Other Considerations & Review Building a Successful Monitoring Plan

Transcription

1 Other Considerations & Review Building a Successful Monitoring Plan Fundamentals of Developing a Water Quality Monitoring Plan Thursday, July 28, 2016 Larry Hauck hauck@tiaer.tarleton.edu Mention of trade names or commercial products does not constitute their endorsement. 1

2 Other Considerations Specialized Types of Monitoring Equipment Needs Personnel Constraints Laboratory Costs Resource Availability & Budget Constraints Data Management Importance of Project Planning

3 Specialized Monitoring Provide monitoring data for models Bacterial source tracking (BST) 3

4 Monitoring Data Needs for Models Monitoring Data Uses Input data to represent boundary conditions of tributaries and upstream/downstream end of models Comparison of measured data to simulated predictions for model verification process o Calibration Step (Using part of data) o Validation Step (Using remaining data) 4

5 Required Monitoring is Model Specific Watershed modeling daily streamflow and longterm monitoring data sufficient to estimate loadings Receiving water models synoptic data sets; multiple stations monitored frequently over a brief period of time; certain models will also need long term data 5

6 Watershed Model Example: SWAT Predictions for a Subbasin of North Bosque River (Streamflow) SC020 Monthly Average daily streamflow E = 0.30 %E = M = 0.11 P = 0.08 m 3 /s Jan-95 Jun-95 Nov-95 Apr-96 Sep-96 Feb-97 Jul-97 Dec-97 measured month predicted Presentation II 6

7 SWAT Predictions for a Subbasin of North Bosque River (Total Phosphorus) SC020 Monthly Total TP 1,600 1,400 1,200 1,000 E = -8.7 %E = 199 M = 88 P = 263 kgs Jan-95 Jun-95 Nov-95 Apr-96 Sep-96 Feb-97 Jul-97 Dec-97 month measured predicted Presentation II 7

8 Receiving Water Example QUAL2K Model Calibration Upper Oyster Creek - Upper portion (8/16/2004) 40.0 Mainstem Upper Oyster Creek - Upper portion (8/16/2004) Mainstem TSS (mgd/l) Avg(P) TSS Min(P) TSS (mgd/l) (O) TSS Max(P) Upper Oyster Creek - Upper portion (8/16/2004) Mainstem NO3 (ugn/l) (O) NO3(ugN/L) Min(P) NO3(ugN/L) Avg(P) NO3(ugN/L) Max(P) DO (mgo2/l) Avg(P) DO (mgo2/l) Avg(O) DO (mgo2/l) Min(P) DO (mgo2/l) Max(P) Presentation III 8 DO (mgo2/l) Min(O) DO (mgo2/l) Max(O) DO sat(p)

9 Bacteria Source Tracking BST is the use of genetic and phenotypic tests to identify bacterial strains that are host specific so that the original host animal and source of the fecal contamination can be identified. Library Dependent & Library Independent Methods

10 One Example: Isolation of E. coli From Feces and Water Fecal Specimens Water Sample Filtered and Filter Placed on Modified mtec Medium (EPA Method 1603) Modified mtec Medium E. coli Colonies Each E. coli colony is called an Isolate

11 BACTERIA SOURCE TRACKING Water Samples Fecal Samples Isolated E. coli Isolated E. coli Sample Site 1 Sample Site 2 Sample Site 3 Dog Sample Human Sample Cow Sample 11

12 Evaluate Equipment Needs, Personnel Constraints, Available Resources, Lab Costs, & Budgets Constraints 12

13 Examples of Sampling Equipment & Approximate Costs Mention of trade names or commercial products does not constitute their endorsement. Automated Sampling Equipment ISCO sampler combination with flow meter ~ $5,500 Sheet metal shelter ~ $500 $1,000 Individual ISCO Units o Sampler ~ $3,000 $3,500 o Flow meter with phone modem ~ $4,500 $5,000 13

14 Flow measurement Wadeable Stream Sontek Flow Tracker ~ $7,000 $9,000 Wading rods ~ $1,000 $1,400 14

15 Flow measurement Non Wadeable Stream Sontek River Surveyor ~ $15,000 $45,000 (toward the low price range suffices for many applications) Back Up Method 15

16 Personnel Constraints Specialized skills: for example, fish and macrobenthos sampling and identification Scheduling of personnel (and lab services): stormwater sampling outside of normal work days Flathead catfish Pylodictis olivaris 16

17 Inclusion of Laboratory Costs 17

18 TCEQ Conventional Parameters total Kjeldahl nitrogen (TKN) total phosphorus (TP) total ammonia (NH 3 N) total nitrite plus nitrate (NO 2 +NO 3 N) soluble reactive phosphorus (dissolved PO 4 P) total dissolved solids (TDS) total suspended solids (TSS) volatile suspended solids (VSS) chloride sulfate total alkalinity total organic carbon (TOC) chlorophyll a Cost Per Sample: ~$250 $400 18

19 Approximate Cost of Some Common Lab Tests (Water Matrix) E. coli (Colilert Method) ~$35/sample E. coli (m TEC Method) ~$55/sample; used with bacterial source track (BST) work Enterococcus ~45 Total Phosphorus ~$35 Total Ammonia ~$30 Total Nitrite+Nitrate ~$30 19

20 Including a Data Management Plan Components: Path of data from generation to final use System design equipment, hardware, software Migration/transfer/conversion Backup/disaster recovery Archives & data retention Information dissemination Do not neglect the resource commitment for this effort. 20

21 Generation of Physicochemical, Informational, and Observational Data in the Field (Water Quality Monitors) Generation of Chemical Data (Laboratory Analysts) Data Entry (Data Entry Staff, Lab Manager, Database Program Manager) Data Screening and Validation (Field Supervisor and Laboratory Manager) Data Screening for Verification and Outliers (Data Analysts and QAO) Data Transfer (Project Data Manager and QAO) Specific example of data flow for a project with TCEQ TCEQ TMDL Project Manager (with data review checklist) Returned to submitter for revision, if necessary TCEQ TMDL Project Manager TCEQ DMA Data Manager SWQMIS 21

22 PURPOSEFULLY INCLUDE PROJECT PLANNING Integrate monitoring component into the overall project For monitoring effort consider: Time for Stakeholder involvement, buy in, input, BMP selection Exploratory data review (including assessing data gaps) Lead time for reconnaissance & site determination Lead time for Monitoring Plan and QAPP development and approval 22

23 REVIEW Steps to Building a Successful Monitoring Plan 23

24 Steps of a Successful Monitoring Plan: 1. Define specific data quality objectives 2. Know approximate budget and personnel constraints 3. Review existing data; check for data gaps 4. Determine sample locations, sampling procedures and frequency, variables to monitor and analytic techniques (i.e., develop a monitoring design plan and QAPP) 5. Initiate and continue monitoring program 6. Prepare regular reports and recommendations 7. Modify and adjust monitoring as needed 24

25 I 25 Step 1. Define Specific Data Quality Objectives EXAMPLES: Analyze long term trends Document changes in management and pollutant source activities Measure performance of specific management practices Fill data gaps in watershed characterization (e.g., suspected hotspots) Track compliance and enforcement in point sources Provide data for educating and informing stakeholder Calibrate and validate models

26 Step 2. Know Budget and Personnel Constraints Monitoring can be very expensive (e.g., wet weather monitoring, streamflow gauges, equipment, lab costs) Monitoring can require specialized skills of personnel and their availability when needed (routine monitoring vs. wetweather monitoring demands on personnel) 26

27 Step 3. Review Existing Data EXAMPLES: Exploratory data analysis. Is good streamflow data available (e.g., USGS streamflow recording station)? What is the nature of the water quality data (e.g., temporal and spatial density)? What do the data show? Can existing data be used to characterize pre management conditions? 27

28 Past Experiences Indicate: Obtaining adequate pre treatment or preimplementation water quality data is often a problem. And this problem is not easily overcome without delaying implementation efforts. 28

29 Step 4. Develop a Monitoring Design Plan What questions are we trying to answer? What assessment techniques will be used? What statistical power and precision is needed? Can we control for the effects of weather and other sources of variation? What are our constraints (financial, personnel, time, etc.)? Will our design allow us to attribute changes in water quality to the implementation program? 29

30 Financial and Personnel Constraints Always Exist! Coordination with other monitoring programs (SWQM, CRP, etc.) if possible. Is there a role for volunteer monitoring in your project? (Texas Stream Team, The Meadows Center for Water and the Environment, Texas State Univ.) 30

31 Common Statistical Designs for Monitoring BMP Effectiveness Single Watershed Before and After Single Watershed Above and Below (Upstream Downstream) with Before and After Single Watershed Trend or Step Trend Paired Watershed Study Design (Before After Control Impact or BACI) 31

32 Single Watershed Before/After Statistical Approach Assumes similar climate and hydrology between the Before and After periods Monitoring covariates, such as flow, can aid in adjusting for differences Source Diagram: NRCS, NWQH

33 Single Watershed Above/Below Spatial Above and Below Practice Location (upstream/downstream) Source Diagram: NRCS, NWQH

34 Single Watershed Above/Below Before monitoring helps account for inherent differences within the watershed Before Monitoring After Monitoring No Practice Source Diagram: NRCS, NWQH

35 Paired Watersheds Calibration Period Treatment Period Source Diagram: NRCS, NWQH

36 Paired Watershed Approach Source: J.D. Hewlett Principles of Forest Hydrology. The University of Georgia Press.

37 Steps 5 7. Implement Your Monitoring Design Plan & Build in an Evaluation Process Initiate and continue monitoring program. Prepare regular reports and recommendations. (don t wait until the end of your project to look at the data thoroughly) Modify and adjust monitoring as needed. 37

38 Steps 5 7. (Continued) Consider delaying monitoring components with anticipated long response time to pollution control practices (e.g., biological monitoring) 38

39 Thank You Questions? 39