WATER QUALITY FROM SOURCE TO TAP

Transcription

1 November 17, 2014 WATER QUALITY FROM SOURCE TO TAP KEVIN T. LAPTOS, REGIONAL PLANNING LEADER

2 ACKNOWLEDGEMENT ACKNOWLEDGEMENT Co-Authors Scott Huneycutt, Union County Public Works Ben Cownie, Black & Veatch Jeff Coggins, Black & Veatch 2

3 PRESENTATION OVERVIEW PRESENTATION OVERVIEW Introduction Case Study -Union County, NC Background/Objective Water quality data analysis Hydraulic modeling Summary & Conclusions 3

4 INTRODUCTION 4

5 DELIVERING HIGH QUALITY WATER THE FOCUS IS SHIFTING Water Treatment Plants Produce high quality drinking water INTRODUCTION Meet water quality regulation standards Water Distribution Systems Degrade treated water quality Meet water quality regulation standards??? Goal Deliver high quality water to the customer tap

6 DISTRIBUTION SYSTEM ADVERSE IMPACTS Increases water travel time from WTP to customer Pipeline network Storage facilities INTRODUCTION Additional time for reactions and processes to occur Reduction in Cl 2 residual Formation of DBPs Nitrification (in Chloramine systems) Sedimentation

7 DISTRIBUTION SYSTEM SOLUTIONS Potential exists for significant water quality problems INTRODUCTION Potential problemscan be avoided through proper system planning, design, and operation Storage facility solutions Elevated Standpipe Ground Reservoir Pipeline network solutions Operational solutions

8 CASE STUDY - 8

9 BACKGROUND Union County Water System Southeast of Charlotte Two (2) sources of supply (Chloramines) Catawba river -CRWTP Yadkin river Wholesale purchase from Anson County Five (5) pressure zones Average daily demand of 10.5 mgd Changes in the Distribution System (2010) Expansion of water supply agreement with Anson County Pressure Zone realignments New WQ and operational challenges Very low chlorine residual in 853 East Zone 9

10 OBJECTIVES Develop understanding of water age, chlorine residual, and other water quality parameter profiles in 853 East Zone Identify capital and/or system operational solutions to increase chlorine residuals in 853 East Zone 10

11 PRELIMINARY WQ DATA ANALYSIS Biological Nitrification Potential exists in systems that add ammonia to form chloramines Microbial activity prevalent in locations of system with low chloramine residuals Free (unreacted) ammonia combined with lower residuals can trigger growth of nitrifying bacteria Two steps Step 1 Conversion of Ammonia to Nitrite NH 3 + O 2 NO H + Step 2 Conversion of Nitrite to Nitrate NO 2- + H 2 O NO H + 11

12 PRELIMINARY WQ DATA ANALYSIS Analyze WQ sampling data From Oct 2011 to Feb Locations Profile key parameters related to chloramines application and WQ Primarily focused on potential biological nitrification 12

13 PRELIMINARY WQ DATA ANALYSIS 5.0 Entry Point 4.5 Presson Road Total Chlorine Tallwoodand Hargette significantly lower Total Chlorine, mg/l Marshville Tank Tallwood Hargette New Salem S O N D J F M A M J J A S O N D J F M

14 PRELIMINARY WQ DATA ANALYSIS 1.0 Entry Point Free (unreacted) ammonia Tallwoodand Hargette significantly lower Free Ammonia, mg/l Presson Road Marshville Tank Tallwood Hargette New Salem S O N D J F M A M J J A S O N D J F M Nitrites, ph and dissolved oxygen values at Tallwood and Hargette also different from other sites 14

15 PRELIMINARY WQ DATA ANALYSIS Utilize model to determine average water age at each sampling point WATER QUALITY SAMPLING POINT ESTIMATED WATER AGE (DAYS) Entry Point 3 Presson Road 9 Marshville Tank 4 Tallwood 17 Hargette 14 New Salem 7 Highest water ages at Tallwood and Hargette 15

16 PRELIMINARY WQ DATA ANALYSIS Tallwoodand Hargette WQ sampling points indicate biological nitrification Model-predicted water ages high (14 to 17 days) Remaining five WQ sampling points do not indicate biological nitrification Model-predicted water ages lower (3 to 9 days) Water age of 12 days established as threshold to avoid biological nitrification 16

17 MODEL CALIBRATION Existing hydraulic model updated All-pipes Water demand allocation Calibration Confirm model accurately simulates SCADA readings at tanks, pump stations, pressure monitoring locations Increase confidence that the model can accurately predict water ages 17

18 WQ MODELING BASE SCENARIO High water ages simulated at Hargette and Tallwood sample locations Hargette: long dead-end main Tallwood: NW Tank impacts High Water Ages High Water Ages 853 East 853 West 18

19 WQ MODELING SCENARIO 1 Shift853 West/East Zone Boundary to the West Added more demand in vicinity of NW Tank Increased tank turnover and decreased water age to < 12 days 853 East 853 West 19

20 WQ MODELING SCENARIO 2 Eliminate 853 West/East Zone Boundary Increased NW Tank turnover similar to Scenario 1 Decreased water ages to < 12 days Provided supply flexibility from Anson County 853 West 853 East Eastern FlowMaximized 20

21 FINAL RECOMMENDATIONS Eliminate 853 West/East Zone Boundary (Scenario 2) Reduces water ages below 12 days at all locations (except some isolated dead-ends) Decreases potential for biological nitrification Increases chlorine residual Previously recommended by Master Plan Free Chlorine Burn-Out Temporarily discontinue ammonia feed Allow free chlorine to kill any nitrifying bacteria in pipes Resume ammonia feed after measurable free chlorine is established throughout system 21

22 SUMMARY & CONCLUSIONS 22

23 SUMMARY & CONCLUSIONS SUMMARY & CONCLUSIONS Many water quality challenges still exist in distribution systems Possible to establish correlation between water quality sampling results and simulated water age Water age is a useful surrogate parameter to assess water quality Complex constituent (i.e. chlorine, DBPs) modeling not necessarily needed 23

24 SUMMARY & CONCLUSIONS (CON T) SUMMARY & CONCLUSIONS Manage water age in distribution systems by proper system planning, design, and operations Increase chlorine residual Reduce Nitrification (chloramine systems) Reduce DBPs (free chlorine systems) System operational changes Effective at reducing water age Much less cost to implement than capital improvements System modeling is an effective system assessment approach System-wide water quality results Ability to compare relative benefit of system improvement scenarios 24

25 November 17, 2014 COMMENTS OR QUESTIONS? KEVIN T. LAPTOS, REGIONAL PLANNING LEADER