Ef coop meetingpres_11102011

East Fork Watershed Water Quality
Monitoring and Modeling Cooperative
(EFWCoop): November 10th Meeting.

Office of Research and Development
1. National Risk Management Laboratory, Water Supply and Water Resources Division, Water Quality Management Branch November 10, 2011

Overarching R&D Objectives for
establishing the East Fork Watershed
Cooperative
1. Integration of natural and built systems
2. Coupled modeling and monitoring programs for
decision support
3. BMP/GI performance to effectiveness linkages
4. Informational (data) architectures and required
cooperation for sustainable total water
management
5. Consider scaling and extrapolation within and
across systems.

R&D Projects Currently Supported by
the EFWCoop Program

• Linked models to support decisions across the
natural/built system interface
• Small stream ecology – monitoring/modeling
• Small-scale modeling protocols for assessing BMP
effectiveness
• Conservation Innovation Grant – Innovative AgBMPs
• Treatability translations
• Evaluation of water quality trading market models
• Development and testing of data management and
exchange architectures

DWTP Sampling Update

Mike provide a review of his
DWTP intake sampling
effort. The next few slides
summarize

East Fork Lake
Large Midwestern
watershed draining to a
National Scenic River and
then the Ohio River
Agriculture
2000 acre water surface
890 km2 of upland drainage
• 64% agriculture
• 26% forest
• 1.5 % imperviousness
• 1.4% lawn
• 1.3% impounded

20 MGD DWTP

20 MGD DWTP
MnO4 pre-oxidation
Coagulation
Settling
Filtration
Cl2

• THM levels exceed 80 ug/L MCL during summer
• increasing number of taste & odor episodes during summer

• increasing period of (reduced) Mn(II) (necessitating more pre-oxidant usage)
(spring-to- fall )
• Increasing number of sulfide episodes (more pre-oxidant usage) during summer

Adding deep-bed GAC to meet 2012 Stage-2 DBP Rule

Clear-well DBP Concentration vs. Source Water Chlorophyll-a
140 120

THMs

120 HAA9
100
CHLa-
surface

100
80

80

CHLa (Ug/L)
DBP (ug/L)

60

60

40
40

20
20

0 0
4/7/2009 7/16/2009 10/24/2009 2/1/2010 5/12/2010 8/20/2010 11/28/2010
date

Algal and Harmful-algal Derived Water Treatment Challenges

Algal blooms

Cl2
Reacti
Stage-2 violations
Advanced
ve
DOM DBPs
Treatment $$$

ozonation
CO
Consumer complaints!
AOP Taste
& odor
Consumer confidence!
2
HABs cmpds
PAC/GAC btu
Consumer confidence!
algal Future regulations?
toxin
s

Algal Concerns
• DBP precursors
• Taste & Odors
• Oxygen deficiencies
• Toxins
• Filter clogging
• pH changes
• Light limiting
• Decreased recreational use
• Decreased property values
• Economy

Content courtesy of Richard Lorenz
City of Westerville

Real-time in-situ monitoring
River and/or Reservoir Treatment Plant Processes
chlorophyll a Ecology Processes coagulation, settling, filtration,
chlorination, activated carbon, membrane
phycocyanin (cyanobact. pigment) biogeochemistry, hydrology, ecology
filtration
DO
pH
ORP
turbidity
Conductivity
UV absorbance (DOM) In Plant Data

Reservoir Modeling Source Modeling
Data - Water Finished
fate and Treatment Water
various Data -
transport Processes Data
depths 1_depth
Grab sampling
chlorophyll a
phycocyanin (cyano bact. pigment)
algal taxonomy (species level counting) Grab sampling
nutrients DBPs -THMs, HAAs
pH UV absorbance (DOM)
turbidity/sechi fluorescence EEMs (DOM)
DOC/TOC, UV absorbance (DOM) Chlorine demand, etc.
fluorescence EEMs (DOM)
DBP (THMs) formation potential

UEFW SWAT Modeling
Update and WQT Case
Study – Large Scale
Modeling

National Risk Management Laboratory, Water Supply and Water Resources Division, Water Quality Management Branch

Overcoming model parameterization
issues (UEFW Scale)

1. SSURGO vs. STATSGO Soils
2. SWAT Project Subbasin
delineation

Summary of Working with the SSURGO data (11/9/2011 by SCK)
•There are two commonly used soils databases: SSURGO and STATSGO. The scale of the SSURGO database generally
ranges from 1:12,000 to 1:63,360. SSURGO is the most detailed level of soil mapping done by the Natural Resources
Conservation Service (NRCS) (http://soils.usda.gov/survey/geography/ssurgo/description.html). For the 48 conterminous
states, the STATSGO database is at the scale of 1:250,000 (http://www.il.nrcs.usda.gov/technical/soils/statsgo_inf.html).
With regard to the information needed for modeling, the formats of SSURGO and STATSGO are the same. More information
on the format details can be found at http://soildatamart.nrcs.usda.gov/documents/SSURGO%20Metadata%20-
%20Tables%20and%20Columns%20Report.pdf. To summarize, the databases include both tabular (text files) and spatial
(shape files) data. Depending on the area to be covered, multiple files need to be combined into one dataset (comprised of
one tabular and one spatial). The East Fork Watershed (EFW) is covered by one STATSGO dataset. Six counties of SSURGO
data need to be aggregated into one dataset for use in SWAT.

•To be used in SWAT, each soil classification listed in the SSURGO/STATSGO for the area being modeled (the EFW) must have
a match in the SWAT soils reference database. Using ArcGIS tools, the area of the SSURGO/STATSGO shape files were clipped
close (a buffer was applied) to the boundary of the EFW. A link was established between the clipped spatial data and the
tabular data. Tabular data not related to the area associated to the buffered EFW was removed from further consideration.
The EFW tabular databases (SSURGO and STATSGO) were each joined to the SWAT soils classification database. There were
no orphan records in the STATSGO database, but there were orphans in the SSURGO database. The following table shows
the orphan SSURGO soil classifications (COMPNAME) and also shows how the soil classification was renamed to match with
the SWAT classification table.

•The substitutions were made based on an extensive review of the STATSGO data and the neighboring soils of the orphan
SSURGO classifications. Information from the following site was also used http://soils.usda.gov/technical/classification/ when
assigning a SWAT classification to the SSURGO orphans.

UEFW Preliminary Discretization

The National Elevation Dataset 10 meter dataset was downloaded
for each of the six counties in the East Fork Watershed. The files
were aggregated into one for use with SWAT. The layer was
reprojected from UTM 1983 17N to 16N. To reduce SWAT
processing time, the NED layer was clipped to just larger than
the East Fork Watershed. The watershed delineation was
performed in the SWAT model using an area of 500 to get the
default outlet locations at this scale. Then the watershed
delineation was performed again using an area of 10. Both
delineations used the NHD flowlines to burn in the stream
network. In the SWAT model that was delineated using an area of
10, all the default outlet locations were removed, and the default
outlet locations from the area of 500 delineation were added.
Then, the default outlets that were in the lake were removed, and
several other outlets were added. This delineation still needs to
be fine tuned.

W ater Quality Trading Case Study: Determining
feasibility and advancing the market model

Assumption:
DWTP operator colludes with
WWTPs to reduce Ag Loadings.

Nutrient Trading program leads to:
• Fewer algal blooms
WWTPs
• Shorter periods of eutrophication
and hence…. DWTP
easier/cheaper water treatment.

Downstream Direction

WSC Proposal 2011 Submitted Oct 19th
The central question is: can watersheds and
drinking water plants be understood as a single

human‐engineered‐natural system?
system, and how can human decisions regarding
water quality be improved by modeling the coupled

CIG Effort Update-

Cover Crop Sign-up
Soil Sampling
Small-scale Modeling


GRT Headwatershed (2.5 km2) where
Innovative AgBMPs are being tested in HUC 12 Subwatershed (111 km2) with weekly monitoring
cooperation with the CC SWCD, Farm points shown
Services, and NRCS

Those areas were used by SWCD
to target fields for cover crop
Preliminary Modeling with
placement. Land Owners were
AnnAGNPs and SWAT Models were
approached. Gray areas are slated
used to project high areas of
for cover crops
sediment yield (rust colored area)

Model Application Development: Rules/Criteria for

1) Delineating Subbasins at GRT Scale
2) Accounting for differences in spatial
distributions of crop rotations
3) Modeling fertilizer and pesticide application
rates.
4) Estimating channel widths and depth at
subbasin outlets.

Rules to Delineate subbasins at GRT scale
1. A threshold area (critical source area) of 2 hectares was selected to define the stream network.
2.The stream network generated by ArcSWAT did not match the actual stream in the field (based on the aerial
photos). So this generated stream network was edited in ArcGIS to conform to the actual stream. This edited
stream network was then burned in to the DEM. The flow direction and accumulation was recalculated after the
burn in. The same threshold area of 2 hectares was selected and the stream network was generated again.
3.The GRT watershed outlet point was selected as the whole watershed outlet and the watershed delineation was
done keeping all the default subbasin outlets generated by ArcSWAT.
4.The areas of the subbasins generated were analyzed to make sure that the individual subbasin areas were
greater than 10% and less than 190% of the mean subbasin area. Any subbasin smaller than the threshold was
removed by deleting the corresponding subbasin outlet and those subbasins which are higher than the
threshold were divided by adding outlets.
5.Adding or deleting an outlet had to be done by redefining the stream network. After the changes are made, the
whole watershed delineation is done again.
6.This process may take a few tries till you obtain a final watershed delineation.

Rules to account for differences in spatial distributions of crop rotations at GRT Scale
1.National Agricultural Statistics Service (NASS) provides the Cropland Data Layer (CDL), which contains crop
specific digital data layers. CDL is available for the Ohio from 2005 to 2010.
2.The CDL for the GRT watershed (Clermont County) was downloaded and for all the years available (2005-
2010). The land use layer for the GRT watershed was super-imposed on the CDL to determine the actual crop
rotations for the watershed. The crop rotations for GRT are shown in Figure 1. The green cells represent
soybean and the yellow cells represent corn.
3.The agricultural land within this watershed was further subdivided into separate land use classes based on the
unique crop rotation pattern they follow. Figure 2 shows the polygon numbers of the agricultural parcels created
within GRT. The crops currently (2011) planted in the GRT watershed was obtained from NRCS and Clermont
County. Having the crop rotation data from 2006 to 2011, the same crop rotation was assumed to be present in
those areas for the years starting at 1989. Table 1 was created based on this assumption and it shows what
crop is grown in which parcel during the years 1989 to 2011. 1989 is the starting year for available climate data
and the starting year of SWAT simulation. The different colors in the table represent unique crop rotation
patterns and the parcels having the unique crop rotation were grouped together to form a unique land use.
These land uses were further subdivided into parcels which would get a cover crop (in winter) and those that
will not. The “NC” at the end of the land use title represents parcels with no cover crops. The land use/land
cover data obtained from EPA for the Little Miami watershed for the year 2002 is shown in Figure 3 and it
shows that only soybean was planted in the GRT watershed during that year. Based on the Table 1, for year
2002 all the parcels would have had only soybean planted and this further validates our assumption.

Figure 1 – Crop rotations for GRT from CDL data.
2006 2007 2008

2009 2010

Crop rotations in recent years
do not follow the Corn, Bean,
Bean rotation rule of thumb

Green represents soybean and yellow is corn

Figure 2 - GRT Parcel Numbers

Had to re-characterize LandUse
for SWAT Model
parameterization based on parcel
and specific crop rotation
schedule. Otherwise all field
would be corn or bean in a given
year. This matters when it comes
to differences in fertilizer and
pesticide application pending the
crop type.

Reclassification of land use.
Table 1 Land use Classification

Parcel No. 65 71 73 246 101 103 74 240 43 243 239 102 98 75 77 80 81 241 57 44 248 244 31 32 30 85 86 247 216 105 59
2011 C C C C C C B B B B B B B B B B B B B B B B B B B B B B B B B
2010 B B B B B B C C C C C C C C C C C C C C C C C C C C C B B B B
2009 C C C C C C B B B B B B B B B B B B B B B B B B B B B B B B C
2008 B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B
2007 C C C C C C C C C C C C C C C C C C C C C B B B B B B B B B B
2006 B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B C
2005 C C C C C C B B B B B B B B B B B B B B B C C C C C C B B B B
2004 B B B B B B C C C C C C C C C C C C C C C B B B B B B B B B B
2000 B B B B B B B B B B B B B B B B B B B B B C C C C C C B B B C
1995 C C C C C C C C C C C C C C C C C C C C C C C C C C C B B B B
1994 B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B C
1990 B B B B B B B B B B B B B B B B B B B B B C C C C C C B B B B

Landuse title CBCB CBCBNC CBB CBBNC BCBBB BCBBBNC BBBB BBBBNC BBC
Landuse code 21 22 23 24 25 26 27 28 29
SWAT Landuse COR1 COR2 COR3 COR4 SOY1 SOY2 SOY3 SOY4 SOY5

“C” represents Corn and “B” represents Soybean

Figure 3 – EPA Land use/ Land cover data for 2002.

Dark Green represents soybean and yellow is corn. Light green is forest.

Rules to model fertilizer and pesticide application rates
Fertilizer
•Steve had provided the following application rates:
Corn:
N – 200 lbs per acre per planting season
P2O5 – 37 lbs per acre per year
K – 37 lbs per acre per year
Soybean:
P2O5 – 24 lbs per acre per year
K – 52 lbs per acre per year
He had mentioned that 20-30 lbs./acre of N and P would be applied before planting and the remaining amount would be applied 30-40 days
after planting. Also due to the non-availability of phosphate, MAP (Mono-ammonium phosphate 11-52-0) and DAP (Di-ammonium phosphate
18-46-0) are being used. UAN (28%) is used as the source for nitrogen.
•Lori had provided the following fertilizer recommendation:
Corn:
N – 1 lbs per acre per bushel yield
P2O5 – 20-40 lbs per acre per year (for soil test level “H”) and 40-80 lbs per acre per year (for soil test level “M”)
K – 20-40 lbs per acre per year (for soil test level “H”) and 40-80 lbs per acre per year (for soil test level “M”)
Soybean:
P2O5 – 40-80 lbs per acre per year (for soil test level “H”) and 80-160 lbs per acre per year (for soil test level “M”)
K – 40-80 lbs per acre per year (for soil test level “H”) and 80-160 lbs per acre per year (for soil test level “M”)
•NASS survey for fertilizer application in Ohio for the year 2010:
Corn:
N – 141 lbs per acre per year (Average)
P2O5 – 64 lbs per acre per year (Average)
K – 91 lbs per acre per year (Average)
Soybean: - No data was available
•Based on these recommendations, it was decided on the following application rates:
(Since SWAT does not track Potash, only Nitrogen and Phosphorus were considered)
P2O5 – 40 lbs per acre per year (for both corn and soybean). Out of which 20 lbs/acre will be applied before planting and 20 lbs/acre will be
applied 35 days after planting.
N – 200 lbs per acre per year (for corn). Out of which 30 lbs/acre will be applied before planting and 170 lbs/acre will be applied 35 days after
planting.
MAP was assumed to be source for P2O5. Since MAP contains 0.11kg N/kg, this would be deducted from the required N so that the total applied
N would sum up to a total of 200 lbs/acre.

Pesticide
•Steve had provided the following application rates :
Spring application:
2,4-D – 0.5 to 1.0 lb per acre
Roundup – 0.56 to 1.12 lbs per acre for Corn and 0.56 to 1.5 lbs per acre for Soybean
Atrazine – 1.4 to 2 lbs per acre
Spring application:
2,4-D – 1.0 qt. per acre (that would be 1 lb/Acre)
Roundup – 0.75 to 1.5 lbs per acre
Canopy – 2.25 oz per acre (Since Canopy is not in SWAT database and since we do not
monitor for Canopy, it is not applied).
•For the Spring application, it was decided to apply all three pesticides at the rate of 1/3rd the
recommended rates for all agricultural land. For the Fall application, it was decided to apply
both 2,4-D and Roundup at half the recommended rate for all agricultural land.

Criteria for estimation of channel widths and depths at subbasins (GRT)
•The actual stream bank full width and depth was measured at the GRT watershed outlet and near the EPA monitoring
point near Cornwell farm.
•SWAT assumes the channel sides have a 2:1 run to rise ratio. Based on this assumption, the channel cross-section area at
the watershed outlet is 60 sq.ft. and the cross-section area near Cornwell farm is 9.63 sq. ft.
•The total area of the GRT watershed is 623 acres and the area of the watershed draining at the monitoring point near
Cornwell farm is 277 acres.
•The width to depth ratios at the two cross-sections were almost the same(0.2). So it was decided to keep this ratio a
constant throughout the entire stream reach of the watershed and linearly interpolate the widths and depths between the
Cornwell site and the watershed outlet. For the channel reaches upstream of the Cornwell site, the same width-depth ratios
will be maintained. The cross-sections at the different reaches will also be cross checked from the lidar DEM.
•The slopes of the different reaches will be calculated based on the DEM elevations at the start and the end of the stream
reaches.

Lake Sampling in Oct 2011


October Sediment
Sampling
Funded by USACE

OM contents came up in the
Lake Sediment discussion for comparison I’ve
provided %OM contents from
Site ID LOI (%)
lake, crop fields, and stream
Bethel-Surface 8.37 beds. All from east fork areas.
*Note, these need to be
EFLMR-Surface 14.49
corrected for bulk density to be
EFL-Surface 2EFRWT 19.90 directly comparable, but BD
DAM-Surface 2EFR20001 21.17 would probably be highest n
lake sediment, so….
GRT Fields
Site ID LOI (%)
Accumulated
Field 6 3.42 Stream Beds
Field 7 3.17
10.23
Field 8 3.21

Office of Research and Development Field 9 3.63

GHG Sampling and closing the lake C and
N budget

First event of new project looking at Green House Gas production
in the Lake along with providing help to close the N and C budget Nutrient Data I collected below suggest that lake anoxia is limiting
for the lake. Leads are colleagues Jake Beaulieu from EPA and Amy nitrification (Ammonia increasing over LG profile of lake).
Townsand-Small from UC. The work will be the master’s thesis of
Becky Smolenski
DATE TIME SITE ID DEPTH UNIT TN TDN TNH4 DNH4 TNO23 DNO23 TUREA DUREA TP TDP TRP DRP
20111025 01:30:00 PM EUS 0 ug N(P)/L 914 814 81.3 97.7 344 324 32.8 19.5 76 52.7 60 51.5
20111025 01:30:00 PM EUS 2M ug N(P)/L 959 840 94.7 101 355 320 42.5 23.9 85.4 54.8 65.4 51.5
20111025 02:30:00 PM EEN 0 ug N(P)/L 894 826 123 130 312 303 51.7 26.4 73.3 50.7 56.5 48.4
20111025 02:30:00 PM EEN 7.5M ug N(P)/L 873 814 109 122 342 312 24.2 26 72 48.4 55.6 46.9
20111025 03:30:00 PM EWN 0 ug N(P)/L 840 810 129 138 307 295 23.8 16.1 70.8 51.6 53.9 51
20111025 03:30:00 PM EWN 8M ug N(P)/L 853 793 146 144 302 290 30.5 31.9 69.5 55.4 57.8 53
20111025 04:30:00 PM EDW 0 ug N(P)/L 831 824 126 132 306 301 31.4 22.9 67.7 55.4 55.9 53.2
20111025 04:30:00 PM EDW 14M ug N(P)/L 839 827 123 132 308 301 30.8 17.5 67.8 54.8 55.2 57.7
20111025 05:30:00 PM EOF 0 ug N(P)/L 873 849 201 206 263 256 27 27.3 73.9 58.1 57.7 56.7
20111025 05:30:00 PM EOF 27M ug N(P)/L 1280 1160 211 205 392 383 59 53 259 211 237 216
20111024 10:59:00 AM ELI (inflow) 0 ug N(P)/L 1720 56.3 617 65.2 453 391
20111024 12:38:00 PM DAM (outflow) 0 ug N(P)/L 915 230 245 23.5 83.4 51.4

Tipping Point
Research -
initiated


COLLABORATIVE RESEARCH: ROLE OF ORGANIC MATTER
SOURCE ON THE PHOTOCHEMICAL FATE OF PHARMACEUTICAL
COMPOUNDS – LEAD PI: ALLISON MACKAY, UCONN - FUNDED
PROLOGUE
An earlier version of this proposal was reviewed by a CBET panel and recommended for funding. The
panel noted that we had “identified an important problem … that deserves attention … [because] there are
knowledge gaps regarding their [pharmaceutical compounds] fate and the contribution of different degradation
mechanisms in actual aquatic systems.” The panel was “impressed by the … collaboration with [the] Pomperaug
River Watershed Coalition, which will serve as a way to disseminate results and offer basic community training.”
“However, the panel felt that a more unified experimental plan would have strengthened the proposal.” In
response to our panel comments, we have developed a new proposal that articulates in more detail how the
experimental tasks are integrated to meet our project objectives. We have also changed our second field site from
Boulder Creek, CO to the East Fork of the Little Miami River, OH to collaborate with the USEPA (Collaborator
Nietch) in this networked experimental watershed. This proposal targets the CBET emphasis area of “emerging
contaminants.”

Figure 2. Fate processes for pharmaceutical
Merged Data Interpretation compounds in aquatic systems. Arrow width is
• NOM/EfOM physiochem contrasts
• Photochem / physiochem relationships
proportional to the relative importance.
• Photochem / spectral relationships
• OM contribution to PO influence in kfield
• Variability in NOM/EfOM contribution to
PO influence in kfield vs season
• Variability in NOM/EfOM contribution to
PO influence in kfield vs site

Engineer (PI MacKay), a geochemist (PI Chin), a photochemist (PI Sharpless) and a systems
ecologist (Collaborator Nietch)

Monitoring Program
Issues:

Flow Gauge in the UEFW!
We talked about where to best install and how to obtain
the funding. Seemed most logical to partner with USACE
who already has flow monitoring contracts with USGS.
Need to get Erich’s input on this.

In the meantime we (EPA) will install a sonteck depth
integrated velocity and level gauge at a location in a
stretch above the Williamsburg Treatment Plant.


A. Aerial and Streams Data Stormwater BMP
Files
Retrofit Project?
B. Subcatchment John discussed the potential for a
discretization
stormwater BMP retrofit demonstration
project. We turned to some of the
C. Land Cover and
Properties Delineation
headwatershed locations that EPA has
studied in the past and are currently part of
the weekly monitoring program. The
D. SWMM Project-Existing
headwatershed at left could be an
Conditions
appropriate one, and it is already modeled

E. Alternative Scenarios

13.

Nex t m eeting scheduled for Decem ber 10 th ;
9:00am

*The ideas and opinions expressed herein are those of
the primary author and do not reflect official EPA position
or policy.
National Risk Management Laboratory, Water Supply and Water Resources Division, Water Quality Management Branch November 10, 2011

Ef coop meetingpres_11102011

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