Attention all water providers: the EPA’s UCMR 5 list includes 30 contaminants (29 PFAS and lithium) that both small and large water systems have to test for and report. Can your current environmental solution handle it?

Locus EIM environmental software can handle new chemicals and analyses seamlessly. Both the standard Locus EIM configuration and the Locus EIM Water configuration (specially tailored to water utilities) are built with ever-changing regulations in mind.

We’ve put together some helpful background and tips for water providers preparing for UCMR 5 monitoring.

What water providers need to know

  • The fifth and latest list (UCMR 5) was published on March 11, 2021, and includes 30 new chemical contaminants that must be monitored between 2023 and 2025 using specified analytical methods.
  • SDWA now requires that UCMR include all large PWSs (serving >10,000 people), all PWSs serving between 3,300 and 10,000 people, and a representative sample of PWSs serving fewer than 3,300 people.
  • Large systems must pay for their own testing, and US EPA will pay for analytical costs for small systems.
  • Labs must receive EPA UCMR approval to conduct analyses on UCMR 5 contaminants.

EPA UCMR 5 Infographic

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What’s the UCMR and why are some contaminants unregulated?

In 1996, Congress amended the Safe Drinking Water Act with the Unregulated Contaminant Monitoring Rule (UCMR). Under this new rule, US EPA can require water providers to monitor and collect data for contaminants that may be in drinking water but don’t have any health-based standards set (yet) under the SDWA.

More than 150,000 public water systems are subject to the SDWA regulations. US EPA, states, tribes, water systems, and the public all work together to protect the water supply from an ever-growing list of contaminants.

However, under the UCMR, US EPA is restricted to issuing a new list every five years of no more than 30 unregulated contaminants to be monitored by water providers.

This helps reduce the burden on water providers, since monitoring and testing for the existing long list of regulated contaminants already requires a significant investment of time and resources.

Throughout the course of this monitoring, US EPA can determine whether the contaminants need to be officially enforced— but this would require regulatory action, routed through the normal legislative process.

Tips for managing UCMR in Locus EIM logo

  • DO use EIM’s Sample Planning module to set your sample collection schedule ahead of time, as requirements vary and are on specific schedules
  • DO take advantage of EIM’s sample program features to track and manage UCMR data, or consider using a dedicated location group to track results, keeping them separate and easy to find for CCR reporting.
  • DON’T worry about adding in new analytical parameters in advance. With EIM’s EDD loader, you can automatically add them when the data arrive from the laboratory.

Contact your Locus Account Manager for help setting up your EIM database in advance of your sampling schedule, and we’ll make sure you’re equipped for UCMR 5!

Not yet a customer? Send us a quick note to schedule a call or a demo to find out how Locus software can completely streamline your water sampling and reporting.

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    MOUNTAIN VIEW, Calif., 18 February 2021 — Locus Technologies (Locus) is pleased to announce that The City of Hillsboro Water Department, Oregon has selected Locus EIM to centralize their water data management. Hillsboro Water will utilize Single Sign-On (SSO) for added security and Locus Mobile for field data collection.

    Locus EIM is a leading cloud solution for streamlining water quality data. First developed in 1999, Locus EIM was the first SaaS solution for managing analytical data. Locus EIM is a robust solution for planning, collecting, analyzing, and reporting environmental data.

    Hillsboro Water manages four public water systems (Hillsboro, Cherry Grove, Butternut Creek, and the Joint Water Commission) for almost half a million customers, as well as Barney Reservoir. Locus EIM will be used to enhance the tracking and managing of Hillsboro Water’s water quality data, coordination of regulatory requirements, and to aid in making data-driven decisions.

    “Locus EIM allows us to easily plan, record, QA/QC, and manage our water quality data collected from many different labs and routine field sampling. We are excited to have a software that helps us to quickly make data-based decisions to ensure safe and reliable drinking water for our rapidly growing community,” said Sarah Honious, Water Quality Program Coordinator, City of Hillsboro.

    “The City of Hillsboro Water Department has a complex and technical set of water quality and regulatory sampling protocols. By utilizing Locus EIM, they can now make key decisions based on the analysis of their data, improving the daily lives of their customers,” said Wes Hawthorne, President of Locus.

    ABOUT THE CITY OF HILLSBORO WATER DEPARTMENT
    The City of Hillsboro, through its appointed three-member Utilities Commission, owns and operates a municipal drinking water system that serves more than 80 percent of Hillsboro residents and businesses. Its delivery of clean, reliable water protects public health, enables emergency fire protection, and supports the City’s economic vitality. Learn more at Hillsboro-Oregon.gov/Water.

    Contact us to learn more about Locus’ Water solutions

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      Let’s look back on the most exciting new features and changes made in EIM, Locus’ environmental data management software, during 2020!

      Locus EIM Devices

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      1. Expanded EIM API

      Locus expanded the EIM application programming interface (API) to support running any EIM Expert Query. Using a drag and drop interface, an EIM user can create an Expert Query to construct a custom SQL query that returns data from any EIM data table. The user can then call the Expert Query through the API from a web browser or any application that can consume a REST API. The API returns the results in JSON format for download or use in another program. EIM power users will find the expanded API extremely useful for generating custom data reports and for bringing EIM data into other applications.[/sc_icon_with_text]

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      2. Enhanced EIM Search Bar Functionality

      Locus enhanced the usefulness of the EIM search box located at the top right of EIM. A user can now search for a location, field sample, or parameter, and choose from quick links showing any found data records plus related field measurements, groundwater levels, or analytical results. The search box also supports searches across EIM help files. These improvements, along with the existing ability to search for EIM menu items or functions, greatly increase the search bar’s usefulness and make it much easier for users to find what they need. In 2021, Locus plans on further expanding the search bar to allow for generating charts or maps for entered locations or parameters.[/sc_icon_with_text]

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      3. Multisite Support for EIM GIS+

      The EIM GIS+ package brings the power of geographical information systems (GIS) to EIM. In 2020, Locus added multisite support for the GIS+. A user can generate a map showing locations and related results for more than one EIM site at a time. This GIS+ improvement supports cross-site queries and maps, which help greatly with analysis across a portfolio of sites in EIM.[/sc_icon_with_text]

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      4. Support for Sample Planning Notifications

      Locus rolled a new EIM feature in 2020 to support automated email notifications for sample planning events. Users can subscribe to notifications for unreported analysis groups, parameters, or samples; late and upcoming samples; and compliance samples at risk of being late. Each notification can be tailored for specific plans, events, and tasks, and are set to run for specific time window. With these new notification types, users gain more control over their sample planning and are better notified about potential issues. The new sample planning notifications are available in Water EIM but can be deployed to other customer EIM instances on request.[/sc_icon_with_text]

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      5. Continued Water EIM Reporting Support

      EIM is the world’s leading water quality management software used since 1999 by many Fortune 500 companies, water utilities, and the US Government. Locus continues to support water utility customers in EIM through multiple updates done to EIM reporting and analysis. From enhanced support for chlorine field data, to incorporating the latest reporting requirements for the Consumer Confidence Report, Locus continues to expand Water EIM functionality while accounting for variable practices that exist among water utility operators.[/sc_icon_with_text]

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      6. Improved Analytical Views

      Locus continues to upgrade and improve the EIM interface and user experience. In 2020, Locus overhauled the Analytical Views pages in EIM, which support data exports for analytical results as well as laboratory QC samples and results. Multiple EIM menu items were combined into one page that supports all analytical data views. Users are directed through a series of filter selections that culminate in a grid of results. The new page improves usability and provides one centralized place for these data reports.[/sc_icon_with_text]

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      7. Enhanced FTP EDD Loader Abilities

      One of the more powerful modules in EIM is the FTP EDD loader, which lets laboratory users upload multiple analytical EDD files for different sites to a Locus FTP server for batch processing. Lab users do not have to login to EIM to upload each EDD individually. In 2020, Locus augmented this function to support non-analytical EDDs and to accept EDDs from non-lab users. With these changes, any EIM user can upload to the FTP site any number of EDD files in any format for multiple sites. Users may still need to login to EIM to resolve any EDD errors. Interested EIM users should contact Locus to get the needed FTP site credentials.[/sc_icon_with_text]

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      8. Expanded DMR Support

      Locus continues to enhance the Discharge Monitoring Report (DMR) module in EIM. In 2020, Locus implemented calculations needed to handle reporting of divalent metals. Locus also added the Florida DEP ezDMR format. Locus continues to add more formats so customers can meet their reporting requirements.[/sc_icon_with_text]

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      9. Improved Parameter Management

      Locus added two new features in EIM to improve support for managing analytical parameters. First, EIM now allows for storing parameter names in the local language and using these translated names in EIM Enhanced Formatted Reports. This function helps non-English customers create reports customized for local users. Second, EIM can handle alternate parameter codes. These ‘aliases’ for the primary parameter code, used in tracking reports and in EDD uploads, ensure that labs are not flagged or penalized for using a parameter code that is synonymous with the expected EIM parameter code.[/sc_icon_with_text]

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      10. Improved Unit Conversions

      Locus enhanced the unit conversion functions in EIM in 2020; these functions are used to convert laboratory analytical results to a consistent set of reporting units. EIM now allows for conversion factors that are parameter specific. Second, EIM now lets users define molecular weight multipliers for use in unit conversions that require molecular weight calculations. Both these changes give users more control and transparency over unit conversions in EIM.[/sc_icon_with_text]

      Contact us to see a demo of Locus EIM and get a quote

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        Becoming water positive is a more difficult task than becoming carbon positive. Both in practice and in tracking complex water data. Less than a decade ago, experts questioned if it was even feasible to have a net-positive impact when it comes to water. Perhaps the biggest reason for the difficulty with water is a relative volatility when compared with carbon. Seasonal environmental changes in rainfall, as well as droughts and floods, effectively make water consumption a non-zero-sum game. And with water, quality is more important than volume. Today, companies and organizations are believing that goal a more attainable one.

        Locus Mobile for Water Quality

        Organizations are now shooting for a goal that will create a net-positive impact on volume and quality. Recently, Microsoft announced their goal of becoming water positive by 2030. Their goal is not only impressive, but it is complex and multi-faceted. They plan to achieve more freshwater collection, lower consumption, working with various agencies and NGOs on regulatory changes, and perhaps most importantly digitizing their water data.

        Why is this goal so important? Almost a third of the world’s population, over 2.2 billion individuals, lack access to safe and clean water. With potential chronic shortages becoming more common and increased demand being more likely, the need for fresh water will be more drastic as time goes on. Organizations aiming for water positivity will lessen the momentum of water becoming less available.

        Screenshot of EIM water utility dashboard and mobile app for locations

        Where does Locus come in? We can’t solve a problem that we can’t understand. With Locus software, companies and organizations can accurately track and report complex ground and surface water data. Our calculation engine can deliver real-time estimates of supply and demand and our water quality software can manage sample planning and configure notifications for late or missing samples or exceedances in pre-defined limits. Our water quality solutions, long used by utilities like San Jose Water Company and Santa Clara Valley Water, can also help businesses achieve a greater perspective on their water consumption, providing the tools to allow them to become water positive.

        Contact us today to start down the path of water positivity

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          Locus will provide water quality and analytical data management software for Valley Water

          MOUNTAIN VIEW, Calif., 1 September 2020 — Locus Technologies (Locus), industry leader in water data management software, today announced that Valley Water (formerly Santa Clara Valley Water District) has chosen Locus environmental software for their data collection and management. 

          Valley Water has selected Locus’ environmental software, EIM, following consultant work Locus provided for the utility going back 14 years. They will seek to utilize Locus EIM as a laboratory database management system, and for data analytics.Locus EIM will be used to manage sample data for over 200 million gallons of drinking water consumed daily by over 2 million people in the district. 

          Valley Water has an award-winning track record of bringing the highest-quality water to the Bay AreaBeing local, we see the hard work that Valley Water puts into providing some of the best drinking water available anywhereWe are proud to be a part of that process,” said Wes Hawthorne, President of Locus.  

          Imagine the time savings and the simplicity of having your regulatory requirements all lined out for the year without having to worry about missing required samples. For water utilities, this is especially valuable given the strict schedules and public health implications of missing sampling events. Locus sample planning streamlines repetitive sampling, such as required samples for drinking water or monitoring wells. Any sampling events can be planned and reused repeatedly, even with tweaks to the schedule for the samples to be collected. We’ve outlined some key features of Locus sample planning in this infographic.

          Locus Sample Planning

          Contact us to see Sample Planning in action

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            Let’s look back on the most exciting new features and changes made in EIM, Locus’ environmental data management software, during 2019!

            1. Migration to AWS Cloud

            In August, Locus migrated EIM into the Amazon Web Services (AWS) cloud. EIM already had superior security, reliability, and performance in the Locus Cloud. The move to AWS improves on those metrics and allows Locus to leverage AWS specific tools that handle big data, blockchain, machine learning, and data analytics. Furthermore, AWS is scalable, which means EIM can better handle demand during peak usage periods. The move to AWS helps ensure that EIM remains the world’s leading water quality management software.

            Infographic: 6 Benefits of EHS on AWS

            2. SSO Login

            EIM now supports Single Sign-On (SSO), allowing users to access EIM using their corporate authentication provider. SSO is a popular security mechanism for many corporations. With SSO, one single login allows access to multiple applications, which simplifies username and password management and reduces the number of potential targets for malicious hacking of user credentials. Using SSO with EIM requires a one-time configuration to allow EIM to communicate with a customer’s SSO provider.

            Locus Single Sign On (SSO)

            3. GIS+ Data Callouts

            The Locus GIS+ solution now supports creating data callouts, which are location-specific crosstab reports listing analytical, groundwater, or field readings. A user first creates a data callout template using a drag-and-drop interface in the EIM enhanced formatted reports module. The template can include rules to control data formatting (for example, action limit exceedances can be shown in red text). When the user runs the template for a specific set of locations, EIM displays the callouts in the GIS+ as a set of draggable boxes. The user can finalize the callouts in the GIS+ print view and then send the resulting map to a printer or export the map to a PDF file.

            Locus GIS+ Data Callouts

            4. EIM One

            For customers who don’t require the full EIM package, Locus now offers EIM One, which gives the ability to customize EIM functionality. Every EIM One purchase comes with EIM core features: locations and samples; analytical and field results; EDD loading; basic data views; and action limit exceedance reports. The customer can then purchase add-on packages to get just the functionality desired–for example a customer with DMR requirements may purchase the Subsurface and Regulatory Reporting packages. EIM One provides customers with a range of pricing options to get the perfect fit for their data management needs.

            EIM One Packages

            5. IoT data support

            EIM can now be configured to accept data from IoT (internet of things) streaming devices. Locus must do a one-time connection between EIM and the customer’s IoT streaming application; the customer can then use EIM to define the devices and data fields to capture. EIM can accept data from multiple devices every second. Once the data values are in EIM, they can be exported using the Expert Query tool. From there, values can be shown on the GIS+ map if desired. The GIS+ Time Slider automation feature has also been updated to handle IoT data by allowing the time slider to use hours, minutes, and seconds as the time intervals.

            Locus IoT Data

            6. CIWQS and NCDEQ exports

            EIM currently supports several dozen regulatory agency export formats. In 2019, Locus added two more exports for CIWQS (California Integrated Water Quality System Project) and the NCDEQ (North Carolina Department of Environmental Quality). Locus continues to add more formats so customers can meet their reporting requirements.

            CIWQS and NCDEQ Exports

            7. Improved Water Utility reporting

            EIM is the world’s leading water quality management software, and has been used since 1999 by many Fortune 500 companies, water utilities, and the US Government. Locus added two key reports to EIM for Water in 2019 to further support water quality reporting. The first new report returns chlorine averages, ranges, and counts. The second new report supports the US EPA’s Lead and Copper rule and includes a charting option. Locus will continue to enhance EIM for Water by releasing the 2019 updates for the Consumer Confidence Report in January 2020.

            Locus Water Utility Reporting

            8. Improved Non-Analytical Views

            Locus continues to upgrade and improve the EIM user interface and user experience. The most noticeable change in 2019 was the overhaul of the Non-analytical Views pages in EIM, which support data exports for locations, samples, field readings, groundwater levels, and subsurface information. Roughly 25 separate pages were combined into one page that supports all these data views. Users are directed through a series of filter selections that culminate in a grid of results. The new page improves usability and provides one centralized place for these data reports. Locus plans to upgrade the Analytical Views in the same way in 2020.

            Non-analytical views in Locus EIM

            9. EIM search box

            To help customers find the correct EIM menu function, Locus added a search box at the top right of EIM. The search box returns any menu items that match the user’s entered search term. In 2020, Locus will expand this search box to return matching help file documents and EDD error help, as well as searches for synonyms of menu items.

            Locus EIM Quick Search

            10. Historical data reporting in EDD loading

            The EIM EDD loader now has a new “View history” option for viewing previously loaded data for the locations and parameters in the EDD. This function lets users put data in the EDD holding table into proper historical context. Users can check for any unexpected increases in parameter concentrations as well as new maximum values for a given location and parameter.

            Historical Data in Locus EIM

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              The Environmental Protection Agency (EPA) announced that it would impose stricter requirements on water utilities to manage lead and copper contamination in drinking water supplies. The EPA said that tackling water pollution is a core duty of the agency.

              The proposed changes, the first affecting lead level in water since 1991, would also give utilities more time to replace lead pipes in their systems. Some environmental groups are not happy with the proposed rule because the change slows by 20 years the timeline for removing aging lead service pipes that could expose children to lead. Lead is a toxin known to harm developing brains. The rule slows down the removal of pipelines where lead levels exceed 15 μg/L to 33 years from the 13 years in the original law.

              The new rule requires water utilities to identify and remove sources of lead when a water sample at faucet exceeds 15 micrograms per liter (μg/L). The EPA said water systems would also have to follow new, improved sampling procedures and adjust sampling sites to better target locations with higher lead levels.

              Health advocates estimate that as many as six million or more lead water lines remain underground in U.S. cities and towns. Additional sampling and monitoring can help to identify affected areas, and ensure the quality of drinking water sources.

              [sc_button link=”https://www.locustec.com/applications/industry/water-utilities/” text=”Locus for water quality management” link_target=”_self” color=”#ffffff” background_color=”#52a6ea” centered=”1″]

              At Locus Technologies, we’re always looking for innovative ways to help water users better utilize their data. One way we can do that is with powerful technologies such as machine learning. Machine learning is a powerful tool which can be very useful when analyzing environmental data, including water quality, and can form a backbone for competent AI systems which help manage and monitor water. When done correctly, it can even predict the quality of a water system going forward in time. Such a versatile method is a huge asset when analyzing data on the quality of water.

              To explore machine learning in water a little bit, we are going to use some groundwater data collected from Locus EIM, which can be loaded into Locus Platform with our API. Using this data, which includes various measurements on water quality, such as turbidity, we will build a model to estimate the pH of the water source from various other parameters, to an error of about 1 pH point. For the purpose of this post, we will be building the model in Python, utilizing a Jupyter Notebook environment.

              When building a machine learning model, the first thing you need to do is get to know your data a bit. In this case, our EIM water data has 16,114 separate measurements. Plus, each of these measurements has a lot of info, including the Site ID, Location ID, the Field Parameter measured, the Measurement Date and Time, the Field Measurement itself, the Measurement Units, Field Sample ID and Comments, and the Latitude and Longitude. So, we need to do some janitorial work on our data. We can get rid of some columns we don’t need and separate the field measurements based on which specific parameter they measure and the time they were taken. Now, we have a datasheet with the columns Location ID, Year, Measurement Date, Measurement Time, Casing Volume, Dissolved Oxygen, Flow, Oxidation-Reduction Potential, pH, Specific Conductance, Temperature, and Turbidity, where the last eight are the parameters which had been measured. A small section of it is below.

              Locus Machine Learning - Data

              Alright, now our data is better organized, and we can move over to Jupyter Notebook. But we still need to do a bit more maintenance. By looking at the specifics of our data set, we can see one major problem immediately. As shown in the picture below, the Casing Volume parameter has only 6 values. Since so much is missing, this parameter is useless for prediction, and we’ll remove it from the set.

              Locus Machine Learning - Data

              We can check the set and see that some of our measurements have missing data. In fact, 261 of them have no data for pH. To train a model, we need data which has a result for our target, so these rows must be thrown out. Then, our dataset will have a value for pH in every row, but might still have missing values in the other columns. We can deal with these missing values in a number of ways, and it might be worth it to drop columns which are missing too much, like we did with Casing Volume. Luckily, none of our other parameters are, so for this example I filled in empty spaces in the other columns with the average of the other measurements. However, if you do this, it is necessary that you eliminate any major outliers which might skew this average.

              Once your data is usable, then it is time to start building a model! You can start off by creating some helpful graphs, such as a correlation matrix, which can show the relationships between parameters.

              Locus Machine Learning - Corr

              For this example, we will build our model with the library Keras. Once the features and targets have been chosen, we can construct a model with code such as this:

              Locus Machine Learning - Construct

              This code will create a sequential deep learning model with 4 layers. The first three all have 64 nodes, and of them, the initial two use a rectified linear unit activation function, while the third uses a sigmoid activation function. The fourth layer has a single node and serves as the output.

              Our model must be trained on the data, which is usually split into training and test sets. In this case, we will put 80% of the data into the training set and 20% into the test set. From the training set, 20% will be used as a validation subset. Then, our model examines the datapoints and the corresponding pH values and develops a solution with a fit. With Keras, you can save a history of the reduction in error throughout the fit for plotting, which can be useful when analyzing results. We can see that for our model, the training error gradually decreases as it learns a relationship between the parameters.

              Locus Machine Learning - Construct

              The end result is a trained model which has been tested on the test set and resulted in a certain error. When we ran the code, the test set error value was 1.11. As we are predicting pH, a full point of error could be fairly large, but the precision required of any model will depend on the situation. This error could be improved through modifying the model itself, for example by adjusting the learning rate or restructuring layers.

              Locus Machine Learning - Error

              You can also graph the true target values with the model’s predictions, which can help when analyzing where the model can be improved. In our case, pH values in the middle of the range seem fairly accurate, but towards the higher values they become more unreliable.

              Locus Machine Learning - Predict

              So what do we do now that we have this model? In a sense, what is the point of machine learning? Well, one of the major strengths of this technology is the predictive capabilities it has. Say that we later acquire some data on a water source without information on the pH value. As long as the rest of the data is intact, we can predict what that value should be. Machine learning can also be incorporated into examination of things such as time series, to forecast a trend of predictions. Overall, machine learning is a very important part of data analytics and the development of powerful AI systems, and its importance will only increase in the future.

              What’s next?

              As the technology around machine learning and artificial intelligence evolves, Locus will be working to integrate these tools into our EHS software. More accurate predictions will lead to more insightful data, empowering our customers to make better business decisions.

              Contact us today to learn how machine learning and AI can help your EHS program thrive

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                Locus will provide cloud environmental water quality software with GIS and mobile integration 

                MOUNTAIN VIEW, Calif., 9 July 2019 — Locus Technologies, (Locus), the industry leader in water quality, EHS, sustainability, and compliance management software, is pleased to announce that the City of San Marcos, Texas Water/Wastewater Utility selected Locus Environmental Information Management (EIM) software to streamline water quality and wastewater management and compliance.

                “With Locus’ water quality software we can streamline and modernize how we manage and report our critical water quality and wastewater data,” said Ron Riggins, San Marcos Water Quality Manager. “With an integrated mobile application, we will be able to access and react to field information faster than ever before.”

                “By selecting Locus EIM water quality software, the City of San Marcos, Texas can simplify managing water and wastewater data and integrate with their existing GIS system. This will provide them a modern cloud solution with fully integrated mobile capabilities,” said Wes Hawthorne, President of Locus.