1

Appendix 3-F: Evaluation of Soil WQI Grouping Classes as a Potential 

Replacement for Individual Soil Map Units in SAM Scenarios

Because the potential number of individual soil map unit-crop group-weather station 

combinations would run in the tens of millions, OPP explored the feasibility of grouping soil 

map units into classes based on factors that have the greatest impact on pesticide loss due to 

runoff and erosion, similar to approaches used by the European Union (Schneider et al, 2007). A 

reduction in the number of scenarios that would need to be stored and processed would have 

an impact on the amount of storage space that would be required for SAM on a national scale 

and on the amount of computer processing time that would be needed for running nationalscale risk assessments on a routine basis for potentially hundreds of pesticide registration and 

registration review assessments each year. 

This appendix describes the soil grouping approach based on USDA’s Water Quality Index 

(Section 3-F.1), initial sensitivity analyses USEPA OPP conducted to determine the potential loss 

of information by using the WQI groupings (Section 3-F.2), and a comparison of model results 

using scenarios based in individual soil map units or the soil WQI groupings (Section 3-F.3 and 

the accompanying 3-F.A spreadsheet). 

The sensitivity analysis looked at the variance in outputs (estimated concentrations) within the 

bounds of the proposed WQI ranges separately, using USEPA OPP’s Surface Water 

Concentration Calculator (SWCC). Outputs used for comparisons – runoff, mass of pesticide 

lost, and pesticide concentrations – were generated using SAM.

3-F.1 Soil Group Classes

USEPA OPP evaluated grouping individual soil map units into classes based on a USDA NRCS 

Water Quality Index (WQI) for runoff from agricultural fields (Lal and McKinney, 2012). The WQI 

used the following grouping classes to derive a WQI for each soil:

Runoff potential based on Hydrologic Soil Group: A, B, C, D

Slope gradient: <2%, 2-5%, 5-10%, 10-15%, >15%

Soil erodibility potential based on K factor: <0.10, 0.11-0.20, 0.21-0.32, 0.33-0.43, 0.44-0.64

Soil Organic Matter (SOM) content (surface layer): <0.5%, 0.5-2%, 2-4%, 4-6%, 6-8%, >8%

The models use soil organic carbon (SOC) as an input. USEPA OPP converted SOM to SOC with 

the general equation SOC = SOM/1.724. 

The resulting SOC groups are: <0.29%, 0.29-1.16%, 1.16-2.32%, 2.32-3.48%, 3.48-4.64%, >4.64% 

These grouping class combinations result in a potential of 600 soil group classes:

4 HSG x 5 slope classes x 5 soil erodibility classes x 6 SOM classes
2

This grouping will result in the following impacts:

- The curve number for the resulting soil group scenarios will not change because the 

curve number and land cover classes remain unchanged.

- Variations in soil OC content (impact on pesticide transport/sorption, as well as 

erodibility potential, water retention properties in soil) are limited to 2% OM/1.16% OC 

increments. 

- Variations in slope as a result of the slope gradient classes may be limited because soil 

map units are split out in slope classes that are similar to the class breaks above; the 

biggest change will be for steeper slopes (>15%). However, agriculture is generally 

limited on such steeper slopes.

- Variations in sediment transport are limited by the range in K factor values (Kwfactor in 

SSURGO) for each class 

- Other soil-related inputs that may impact the estimated concentrations do not vary 

independently of each other or of the properties listed above. Full sensitivity analyses 

will need to take these correlations into account.

o Bulk density, field capacity, and wilting point affect the water capacity of the soil. 

These vary with SOM content, soil texture (percent of sand, silt, and clay), and 

soil structure (aggregation of soil particles, forming larger pores that serve as 

conduits for water). In general, lower bulk densities and subsequent higher 

water capacities are associated with higher SOM contents; higher bulk densities 

and resulting lower water capacities are associated with lower SOM contents. 

Sensitivity analyses for bulk density and water capacity parameters should be 

done within SOM classes, and needs to consider the correlation among the soil 

properties. 

o Soil erodibility (K factor) is also related to SOM content, soil texture, soil 

structure, and permeability (which is related to SOM content, texture, and 

structure). Sensitivity analyses for K factor classes should be done within SOM 

classes and, possibly, within Hydrologic Soil Groups.

o Slope gradient and slope length are used to derive the USLE LS (slope-length) 

factor used to estimate soil erosion and resultant sediment transport. Slope 

length is estimated for soil map units from the average slope length 

(SLOPELENUS in SSURGO) for the soil map unit. This average length and average 

slope for the map unit are used to estimate the USLELS factor used in the model. 

Sensitivity analyses for USLELS values should be done within slope classes.

3-F.2 Approaches to Evaluating Soil Groupings

USEPA OPP considered three approaches to evaluating the potential impacts of the aggregation 

methods on SAM. Section 3-F.3 covers the sensitivity analysis; section 3-F.4 covers the

comparison of model results. No work has been done on the PCA. 
3

(1) Sensitivity analysis to determine the major driving inputs in the model. This would 

determine which inputs have the greatest impact on estimated concentrations and at 

what range(s). It would also determine which parameters should be constrained in 

classes (such as those listed above) to reduce the variability in exposure estimates. 

a. Many model parameters are related to each other so we need to account for 

autocorrelations. We can’t vary values independently.

b. One option may be to use the actual combinations found in the scenarios to 

bracket the high and low ends of the input ranges.

c. Relative sensitivities to model inputs will likely vary with pesticide properties 

(low vs high Koc, low vs high half-life values). Recommend simulating pesticides 

using a combination of pesticide properties.

i. Koc: 100, 500, 1000, 10,000

ii. Aerobic soil/aquatic half-life, day: 7, 30, 90, 365

(2) Comparison of model results from scenarios developed using all of the SSURGO Map 

Units to those from scenarios using the soil groupings. These comparisons would 

particularly focus on changes in spatial and temporal patterns in:

a. Runoff flux by watershed, which would indicate potential impacts from the 

runoff routines 

b. Pesticide mass flux by runoff by watershed, which would indicate potential 

impacts from the pesticide fate/transport routines

c. Pesticide concentrations, which integrates the potential impacts 

(3) Principle component analysis (PCA) to identify the major factors affecting estimated 

concentrations. 

a. Ideally, we compare outputs to model inputs. However, with SAM, the model 

inputs are compiled scenario-by-scenario, while the outputs are compiled by 

watershed and reflect the area-weighting of individual scenarios as they occur in 

the watersheds.

b. To do a comparison for sensitivity analysis, we would need an intermediary 

output (for instance, edge-of-field flux values by scenarios). An alternate 

approach – looking at area-weighted input parameters at the watershed level –

would also require extra computation but would likely average out individual 

input differences.

3-F.3 Sensitivity Analysis

Preliminary scoping analyses used the IL corn scenario and test chemicals with a half-life of 30 

days and Koc values of 100, 500, 1000, and 10,000. Scenarios were modified using the Surface 

Water Concentration Calculator (SWCC) and run in batch mode for each test chemical. These

scoping exercises are intended to determine the extent to which we need to consider further 

sensitivity analyses. Outputs for the index reservoir were compared in this analysis. 
4

3-F.3.1 Soil Organic Matter Groupings

Soil organic matter (SOM) classes vary in 2% increments. For the revised soil grouping classes, 

input values are calculated as the average of all of the values within each soil grouping class. 

The preliminary analysis looked at outputs for SOM content at the break points and at the 

midpoint between breaks. For the model runs, SOM was converted to soil organic carbon (SOC) 

by the equation 

SOC = SOM/1.724

SOM 0.5 1 2 3 4 5 6 8 14

SOC 0.29 0.58 1.16 1.74 2.32 2.90 3.48 4.64 8.0

For each test chemical, changes in 1-in-10-year concentrations (peak, 4-, 21-, 60-, 90-, and 365-

day averages in water and peak and 21-day averages in benthic pore water), as well as total 

mass moving to the water body from runoff and erosion are compared between 1% increments 

in SOM content. Peak values for each year were compared; Figures 1-4 show the yearly 

variations in concentrations across SOM contents of 0.5 to 14%. 

The estimated concentrations (maximum yearly peaks as well as various time-averaged 

maximums) in water generally decreased with increasing SOM content. Differences in 

estimated concentrations in water between the lowest and highest simulated SOM content 

averaged 3-4X (with a maximum of 20X) for the test chemical with a Koc of 100. Contrasts were 

less pronounced as the Koc increased. Differences between the lowest and highest simulated 

SOM content averaged 2X (with a maximum of 4X) for the test chemical with a Koc of 500, and 

1.5X (with maximum less than 3X) for Koc values of 1,000 and 10,000 (Figures 1-4). 

The upper graph in Figures 1-4 show the range in estimated yearly peak concentrations (in 

ug/L) across 30 years for the 4 test chemicals. The largest ratios between the highest and 

lowest estimated peak concentrations occurred with the lowest estimated concentrations.

Most of the differences in estimated concentrations occurred in low SOM content soils. The 

differences between the high and low end of the range within each SOM class averaged less 

than 2X for the lowest Koc test chemical in the 0.5-2% SOM class, and were essentially the 

samd for SOM classes of 2-4% or greater. As the Koc increased, the differences in estimated 

yearly peaks decreased across all SOM classes (Figures 1-4).

The lower graph in Figures 1-4 plot the ratio between the estimated yearly peak concentration 

at the upper end of the SOM range in each class to the estimated peak at the lower end of the 

SOM range in that class. For the 0.5-2% SOM class, differences in estimated peak 

concentrations across that range varied by less than 6-fold (for the test chemical with a Koc of 

100) and averaged less than a factor of 2 greater. For the higher SOM classes (4-6% SOM and 

greater), little difference yearly peak concentrations was seen across the SOM range. As the 

test chemical Koc increased, differences across the SOM class ranges decreased.
5

The following trends are evident in a comparison of total pesticide mass lost by runoff and 

erosion (Figure 5):

- The total mass of pesticide lost in runoff decreased as the SOM increased for test 

chemicals with a Koc of 500 or greater. For the test chemical with a Koc of 100, the total 

mass lost by runoff increased as SOM increased from 0.5 to 6% and then declined at 

higher SOM contents. This different trend likely reflects the impact of sorption on 

competing leaching and runoff losses for low Koc chemicals.

- The total mass of pesticide lost in erosion/sediment increased as the SOM increased. 

The total mass of pesticide lost by erosion also increased as the Koc increased. These 

trends suggest that more pesticide mass is held onto soil particles as both Koc and SOM 

increase, with less mass lost to leaching and runoff. 

- The total combined mass of pesticide lost by runoff and erosion increased as the SOM 

and Koc increased. That increase is due to the increase in pesticide mass on sediment. 

This trend may in part reflect the greater retention of pesticide in the surface as 

sorption increases. However, because the erosion/sediment inputs were not changed in 

the scenarios as SOM increased, this simulation does not reflect the impact of increasing 

SOM on reducing the overall erodibility of the soil. 

Based on these results, USEPA OPP concluded:

- Varying the SOM content within the 2% increments in the SOM classes does not have an 

appreciable impact on estimated peak or time-averaged concentrations for SOM 

contents of 2% or greater. 

- For SOM contents less than 2%, the variability within the SOM class (0.5-2%) could be 

reduced by breaking them down into 0.5% increments (<0.5, 0.5-1.0, 1.0-1.5, 1.5-2%). 

This would result in 3 additional SOM classes if we choose to go this route.

- Further sensitivity analyses, particularly for soil erodibility parameters, need to account 

for the correlations between the various input parameters (particularly K factor and C 

factor) and SOM. One approach may be to run sensitivity analyses on inputs within the 

SOM groups. 
6

Figure 1 - (a) Estimated yearly peak concentrations over 30 years for a range of soil organic matter 

(SOM) content for IL corn scenario for a test chemical with Koc 100 and t1/2 30 days; (b) ratio in yearly 

peaks between the low and high end of SOM increments.
7

Figure 2- (a) Estimated yearly peak concentrations over 30 years for a range of soil organic matter 

(SOM) content for IL corn scenario for a test chemical with Koc 500 and t1/2 30 days; (b) ratio in yearly 

peaks between the low and high end of SOM increments.
8

Figure 3- (a) Estimated yearly peak concentrations over 30 years for a range of soil organic matter 

(SOM) content for IL corn scenario for a test chemical with Koc 1,000 and t1/2 30 days; (b) ratio in 

yearly peaks between the low and high end of SOM increments.
9

Figure 4- (a) Estimated yearly peak concentrations over 30 years for a range of soil organic matter 

(SOM) content for IL corn scenario for a test chemical with Koc 10,000 and t1/2 30 days; (b) ratio in 

yearly peaks between the low and high end of SOM increments.
10

Figure 5 - Cumulative Mass of Pesticide Lost by Runoff and Erosion from 30 Years of Simulations for 

Test Chemicals with a Half-life of 30 Days and Koc of (a) 100, (b) 500, (c) 1,000, and (d) 10,000.

3-F.3.2 Soil Bulk Density and Water Capacity Variability within Organic Matter Groupings

Bulk density, field capacity, and wilting point affect the water capacity of the soil. These vary 

with SOM content, soil texture (percent of sand, silt, and clay), and soil structure (aggregation 

of soil particles, forming larger pores that serve as conduits for water). In general, lower bulk 

densities and subsequent higher water capacities are associated with higher SOM contents; 

higher bulk densities and resulting lower water capacities are associated with lower SOM 

contents. For the preliminary analyses, we selected highest and lowest bulk density (BD) values 

in each SOM group class, and water holding properties, characterized by lowest and highest 

values for field capacity (FC) and accompanying wilting point (WP) that resulted in the lowest 

and highest water holding capacity, within each SOM classes. For this initial scoping analysis, we 

selected bulk density, field capacity, and wilting point values for low (0.5%), medium (3%), and 

high (6%) SOM soils (see Table 1 below). We used the test chemical with Koc of 500 and t1/2 of 

30 days.
11

Table 1 - Inputs for SOM, Bulk Density (BD), Field Capacity (FC), and Wilting Point (WP) for Surface and 

Subsurface Layers for Preliminary Analyses

Soil Scenario OM OC BD1 FC1 WP1 BD2 FC2 WP2

Low SOM, High Bulk Density, Low

Water Capacity

0.50 0.29 1.95 0.03 0.02 1.89 0.02 0.01

Low SOM, Low Bulk Density, High 

Water Capacity

0.50 0.29 1.15 0.43 0.23 1.15 0.35 0.18

Medium SOM, High Bulk Density, Low 

Water Capacity

3.00 1.74 1.80 0.02 0.01 1.90 0.02 0.01

Medium SOM, Low Bulk Density, High 

Water Capacity

3.00 1.74 1.10 0.38 0.11 1.10 0.39 0.15

High SOM, High Bulk Density, Low 

Water Capacity

6.00 3.48 1.60 0.05 0.04 1.58 0.02 0.01

High SOM, Low Bulk Density, High 

Water Capacity

6.00 3.48 1.00 0.38 0.19 1.00 0.32 0.20

While the evaluation focused on a limited scope (only 1 test chemical and 3 SOM contents), 

results of the comparisons suggest that differences in yearly estimated peak and time-averaged 

exposures for the three representative SOM soils indicate that differences resulting from 

variations in bulk density and water capacity input values are likely to have minimal effect on 

estimated concentrations (Figure 6).

Based on these results, USEPA OPP concluded:

- Model runs using the highest and lowest soil bulk density values and corresponding 

lowest and highest water capacity (represented by FC and WP) showed minimal impacts 

of these inputs on yearly maximum (peak) estimated concentrations for soils with 

varying SOM content.

- No additional adjustments are needed for soil grouping classes to account for variability 

in bulk density, field capacity, or wilting point within the SOM groups.
12

Figure 6 - Comparisons Of Estimated Yearly Concentrations Over 30 Years For Varying Bulk Density 

And Water Capacity Inputs For Soils With A SOM Content Of 0.5% (Top), 3% (Middle), And 6% 

(Bottom).
13

3-F.3.3 Soil Erodibility (K Factor) Groupings

The K factor is an indicator of the inherent erodibility of the soil. While the alpha test version of 

SAM is not accounting for pesticide transport on eroded sediment, this factor will be important 

once that routine is included. Although it is a unitless fraction, the K factor actually consists of 

11 distinct classes (0.02, 0.05, 0.10, 0.17, 0.24, 0.28, 0.32, 0.43, 0.49, 0.55, 0.64). The K factor is 

derived from SOM content, soil texture (particularly, percent of sand and silt), soil structure, 

and permeability (which is related to SOM content, texture, and structure). While sensitivity 

analyses for K factor classes should be done within SOM classes and, possibly, Hydrologic Soil 

Groups, this preliminary analysis compared estimated concentrations for each K factor value 

using the IL Corn standard scenario.

Comparisons using two text chemicals – one with a Koc of 500 and the other with a Koc of 

10,000 – looked at yearly peak concentrations in water and benthic compartments (Figures 7 

and 8 show peak water concentrations; Figures 9 and 10 show peak benthic concentrations). 

The comparisons looked at changes in estimated peak concentrations as the K factor value 

changed and differences in concentrations at the high and low end of the K factor class breaks.

Estimated yearly peak concentrations in water and in benthic (pore water) increased as the K 

factor value increased, largely due to increases in pesticide mass carried in erosion/sediment 

loss from the field to the water body.

For the test chemical with a Koc of 500 (considered to be mobile, with transport primarily 

dissolved in runoff water), the estimated concentrations in water increased by roughly 4-7% 

between the low and high end of the K factor breaks. Estimated concentrations in benthic 

sediment (pore water) increased by roughly 10-25% within the K factor breaks. 

For the less mobile test chemical with a Koc of 10,000, estimated peak concentrations were 

lower. Differences in estimated concentrations between the low and high end of the K factor 

breaks were greater for the high Koc (10,000) test chemical than for the low Koc (500) chemical. 

However, the estimated concentrations were within a factor of 3 of each other for the lowest Kfactor class (<0.10) and within a factor of 1.5 for the remaining K-factor classes.
14

Figure 7 - (a) Estimated yearly peak water concentrations over 30 years for a range of K factor values

for IL corn scenario for a test chemical with Koc 500 and t1/2 30 days; (b) ratio in yearly peaks 

between the high and low end of K factor increments.
15

Figure 8 - (a) Estimated yearly peak water concentrations over 30 years for a range of K factor values 

for IL corn scenario for a test chemical with Koc 10,000 and t1/2 30 days; (b) ratio in yearly peaks 

between the high and low end of K factor increments.
16

Figure 9 - (a) Estimated yearly peak benthic concentrations over 30 years for a range of K factor values 

for IL corn scenario for a test chemical with Koc 500 and t1/2 30 days; (b) ratio in yearly peaks 

between the high and low end of K factor increments.
17

Figure 10 - (a) Estimated yearly peak benthic concentrations over 30 years for a range of K factor 

values for IL corn scenario for a test chemical with Koc 10,000 and t1/2 30 days; (b) ratio in yearly 

peaks between the high and low end of K factor increments.
18

3-F.3 Comparison of Outputs Using Individual Soil Map Units and Soils Grouped by 

WQI Classes

USEPA OPP generated scenarios based on individual soil map units (individual MU scenarios) 

and on the resulting aggregation of soils into the water quality criteria (aggregated soil 

scenarios) for the test basins used for this evaluation (see Appendix 2.B). Test evaluations 

covered 15 years of weather data (2000-2014).

Table 2 lists the test basins used for this analysis. 

Table 2: Test basin monitoring sites used for evaluating results based on individual soil map unit 

scenarios or aggregated soil group scenarios.

Monitoring 

Site

NHD+ 

Catchment 

ID

Monitoring 

Site

NHD+ 

Catchment 

ID

Monitoring 

Site

NHD+ 

Catchment 

ID

MO-01 4989415 OH-04 3483775 IN-10 eco 18459870

MO-04a 4989385 OH-10 river 5214753 IN-04 river 18454511

MO-04b 4989739 OH-11 

reservoir

5213585 IN-06 river 18450057

MO-02 5042380 IN-08 river 18445664

MO-05 5042400 IN-13 river 18451035

MO-05b 5039952

MO-08 2508563

Detailed distributions and comparisons can be found in Appendices 3-F(1), 3-F(2), and 3-F(3). 

3-F.3.1 Comparisons

USEPA OPP generated scenarios based on individual soil map units (individual MU scenarios) 

and on the resulting aggregation of soils into the water quality criteria (aggregated soil 

scenarios) for the test basins used for this evaluation. Test evaluations covered 15 years of 

weather data (2000-2014).

OPP EFED examined the annual total runoff volume, mass runoff loss, and maximum annual 

concentrations over the 15 years of simulations in each test basin (Tables 3, 4, and 5). 

For all seven test basins in MO, the total annual runoff was within <1% and the total annual 

pesticide mass lost was within <2%. Estimated annual maximum concentrations were within 5% 

of each other in 4 of the 7 basins and within 10% in 6 of the 7 test basins (Table 3). The MO-02 

site showed the greatest difference in estimated maximum concentrations, with estimates 
19

generated using scenarios based on aggregated soil groupings more than 10% greater than 

estimates from individual map units in 3 of 15 model years. 

Table 3: Comparison of Annual Total Runoff, Total Mass Loss, and Maximum Concentrations for 

Scenarios based on Individual Soil Map Units vs Scenarios based on Soils Grouped by WQI Categories 

for MO Test Basins.

Site Year

Runoff (m) Mass Runoff Loss (kg) Max. Annual Conc (ug/L)

Indiv. MU 

Scenarios

Aggreg 

Scenarios

Pct 

Diff

Indiv. MU 

Scenarios

Aggreg 

Scenarios

Pct 

Diff

Indiv. MU 

Scenarios

Aggreg 

Scenarios

Pct 

Diff

MO-01

4989415

2000 2.46E+06 2.44E+06 0.5% 63.4 63.3 0.1% 106.0 104.0 1.9%

2001 7.28E+06 7.24E+06 0.5% 127.8 127.4 0.3% 82.8 82.7 0.1%

2002 4.56E+06 4.54E+06 0.3% 65.6 65.9 -0.4% 75.7 76.8 -1.5%

2003 6.97E+06 6.94E+06 0.4% 71.6 70.5 1.6% 115.0 118.0 -2.6%

2004 5.31E+06 5.29E+06 0.3% 66.4 66.2 0.3% 100.0 101.0 -1.0%

2005 2.77E+06 2.77E+06 0.0% 77.1 77.2 -0.2% 151.0 155.0 -2.6%

2006 3.40E+06 3.39E+06 0.2% 54.2 54.4 -0.3% 86.1 86.4 -0.3%

2007 3.75E+06 3.74E+06 0.2% 45.0 44.9 0.4% 102.0 103.0 -1.0%

2008 1.11E+07 1.11E+07 0.3% 156.1 155.0 0.7% 82.3 83.3 -1.2%

2009 8.45E+06 8.44E+06 0.1% 89.2 89.3 -0.1% 93.1 93.9 -0.9%

2010 9.76E+06 9.74E+06 0.3% 75.2 74.6 0.9% 45.0 45.4 -0.9%

2011 5.56E+06 5.55E+06 0.3% 97.5 97.3 0.2% 72.0 72.8 -1.1%

2012 3.77E+06 3.77E+06 0.1% 62.3 61.4 1.5% 180.0 180.0 0.0%

2013 7.26E+06 7.24E+06 0.3% 94.6 94.4 0.2% 99.3 101.0 -1.7%

2014 7.40E+06 7.34E+06 0.8% 78.5 78.0 0.6% 47.2 47.7 -1.1%

MO-04a

4989385

2000 1.66E+06 1.67E+06 -0.1% 38.9 39.0 -0.2% 95.4 93.8 1.7%

2001 4.91E+06 4.93E+06 -0.3% 75.3 75.2 0.0% 75.3 68.2 9.4%

2002 2.80E+06 2.81E+06 -0.3% 27.6 27.6 0.1% 66.3 71.8 -8.3%

2003 4.75E+06 4.76E+06 -0.1% 71.8 70.4 2.0% 145.0 146.0 -0.7%

2004 3.96E+06 3.98E+06 -0.4% 44.1 44.0 0.1% 96.0 98.5 -2.6%

2005 1.94E+06 1.94E+06 -0.2% 48.3 48.3 -0.1% 97.0 94.4 2.7%

2006 2.61E+06 2.62E+06 -0.5% 29.2 29.2 0.1% 48.6 50.1 -3.1%

2007 2.28E+06 2.29E+06 -0.4% 34.7 34.4 0.7% 157.0 159.0 -1.3%

2008 7.75E+06 7.80E+06 -0.6% 100.9 100.4 0.4% 70.1 70.6 -0.7%

2009 6.03E+06 6.08E+06 -0.8% 56.5 56.7 -0.4% 73.3 73.9 -0.8%

2010 6.65E+06 6.69E+06 -0.6% 33.6 33.6 -0.1% 29.3 29.1 0.7%

2011 3.90E+06 3.93E+06 -0.6% 102.9 103.4 -0.5% 84.0 85.9 -2.3%

2012 2.57E+06 2.55E+06 0.7% 39.9 39.1 2.0% 134.0 137.0 -2.2%

2013 5.20E+06 5.23E+06 -0.6% 55.2 55.6 -0.7% 83.5 82.7 1.0%

2014 5.00E+06 4.97E+06 0.6% 33.8 33.7 0.5% 28.3 28.1 0.7%

MO-04b

4989739

2000 6.03E+07 5.97E+07 1.0% 931.1 929.5 0.2% 46.5 46.2 0.6%

2001 1.98E+08 1.96E+08 1.0% 1613.1 1604.9 0.5% 25.4 25.7 -1.2%

2002 1.40E+08 1.39E+08 0.6% 966.1 967.9 -0.2% 45.3 45.3 0.0%

2003 1.72E+08 1.70E+08 0.7% 907.1 894.4 1.4% 49.9 50.3 -0.8%
20

Site Year

Runoff (m) Mass Runoff Loss (kg) Max. Annual Conc (ug/L)

Indiv. MU 

Scenarios

Aggreg 

Scenarios

Pct 

Diff

Indiv. MU 

Scenarios

Aggreg 

Scenarios

Pct 

Diff

Indiv. MU 

Scenarios

Aggreg 

Scenarios

Pct 

Diff

2004 1.40E+08 1.39E+08 0.6% 845.2 841.7 0.4% 44.3 45.1 -1.8%

2005 7.93E+07 7.88E+07 0.7% 1031.4 1027.3 0.4% 47.2 47.7 -1.1%

2006 8.20E+07 8.14E+07 0.7% 720.7 716.7 0.6% 39.7 39.4 0.8%

2007 1.34E+08 1.33E+08 0.7% 698.1 696.5 0.2% 37.7 38.0 -0.8%

2008 3.56E+08 3.53E+08 0.7% 1952.6 1938.0 0.7% 32.2 32.8 -1.9%

2009 2.41E+08 2.40E+08 0.4% 1184.9 1186.0 -0.1% 35.9 36.1 -0.6%

2010 2.97E+08 2.94E+08 0.8% 1100.8 1097.6 0.3% 22.0 22.4 -1.8%

2011 1.41E+08 1.40E+08 0.9% 1181.7 1181.4 0.0% 27.0 27.2 -0.7%

2012 9.96E+07 9.93E+07 0.3% 862.1 852.8 1.1% 96.8 95.6 1.2%

2013 2.04E+08 2.03E+08 0.7% 1269.9 1270.4 0.0% 36.8 39.0 -6.0%

2014 2.54E+08 2.52E+08 1.0% 1059.2 1052.1 0.7% 21.7 21.8 -0.5%

MO-02

5042358

2000 1.30E+07 1.30E+07 0.3% 164.4 167.0 -1.6% 112.0 113.0 -0.9%

2001 1.46E+07 1.46E+07 0.1% 128.1 126.9 0.9% 64.1 94.3 -47%

2002 1.34E+07 1.35E+07 -0.4% 194.5 186.1 4.3% 118.0 120.0 -1.7%

2003 1.42E+07 1.42E+07 -0.3% 106.9 107.3 -0.4% 129.0 127.0 1.6%

2004 1.87E+07 1.87E+07 -0.2% 89.6 89.9 -0.4% 81.6 84.2 -3.2%

2005 9.27E+06 9.29E+06 -0.2% 118.7 117.1 1.4% 66.7 65.9 1.2%

2006 1.35E+07 1.35E+07 0.3% 256.6 251.4 2.0% 141.0 144.0 -2.1%

2007 7.48E+06 7.48E+06 0.0% 113.6 116.9 -2.9% 110.0 108.0 1.8%

2008 3.36E+07 3.37E+07 -0.4% 130.4 136.4 -4.7% 62.7 69.4 -11%

2009 2.07E+07 2.08E+07 -0.2% 128.0 122.1 4.6% 65.9 65.9 0.0%

2010 2.40E+07 2.40E+07 0.0% 154.5 153.4 0.7% 68.2 72.0 -5.6%

2011 9.86E+06 9.89E+06 -0.4% 113.4 116.0 -2.3% 78.3 78.3 0.0%

2012 1.17E+07 1.17E+07 -0.1% 164.0 160.9 1.9% 177.0 182.0 -2.8%

2013 1.45E+07 1.46E+07 -0.4% 110.5 109.1 1.2% 64.0 75.7 -18%

2014 1.56E+07 1.56E+07 0.3% 73.7 70.8 3.9% 69.8 68.5 1.9%

MO-05

5042400

2000 1.38E+07 1.37E+07 0.2% 242.6 239.4 1.3% 87.8 87.1 0.8%

2001 1.54E+07 1.54E+07 0.1% 210.1 208.0 1.0% 60.8 60.8 0.0%

2002 1.39E+07 1.40E+07 -0.6% 298.5 297.1 0.5% 125.0 127.0 -1.6%

2003 1.35E+07 1.37E+07 -0.9% 145.2 144.6 0.4% 89.8 91.3 -1.7%

2004 1.93E+07 1.94E+07 -0.3% 125.2 124.3 0.7% 85.2 87.2 -2.3%

2005 1.05E+07 1.05E+07 -0.4% 188.7 185.3 1.8% 103.0 102.0 1.0%

2006 1.36E+07 1.36E+07 0.2% 391.4 385.5 1.5% 104.0 105.0 -1.0%

2007 7.66E+06 7.67E+06 -0.2% 154.4 149.9 2.9% 120.0 116.0 3.3%

2008 3.31E+07 3.34E+07 -0.7% 185.3 185.8 -0.3% 71.4 71.7 -0.4%

2009 2.21E+07 2.22E+07 -0.4% 213.0 212.8 0.1% 85.6 84.9 0.8%

2010 2.44E+07 2.45E+07 -0.3% 234.5 232.4 0.9% 84.1 84.4 -0.4%

2011 1.03E+07 1.04E+07 -0.7% 156.2 155.8 0.3% 84.8 82.0 3.3%

2012 1.27E+07 1.27E+07 0.0% 252.9 249.5 1.3% 190.0 193.0 -1.6%

2013 1.54E+07 1.55E+07 -0.8% 181.4 181.3 0.1% 64.5 64.5 0.0%

2014 1.54E+07 1.54E+07 0.0% 114.6 113.1 1.3% 84.8 84.6 0.2%
21

Site Year

Runoff (m) Mass Runoff Loss (kg) Max. Annual Conc (ug/L)

Indiv. MU 

Scenarios

Aggreg 

Scenarios

Pct 

Diff

Indiv. MU 

Scenarios

Aggreg 

Scenarios

Pct 

Diff

Indiv. MU 

Scenarios

Aggreg 

Scenarios

Pct 

Diff

MO-05b

5039952

2000 8.18E+07 8.15E+07 0.3% 1254.8 1238.6 1.3% 74.6 73.9 0.9%

2001 9.15E+07 9.15E+07 0.1% 1023.4 1012.7 1.1% 49.6 49.3 0.6%

2002 8.56E+07 8.59E+07 -0.4% 1410.8 1408.4 0.2% 73.5 73.3 0.3%

2003 9.55E+07 9.59E+07 -0.5% 762.9 758.0 0.6% 67.6 67.2 0.6%

2004 1.19E+08 1.19E+08 -0.2% 700.8 699.8 0.1% 60.0 59.9 0.2%

2005 5.67E+07 5.68E+07 -0.2% 934.0 916.4 1.9% 80.4 79.6 1.0%

2006 8.82E+07 8.80E+07 0.2% 1878.4 1847.0 1.7% 68.4 68.3 0.1%

2007 4.69E+07 4.69E+07 0.0% 813.8 790.1 2.9% 76.8 75.5 1.7%

2008 2.19E+08 2.20E+08 -0.5% 1056.5 1058.9 -0.2% 62.5 62.4 0.2%

2009 1.36E+08 1.36E+08 -0.3% 1116.1 1114.6 0.1% 70.7 69.9 1.1%

2010 1.54E+08 1.54E+08 -0.1% 1144.2 1135.4 0.8% 64.2 64.1 0.2%

2011 6.26E+07 6.29E+07 -0.6% 793.2 790.5 0.3% 55.4 53.5 3.4%

2012 6.98E+07 6.96E+07 0.2% 1212.2 1196.6 1.3% 139.0 139.0 0.0%

2013 9.41E+07 9.47E+07 -0.6% 926.2 926.6 0.0% 53.7 53.8 -0.2%

2014 1.02E+08 1.01E+08 0.2% 499.9 494.4 1.1% 55.0 54.3 1.3%

MO-08

2508563

2000 1.86E+07 1.86E+07 -0.2% 239.0 241.5 -1.1% 82.4 81.2 1.5%

2001 2.18E+07 2.18E+07 -0.1% 327.2 324.7 0.8% 63.9 63.2 1.1%

2002 1.42E+07 1.43E+07 -0.3% 263.4 264.5 -0.4% 96.4 94.4 2.1%

2003 1.49E+07 1.49E+07 -0.2% 176.1 175.4 0.4% 83.5 82.6 1.1%

2004 2.27E+07 2.28E+07 -0.4% 158.6 158.4 0.1% 52.9 52.6 0.6%

2005 9.71E+06 9.72E+06 -0.1% 100.3 97.4 2.9% 107.0 105.0 1.9%

2006 1.69E+07 1.68E+07 0.3% 409.7 405.6 1.0% 75.2 75.0 0.3%

2007 7.52E+06 7.53E+06 -0.1% 153.9 151.6 1.5% 76.2 75.6 0.8%

2008 5.02E+07 5.04E+07 -0.4% 284.4 287.0 -0.9% 64.0 65.0 -1.6%

2009 3.44E+07 3.45E+07 -0.3% 327.1 328.8 -0.5% 62.8 62.8 0.0%

2010 3.54E+07 3.55E+07 -0.2% 244.9 243.0 0.8% 72.4 70.5 2.6%

2011 1.85E+07 1.86E+07 -0.2% 237.5 237.9 -0.1% 67.5 66.6 1.3%

2012 1.48E+07 1.47E+07 0.6% 285.8 281.8 1.4% 183.0 179.0 2.2%

2013 2.62E+07 2.63E+07 -0.5% 302.0 304.3 -0.7% 80.3 82.4 -2.6%

2014 2.10E+07 2.10E+07 -0.1% 147.2 148.0 -0.6% 56.8 55.4 2.5%

For the five test basins in IN, the total annual runoff was within <1% and the total annual 

pesticide mass lost was within <2%. Estimated annual maximum concentrations were within 5% 

of each other in 4 of the 5 basins and within 10% in all 5 test basins (Table 4). 
22

Table 4: Comparison of Annual Total Runoff, Total Mass Loss, and Maximum Concentrations for 

Scenarios based on Individual Soil Map Units vs Scenarios based on Soils Grouped by WQI Categories 

for IN Test Basins.

Site Year

Runoff (m) Mass Runoff Loss (kg) Max. Annual Conc (ug/L)

Indiv. MU 

Scenarios

Aggreg 

Scenarios

Pct 

Diff

Indiv. MU 

Scenarios

Aggreg 

Scenarios

Pct 

Diff

Indiv. MU 

Scenarios

Aggreg 

Scenarios

Pct 

Diff

IN-10 

eco

18459870

2000 1.08E+07 1.08E+07 0.2% 161.6 161.5 0.1% 59.4 60.5 -1.9%

2001 1.13E+07 1.13E+07 0.8% 128.3 126.2 1.7% 73.8 74.6 -1.1%

2002 1.12E+07 1.11E+07 0.4% 130.1 131.7 -1.3% 70.0 71.3 -1.9%

2003 1.68E+07 1.68E+07 0.4% 298.4 298.7 -0.1% 66.8 67.7 -1.3%

2004 9.94E+06 9.91E+06 0.3% 201.2 202.9 -0.8% 61.4 62.1 -1.1%

2005 1.56E+07 1.55E+07 0.5% 189.7 188.2 0.8% 94.6 97.7 -3.3%

2006 1.55E+07 1.54E+07 0.2% 113.7 113.3 0.3% 58.9 59.7 -1.4%

2007 1.18E+07 1.17E+07 0.7% 101.4 100.0 1.4% 93.2 94.7 -1.6%

2008 1.78E+07 1.77E+07 0.5% 232.9 233.6 -0.3% 55.3 56.8 -2.7%

2009 1.13E+07 1.13E+07 0.3% 152.7 152.7 0.1% 57.6 58.7 -1.9%

2010 1.09E+07 1.09E+07 0.5% 168.6 167.7 0.5% 42.7 43.5 -1.9%

2011 1.97E+07 1.96E+07 0.7% 123.3 122.6 0.6% 74.5 76.0 -2.0%

2012 8.41E+06 8.39E+06 0.2% 83.8 83.2 0.8% 155.0 159.0 -2.6%

2013 1.29E+07 1.28E+07 0.6% 66.5 65.2 1.9% 92.9 93.7 -0.9%

2014 7.09E+06 7.03E+06 0.8% 56.4 56.5 -0.2% 49.6 51.0 -2.8%

IN-04 

river

18454511

2000 5.20E+07 5.18E+07 0.5% 678.1 679.9 -0.3% 71.4 70.5 1.3%

2001 5.60E+07 5.57E+07 0.6% 558.4 562.8 -0.8% 60.1 59.7 0.7%

2002 4.98E+07 4.94E+07 0.8% 454.0 453.3 0.2% 46.6 46.5 0.2%

2003 4.24E+07 4.20E+07 0.8% 376.0 376.8 -0.2% 64.4 64.2 0.3%

2004 4.76E+07 4.73E+07 0.7% 518.1 518.5 -0.1% 59.2 58.5 1.2%

2005 4.81E+07 4.78E+07 0.5% 434.1 440.2 -1.4% 76.0 75.9 0.1%

2006 6.33E+07 6.30E+07 0.5% 427.7 429.0 -0.3% 63.8 63.0 1.3%

2007 3.91E+07 3.89E+07 0.6% 480.4 492.0 -2.4% 58.3 59.8 -2.6%

2008 8.06E+07 8.00E+07 0.8% 824.8 829.8 -0.6% 59.6 59.0 1.0%

2009 5.71E+07 5.68E+07 0.5% 623.4 623.5 0.0% 67.2 66.1 1.6%

2010 4.36E+07 4.32E+07 0.7% 537.3 537.5 0.0% 54.1 53.5 1.1%

2011 7.49E+07 7.42E+07 0.9% 585.4 586.6 -0.2% 72.0 71.2 1.1%

2012 3.40E+07 3.38E+07 0.4% 295.6 302.0 -2.1% 161.0 154.0 4.3%

2013 3.75E+07 3.72E+07 0.7% 217.9 218.9 -0.5% 72.5 71.3 1.7%

2014 2.35E+07 2.33E+07 0.9% 123.3 124.7 -1.1% 41.1 40.9 0.5%

IN-06 

river

18450057

2000 6.47E+07 6.43E+07 0.6% 606.0 610.0 -0.6% 70.4 67.2 4.5%

2001 6.16E+07 6.13E+07 0.5% 328.0 333.1 -1.6% 61.3 62.0 -1.1%

2002 6.17E+07 6.14E+07 0.4% 502.6 502.4 0.1% 49.4 48.5 1.8%

2003 4.63E+07 4.60E+07 0.5% 345.1 354.3 -2.7% 68.3 67.1 1.8%

2004 5.60E+07 5.57E+07 0.5% 543.8 550.8 -1.3% 62.5 60.2 3.7%

2005 5.14E+07 5.11E+07 0.6% 334.7 336.8 -0.6% 80.9 81.6 -0.9%

2006 7.04E+07 7.01E+07 0.5% 301.6 303.4 -0.6% 70.9 69.8 1.6%

2007 3.62E+07 3.61E+07 0.3% 288.4 299.4 -3.8% 60.9 65.4 -7.4%
23

Site Year

Runoff (m) Mass Runoff Loss (kg) Max. Annual Conc (ug/L)

Indiv. MU 

Scenarios

Aggreg 

Scenarios

Pct 

Diff

Indiv. MU 

Scenarios

Aggreg 

Scenarios

Pct 

Diff

Indiv. MU 

Scenarios

Aggreg 

Scenarios

Pct 

Diff

2008 9.04E+07 8.99E+07 0.6% 712.7 723.5 -1.5% 64.5 63.4 1.7%

2009 6.21E+07 6.18E+07 0.5% 523.6 527.9 -0.8% 74.2 72.8 1.9%

2010 3.69E+07 3.68E+07 0.4% 380.5 389.1 -2.3% 61.7 60.0 2.8%

2011 7.91E+07 7.87E+07 0.5% 579.7 582.9 -0.5% 75.4 74.4 1.3%

2012 3.51E+07 3.49E+07 0.5% 232.0 235.4 -1.5% 165.0 161.0 2.4%

2013 4.27E+07 4.24E+07 0.5% 257.9 261.8 -1.5% 82.9 80.8 2.5%

2014 2.39E+07 2.37E+07 0.7% 123.7 125.4 -1.4% 48.5 48.5 0.0%

IN-08 

river

18445664

2000 1.84E+09 1.82E+09 1.0% 19020.7 19024.5 0.0% 64.6 64.9 -0.5%

2001 1.71E+09 1.69E+09 1.1% 14202.8 14179.6 0.2% 52.4 52.5 -0.2%

2002 1.79E+09 1.78E+09 1.0% 14047.5 14049.3 0.0% 53.9 49.3 8.5%

2003 1.82E+09 1.80E+09 1.1% 17803.6 17779.8 0.1% 56.7 56.0 1.2%

2004 1.87E+09 1.85E+09 1.1% 21633.3 21646.3 -0.1% 45.9 46.0 -0.2%

2005 2.06E+09 2.04E+09 1.0% 20515.4 20577.1 -0.3% 60.8 61.7 -1.5%

2006 2.46E+09 2.44E+09 0.9% 14783.7 14778.2 0.0% 44.8 45.0 -0.4%

2007 1.36E+09 1.35E+09 1.0% 8757.2 8823.7 -0.8% 57.8 58.9 -1.9%

2008 2.95E+09 2.92E+09 0.9% 28350.0 28347.4 0.0% 45.1 45.4 -0.7%

2009 2.26E+09 2.24E+09 0.9% 21455.4 21451.7 0.0% 49.7 49.3 0.8%

2010 1.54E+09 1.53E+09 0.9% 19940.3 19919.6 0.1% 49.7 50.1 -0.8%

2011 2.93E+09 2.90E+09 1.1% 19986.1 20004.2 -0.1% 63.2 63.7 -0.8%

2012 1.28E+09 1.26E+09 1.0% 10946.1 10995.3 -0.4% 93.6 90.7 3.1%

2013 1.70E+09 1.69E+09 1.0% 8919.5 8966.5 -0.5% 56.8 56.9 -0.2%

2014 9.96E+08 9.84E+08 1.2% 5752.9 5764.8 -0.2% 39.3 39.4 -0.3%

IN-13 

river

18451035

2000 1.90E+08 1.90E+08 0.0% 966.5 974.2 -0.8% 48.7 47.5 2.5%

2001 1.38E+08 1.38E+08 0.3% 511.4 515.3 -0.8% 49.2 48.6 1.2%

2002 1.87E+08 1.87E+08 0.2% 709.9 708.3 0.2% 27.0 26.9 0.4%

2003 1.23E+08 1.23E+08 0.2% 528.6 533.3 -0.9% 41.7 41.3 1.0%

2004 2.05E+08 2.04E+08 0.2% 1018.1 1022.9 -0.5% 37.1 36.8 0.8%

2005 1.48E+08 1.48E+08 0.2% 695.8 698.8 -0.4% 55.2 55.0 0.4%

2006 1.98E+08 1.98E+08 0.2% 442.5 442.1 0.1% 35.2 34.6 1.7%

2007 1.11E+08 1.11E+08 0.0% 292.1 297.6 -1.9% 37.0 38.0 -2.7%

2008 2.22E+08 2.22E+08 0.2% 1038.9 1040.4 -0.1% 28.0 28.8 -2.9%

2009 1.87E+08 1.86E+08 0.2% 861.2 863.6 -0.3% 49.3 48.5 1.6%

2010 1.04E+08 1.03E+08 0.3% 565.1 568.3 -0.6% 36.1 36.2 -0.3%

2011 2.45E+08 2.44E+08 0.2% 1003.8 1004.7 -0.1% 62.2 61.5 1.1%

2012 1.11E+08 1.10E+08 0.2% 685.0 686.1 -0.1% 117.0 114.0 2.6%

2013 1.39E+08 1.39E+08 0.1% 526.6 532.6 -1.1% 56.9 55.8 1.9%

2014 8.16E+07 8.15E+07 0.1% 182.4 184.8 -1.3% 20.2 20.6 -2.0%
24

For the three test basins in OH, the total annual runoff was within <1%, total annual pesticide 

mass lost was within <2%, and estimated annual maximum concentrations were within 2% of 

each other (Table 5). 

Table 5: Comparison of Annual Total Runoff, Total Mass Loss, and Maximum Concentrations for 

Scenarios based on Individual Soil Map Units vs Scenarios based on Soils Grouped by WQI Categories 

for OH Test Basins.

Site Year

Runoff (m) Mass Runoff Loss (kg) Max. Annual Conc (ug/L)

Indiv. MU 

Scenarios

Aggreg 

Scenarios

Pct 

Diff

Indiv. MU 

Scenarios

Aggreg 

Scenarios

Pct 

Diff

Indiv. MU 

Scenarios

Aggreg 

Scenarios

Pct 

Diff

OH-04 

eco

3483775

2000 8.03E+06 8.03E+06 0.1% 69.0 68.3 1.0% 59.0 58.3 1.2%

2001 7.01E+06 6.98E+06 0.4% 116.0 114.4 1.4% 41.1 40.8 0.7%

2002 7.94E+06 7.90E+06 0.5% 110.8 109.3 1.4% 61.8 61.6 0.3%

2003 4.87E+06 4.84E+06 0.6% 40.8 40.5 0.8% 33.3 32.8 1.5%

2004 1.10E+07 1.10E+07 0.5% 131.0 129.4 1.2% 44.0 43.7 0.7%

2005 9.60E+06 9.57E+06 0.3% 64.8 65.0 -0.3% 63.2 63.0 0.3%

2006 1.05E+07 1.04E+07 0.5% 98.5 97.8 0.7% 56.1 55.7 0.7%

2007 1.11E+07 1.10E+07 0.3% 31.1 31.5 -1.2% 40.6 39.5 2.7%

2008 1.09E+07 1.08E+07 0.5% 151.0 148.8 1.5% 47.0 46.5 1.1%

2009 7.23E+06 7.20E+06 0.3% 91.0 90.7 0.4% 61.2 60.5 1.1%

2010 7.72E+06 7.69E+06 0.4% 107.4 106.1 1.3% 47.9 47.7 0.4%

2011 1.07E+07 1.06E+07 0.7% 50.7 50.5 0.5% 40.8 40.3 1.2%

2012 5.77E+06 5.73E+06 0.7% 78.3 77.9 0.5% 67.9 67.2 1.0%

2013 4.94E+06 4.92E+06 0.5% 41.1 41.2 -0.2% 64.4 63.6 1.2%

2014 2.84E+06 2.83E+06 0.3% 27.2 27.2 0.2% 41.2 41.5 -0.7%

OH-10 

river

5214753

2000 1.75E+08 1.75E+08 0.0% 1803.8 1761.9 2.3% 39.9 39.5 1.0%

2001 1.13E+08 1.14E+08 -0.4% 850.7 846.2 0.5% 37.0 36.9 0.3%

2002 6.31E+07 6.32E+07 -0.2% 619.5 601.0 3.0% 44.1 43.6 1.1%

2003 1.43E+08 1.44E+08 -0.3% 861.7 862.0 0.0% 38.7 39.0 -0.8%

2004 1.55E+08 1.55E+08 -0.3% 1993.5 2011.6 -0.9% 32.7 32.9 -0.6%

2005 1.59E+08 1.59E+08 -0.2% 757.4 746.3 1.5% 38.8 38.9 -0.3%

2006 1.80E+08 1.79E+08 0.3% 1050.0 1043.8 0.6% 32.9 32.5 1.2%

2007 2.11E+08 2.11E+08 0.4% 936.4 907.2 3.1% 34.5 34.0 1.4%

2008 1.91E+08 1.91E+08 -0.1% 1934.7 1916.8 0.9% 51.4 51.4 0.0%

2009 1.20E+08 1.19E+08 0.7% 1103.2 1079.6 2.1% 42.1 42.8 -1.7%

2010 1.20E+08 1.19E+08 0.7% 1439.2 1435.6 0.2% 45.9 45.7 0.4%

2011 2.78E+08 2.79E+08 -0.3% 1470.1 1454.6 1.1% 38.3 38.4 -0.3%

2012 1.33E+08 1.33E+08 0.7% 1356.7 1322.4 2.5% 64.3 62.9 2.2%

2013 1.94E+08 1.93E+08 0.2% 1463.1 1461.7 0.1% 50.6 50.5 0.2%

2014 6.77E+07 6.65E+07 1.8% 757.2 737.3 2.6% 28.1 27.4 2.5%

OH-11 

reservoir

5213585

2000 6.84E+07 6.78E+07 0.8% 475.2 473.9 0.3% 30.3 30.8 -1.7%

2001 3.70E+07 3.67E+07 0.8% 237.8 236.1 0.7% 24.5 25.2 -2.9%

2002 3.04E+07 3.02E+07 0.6% 341.1 342.3 -0.3% 33.9 34.3 -1.2%
25

Site Year

Runoff (m) Mass Runoff Loss (kg) Max. Annual Conc (ug/L)

Indiv. MU 

Scenarios

Aggreg 

Scenarios

Pct 

Diff

Indiv. MU 

Scenarios

Aggreg 

Scenarios

Pct 

Diff

Indiv. MU 

Scenarios

Aggreg 

Scenarios

Pct 

Diff

2003 5.92E+07 5.88E+07 0.6% 241.8 238.7 1.3% 20.1 20.3 -1.0%

2004 5.46E+07 5.43E+07 0.5% 521.0 522.4 -0.3% 29.0 29.4 -1.4%

2005 6.57E+07 6.54E+07 0.4% 349.4 345.6 1.1% 38.9 39.2 -0.8%

2006 4.60E+07 4.58E+07 0.4% 293.5 288.2 1.8% 33.0 33.9 -2.7%

2007 5.26E+07 5.23E+07 0.5% 209.1 206.3 1.4% 30.8 32.0 -3.9%

2008 6.42E+07 6.36E+07 0.8% 627.0 623.2 0.6% 43.5 45.1 -3.7%

2009 4.26E+07 4.24E+07 0.5% 358.0 351.4 1.8% 32.3 32.7 -1.2%

2010 3.52E+07 3.50E+07 0.6% 357.2 357.1 0.0% 37.8 39.2 -3.7%

2011 8.40E+07 8.34E+07 0.7% 374.9 373.4 0.4% 31.5 32.3 -2.5%

2012 3.59E+07 3.56E+07 0.8% 310.4 306.9 1.1% 42.5 43.4 -2.1%

2013 4.92E+07 4.88E+07 0.9% 325.8 319.0 2.1% 38.3 38.9 -1.6%

2014 3.34E+07 3.31E+07 0.8% 291.3 290.8 0.2% 23.7 23.9 -0.8%

A visual comparison of plots of the estimated concentration distributions over time (Figure 11) 

for the two scenario (individual map units or aggregated soil group) approaches showed nearly 

identical overlaps for most of the test basin sites and years. Figure 12 shows the gap between 

the two methods for the years with greatest variability. Even with these sites, the majority of 

estimated peaks are in close agreement. 

Figure 11: Comparison of Estimated Atrazine Concentrations Using Individual Soil Map Unit (blue) or 

Aggregated Soil Group (yellow dash) Scenarios for MO-01.
26

Figure 12: Comparison of Estimated Atrazine Concentrations Using Individual Soil Map Unit (blue) or 

Aggregated Soil Group (yellow dash) Scenarios for MO-02.

Comparisons for all of the test basins can be found in the accompanying Appendix 3-F.B 

spreadsheet.