DWQ-2024-004417

Understanding E.coli in the
San Juan Watershed:
Preliminary Data Gap Analysis and
Recommendations for an E.coli
Watershed Monitoring Program
Final Report
February 2024
Utah Department of Environmental Quality
Division of Water Quality
Prepared by:
Animas Environmental Services, LLC
624 E Comanche St.
Farmington, NM 87401
Tel [phone]
animasenvironmental.com

This page is intentionally left blank.

Contents
1.0 Introduction ................................................................................................................... 1
1.1 Purpose......................................................................................................................1
1.2 E.coli as a Water Quality Parameter ......................................................................... 2
1.3 Project Area ............................................................................................................... 3
Graph 1: Sub-Watersheds and Acreage within the San Juan Watershed ............... 4
1.4 Water Quality Standards ........................................................................................... 4
Table 1: Assessment Units, Designated Uses, and E.coli Water Quality Standards
per Jurisdiction .......................................................................................................... 5
2.0 Methods..................................................................................................................... 6
2.1 Data Sources .............................................................................................................. 6
Table 2: Data Sources, Availability, and Inclusion into Dataset................................6
2.2 Data Quality Assurance ............................................................................................. 7
2.3 Data Consolidation .................................................................................................... 8
2.3.1 Data Mapping .................................................................................................... 9
2.3.2 Merging Datasets .............................................................................................. 9
2.3.3 Data Scrubbing .................................................................................................. 9
2.4 Assumptions ............................................................................................................ 10
3.0 Data Characterization..................................................................................................11
3.1 Bacteria Types and Laboratory Analytical Methods ............................................... 11
: Bacteria and MST Results within Combined Dataset...............................11 Graph 2
(2004-2021) ............................................................................................................. 11
Table 3: Laboratory Method, Bacteria Measured, and Year(s) Used by Entity......12
3.2 Sample Location Density ......................................................................................... 12
Table 4: Sample Location Density per Sub-Watershed........................................... 13
3.3 E.coli Results over the Federal Water Quality Standard.........................................14
Table 5 Total Number of E.coli Samples Collected, Above the USEPA RWQC, and
Maximum Concentration per Sub-Watershed........................................................ 15
Table 6 E.coli Results over the USEPA RWQC per Sub-Watershed ........................ 15
3.4 Temporal Distribution .............................................................................................16
Graph 3: Seasonal Variation in Total E.coli Results and E.coli Results Over USEPA
RWQC by Sub-Watershed........................................................................................ 17
3.5 Preliminary Statistical Analysis ................................................................................ 18
3.5.1 Waterways with No RWQC Exceedances........................................................18
3.5.2 Waterways with USEPA RWQC Exceedances ................................................. 19
3.6 Microbial Source Tracking (MST) ............................................................................ 20
3.6.1 San Juan Watershed Group (SJWG) MST Sampling, 2013 and 2014.............. 21
3.6.2 SJWG 2013 and 2014 MST Sampling Results..................................................21
3.6.3 SJWG MST Sampling, 2021.............................................................................. 22
3.6.4 SJWG 2021 MST Sampling Results .................................................................. 22

Graph 4: Count of MST DNA Markers in MST Dataset (2013, 2014, 2021) ...........23
3.7 Land Use and Land Cover ........................................................................................23
3.7.1 Urban Development........................................................................................24
3.7.2 Wastewater Treatment Infrastructure ........................................................... 25
3.7.3 Irrigated Pasture and Grazing .........................................................................26
3.8 Potential Factors Limited Sampling Frequency and Density ..................................28
3.8.1 Hydrology Categories and Environmental Conditions....................................28
Graph 5: Number and Percentage of Hydrographic Categories of Major Tributaries
within the Watershed..............................................................................................29
Graph 6: Hydrographic Category of Major Tributaries per Sub-Watershed ..........29
3.8.2 Geographical Constraints ................................................................................30
3.8.3 Certified Laboratory Access and Capacities....................................................30
4.0 Conclusions and Recommendations ...........................................................................31
4.1 Conclusions ..............................................................................................................31
4.1.1 Waterways Sampled, Sample Locations and Sampling Density .....................32
4.1.2 E.coli Results Over USEPA RWQC Threshold................................................... 32
4.1.3 Temporal Distribution of E.coli Concentrations .............................................32
4.1.4 Preliminary Statistical Analyses.........................................................................33
4.1.5 MST Sampling ..................................................................................................33
4.1.6 Land Use and Land Cover ................................................................................. 33
4.1.7 Sampling Frequency and Locations Across the Watershed.............................34
4.2 Recommendations...................................................................................................34
5.0 References ...................................................................................................................36
6.0 Preparers and Funding Sources...................................................................................39
Figures
1. Project Area and Jurisdictional Boundaries
2. Sample Locations and Sampling Entities for E.coli, Total Coliform, Fecal Coliform,
and Microbial Source Tracking Data
3. All E.coli Sample Locations and Results over the USEPA Recreation Water Quality
Criteria
4. E.coli Sample Locations and Results over the USEPA Recreation Water Quality
Criteria: Upper San Juan (HUC 14080101) and Piedra (HUC 14080102) Sub-
Watersheds
5. E.coli Sample Locations and Results over the USEPA Recreation Water Quality
Criteria: Blanco (HUC 14080103 ) Sub-Watershed
6. E.coli Sample Locations and Results over the USEPA Recreation Water Quality
Criteria: Animas (HUC 14080104) Sub-Watershed
7. E.coli Sample Locations and Results over the USEPA Recreation Water Quality
Criteria: Middle San Juan (HUC 14080105) Sub-Watershed

8. E.coli Sample Locations and Results over the USEPA Recreation Water Quality
Criteria: Mancos (HUC 14080107) Sub-Watershed
9. E.coli Sample Locations and Results over the USEPA Recreation Water Quality
Criteria: Lower San Juan - Four Corners (HUC 14080201), McElmo (HUC
14080202), and Montezuma (HUC 14080203) Sub-Watersheds
10. E.coli Sample Locations and Results over the USEPA Recreation Water Quality
Criteria: Chinle (HUC 14080204) and Lower San Juan (HUC 14080205) Sub-
Watersheds
11. Microbial Source Tracking Sample Locations
12. Preliminary Land Use, Land Cover, Community Boundaries, and Permitted
Wastewater Infrastructure
13. Preliminary Hydrographic Category of Major Rivers and Streams
14. 2004-2021 Combined Data Laboratory Locations
Appendices
A. Recreation Designated Uses and Water Quality Standards for Multi-Jurisdictional
Assessment Units within the San Juan Watershed
B. Parameters Used for USEPA WQP Data Download
C. Complete List of Confirmed and Potential Data Sources for Further Consideration
D. Project QAPP
E. Combined Dataset, Data Mapping, Pre and Post Data Consolidation Notes, and
Template E.coli Database
F. Number of Sample Locations for each Waterway per Sub-Watershed
G. Percentage of E.coli Results over USEPA RWQC per Sub-Watershed and
Waterway
H. Total E.coli Results and E.coli Results over USEPA RWQC per Month and Year per
Sub-Watershed
I. Preliminary Statistical Evaluation
J. MST DNA Marker Sampling Detection Status within the Watershed
K. Percentage of Land Use and Land Cover for Each Sub-Watershed
L. Preliminary Identification of Permitted Wastewater Treatment Plants within the
Watershed
M. Preliminary Identification of Bacteriological Laboratory Services Utilized in the
Watershed

1.0 Introduction
1.1 Purpose
The Water Infrastructure Improvements for the Nation (WIIN) Act, enacted by the U.S.
Congress in 2016, authorized the appropriation of $4 million per year between 2017 and
2021 to be used in the San Juan Watershed (Watershed). This funding source was
allocated in response to the Gold King Mine Spill of 2015 which released approximately
3 million gallons of discharge from the Gold King Mine near Silverton, Colorado, the
headwaters of the Watershed (USEPA, 2023). The WIIN Act directs the U.S.
Environmental Protection Agency (USEPA) to work in consultation with states and tribes
impacted by the spill to support ongoing water quality monitoring, multi-jurisdictional
communication, and restoration planning efforts. This working group, known as the
WIIN Act Group, is composed of representatives from the USEPA Regions 6, 8, and 9,
Colorado Department of Public Health and Environment (CDPHE) Water Quality Control
Division (WQCD), New Mexico Environmental Department (NMED) Surface Water
Quality Bureau (SWQB), Southern Ute Indian Tribe (SUIT), Ute Mountain Ute Tribe (Ute),
Navajo Nation Environmental Protection Agency (NNEPA), Arizona Department of
Environmental Quality (ADEQ), and the Utah Department of Environmental Quality
(UDEQ) Division of Water Quality (UTDWQ).
To support this effort, the UTDWQ contracted Animas Environmental Services, LLC
(AES), on behalf of the WIIN Act Group, to evaluate the availability, spatial and temporal
trends, and potential sources of fecal pollution using all existing Escherichia coli (E.coli)
data sampled from surface waterways within the Watershed. Contamination of E. coli
over federal, state, and tribal water quality standards for recreational waters has been
an ongoing concern that warrants further research. Analyzing E.coli surface water
quality data from a multi-jurisdictional perspective is critical to further understand
potential pollution sources and to assist in strategic planning on a watershed scale to
improve surface water quality for the communities within the Watershed.
Once the E.coli data included in this project was compiled, consolidated, and
characterized, AES and UTDWQ determined that the data available could not be used to
conclusively determine potential sources of fecal pollution. The factors used in making
this determination include but are not limited to:
The geospatial distribution of the data is highly varied on a watershed,
waterway, temporal, and jurisdictional level;
A sizeable portion of sampling locations have not been sampled on a routine
basis;
E. coli in the San Juan Watershed
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Sampling locations for a single waterway over multiple jurisdictions have not
been sampled on the same date and do not have associated ambient field
measurements such as flow and precipitation, limiting the comparability of
results on a geospatial level.
The scope of work for this project was adapted accordingly to characterize the data
available and conduct a preliminary geospatial, temporal, and data gap analysis that will
provide a menu of recommendations for a long-term watershed-based monitoring
program and further analysis of existing data to assist in watershed planning efforts.
1.2 E.coli as a Water Quality Parameter
Under Section 304 of the Clean Water Act (CWA), pathogenic bacteria is one of the
many contaminants that federal, state, and tribal entities are required to monitor in
fresh surface waters of the United States. E.coli, a type of bacteria that lives in the
intestines of all warm blooded animals and is commonly found in human and animal
feces, is used as an indicator of more harmful bacteria to determine human health risk
(USEPA, 2021). The presence of and/or high quantities of pathogens in recreational
waters increase human health risk for gastrointestinal, respiratory, eye, ear, nose,
throat, and skin diseases (Rock & Rivera, 2014).
E.coli is both naturally and anthropogenically introduced to surface waters through
sources such as untreated wastewater plant (WWTP) effluent, faulty or failing on-site
wastewater treatment systems (septic systems), runoff from livestock management
(feedlots, pastures, manure storage areas), and wildlife habitat (USEPA, 2021).
Stormwater and sources within riparian corridors are direct vectors of the
transportation of E.coli and other contaminants to surface waters (Ahmed, Hamilton,
Toze, Cook, & Page, 2019).
While E.coli is a cost effective indicator of fecal pollution, it cannot provide definitive
information on host organisms, or potential sources, for fecal bacteria. Microbial
Source Tracking (MST) is a suite of analytical methods that were developed to
determine host organisms of fecal bacteria by quantifying specific DNA markers that
have evolved to correlate to specific host organisms (Harwood, Staley, Badgley, Borges,
& Korajkic, 2013). Both E.coli sampling, for comparison to federal, state, and tribal
water quality standards, and MST, for source identification, is needed for strategic
watershed planning.
There are several challenges to using E.coli as a water quality parameter, including: 1) a
short hold time of six hours from collection to laboratory analysis (as described in
Standard Method 9223B); 2) high variability in concentrations in time and space due to
E.coli’s aerobic life cycle; 3) E.coli’s ability to attach to sediment particles; and 4) positive
correlation with stormwater flow (USEPA, 2021).
E. coli in the San Juan Watershed
p. 2
1.3 Project Area
The San Juan Watershed (Watershed), Hydrologic Unit Code (HUC) 14080, is centrally
located in the American Southwest’s Four Corners Region of New Mexico (NM),
Colorado (CO), Utah (UT), and Arizona (AZ) and within Navajo Nation (NN), SUIT, Ute,
and Jicarilla Apache Nation (Jicarilla) lands. The Watershed encompasses over 15
million acres of the alpine mountain forest of Colorado, the semi-arid high desert
scrub/shrubland of New Mexico and Arizona, and lower elevation canyon country of
Utah.
The headwaters of the 355-mile-long San Juan River originate in the snowpack fed
streams of the San Juan Mountains of southern Colorado before it crosses over the New
Mexico state line and is retained in Navajo Reservoir. From its release from Navajo
Dam, the San Juan River proceeds to flow through Farmington, New Mexico, the Navajo
Nation, and the southeast corner of Utah to its terminus at Lake Powell and ultimately
the Colorado River. The Animas River, also originating in the San Juan Mountains of
Colorado, meets its confluence with the San Juan River in Farmington, New Mexico and
is the largest free-flowing perennial source of water to the San Juan River (USEPA,
2020). Other major tributaries are predominantly intermittent and flow during
patchwork precipitation events in a semi-arid environment.
©Bureau of Land Management, Utah

The San Juan River in Utah.
E. coli in the San Juan Watershed
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A total of 12 HUC8 sub-
watersheds (Sub-Watersheds)
encompass the Watershed
and funnel water to the San
Juan River. Each of the Sub-
Watersheds has their own
unique tributaries and lakes,
land use, and resource
concerns. The total acreage
and percentage for each
Sub-Watershed in
comparison to the acreage
for the entire Watershed is
provided in Graph 1. The
projection used to calculate
acreage in Graph 1 was
EPSG 4269: NAD83. The
Watershed, including major
tributaries and jurisdictional
boundaries, is depicted in
Figure 1.
Graph 1: Sub-Watersheds and Acreage within
the San Juan Watershed
1,561,147 (10%) 2,195,833 (14%)
432,886 (3%)
2,623,452 (16%) 1,096,869 (7%)
876,590 (5%)
748,156 (5%)
458,852 (3%) 1,244,785 (8%)
1,276,408 (8%)
513,247 (3%) 2,927,139 (18%)
Upper San Juan Piedra
Blanco Animas
Middle San Juan Chaco
Mancos Lower San Juan - Four Corners
McElmo Montezuma
Chinle Lower San Juan
1.4 Water Quality Standards
The CWA requires states and tribes to implement routine monitoring of surface waters
within their jurisdiction to ensure that they are meeting their designated use and
protect the associated resources and communities that use that water. E.coli, as an
indicator of human health risk, is a contaminant of concern specific to primary contact
and secondary contact designated uses. Primary contact includes recreation where
immersion and ingestion are likely, such as swimming, bathing, and diving. Secondary
contact includes recreation where human contact is less likely, such as fishing, wading,
and boating. Water quality standards for E.coli, as well as other contaminants of
concern, are independently established by states and tribes as the baseline water
quality needed for rivers and streams to meet their designated use (USEPA, 2023). This
analysis is done by states and tribes on each of their individual Assessment Units (AU),
or individual reaches of rivers and streams as determined by the respective regulating
agency. AUs that are found to exceed their water quality standard during routine
sampling are identified as impaired and included in state and tribal government CWA
Section 303(d) reports to the USEPA to be prioritized for watershed restoration planning
and implementation.
E. coli in the San Juan Watershed
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Jurisdiction Number
of AUs¹
Designated
Recreation
Use for E.coli Single
Sample Max
(MPN/100 mL)
E.coli Geometric
Monthly Mean
(MPN/100 mL)
CDPHE 39
Primary Contact – 126
Not Primary Contact – 205
Potential
Contact
Primary – 630
NNEPA 4
Primary Contact 235 126
Secondary Contact 575 126
NMED SWQB 10 Primary Contact 410 126
SUIT 19 Primary
Contact
and Secondary 410 126
Ute 14
Primary Contact 235 126
Secondary Contact 1,152 –
UTDWQ 4
Domestic Source 668 206
Primary Contact 409 126

Based on the review of surface water quality standard documentation for CDPHE, SUIT,
Ute, NMED-SWQB, NNEPA, and UTDWQ, there are approximately 90 individual AUs
within the Watershed. Each AU has its own designated use and water quality standard.
All jurisdictions, excluding CDPHE which does not have a single sample standard, have
an E.coli water quality standard for both a single sample and for a geometric monthly
mean of at least 4 individual samples taken from the same AU within a 30 day timespan.
As summarized below in Table 1, different jurisdictions have adopted numerical water
quality standards for E.coli based on factors specific to the jurisdiction, AU, designated
use, and calculation method. A more detailed summary of each individual AU is
available in Appendix A.
Table 1: Assessment Units, Designated Uses, and E.coli Water Quality
Standards per Jurisdiction
¹With recreation designated use and within the Watershed.
Considering the varied water quality standards being used within the Watershed and
the WIIN Act Group’s goal of conducting a multijurisdictional water quality analysis, the
USEPA’s Recreation Water Quality Criteria (RWQC) of 410 cfu/100 mL for a single
sample maximum and 126 cfu/100 mL geometric monthly mean was adapted for this
analysis. This standard was established as the calculated threshold where 36 out of
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1,000 swimmers would become ill with a gastrointestinal illness if the water were
ingested and has been adapted by some states and tribes in their monitoring program.
As discussed in Section 3.1, E.coli quantification is reported in Colony Forming Units
(cfu)/100 mL and Most Probable Number (MPN)/100 mL depending on the laboratory
method used (visible colony count or statistical estimation). Both units provide
comparable values for bacteria quantification. Therefore, these units are also used
interchangeably in this report.
2.0 Methods
2.1 Data Sources
The initial inventory of potential data sources and acquisition of data was completed by
the San Juan Soil & Water Conservation District (San Juan SWCD) in 2022. Entities
collecting E.coli data from drinking water and groundwater were not included in the call
for data for this project focusing on surface water quality. During this initial data
collection phase, entities who were known or suspected of having bacteriological data
were identified from a review of regulatory agencies required to conduct water quality
monitoring and watershed plans addressing E.coli concerns. Each entity or agency was
individually contacted by the San Juan SWCD to discuss data availability and the purpose
and scope of the project. Several entities and agencies recommended downloading
bacteriological data from the USEPA Water Quality Portal (WQP), a USEPA and U.S.
Geological Survey (USGS) operated publicly accessible portal of federal, state, and tribal
water quality data. A batch download from the WQP of all available bacteriological data
within the Watershed was completed by San Juan SWCD on February 24-25, 2022.
These entities include, but are not limited to, those identified in Table 2, and a list of
parameters used to query the database for water quality data specific to the purposes
of this analysis is available in Appendix B.
Table 2: Data Sources, Availability, and Inclusion into Dataset
Entity
Federal
National Park Service
(NPS) Water Resources
Division (WRD)
USGS
State
Data Source /
Availability
WQP Download
WQP Download
Data
Available
2005
2004-2022
Years of Data
Included
2005
2004-2021
Number of
E.coli Results
7
86
CDPHE WQP Download 2004-2020 2004-2020 676
E. coli in the San Juan Watershed
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Entity Data Source /
Availability
Data Years of Data
Available Included
Number of
E.coli Results
NMED SWQB WQP Download 2005, 2010, 2005, 2010,
2017, and 2018 2017, and 2018 383
UTDWQ WQP Download,
Internal Database 2012-2021 2012-2021 299
Tribal
NNEPA WQP Download,
Internal Database 1995-2005 2004-2005 0¹
SUIT WQP Download 2009-2020 2009-2020 542
Ute WQP Download,
Internal Database 2004-2021 2004-2018 276
Other Agencies
Animas Watershed
Partnership (AWP) WQP Download 2015 2015 60
San Juan Watershed
Group (SJWG) Internal Database
2002-2008,
2013-2014,
2016, 2021
2004-2008,
2013-2014,
2021
546
¹Data provided was for Fecal Coliform only.
A complete list of the entities that provided data but which did not meet quality
assurance criteria; provided data outside of the timeframe used for this analysis;
required additional follow up to confirm data availability; or confirmed data availability
but additional coordination is required, is provided in Appendix C.
2.2 Data Quality Assurance
The data exported from the WQP revealed that harmful pathogens and fecal indicator
bacteria, such as E.coli, total coliform, fecal coliform, cryptosporidium, enterococcus,
giardia, and iron reducing, slime forming, and sulfate reducing bacteria, have been
sampled and uploaded by various agencies and entities to the WQP since 1968. A total
of 11,540 individual sample results for these bacterium types spanning over 538 sample
locations within the San Juan Watershed were included in the data set.
Considering the volume and timescale of this data, as well as the purpose of the project
to analyze data using current water quality standards, AES and UTDWQ prioritized
analyzing E.coli data collected from the earliest year that state and tribal jurisdictions
within the Watershed transitioned from fecal coliform to E.coli for their water quality
standard. According to their respective Monitoring Program Managers, E.coli became
the water quality standard for the Navajo Nation and Utah in 2004, 2005 for New
Mexico, and 2006 for Colorado. Therefore, all E.coli data between 2004 and 2021 were
E. coli in the San Juan Watershed
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included for data quality assurance and consolidation. While E.coli was prioritized for
analysis, fecal coliform, as a previous water quality standard for recreation, and total
coliform, as a companion result in most laboratory reports quantifying E.coli, were
retained in the combined dataset along with available MST data for potential source
identification, within the project timespan of 2004 to 2021.
Projects that include modeling, geospatial information, analysis of existing information,
and collection of new information (i.e. sampling) and are supported by USEPA are
required to have a certified Quality Assurance Project Plan (QAPP). A QAPP succinctly
summarizes the operations, technical activities, and quality assurance and quality
controls (QA/QC) procedures that will be implemented throughout a project (USEPA,
2002). A secondary data QAPP for existing data was developed for this project and
approved by UTDWQ on September 19, 2023, and is available in Appendix D.
To ensure the quality of E.coli data, results from sampling that were conducted under a
USEPA approved QAPP for either project based sampling and/or in a federal, state, tribal
program management plan, were included in the analysis. Copies of the individual
QAPPs for data sources included in the analysis are available in the project QAPP and
upon request. To ensure comparability of results, datasets were limited to E.coli
measurements that were completed in a laboratory using comparable methods that
have been approved by USEPA by a validation study process and/or are listed in CFR 40
Part 136, Guidelines Establishing Test Procedures for the Analysis of Pollutants. In
addition, all complete datasets received were required to have the following minimum
metadata or context provided in the dataset or by the entity:
Bacteria Type
Sample Location ID/Name
Sample Location Type
Sampling Start Date and Time
Sample Location Coordinates (decimal degrees)
Sample Media
Sample Collection Method
Result Measure Value
Laboratory Method
Detection Quantification Limit
2.3 Data Consolidation
Eight datasets met the QA/QC criteria and was subjected to a thorough consolidation
process to ensure that the integrity of the metadata remained intact for each individual
sampling result. Each entity or agency initially used a unique excel template to manage
their data, with different field types, cell formats, terminology, order of progression, and
E. coli in the San Juan Watershed
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supplemental parameters beyond the minimum metadata required. The WQP batch
download itself was an aggregation of multiple dataset formats that was used by each
entity to submit the data. Accumulatively there were many duplicate fields (ie.
columns) for the same parameter within the WQP database. Before any analysis could
occur, all data needed to be mapped, consolidated, and scrubbed to a single combined
dataset.
2.3.1 Data Mapping
As part of preliminary data mapping, each field within each dataset was reviewed to
document their contents, terminology, comparability between datasets, and
significance in relation to the purposes of the project. These observations, combined
with the minimum metadata required in this project’s QAPP, were used to develop the
template for the combined dataset. This data mapping exercise identified and
confirmed each field that would populate this template from each dataset.
2.3.2 Merging Datasets
The MS Access Append Query, an action query that allows records from one table to be
added to another, was used to combine the datasets one at a time using the data
mapping described above. The combined dataset was exported back to excel and
underwent four consecutive rounds of QA/QC evaluation and Update Queries in MS
Access to ensure that the integrity of the data remained intact.
2.3.3 Data Scrubbing
Once the datasets were merged, the combined dataset was scrubbed, or cleaned and
organized, to prepare for analysis. Best management practices used during the data
scrubbing process included periodic backups, documentation of edits done to each
individual entry as they occurred, and opportunities for review by UTDWQ as the
consolidation process proceeded. Examples of data scrubbing include, but are not
limited to, the following:
Removed data entries that were identified as quality control blanks, duplicates,
replicates, and not analyzed;
Removed bacteria types other than E.coli, fecal coliform, total coliform, and
MST;
Removed any sample locations and associated results that did not have geo-
locational coordinates;
Standardizing terminology for bacteria types, laboratory methods, units,
jurisdiction names, and results above or below quantification limits;
Substituted blank entries with metadata based on confirmation with
stakeholders and/or project reports. All remaining blank entries where
confirmation was not viable were substituted with “N/A” (not available);
Standardized formats for number cells such as dates and times;
E. coli in the San Juan Watershed
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Populated HUC8 Watershed and Waterway metadata specific to the sampling
location using GIS software;
All result units for E.coli, total coliform, and fecal coliform originally identified as
cfu/100 mL were substituted to MPN/100 mL;
Consolidated sample location IDs or names for identical coordinates that were
differentiated by grammar or syntax; and
Populated a separate Analysis Result field for results that were above or below
quantification limits for statistical analysis;
o “Present above Quantification” was substituted for 2,420 MPN/100mL, as
2,419.6 MPN/100 mL is the quantification limit for most laboratory
methods for E.coli.
o “Present below Quantification” was substituted for 1 MPN/100mL.
The combined dataset, data mapping exercise and pre- and post-consolidation notes are
provided in Appendix E.
2.4 Assumptions
During the data consolidation and scrubbing process, the following assumptions were
made:
Sampling locations with different names and similar, but not exact, coordinates
were assumed to be individual sampling locations;
Data collected under a QAPP and/or submitted through the WQP were assumed
to: 1) have not exceeded sample holding times; 2) be representative of water
quality conditions at the time of collection; and 3) have been collected by trained
personnel familiar with appropriate standard operating procedures;
AES assumed that while attempts were made to obtain all reasonably available
data, there were most likely additional data sources that were not identified
within the project timeline. These potential data sources can be more closely
investigated in future phases of work.
E. coli in the San Juan Watershed
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3.0 Data Characterization
3.1 Bacteria Types and Laboratory Analytical Methods
A total of 5,706 reported results for Graph 2: Bacteria and MST Results E.coli, total coliform, fecal coliform, within Combined Dataset and different MST DNA markers were
included in the combined dataset. The (2004-2021)
results that comprised the dataset are 1,011 (18%) depicted in Graph 2.
75 (1%) The majority of total coliform results
were reported with E.coli results, as it 2,875 (50%) is standard to report both when using
E.coli culture based laboratory methods such
Total Coliform as USEPA Standard Method (SM) 9223 1,745 (31%)
and Colilert. Additional detail on MST Fecal Coliform
data collected in the Watershed to MST
date is available in Section 3.6.
All E.coli, total coliform, and fecal coliform results were quantified using laboratory
methods approved by the USEPA under 40 CFR 136, including Colilert, Colilert-18,
ColiBlue24, SM 9223-B, SM 9222-D, SM 1106.1, and SM 9221-B, C, E, and F. The
majority of these methods, excluding ColiBlue24, SM 9222-D, and SM 1106.1, utilize the
multiple tube/multiple well approach that statistically estimates the presence of
bacteria through a fluorescence producing chemical reagent. Bacteria quantification is
expressed in units of MPN/100 mL using this approach. The ColiBlue24, SM 9222-D, and
SM 1106.1 methods utilize membrane filtration, where samples are filtered through
culture media, incubated, and the number of visible colonies are counted. Bacteria
quantification is expressed in units of cfu/100 mL using this approach (Wisconsin
Department of Natural Resources, 2020).
Both methods are living culture based quantification methods and have been used
interchangeably by entities and agencies monitoring for exceedances of the recreation
water quality standard based on the water quality standard at the time of sampling and
the availability of laboratory equipment and/or trained staff. Considering the
comparable laboratory methods used to produce the combined dataset, no E.coli data
were removed based on the laboratory method used. Details on the laboratory
method, bacteria quantified, and year used by each entity are provided in Table 3.
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Entity Laboratory Method Bacteria Measured Year(s) Used
Federal
NPS WRD USGS Fecal Indicator
Bacteria 7.1 (Colilert) E.coli 2005
E.coli, Total
USGS Colilert Coliform, Fecal 2004-2011
Coliform
State
CDPHE
USEPA SM 9221-B E.coli 2004-2006
ColiBlue24 E.coli 2009-2010
USEPA SM 9221-E Fecal Coliform 2005
USEPA SM 9223-B E.coli, Total Coliform 2004-2012,
2017, 2020
2014, 2015,
NMED SWQB
USEPA SM 9222-D Fecal Coliform 2005
Colilert E.coli, Total Coliform 2010
Colilert/2000 Comparator E.coli, Total Coliform 2017-2018
Colilert-18 E.coli, Total Coliform 2017-2018
UTDWQ Colilert E.coli, Total Coliform 2012, 2014, 2017-2021
Colilert-18 E.coli, Total Coliform 2019
Tribal
NNEPA USEPA SM 9222-D Fecal Coliform 2004-2005
SUIT USEPA SM 9223-B E.coli, Total Coliform 2009-2020
Ute
USEPA SM 1106.1 E.coli, Total Coliform 2005-2006, 2008
USEPA SM 9221-B Total Coliform 2005
USEPA SM 9221-C Fecal Coliform,
Coliform
Total 2005
USEPA SM 9221-E Total Coliform 2005
USEPA SM 9221-F Fecal Coliform 2005
Colilert E.coli, Total Coliform 2016-2018
Colilert/2000 Comparator E.coli, Total Coliform 2004, 2005, 2009-2015
Other Agencies
SJWG Colilert E.coli, Total Coliform 2004-2008
SJWG USEPA SM 9223-B E.coli, Total Coliform 2013-2014
AWP Colilert-18 E.coli, Total Coliform 2015

Table 3: Laboratory Method, Bacteria Measured, and Year(s) Used by Entity
3.2 Sample Location Density
The combined dataset encompasses a total of 410 sample locations for all E.coli, total
coliform, fecal coliform, and MST results. Sample locations reflect a general trend of
higher density within the middle and upper portions of the Watershed in Colorado and
E. coli in the San Juan Watershed
p. 12

--
New Mexico. Five Sub-Watersheds, including the Upper San Juan, Animas, Middle San
Juan, Mancos, and McElmo, have 25 or more sample locations and the highest sample
location density ranging between 10,690 and 19,606 acres per sample location. The
Piedra Sub-Watershed, with a total of 15 sampling locations, has the middle range
sample location density at 28,859 acres per sample location. In contrast, the Chaco
(fecal coliform only), Chinle, Montezuma, Lower San Juan - Four Corners, and Blanco
Sub-Watersheds have less than or equal to 10 sample locations, with the lowest sample
location density ranging between 109,687 and 1,463,568 acres per sample location.
Additional details on the number of sample locations, sample location density, and
associated entities and agencies for each Sub-Watershed are provided in Table 4.
Sample locations are displayed in Figure 2.
Table 4: Sample Location Density per Sub-Watershed
Sub Sub
Watershed Watershed
Name HUC ID
Total
Acres¹
Number of
Waterways
Sampled
Number of
Sample
Locations
Entities
Conducting
Sampling
Sample
Location
Density²
Upper 14080101 San Juan 2,195,833 26 113
SJWG, CDPHE,
USGS, SUIT,
NMED SWQB
19,606
Piedra 14080102 432,886 7 15 CDPHE, SUIT 28,859
Blanco 14080103 1,096,869 4 10 SJWG 109,687
Animas 14080104 876,590 27 82
SJWG, AWP,
CDPHE, NMED
SWQB, SUIT,
USGS
10,690
Middle 14080105 San Juan 1,244,785 10 102
SJWG, CDPHE,
NMED SWQB,
SUIT, USGS
12,204
Chaco 14080106 2,927,137 23 23 NNEPA 1,463,568
Mancos 14080107 513,247 16 38 CDPHE, Ute 13,872
Lower San
Juan - Four 14080201
Corners
1,276,408 7 9 UTDWQ, Ute 141,823
McElmo 14080202 458,852 13 28 CDPHE,
UTDWQ, Ute 16,388
Montezuma 14080203 748,156 1 1 Ute 748,156
Chinle 14080204 2,623,452 2 9 NPS WRD,
NNEPA 291,495
Lower 14080205 San Juan 1,561,147 1 4 UTDWQ 390,2867
TOTAL 15,955,361 117 410
¹Projection used to calculate acreage was EPSG 4269: NAD83.
E. coli in the San Juan Watershed
p. 13

²Provided in number of samples per acre.
3All sample locations and results are for fecal coliform.
A total of 117 waterways, including rivers, streams, arroyos, lakes, reservoirs, ponds,
springs, irrigation ditches, and municipal contributions, have been sampled throughout
the Watershed and included in this analysis. The results for sample locations designated
as municipal waste from their data source were retained in the analysis under the
recognition that these types of sample locations cannot be identified in the other data
sources. Sample locations noted as municipal waste in their data source were
designated as their own waterway to keep them separated as such separate (ie. Aztec
WWTP, Farmington WWTP, etc). Each of the following Sub-Watersheds have waterways
with four or more sample locations:
Upper San Juan: Los Pinos River (7), Navajo Reservoir (4), San Juan River (66),
Spring Creek (4), and Vallecito Reservoir (4);
Piedra: Piedra River (6);
Blanco: Canyon Largo (6);
Animas: Animas River (34), Florida River (7), Lemon Reservoir (4), Salt Creek (5)
Middle San Juan: La Plata River (14), San Juan River (61), Shumway Arroyo (8),
Stevens Arroyo (12);
Mancos: Mancos River (14); Navajo Wash (6);
Lower San Juan - Four Corners: None;
McElmo: McElmo Creek (10), Narraguinnep Reservoir (4);
Chinle: Tsaile Lake (4); and
Lower San Juan: San Juan River (4).
A table summarizing the number of sample locations for each waterway per Sub-
Watershed is provided in Appendix F.
3.3 E.coli Results over the Federal Water Quality Standard
As stated in Section 1.4, the USEPA RWQC single sample maximum of 410 cfu/100 mL
was adapted for this project. Of the 2,875 E.coli samples that were included in the
combined dataset, 17% were at or above the USEPA RWQC (487 results). Of the 12 Sub-
Watersheds, there was a wide range of the number of samples collected and a wide
range of E.coli concentrations. Nine out of the 12 Sub-Watersheds had reported at 1 or
more of the highest E.coli concentrations at the upper quantification limit of 2,420
cfu/100 mL. A summary of the number of samples collected, above the USEPA RWQC,
and maximum concentration is provided in Table 5 is presented below.
E. coli in the San Juan Watershed
p. 14

--
--
Table 5 Total Number of E.coli Samples Collected, Above the USEPA RWQC,
and Maximum Concentration per Sub-Watershed
Sub Sub Watershed Watershed Name HUC ID
Number
of E.coli
Results
Number of
E.coli Results
over USEPA
RWQC
Maximum
Concentration
(MPN/100 mL)
Upper San Juan 14080101 684 117 2420
Piedra 14080102 144 12 2420
Blanco 14080103 11 11 2420
Animas 14080104 779 88 2420
Middle San Juan 14080105 478 128 2420
Mancos 14080107 278 45 2420
Lower San Juan -14080201 Four Corners 162 33 2420
McElmo 14080202 186 29 2420
Montezuma 14080203 1 0 248.1
Chinle 14080204 7 0 280
Lower San Juan 14080205 145 24 2420
GRAND TOTAL 2875 487 --
Note that the combined dataset included in this study did not provide detailed
information on the types of sample locations included and the objective of the sampling
program (i.e. high-bias sampling). It also did not include information on the conditions
under which the samples were collected (e.g. steady perennial flow, first flush of
stormwater in an intermittent stream, weather, etc.). Therefore, while the frequency of
exceedances and maximum values provide initial insight about E.coli in the Sub-
Watershed, no extensive conclusions should be extrapolated.
The disparity between the percentage of exceedances within a single Sub-Watershed
compared to exceedances within the entire Watershed reflects the uneven distribution
of frequency of sampling and also the number of waterways sampled within a Sub-
Watershed. The percentages of E.coli results above RWQC both within the Sub-
Watershed and within the entire Watershed are summarized in Table 6.
Table 6 E.coli Results over the USEPA RWQC per Sub-Watershed
Sub Watershed
Name
Upper San Juan
Piedra
Sub
Watershed
HUC ID
14080101
14080102
Number of
Waterways
Sampled for
E.coli
26
7
Total
E.coli
Results
686
144
E.coli
Results
Over USEPA
RWQC
117
12
% E.coli Results
Over USEPA
RWQC
(SubWatershed)
17%
8%
% E.coli
Results Over
USEPA RWQC
(Watershed)
4.1%
0.4%
Blanco 14080103 4 11 11 100% 0.4%
E. coli in the San Juan Watershed
p. 15

--Sub Sub Watershed Watershed Name HUC ID
Number of
Waterways
Sampled for
E.coli
Total
E.coli
Results
E.coli
Results
Over USEPA
RWQC
% E.coli Results
Over USEPA
RWQC
(SubWatershed)
% E.coli
Results Over
USEPA RWQC
(Watershed)
Animas 14080104 27 781 88 11% 3.1%
Middle San Juan 14080105 10 474 128 27% 4.5%
Chaco 14080106 01 01 01 --0%
Mancos 14080107 16 278 45 16% 1.6%
Lower San Juan 14080201 - Four Corners 7 162 33 20% 1.1%
McElmo 14080202 13 186 29 16% 1.0%
Montezuma 14080203 1 1 0 0% 0%
Chinle 14080204 2 7 0 0% 0%
Lower San Juan 14080205 1 145 24 17% 0.8%
TOTAL 114 2,875 487 --17%
1Samples were only for Fecal Coliform.
Of note, both Montezuma (1 result from 1 waterway) and Chinle (7 results from 2
waterways) Sub-Watersheds had no E.coli results over the USEPA RWQC; however,
these datasets are extremely limited in sample size. The Chaco Sub-Watershed has not
been sampled for E.coli according to the combined dataset; instead it has only been
sampled for Fecal Coliform by the NNEPA. All E.coli results and results over the USEPA
RWQC throughout the Watershed are also provided in Figure 3. Maps showing total
E.coli results and results over the USEPA RWQC for each individual Sub-Watershed,
excluding Chaco, are provided in Figures 4 through 10. Graphs summarizing the ratio of
E.coli samples over the USEPA RWQC to the total number of samples is available for all
waterways per Sub-Watershed and the entire Watershed in Appendix G.
3.4 Temporal Distribution
Sub-Watersheds have been sampled for E.coli on various dates and seasons within a
year and from one year to the next. Time-series scatter plots from 2004 through 2021
showing total sample count and samples exceeding the USEPA RWQC vs. time have
been prepared for Sub-Watersheds with adequate temporal distribution of data
including multiple seasons in year for more than one year. The graphs show collective
Sub-Watershed counts as a preliminary evaluation of seasonal trends (if any) of E.coli
results over the USEPA RWQC. Note that Blanco (sampled only in September 2004 and
October 2006), Montezuma (sampled May 2014), and Chinle (sampled April, May, and
October 2005) were omitted from graphs because the Sub-Watershed datasets were
limited. The time series scatter plots displaying the number of E.coli sampling results
under and over the USEPA RWQC over time for each Sub-Watershed is presented in
Appendix H.
E. coli in the San Juan Watershed
p. 16

While not consistent for all Sub-Watersheds, the annual occurrence of E.coli results over
the USEPA RWQC appeared to be more prevalent between May and October based on
currently available data. The greatest number of occurrences of E.coli concentrations
over the USEPA RWQC for each Sub-Watershed was between July and September,
which coincides with the average monsoon season for the Watershed (Wester Regional
Climate Center, 2016). This correlation could be associated with a variety of factors,
including stormwater flows, E.coli’s ability to attach to and be transported by sediment,
high growth and survival rates in warmer temperatures, and less dilution during lower
flows (Chen & Chang, 2014). This trend is depicted in Graph 3.
Graph 3: Seasonal Variation in Total E.coli Results and E.coli Results Over
USEPA RWQC by Sub-Watershed
E. coli in the San Juan Watershed
p. 17

While this preliminary analysis indicates a possible correlation between E.coli
concentrations over the USEPA RWQC and the summer monsoon season within the
Watershed, future analysis on an updated dataset is recommended to better evaluate
this potential correlation.
3.5 Preliminary Statistical Analysis
An initial statistical analysis was conducted for all Sub-Watershed waterways that met
the minimum sample size required for a meaningful statistical evaluation (n=10). E.coli
results, including all sample locations and dates and times of collection, were
aggregated into a collective sample size (n) per waterway. A minimum n of 10
independent results was adapted as the threshold for a meaningful statistical analysis.
This sample size criterion was defined in consultation with UTDWQ as the minimum
sample size that UTDWQ uses to assess impairments for AUs within their jurisdiction.
In order to prepare for preliminary recommendations on further analysis, monitoring,
and/or watershed planning, the following initial statistical analysis was implemented for
each waterway that has the minimum sample size (Barnett, 2004):
Minimum;
First quartile (Q1);
Median (Q2);
Third quartile (Q3);
Maximum;
Upper outlier limit;
Range;
Standard deviation; and
Outliers, which were not removed from the dataset for this preliminary
statistical analysis.
The list of 38 waterways and the statistical analysis results are provided in Appendix J.
3.5.1 Waterways with No RWQC Exceedances
Of the 117 waterways, only 38 waterways within eight Sub-Watersheds met the
minimum sample size (n=10) for a preliminary statistical analysis. Of these, seven
waterways within three Sub-Watersheds had no E.coli results over the USEPA RWQC:
Animas: Cascade Creek and Lemon Reservoir.
McElmo: Hanna Spring, Little Ruin Canyon, and Narraquinnep Reservoir; and
Upper San Juan: Vallecito Creek and Vallecito Reservoir.
E. coli in the San Juan Watershed
p. 18

While there were no exceedances in these waterways over the RWQC, there were also
no detectable E.coli concentrations in Vallecito Reservoir, Lemon Reservoir, and
Narraquinnep Reservoir. Accordingly, the calculated outlier upper limits are 1 cfu/100
mL, and the standard deviations for these waterways are 0. In contrast, Vallecito Creek,
Cascade Creek, Hanna Spring, and Little Ruin Canyon had low reportable E.coli
concentrations, with the maximum concentration reported in Little Ruin Canyon with
172 cfu/100 mL. Similarly, the outlier upper limits ranged from 7 to 75 cfu/100 mL, and
standard deviations for these waterways ranged from 3 to 42 cfu/100 mL.
3.5.2 Waterways with USEPA RWQC Exceedances
A total of 31 out of 38 waterways meeting the minimum sample size (n=10) had one or
more exceedances over the USEPA RWQC. Of these, 13 waterways within five Sub-
Watersheds had maximum concentrations that were below the quantification limit of
2,420 cfu/100 mL ranging from 435 and 1,553 cfu/100 mL. Of this set of waterways, the
calculated outlier upper limits ranged between 14 cfu/100 mL and 1600 cfu/100 mL.
These 13 waterways had between 0% and 21% of their concentrations over the upper
outlier limits (ie. were outliers). The standard deviations of each of these waterways
ranged from 105 to 409 cfu/100 mL. The Sub-Watershed and 13 waterways that had
one or more exceedance over the USEPA RWQC and below the quantification limit are:
Animas: Junction Creek
McElmo: Hartman Draw
Middle San Juan: Cherry Creek
Piedra: Capote Lake, Piedra River
Upper San Juan: Navajo Reservoir, Los Pinos River, Rio Blanco, Sambrito Creek,
Ute Creek, Beaver Creek, Dry Creek, and Spring Creek
Out of the 38 waterways that met the minimum sample size (n=10), 18 (47%) of them
had one or more concentrations at the 2,420 cfu/100 mL quantification limit. These
maximum concentrations may indicate ongoing sources, first flush concentration
impacts from stormwater, or a combination thereof. Sub-Watersheds with waterways
that had E.coli concentrations that met the 2,420 cfu/100 mL quantification threshold
are:
Animas: Animas River, Florida River, Salt Creek
Lower San Juan: San Juan River
Lower San Juan -Four Corners: San Juan River
Mancos: Navajo Wash, Mancos River
McElmo: Mud Creek, McElmo Creek
E. coli in the San Juan Watershed
p. 19

Middle San Juan: La Plata River, San Juan River, Shumway Arroyo, and Stevens
Arroyo
Piedra: Stollsteimer Creek
Upper San Juan: Navajo River, San Juan River, Rock Creek, and Ignacio Creek
Of interest, three of these waterways, Shumway Arroyo and Stevens Arroyo in the
Middle San Juan and Ignacio Creek in the Upper San Juan, had E.coli concentrations
above the RWQC more than 50% of the time. The calculated outlier upper limits in
these waterways ranged from 2,707 cfu/100 mL (Stevens Arroyo) up to 3,811 cfu/100
mL (Shumway Arroyo). Standard deviations for these three waterways were also the
highest calculated, with 813, 823 and 960 cfu/100 mL, respectively.
For the other 15 waterways that had E.coli results that met the upper quantification
limit of 2,420 cfu/100 mL but had calculated outlier upper limits that were below the
quantification limit, the range of outlier upper limits were between 254 cfu/100 mL
(Mancos River) and 1,651 cfu/100 mL (Salt Creek). Two outlier upper limits were
calculated to be below the RWQC of 410 cfu/100 mL, with 254 cfu/100 mL (Mancos
River) and 241 cfu/100 mL (La Plata River). All of the remaining outlier upper limits
were above the RWQC but below the quantification limit of 2,420 cfu/100 mL. Upper
limit outliers within this data set had outlier concentrations that ranged between 6%
and 17% of the sample size for each waterway. Standard deviations for this set of
waterways ranged from between 333 cfu/100 mL to 690 cfu/100 mL.
This range of standard deviations reaffirms that overall E.coli data sets were quite
variable over time for each waterway. This could be due to a variety of factors,
including but not limited to the source of E.coli, E.coli’s aerobic life cycle, ability to
attach to sediment particles, and positive correlation with stormwater flow.
3.6 Microbial Source Tracking (MST)
As previously stated in Section 1.2, as a bacteria found in the intestinal tract and fecal
waste of all mammals, E. coli cannot provide definitive links to sources of fecal pollution.
However, MST is a family of techniques used to determine the host organism(s), and
therefore environmental vectors, of fecal contamination. The DNA marker MST
approach uses Qualitative Polymerase Chain Reaction (qPCR) to pinpoint and quantify
specific mRNA sections that have been well established in the scientific community
(Harwood, Staley, Badgley, Borges, & Korajkic, 2013). Several DNA markers have been
developed to investigate host organism(s), including canine, ruminants (deer, elk, sheep,
and goats), birds, cattle, humans, and more.
While limited in comparison to the majority of E.coli sampling in the Watershed, MST
sampling has been conducted by the SJWG in the Animas, Upper San Juan, and Middle
E. coli in the San Juan Watershed
p. 20

San Juan Sub-Watersheds in 2013, 2014, 2016, and 2021. Note that MST results from
2016 were not included in the combined dataset as they were not collected under a
project QAPP.
3.6.1 San Juan Watershed Group (SJWG) MST Sampling, 2013 and 2014
The 2013 and 2014 MST sampling was done during the Animas and San Juan Concurrent
Nutrient and Bacteria Monitoring Project. This sampling study, supported by CWA
Section 604(b) grant funding through NMED-SWQB and other leveraged funds, was
designed to develop the Lower Animas Watershed Based Plan (LAWBP) and address the
history of nutrient and bacteria water quality impairments on the Animas River within
the Animas Sub-Watershed of New Mexico. Nutrient, E.coli, and MST water quality
samples were collected as part of this study, including MST samples for human (DNA
Markers HumM2, HF183, and HF183/BacR287), bird (DNA Marker GFD), cow (DNA
Marker CowM2), ruminant (DNA Marker Rum2Bac), and general bacteroides (DNA
Marker GenBac3). Samples were collected weekly between April and October during
both 2013 and 2015. Five sample locations were used in this study, including three
along the Animas River in the Animas Sub-Watershed and two along the San Juan River,
one above the confluence of the Animas River in the Upper San Juan Sub-Watershed
and one at the jurisdictional boundary of the Navajo Nation in the Middle San Juan Sub-
Watershed. The sample locations from this 2013 and 2014 sampling study are provided
in Figure 11.
3.6.2 SJWG 2013 and 2014 MST Sampling Results
The results of the 2013 and 2014 MST sampling showed that human and ruminant fecal
bacteria were more prevalent than any other hosts analyzed. Ruminant fecal bacteria
were detected in 94% of samples, and human fecal bacteria were detected in 77% of all
samples. The sample locations along the San Juan River had a greater number of
positive and quantifiable results for human sources than the Animas River sample
locations. Conclusions for the study included the following:
Based on the 2014 sampling results, the sample location on the San Juan River
near the jurisdictional boundary of the Navajo Nation had on average four times
higher concentrations of human source bacteria than the upriver San Juan River
sample location near Farmington, New Mexico.
For the sample locations on the Animas River, the sample location near the
Colorado/New Mexico state line had higher concentrations of human fecal
bacteria than the downriver sample locations.
Bird fecal bacteria was consistently present at all sample locations.
Canine and horse fecal bacteria were not detected or present below the
quantification limit for all results (May, 2014).
E. coli in the San Juan Watershed
p. 21

The findings from the 2013 and 2014 Animas and San Juan Concurrent Nutrient and
Bacteria Monitoring Project were adapted into the 2016 LAWBP, which proposed and
documented the progress of various projects that would improve surface water quality
as a whole, including but not limited to wastewater infrastructure management,
agriculture best management practices, and riparian restoration. Many of these
projects are in progress or have been completed (SJWG, 2021).
3.6.3 SJWG MST Sampling, 2021
The 2021 San Juan Human Bacteria Sampling and Investigation Study was a follow up
sampling to the 2013 and 2014 study specific to human DNA marker HF183. In contrast
to the fewer sample locations and high frequency of sampling in the 2013 and 2014
study, the 2021 MST sampling was designed to sample from 17 locations once a month
between August and October and to identify potential hotspots of human fecal
pollution. Sample locations included the same two sample locations on the San Juan
River utilized in the 2013 and 2014 study, eight additional locations on the San Juan
River (one being effluent discharge from the Bloomfield WWTP) in the Upper San Juan
Sub-Watershed, two locations on the San Juan River in the Middle San Juan Watershed
(one being the effluent discharge from the Farmington WWTP), one of the same sample
locations on the Animas River used in the 2013 and 2014 study, and one location each
on the La Plata River, Shumway Arroyo, and Stevens Arroyo in the Middle San Juan Sub-
Watershed. The sample locations from this 2021 study are provided in Figure 11.
3.6.4 SJWG 2021 MST Sampling Results
Based on the MST sampling results from the 2021 study, the quantity of human fecal
pollution was still present but significantly less in comparison to the results of the 2013
and 2014 study, indicating progress in reducing vectors of human fecal waste in this
reach of the Watershed. Almost half of the MST results that had no detections for
human source bacteria had accompanying E.coli results over the USEPA RWQC,
indicating fecal waste from other host organisms were present but not sampled for,
such as ruminant, bird, or other sources (Richmond, 2022). A summary of MST hosts
and DNA markers that have been sampled in the Watershed by the SJWG is provided in
Graph 3.
E. coli in the San Juan Watershed
p. 22

308 (30%)
108 (11%) 193 (19%)
Results from the MST studies have Graph 4: Count of MST DNA Markers provided a template for creating a in MST Dataset (2013, 2014, 2021) baseline dataset of fecal bacteria host
identification, incorporating these 40 (4%) 22 (2%) results into a watershed-based
mitigation plan, and improving water
quality over time in relation to human 212 (21%)
fecal waste. MST sampling specifically
tailored to Sub-Watershed land use is
recommended in reaches of the
Watershed that show trends of
chronic exceedances over the USEPA
RWQC.
Additional details on the SJWG studies 128 (13%) are available in the project reports and
General (GenBac3) associated presentations available on
Human (HF183/BacR287) the San Juan SWCD website. The
Human (HumM2) sample locations used for 2013, 2014,
Human (HF183) and 2021 sampling are provided in
Ruminant (Rum2Bac) Figure 11. A table summarizing the
Cow (CowM2) MST DNA markers, hosts, waterways
Bird (GFD) sampled, number of samples, sample
locations and years sampled, and
results is provided in Appendix K.
3.7 Land Use and Land Cover
At this project’s current scale, sources of fecal contamination to surface waters cannot
be definitively identified. However, a preliminary land use and land cover analysis has
been conducted as an initial step to identify and recommend pathways for future
implementation to reach this goal. These recommendations should be considered both
during the prioritizing of a targeted multi-jurisdictional and E.coli monitoring program
and watershed planning efforts.
The factors identified as part of the land use and cover analysis were based on
hypothesized potential vectors as defined by the LAWBP (SJWG, 2021). The following
potential vectors for fecal bacteria in the Watershed are tentatively identified as:
Untreated or undertreated WWTP effluent;
Faulty or improperly installed on-site liquid waste systems;
Illegal dumping of human waste;
E. coli in the San Juan Watershed
p. 23

Irrigated pasture land;
Upland cattle grazing;
Urban development;
Outdoor defecation (camping and/or homeless populations); and
Wildlife habitat.
A preliminary identification of urban development, WWTP infrastructure, and irrigated
pastures has been included as part of this analysis. The remaining potential vectors are
recommended to be further investigated as needed in future phases of work.
3.7.1 Urban Development
Developed areas, combined with their higher human population densities and greater
areas of impervious surfaces, have a high correlation of contributing pollutants to
surface water. The more developed a community is with impervious surfaces in
conjunction with minimal low impact and green infrastructure, the more likely that
surface water quality will be negatively impacted. Potential sources of E.coli in urban
developed environments are human and pet (canine) waste.
According to 2023 U.S. Census Bureau, there are a total of 93 communities within the
Watershed, 14 of them being incorporated cities and/or towns, while the remaining 79
are unincorporated. Cities and towns within the Watershed include:
Colorado: Bayfield, Ignacio, Silverton, Durango, Pagosa Springs, Cortez, and
Mancos;
New Mexico: Farmington, Bloomfield, Aztec, and Kirtland; and
Utah: Bluff and Monticello.
The populations from these incorporated communities range from 600 in Silverton,
Colorado up to approximately 46,000 in Farmington, New Mexico (U.S. Census Bureau,
2020). Considering the approximately 16 million acres that comprise the Watershed,
this is a proportionately small ratio of incorporated communities to overall land mass.
According to the 2021 Multi-Resolution Land Characteristics Consortium (MRLC) 2021
National Land Use Land Cover Dataset (NLCD), the only Sub-Watersheds that have any
percentage of urban development in comparison to the total size of the Sub-Watershed
are the Upper San Juan (1%), Animas (3%), Middle San Juan (1%), McElmo (1%), and
Montezuma (1%) Sub-Watersheds. Incorporated communities and the 2021 NLCD for
the Watershed are displayed in Figure 12. A table detailing the percentage of land use
and land cover for both the anthropogenic and natural environment for each Sub-
Watershed is included in Appendix L.
The majority of the cities and towns listed have had their nearby waterways exhibit at
least one exceedance for E.coli over the USEPA RWQC, such as:
E. coli in the San Juan Watershed
p. 24

San Juan River passing through Farmington, New Mexico;
McElmo Creek near Cortez, Colorado; and
Los Pinos River near Ignacio, Colorado.
The majority of the unincorporated communities have not had nearby waterways
sampled. Noteworthy exceptions of waterways near unincorporated communities that
have been sampled and were found to have E.coli exceedances over the USEPA RWQC,
include the following:
Navajo Wash near Mancos, Colorado;
San Juan River between Bloomfield, Farmington, and Shiprock, New Mexico; and
La Plata River near La Plata, New Mexico.
Samples from these low population and unincorporated areas indicate potential E.coli
contributions from adjacent or upstream urban development.
A data gap recommended for investigation in future phases of work is an inventory of
Municipal Separate Storm Sewer System (MS4) permits within the Watershed.
Regulated under USEPA or state delegated NPDES programs, municipalities that meet
the threshold as a small or large MS4 system are required to monitor for illicit
discharges, routinely sample stormwater outfalls to navigable waterways, implement
pollution prevention best management practices, and conduct public education and
outreach. The information and data that may be available through MS4 permit
programs would further assist identifying potential sources of fecal pollution and
incorporate municipalities into the watershed monitoring and planning process.
3.7.2 Wastewater Treatment Infrastructure
In extension of potential vectors of fecal waste from human land use, untreated WWTP
effluent and faulty and/or improperly installed on-site liquid waste systems (ie. septic
systems and lagoons) can be the most direct route for human fecal contamination to
surface waterways. Both wastewater treatment infrastructure types are required to be
permitted either through a National Pollution Discharge Elimination System (NPDES)
permit for WWTPs or on-site liquid waste system permits in accordance with the
regulatory authority’s program. NPDES permits for WWTPs on tribal lands are managed
through USEPA Region 8 (Navajo Nation in Utah) and USEPA Region 9 (all other tribal
lands in the Watershed). On-site liquid waste systems on the Navajo Nation are
permitted through NNEPA. In New Mexico, NPDES permits for WWTPs are permitted
through USEPA Region 6, and on-site liquid waste systems are permitted through NMED
Environmental Health Bureau. Both NPDES permits for WWTPs and permits for on-site
liquid waste systems in Colorado are managed through CDPHE, a state delegated NPDES
program.
E. coli in the San Juan Watershed
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A preliminary inventory of permitted NPDES WWTP facilities was conducted to begin to
understand the geographic distribution of wastewater treatment infrastructure in the
Watershed. Permitted WWTPs are designed to mitigate human source pollution before
discharging effluent to waterways and when operating effectively are not sources of
human waste. However, knowing the distribution of permitted WWTPs and their
service area can be used to interpret developed areas that are primarily serviced by on-
site liquid waste systems. As identified in the LAWBP for the Animas River in New
Mexico permitting, maintenance, and proper design of on-site liquid waste systems are
an ongoing concern for NMED Environmental Health Bureau and septic professionals
(SJWG, 2021).
Thirty permitted WWTPs were identified in the Upper San Juan, Animas, Middle San
Juan, Mancos, McElmo, and Montezuma Sub-Watersheds. All these WWTPs are located
within the upper portions of the Watershed in Colorado and New Mexico. Based on this
inventory, the most downriver WWTP in the Watershed is based in Shiprock, New
Mexico, indicating that the majority, if not all, of the unincorporated and incorporated
communities in the Blanco, Chaco, Chinle, Lower San Juan – Four Corners, and Lower
San Juan Sub-Watersheds utilize on-site liquid waste systems. Incorporating MST for
human source bacteria into a monitoring program is recommended along waterways in
the lower Sub-Watersheds that have adjacent unincorporated communities and
exceedances in E.coli over the USEPA RWQC. The specific locations of WWTPs are
provided on Figure 12 and in Appendix M.
This permitted WWTP inventory was compiled by a review of publicly accessible online
federal and state NPDES lists managed by USEPA, CDPHE, and NMED in December 2023.
Further confirmation of this list with the respective regulatory agency is recommended.
In addition, acquiring geospatial data (shapefiles, Google Earth files, etc) of service lines
for each WWTP from their respective management is recommended to more accurately
define areas that are or are not serviced by on-site liquid waste systems.
3.7.3 Irrigated Pasture and Grazing
Agriculture is a primary land use for all the communities within the Watershed. San
Juan County, New Mexico, which is located within the Watershed in the northwest
corner of New Mexico, is comprised of 150,000 acres, or 10%, of the irrigated cropland
in the state. Irrigated pasture and dryland grazing of livestock, including cattle, sheep,
and goats, is part of the economy and was a key component of cultural identity for the
local community long before New Mexico became a state. In the Animas River Valley in
New Mexico alone, pasture is the most prevalent human land use in the riparian
corridor (SJWG, 2021). Proximity to a water source is one of the key factors in where
pasture or grazing operations are located, making irrigated pasture typically
E. coli in the San Juan Watershed
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concentrated near waterways and valley floodplains for ease of access to surface water.
Livestock grazing near waterways could be another primary source of E.coli
contamination within the Watershed.
Based on the 2021 NLCD, the following six Sub-Watershed have the following
approximate percentage and distribution of irrigated pasture and/or hay land use.
Upper San Juan: 2% concentrated along Beaver Creek and Los Pinos River near
Bayfield and Ignacio, Colorado, and along the San Juan River between Navajo
Reservoir and Farmington, New Mexico;
Piedra: 1% concentrated along the Piedra River and Weminuche Creek near the
unincorporated community of Piedra, Colorado;
Animas: 3% concentrated along the Florida River near its confluence with the
Animas River and along the Animas River between Durango, Colorado, and
Farmington, New Mexico;
Middle San Juan: 1% concentrated along the La Plata River near the
unincorporated community of La Plata, New Mexico, and along the San Juan
River between Farmington and Shiprock, New Mexico;
Mancos: 1% concentrated along the Mancos River and Navajo Wash near
Mancos, Colorado; and
McElmo: 3% concentrated along McElmo Creek near Cortez, Colorado.
The Blanco, Chaco, Lower San Juan – Four Corners, Montezuma, Chinle, and Lower San
Juan Sub-Watersheds do not have irrigated pasture documented in the NLCD.
Based on E.coli sample results, each of the waterways listed above have had
exceedances in E.coli over the USEPA RWQC, and many of them, such as the La Plata
River, San Juan River and Animas River in New Mexico have been listed as impaired by
the NMED-SWQB for primary recreation. Irrigated pasture and livestock grazing could
be potential sources of fecal contamination. Incorporating MST sampling for cattle and
other livestock along these reaches into an E.coli monitoring program is recommended
for further investigation.
An additional analysis that is recommended for a future phase of work is analyzing
upland grazing land use within the Watershed; this land use is not included in the 2021
NLCD. At this time, it is unknown what sources could have influenced the E.coli
exceedances over the USEPA RWQC at the sample locations in the Blanco Sub-
Watershed in 2004 and 2006. Rotational grazing of livestock in the dry uplands during
the winter season is common practice in this area. Analyzing the distribution and
grazing privileges of Bureau of Land Management (BLM) grazing allotments and grazing
permits on tribal land through the Navajo, Southern Ute, and Ute lands could provide
some additional context on potential sources from intermittent arroyos in the shrub
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scrub uplands of the Watershed. Irrigated pasture, as well as other land use types, are
provided in Figure 12 and summarized in Appendix K. Further evaluation and maps of
each Sub-Watershed and its land use is recommended for future phases of work.
3.8 Potential Factors Limited Sampling Frequency and Density
Density of sample locations and overall sampling frequency in the middle and upper
portions of the Watershed in Colorado and New Mexico are greater than in comparison
to the lower portions of the Watershed across the Navajo Nation and in Utah. The
Blanco, Chaco, Chinle, Montezuma, and Lower San Juan Sub-Watersheds have few
sample locations, if any, and sampling has generally not been done as frequently in
comparison to other Sub-Watersheds. The presence of a smaller data set for the lower
portion of the Watershed could be associated with a variety of factors, including the
hydrology and geographical remoteness. Both factors are explored on a preliminary
level as part of this analysis.
3.8.1 Hydrology Categories and Environmental Conditions
Other than the high-altitude alpine climate of the San Juan Mountains, the majority of
the Watershed expands south and west through a vast semi-arid shrubland desert that
receives on average 8 inches of precipitation a year according to National Oceanic and
Atmospheric Administration (NOAA) climate stations in Farmington, New Mexico, and
Bluff, Utah (Wester Regional Climate Center, 2016). Approximately 25% of this annual
precipitation is received during the monsoon season in brief, frequently intense
thunderstorms that manifest in a spotty fashion across the landscape between July and
August (WRCC, 2024). Precipitation drains to a network of predominantly intermittent
tributaries, or rivers and streams that only flow during certain times of the year, to the
San Juan River through highly erosive sedimentary strata, such as sandstone, siltstone,
and shale (Thompson, 1982).
©Alyssa Richmond 2021
Vista of Canyon Largo, a major intermittent tributary to the San Juan River.
E. coli in the San Juan Watershed
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AES conducted an inventory of Graph 5: Number and Percentage of hydrographic categories (perennial, Hydrographic Categories of Major ephemeral, and intermittent) of major Tributaries within the Watershed tributaries in the Watershed using
geospatial data from the USGS National 30 (14%) 24 (12%)
Hydrology Dataset (NHD). Based on
the 2021 NHDPlus High Resolution
dataset, there are 209 major Perennial tributaries, excluding the San Juan
River, in the Watershed. The number Intermittent and percent of the hydrographic
categories for all major tributaries in Perennial and the entire Watershed is provided in Intermittent
Graph 4. 155
(74%)
The Sub-Watersheds that have had few or no occurrences of E.coli sample locations on
major tributaries, other than the San Juan River (i.e Blanco, Chaco, Monezume, Chinle,
Lower San Juan - Four Corners, and Lower San Juan), are predominantly or completely
composed of intermittent drainages that flow in response to precipitation. Because
74% of the waterways are classified as intermittent, there is an inherent challenge to
identifying potential sample locations that can be reasonably expected to flow during
precipitation events. The hydrographic categories of these major tributaries are
included in Figure 13. The number and percentage of the hydrographic categories for all
major tributaries in each Sub-Watershed is provided in Graph 5.
Graph 6: Hydrographic Category of Major Tributaries per Sub-Watershed
Animas
Blanco
Chaco
Chinle
Lower San Juan
Lower San Juan - Four Corners
Mancos
McElmo
Middle San Juan
Montezuma
Piedra
Count
Perennial Intermittent Perennial and Intermittent
0 5 10 15 20 25 30 35 40
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Note that the hydrographic category determinations may not accurately represent on-
the-ground conditions. The USGS NHDPlus dataset is a nationwide dataset refined
through geospatial analysis on a continental scale and is not confirmed in the field by its
producers. Some tributaries may not be accurately described in this preliminary
analysis. If the WIIN Act Group wishes to further explore waterways to prioritize for
monitoring and watershed planning on a multijurisdictional level, additional
coordination with entities or agencies familiar with these tributaries and/or Sub-
Watersheds, evaluation of Federal Emergency Management Agency (FEMA) floodplain
data (if available), and field verification is recommended.
3.8.2 Geographical Constraints
While there are permanent USGS sondes stations throughout the Watershed that
passively record river flow and water quality parameters such as metals and sediment
(USEPA, 2023), E.coli samples must be collected quickly in real time in order to be
analyzed at the laboratory within 6 hours of collection and ensure an accurate measure
of living bacteria. The remoteness of the region requires significant travel times to
collect the sample(s) and then transport the samples to the laboratory. There is a
logistical challenge in planning for precipitation events across the Watershed, mobilizing
to geographically remote (and predominantly intermittent) tributaries to sample during
the first flush, and then delivering samples to an accredited laboratory within the
limited hold time.
3.8.3 Certified Laboratory Access and Capacities
An extension of the logistical challenges of monitoring for E.coli in a geographically
remote Watershed is the availability of accredited laboratories that offer bacteriological
quantification services.
AES reviewed the combined dataset for the laboratories utilized by various entities for
laboratory analyses, including E.coli, total coliform, fecal coliform, and MST, and
confirmed this information with the collecting entity/agency. Based on available
information, it appears there are currently 12 laboratories that conduct E. coli analyses
for samples from the Watershed, 5 of which are within the Watershed itself. AES
acknowledges that the preliminary list of laboratories requires further verification; there
may be additional laboratories available in the region. LuminUltra Technologies, the
laboratory used for MST analyses, is located in Baltimore, Maryland, and MST samples
must be shipped on ice for overnight delivery. Notes that NMED-SWQB utilizes a mobile
laboratory unit for their routine sampling, a valuable asset that makes sampling more
efficient and cost effective for all the AUs sampled throughout the state on a rotational
basis. A list of these laboratories, their locations, which entities are using them, and
links for further information is provided in Appendix N. A map of all laboratories used
for the 2004-2021 combined dataset is provided in Figure 14.
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Additionally, many of the regional laboratories that conduct E. coli analyses have limits
on the number of samples they can take in a day, as well as limitations on the number of
days each week they can take samples. These factors often limit how many samples can
be analyzed during rainfall events or at times when intermittent drainages are flowing.
4.0 Conclusions and Recommendations
4.1 Conclusions
AES completed an analysis of available E.coli data for the San Juan Watershed
(Watershed), on behalf of the UTDWQ and the WIIN Act Group between Fall 2023 and
Spring 2024. As part of the approved project scope, AES compiled and completed a data
quality review of sample data obtained from a variety of entities and agencies, including
NPS WRD, USGS, NMED-SWQB, CDPHE, NNEPA, SUIT, Ute, SJWG, and AWP.
A total of 2,875 E.coli sample results, along with additional results for total coliform,
fecal coliform, and MST analyses were compiled for 12 HUC8 Sub-Watersheds. The data
set was limited to samples that were collected under an approved QAPP and collected
when regulatory agencies adapted E.coli as the water quality standard for recreation in
surface waters. Under this criteria sample data ranged from 2004 to 2021. While
extensive attempts were made to collect as much data as possible from a wide range of
entities and agencies, it is recognized that some potential datasets may not have been
identified and obtained.
The Watershed encompasses nearly 16 million acres of the mountainous areas of
Colorado, the semi-arid high desert scrub/shrubland of New Mexico and Arizona, and
lower elevation canyon country of Utah. Sample locations ranged across the entire
Watershed and included locations within perennial, intermittent, and a combination of
perennial/intermittent waterways; however, most samples were collected from the
upper and middle portions of the Watershed where perennial tributaries are more
prominent. The USEPA RWQC of 410 cfu/100 mL was utilized as the threshold criteria
for this initial analysis because the project area encompasses four states and multiple
tribal lands with their own unique water quality standard for E.coli.
Given the large data set, as well as the wide-ranging entities and agencies that
contributed data, key assumptions were required to be made. Primary assumptions
included:
1. Sample locations that had coordinates in close proximity to other locations
but could not be confirmed as being the same location were considered as
separate sample locations;
E. coli in the San Juan Watershed
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2. Data were assumed to have not exceeded sample holding time;
3. Data were assumed to be representative of water quality conditions at the
time of collection; and
4. Samples were collected by trained personnel familiar with appropriate
standard operating procedures.
4.1.1 Waterways Sampled, Sample Locations and Sampling Density
The number of waterways sampled, sample locations, samples collected, and the
sampling density varied significantly across the Watershed. Based on the aggregated
dataset, 117 different waterways were sampled for E.coli, total coliform, fecal coliform,
and MST, with 410 discrete sampling locations identified. All of these 410 sample
locations were sampled for E.coli, except for the Chaco Sub-Watershed, which has only
had two waterways sampled for fecal coliform. Of note, the three largest Sub-
Watersheds in terms of size, the Upper San Juan, Chaco and Chinle, all had areas greater
than 2 million acres. While the Upper San Juan had data for 26 waterways with 113
discrete sampling locations for E.coli, the Chinle (1 location in 1 waterway), Montezuma
(9 locations in 4 waterways), and Lower San Juan (4 location for 1 waterway) Sub-
Watersheds had the least sample locations. The Sub-Watersheds with the most
sampling locations were Upper San Juan (113) and Middle San Juan (102), Animas (82),
Mancos (38) and McElmo (28).
4.1.2 Results Over USEPA RWQC Threshold
Of the 2,875 E.coli samples that were included in the aggregated dataset, 17% were at
or above the USEPA RWQC (487 results). In 9 of the 12 Sub-Watersheds, E.coli
concentrations were reported one or more times at the upper quantification limit of
2,420 cfu/100 mL. The disparity between the percentage of exceedances within a single
Sub-Watershed compared to exceedances within the entire Watershed confirms the
uneven distribution of sampling frequencies and the number of waterways sampled
within a Sub-Watershed. Of note, RWQC exceedances within the Sub-Watershed
datasets were calculated for the Upper San Juan (17%), Middle San Juan (27%), and
Animas (11%). For these same Sub-Watersheds, RWQC exceedances comprised 4.1%,
4.5%, and 3.1%, respectively, of the overall 17% of RWQC exceedances of the 2,875
E.coli samples collected across the entire San Juan Watershed.
4.1.3 Temporal Distribution of Concentrations
Preliminary evaluation of temporal distributions from 2004 to 2021 for several Sub-
Watersheds was limited because of the lack of a robust dataset. Based on available
data, E.coli results over the USEPA RWQC appeared to be more prevalent between May
and October. The greatest number of E.coli concentration exceedances of the USEPA
RWQC for each Sub-Watershed evaluated was between July and September, which
coincides with the typical monsoon season for the Watershed.
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4.1.4 Preliminary Statistical Analyses
Initial statistical analyses were conducted on waterways within Sub-Watersheds that
had the minimum required sample size (n=10). Of the 38 waterways that met the
sample size criterion, most showed wide standard deviations, confirming that overall
E.coli data sets were quite variable over time for each waterway. This range in E.coli
data could be associated with a variety of factors, including but not limited to, the
ongoing and/or intermittent sources of E.coli, E.coli’s aerobic life cycle, and ability to
attach to sediment particles transported in stormwater and surface water. A total of
seven waterways had no exceedances and/or detections of E.coli. A total of 13
waterways had exceedances of E.coli over the USEPA RWQC but no concentrations at
the 2,420 cfu/100 mL quantification limit. A total of 18 waterways had concentrations
of E.coli both over the USEPA RWQC and at the 2,420 cfu/100 mL quantification limit.
4.1.5 MST Sampling
This report included discussion of MST sampling conducted along the Animas River and
San Juan River in the Animas and Middle San Juan Sub-Watersheds in 2013, 2014, and
2021 by the SJWG. For the 2013 and 2014 MST sampling, ruminant fecal bacteria were
detected in 94% of samples, and human fecal bacteria were detected in 77% of all
samples. The sample locations along the San Juan River had a greater number of
positive and quantifiable results for human sources than the Animas River sample
locations. In the 2021 MST sampling, human source bacteria was still present but
significantly less in comparison to the results of the 2013 and 2014 study, indicating
progress in reducing vectors of human fecal waste in this reach of the Watershed.
Almost half of the MST results that had no detections for human source bacteria had
accompanying E.coli results over the USEPA RWQC, indicating fecal waste from other
host organisms were present but not sampled for, such as ruminant, bird, or other
sources
4.1.6 Land Use and Land Cover
Urban development, wastewater treatment infrastructure and irrigated pasture and
grazing were discussed as possible impacts to surface water quality, in particular with
increased E.coli concentrations. Urban development is limited to the upper portions of
the Watershed in incorporated communities such as Farmington, New Mexico, and
Durango, Colorado, and E.coli exceedances over the USEPA RWQC have been detected
in waterways near these areas. Approximately 85% (79) of the 93 communities within
the Watershed are unincorporated rural communities, and adjacent waterways have
not been sampled consistently. Wastewater infrastructure mirrors this pattern with
WWTPs concentrated in the upper portions of the Watershed near incorporated
communities, indicating that much of the Watershed downstream of Shiprock, New
Mexico, are on on-site liquid waste systems. Irrigated pasture is also highly
concentrated in the upper portions of the Watershed within the waterways. Each of
E. coli in the San Juan Watershed
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these land use and land cover conditions may indicate potential correlations to E.coli
concentrations that requires further research.
4.1.7 Sampling Frequency and Locations Across the Watershed
Several factors were noted to affect the ability to collect E.coli samples evenly across the
Watershed. These factors include hydrology classifications of the waterways, i.e.
perennial, intermittent, or possibly both, within a single waterway. Intermittent
streams and drainages present logistical challenges in planning and implementing a
sampling program. Geographical constraints associated with the remote portions of the
San Juan Watershed also present challenges in scheduling sampling so the samples can
be collected and delivered to the analytical laboratory within hold times. Finally, the
availability of analytical laboratories, and their capacity to analyze a large number of
samples, also presents a challenge.
4.2 Recommendations
Based on the extensive but incomplete dataset and the initial evaluation of data, AES
has prepared the following recommendations for consideration as part of future efforts:
Formalize a multijurisdictional protocol for assembling and sharing datasets for
entities and agencies that collect E.coli data within the Watershed. As an initial
step to this recommendation, it will be imperative to identify and work with
stakeholders across the region. Participation and input from the multitude of
federal, state, tribal, county and municipal governments, in addition to other
non-profit groups, will be essential. In particular, working with Navajo Nation,
Southern Ute, Ute Mountain Ute, and Jicarilla Apache will be key in ensuring a
better understanding of Watershed conditions.
Develop a regional or Watershed QAPP that can be utilized by governmental and
non-government entities. This effort will further support the quality assurance
of sampling efforts and help ensure inclusion of regulatory and non-regulatory
agency datasets. The QAPP should include the objective of concurrent or
simultaneous sample collection to allow for comprehensive snapshots of E.coli
conditions across the entire Watershed at different times of the year.
While preliminary analysis indicates a possible correlation between E.coli
concentrations over the USEPA RWQC during the summer season within the
Watershed, further analysis is recommended once additional data is
incorporated into the dataset. Future analyses should include statistical and
temporal investigation per waterway, as well as a prioritized subset of sample
locations with the most consistent sampling events over multiple months,
seasons and years.
E. coli in the San Juan Watershed
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MST sampling, specifically tailored to the land use of the associated Sub-
Watershed, is recommended in reaches of the Watershed that show trends of
chronic exceedances over the USEPA RWQC. MST for human source bacteria is
recommended for unincorporated areas downriver of Shiprock, New Mexico.
Further monitoring and evaluation are recommended for waterways that had 1
or more E.coli exceedances over the USEPA RWQC exceedances but under the
quantification limit and 1 or more concentrations at the quantification limit:
o Sub-Watershed and Waterways with E.coli Concentration(s) over the
USEPA RWQC and under the Quantification Limit:
Animas: Junction Creek
McElmo: Hartman Draw
Middle San Juan: Cherry Creek
Piedra: Capote Lake, Piedra River
Upper San Juan: Navajo Reservoir, Los Pinos River, Rio Blanco,
Sambrito Creek, Ute Creek, Beaver Creek, Dry Creek, and Spring
Creek
o Sub-Watersheds and Waterways with E.coli Concentration(s) at the
Quantification Limit:
Animas: Animas River, Florida River, Salt Creek
Lower San Juan: San Juan River
Lower San Juan -Four Corners: San Juan River
Mancos: Navajo Wash, Mancos River
McElmo: Mud Creek, McElmo Creek
Middle San Juan: La Plata River, San Juan River, Shumway Arroyo,
and Stevens Arroyo
Piedra: Stollsteimer Creek
Upper San Juan: Navajo River, San Juan River, Rock Creek, and
Ignacio Creek
Further investigation into wastewater infrastructure should be completed. The
initial WWTP inventory was compiled through review of publicly accessible
online federal and state NPDES lists managed by USEPA, CDPHE, UTDEQ, and
NMED in January 2024. However, there are additional community wastewater
systems that may have not been identified during the inventory. In addition,
acquisition of geospatial data (shapefiles, Google Earth files, etc) for WWTPs,
community systems, and any other wastewater facilities or infrastructure will
assist in better understanding potential ongoing E.coli sources and impacts.
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Water Quality Criteria. (EPA 822R23003). USEPA Office of Water. Retrieved
October 12, 2023, from https://www.epa.gov/wqc/five-year-reviews-epas-
recreational-criteria
USEPA. (2023, December 21). San Juan Watershed Storymap Collection. Retrieved
January 20, 2024, from
https://storymaps.arcgis.com/collections/cf0c0658ae114e57a720c0c0c0e1b28b
Wester Regional Climate Center. (2016). Farmington Agriculture Science Center Montly
Climate Summary. Farmington, New Mexico, United States of America. Retrieved
February 2, 2024, from https://wrcc.dri.edu/cgi-bin/cliMAIN.pl?nm3142
Western Regional Climate Center. (2016). Bluff, Utah Monthly Climate Summary. Bluff,
Utah, United States of American. Retrieved February 2, 2024, from
https://wrcc.dri.edu/cgi-bin/cliMAIN.pl?ut0788
Wisconsin Department of Natural Resources. (2020). Test Methods for Measuring E.coli
in Wastewater. Wisconsin, United State of America. Retrieved January 29, 2024,
from chrome-
E. coli in the San Juan Watershed
p. 37

extension://efaidnbmnnnibpcajpcglclefindmkaj/https://dnr.wisconsin.gov/sites/
default/files/topic/LabCert/Test-Methods-for-Measuring-Ecoli-DNR.pdf
E. coli in the San Juan Watershed
p. 38

6.0 Preparers and Funding Sources
This project was generously supported by Water Infrastructure Improvements for the
Nation (WIIN) Act grant funding through the WIIN Act Group and Utah Department of
Environmental Quality (UTDEQ).
Preparers and contributors for this report include:
Name Project Title
Animas Environmental Services, LLC
Alyssa Richmond Project Manager
Elizabeth McNally, P.E. Project Manager / Quality Assurance Officer
Lany Cupps Environmental Specialist
Angela Todd Environmental Specialist
Kate Pickford Environmental Specialist
Corwin Lameman Drafter
Lynn Lane Data Consolidation Consultant
UTDEQ Division of Water Quality
Christine Osborne Project Manager
Jodi Gardberg Project Manager
Toby Hooker Quality Assurance Officer
E. coli in the San Juan Watershed
p. 39

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Parameters used for EPA Water Quality Portal Download
During the initial bacteriological data download process from the USEPA Water Quality Portal
conducted by the San Juan SWCD in 2022, various location, date range, and water quality
parameter filters were used to specify downloads from the portal. Downloads were done on
February 24th and 25th, 2022. The parameters below were used to query the database for water
quality data specific to the purposes of this project.
Any parameters not mentioned below in the portal were left blank during the downloading
process.
Country: United States of America
Site Type: Stream, Spring, Lake/Reservoir/Impoundment, and Wetland
Sample Media: water (STEWARDS) and Water (NWIS, STEWARDS, STORET)
Characteristic Group: Microbiological (NWIS, STEWARDS, STORET)
Data Source: NWIS, STEWARDS, and WQX
File Format: MS Excel 2007+
Data Profiles: Samples Results (biological metadata)
HUC6: 140802 and 140801
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