Area

Increase, % Outflow

Change, %

Baseline 23.65 1.450 176.2 130.6 25.9

2010 27.61 1.480 179.9 133.7 25.7 17 2.35

2015 30.40 1.478 179.6 133.6 25.6 29 2.27

2020 29.73 1.467 178.2 132.4 25.7 26 1.38

2022 29.40 1.461 177.6 131.8 25.8 24 0.95

Tables 2.7 – 2.9 show results for both sediment and flow baseline and future projections for the

three scenarios. Neither constituent showed dramatic change from one scenario to the next.

This is primarily due to the corn being model ed as a well-managed crop in terms of sediment

loss, including the corn stover remaining on the fields as protective cover following harvest.

Table 2.7 : Comparison of average annual sediment outfl ow and streamflow for AEO 2007 Scenario

Scenario Corn Area,

Million ac Sediment,

million tons Flow,

cfs Sediment

Change, % Flow

Change, %

Baseline 23.65 6.201 121920

2010 26.83 6.231 122170 0.48 0.21

2015 26.78 6.221 121920 0.32 0.00

2020 26.80 6.214 121740 0.21 -0.15

2022 26.96 6.211 121670 0.16 -0.21

A Q U A T E R R A C o n s u l t a n t s 

# 9

# Table 2.8 : Comparison of average annual sediment outflow and streamflow for RFS1 Scenario

Scenario Corn Area,

Million ac Sediment,

million tons Flow,

cfs Sediment

Change, % Flow

Change, %

Baseline 23.65 6.201 121920

2010 23.65 6.190 121830 -0.05 -0.07

2015 22.78 6.187 121620 -0.23 -0.25

2020 22.35 6.178 121410 -0.37 -0.42

2022 22.20 6.174 121320 -0.44 -0.49

Table 2.9 : Comparison of average annual sediment outflow and streamflow for 2022 Control Case

Volume Scenario

Scenario Corn Area,

Million ac Sediment,

million tons Flow,

cfs Sediment

Change, % Flow

Change, %

Baseline 23.65 6.201 121920

2010 27.61 6.232 122110 0.49 0.16

2015 30.40 6.233 122000 0.52 0.06

2020 29.73 6.224 121790 0.37 -0.10

2022 29.40 6.220 121710 0.30 -0.17

Along with the percent changes in constituent loads, an additional comparison of interest is the

percent difference in loads between the two scenarios with significant corn area increases (AEO

2007, 2022 Control Case Volume). As shown in Table 2.10, the 2022 Control Case Volume

scenario had substantially higher ethanol goals and corn area increases than the AEO 2007

scenario. Tables 2.11 – 2.13 show that years with substantial differences in corn area (2015 –

2022) exhibited greater load increases in the 2022 Control Case Volume scenario than in the

AEO 2007 scenario. For 2010 the difference in corn areas is much smaller, yielding a nearly

imperceptible decrease in loads.

Table 2.10 : Comparison of 2007 AEO and 2022 Control Volume Case scenarios’ corn areas

and ethanol goals (% difference between scenarios in parentheses)

AEO 2007 2022 Control Case Volume

Model

Run Average

Yield,

bu/ac Corn

Area,

million ac Ethanol

Goal,

BGY Corn Area,

million ac Ethanol Goal,

BGY

Baseline 144.2 23.65

- 23.65

-

2010 149.6 26.83 4.44 27.61 (2.9) 4.75 (6.9)

2015 159.0 26.78 4.70 30.40 (13.5) 6.26 (33.2)

2020 169.0 26.80 5.00 29.73 (10.9) 6.35 (27.0)

2022 173.2 26.96 5.20 29.40 (9.1) 6.35 (22.1)

A Q U A T E R R A C o n s u l t a n t s 

# 10

# Table 2.11 : Comparison of 2007 AEO and 2022 Control Volume Case scenarios’ average

annual nitrogen loads (% difference between scenarios in parentheses)

2007 AEO 2022 Control Volume Case

Model

Run Total Land Load,

million lbs Total Outflow,

million lbs Total Land Load,

million lbs Total Outflow,

million lbs

2010 1948 1470 1944 (-0.21) 1467 (-0.20)

2015 1911 1441 1946 (1.83) 1469 (1.94)

2020 1887 1421 1912 (1.32) 1442 (1.48)

2022 1877 1413 1897 (1.07) 1430 (1.20)

Table 2.12 : Comparison of 2007 AEO and 2022 Control Volume Case scenarios’ average

annual phosphorous loads (% difference between scenarios in parentheses)

2007 AEO 2022 Control Volume Case

Model

Run Total Land Load,

million lbs Total Outflow,

million lbs Total Land Load,

million lbs Total Outflow,

million lbs

2010 180.0 133.8 179.9 (-0.06) 133.7 (-0.07)

2015 178.2 132.3 179.6 (0.79) 133.6 (0.98)

2020 177.0 131.3 178.2 (0.68) 132.4 (0.84)

2022 176.5 130.9 177.6 (0.62) 131.8 (0.69)

Table 2.13 : Comparison of 2007 AEO and 2022 Control Volume Case scenarios’ average

annual sediment outflow (% difference between scenarios in parentheses)

2007 AEO 2022 Control Volume

Case

Model

Run Total Outflow,

million tons Total Outflow,

million tons

2010 6.231 6.232 (0.02)

2015 6.221 6.233 (0.19)

2020 6.214 6.224 (0.16)

2022 6.211 6.220 (0.14)

While the above results provide insight into the entire UMRB’s response to the various

scenarios, results from the distinct subwatersheds were also analyzed to assess spatial

variability across the study area. Along with the HUC4 values shown in the Appendix, unit land

load values were also compared at the model’s subwatershed (HUC8) level. In discussing the

spatial variability, a specific scenario (2022 Control Volume Case) and year (2010) that

exhibited significant overall change from bas eline loads was examined. Changes in nitrogen

loads ranged from -2% to 9.4%, with 110 (of the 131) subwatersheds showing an increase; 94

of which were less than 5%. Changes in phosphorous loads ranged from -3.2% to 17.7%, with

101 subwatersheds showing an increase; 78 of which were less than 5%. Changes in sediment

loads ranged from -4.3% to 8.3% with 72 subwatersheds showing an increase; 68 of which were

less than 3%.

A Q U A T E R R A C o n s u l t a n t s 

# 11

# Given the complexity of the SWAT model, there are likely numerous factors that contributed to

these variations. The most significant of thes e factors was likely the impact of tile drained

agricultural areas. The current version of the SWAT model does not keep track of phosphorous

entering tile drains (revisions are being made to account for this in the next version). Thus,

adding agricultural area in subwatersheds containi ng tile drainage resulted in less phosphorous

load to the reaches. Though this model limitation is not documented for nitrogen, tile drainage

also appears to lead to decreasing nitrogen loads. This is clearly noted in Appendices A.10 and

A.11, where the 0702 HUC4 (a heavily tile drained area) loading rates for nitrogen and

phosphorous decrease from baseline to year 2010 model runs while all other HUC4 loading

rates increase. Another factor likely contributing to decreasing loads was the significant amount

of low slope area. With SWAT modeling corn as a relatively well-managed crop, it is reasonable

to assume that increasing the amount of low-slope corn area would lead to minimal or even

negative load changes, particularly for sediment. This would help explain the significant number

of subwatersheds that showed decreasing sediment loads. Additionally, this would explain the

greater number of subwatersheds showing phosphorous decreases than nitrogen, due to

phosphorous being a sediment-associated constituent. Further analysis of the results may

provide insight into other factors (e.g. soil types , land use conversions to create more corn) that

may be contributing to the spatial variation of load changes.

2.4 SUMMARY ANALYSES OF CURRENT MODEL RESULTS

In summary, model runs have been made for the baseline and future target years (2010, 2015,

2020, and 2022) on the Upper Mississippi River Basin (UMRB) for three scenarios and have

produced the following assessments:

• Target ethanol production values were reached for all scenarios (see Table 1.1). These

values were developed from the national pr oduction goals of the three scenarios, using

the fraction of nationwide ethanol production capacity of 42.3% found in the UMRB study

area.

• The current national average for corn yield, 150 bu/ac, was used to establish baseline

yield levels. The area-weighted baseline average yield for the UMRB was established at

144.3bu/ac. This was considered acceptable due to the significant amount of crop area

in Northern states where yield values are lower than the national average.

• Increases in corn yield were built into the future scenarios to account for assumed

advances in crop science. An annual increase of 1.23% was incorporated into future

scenarios, producing the following target yield averages:

o 2010 – 149.6 bu/ac

o 2015 – 159.0 bu/ac

o 2020 – 169.0 bu/ac

o 2022 – 173.2 bu/ac

• Average annual outflow of total nitrogen from the study area increased from the baseline

conditions for scenarios where corn area increases were needed to meet future ethanol

goals (AEO 2007, 2022 Control Case Volume). These scenarios showed increases

(2.72% for AEO 2007; 3.2% for 2022 Control Case Volume) for the early years (2010,

2015), but then showed decreasing loads for the later years (2020, 2022). A detailed

analysis of the scenario results included a review of nitrogen application rates and plant

uptake values for all scenarios. This showed that the decreasing of nitrogen loads can

be attributed to the increased yield production of future scenarios, resulting in greater

A Q U A T E R R A C o n s u l t a n t s 

# 12

# plant uptake of nitrogen. Additionally, less corn area was needed for the 2020 and 2022

scenarios due to the increased yield values. These factors contributed to the decreasing

total nitrogen loads for the RFS1 scenario, where decreasing corn areas were modeled.

• Average annual outflow of total phosphorous exhibited patterns similar to the nitrogen

loads. The AEO 2007 scenario projected an increase of 3.09% in 2010 while the 2022

Control Case Volume scenario projected an increase of 2.35% in 2010. Model runs

beyond 2010 then showed decreasing total phosphorous outflow from the 2010 level.

Analysis of the scenario results showed that, as with nitrogen, increased yield production

in future scenarios resulted in greater plant uptake of phosphorous. Additionally, less

corn area was needed for the 2020 and 2022 scenarios due to the increased yield

values. As with nitrogen, the RFS1 scenario also projected lower phosphorous loads.

• Total sediment outflow showed very little change (less than 1%) over all scenarios. This

is primarily due to the corn being modeled as well-managed crop in terms of sediment

loss, resulting in the corn stover remaining on the fields as protective cover following

harvest.

• Spatial variability of load changes was noted throughout the UMRB, with some

subwatersheds experiencing decreases while the UMRB experienced increases. The

complexity of the SWAT model means there are likely many factors that contributed to

this. However, the impact of low-slope and/or tile-drained areas were noted as the most

likely factors.

A Q U A T E R R A C o n s u l t a n t s 

# 13

# SECTION 3.0

REFERENCES

Renewable Fuels Association: Biorefinery Locations (2008). Accessed April, 2008, from

Renewable Fuels Association web site: http://www.ethanolrfa.org/industry/locations/

USDA, 2008. USDA Projections to 2017

. OCE-2008-1. U.S. Department of Agriculture, Office

of the Chief Economist, World Agricultural Outlook Board. Available at:

http://www.ers.usda.gov/Publications/OCE081/

U.S. Department of Agriculture, 2009. USDA Agricultural Projections to 2018, February 2009,

OCE-2009-1, available on-line at: http://www.ers.usda.gov/Publications/OCE091/

US EPA, 2008. Modeling Water Quality Impacts of Corn Production for Ethanol in the Upper

Mississippi River Basin. U.S. Environmental Protection Agency, Office of Water,

Washington, DC.

A Q U A T E R R A C o n s u l t a n t s 

# 14

# A Q U A T E R R A C o n s u l t a n t s 

# 15 

# APPENDICES

A. Detailed Modeling Results ......................................................................................... A-1

A.1 HUC4 summary of corn yields for 2007 AEO scenario ..................................... A-1

A.2 HUC4 summary of total nitrogen loads for 2007 AEO scenario ........................ A-2

A.3 HUC4 summary of total phosphorous loads for 2007 AEO scenario ................ A-3

A.4 HUC4 summary of sediment loads for 2007 AEO scenario .............................. A-4

A.5 HUC4 summary of corn yields for scenarios for RFS1 scenario ....................... A-5

A.6 HUC4 summary of total nitrogen loads for RFS1 scenario ............................... A-6

A.7 HUC4 summary of total phosphorous loads for RFS1 scenario........................ A-7

A.8 HUC4 summary of sediment loads for RFS1 scenario...................................... A-8

A.9 HUC4 summary of corn yields for 2022 Control Case Volume Scenario .......... A-9

A.10 HUC4 summary of total nitrogen loads for 2022 Control Case Volume

Scenario ............................................................................................................ A-10

A.11 HUC4 summary of total phosphorous loads for 2022 Control Case Volume

Scenario ............................................................................................................ A-11

A.12 HUC4 summary of sediment loads for 2022 Control Case Volume Scenario ... A-12APPENDIX ADETAILED MODELING RESULTSTable A.1. HUC4 summary of corn yields for AEO 2007 scenarioBaseline Scenario2010 Scenario2015 Scenario2020 Scenario2022 ScenarioHUC4CornArea,millionacYield,1bu/acBushEls,millionsCornArea,MillionacYield,bu/acBushEls,millionsCornArea,millionacYield,bu/acBushEls,millionsCornArea,millionacYield,bu/acBushEls,millionsCornArea,millionacYield,bu/acBushEls,millions07010.88130.51150.990.99141.01390.99149.81480.99153.815307023.50141.94973.543.54153.55443.54163.15783.54167.559407030.10121.9120.190.19133.7250.19142.2270.19146.12807040.86138.01190.980.97149.01450.97158.51540.98162.816007050.15130.2190.250.25143.2360.25152.4390.26156.64107061.02138.71421.221.22150.71831.22160.41951.23164.920207070.27132.2360.410.40145.1590.41154.4630.41158.76507085.14142.67325.765.75155.88965.76165.79545.79170.398607091.77137.72432.002.00150.23002.00159.73202.01164.233107103.16150.04743.533.52164.05783.53174.46153.55179.363607110.93151.41401.081.08167.21811.08177.81921.09182.819907121.15138.31591.311.31151.81981.31161.52111.32166.121907133.70150.95584.224.21167.27044.21177.97494.24183.077507141.02162.71661.351.34182.62451.34194.32611.36199.9272Sum/Avg23.65144.3341326.8326.78158.1423426.80168.2450726.96172.84659Total Ethanol Production, in BGY233% of baseline corn:3.04Baseline corn:1.15Baseline corn:3.33Baseline corn:3.54Baseline corn:3.64New corn:3.95New corn:1.34New corn:1.44New corn:1.55Total:5.10Total:4.67Total:4.98Total:5.191Yield values adjusted for moisture content2Ethanol production values based on conversion rate of 2.7 gallons of ethanol/bushelAQUATERRAConsultants16Table A.2. HUC4 summary of total nitrogen loads for AEO 2007 scenarioBaseline Scenario2010 Scenario2015 Scenario2020 Scenario2022 ScenarioHUC4Area,million acRate,lbs/acTotal,million lbsRate,lbs/acTotal,million lbsRate,lbs/acTotal,million lbsRate,lbs/acTotal,million lbsRate,lbs/acTotal,million lbs070112.907.5797.687.6698.887.6098.107.5697.607.5597.41070210.8010.76116.3010.77116.4010.57114.1510.42112.6310.36111.9707034.957.0935.097.3336.287.2936.077.2635.947.2635.9307046.8811.9982.5112.1783.7712.0282.6911.9181.9511.8781.6607056.119.5158.099.7259.369.6759.059.6358.859.6258.8007065.4917.0393.4717.3695.2917.0393.5116.8192.2816.7291.7807077.6312.2293.2712.4695.0812.3694.3412.2993.8312.2693.62070814.6723.41343.5824.33357.0723.76348.6823.36342.8623.20340.5007097.0021.89153.3922.58158.1922.18155.3721.90153.4321.79152.6407109.2617.89165.8018.45171.0118.05167.2417.76164.6217.65163.5307116.4417.82114.9018.36118.3418.05116.3917.87115.1917.79114.6507126.9818.72130.6319.29134.6618.99132.5818.80131.2518.73130.73071311.4519.88227.7520.87239.1820.25232.0519.84227.3019.67225.37071410.9116.21176.9716.87184.1616.58180.9916.40178.9816.32178.11AQUATERRAConsultants17Table A.3. HUC4 summary of total phosphorous loads for AEO 2007 scenarioBaseline Scenario2010 Scenario2015 Scenario2020 Scenario2022 ScenarioHUC4Area,million acRate,lbs/acTotal,million lbsRate,lbs/acTotal,million lbsRate,lbs/acTotal,million lbsRate,lbs/acTotal,million lbsRate,lbs/acTotal,million lbs070112.900.617.90.638.10.638.10.638.10.638.1070210.801.1712.71.1812.71.1612.51.1512.41.1412.407034.950.572.80.602.90.592.90.592.90.592.907046.881.037.11.057.21.047.11.037.11.037.107056.111.086.61.106.71.106.71.106.71.106.707065.491.387.61.407.71.397.61.387.61.387.607077.631.128.61.138.71.138.61.138.61.138.6070814.672.0630.22.0830.52.0530.12.0429.92.0329.807097.001.8312.81.8512.91.8312.81.8212.71.8112.707109.261.5914.71.6114.91.5914.81.5814.71.5814.607116.442.0113.02.1013.52.0713.32.0513.22.0413.207126.981.5010.51.5510.81.5310.71.5310.71.5310.6071311.452.0923.92.1624.72.1324.32.1024.12.0924.0071410.911.6317.71.7118.61.6918.41.6818.31.6718.3AQUATERRAConsultants18Table A.4. HUC4 summary of sediment loads for AEO 2007 scenarioBaseline Scenario2010 Scenario2015 Scenario2020 Scenario2022 ScenarioHUC4Area,million acRate,tons/acTotal,milliontonsRate,tons/acTotal,milliontonsRate,tons/acTotal,milliontonsRate,tons/acTotal,milliontonsRate,tons/acTotal,milliontons070112.901.5620.181.5720.331.5720.351.6020.691.5820.38070210.800.566.110.566.100.566.120.566.100.576.1407034.952.1210.522.1410.602.1410.602.1710.742.1410.6107046.883.4523.793.4523.823.4623.843.4623.873.4623.8507056.113.9424.153.9524.193.9524.193.9624.263.9524.2007065.496.0333.176.0333.196.0433.216.0333.186.0433.2407077.638.2863.348.2863.328.2863.328.2863.328.2863.33070814.672.0429.982.0229.642.0329.791.9528.642.0429.9407097.002.3316.392.3216.262.3216.322.2515.812.3316.3807109.262.6424.522.6324.462.6424.512.6124.232.6424.5607116.447.0745.657.1246.007.1346.057.2246.657.1446.1407126.981.5510.881.5610.881.5610.931.5110.571.5710.99071311.453.3138.013.3137.993.3238.093.1936.633.3338.20071410.917.4881.797.5082.087.5182.147.4981.887.5182.20AQUATERRAConsultants19Table A.5. HUC4 summary of corn yields for RFS1 scenario1Yield values adjusted for moisture contentBaseline Scenario2010 Scenario2015 Scenario2020 Scenario2022 ScenarioHUC4CornArea,millionacYield,1bu/acBushEls,millionsCornArea,MillionacYield,bu/acBushEls,millionsCornArea,millionacYield,bu/acBushEls,millionsCornArea,millionacYield,bu/acBushEls,millionsCornArea,millionacYield,bu/acBushEls,millions07010.88130.51150.88135.41190.88143.41260.88152.81350.88156.913807023.50141.94973.50147.15153.50155.95463.50166.15823.50170.459707030.10121.9120.10126.3130.10133.6130.09142.2130.09145.81407040.86138.01190.86143.21240.85152.11290.84162.31370.84166.714007050.15130.2190.15135.1200.13141.9180.12150.5180.12154.11807061.02138.71421.02143.81470.94153.01440.90163.41470.88167.914807070.27132.2360.27137.2370.24143.7350.23152.0350.22155.63507085.14142.67325.14147.97594.86156.77624.73167.17904.68171.580207091.77137.72431.77142.92521.65151.32501.59161.32571.57165.526007103.16150.04743.16155.74913.01164.94972.94175.75172.92180.352607110.93151.41400.93157.11460.92166.31530.91177.21620.91181.916607121.15138.31591.15143.51651.11152.11681.09162.11761.08166.417907133.70150.95583.70156.65793.59165.65943.53176.36223.51180.963507141.02162.71661.02168.71731.00178.51780.99190.11880.98195.0192Sum/Avg23.65144.3341323.65149.7354122.78158.6361322.35169.0377822.20173.53851Total Ethanol Production, in BGY233% of baseline corn:3.04Baseline corn:3.16Baseline corn:3.34Baseline corn:3.56Baseline corn:3.65New corn:0.00New corn:-0.37New corn:-0.59New corn:-0.68Total:3.16Total:2.97Total:2.97Total:2.982Ethanol production values based on conversion rate of 2.7 gallons of ethanol/bushelAQUATERRAConsultants20Table A.6. HUC4 summary of total nitrogen loads for RFS1 scenarioBaseline Scenario2010 Scenario2015 Scenario2020 Scenario2022 ScenarioHUC4Area,million acRate,lbs/acTotal,million lbsRate,lbs/acTotal,million lbsRate,lbs/acTotal,million lbsRate,lbs/acTotal,million lbsRate,lbs/acTotal,million lbs070112.907.5797.687.5597.47.5297.07.4896.67.4796.4070210.8010.76116.3010.69115.410.56114.010.41112.510.35111.907034.957.0935.097.0835.07.0634.97.0434.87.0334.807046.8811.9982.5111.9482.211.8181.311.7080.511.6580.207056.119.5158.099.5058.09.4257.69.3857.39.3657.207065.4917.0393.4716.9292.916.3889.915.9487.515.7886.607077.6312.2293.2712.2093.112.0592.011.9691.311.9391.1070814.6723.41343.5823.22340.722.43329.221.83320.321.59316.807097.0021.89153.3921.76152.421.03147.320.52143.720.32142.407109.2617.89165.8017.76164.617.31160.416.96157.116.82155.807116.4417.82114.9017.74114.317.56113.217.39112.117.32111.707126.9818.72130.6318.63130.018.29127.618.04125.917.95125.3071311.4519.88227.7519.70225.719.09218.718.63213.418.44211.3071410.9116.21176.9716.15176.215.99174.515.85173.015.79172.4AQUATERRAConsultants21Table A.7. HUC4 summary of total phosphorous loads for RFS1 scenarioBaseline Scenario2010 Scenario2015 Scenario2020 Scenario2022 ScenarioHUC4Area,million acRate,lbs/acTotal,million lbsRate,lbs/acTotal,million lbsRate,lbs/acTotal,million lbsRate,lbs/acTotal,million lbsRate,lbs/acTotal,million lbs070112.900.617.90.617.90.617.90.617.90.617.9070210.801.1712.71.1712.61.1612.51.1512.41.1412.307034.950.572.80.572.80.572.80.562.80.562.807046.881.037.11.037.11.037.11.027.01.027.007056.111.086.61.086.61.086.61.086.61.086.607065.491.387.61.377.51.367.51.357.41.347.307077.631.128.61.128.61.128.51.128.51.128.5070814.672.0630.22.0530.12.0229.72.0029.31.9829.107097.001.8312.81.8212.81.7912.61.7712.41.7612.307109.261.5914.71.5814.71.5714.51.5514.31.5414.307116.442.0113.02.0012.91.9812.81.9612.71.9612.607126.981.5010.51.5010.51.4810.31.4610.21.4610.2071311.452.0923.92.0823.82.0323.21.9922.81.9822.6071410.911.6317.71.6217.71.6117.51.5917.41.5917.3AQUATERRAConsultants22Table A.8. HUC4 summary of sediment loads for RFS1 scenarioBaseline Scenario2010 Scenario2015 Scenario2020 Scenario2022 ScenarioHUC4Area,million acRate,tons/acTotal,milliontonsRate,tons/acTotal,milliontonsRate,tons/acTotal,milliontonsRate,tons/acTotal,milliontonsRate,tons/acTotal,milliontons070112.901.5620.181.5620.191.5620.201.5620.211.5620.21070210.800.566.110.566.120.576.130.576.150.576.1607034.952.1210.522.1210.522.1210.522.1210.522.1210.5207046.883.4523.793.4523.803.4523.813.4523.823.4523.8307056.113.9424.153.9424.153.9424.153.9524.163.9524.1607065.496.0333.176.0333.186.0433.226.0433.236.0433.2307077.638.2863.348.2863.348.2863.368.2863.388.2863.38070814.672.0429.982.0430.032.0530.152.0630.252.0630.2907097.002.3316.392.3416.412.3516.472.3516.502.3516.5207109.262.6424.522.6424.532.6524.592.6524.632.6524.6507116.447.0745.657.0745.677.0845.727.0845.777.0945.8007126.981.5510.881.5610.891.5610.891.5610.911.5610.92071311.453.3138.013.3138.053.3137.963.3037.953.3137.96071410.917.4881.797.4881.817.4881.827.4881.847.4881.86AQUATERRAConsultants23Table A.9. HUC4 summary of corn yields for 2022 Control Case scenario1Yield values adjusted for moisture contentBaseline Scenario2010 Scenario2015 Scenario2020 Scenario2022 ScenarioHUC4CornArea,millionacYield,1bu/acBushEls,millionsCornArea,MillionacYield,bu/acBushEls,millionsCornArea,millionacYield,bu/acBushEls,millionsCornArea,millionacYield,bu/acBushEls,millionsCornArea,millionacYield,bu/acBushEls,millions07010.88130.51151.01132.91351.11140.11551.09149.01620.99153.016407023.50141.94973.55144.85143.59152.95493.58162.65823.54166.959707030.10121.9120.21126.3260.29133.9380.27142.4380.19146.23807040.86138.01191.00140.41411.10148.11631.08157.61700.98162.017307050.15130.2190.28135.3380.38143.7540.35152.8540.26156.95407061.02138.71421.27142.21801.44150.62171.40160.22241.23164.622707070.27132.2360.44137.0600.56145.7810.53154.9820.41159.08207085.14142.67325.92147.08706.47156.410116.33166.210535.79170.6107007091.77137.72432.06141.72922.27150.53422.22160.03562.01164.336107103.16150.04743.62154.85613.95164.66503.87175.06773.55179.668907110.93151.41401.12158.21771.26169.32131.23179.62201.09184.222307121.15138.31591.35143.41931.49153.02281.45162.62361.32166.924007133.70150.95584.34158.36884.80169.98154.69180.38454.24184.985707141.02162.71661.43173.22471.71186.33191.64197.73251.36202.7326Sum/Avg23.65144.3341327.61149.3412330.40159.1483629.73169.0502429.40173.55100Total Ethanol Production, in BGY233% of baseline corn:3.04Baseline corn:3.14Baseline corn:3.35Baseline corn:3.56Baseline corn:3.65New corn:1.60New corn:2.92New corn:2.79New corn:2.71Total:4.75Total:6.26Total:6.35Total:6.362Ethanol production values based on conversion rate of 2.7 gallons of ethanol/bushelAQUATERRAConsultants24Table A.10. HUC4 summary of total nitrogen loads for 2022 Control Case scenarioBaseline Scenario2010 Scenario2015 Scenario2020 Scenario2022 ScenarioHUC4Area,million acRate,lbs/acTotal,million lbsRate,lbs/acTotal,million lbsRate,lbs/acTotal,million lbsRate,lbs/acTotal,million lbsRate,lbs/acTotal,million lbs070112.907.5797.687.6698.87.6899.17.6298.47.6098.1070210.8010.76116.3010.69115.510.54113.910.40112.410.35111.807034.957.0935.097.3736.57.5037.17.4236.77.3936.607046.8811.9982.5112.1583.612.1583.612.0182.611.9482.207056.119.5158.099.7459.59.8460.19.7659.79.7359.507065.4917.0393.4717.2894.917.1294.016.8792.616.7792.007077.6312.2293.2712.4895.212.5996.112.4695.112.3994.6070814.6723.41343.5824.27356.224.37357.723.83349.823.58346.007097.0021.89153.3922.54157.922.54157.922.19155.522.02154.307109.2617.89165.8018.40170.618.44170.918.05167.317.88165.707116.4417.82114.9018.35118.318.41118.718.14116.918.00116.007126.9818.72130.6319.28134.619.31134.819.04132.918.92132.1071311.4519.88227.7520.80238.320.69237.120.14230.819.91228.1071410.9116.21176.9716.88184.216.91184.516.62181.416.48179.9AQUATERRAConsultants25Table A.11. HUC4 summary of total phosphorous loads for 2022 Control Case scenarioBaseline Scenario2010 Scenario2015 Scenario2020 Scenario2022 ScenarioHUC4Area,million acRate,lbs/acTotal,million lbsRate,lbs/acTotal,million lbsRate,lbs/acTotal,million lbsRate,lbs/acTotal,million lbsRate,lbs/acTotal,million lbs070112.900.617.90.638.20.648.30.648.20.648.2070210.801.1712.71.1712.61.1612.51.1512.41.1412.307034.950.572.80.603.00.623.10.613.00.613.007046.881.037.11.057.21.057.21.047.21.047.107056.111.086.61.106.71.116.81.116.81.116.807065.491.387.61.407.71.397.71.397.61.387.607077.631.128.61.148.71.148.71.148.71.148.7070814.672.0630.22.0730.32.0530.02.0329.92.0329.807097.001.8312.81.8412.91.8212.71.8112.71.8112.707109.261.5914.71.6114.91.6014.81.5914.71.5814.707116.442.0113.02.1113.62.1513.82.1113.62.0913.507126.981.5010.51.5510.81.5410.71.5310.71.5310.7071311.452.0923.92.1524.62.1224.22.1024.12.0924.0071410.911.6317.71.7218.71.7419.01.7218.71.7118.6AQUATERRAConsultants26Table A.12. HUC4 summary of sediment loads for 2022 Control Case scenarioBaseline Scenario2010 Scenario2015 Scenario2020 Scenario2022 ScenarioHUC4Area,million acRate,tons/acTotal,milliontonsRate,tons/acTotal,milliontonsRate,tons/acTotal,milliontonsRate,tons/acTotal,milliontonsRate,tons/acTotal,milliontons070112.901.5620.181.5820.381.5920.511.5820.501.5820.49070210.800.566.110.566.100.566.110.576.120.576.1407034.952.1210.522.1410.622.1510.682.1510.672.1510.6707046.883.4523.793.4623.833.4623.863.4623.873.4623.8707056.113.9424.153.9524.203.9624.233.9624.233.9624.2307065.496.0333.176.0333.206.0433.216.0433.236.0433.2507077.638.2863.348.2863.318.2763.318.2863.328.2863.32070814.672.0429.982.0129.601.9929.292.0129.512.0129.6207097.002.3316.392.3116.242.2916.102.3116.192.3116.2407109.262.6424.522.6324.462.6324.402.6324.462.6424.4907116.447.0745.657.1346.097.1746.357.1746.357.1746.3507126.981.5510.881.5610.881.5510.811.5610.881.5610.92071311.453.3138.013.3037.953.2737.603.2937.803.3037.89071410.917.4881.797.5182.137.5182.147.5182.207.5282.23AQUATERRAConsultants27