Forecasting your environmental data

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In the world of data visualization, understanding the past and predicting the future is essential, and that’s exactly what our new Forecast Charts are designed to help you achieve. Todd Pierce, Vice President of Data Management and Visualization at Locus Technologies will tell you more about this feature.

Click the video to learn more.

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    Finally, An Environmental Software Suite that Works Together

    When looking for a GHG reporting program, there is one element that is typically overlooked. This short video gives us more insight.

    What do DMRs and EDDs have in common that pains us?


    Almost everyone has run into Discharge Monitoring Reports (DMRs) and Electronic Data Deliverables (EDDs) when managing and reporting environmental data. And almost everyone hates them. So, what do these things have in common? They should all be the same, yet they are all different with a wide range of variations.   

    For EDDs, every data system (Federal, State and Commercial) requires a different format for data submittal. Some want you to manually fill in an online form, some want a CSV file in a specific format, and some want XML files, also in various formats. Analytical laboratories have to produce and maintain a wide range of formats from their LIMs systems to meet the demands of the different receiving systems, and commercial data systems have to produce a wide range of exports to go to various agencies. Even agencies like the EPA don’t have a single uniform regulatory export format for all the various regions. And basically, this is all the very same analytical laboratory data, just delivered in multiple formats, all of which require configuration and maintenance by dedicated IT professionals.  

    Many EDDs are submitted as a single flat file (one row equates to one record), but the number of columns and different data rules. However, state-specific formats can have other more complicated formats. One prime example is California’s Electronic Deliverable Format (EDF) which can require 3 or 5 files that contain various information parsed out into different record sets. The records in the different files can have one-to-many or many-to-many relationships.   

    DMRs are another area of constant challenge and frustration. The EPA tried to provide a uniform submittal process with NetDMR, but it failed to work when individual states or local cities were the responsible agency vs the EPA. So not only are there format submittal variations, but there is also a wide variation in how DMR parameter limits are calculated and reported. Yes, receiving waters will vary by location and concerns for the constituents of the discharge, but it would be a huge step forward to have a set of consistent rules to apply to all DMRs.   

    The lack of uniform parameter codes is also another source of frustration. Most commercial data systems and laboratory LIMS systems rely on the uniform Chemical Abstract Service (CAS) numbers to identify a parameter. These codes are used worldwide and commonly accepted. DMRs typically require the more obscure STORET codes (see example below) used by older EPA data systems


    For all these reasons, DMRs and EDDs are much disliked by anyone managing environmental data for a living. Both processes would benefit from a uniform set of standards and a historical data update to streamline data management and reporting for all parties. However, just as with cars, Locus knows how to help you manage your EDDs and DMRs, just as a mechanic can fix different auto makes/models. 


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      Valley Water selects Locus Environmental Software for Data Collection and Management

      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.  

      Stay in Compliance With Smart Sample Planning and Management Tools

      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

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        Top 10 Enhancements to Locus Environmental Software in 2019

        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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          Predicting Water Quality with Machine Learning

          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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            Is PFAS Contamination in US Drinking Water Supply the Next Crisis?

            In most cities in the US, drinking water quality conforms with the norms of the Safe Drinking Water Act, which requires EPA to set Maximum Contaminant Levels (MCL) for potential pollutants. Besides, the EPA’s Consumer Confidence Rule (CCR) of 1998 requires most public water suppliers to provide consumer confidence reports, also known as annual water quality reports, to their customers.

            PFAS stands for “perfluoroalkyl and polyfluoroalkyl substances,” with the most important thing to know that this large group of synthetic chemicals includes perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS).

            Not Regulated by EPA

            When it comes to drinking water from the tap in the US, the phrase that fits concerning PFOA and PFOS is “caveat emptor” (buyer beware). The EPA has not regulated these chemicals. There are no federal regulations for PFOA and PFOS in drinking water in the US.

            In May 2016, the EPA established a drinking water “health advisory” of 70 parts per trillion (ppt) for the combined concentrations of PFOA and PFOS. While that was a start, there’s a big difference between a health advisory and a regulation that has teeth. Moreover, many scientists consider 70 ppt too high a limit. Reportedly, the EPA is considering turning its 70 ppt health advisory into regulation.

            Meanwhile, some states have stepped up to the plate to protect their residents and visitors better. In April 2019, for instance, the New Jersey Department of Environmental Protection (DEP) proposed maximum contamination levels (MCLs) of 14 ppt for PFOA and 13 ppt for PFOS in the state’s drinking water.

            As a water consumer, you should be aware of this crisis, as it has the potential to affect both your health and wealth.

            What are PFOA and PFOS?

            This toxic couple has contaminated the drinking water supply in areas surrounding some industrial sites and military bases. They’re the most studied of the PFAS group because they’re the ones that have been produced in the most significant quantities in the United States, according to the US Environmental Protection Agency (EPA).

            PFOA and PFOS, which repel water and stains of various types, have been used as coatings on fabrics and leather and in the production of stain-repellent carpeting and are found in firefighting foams — which have been used extensively on US military bases for decades — among other products. Moreover, some related polyfluoroalkyl compounds can be transformed into these chemicals in the environment, per the National Institutes of Health (NIH), with the Environmental Working Group (EWG) stating that some perfluorinated chemicals not only break down into PFOA in the environment but also can do so in the human body.

            While PFOA and PFOS are no longer made in the US, that hardly matters in our global economy. Both are still produced internationally, which means they end up in our country via imports of consumer goods such as carpet, apparel, textiles, and paper and packaging.

            Why all the concern about PFOA and PFOS?

            These chemicals — dubbed “forever chemicals” because they’re persistent in the environment and the human body — have been linked to cancer, thyroid disease, weakened the immune system and liver function, low infant birth weight, and other health problems, according to many sources.

            And this is what the EPA says: “There is evidence that exposure to PFAS can lead to adverse health outcomes in humans. If humans, or animals, ingest PFAS…the PFAS are absorbed and can accumulate in the body. PFAS stay in the human body for long periods. As a result, as people get exposed to PFAS from different sources over time, the level of PFAS in their bodies may increase to the point where they suffer from adverse health effects.”

            EHS Digital Transformation: Managing Drinking Water Quality Data and Compliance: CCR in the Cloud

            In most industrialized cities around the world, drinking water is readily available and safe. Safeguarding groundwater (aquifers), streams, rivers, reservoirs, and lakes is crucial to continue delivering clean water on the tap. So is testing and validated water quality data. There are several aspects of drinking water quality that is of concern in the United States, including Cryptosporidium, disinfection by-products, lead, perchlorates, and pharmaceutical substances.

            Mobile - Managing Drinking Water Quality Data and Compliance

            Recent headlines about water quality issues in cities like Flint, Pittsburgh, Asheville, or Rome and Capetown are motivating consumers to ask more questions about their water quality. Albuquerque’s groundwater is becoming seriously depleted; Fresno’s groundwater is highly susceptible to contamination; In Atlanta, Chicago, Detroit, Houston, Los Angeles, New Orleans, Newark, Philadelphia, Phoenix, San Diego and Washington, D.C., source water is threatened by runoff and industrial or sewage contamination; Water supplies in Baltimore, Fresno, Los Angeles, New Orleans, San Diego, and several other cities are vulnerable to agricultural pollution containing nitrogen, pesticides or sediment.

            Drinking water supply

            Locus Technologies IoT Monitoring. Connected at all times.

            In most cities in the US, drinking water quality is in conformity with the norms of the Safe Drinking Water Act, which requires EPA to set Maximum Contaminant Levels (MCL) for potential pollutants. In addition, the EPA’s Consumer Confidence Report (CCR) Rule of 1998 requires most public water suppliers to provide consumer confidence reports, also known as annual water quality reports, to their customers. Each year by July 1 anyone connected to a public water system should receive in the mail an annual water quality report that tells where water in a specific locality comes from and what’s in it. Locus EIM automates this reporting and allows utilities to be transparent by publishing CCR online in real time so that consumers have access to their CCR at all times. Consumers can also find out about these local reports on a map provided by EPA.

            Utilities must maintain good water quality records and manage them in a secure database with built-in alerts for any outliers so that responsible water quality managers can react quickly when there is exceedance of MCL or another regulatory limit.

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            Cut your monitoring costs with EIM sample planning

            Sample planning can be a valuable and necessary tool for many in highly regulated fields, including water utilities, where adherence to regulatory defined sampling schedules is essential.  Moreover, if you have reviewed the drinking water requirements, you know the regulations require complex and variable schedules ranging from monthly samples at routine locations for a set list of parameters to once every five, seven, or nine years at other locations for a completely different list of parameters.  Missing a required sampling event can mean fines and public notice to customers.

            Other industries face similar complex sampling needs and the financial and reputational impacts can be hefty for missing required samples. So if you are currently an EIM user, or considering an environmental information management system, don’t forget about sample planning components that will save you time and money.

            Here are some benefits of Sample Planning that may make you a believer.

            Streamline routine or repetitive sampling – set it up once and reuse or modify as needed

            Sample Planning in EIM excels in streamlining repetitive sampling, such as required drinking water samples, or quarterly monitoring well samples.  Any sampling events with a schedule from daily to once every 10 years can be planned in EIM’s module and reused again and again, even with tweaks to the schedule for the samples to be collected.  Imagine the time savings and the simplicity of having your regulatory requirements all lined out for the year and not have to worry about missing required samples.  For water utilities, this is especially valuable given the very strict schedules and the public health implications of missing sampling events.

            EIM screenshot of sample planning edit form with email notification and calendars popouts



            Automatically generate COCs and bottle labels

            When samples are planned in EIM, it is a few simple clicks of the mouse to generate COCs, work lists, and bottle labels for the field crew.  This saves time for the field and office staff, and helps ensure they collect the needed samples and not miss a collection or a field or laboratory parameter. Moreover, higher levels of accuracy and fewer transcription errors are ensured as sample IDs and requested analyses are printed electronically rather than entered by hand.

            Screenshots of sample planning module with form and environmental reporting output


            Its fully integrated with Locus Mobile  – you can send your Sample Plan to field staff to ensure they collect the samples needed

            For customer’s considering using Locus Mobile to streamline their field data collection, Sample Planning is a natural fit.  All the samples planned in the Sample Planning module can be delivered directly to Locus Mobile for one or more field staff.  You can even have multiple different events sent to the field crew so they can plan ahead in the field.  All the collected data is uploaded to EIM in real-time (if service is available) or later (if not) for review and final checks after the field event is concluded.  Imagine giving your sampling teams the weekly plan and tracking the progress each day as they sync their data.  A handy feature of Locus Mobile, it can remove all the previously collected samples from the plan each day to make your field sampler’s life much simpler.

            Larger drinking water utilities will find the integration of Sample Planning and mobile quite appealing, especially with daily sampling by multiple sampling teams and a large number of required routine samples.

            Locus Mobile


            Analytical Results GridAll your required field sample information is already in EIM for your sampling event.

            When lab data comes back from the lab, you no longer need to enter in the field sample information, it will already be in EIM.

            For drinking water utilities, where you may be sampling daily for chlorine at your sample locations, imagine seeing the results across your distribution system instantly, and ability to see it on a map in near real time.  Even better, you can share the results with your operations team with a simple dashboard link.



            Locus sample planning module with configurable calendars and email notifications

            Always know where you stand on your sampling activities

            By using Sample Planning, you will know exactly what samples have and have not been collected.  You will also know which ones were collected late, and which ones are yet to be collected.  This type of information can help ensure you don’t’ miss required samples, and identify schedule impacts when collection is not going according to plan.

            When missed samples are identified, its easy to add to the next day’s sampling and send that information to field teams using the integrated mobile app.



            Environmental data management and environmental reporting software- EIM screenshot in labGain ability to track receipt of laboratory results with fine precision

            For customers that need to track laboratory results down to the method and analyte level, Sample Planning will make that tedious task easy.  Therefore, if you ordered an EPA Method 6010C analysis and no result for lead is reported, you will know immediately when the results arrive back from the lab that the deliverable is incomplete.  EIM will also tell you when the lab substituted one method for another. You can then decide whether this change is acceptable or not.  Because most regulations include a long list of required analytes and acceptable methods, this type of detail is invaluable to help ensure that you remain in compliance.



            Locus EIM - Lab invoice trackingMake review of laboratory invoice easy as pie

            Trying to review laboratory invoices, especially for large sampling events or complex sampling programs, can be a chore.  With EIM’s Sample Planning module, most of the hard work is already done for you.  Once you have all your data back, EIM will tell you:

            • If the quantity invoiced is more than the order
            • If an invoiced line item has been invoiced previously
            • If an invoiced line item total cost and/or unit cost is incorrect