pH measurement in natural aquatic environments is commonly done electrochemically by measuring the voltage between a pH-sensitive glass electrode and a reference electrode. Commercial pH meters convert voltage readings into pH units using calculations based on the Nernst equation and sometimes other assumptions about the environment and measurement system. Because of unavoidable differences between theoretical pH measurement systems and real-world pH measurements systems, pH is often said to be defined “operationally” based on an accepted electrochemical method such as Standard Method 4500-H+ or similar methods from other standards organizations. Despite pH sensor imperfections, most water resource professionals accept measurements derived from glass electrode measurement systems as the “operational definition” of pH and use them for meaningful and defensible scientific endeavors.
A Hydrolab pH sensor for use on Hydrolab multiparameter sondes.
The millivolt reading from a theoretically perfect pH sensor in a pH 7 solution is zero. In nominal pH 4 and pH 10 buffers at 25 °C, millivolt readings are 177.48 and -177.48, respectively. In practice, millivolt readings will differ in an amount referred to as the asymmetry potential of the electrode. As the electrodes age and degrade with use, mV readings during calibration will change – decreasing in acidic solutions and increasing in basic solutions.
Changes in mV readings observed during calibration procedures over time can be used as an indicator of electrode condition and the quality of the calibration procedure. Small deviations from theoretical mV readings or historic readings are not a concern because they are corrected during the calibration process and are generally stable between calibration events. Additional confidence in the calibration can be built by performing a linearity check. This is done by placing the sensor in a third reference standard (different from the two used in calibration) and comparing the reading to the expected reading.
Reading mV directly could allow the user to derive a unique mathematical equation relating voltage to pH that is different from the one used in the pH meter. Deriving a unique equation has little purpose for most water monitoring plans.
Follow best practices for pH calibration procedures, considering the goals and constraints of a water quality monitoring program
Record the mV reading during calibrations in a calibration log or laboratory notebook
Watch for sudden changes from prior calibrations to indicate there was an error or change in the calibration procedure, incomplete maintenance, or sensor damage
Use large deviations that develop with time along with slow response times or erratic readings as an indicator that measuring electrode or reference electrode needs to be regenerated or replaced.
Published guidelines on acceptable mV readings or slope percents vary. Rather than relying on absolute values of mV or slope to determine sensor quality, it is best to incorporate the data to a comprehensive QA/QC program where it can be used to assess overall sensor, calibration, and data quality.
References What is pH and How is it Measured: A Technical Handbook for Industry by Frederick J. Kohlman. Hach Company 2003 The Sometimes Maddening Science of pH Measurement by Richard Presley. American Laboratory News June 1999. Standard Methods for the Examination of Water and Wastewater
Turbidity is one of the most talked about parameters in environmental water quality monitoring, yet the details around turbidity measurement are not always known or fully understood. Use our guide below for a better understand of all things turbidity!
The amount of dispersed suspended solids in natural water bodies is an important indicator of water quality. These solids (such as silt, clay, algae, and organic matter) obstruct the transmittance of light through water and create a qualitative characteristic known as turbidity. Turbidity is often closely correlated to climatological or surface water conditions, and therefore indicates changes in environmental conditions of lakes, rivers and streams. For example, high levels of suspended sediment can interfere with photosynthesis by blocking light from reaching aquatic plants. This not only damages vegetation but also results in reduced levels of dissolved oxygen because of the reduction in photosynthesis. Moreover, waters with high levels of suspended solids absorb more light, which can cause an increase in water temperature, creating even lower dissolved oxygen. This stresses aerobic aquatic organisms and could ultimately lead to fish kills.
Turbidity as a Valuable Surrogate
The Clean Water Act requires States to establish total maximum daily loads (TMDLs) of various pollutants to meet water quality standards. The ability to continuously measure water parameters associated with impairments is often limited by technical and financial constraints. Turbidity, however, can be effective as a surrogate measurement because it can be measured in-stream on a continuous basis and it is strongly correlated with sediment, nutrients, and bacteria concentrations. Below is a list of turbidity as a surrogate measurement for many environmental influencers:
Monitoring the impact of humans on natural water bodies.
Monitoring pathogens in water, such as E.coli in storm water runoff from cattle pastures.
Monitoring sediments to track erosion and landscape change.
Monitoring natural streams below mining and dredging operations
Measuring total phosphorous in water is very difficult, but an increase in phosphate or phosphorous typically correlates to an increase in turbidity levels.
Turbidity measurement with the Hydrolab HL4 multiparameter sonde.
Phytoplankton measurement is key for understanding the health of an aquatic ecosystem in both freshwater and saltwater environments.
Measuring phytoplankton can provide valuable insights regarding the biological status of any given aquatic system. Some common applications include:
Primary Productivity Quantification As phytoplankton form the foundation of aquatic food webs, concentrations of phytoplankton can have a direct effect on all organisms higher up on the food chain. Quantifying primary production through phytoplankton biomass measurements is a common way to gather direct insights on the baseline energy available within any given aquatic food web.
Eutrophication / Nutrient Status Monitoring
Eutrophication is the process where nutrients such as nitrogen and phosphorous are loaded into an aquatic system, typically caused by watershed run-off inputs. Eutrophic systems are highly prone to phytoplankton blooms which can lead to dissolved oxygen depletion when phytoplankton cells die off. Phytoplankton monitoring can help water resource managers to control watershed inputs that can affect nutrient loading within aquatic systems.
Harmful Algal Bloom (HAB) Monitoring
Certain species of phytoplankton, mainly cyanobacteria, can release toxins that can cause adverse health effects to humans and animals. Continuous monitoring of phytoplankton levels as part of a broad management plan can help water quality managers to decrease the prevalence of health incidents due to harmful algae.
Drinking Water Management
Certain species of phytoplankton can produce compounds that create taste and odor issues in water, including the compounds 2-MIB and geosmin. Proactive phytoplankton monitoring can provide data that helps managers determine when and where to apply algaecide, as well as which source water intakes to pull from in order to minimize the biological load entering a treatment system.
Identifying the best level logger for your groundwater monitoring application can be a complex task with many different technologies available that are best suited for a variety of different measurement goals.
The most critical information to gather as you start your selection search are the physical characteristics of your groundwater well and the approximate depth-to-water range.
While all groundwater loggers measure level, some have the capability to measure water quality parameters like conductivity, salinity, and total dissolved solids (TDS) as well. These parameters are useful in saltwater intrusion studies in aquifers or also to monitor the impact of man-made activities on groundwater supplies.
A final and important item to consider is the remote data communication (telemetry) element. Remote data communication from a groundwater logger can send updates hourly, daily, or weekly and can limit the number of required field visits to service the well. A variety of transmission technologies are available, though some (like GSM / GPRS) can be limited by the signal strength in your well area.
Click here to read the full OTT Hydromet Groundwater Sensor Selection guide, or see the review the image below for a list of groundwater logger considerations.
Instructions for calibrating dissolved oxygen (DO) sensors are not the same from every manufacturer. For example some manufacturers recommend calibrating in water-saturated air and others in air-saturated water. Then, the recommended methods for making a saturated environment are often different. Furthermore, when it comes to optical dissolved oxygen sensing methods there is inconsistency in requirements for calibration coefficients and membrane replacement frequency. This technical brief aims to minimize the uncertainty in the Hydrolab optical DO (LDO) sensor calibration process.
In principle, sensor calibrations require the sensor be subjected to a calibration standard with a known value to which the sensor reading is compared and adjusted. For a dissolved oxygen sensor, this calibration standard is normally an environment that is 100% saturated with air and water. This environment has known conditions based on an accepted relationship between oxygen concentration, temperature, salinity, and barometric pressure. Therefore controlling or knowing the values of these three variables during calibration is required to have a good calibration standard.
Though ORP is classically based on a standard hydrogen electrode (SHE) as a reference, practical limitations to this approach cause most commercial ORP sensors to use an Ag/AgCl reference.
ORP measurement results are relative to the reference electrode used in the sensor. Through known relationships, results can be converted to other reference systems like the SHE. The Hydrolab HL Series uses a KCl-saturated Ag/AgCl reference but reports results relative to it and the SHE.
The measurement result from an ORP sensor represents the net status of all the oxidation and reduction reactions in the sample being measured. Positive results indicate an oxidizing environment and negative results indicate a reducing environment, when referencing the SHE. Together with pH, temperature, and knowledge of the dominant species in a sample, ORP results help predict the oxidation state of ions in solution and whether certain reactions may take place.
The Hydrolab ORP sensor available on Hydrolab sondes
The Colorado Water Watch is a state and privately funded program brought together by a team of engineers and scientists from the Center of Energy Water Sustainability, making it a neutral third party to measure the impact of natural gas drilling on the surrounding groundwater supplies.
The goal of the project is to gather groundwater monitoring data in real time, and analyze and report it in real or near-real time, depending on whether the data requires further evaluation. The project is designed to bridge the gap between fears about public health impacts caused by oil and natural gas development and the assumption that industry environmental and health practices are reliable.
Calibrating a water quality sensor is a necessary step in creating measurement results that meet the highest standards of accuracy. Water quality instruments that allow user calibration are common. Because calibrations impact the quality of the data retrieved from the instrument it is important to understand the sources of error that may contribute to calibration uncertainty and make procedural adjustments to minimize uncertainty in a calibration result.
One way to frame and visualize the variables that impact the calibration result is a cause and effect diagram, also known as a fishbone diagram (Figure 1). Such a diagram categorizes causes into groups with similarities. A popular way of categorizing causes is by the 6 Ms: machine, method, material, man power, measurement, and Mother Nature. With some modification the 6Ms become a useful set of categories for sources of calibration uncertainty. These are: User, How, Sonde, Weather, Standards, and Location.
Figure 1: Cause and Effect Diagram Illustrating Categories of Factors that Impact Calibration Results
Copper is widely recognized as an effective inhibitor to biological growth and it has been used successfully in many applications where biological activity impedes the desired result. One example is in marine transportation where ship hulls are often treated with copper to be kept free of biological growth that slows the ship’s speed.
In natural aqueous environments, copper ions are released from their solid form and are exposed to microorganisms in sufficient concentrations to be toxic. This is the primary reason copper is such an effective tool for use against biological growth.
Specific to applications in water quality monitoring, instrument manufacturers and their users have been using copper to prevent biological growth from negatively impacting measurements. Experiments and user experience clearly show that copper effectively inhibits biological growth in many aqueous environments. Comparing biological growth rates on untreated surfaces to surfaces that are covered with some form of copper show that biological growth is reduced.
Copper’s effectiveness of significantly preventing erroneous readings due to accumulation of biological growth on water quality sensors is not universally accepted. For example, copper tends to be more effective in saline environments where copper will dissolve more rapidly. Also, biological growth can occur on any untreated surface, such as a pH sensor bulb. As an unintended side effect, copper-clad surfaces – especially surfaces that have not been oxidized – have reflective properties that can artificially influence optical sensors, such as turbidity sensors. Nevertheless, copper is a popular tool that is used often as part of a comprehensive strategy to maximize the success of a water quality monitoring program where bio-fouling is an issue.
Sensors fouled after deployment (L) vs. sensors deployed with copper tape (R)
Electrical conductivity is one of the most common general water quality parameters in surface water and groundwater as it is a popular surrogate measurement for naturally-occurring and anthropogenic contamination of environmental water. Electrical conductivity’s usefulness is based on the fact that water constituents impact its electrical conductivity. Therefore, the measurement result from a conductivity sensor provides insights to water purity.
The electrical conductivity of a water sample increases as temperature increases. Usually temperature compensation methods are applied to the conductivity measurement results that allow users to compare conductivity measurement results from water samples at different temperatures. Scientists have developed temperature compensation methods that are generally accepted. However, no two species or matrices have the exact same relationship between conductivity and temperature. For this reason care should be taken to choose an appropriate compensation method and record the one that was used.