Relationship Between Bacteria and Conventional Water Quality Parameters
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1 Relationship Between Bacteria and Conventional Water Quality Parameters Hanadi S. Rifai, Ph. D., P. E., F. ASCE Professor and Director Environmental Engineering Graduate Program Civil and Environmental Engineering TX Watershed Coordinator Roundtable July 27, 2011
2 Outline Conventional water quality parameters Data for Houston Metro High resolution monitoring data in White Oak Data for tidal metro segments Data for a coastal watershed Summary and conclusions
3 Outline Conventional water quality parameters Data for Houston Metro High resolution monitoring data in White Oak Data for tidal metro segments Data for a coastal watershed Summary and conclusions
4 Conventional Water Quality Parameters Physical Chemical Biological Total Suspended Solids Total Dissolved Solids ph Temperature Turbidity Solar Radiation Conductivity Taste, color, odor Total Organic Carbon Dissolved Oxygen Ammonia/nitrate Biochemical Oxygen Demand Pathogens
5 Suspended Solids An increase in the amount of sediment causes: Increase of turbidity Decrease of light penetration Increase in amount of bacteria Increase in solids settled on the bottom which destroys animal habitats
6 Oxygen Demanding Material Dissolved Oxygen (DO) critical for fish and other higher forms of aquatic life Oxygen Demanding Material can be oxidized thus consuming DO Examples: BOD, COD Almost all naturally occurring organic matter contributes to the depletion of DO
7 Pathogenic Organisms Bacteria, viruses, and protozoa from diseased persons or animals Water unsafe for drinking, swimming, and fishing Antibiotic-resistant bacteria are most dangerous Bacteria found in urban and rural environments with no observable pattern Examples: E. Coli, Salmonella (typhoid fever), Shigella (dysentery), Cryptosporisium (protozoa), and Giardia (protozoa)
8 Temperature Temperature affects dissolved oxygen and microorganisms Oxygen use speeds up as the temperature increases and slows down as the temperature decreases Oxygen use caused by the metabolism of microorganisms
9 Outline Conventional water quality parameters Data for Houston Metro High resolution monitoring data in White Oak Data for tidal metro segments Data for a coastal watershed Summary and conclusions
10 Houston Metropolitan Watersheds Greens Bayou Buffalo Bayou LakeHouston Houston Lake Whiteoak Bayou Brays Bayou Source of Landuse data: Houston Galveston Area Council
11 Geometric Mean E. coli Levels Brays & Whiteoak > Buffalo > Halls > Sims & Greens 2,400 MPN/dL > 2,000MPN/dL > 1,600 MPN/dL > 600 MPN/dL Data record:
12 Data record: E. coli concentrations: Change Over Time
13 Data record: Warm temperatures: 24 to 32 C Cool temperatures: 12 to 18 C E. coli Trends with Temperature
14 Data record: NA: Data Not Available E. coli Trends with Rainfall
15 Multiple Linear Regression WO Bayou Coefficients of Predictor Variables Site Day Ln Flow Temperature ( C) TSS (mg/l) SC ph Turbidity R US * * * * NA * NA NA NA * Blue values indicate statistical significance at 95% confidence level * Statistically significant at 90% confidence level
16 Outline Conventional water quality parameters Data for Houston Metro High resolution monitoring data in White Oak Data for tidal metro segments Data for a coastal watershed Summary and conclusions
17 Whiteoak Bayou Watershed
18 Data from 3 Month Daily Sampling in WO
19 Spatial Variability in 3- Month Data Weekly Geomean Upstream locations had lower median and geometric mean E. coli concentrations Downstream locations had similar variability of E. coli concentrations
20 Real-Time Continuous Monitoring Schematic Solar Panel to Power Equipment Bayou Strainer Suction Line Sonde Flow Through Cell Monitor ph, DO, Conductivity, and Temperature Interface (A) Automated Sampler (B) Peristaltic Pump (C) Rain Gage Data Logger Transmitter Monitoring systems Installed at &
21 Inside the Stormbox Multiprobe Automated sampler 24 Bottle configuration Solar Power Port Rain Gage Port Interrogator Port Flow Module Sampler Display
22 High resolution Sampling Sites
23 E. coli Conc. at Site BG Dry Weather E. coli (MPN/dL) 100,000 10,000 1, BG Water Temperature ( C) E. coli (MPN/dL) 1,000, ,000 10,000 1, BG Water Temperature ( C) 10 6/1/09 6:00 6/1/09 8:00 6/1/09 10:00 6/1/09 12:00 6/1/09 14:00 6/1/09 16:00 6/1/09 18: /1/09 6:00 6/1/09 8:00 6/1/09 10:00 6/1/09 12:00 6/1/09 14:00 6/1/09 16:00 6/1/09 18:00 22 E. coli (MPN/dL) 100,000 10,000 1,000 BG 05 Bacteria Diurnal Sag Decay Sag Regeneration Water Temperature (oc) 1,000, ,000 E. coli (MPN/dL) 10,000 1, BG Water Temperature (oc) /18/10 6:00 3/18/10 18:00 3/19/10 6: /24/10 6:00 5/24/10 18:00 5/25/10 6:00 24
24 E. coli Conc. at Site HB Dry Weather 100,000 HB ,000 HB E. coli (MPN/dL) 10,000 1, Water Temperature ( C) E.coli (MPN/dL) 1, Water Temperature ( C) 100 5/8/09 6:00 5/8/09 8:00 5/8/09 10:00 5/8/09 12:00 5/8/09 14:00 5/8/09 16: /8/09 18: /28/09 6:00 5/28/09 8:00 5/28/09 10:00 5/28/09 12:00 5/28/09 14:00 5/28/09 16: /28/09 18:00 10,000 HB ,000 HB E. coli (MPN/dL) 1, Water Temperature (oc) E. coli (MPN/dL) 1, Water Temperature (oc) 100 1/19/10 6:00 1/19/10 18:00 1/20/10 6: /2/10 7:00 2/2/10 13:00 2/2/10 19:00 12 E. coli 394 MPN/dL Std. Temperature
25 Solar Radiation Effects on E. coli 100,000 E. coli (MPN/dL) 10,000 1, BG /20/10 6:00 2/20/10 18:00 2/21/10 6:00 Solar Radiation (Ly/min) 100,000 BG E. coli (MPN/dL) 10,000 1, /18/10 6:00 3/18/10 18:00 3/19/10 6:00 1 Solar Radiation (Ly/min) E. coli (MPN/dL) 10,000 1,000 HB Solar Radiation (Ly/min) E. coli (MPN/dL) HB Solar Radiation (Ly/min) 100 1/19/10 6:00 1/19/10 18:00 1/20/10 6: /2/10 6:00 2/2/10 12:00 2/2/10 18:00 0 Source of solar radiation data
26 Storm Event Monitoring Location: Heights Blvd. Date Event # Rainfall (inch) 7/22/2009 HB /13/2009 HB /22/2009 HB /22/2009 HB /2/2009 HB /09/2010 HB
27 Storm HB Site EC and Flow 100,000 10,000 1,000 HB 05 Attenuation due to Temperature Rainfall: 0.28 inch* Attenuation due to flow Turbididty (NTU) E. coli (MPN/dL) 100,000 10,000 1,000 HB 06 Rainfall: 0.43 inch * E. coli Flow (cfs) Turbidity (NTU) Flow and Turbidity E.coli (MPN/dL) Flow (cfs) Turbidity E. coli (MPN/dL) 100,000 10,000 HB 09 Rainfall: 1.54 inch* E.coli Flow (cfs) Turbidity (NTU) Flow and Turbidity 1,000 0 *Not to scale
28 WO Bayou Real Time Monitoring EC and Turbidity Rain Event 8/12/ EC Turbidity :48 9:12 1:36 0:00 2:24 4:48 7:12 9:36
29 Outline Conventional water quality parameters Data for Houston Metro High resolution monitoring data in White Oak Data for tidal metro segments Data for a coastal watershed Summary and conclusions
30 Tidal Metro Segments
31 EC Tidal Metro
32 ENT Tidal Metro
33 FC Tidal Metro
34 Indicator Bacteria & DO Tidal Metro
35 Indicator Bacteria & Temp Tidal Metro
36 Indicator Bacteria and TSS Tidal Metro
37 Indicator Bacteria & Salinity Tidal Metro
38 Indicator Bacteria & ph Tidal Metro
39 FC and ENT Tidal Metro
40 Outline Conventional water quality parameters Data for Houston Metro High resolution monitoring data in White Oak Data for tidal metro segments Data for a coastal watershed Summary and conclusions
41 Dickinson Bayou Watershed
42 Dickinson Bayou Land Use
43 Dickinson Bayou WQ Stations Developed Core
44 Dissolved Oxygen Dickinson
45 Dissolved Oxygen Geometric Mean
46 E. coli and ENT Dickinson Enterococci (MPN/100 mlor #/100mL) Main stem Tributary GCHD Data* Segment ID 1103 Segment ID Distance from mouth of Dickinson Bayou (miles)
47 EC and ENT and DO Dickinson Bayou
48 EC and Salinity Dickinson E.coli (MPN/dL) E.coli (MPN/dL) Segment 1103 <3 ppt (freshwater) 3 to 16 ppt (brackish)> 16 ppt (sea water) Salinity (µs/cm) Segment 1104 maximum 25th pct geomean median 75th pct minimum maximum 25th pct geomean median 75th pct minimum 10 1 (n=2) <3 ppt (freshwater) 3 to 16 ppt (brackish) > 16 ppt (sea water) Salinity (µs/cm)
49 ENT and Salinity in Dickinson ENT (MPN/dL) Segment 1103 <3 ppt (freshwater)3 to 16 ppt (brackish)> 16 ppt (sea water) Salinity (µs/cm) maximum 25th pct geomean median 75th pct minimum ENT (MPN/dL) Segment 1104 (n=2) <3 ppt (freshwater) 3 to 16 ppt (brackish)> 16 ppt (sea water) Salinity (µs/cm) maximum 25th pct geomean median 75th pct minimum
50 Summary and Conclusions As watersheds urbanize, less correlation between biological water quality and other parameters Correlation may be observed at high resolution scale, e.g., EC and turbidity during storm event Some conventional water quality parameters no longer sufficient indicators, e.g., TSS Other indicators needed for urbanizing watersheds to characterize particulate, biological, and chemical water quality
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