Middle Santa Ana River Bacterial Indicator TMDL Implementation Report

Transcription

1 Middle Santa Ana River Bacterial Indicator TMDL Implementation Report February 2013 on behalf of Santa Ana Watershed Project Authority San Bernardino County Stormwater Program County of Riverside Cities of Chino Hills, Upland, Montclair, Ontario, Rancho Cucamonga, Rialto, Chino, Fontana, Norco, Corona, Riverside, Pomona, and Claremont

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3 Table of Contents Section 1 Introduction Background and Purpose Report Roadmap Section 2 Triennial Review Report Introduction Water Quality Program Summary Watershed wide Compliance Monitoring Sites Water Quality Sampling Program Water Quality Measurements Sample Frequency Sample Collection Sample Handling Data Management Data Handling Data Analysis Compliance with Wasteload Allocations Bacterial Indicator Concentrations Compliance Frequency Comparison to Previous Findings Compliance with Load Allocations Agricultural Sources Natural Sources Section 3 CBRP Tier 1 Source Evaluation Report Introduction CBRP Framework CBRP Source Evaluation Activities Source Evaluation Monitoring Monitoring Locations Data Collection Data Management Tier 1 Source Monitoring Results Dry Weather Flow Water Quality Prioritization Analysis Prioritization Criteria Prioritization Factor Analysis Bacterial Indicator Source Evaluation Analysis Background and Purpose Source Evaluation Analysis Methodology Sub Watershed Analysis Results Chino Creek Subwatershed Draft i

4 Table of Contents (Continued) Cucamonga Creek Subwatershed Santa Ana River Subwatershed Non MS4 Bacterial Indicator Sources Correlation Analysis Relationship between E. coli Concentrations at SAR Compliance Sites Seasonal E. coli Trends Potential Seasonal E. coli Source Section 4 Summary of Findings and Recommendations Summary of Findings Recommendations Section 5 References List of Attachments Attachment A Water Quality Data List of Tables Table 2 1 Watershed wide compliance monitoring program sample sites Table 2 2 Summary of water sample collection activity during 2010 dry season Table 2 3 Summary of water sample collection activity during 2011 dry Season Table 2 4 Summary of water sample collection activity during 2012 dry Season Table 2 5 Summary of water sample collection activity during wet season Table 2 6 Summary of water sample collection activity during wet season Table 2 7 Summary of water sample collection activity during wet season Table 2 8 Summary of samples classified as wet weather samples during the , , and wet seasons Table 2 9 Fecal coliform and E. coli (cfu/100 ml) concentrations observed at watershedwide compliance sites during the wet season Table 2 10 Fecal coliform and E. coli concentrations (cfu/100 ml) observed at watershedwide compliance sites during the 2010 dry season Table 2 11 Fecal coliform and E. coli concentrations (cfu/100 ml) observed at watershedwide compliance sites during the wet season Table 2 12 Fecal coliform and E. coli concentrations (cfu/100 ml) observed at watershedwide compliance sites during the 2011 dry season Table 2 13 Fecal coliform and E. coli concentrations (cfu/100 ml) observed at watershedwide compliance sites during the wet season Table 2 14 Fecal coliform and E. coli concentrations (cfu/100 ml) observed at watershedwide compliance sites during the 2012 dry season Table 2 15 Summary of fecal coliform concentrations (cfu/100 ml) and data variability by sample location during the 2010, 2011 and 2012 dry seasons Table 2 16 Summary of fecal E. coli concentrations (cfu/100 ml) and data variability by sample location during the 2010, 2011 and 2012 dry seasons ii Draft

5 Table of Contents (Continued) Table 2 17 Summary of fecal coliform concentrations (cfu/100 ml) and data variability by sample location during the , and wet seasons (dry weather only) Table 2 18 Summary E. coli concentrations (cfu/100 ml) and data variability by sample location during the , and wet seasons (dry weather only) Table 2 19 Compliance frequency for fecal coliform during the 2010, 2011, and 2012 dry seasons (as compared to existing Basin Plan objectives for fecal coliform) Table 2 20 Frequency of compliance with proposed geometric mean water quality objectives for E. coli during the 2010, 2011, and 2012 dry seasons Table 2 21 Compliance frequency for fecal coliform during the , , and wet seasons Table 2 22 Frequency of compliance with proposed geometric mean water quality objectives for E. coli during the , , and wet seasons Table 3 1 CBRP Tier 1 source evaluation monitoring sites Table 3 2 Summary of DWF observations by sample site Table 3 3 Descriptive statistics for dry weather flow, all Tier 1 sites Table 3 4 Correlation analysis between E. coli concentrations and TSS, temperature, and dry weather flow for all Tier 1 sites Table 3 5 Results of student T Test comparing E. coli geometric mean concentrations to detection of human specific Bacteroidales markers for all Tier 1 sites Table 3 6 Relative rank results for each prioritization criteria and composite bacteria prioritization score for all Tier 1 sites Table 3 7 Cliff Swallow nest analysis List of Figures Figure 2 1 Location of watershed wide compliance monitoring program sample locations in the Middle Santa Ana River watershed Figure 2 2 Time series plot of fecal coliform single sample results and geometric means for samples collected from Prado Park Lake, 2007 through 2012 dry seasons Figure 2 3 Time series plot of fecal coliform single sample results and geometric means for samples collected from Chino Creek, 2007 through 2012 dry seasons Figure 2 4 Time series plot of fecal coliform single sample results and geometric means for samples collected from Mill Cucamonga Creek, 2007 through 2012 dry seasons Figure 2 5 Time series plot of fecal coliform single sample results and geometric means for samples collected from Santa Ana River at MWD crossing, 2007 through 2012 dry seasons Figure 2 6 Time series plot of fecal coliform single sample results and geometric means for samples collected from Santa Ana River at Pedley Ave., 2007 through 2012 dry seasons Figure 2 7 Time series plot of E. coli single sample results and geometric means for samples collected from Prado Park Lake, 2007 through 2012 dry seasons Draft iii

6 Table of Contents (Continued) Figure 2 8 Time series plot of E. coli single sample results and geometric means for samples collected from Chino Creek, 2007 through 2012 dry seasons Figure 2 9 Time series plot of E. coli single sample results and geometric means for samples collected from Mill Cucamonga Creek, 2007 through 2012 dry seasons Figure 2 10 Time series plot of E. coli single sample results and geometric means for samples collected from Santa Ana River at MWD crossing, 2007 through 2012 dry seasons Figure 2 11 Time series plot of E. coli single sample results and geometric means for samples collected from Santa Ana River at Pedley Avenue, 2007 through 2012 dry seasons Figure 2 12 Box whisker plots of bacteria indicator concentrations from during dry weather in the dry season (red) and wet season (blue), and wet weather events (yellow points) Figure 2 13 Fecal coliform dry season geometric means for Figure 2 14 E. coli dry season geometric means for Figure 2 15 Fecal coliform wet season dry weather seasonal geometric means for Figure 2 16 E. coli wet season dry weather seasonal geometric means for Figure 3 1 CBRP Tier 1 source evaluation monitoring sites Figure 3 2 Change in mean dry weather flow measurements from 2007 USEP to 2012 Tier 1 Inspection Program Figure 3 3 Box whisker plots of E. coli concentration from Tier 1 monitoring sites (2012) Figure 3 4 Change in E. coli concentration from 2007 USEP to 2012 Tier 1 Inspection Program Figure 3 5 Persistence of human Bacteroides marker for Tier 1 sites with at least one detection in the 2012 dry season Figure 3 6 Change in persistence of human Bacteroides from 2007 USEP to 2012 Tier 1 Inspection Program Figure 3 7 Box whisker plots for E. coli in samples with and without detection of human Bacteroides marker for all Tier 1 sites Figure 3 8 Bacteria prioritization score for all Tier 1 sites Figure 3 9 Map of bacteria prioritization category for all Tier 1 sites Figure 3 10 Schematic showing bacteria and DWF inflows to Chino Creek in relation to compliance monitoring site Figure 3 11 Comparison of estimated blended E. coli concentration of MS4 and clean POTW effluent with downstream watershed wide compliance monitoring data for Chino Creek at Central Avenue Figure 3 12 Responsibility of individual MS4 drainage areas to exceedences of the WLA in estimated blended concentration for Chino Creek at Central Avenue Figure 3 13 Schematic showing bacteria and DWF inflows to Cucamonga Creek in relation to compliance monitoring site Figure 3 14 Comparison of estimated blended E. coli concentration of MS4 and clean POTW effluent with downstream watershed wide compliance monitoring data for Mill Cucamonga Creek at Chino Corona Road iv Draft

7 Table of Contents (Continued) Figure 3 15 Responsibility of individual MS4 drainage areas to exceedences of the WLA in estimated blended concentration for Mill Cucamonga Creek at Chino Corona Road Figure 3 16 Schematic showing bacteria and DWF inflows to Santa Ana River in relation to compliance monitoring sites Figure 3 17 Comparison of estimated blended E. coli concentration of MS4 and clean POTW effluent with downstream watershed wide compliance monitoring data for Santa Ana River and MWD crossing Figure 3 18 Comparison of estimated blended E. coli concentration of MS4 and clean POTW effluent with downstream watershed wide compliance monitoring data for Santa Ana River at Pedley Avenue Figure 3 19 Responsibility of individual MS4 drainage areas to exceedences of the WLA in estimated blended concentration for Santa Ana River at MWD Crossing Figure 3 20 Responsibility of individual MS4 drainage areas to exceedences of the WLA in estimated blended concentration for Santa Ana River at Pedley Avenue Figure 3 21 Relationship between E. coli and other water quality constituents at SAR at MWD crossing Figure 3 22 Relative locations of SAR compliance sites and Riverside treated waste water discharge Figure 3 23 Seasonal E. coli geometric mean concentrations at MWD crossing and Pedley Avenue during summery dry season from 2008 through 2012 (GM=geometricmean) Figure 3 24 Photographs of Swallows within the MSAR Watershed: Left = Swallow nest in boys republic south channel culvert in Chino Hills; Right: Swallow nests under Hellman Avenue Bridge on Cucamonga Creek Figure 4 1 Photo of Santa Ana River at MWD crossing monitoring site (September 11, 2012) Draft v

8 Table of Contents (Continued) Acronyms CAFOs EPA LA MSAR QAPP RCFC&WCD RWQCB SAR SAWDMS SAWPA SBCFCD TMDL TSS USGS concentrated animal feeding operations Environmental Protection Agency load allocations Middle Santa Ana River Quality Assurance Project Plan Riverside County Flood Control & Water Conservation District Regional Water Quality Control Board Santa Ana River Santa Ana Watershed Data Management System Santa Ana Watershed Project Authority San Bernardino County Flood Control District Total Maximum Daily Load total suspended solids United States Geological Survey vi Draft

9 Section 1 Introduction This report was prepared to fulfill two requirements associated with the implementation of the Middle Santa Ana River (MSAR) Bacterial Indicator Total Maximum Daily Load (TMDL) ( MSAR Bacterial Indicator TMDL ). These requirements include preparation of the: (1) 2013 Triennial Report; and (2) findings from Tier 1 source evaluation activities. The information below provides an overview regarding the regulatory background and purpose for this report. Subsequent report sections provide the data and analyses associated with the TMDL related reporting requirements. 1.1 Background and Purpose Water quality data collected in 1994 and 1998 from waterbodies in the MSAR watershed showed exceedences of fecal coliform bacterial indicator water quality objectives. Based on these data and potential impacts to recreational uses, the Santa Ana Regional Water Quality Control Board (RWQCB) recommended that the following waterbodies be placed on the 303(d) list: Santa Ana River, Reach 3 Prado Dam to Mission Boulevard (excludes Prado Basin Management Zone) Chino Creek, Reach 1 Santa Ana River confluence to beginning of hard lined channel south of Los Serranos Road Chino Creek, Reach 2 Beginning of hard lined channel south of Los Serranos Road to confluence with San Antonio Creek Mill Creek (Prado Area) Natural stream from Cucamonga Creek Reach 1 to Prado Basin Cucamonga Creek, Reach 1 Confluence with Mill Creek to 23rd Street in City of Upland Prado Park Lake Waterbodies on the 303(d) list are subject to the development of a TMDL. Accordingly, on August 26, 2005 the RWQCB adopted Resolution No. R , amending the Water Quality Control Plan for the Santa Ana Region (Basin Plan) to incorporate bacterial indicator TMDLs for the above listed waterbodies in the watershed (i.e., MSAR Bacterial Indicator TMDL) (RWQCB 2005). The TMDLs adopted by the RWQCB were subsequently approved by the State Water Resources Control Board on May 15, 2006, by the California Office of Administrative Law on September 1, 2006, and by EPA Region 9 on May 16, The Environmental Protection Agency (EPA) approval date is the TMDL effective date. The MSAR Bacterial Indicator TMDL established wasteload allocations (WLA) for urban MS4 and confined animal feeding operation (CAFO) discharges and load allocations (LA) for agricultural and natural sources. The WLAs and LAs were established for both fecal coliform and E. coli: Draft 1 1

10 Section 1 Introduction Fecal coliform: 5 sample/30 day logarithmic mean (or geometric mean) less than 180 organisms/ 100 ml and not more than 10 percent of the samples exceed 360 organisms/100 ml for any 30 day period. E. coli: 5 sample/30 day logarithmic mean (or geometric mean) less than 113 organisms/100 ml and not more than 10 percent of the samples exceed 212 organisms/100 ml for any 30 day period. The TMDL listed a number of required tasks for implementation by urban dischargers in the MSAR portions of Riverside and San Bernardino Counties, including establishment of a watershed wide compliance monitoring program and establishment of an urban source evaluation program. In addition, the TMDL requires preparation of a Triennial Report every three years to assess the status of compliance with TMDL WLAs and LAs. Subsequent to TMDL adoption on January 29, 2010, the RWQCB adopted new MS4 permits for the Santa Ana Region of Riverside County (Order No , NPDES No. CAS618033) and San Bernardino County (Order No , NPDES No. CAS618036). These MS4 permits incorporated the TMDL requirements applicable to MS4 dischargers in the MSAR watershed. In addition, the MS4 Permit also required the development of a Comprehensive Bacteria Reduction Plan (CBRP) by each County. The CBRP is designed to provide a comprehensive plan for attaining the MS4 permit s water quality based effluent limits for the MSAR Bacterial Indicator TMDL by integrating existing control programs and efforts with new permit mandates and other additional activities necessary to address controllable urban sources of bacterial indicators. Each County submitted final CBRPs to the RWQCB in June The RWQCB approved both CBRPs on February 10, 2012 (Riverside County: Order No. R ; San Bernardino County: Order No. R ). 1.2 Report Roadmap The reporting requirements contained within the MSAR Bacterial Indicator TMDL were incorporated into the MS4 permits for each County and have subsequently been incorporated into the RWQCBapproved CBRPs (e.g., see Attachment E of each County s CBRP). This TMDL implementation report addresses two of these specific reporting requirements: 2013 Triennial Report This report is required every three years after adoption of the MSAR Bacterial Indicator TMDL. The first Triennial Report for the period 2007 to 2009 was submitted to the RWQCB in 2010 (SAWPA 2010). Per the CBRP the purpose of this 2013 Triennial Report (see CBRP Table E 5) includes: Evaluate progress towards meeting urban WLAs (dry weather April 1 October 31). Section 2 of this report provides this information. Review and revise the compliance analysis contained in the CBRP based on the most recent data, including analysis of the relative contribution of bacterial indicators from controllable urban sources. Section 3.5 of this report provides the findings from the revised compliance analysis. This revision is based on the substantial amount bacterial indicator and flow data collected since the CBRP was prepared. Tier 1 Source Evaluation Data Analysis Report The CBRP requires submittal of a report that summarizes the findings of Tier 1 source evaluation data collection activities in each County by March 31, 2013 (see Table E 3, Activity 3B). The purpose of this report is to prioritize drainage 1 2 Draft

11 Section 1 Introduction areas within the watersheds that encompass each watershed wide compliance site for subsequent bacterial indicator source evaluation activities. Section 3.4 of this TMDL implementation report provides this CBRP deliverable. Based on the findings reported and discussed in Sections 2 and 3, Section 4 provides a summary of findings and recommendations for continued MSAR Bacterial Indicator TMDL implementation through the CBRP. Draft 1 3

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13 Section 2 Triennial Report 2.1 Introduction The MSAR Bacterial Indicator TMDL requires implementation of a watershed wide compliance monitoring program for bacterial indicators. This program, which was initiated in July 2007, collects bacterial indicator data from five sites in the MSAR watershed during both the dry and wet seasons. Specifically, dry weather samples are collected weekly over 20 consecutive weeks generally from May to September in the summer and over 11 consecutive weeks generally from late December through early March in the winter. In addition, one wet weather event is sampled each year, typically during late fall or early winter. Biannual data reports are produced to provide the dry and wet season sample results (see SAWPA 2009a, 2009b, 2009c, 2010b, 2010c, 2011c, 2011d, 2012a, and 2012b). These periodic monitoring reports are submitted to the RWQCB to comply with CBRP reporting requirements (see CBRP Table E 5). In addition to the biannual reporting requirement, the TMDL requires preparation of a water quality assessment every three years that summarizes the data collected for the preceding three year period and evaluates progress towards achieving the WLAs and LAs. This requirement or Triennial Report is also included in the RWQCB approved CBRPs for San Bernardino County and Riverside County (see CBRP Table E 5). The first Triennial Report, covering the period from 2007 through the 2009 dry season, was submitted to the RWQCB in 2010 (SAWPA 2010a). This section constitutes the second Triennial Report submitted for the MSAR Bacterial Indicator TMDL. It summarizes the results of dry and wet weather watershed wide compliance monitoring conducted from the wet season through the 2012 dry season. The findings are presented within the context of the WLAs and LAs applicable to the MSAR Bacterial Indicator TMDL. 2.2 Water Quality Program Summary ( ) The MSAR Bacterial Indicator TMDL required urban and agricultural dischargers to implement a watershed wide bacterial indicator monitoring program by November 2007 (RWQCB 2005). The dischargers worked collaboratively through the MSAR Watershed TMDL Task Force 1 ( Task Force ) to develop this program, and prepared a Monitoring Plan and Quality Assurance Project Plan (QAPP) in 2007 that was subsequently approved by the RWQCB. These documents have been updated, as needed, to support MSAR Bacterial Indicator TMDL monitoring activities 2. The Task Force implemented the monitoring program in July 2007 following RWQCB approval of program documents; the program continues on a seasonal basis. The first Triennial Report provides a summary of monitoring activities that occurred from 2007 through the dry season of The 1 This Task Force includes representation by key watershed stakeholders, including representatives of the MS4 programs for Riverside and San Bernardino Counties, the Cities of Claremont and Pomona, agricultural operators, RWQCB, and SAWPA. 2 The Middle Santa Ana River Monitoring Plan and Quality Assurance Project Plan are available at santa ana river watershed tmdl taskforce/ Draft 2 1

14 Section 2 Triennial Report following section provides a summary of sampling and data management activities that have occurred since, specifically during the period from the wet season through the 2012 dry season Watershed wide Compliance Monitoring Sites The Task Force currently samples five watershed wide compliance monitoring sites in the MSAR watershed 3. Table 2 1 and Figure 2 1 identify these five locations. Attachment A of the Monitoring Plan (see footnote 2) provides additional information about each sample location. Table 2 1 Watershed wide compliance monitoring program sample sites Waterbody Sample Location Site Code Prado Lake Prado Lake Outlet WW C3 Chino Creek Central Avenue WW C7 Mill Cucamonga Creek Chino Corona Road WW M5 Santa Ana River MWD Crossing WW S1 Santa Ana River Pedley Avenue WW S Water Quality Sampling Program The RWQCB approved Monitoring Plan and QAPP (SAWPA 2011a, b) provide detailed information regarding the collection and analysis of field data and water quality samples. The following sections provide a summary of these methods Water Quality Measurements At each sample site water quality measurements include the collection of field parameter data and water samples for laboratory analysis: Field Measurements: Flow, temperature, conductivity, ph, dissolved oxygen, and turbidity. Laboratory Analysis: Fecal coliform, E. coli, and total suspended solids (TSS). 3 Prior to the 2009 dry season, Icehouse Canyon (WW C1) was included as watershed wide compliance monitoring site. However, with RWQCB approval the Task Force removed this site from the sampling program prior to the start of the 2009 dry season monitoring program. 2 2 Draft

15 Section 2 Triennial Report Figure 2 1 Location of watershed wide compliance monitoring program sample locations in the Middle Santa Ana River watershed Draft 2 3

16 Section 2 Triennial Report Sample Frequency The Monitoring Plan established seasonal sample collection dates for each year of the monitoring program. No samples were missed during the period of record covered by this Triennial Report. Dry Season 2010 Weekly samples were collected over a 20 week period from the week ending May 22, 2010 to the week ending October 2, Table 2 2 summarizes the results of this effort. Table 2 2 Summary of water sample collection activity during 2010 dry season Sample Month Planned Collected Samples Missed (Cause) May June July August September Total Weekly samples were collected over a 20 week period from the week ending May 21, 2011 to the week ending October 1, Table 2 3 summarizes the results of this sampling effort. Table 2 3 Summary of water sample collection activity during 2011 dry season Sample Month Planned Collected Samples Missed (Cause) May June July August September Total Weekly samples were collected over a 20 week period from the week ending June 2, 2012 to the week ending October 13, Table 2 4 summarizes the results of this sampling effort. Table 2 4 Summary of water sample collection activity during the 2012 dry season Sample Month Planned Collected Samples Missed (Cause) May June July August September October Total Draft

17 Section 2 Triennial Report Wet Season Wet Season Weekly samples were collected over an 11 week period from the week ending December 26, 2009 to the week ending March 6, In addition, one storm event was sampled. Storm event sampling includes: (1) collection of a sample on the day of the storm event; (2) collection of additional samples at 48, 72 and 96 hours after the onset if the storm event. During the wet season a storm event was sampled on October 14, Additional samples were collected 48, 72 and 96 hours after the storm event on October 16th, 17th and 18th, respectively. Table 2 5 summarizes the results of the wet season sampling effort. Table 2 5 Summary of water sample collection activity during wet season Sample Month Planned Collected Samples Missed (Cause) Weekly Sampling December January February March Total Storm Event Sampling October Storm event occurred on October 14 th Wet Season Weekly samples were collected over an 11 week period from the week ending December 25, 2010 to the week ending March 5, During the sampling period, a storm event was sampled on November 20, Additional samples were collected 48, 72 and 96 hours after the storm event on November 22nd, 23rd and 24th, respectively. Table 2 6 summarizes the results of the wet season sampling effort. Table 2 6 Summary of water sample collection activity during wet season Sample Month Planned Collected Samples Missed (Cause) Weekly Sampling December January February March Total Storm Event Sampling November Storm event occurred on November 20 th Wet Season Weekly samples were collected over an 11 week period from the week ending December 24, 2011 to the week ending March 3, During the wet season a storm event was sampled on December 12, Additional samples were collected Draft 2 5

18 Section 2 Triennial Report 48, 72, and 96 hours after the storm event on the 14th, 15th, and 16th, respectively. Table 2 7 summarizes the results of the wet season sampling effort. Table 2 7 Summary of water sample collection activity during wet season Sample Month Planned Collected Samples Missed (Cause) Weekly Sampling December January February Total Storm Event Sampling December Storm event occurred on December 12 th Sample Collection San Bernardino County Flood Control District (SBCFCD) staff collected the field measurements and water quality samples. CDM Smith coordinated the activities of the sample team and the submittal of samples to the laboratory for analysis Sample Handling Sample collection and laboratory delivery followed approved chain of custody procedures, holding time requirements, and required storage procedures for each water quality analysis. The Orange County Health Care Agency Water Quality Laboratory conducted all analyses for fecal coliform, E. coli, and TSS Data Management The following sections describe data handling and analysis methods. Additional details are provided in the Monitoring Plan and QAPP (SAWPA 2011a, b) Data Handling CDM Smith and SAWPA maintain a file of all laboratory and field data records (e.g., data sheets, chain of custody forms) as required by the QAPP. CDM Smith enters all field measurements and laboratory analysis results into a project database that is compatible with guidelines and formats established by the California Surface Water Ambient Monitoring Program (SWAMP). CDM Smith periodically submits to SAWPA updates of compiled data for incorporation into the Santa Ana Watershed Data Management System (SAWDMS), which SAWPA manages. Prior to a data submittal to SAWPA, CDM Smith completes a quality assurance/quality control review of the data Data Analysis Data analysis relied primarily on the use of descriptive statistics and comparisons to water quality objectives or TMDL allocations. For any statistical analyses, the bacterial indicator data were assumed to be log normally distributed as was observed in previous studies (SAWPA 2009a). Accordingly, prior to conducting statistical analyses, the bacterial indicator data were log transformed. 2 6 Draft

19 Section 2 Triennial Report Although only one storm event was targeted for sampling during each wet season, regular wet season sampling sometimes coincided with wet weather events. The following sources/criteria were evaluated to determine whether a wet season sample was influenced by wet weather conditions: Rainfall recorded at a nearby meteorological station; Daily flow record from several U.S. Geological Survey (USGS) or SBCFCD operated flow gauges in the watershed (as available); and Comparison of the flow measurement taken at the time of sample collection to the typical site baseflow observed during the sample period. The daily rainfall and flow data recorded during the , , and wet season sampling events is provided in the corresponding wet season reports (SAWPA 2010a, 2011c, 2012a). Table 2 8 lists the wet season samples classified as influenced by wet weather. All other samples were classified as dry weather samples. Unless otherwise specified, wet weather samples were not included in analyses of wet season data. Draft 2 7

20 Section 2 Triennial Report Table 2 8 Summary of samples classified as wet weather samples during the , , and wet seasons Sampling Season Site Sample Date Preceding 3 Day Rainfall (inches) Measured Flow (cfs) Approximate Baseflow (cfs) Wet Season Wet Season Wet Season Prado Park Lake Outflow 10/14/ /19/ Chino Creek at Central Ave 10/14/ Mill Cucamonga Creek at Chino Corona Rd Santa Ana River at MWD Crossing 12/22/ /19/ /14/ /22/ /19/ /9/ /14/ /22/ /19/ Santa Ana River at Pedley Ave 10/14/ /22/ /19/ Prado Park Lake Outflow 11/24/ /21/ n/a 1 4 Chino Creek at Central Ave 11/20/ Mill Cucamonga Creek at Chino Corona Rd Santa Ana River at MWD Crossing 11/24/ /21/ n/a /20/ /21/ n/a /22/ /24/ /21/ n/a /22/ Santa Ana River at Pedley Ave 11/20/ /22/ /24/ /21/ n/a /22/ Prado Park Lake Outflow 12/12/ Chino Creek at Central Ave 12/12/ /24/ Mill Cucamonga Creek at Chino Corona Rd 12/12/ Santa Ana River at MWD Crossing 12/16/ /24/ /28/ Santa Ana River at Pedley Ave 12/16/ Unsafe flow conditions prevented flow measurement 1/24/ /28/ Draft

21 Section 2 Triennial Report 2.3 Compliance with Wasteload Allocations The MSAR Bacterial Indicator TMDL contains WLAs for urban discharges and CAFOs. The watershedwide compliance monitoring program samples five locations on a regular basis (see Table 2 1 and Figure 2 1). The data from these sites are used to evaluate compliance with WLAs. The following sections summarize the bacterial indicator concentrations observed at the watershed wide compliance sites during the last three years Bacterial Indicator Concentrations The following tables summarize the observed E. coli and fecal coliform concentrations at each of the watershed wide compliance sites during the dry and wet season sample periods covered by this report: Table 2 9 summarizes observations during the wet season of Table 2 10 summarizes the observations during the dry season of Table 2 11 summarizes the observations during the wet season of Table 2 12 summarizes the observations during the dry season of Table 2 13 summarizes the observations during the wet season of Table 2 14 summarizes the observations during the dry season of Tables 2 15 and 2 16 summarize the geometric mean, median, and coefficient of variation of the fecal coliform and E. coli data for samples collected during each dry season from 2010 to During each year of dry season sampling, the highest fecal coliform geometric means were observed at the Mill Cucamonga Creek and Chino Creek sites (Concentration Range: cfu/100 ml and cfu/100 ml, respectively). The same pattern was observed for E. coli data, with Mill Cucamonga Creek and Chino Creek reporting the highest annual geometric means (Concentration Range: cfu/100 ml and cfu/100 ml, respectively). Intermediate values were observed at the Santa Ana River sites for both fecal coliform (Concentration Range: cfu/100 ml and cfu/100 ml at Santa Ana River (SAR) at MWD Crossing, and SAR at Pedley Avenue sites, respectively) and E. coli (Concentration Range: cfu/100 ml and cfu/100 ml at SAR at MWD Crossing, and SAR at Pedley Avenue sites, respectively). The Prado Park Lake site generally reported the lowest geometric means for both fecal coliform ( cfu/100 ml) and E. coli ( cfu/100 ml). Tables 2 17 and 2 18 summarize the geometric mean, median, and coefficient of variation of the fecal coliform and E. coli data for samples collected during the wet season from 2009 to More seasonal variability was observed in wet season data than dry season data. No sites consistently displayed the highest or lowest E. coli geometric means. Figures 2 2 to 2 6 illustrate the trend in single sample and geometric mean results for fecal coliform for the 2007 through 2012 dry seasons for all sites. Figures 2 7 to 2 11 illustrate the same for E. coli. Figure 2 12 illustrates the variability of bacterial indicator concentrations observed during the period for both dry and wet seasons. Superimposed on this figure are the individual wet weather event sample results. These wet weather results tend to be higher than the median bacterial indicator concentrations. Draft 2 9

22 Section 2 Triennial Report Table 2 9 Fecal coliform and E. coli (cfu/100 ml) concentrations observed at watershed wide compliance sites during the wet season Bacterial Indicator Fecal Coliform E. coli Sample Date Prado Park Lake Outlet Chino Creek at Central Avenue Mill Creek at Chino Corona Rd SAR at MWD Crossing SAR at Pedley Avenue Prado Park Lake Outlet Chino Creek at Central Avenue Mill Creek at Chino Corona Rd SAR at MWD Crossing SAR at Pedley Avenue (Week of) (WW C3) (WW C7) (WW M5) (WW S1) (WW S4) (WW C3) (WW C7) (WW M5) (WW S1) (WW S4) Regular Sample Events 22 Dec 280 1,040 4,200 3,100 3, ,900 2,200 2, Dec Jan Jan , , Jan 1,290 1,700 2,200 4,600 6,200 1,750 2,800 2,100 3,700 5, Jan ,100 2 Feb Feb Feb Feb Mar 2, , , , Storm Event Samples 14 Oct 90 9,100 3, , ,000 4, , Oct 40 3,700 4, , Oct 20 3, Oct , < < Draft

23 Section 2 Triennial Report Table 2 10 Fecal coliform and E. coli concentrations (cfu/100 ml) observed at watershed wide compliance sites during the 2010 dry season Bacterial Indicator Fecal Coliform E. coli Sample Date Prado Park Lake Outlet Chino Creek at Central Avenue Mill Creek at Chino Corona Rd SAR at MWD Crossing SAR at Pedley Avenue Prado Park Lake Outlet Chino Creek at Central Avenue Mill Creek at Chino Corona Rd SAR at MWD Crossing SAR at Pedley Avenue (Week of) (WW C3) (WW C7) (WW M5) (WW S1) (WW S4) (WW C3) (WW C7) (WW M5) (WW S1) (WW S4) 18 May , , May Jun Jun , , Jun 130 1,500 1, Jun > < > 1, Jun Jul Jul , Jul 40 4,100 1, Jul 20 2,100 2,900 2, , Aug , , Aug 200 > 690 > , Aug 350 > 490 3, > 490 2, Aug 30 2,200 4, , Aug , , Sep , , Sep 40 > 380 > 1, > 240 > 1, Sep , , Sep > 2,700 > 430 > > 1, > 1, Draft 2 11

24 Section 2 Triennial Report Table 2 11 Fecal coliform and E. coli concentrations (cfu/100 ml) observed at watershed wide compliance sites during the wet season Bacterial Indicator Fecal Coliform E. coli Sample Date Prado Park Lake Outlet Chino Creek at Central Avenue Mill Creek at Chino Corona Rd SAR at MWD Crossing SAR at Pedley Avenue Prado Park Lake Outlet Chino Creek at Central Avenue Mill Creek at Chino Corona Rd SAR at MWD Crossing SAR at Pedley Avenue (Week of) (WW C3) (WW C7) (WW M5) (WW S1) (WW S4) (WW C3) (WW C7) (WW M5) (WW S1) (WW S4) Regular Sample Events 21 Dec 68,000 6,600 3, ,000 71,000 8,800 4, , Dec ,400 > Jan Jan Jan Jan Feb Feb Feb Feb Mar Storm Event Samples 20 Nov 530 9,400 7, , ,000 5, , Nov , , Nov Nov > 150 1,100 1,900 5,100 4, ,550 2, Draft

25 Section 2 Triennial Report Table 2 12 Fecal coliform and E. coli concentrations (cfu/100 ml) observed at watershed wide compliance sites during the 2011 dry season Bacterial Indicator Fecal Coliform E. coli Sample Date Prado Park Lake Outlet Chino Creek at Central Avenue Mill Creek at Chino Corona Rd SAR at MWD Crossing SAR at Pedley Avenue Prado Park Lake Outlet Chino Creek at Central Avenue Mill Creek at Chino Corona Rd SAR at MWD Crossing SAR at Pedley Avenue (Week of) (WW C3) (WW C7) (WW M5) (WW S1) (WW S4) (WW C3) (WW C7) (WW M5) (WW S1) (WW S4) 17 May 70 4,800 > ,700 > May May Jun Jun Jun 130 > 500 4, > 3, Jun > 1,500 > 540 > > 260 > Jul 850 > 350 > Jul , , Jul > , > 160 > 140 7, Jul > > 1, Aug 9 2,300 > 3,600 2,000 4, ,600 > 4,600 > 620 > Aug 20 > 580 > 390 > 140 > 420 > 40 > 1,160 > 500 > 170 > Aug Aug Aug Sep 50 > 450 2,100 3,000 5, > 1,060 > 550 1, Sep 70 > 520 > , Sep Sep 60 > 160 > Draft 2 13

26 Section 2 Triennial Report Table 2 13 Fecal coliform and E. coli concentrations (cfu/100 ml) observed at watershed wide compliance sites during the wet season Bacterial Indicator Fecal Coliform E. coli Sample Date Prado Park Lake Outlet Chino Creek at Central Avenue Mill Creek at Chino Corona Rd SAR at MWD Crossing SAR at Pedley Avenue Prado Park Lake Outlet Chino Creek at Central Avenue Mill Creek at Chino Corona Rd SAR at MWD Crossing SAR at Pedley Avenue (Week of) (WW C3) (WW C7) (WW M5) (WW S1) (WW S4) (WW C3) (WW C7) (WW M5) (WW S1) (WW S4) Regular Sample Events 20 Dec Dec Jan Jan Jan Jan Jan , , Feb Feb Feb Feb Storm Event Samples 12 Dec 280 8, , Dec Dec Dec Draft

27 Section 2 Triennial Report Table 2 14 Fecal coliform and E. coli concentrations (cfu/100 ml) observed at watershed wide compliance sites during the 2012 dry season Bacterial Indicator Fecal Coliform E. coli Sample Date Prado Park Lake Outlet Chino Creek at Central Avenue Mill Creek at Chino Corona Rd SAR at MWD Crossing SAR at Pedley Avenue Prado Park Lake Outlet Chino Creek at Central Avenue Mill Creek at Chino Corona Rd SAR at MWD Crossing SAR at Pedley Avenue (Week of) (WW C3) (WW C7) (WW M5) (WW S1) (WW S4) (WW C3) (WW C7) (WW M5) (WW S1) (WW S4) 30 May > , Jun > > 230 1, Jun Jun , Jun 140 > 390 > > 130 > Jul 50 > 470 > , Jul Jul 40 > 80 > Jul Jul , , Aug Aug 870 > 1,200 > > 1, Aug 90 5, ,900 1, , Aug 360 1,500 > > 200 > 920 > Sep > 210 > 1,100 > 480 > 1,600 > 1, > 490 > 470 > 760 > Sep 100 2, , < ,500 5, Sep Sep 170 > 290 > > 460 > Oct , , Oct 30 > 660 > > Draft 2 15

28 Section 2 Triennial Report Table 2 15 Summary of fecal coliform concentrations (cfu/100 ml) and data variability by sample location during the 2010, 2011 and 2012 dry seasons Site N Geometric Mean Median Coefficient of Variation 1 N Geometric Mean Median Coefficient of Variation 1 N Geometric Mean Median Coefficient of Variation 1 Prado Park Lake Chino Creek Mill Cucamonga Creek SAR at MWD Crossing SAR at Pedley Ave. 20 1,378 1, Coefficient of variation was calculated using natural log transformed data Table 2 16 Summary of E. coli concentrations (cfu/100 ml) and data variability by sample location during the 2010, 2011, and 2012 dry seasons Site N Geometric Mean Median Coefficient of Variation 1 N Geometric Mean Median Coefficient of Variation 1 N Geometric Mean Median Coefficient of Variation 1 Prado Park Lake Chino Creek Mill Cucamonga Creek SAR at MWD Crossing SAR at Pedley Ave. 20 1,299 1, Coefficient of variation was calculated using natural log transformed data 2 16 Draft

29 Section 2 Triennial Report Table 2 17 Summary of fecal coliform concentrations (cfu/100 ml) and data variability by sample location during the , , and wet seasons (dry weather only) Site N Geometric Mean Median Coefficient of Variation 1 N Geometric Mean Median Coefficient of Variation 1 N Geometric Mean Median Coefficient of Variation 1 Prado Park Lake Chino Creek Mill Cucamonga Creek SAR at MWD Crossing SAR at Pedley Ave. 1 Coefficient of variation was calculated using natural log transformed data Table 2 18 Summary of E. coli concentrations (cfu/100 ml) and data variability by sample location during the , and wet seasons (dry weather only) Site N Geometric Mean Median Coefficient of Variation 1 N Geometric Mean Median Coefficient of Variation 1 N Geometric Mean Median Coefficient of Variation 1 Prado Park Lake Chino Creek Mill Cucamonga Creek SAR at MWD Crossing SAR at Pedley Ave Coefficient of variation was calculated using natural log transformed data Draft 2 17

30 Section 2 Triennial Report Figure 2 2 Time series plot of fecal coliform single sample results and geometric means for samples collected from Prado Park Lake, 2007 through 2012 dry seasons 2 18 Draft

31 Section 2 Triennial Report Figure 2 3 Time series plot of fecal coliform single sample results and geometric means for samples collected from Chino Creek, 2007 through 2012 dry seasons Draft 2 19

32 Section 2 Triennial Report Figure 2 4 Time series plot of fecal coliform single sample results and geometric means for samples collected fromm Mill Cucamonga Creek, 2007 through 2012 dry seasons 2 20 Draft

33 Section 2 Triennial Report Figure 2 5 Time series plot of fecal coliform single sample results and geometric means for samples collectedd from Santa Ana River at MWD crossing, 2007 through 2012 dry seasons Draft 2 21

34 Section 2 Triennial Report Figure 2 6 Time series plot of fecal coliform single sample results and geometric means for samples collectedd from Santa Ana River at Pedley Ave, 2007 through 2012 dry seasons 2 22 Draft

35 Section 2 Triennial Report Figure 2 7 Time series plot of E. coli single sample results and geometric means for samples collected from Pradoo Park Lake, 2007 through 2012 dry seasons Draft 2 23

36 Section 2 Triennial Report Figure 2 8 Time series plot of E. coli single sample results and geometric means for samples collected from Chino Creek, 2007 through 2012 dry seasons 2 24 Draft

37 Section 2 Triennial Report Figure 2 9 Time series plot of E. coli single sample results and geometric means for samples collected from Mill Cucamonga Creek, 2007 through 2012 dry seasons Draft 2 25

38 Section 2 Triennial Report Figure 2 10 Time series plot of E. coli single sample results and geometric means for samples collected fromm Santa Ana River at MWD crossing, 2007 through 2012 dry seasons 2 26 Draft

39 Section 2 Triennial Report Figure 2 11 Time series plot of E. coli single sample results and geometric means for samples collected from Santa Ana River at Pedley Avenue, 2007 through 2012 dry seasons Draft 2 27

40 Section 2 Triennial Report Figure 2 12 Box whisker plots of bacteria indicator concentrations from during dry weather in the dry season (red) and wet season (blue), and wet weather events (yellow points) 2 28 Draft

41 Section 2 Triennial Report Compliance Frequency Tables 2 19 and 2 20 summarize the frequency of compliance with single sample and geometric mean Basin Plan water quality objectives for fecal coliform (single sample maximum: 400 cfu/ml; geometric mean: 200 cfu/ml) and proposed water quality objectives for E. coli (geometric mean maximum: 126 cfu/ml) during the dry seasons of 2010, 2011 and In general, compliance rates have remained steady for both single sample and geometric mean criteria. Chino Creek and Mill Cucamonga Creek exceeded the geometric mean criteria for both fecal coliform and E. coli 100 percent of the time during dry season sampling. However, Mill Cucamonga Creek did show a small decrease in single sample exceedence from the 2010 to 2012 season. Tables 2 21 and 2 22 summarize the frequency of compliance with single sample and geometric mean Basin Plan water quality objectives for fecal coliform (single sample maximum: 400 cfu/ml; geometric mean: 200 cfu/ml) and proposed water quality objectives for E. coli (geometric mean maximum: 126 cfu/ml) during the wet seasons of , , and For the single sample data, the compliance frequency was calculated separately for dry and wet weather samples. Dry weather samples tended to have a lower frequency of exceedence than wet weather samples. For the geometric mean data, geomeans were calculated for dry and wet weather samples combined, where five or more samples were taken in a five week period. No particular trend in wet season geomean compliance was evident for either fecal coliform or E. coli. Table 2 19 Compliance frequency for fecal coliform during the 2010, 2011, and 2012 dry seasons (as compared to existing Basin Plan objectives for fecal coliform) Site Single Sample Criterion Exceedence Frequency (%) Geometric Mean Criterion Exceedence Frequency (%) Prado Park Lake 5% 10% 15% 6% 25% 31% Chino Creek 55% 35% 70% 100% 100% 100% Mill Cucamonga Creek 95% 60% 70% 100% 100% 100% SAR at MWD Crossing 35% 15% 40% 63% 44% 81% SAR at Pedley Ave. 10% 20% 20% 19% 50% 50% Table 2 20 Frequency of compliance with proposed geometric mean water quality objectives for E. coli during the 2010, 2011, and 2012 dry seasons Site Geometric Mean Criterion Exceedance Frequency (%) Prado Park Lake 44% 0% 25% Chino Creek 100% 100% 100% Mill Cucamonga Creek 100% 100% 100% SAR MWD Crossing 75% 56% 94% SAR at Pedley Ave. 25% 50% 50% 1 Evaluation of compliance based on proposed geometric mean water quality objectives (See SWQTF_IV.html) Draft 2 29

42 Section 2 Triennial Report Table 2 21 Compliance frequency for fecal coliform during the , and wet seasons Site Dry Weather Single Sample Criterion Exceedence Frequency (%) Wet Weather Dry Weather Wet Weather Dry Weather Wet Weather Geometric Mean Criterion Exceedence Frequency (%) Prado Park Lake 46% 50% 15% 50% 7% 0% 86% 29% 0% Chino Creek 33% 100% 0% 100% 8% 50% 71% 14% 82% Mill Cucamonga Creek SAR at MWD Crossing SAR at Pedley Ave. 55% 75% 31% 100% 43% 0% 82% 43% 73% 0% 67% 18% 75% 0% 33% 43% 14% 0% 8% 100% 10% 80% 0% 100% 71% 71% 55% Table 2 22 Frequency of compliance with proposed geometric mean water quality objectives for E. coli during the , , and wet seasons Site Geometric Mean Criterion Exceedence Frequency (%) Prado Park Lake 100% 57% 45% Chino Creek 100% 100% 100% Mill Cucamonga Creek 91% 86% 100% SAR at MWD Crossing 71% 86% 0% SAR at Pedley Ave. 100% 100% 100% 1 Evaluation of compliance based on proposed geometric mean water quality objectives (See SWQTF_IV.html) Comparison to Previous Findings Figures 2 13 and 2 14 display the dry season annual geometric mean for fecal coliform and E. coli from 2007 to The annual geometric mean at the Prado Park Lake site has been below the WLA for fecal coliform during all seasons of dry weather sampling. The remaining compliance monitoring sites saw an overall decrease in the annual geometric mean for fecal coliform from 2007 to However, while the first three years of dry season sampling were characterized by a steady annual decline in the annual geometric mean, the subsequent three years were more variable, with some stations seeing an increase in fecal coliform concentrations from one year to the next Draft

43 Section 2 Triennial Report The annual geometric mean for E. coli has remained generally constant at all compliance stations during the six seasons of dry season monitoring, with no stations reporting a marked increase or decrease in concentration from 2007 to With the exception of the 2009 season, Prado Park Lake has generally remained below the E. coli WLA (on an annual basis) during the dry season. Figures 2 15 and 2 16 illustrate the dry weather wet season annual geometric means for fecal coliform and E. coli from the season through the season. In general, no trends in wet season data results have been observed from 2007 to On an annual basis, the Prado Park Lake site and both Santa Ana River sites have generally been below the WLA for fecal coliform during dry weather in the wet season. However, with the exception of Prado Park Lake and Santa Ana River at MWD Crossing in , no site has met the WLA for E. coli on an annual basis during the last three seasons of wet season sampling. Draft 2 31

44 Section 2 Triennial Report Figure 2 13 Fecal coliform dry season geometric means for Figure 2 14 E. coli dry season geometric means for Draft

45 Section 2 Triennial Report Figure 2 15 Fecal coliform wet season dry weather seasonal geometric means for Figure 2 16 E. coli wet season dry weather seasonal geometric meanss for Draft 2 33

46 Section 2 Triennial Report 2.4 Compliance with Load Allocations The MSAR Bacterial Indicator TMDL contains LAs for agricultural runoff discharges and natural sources. These LAs are the same as the WLAs that have been established for urban dischargers and CAFOs. Section 2.3 summarizes these allocations. The following sections summarize the TMDL related implementation activities associated with the LAs linked to agricultural runoff and natural sources. As noted previously, the watershed wide compliance monitoring program samples five locations on a regular basis, which includes natural sources during dry and wet weather and agricultural discharges during runoff events. Monitoring specific to agriculture discharges has also occurred during wet weather. Monitoring that targets natural sources has not occurred during the past three years. The following sections provide information on FIB concentrations observed during agricultural discharge monitoring Agricultural Sources Agricultural dischargers implemented a source evaluation program in This program included wet weather sampling at selected sites in the MSAR watershed where agricultural activity occurs. Sampling occurred during two separate storm events at four sites in The findings from this sampling effort are reported in the 2010 Triennial Report (SAWPA 2010a). No additional wet weather sampling has occurred in relation to sources to agricultural discharger runoff since the 2008 sampling event. Instead, during the reporting period agricultural dischargers worked collaboratively with the RWQCB to finalize the mapping of agricultural lands in the MSAR watershed. Based on work completed by Aerial Information Systems, agricultural lands represent approximately 7 percent of the watershed. The completion of this work will support future efforts to manage runoff from agricultural lands Natural Sources The MSAR Bacterial Indicator TMDL establishes a LA for natural sources of bacterial indicators. The allocation for this source is the same as that established for other LA and WLA sources. To date, efforts to develop understanding regarding the relative contribution of bacterial indicators from natural sources has been limited to indirect analyses, e.g., identifying the degree of contribution of bacterial indicators from unaccountable sources. These findings were first reported in Section 3 of each County s CBRP (RWQCB 2012a, 2012b). Recent analyses of bacterial indicator data from selected watershed wide compliance sites coupled with an updated compliance analysis from recent Tier 1 source evaluation activities suggest that natural sources of bacterial indicators may be important contributors to bacterial indicator concentrations at the watershed wide compliance sites. Section 3 of this report provides additional information regarding the updated compliance analyses and Section 4 provides a summary of findings and recommendations that include looking further at potentially uncontrollable bacterial indicator sources as part of on going CBRP implementation Draft

47 Section 3 CBRP Tier 1 Source Evaluation Report 3.1 Introduction As stated in Section 1, the CBRP is designed to provide a comprehensive plan for attaining the MS4 permit s water quality based effluent limits for the MSAR Bacterial Indicator TMDL by integrating existing control programs and efforts with new permit mandates and other additional activities necessary to address controllable urban sources of bacterial indicators. Riverside and San Bernardino County MS4 permittees implemented Tier 1 source evaluation activities described in this section as the first key step in the implementation of the CBRP. Following is a brief overview of the CBRP framework under which these activities were conducted CBRP Framework The applicability of the CBRP is limited to the following circumstances (see CBRP Section 1.5): Bacterial Indicator Sources The CBRP is designed to mitigate controllable urban sources of bacterial indicators that cause non attainment of bacterial indicator water quality objectives at the watershed wide compliance sites. Jurisdiction This CBRP only applies to the MS4 Permittees named in the TMDL: - Riverside County: Cities of Corona, Eastvale, Jurupa Valley, Norco, and Riverside and the County of Riverside - San Bernardino County: Cities of Chino, Chino Hills, Fontana, Montclair, Ontario, Rancho Cucamonga, Rialto, and Upland and the County of San Bernardino Hydrologic Condition This CBRP applies only to urban discharges from the MS4 during dry weather conditions that have the potential to impact the downstream watershed wide compliance monitoring site. Seasonal Condition This CBRP applies only to urban discharges from the MS4 during the period April 1st through October 31st. Per the CBRPs developed for Riverside and San Bernardino Counties, compliance with the MSAR Bacteria TMDL s wasteload allocations can be measured in several ways: Water quality objectives are attained at the watershed wide compliance sites established as part of the implementation of the MSAR Bacterial Indicator TMDL. If not attained, then it must be demonstrated that bacterial indicators from controllable urban sources are not the cause of non attainment. Compliance with controllable urban source wasteload allocations demonstrated from specific MS4 facilities, e.g., sampling demonstrates that controllable urban sources discharged from MS4 outfalls or drains are in compliance with the wasteload allocation during dry weather conditions. Draft 3 1

48 Section 3 CBRP Tier 1 Source Evaluation Report MS4 facilities, e.g., outfalls, are dry, or that flows from these MS4 outfalls are infiltrating prior to connection with impaired waterbodies, and thus not contributing to dry weather flow (DWF) to downstream waters CBRP Source Evaluation Activities Each County is implementing the CBRP using a stepwise project approach that includes three distinct steps (See CBRP Section 2.1). The primary purpose of each step is as follows: Step 1 Identify, Prioritize, and Evaluate MS4 Dry Weather Flow Sources This step includes implementation of non structural BMPs and inspection activities. These inspections, or urban source evaluation investigations are to occur systematically in each area draining to a watershed wide compliance site. Step 2 Evaluate and Select Structural BMP Projects Where it is determined during Step 1 that a structural BMP project is needed to comply with the urban wasteload allocation, Step 2 focuses on the development of that project through implementation of the budget/planning, design and permitting steps associated with a capital improvement project. Step 3 Construct Structural BMP Projects This step focuses on construction of a structural BMP project that has received all necessary approvals obtained through completion of step 2 above. CBRP Step 1, as described above, includes a number of source evaluation or inspection activities designed to identify controllable MS4 DWF sources and their contributions to elevated bacterial indicator concentrations at downstream watershed wide compliance sites. The first of these activities is a Tier 1 source evaluation 1. This activity is designed to gather sufficient DWF and bacterial indicator data to provide the basis for prioritizing MS4 drainage areas within the MSAR watershed for subsequent inspection and, where necessary, development of alternatives to mitigate controllable urban sources of bacterial indicators. Ultimately, CBRP Step 1 activities will be implemented over an extended period so that MS4 outfalls in each prioritized drainage area can be properly investigated and evaluated for mitigation of controllable sources. The following sections provide the methods and results from the Tier 1 source evaluation activities that were completed in Specifically, Section 3.2 describes the monitoring program implemented to gather data from Tier 1 sites. Section 3.3 summarizes the data results from each of the sampled Tier 1 sites. Section 3.4 provides the prioritization of drainage areas within the MSAR watershed for subsequent inspection and potential mitigation activities based on selected ranking criteria; and 1 Per each County s CBRP, Tier 1 sites are defined as locations where urban sources of dry weather flow may directly discharge to a downstream watershed wide compliance site. 3 2 Draft

49 Section 3 CBRP Tier 1 Source Evaluation Report Section 3.5 evaluates the potential effectiveness of DWF and/or mitigation of controllable bacterial indicator sources in the subwatersheds draining to the watershed wide compliance sites. Section 3.6 evaluates the potential role of non MS4 sources of bacteria within receiving waterbodies. 3.2 Source Evaluation Monitoring The CBRP inspection program was initiated in May 2012 with Tier 1 source evaluation monitoring of outfalls in all major MS4 drainage areas draining to a downstream watershed wide compliance site (See Section for a description of these sites; also see Attachments A 1 and A 2 of the MSAR Bacterial Indicator TMDL Monitoring Plan 2 ). Dry weather monitoring was performed weekly for 10 consecutive weeks through the second week in July Samples were analyzed for TSS and E. coli concentrations, presence or absence of the human Bacteroides marker, and field measured parameters. The data collected provide a basis for prioritization of future CBRP inspection program activities. The following sections provide additional details regarding source evaluation monitoring activities Monitoring Locations Tier 1 source evaluation monitoring occurred at all major MS4 outfalls in each of the subwatersheds draining to a watershed wide compliance site. In total, 34 Tier 1 MS4 outfalls were monitored covering multiple jurisdictions (Table 3 1). Some of the Tier 1 monitoring sites were also sampled in as part of implementation of the Urban Source Evaluation Program (USEP) 3. Desktop GIS tools and aerial photographs were used to identify additional locations for Tier 1 monitoring that were not monitored during previous USEP monitoring activities. Prior to conducting Tier 1 monitoring activities in 2012, Riverside County Flood Control & Water Conservation District (RCFC&WCD) and San Bernardino County Flood Control District (SBCFCD) staff visited the proposed sites to confirm the locations of MS4 outfalls and assess the feasibility for collecting samples. In some cases, site locations were adjusted based on field reconnaissance surveys. Figure 3 1 shows the locations of all Tier 1 source evaluation monitoring sites. 2 The TMDL Monitoring Plan provides information regarding each of these samples sites in Attachment A 1 (Riverside County) and Attachment A 1 (San Bernardino County). The Monitoring Plan is available at santa ana river watershed tmdl taskforce/). 3 The MSAR Bacterial Indicator TMDL required permitted MS4 discharges to develop the USEP within six months after TMDL adoption or by November 30, Per Section 4.1 of the TMDL, the purpose of the USEP was to identify specific activities, operations, and processes in urban areas that contribute bacterial indicators to MSAR waterbodies. The RWQCB approved the USEP developed by the MS4 permittees April 18, 2008 (RWQCB Resolution R ). The inspection activities identified in the CBRP (adopted February 15, 2012) replaced the requirements of this 2008 adopted USEP. Draft 3 3

50 Section 3 CBRP Tier 1 Source Evaluation Report Figure 3 1 CBRP Tier 1 source evaluation monitoring sites 3 4 Draft

51 Section 3 CBRP Tier 1 Source Evaluation Report Table 3 1 CBRP Tier 1 source evaluation monitoring sites TMDL Waterbody County Primary MS4 Site ID Description Chino Creek Mill Cucamonga Creek Santa Ana River T1 SACH Chino Storm Drain to San Antonio Channel Chino T1 PPLN Pipeline Ave 84" RCP outlet under bridge T1 YRBA Yorba Ave extension to Chino Creek San Bernardino T1 CYP Cypress Channel T1 BRSC Boys Republic South Channel Chino Hills T1 CCCH Carbon Canyon Creek Channel T1 LLSC Lake Los Serranos Channel T1 CBLD Big League Dreams Outfall Los Angeles Pomona CHINOCRK Chino Creek upstream of San Antonio Channel T1 CAPT Cucamonga Airport Drive T1 CNRW Cucamonga North Runway T1 CFRN Cucamonga Francis Ave San Bernardino Ontario T1 WCUC West Cucamonga Creek T1 SR60 Cucamonga Creek above SR 60 T1 CHRIS Chris Basin Outflow T1 CLCH County Line Channel Riverside Eastvale T1 EVLA Eastvale MPD Line A T1 EVLB Eastvale MPD Line B San Bernardino Rialto T1 RISD Rialto Storm Drain SW of Riverside Avenue T1 WLSD Wilson Storm Drain Riverside Riverside Jurupa Valley Eastvale T1 EVAN City of Riverside Outfall (Lake Evans) T1 BXSP Box Springs Channel T1 RBDX City of Riverside Outfall at Rubidoux T1 MCSD Magnolia Center SD T1 PHNX Phoenix Storm Drain T1 SNCH Sunnyslope Channel T1 IDST City of Riverside Outfall (Industrial/Freemont) T1 ANZA Anza Drain T1 CREST City of Riverside Outfall (Crest/Ontario) T1 64ST 64th Street Storm Drain T1 SSCH San Sevaine Channel T1 DAY Day Creek T1 EVLD Eastvale MDP Line D T1 EVLE Eastvale MDP Line E Draft 3 5

52 Section 3 CBRP Tier 1 Source Evaluation Report Data Collection SBCFCD staff collected field measurements and water quality samples at San Bernardino County sites; RCFC&WCD staff collected the same data Riverside County sites. CDM Smith coordinated the activities of the sample teams and the submittal of samples to the appropriate laboratories for analysis. Sample teams visited each of the Tier 1 sites once each week for 10 consecutive weeks beginning the week of May 6, 2012 and ending the week of July 8, Orange County Public Health Laboratory analyzed samples for E. coli and TSS concentrations; the Orange County Water District laboratory analyzed for presence/absence of the human Bacteroides marker. The MSAR Bacteria TMDL Quality Assurance Project Plan (QAPP) provides additional information regarding sampling and laboratory analysis methods 4. Tier 1 field measurements included the collection of data temperature, conductivity, ph, dissolved oxygen, turbidity and flow. In many instances (134 of 340 sample events), no measurable DWF was present during a sampling event. Table 3 2 summarizes the of a DWF observation at each of the Tier 1 sites. Table 3 2 Summary of DWF observations by sample site DWF Never Observed (0 Events) Sites with Variable DWF Observations (Numbers in Columns Indicate Frequency of Sample Events) DWF Always Observed (10 Events) T1 RISD T1 EVAN T1 RBDX T1 IDST T1 CREST T1 64ST T1 CBLD T1 CFRN T1 CLCH T1 WLSD T1 SR60 T1 PHNX T1 SACH T1 WCUC T1 LLSC T1 PPLN T1 DAY T1 EVLB T1 CYP T1 BRSC T1 CCCH T1 YRBA T1 CHINOCRK T1 CAPT T1 CNRW T1 CHRIS T1 EVLA T1 BXSP T1 MCSD T1 SNCH T1 ANZA T1 SSCH T1 EVLD T1 EVLE Data Management CDM Smith and SAWPA maintain a file of all laboratory and field data records (e.g., data sheets, chain of custody forms) as required by the project QAPP. CDM entered all field measurements and laboratory analysis results into the project database that is compatible with guidelines and formats established by the California SWAMP program. This database is periodically submitted to SAWPA for incorporation into the Santa Ana Watershed Data Management System (SAWDMS). Prior to submittal to SAWPA, CDM Smith completes a QA/QC review of the data, as required by the project QAPP. 4 The QAPP is available at santa ana river watershed tmdl taskforce/) 3 6 Draft

53 Section 3 CBRP Tier 1 Source Evaluation Report 3.3 Tier 1 Source Monitoring Results Dry Weather Flow Regular DWF exist in many MSAR waterbodies. Sources of DWF include: Effluent from publicly owned treatment works (POTWs) Turnouts of imported water by Metropolitan Water District (MWD) Well blow offs Water transfers Groundwater inputs Other authorized discharges (as defined by permit) Urban water waste from excess irrigation and other outdoor water uses Non permitted discharges Each of these sources of runoff has a different pathway and potential to transport bacteria to receiving waterbodies. Thus, it is important to understand the relative role of each of these categories of DWF. Additionally, some sources of bacteria are not directly related to DWF inputs such as birds and other wildlife within waterbodies, re suspension of bacteria in channel bottom sediment, air deposition, and transient encampments. DWF measurements were collected during site visits for 10 consecutive weeks at the 34 Tier 1 monitoring sites. The rate of DWF from MS4 drainage areas in the MSAR watershed varies significantly (Table 3 3). At some MS4 outfalls, higher DWF rates are associated with known areas of rising groundwater in the watershed. Better water quality at these outfalls is frequently in compliance with the E. coli WLA. MS4 outfalls with no or minimal DWF were typically associated with smaller urban MS4 drainage areas with some unlined watercourses prior to reaching the TMDL waterbodies. In such cases, it may be more effective to manage DWF near the outfall in small scale BMPs, as opposed to embarking on rigorous Tier 2 inspection program activities. Comparing 2007 (USEP) and 2012 (CBRP Inspection Program) data from the same sites showed a general decline in DWF from MS4 drainage areas (Figure 3 2). This may be the result of better water management by residents and businesses as a result of water purveyor and stormwater agency education and outreach, or could be a side effect of the economic recession. Draft 3 7

54 Section 3 CBRP Tier 1 Source Evaluation Report Table 3 3 Descriptive statistics for dry weather flow (cfs), all Tier 1 sites Site ID N Min Max Mean SD T1 ANZA T1 BRSC T1 BXSP T1 CAPT T1 CCCH T1 CFRN NA T1 CHINOCRK T1 CHRIS T1 CLCH NA T1 CNRW T1 CYP T1 DAY T1 EVLA T1 EVLB T1 EVLD T1 EVLE T1 LLSC T1 MCSD T1 PHNX T1 PPLN T1 SACH T1 SNCH T1 SR T1 SSCH T1 WCUC T1 WLSD NA T1 YRBA Draft

55 Section 3 CBRP Tier 1 Source Evaluation Report Figure 3 2 Change in mean DWF measurements from 2007 USEP to 2012 Tier 1 Inspection Program In addition to typical DWF sources within MS4 drainage areas, it was necessary to obtain information regarding other non MS4 sourcess of DWF in receiving waterbodies. The primary non MS4 source of DWF in the TMDL waterbodies is POTW effluent. In recent years, POTW effluent discharge rates to Chino Creek, Cucamonga Creek, and the Santa Ana River have declined as a result of reduced outdoor water use from the economic recession, and increased recycling of POTW effluent to serve indirect and direct reuse projects. For Day Creek, a flood control channel lining project was under construction during the 10 week monitoring District (JCSD) to minimize well blow offs to Day Creek during the construction period to not period in May July of RCFC&WCD requested Jurupa Community Services overwhelm the temporary stream diversion that was in place just downstream of the Tier 1 monitoring site. Section 3.5 will evaluate the water quality impacts of reduced discharge of clean water within the receiving waterbodies Water Quality Analysis of E. coli concentration data from the CBRP Tier 1 source evaluation monitoring showed that bacterial water quality in dry weather flow at MS4 outfalls is highly variable, but typically exceeds the WLA for E. coli of 113 Most Probable Number (MPN)/100 ml (Figure 3 3). Some MS4 drainages had significantly greater E. coli concentration than others, which influences the prioritization of MS4 drainage areas for future CBRP implementation activities, as described in the following section. Comparison of dry season monitoring data from the 2012 Tier 1 source evaluation with the 2007 USEP showed significant increases in E. coli concentration at some sites, such as Chris Basin, County Line Channel and San Sevaine Channel and decreases at some sites, such as Anza Drain, Cypress Channel, and Box Springs Channel (Figure 3 4). Generally, outfalls that showed increases in concentration showed decreases in dry weather flowrate. Data from 9 of 24 Tier 1 source evaluation monitoring sites that were not part of the USEP were foundd to have highh E. coli concentrations with 10 week geomeans exceeding 1,000 MPN/100 ml at T1 PPLN, T1, YRBA, T1 CAPT, T1 CNRW, T1 CFRN, T1 CFRN, T1 EVLA, T1 EVLB, T1 EVLD, and T1 EVLD. Draft 3 9

56 Section 3 CBRP Tier 1 Source Evaluation Report Figure 3 3 Box whisker plots of E. coli concentration from Tier 1 monitoring sites (2012) Figure 3 4 Change in E. coli concentration from 2007 USEP to 2012 Tier 1 Inspection Program E. coli concentration was compared with field measured parameters to assess any statistically significant relationships (Table 3 4). This analysis did not identify any strong correlations between any of the field measured parameters and E. coli concentration Draft

57 Section 3 CBRP Tier 1 Source Evaluation Report Table 3 4 Correlation analysis between E. coli concentrationss and TSS, temperature, and DWF for all Tier 1 sites Comparison E. coli vs.. TSS Temperature Dry Weather Flow Pearson s r coefficient Degrees of freedom (n 2) Student t statistic In addition to E. coli,, the human Bacteroides marker was evaluated in samples from the Tier 1 source evaluation monitoring. The analytical method provides semi quantitative results, however; for this analysis, results were simplified to presence or absence of human Bacteroides. Figure 3 5 summarizes the frequency of human Bacteroides presence at sites with one or more detections over the ten week monitoring period (14 of 34 sites). Figure 3 6 shows that similar resultss were found a sites also monitored during the USEP with one significant exception; Bacteroides results from Box Springs Channel verified that a previously identified source of human bacteria had been successfully addressed in 2008 by RCFC&WCD with the correction of the restroom cross connection (see CBRP Section 3.5.3) p value Significant at p < 0.05? Yes Yes No Figure 3 5 Persistence of human Bacteroides marker for Tier 1 sites with at least one detection in the 2012 dry season Draft 3 11

58 Section 3 CBRP Tier 1 Source Evaluation Report Figure 3 6 Change in persistence of human Bacteroides from 2007 USEP to 2012 Tier 1 Inspection Program The relationship between human Bacteroides detection and bacterial indicator data shows the effectiveness of using bacterial indicators to assess potential health risk of recreational users. Table 3 5 provides the results of the Student t test showing a statistically significant difference in E. coli concentration exists in samples that did or did not coincide with a detection of human Bacteroides. The geomean of E. coli concentration was approximately 3500 percent greater in samples where a human source was detected (Figure 3 7). Thus, the presence of human sources may be integral to bacterial indicator concentration at MS4 outfalls. This same analysis for a smaller set of monitoring sites did not find a statistically significant difference based onn the 2007 dry season USEP data analysis. Table 3 5 Results of Student T Test comparing E. Coli geometric mean concentrations to detection of human specific Bacteroides markers for All Tier 1 sites E. coli Geomean N P value (MPN/100 ml) Human Marker Detected 41 Human Marker Not Detected Draft

59 Section 3 CBRP Tier 1 Source Evaluation Report Figure 3 7 Box Whisker plots of E. coli in samples with and without detection of human Bacteroides marker for all Tier 1 sites 3.4 Prioritization Analysis Future implementation of the CBRP requires prioritization of MS4 drainage areas to focus Tier 2 inspection activities. The following sections describe the methodology used to prioritize MS4 drainage areas based on the results of Tier 1 of the CBRP inspection program. This prioritization was performed on the complete set of Tier 1 monitoring locations, including 17 sites in San Bernardino County, 16 sites in Riverside County, and 1 site in Los Angeles County. Accordingly, the results are intended to address the watershed scale, which involves many different jurisdictions, all of which are members of the Task Force Prioritization Criteria The relative rankings from each of the following four criteria create a composite ranking for the Tier 1 MS4 outfall drainage areas: Average DWF rate (cfs) Geometric mean of E. coli concentration (MPN/100 ml) Draft 3 13

60 Section 3 CBRP Tier 1 Source Evaluation Report Frequency of human Bacteroides detection (%) Risk of exposure rating (low or high) with regards to recreation activity The first three criteria are computed from data collected in the 10 weeks of consecutive monitoring at each Tier 1 monitoring location in May through July Days with no flow were included in the average DWF rate calculation as zeros. Data from collected samples only is used for the calculation of geometric mean of E. coli concentration. For the risk of exposure criteria, each site was assigned either a low or high rating based on the following principles: Low completely concrete lined MS4 system that outfalls to a concrete lined receiving waterbody segment. High natural channel is present anywhere within an MS4 system, or an outfall that discharges to a natural channel segment of a receiving waterbody Prioritization Factor Analysis The composite bacteria prioritization score was computed by applying weighting factors (W f ) to the relative ranking (R r ) for each criteria. Relative rank is determined by dividing a sites rank (ascending order basis; i.e. high values given high ranks) by the total number of sites (n=34). This serves to normalize the relative rank on a scale of 0 to 1. For the risk of exposure criteria, sites with high risk are given a relative rank of 1.0 and sites with low risk are given a relative rank of 0.0. Weighting factors used in the prioritization were 0.3 each for average dry weather flow rate, geometric mean of E. coli concentration, and frequency of human Bacteroides detection, and 0.1 for risk of exposure. Table 3 6 provides results for the relative rank for each of the 34 Tier 1 monitoring locations for each of the four prioritization criteria. The composite bacteria prioritization score (BPS) is then computed as follows; 100 ; / Results for the composite BPS, also shown in Table 3 6, were categorized as high priority, low priority, and areas found to be hydrologically disconnected (Figure 3 8). Figure 3 9 maps these three priority categories for each of the Tier 1 monitoring sites. The distribution of high priority MS4 drainage areas includes multiple outfalls to each of the monitored waterbodies. In fact, the top three BPSs were computed for MS4 drainage areas that are not upstream of any compliance monitoring site (T1 ELVE, T1 EVLD, and T1 CYP) Draft

61 Section 3 CBRP Tier 1 Source Evaluation Report Table 3 6. Relative rank results for each prioritization criteria and composite bacteria Site E. coli Geomean Relative Rank (0 100) for Prioritization Criteria Bacteroides Persistence Mean Flow Risk of Exposure Composite Bacteria Prioritization Score T1 EVLD T1 EVLE T1 CYP T1 EVLB T1 ANZA T1 CAPT T1 CHRIS T1 SSCH T1 EVLA T1 CHINOCRK T1 BRSC T1 BXSP T1 PHNX T1 WLSD T1 YRBA T1 SNCH T1 CLCH T1 CCCH T1 DAY T1 MCSD T1 PPLN T1 LLSC T1 CFRN T1 CNRW T1 SACH T1 SR T1 WCUC T1 64ST T1 CBLD T1 CREST T1 EVAN T1 IDST T1 RBDX T1 RISD Draft 3 15

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63 Section 3 CBRP Tier 1 Source Evaluation Report Bacteria Prioritization Score T1 EVLD T1 EVLE T1 CYP T1 EVLB T1 ANZA T1 CAPT T1 CHRIS T1 SSCH T1 EVLA T1 CHINOCRK T1 BRSC T1 BXSP T1 PHNX T1 WLSD T1 YRBA T1 SNCH T1 CLCH T1 CCCH T1 DAY T1 MCSD T1 PPLN T1 LLSC T1 CFRN T1 CNRW T1 SACH T1 SR60 T1 WCUC T1 64ST T1 CBLD T1 CREST T1 EVAN T1 IDST T1 RBDX T1 RISD High Priority Low Priority No Dry Weather Flow Figure 3 8 Bacteria Prioritization Score for all Tier 1 sites Draft 3 17

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65 Section 3 CBRP Tier 1 Source Evaluation Report Figure 3 9 Map of bacteria prioritization category for all Tier 1 sites Draft 3 19

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67 Section 3 CBRP Tier 1 Source Evaluation Report 3.5 Bacterial Indicator Source Evaluation Analysis Background & Purpose The CBRP Tier 1 source evaluation monitoring provides new data on MS4 sources of bacterial indicators in the MSAR watershed. These data were used to improve the relative source contribution analysis previously prepared for the CBRP (Section 3). The CBRP compliance analysis had anticipated an update to the relative source contribution analysis as a result of implementation of the inspection program for a larger set of MS4 outfalls identified for Tier 1 monitoring. Accordingly, the MS4 permittees intend for the following sections this report to serve as an update to the CBRP compliance analysis. Alternative approaches were considered for demonstrating how implementation of the CBRP would achieve compliance with urban source WLAs: Alternative 1 Demonstrate that implementation of the CBRP would result in achieving the WLAs at every outflow to a receiving waterbody. This approach can be achieved by either reducing E. coli concentrations at flowing MS4 outfalls to 113 MPN/100 ml or eliminating DWF from the majority of urban area draining to each outfall. Alternative 2 If data demonstrate that receiving water impairment is potentially caused by the MS4, then demonstrate sufficient reduction in controllable human sources of bacterial indicator loads in DWF from MS4 facilities to not cause an exceedence of the E. coli water quality objective at downstream watershed wide compliance monitoring sites. The MS4 permittees plan to use the second alternative approach to evaluate compliance with the MSAR Bacterial Indicator TMDL. This approach allows for a watershed wide assessment of bacterial water quality in downstream receiving waterbodies. All three of these waterbodies are effluent dominated in the dry season, which involves a greater proportion of POTW effluent than other dry weather flow sources. The POTW effluent provides a source of clean water to dilute inputs from MS4 outfalls. Despite this condition, compliance monitoring data show water quality objectives are being exceeded. Further bacterial indicator reduction of controllable sources may be necessary to achieve compliance with the TMDL Source Evaluation Analysis Methodology Sources of bacteria during dry weather conditions include MS4 discharges as well as non MS4 sources such as wildlife and in stream growth. This source evaluation estimates the relative role of MS4 sources in downstream receiving waterbody bacterial indicator concentrations. Data collected at Tier 1 monitoring sites represent most of DWF from MS4 facilities to downstream compliance sites. The bacterial indicator concentrations in the blend of MS4 inputs and clean POTW effluent (C blended ) was compared with downstream bacterial indicator concentrations (C comp ) to assess the potential role of other non MS4 sources to an impaired waterbody. The blended concentration is a function of MS4 inputs of flow (Q inflow ) and bacterial indicator concentrations (C inflow ) and POTW effluent flow (Q effluent ), as follows: Draft 3 21

68 Section 3 CBRP Tier 1 Source Evaluation Report This type of analysis characterizes the relative role of different flow sources in the watershed on downstream bacterial indicator concentrations. An important outcome of this analysis is the identification of the level of bacterial indicators (e) at the compliance sites that cannot be explained by MS4 inflows (referred to as unaccounted for sources ). The presence of an unbalanced set of inputs and outputs in relation to downstream bacterial indicator levels is not surprising, given the potential for increases in bacteria indicator levels from illegal and illicit discharges, direct input from wildlife, air deposition, transient encampments, environmental growth, or resuspension, or decreases in bacterial indicator levels due to environmental decay or settling. This approach is equivalent to the analysis in the CBRP; however, in this report results are computed as concentrations instead of loads. This adjustment to the methodology was made to provide results that are more readily compared with the concentration based WLA Sub Watershed Analysis Results Results of the source evaluation analysis for each of the impaired waterbodies are provided in the following sections. Each section contains a comparable series of figures including: Schematic of MS4 and POTW inflows to the waterbody, key retention facilities, and downstream compliance monitoring sites Weekly time series of blended (MS4 + POTW) concentration compared with concentration at the downstream compliance monitoring site Proportion of each Tier 1 MS4 drainage area in the estimated blended bacterial indicator concentration Chino Creek Subwatershed DWF from most of the Chino Creek subwatershed does not reach the downstream compliance site. DWF in San Antonio Channel, the largest tributary to Chino Creek, is diverted into a series of retention basins that span from San Antonio Dam to Brooks Basin in the City of Montclair. Downstream of the diversion to Brooks Basin, there are nine MS4 outfalls to Chino Creek (Figure 3 10). The source evaluation analysis for the Chino Creek watershed involved computation of a blended bacterial indicator concentration from these MS4 outfalls to Chino Creek and POTW effluent from IEUA s Carbon Canyon WRP. For the seven consecutive weeks when both upstream (Tier 1 monitoring) and downstream (watershed wide compliance monitoring) bacteria indicator data were collected, the estimated concentration in the MS4 and POTW blend was compared with actual concentrations (Figure 3 11). Figure 3 12 shows that the two high priority MS4 drainage areas account for 83 percent of the estimated blended bacterial indicator concentration in Chino Creek, including: T1 CHINOCRK, mostly from the City of Pomona underground MS4 system T1 BRSC, Boys Republic South Channel DWF from Carbon Canyon Creek Channel has a higher flow rate and lower bacterial indicator concentration due to the influence of rising groundwater. Inflows from this MS4 drainage area to Chino Creek serve to reduce the blended bacterial indicator concentration under current conditions Draft

69 Section 3 CBRP Tier 1 Source Evaluation Report Figure 3 10 Schematic showing bacteria and DWF inflows to Chino Creek in relation to downstream compliance monitoring site. (MS4 sources are in red shaded boxes; POTW effluent sources are shaded green. High priority MS4 drainages have a double border. Values for criteria used in the prioritization analysis is included next to each inflow box) Draft 3 23

70 Section 3 CBRP Tier 1 Source Evaluation Report Figure Comparison of estimated blended E. colii concentration of MS4 and clean POTW effluent with downstream watershed widee compliance monitoring data for Chino Creek at Central Avenuee Figure 3 12 Potential for individual MS4 drainage areas to contribute to exceedences of the WLA in estimated blended concentration att Chino Creek at Central Avenue 3 24 Draft

71 Section 3 CBRP Tier 1 Source Evaluation Report Cucamonga Creek Subwatershed DWF from most of the Cucamonga Creek subwatershed does not reach the downstream compliance site. DWF from Cucamonga Creek and Upper Deer Creek upstream of the I 10 Freeway is retained in the Turner Basins. Downstream of the I 10 Freeway the Ely Basins retains all DWF from West Cucamonga Creek. Downstream of these retention basins, there are nine major MS4 outfalls to Cucamonga Creek (Figure 3 13). The source evaluation analysis for the Cucamonga Creek watershed involved computation of a blended bacterial indicator concentration from these MS4 outfalls to Cucamonga Creek and POTW effluent from IEUA s RP1. For the seven consecutive weeks when both upstream (Tier 1 monitoring) and downstream (watershed wide compliance monitoring) bacteria indicator data was collected, the estimated concentration in the MS4 and POTW blend was compared with actual concentrations (Figure 3 14). The analysis shows a close correlation between estimated blended concentration and data from the downstream watershed wide compliance site. Thus, it may be inferred that in stream sources of bacteria are small relative to MS4 inputs, or that decay by exposure to UV light offsets non MS4 sources of bacteria. This finding updates the results of the CBRP compliance analysis, which estimated that only 12 percent of bacteria indicators in Mill Cucamonga Creek at Chino Corona Road could be attributed to MS4 inputs. New information was used in the Tier 1 source evaluation analysis that was not available when the CBRP compliance analysis was conducted, including: Monitoring data for additional MS4 outfalls to Cucamonga Creek, which were found to be significant sources of bacteria, most notable being drainage from City of Eastvale Line A. Concurrent daily effluent discharge from IEUA RP1. This discharge is highly variable, with flows ranging from 3 to 20 cfs in May through July of Therefore the source evaluation analysis is sensitive to any averaging of effluent at IEUA RP1, as was done for the CBRP compliance analysis. Also, RP1 the volume of effluent discharged to Cucamonga Creek has changed significantly over the past several years as a result of regional recycled water projects for direct and indirect reuse. Figure 3 15 shows that three high priority MS4 drainage areas account for 93 percent of the estimated blended bacterial indicator concentration in Mill Cucamonga Creek, including: T1 CAPT, mostly from industrial area just south of Ontario Airport T1 CHRIS, Outflow from Chris Basin, which receives MS4 drainage from Lower Deer Creek in southern Ontario T1 EVLA, mostly from the City of Eastvale underground MS4 system Draft 3 25

72 Section 3 CBRP Tier 1 Source Evaluation Report Figure 3 13 Schematic showing bacteria and DWF inflows to Cucamonga Creek in relation to downstream compliance monitoring site. (MS4 sources are in red shaded boxes; POTW effluent sources are shaded green. High priority MS4 drainages have a double border. Values for criteria used in the prioritization analysis is included next to each inflow box) 3 26 Draft

73 Section 3 CBRP Tier 1 Source Evaluation Report Figure 3 14 Comparison of estimated blended E. coli concentration of MS4 and clean POTW effluent with downstream watershed wide compliance monitoring data at Mill Cucamonga Creek at Chino Corona Road Figure 3 15 Potential for individual MS4 drainagee areas to contribute to exceedences of the WLA in estimated blended concentration att Mill Cucamonga Creek at Chino Corona Road Draft 3 27

74 Section 3 CBRP Tier 1 Source Evaluation Report Santa Ana River Subwatershed Within San Bernardino County, most DWF in MS4 drainage areas tributary to the MSAR is retained in basins, including the Wineville, Riverside, Jurupa, and Declez Basins, which capture flow from Etiwanda Creek, Day Creek, San Sevaine Channel, and Declez Channel, respectively. Within Riverside County, MS4 drainage areas exist on either side of the MSAR and have the potential to contribute DWF to the river (Figure 3 16); however, the width of the river bottom is much wider than the banks containing low flows. MS4 discharges to the river can percolate into underlying groundwater prior to reaching the rivers flowpath, which was used as a basis for making the previous CBRP finding that certain MS4 drainage areas are hydrologically disconnected. For the CBRP Tier 1 inspection program, two of these outfalls (T1 MCSD and T1 PHNX) were found to contribute DWF to the river flowpath. Review of recent aerial photography shows a shift in the course of the river banks occurred following the wet season. Such changes in the river flow path may continue to alter the mix of MS4 drainage areas that effectively contribute DWF to the river. The source evaluation analysis for the Reach 3 Santa Ana River involved computation of a blended bacterial indicator concentration from MS4 outfalls and POTW effluent from the City of Riverside s WQCP, City of Colton and San Bernardino RIX facility, and the City of Rialto WWTP. For the seven consecutive weeks when both upstream (Tier 1 monitoring) and downstream (watershed wide compliance monitoring) bacteria indicator data was collected, the estimated concentration in the MS4 and POTW blend was compared with actual concentrations in the Santa Ana River at MWD Crossing (Figure 3 17) and at Pedley Avenue (Figure 3 18). These comparisons suggest the presence of an additional non MS4 source of E. coli upstream of the Santa Ana River at MWD Crossing. For the Santa Ana River at Pedley station, a very high E. coli concentration occurred in the first week with both upstream and downstream data. This data point was not expected based on the Tier 1 monitoring data from the same week, in the remaining weeks, there is a close correlation between estimated blended concentration and data from the downstream watershed wide compliance site (WW S4). Thus, it may be inferred that, in some periods of the dry season, in stream sources of bacteria are small relative to MS4 inputs, or that decay by exposure to UV light offsets non MS4 sources of bacteria. Figure 3 19 shows that two MS4 drainage areas account for 85 percent of the estimated blended bacterial indicator concentration in the Santa Ana River upstream of MWD Crossing, including: T1 BXSP, mostly from the City of Riverside underground MS4 system T1 SNCH, an open channel that capture urban runoff from residential areas in Jurupa Valley as well as rising groundwater Figure 3 20 shows that the two high priority MS4 drainage areas, in addition to flows from above MWD Crossing, account for 92 percent of the estimated blended bacterial indicator concentration in the Santa Ana River upstream of Pedley Avenue, including: T1 ANZA, Anza Drain is an open channel that captures runoff from a large part of the City of Riverside as well as rising groundwater T1 SSCH, San Sevaine Channel is an open channel that extends to the San Gabriel Mountains, but is hydrologically disconnected in southern Fontana. Most runoff comes from the City of Jurupa Valley Draft

75 Section 3 CBRP Tier 1 Source Evaluation Report Figure 3 16 Schematic showing bacteria and DWF inflows to SAR in relation to compliance monitoring sites. (MS4 sources are in red shaded boxes; POTW effluent sources are shaded green. High priority MS4 drainages have a double border. Values for criteria used in the prioritization analysis is included next to each inflow box) Draft 3 29

76 Section 3 CBRP Tier 1 Source Evaluation Report Figure 3 17 Comparison of estimated blended E. coli concentration of MS4 and clean POTW effluent with downstream watershed wide compliance monitoring data for SAR at MWD Crossing Figure 3 18 Comparison of estimated blended E. coli concentration of MS4 and clean POTW effluent with downstream watershed wide compliance monitoring data for SAR at Pedley Avenue 3 30 Draft

77 Section 3 CBRP Tier 1 Source Evaluation Report Figure 3 19 Potential for individual MS4 drainage areas to contributee to exceedences of the WLA in estimated blended concentration at SAR at MWD Crossing Figure 3 20 Potential for individual MS4 drainage areas to contributee to exceedences of the WLA in estimated blended concentration at SAR at Pedley Avenue Draft 3 31

78 Section 3 CBRP Tier 1 Source Evaluation Report 3.6 Non MS4 Bacterial Indicator Sources To support the Tier 1 source evaluation analysis, CDM Smith performed a preliminary analysis to examine possible reasons for the seasonal increases in bacterial indicators regularly observed at the watershed wide compliance monitoring sites. Understanding the cause of this increase may provide information regarding controllable and uncontrollable sources of bacterial indicators in the watershed. This analysis focused on the SAR at MWD Crossing compliance site because that site exhibited the strongest seasonal trends over the six year monitoring period Correlation Analysis CDM Smith conducted a correlation analysis to evaluate if there were any significant relationships between the E. coli concentrations and other monitored parameters such as TSS, turbidity and temperature. Figure 3 21 illustrates geometric mean concentration plots averaged over a one month period for each of the water quality parameters for Each plot exhibits the observed seasonal increase in E. coli observed over time (blue line). In many years, this seasonal increase can mean the difference between compliance and non compliance with water quality objectives. There appear to be two types of trends observed in the water quality data: TSS/turbidity and E. coli are directly correlated: This pattern occurs in In this dataset, a spike of TSS and turbidity concentrations (i.e., up to 5760 mg/l for TSS) corresponds to a spike in the geometric mean E. coli concentration. Inverse relationship exists between with TSS/turbidity and E. coli: This pattern occurs in 2009, 2010 and For example, in 2009 and 2011 a general decline in TSS/turbidity concentrations occurs over the season while E. coli concentrations generally increase over time. The year 2010 has a more unusual pattern. In that year, the TSS/turbidity concentrations spike around the middle of August while E. coli concentrations temporarily drop and then return to the generally increasing trend observed earlier in the season. During the summer dry season, water temperature varies little, averaging around 19.6 o C; therefore, no relationships were observed between temperature and E. coli concentration. While the above analyses are interesting, they do not identify a consistent pattern that can be used to explain the reasons behind the seasonal trend of increasing E. coli. Therefore, additional data evaluation is warranted Relationship between E. coli Concentrations at SAR Compliance Sites Seasonal E. coli Trends CDM Smith investigated seasonal trends further by examining the relationship between E. coli concentrations at the SAR at MWD Crossing and SAR at Pedley Avenue sites. MWD Crossing is located approximately 7 miles upstream of Pedley Avenue (Figure 3 22) Draft

79 Section 3 CBRP Tier 1 Source Evaluation Report mg/l (TSS), C (temperature), or NTU (turbidity) TSS Temperature Turbidity E. coli E. coli (cfu/100 ml) mg/l (TSS), C (temperature), or NTU (turbidity) E. coli (cfu/100 ml) /16 7/6 7/26 8/15 9/4 9/24 10/ / /22 6/11 7/1 7/21 8/10 8/30 9/ / mg/l (TSS), C (temperature), or NTU (turbidity) /6 6/26 7/16 8/5 8/25 9/14 10/ / E. coli (cfu/100 ml) mg/l (TSS), C (temperature), or NTU (turbidity) Figure 3 21 Relationship between E. coli and other water quality constituents at SAR at MWD Crossing 0 6/20 7/10 7/30 8/19 9/8 9/28 10/ E. coli (cfu/100 ml) Figure 3 22 Relative locations of SAR compliance sites and Riverside treated wastewater discharge Draft 3 33

80 Section 3 CBRP Tier 1 Source Evaluation Report Figure 3 23 illustrates the geometric mean E. coli concentrations over a one month period at the SAR sample sites for 2008 through The E. coli concentrations at the two stations follow very similar trends in 2008, 2009 and This is somewhat unexpected given that Riverside Water Quality Control Plant (RWQCP) discharges a significant volume of treated wastewater effluent to the SAR upstream of the Pedley Avenue site (average of 46 cfs). The RWQCP discharge, which has a nondetectable E. coli concentration, provides significant dilution by increasing the instream flow in the SAR by approximately a factor of two. A statistical analysis (t test) demonstrated that no statistical difference (95 percent confidence level) was found between the MWD Crossing and Pedley Avenue E. coli concentrations levels for 2008, 2009 and Therefore, both stations generally exhibit the same seasonal increase of bacterial indicator concentrations during the summer dry season. In 2010 and 2012, however, the difference in E. coli concentrations observed at these two sites was found to be statistically significant (t test; 95 percent confidence level). Both sites exhibited the seasonal increase in E. coli, but the Pedley Avenue concentrations were observed to be around the levels seen in 2008, 2009 and 2011 while the MWD Crossing concentration were much higher than previously observed. This difference may be due to a September 10, 2012 rainfall event that occurred in the San Bernardino Mountains, and caused flow from upper reaches of the Santa Ana River to discharge to Reach Potential Seasonal E. coli Source A potential source of bacterial indicators in waterbodies is wildlife including birds and potentially bats. However, the degree to which wildlife can contribute to an exceedence of a water quality objective is not well understood. However, evidence from the literature and recent sampling conducted by Chino Hills suggest that birds and bats have the potential to be significant contributors of bacterial indicators to waterbodies in the MSAR watershed. A common nesting area for birds near waterbodies is bridges and culverts. For example, Sejorka et al. (2011) documented the significant increase in E. coli concentrations downstream of a Texas bridge crossing where there was a high density of cliff swallow nests. In addition, the City of Chino Hills recently conducted an investigation of an apparent seasonal increase in E..coli concentrations in the Boys Republic culvert in the Chino Creek subwatershed. They documented the presence of nesting swallows in the culvert during the period of increased E. coli concentrations (Figure 3 24, left). The potential for birds and bats to contribute high levels of bacterial indicators to MSAR waterbodies is largely speculative at this time. The presence of swallow nests on bridge crossings in the area has been documented previously (Figure 3 24, right). The nesting and fledging/foraging period for swallows occurs concurrent to the dry season monitoring period for the watershed wide compliance sites. Nesting brings a concentrated number of birds around the bridge and typically occurs in the early to middle part of the dry season (UP IPM, 2005). This timing generally aligns with the initial increases that are observed in the E. coli data (July) at numerous compliance monitoring sites, including MWD Crossing and Pedley Avenue. While the potential contribution of bacterial indicators by birds and bats (and for that matter wildlife in general) is largely anecdotal at this time, this potential bacteria source warrants further consideration Draft

81 Section 3 CBRP Tier 1 Source Evaluation Report E. coli (cfu/100 ml) GM - SAR at MWD Crossing GM - SAR at Pedley E. coli (cfu/100 ml) GM - SAR at MWD Crossing GM - SAR at Pedley /5/08 6/4/08 7/4/08 8/3/08 9/2/08 10/2/08 11/1/08-4/27/09 5/27/09 6/26/09 7/26/09 8/25/09 9/24/09 10/24/09 E. coli (cfu/100 ml) GM - SAR at MWD Crossing GM - SAR at Pedley - 4/22/10 5/22/10 6/21/10 7/21/10 8/20/10 9/19/10 10/19/10 E. coli (cfu/100 ml) GM - SAR at MWD Crossing GM - SAR at Pedley - 4/17/11 5/17/11 6/16/11 7/16/11 8/15/11 9/14/11 10/14/11 E. coli (cfu/100 ml) GM - SAR at MWD Crossing GM - SAR at Pedley 100-5/11/12 6/10/12 7/10/12 8/9/12 9/8/12 10/8/12 11/7/12 Figure 3 23 Seasonal E. coli geometric mean concentrations at MWD Crossing and Pedley Avenue during summer dry season from 2008 through 2012 (GM = geometric mean) Draft 3 35

82 Section 3 CBRP Tier 1 Source Evaluation Report Figure 3 24 Photographs of swallows within the MSAR Watershed: Left = Swalloww nest in Boys Republic South Channel Culvert in Chino Hills; Right: Swallow nests under Hellman Avenue Bridge on Cucamonga Creek. To illustrate the potential of birds as contributors of bacterial indicators to the SAR, an impact analysis was prepared using the typical bacterial load associated withh cliff swallows from under a Texas bridge (Sejorka et al. [2011]) (0.31 billion cfu/day) coupled with thee average dry weather flow for each impaired MSAR waterbody. Based on these baseline data, thee number of cliff swallow nests necessary to cause a 100 cfu/1000 ml change in E. coli concentration was calculated (selection of a 100 cfu/100 ml change was chosen to represent the typical seasonal increase in E. colii concentrations observed during the dry season at compliance sites). Based on this analysis, it appears that the number of swallow nests necessary to cause the increased concentrationn ranges from 73 to over 900, depending on the flow in the stream (Table 3 7). While these numbers may seem high, a review of the literature by Sejorka et al. (2011) found that cliff swallowss typically form nesting colonies with up to 3,500 individual birds. Table 3.7 Cliff Swalloww nest analysiss Watershed wide Compliance Site Average dryy weather flow (cfs) Changee in E. coli (cfu /100mL) Number of Cliff Swallow Nests 1 Mill Cucamonga Creek at Chino Corona Rd (WW M5) Chino Creek at Central (WW C7) Santa Ana River at MWD Crossing (WW S1) Santa Ana River at Pedley Ave (WW S4) Based on Sejorka et al., (2001); assumes 0.31 billion cfu/day associated with cliff swalloww nest 3 36 Draft

83 Section 4 Summary of Findings and Recommendations This TMDL implementation report provided a triennial report on the status of compliance with urban WLAs in the MSAR Bacterial Indicator TMDL and results from source evaluation activities conducted under the CBRPs established for Riverside and San Bernardino Counties. Following is a brief overview of the reports key findings and recommendations. 4.1 Summary of Findings Compliance with urban WLAs for dry weather (April 1 October 31): Bacterial indicator concentration and WLA exceedence frequency have remained generally constant at all compliance stations during the six seasons of dry season monitoring, with no stations reporting a marked increase or decrease in concentration from 2007 to During each year of dry season sampling, the highest bacterial indicator concentrations were observed at the Mill Cucamonga Creek and Chino Creek sites. With the exception of the 2009 season, Prado Park Lake has generally remained below the E. coli WLA (on an annual basis) during the dry season. Recent analyses of bacterial indicator data from selected watershed wide compliance sites coupled with an updated compliance analysis from recent Tier 1 source evaluation activities suggest that natural or uncontrollable sources of bacterial indicators may be important contributors to bacterial indicator concentrations at the watershed wide compliance sites. Seasonal increases in bacterial indicators were regularly observed at the watershed wide compliance monitoring sites. Understanding the cause of these increases may provide information regarding controllable and uncontrollable sources of bacterial indicators in the watershed. Tier 1 source evaluation data analysis activities: Dry weather flow rates from MS4 outfalls were low in most places where there are no known sources of rising groundwater. Bacterial water quality observed in dry weather flows from MS4 outfalls is highly variable across the MSAR watershed. E. coli concentrations in samples that also had a detection of the human Bacteroides marker were higher than in samples with no human Bacteroides marker detection. Data results provided the basis for prioritizing MS4 sub drainages for subsequent CBRP compliance activities within the MSAR watershed. In some weeks, a close correlation exists between the estimated E. coli concentration expected from blended MS4 outfall flows, and POTW discharges. However, in a number of cases, the observed E. coli concentrations are substantially higher than expected suggesting that additional sources of E. coli have not yet been accounted for. Draft 4 1

84 Section 4 Summary of Findings and Recommendations Data analysis identified the key MS4 outfalls within each impaired waterbody (based on dry weather flows and E. coli concentrations) where subsequent source evaluation work may provide the most benefit with regards to meeting bacterial indicator water quality objectives at watershed wide compliance sites. 4.2 Recommendations This TMDL implementation report identifies the recommended priority sub drainages within Riverside and San Bernardino Counties for implementation of next steps with regards to CBRP implementation (e.g., see Figure 3 8). Each County s MS4 permittees can use this information coupled with the approach established within the CBRP Framework to identify the next steps to mitigate controllable sources. In addition to providing information to prioritize the next steps of CBRP implementation, the data analyses contained in this report also demonstrate that not all urban sources of bacterial indicators can be accounted for by simply looking at MS4 and POTW sources. This finding is consistent with the compliance analysis previously prepared to support the CBRP. Because of the potential for unaccounted sources of bacterial indicators to be contributing to non compliance at watershed wide compliance sites, it is recommended that the MS4 permittees consider implementation of special studies to develop additional understanding in this area, i.e., implement studies to develop understanding regarding these unaccounted sources and whether they are controllable or uncontrollable. At a minimum it is recommended that two specific studies be completed (others may be identified as CBRP implementation moves forward): Contribution of Bacterial Indicators by Birds and Bats Based on the analysis provided in Section 3.6, a special study to investigate the potential influence of swallows (or other birds) and potentially bats on surface water quality in the MSAR watershed may be warranted. Elements to include in this study include: Identify the potential bird and bat species common to the MSAR watershed and research their potential to contribute bacterial indicators to waterbodies (i.e., their related life history attributes, e.g., reproductive cycles, nesting requirements, etc.); Based on the species identified above, identify the potential habitat available for colonization (e.g., number of bridges or other habitat favored by identified species for nesting or roosting) upstream of or in the area of watershed wide compliance monitoring sites; Determine the potential number of bird nests or bat roosts that may be supported by the available habitat (e.g., typical number of swallow nests per bridge); Evaluate differences in bacterial indicator concentrations upstream and downstream of selected preferred habitats (e.g., bridges), especially during the peak season for bird activity, collecting data on E. coli concentrations and, if practical, microbial source tracking data targeting birds or bat species. 4 2 Draft

85 Section 4 Summary of Findings and Recommendations This recommended study would best be implemented inn three steps: 1. Gather basic biological information, i.e., identify potential speciess and their related life history attributes, and determine potential for these speciess to impact water quality by identifying potential available habitat in the MSAR watershed; 2. Develop and implement a pilot study in one or two target areas to evaluate site specific potential impact of identified species on water quality; and 3. If appropriate based on findings from above, expandd the study to additional target areas in the watershed to fully understand scope of potential for species to impact water quality. Potential Impact of Elevated Flows from Summer Mountainn Storms on Water Quality in the Santaa Ana River A storm occurred in the San Bernardino National Forest on September 10, 2012 that generated sufficient runoff to caused runoff from the upper Santa Anaa River watershed to discharge to Reach 3 (USGS gauge for Santa Ana River near E Street). Significantly higher concentrations of TSS (5,760 mg/l) and E. coli (5, 500 mpn/100ml) occurred from Santaa Ana River samples taken the following morning, than during typical dry weather conditions withinn the MS4 areas (Figure 4 1). Figure 4 1 Photo of Santa Ana River at MWD crossing monitoring site (September 11, 2012) A preliminary comparison of upper Santa Ana River flow and water quality at the watershed wide monitoring sites did not suggest that summer thunderstorms in the mountains would be the only potential cause of elevated bacteria concentrations. Additionally, changes to water quality are not always observed following a storm that caused flow from the upper watershed into Reach 3. Further study is warranted to evaluate the full range of mountain canyons tributary to each of the TMDL waterbodies. 4 3