Overview of Continuous Water-Quality Monitoring

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Presentation transcript:

Overview of Continuous Water-Quality Monitoring Today I’m going to be addressing topics related to continuous water quality monitoring First describe what is meant by CWQM vs discrete monitoring

Purpose of Monitoring Define the objectives of the water quality monitoring project Environmental impacts of effluent Contaminant alerts Plume tracking Trends Establishing the objectives of monitoring is the first step

How will data be used ? Investigate variations in water quality Event Diurnal Monthly Seasonal Annual Evaluate loads (requires flows) Regulations (daily mean, max, min) Threshold warnings Development of surrogate relations

Design of Monitoring Plan Data requirements Period and duration Seasonal Short term Long-term Frequency of data collection Continuous or discrete 15 minute, hourly, daily, monthly, etc… Sensor selection Once the objectives are established the monitoring plan can be designed to achieve the intended goals

Water-Quality Parameters Common parameters measured: Temperature Specific conductance Salinity (based on specific conductance) pH Dissolved oxygen Turbidity

Typical Probe Specifications Maximum depth: 60 m Temperature: -5 to 50o Celsius Specific conductance: 0 to 100 mS/cm Salinity: 0 to 80 ppt pH: 0 – 14 pH units Dissolved oxygen: 0 to 50 mg/L, 0 to 500 % saturation Turbidity: 0 to 1,000 NTU

Water-Quality Sensors YSI

Chlorophyll-a (algae) Temperature and Specific Conductance Optical Dissolved Oxygen Turbidity

Clark Cell Dissolved Oxygen

Other Sensors Troll

Other Sensors Hydrolab

Temperature Thermistor Resistance changes with temperature Resistance converted to temperature using algorithm Common unit: degrees Celsius

Specific Conductance Measure of the water’s ability to conduct electrical current Electrodes must be submerged in water Approximate measure of the amount of dissolved solids or ions in water Specific conductance is conductance “normalized” to 25 degrees C Common unit: uS/cm (microSiemens per centimeter), also umhos/cm (same units) Current flow through electrodes and sample

Salinity Not measured directly Computed parameter based on conductivity and temperature Essentially measuring the amount of chloride in water Common unit: ppt (parts per thousand)

pH Measure of acid/base characteristics pH 7.0 = neutral pH > 7.0 = alkaline/basic pH < 7.0 = acidic Measures differential of hydrogen ions (H+) inside/outside of electrode Common unit: standard pH units

Dissolved Oxygen 2 major types Common units: mg/L and % saturation Rapid pulse Clark cell Optical Common units: mg/L and % saturation

Advantages of Optical Sensors Less susceptible to FOULING Less susceptible to CALIBRATION DRIFT Sensors require fewer site visits Still need routine cleaning BASED ON OWSC TESTING Less susceptible to fouling because no oxygen is consumed. Less susceptible to calibration drift because there is no electrochemical reaction that causes probe behavior to change. Still need to worry about micro environments when the probe may become isolated from the environment that we are trying to measure. More rugged in that it is much more difficult to damage the probe by hitting it with the sensor guard or aquatic bugs from puncturing holes in the membrane. Clark cells are dependent upon rate of O2 transfer Optical sensors do not consume oxygen

Advantages of Optical Sensors, cont. More rugged Greater range of operation More accurate readings at low DO No need for stirring Not strongly affected by temperature Optical Sensor: 0-50 mg/L of operational range for the optical sensor. 0-20 mg/L +-.1 mg/L or 1% of reading, whichever is greater. 20 – 50 mg/L +- 15% Clark Cell Sensor 0-20 mg/L is 0.2 mg/L or 2%, whichever is greater. 20-50 mg/L is +- 6% of reading

Turbidity Measure of water clarity Light is emitted, scatters off particles Amount of light scattered at 90 degrees is measured Common units (depends on probe): NTU (nephelometric turbidity units) FNU (formazin turbidity units)

Detector measures how much light is scattered at 90 degrees Turbidity Detector measures how much light is scattered at 90 degrees Light source Sample Detector Photo courtesy of Sontek YSI Inc.

Design of Monitoring Plan Installation type Flow through In situ internal logger and power external logger and power Once the objectives are established the monitoring plan can be designed to achieve the intended goals

Flow through system Slide 75 Water from river outlet

Flow through Advantages Disadvantages Secure Reduced fouling Real-time data access Disadvantages Requires AC electric service More maintenance Results can be less accurate (turbidity)

In situ (external logger)

In situ (external logger) Advantages Data are secure Real-time data access Instream monitoring often yields more accurate results No AC requirement permits remote sites Disadvantages Sonde and probes are vulnerable to vandalism and loss Probes are subject to fouling and damage from debris

In situ (internal logger)

In situ (internal logger) Advantages Remote locations possible Instream monitoring often yields more accurate results Less maintenance Disadvantages Telemetry not an option Sonde, probes, and data are vulnerable to vandalism and loss Probes are subject to fouling and damage from debris

Continuous Water Quality Monitoring Advantages Disadvantages Needed in rapidly changing systems Provides better understanding of interaction between constituents Provides better understanding of transport processes Equipment costs are greater Operation and maintenance costs are greater Vulnerable to damage and/or loss

Relations Between Parameters DO and pH DO and pH track together Diurnal Pattern Why? Aquatic organisms produce CO2 at night combining with H20 to form H2CO3 (carbonic acid) causing pH to go down. DO goes up during the day when biological productivity is high DO drops off at night when aquatic organisms are using DO and respiring CO2 CO2 combines with H20 to form H2CO3 or carbonic acid The increased carbonic acid causes pH to go down at night. Thus there is a direct relation between DO and pH with a strong diurnal cycle Collecting continuous QW data allows you to better observe these types of relations which leads to a better understanding of physical processes and the interacton of constituents

Relations Between Parameters DO and Temperature Super-saturated DO DO crash in June Variation in DO changes seasonally Saturated means the amount of DO under equilibrium conditions but supersaturation occurs as a result of aquatic growth and mechanical entrainment. The DO concentration for saturation is reduced as the water temperature rises which produces the monthly and seasonal variations. Daily variations are controlled by photosynthesis and respiration. During the day when photosynthesis is at its peak you have maximum DO. At night photosynthesis shuts down and organisms begin respiring and producing CO2. DO drop in June is likely due to an algae bloom producing lots of oxygen in the day followed by a drop off in DO production at night but with the respiration process of the algae dominating and taking up the available DO during the night If you go out at 10 everyday you’re going to get 120% and think everything’s great and you’re not aware of the DO sag at night that stress the fish. In winter less aquatic growth so less DO production and swings

Relations Between Parameters Turbidity –vs- Discharge This slide shows the relation between turbidity and streamflow. Turbidity is a good surrogate for suspended sediment or TSS In a natural stream you often see a first flush of sediment during the high flows that occur after a long period of low flow. (snowmelt in ID) After this flush the sediment concentrations are often lower even during a higher flow event.

Discrete vs Continuous Monitoring In this slide we have 4 types of data shown Streamflow (cfs) Suspended sediment concentration (mg/l) from discrete samples LOADEST model results which are estimates of the sediment load based on streamflow and discrete samples Continuous suspended sediment concentrations from an Acoustic Backscatter signal (similar to turbidity) This illustrates the disadvantage of using only a few discrete samples, even when coupled with flow, to estimate instantaneous or even daily loads.

Other Surrogate Possibilities Continuous Parameter(s) Surrogate Constituent Specific Conductance TDS, Total Nitrogen Turbidity Suspended Sediment, Total Phosphorous Turbidity + Temperature Bacteria Relations are developed using discrete samples and linear regression Regression model used to synthesize continuous record of target parameters that are difficult to monitor. Parameter -vs- surrogate relations are not universal but site specific

Applications Continuous monitoring the constituent or its surrogate to aid in identifying occurrence and duration of water-quality parameters that exceed regulatory limits.

Relation between SC and TN

Applications (cont) Identify and optimize periods for sample collection Quantify constituent loads (volume/time) Familiarity with the site and data will lead to a better understanding of physical processes and interactions between constituents

Questions?