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Digital engineering solutions tailored to your needs

HydroWeb provides water professionals and operators with data-driven insights and predictions to plan and act with confidence. The platform facilitates intelligent management of water system performance and leverages our industry-leading real-time control solution, Csoft®, to optimize complex water systems.

Solutions

HydroWeb is an integrated and intelligent platform to collect, analyze, and manage water system data. This intuitive web platform combines science and engineering expertise with advanced analytics and technology, enabling our clients to protect and manage valuable water resources around the world. Our interdisciplinary teams collaborate with our clients to create customized and scalable digital solutions. HydroWeb can be customized to support smart data collection, advanced analytics, and automated intelligent processes within a secure cloud environment.

HydroWeb builds on more than 20 years of implemented value-generating and pragmatic solutions that have addressed the most challenging problems for water, environment, and sustainable infrastructure programs resulting in optimized performance and reduced asset costs.

Dashboard view of color-coded Thiessen polygons based on rainfall amount and corresponding rainfall statistics per event by rain gauge

Rainfall Analysis

  • Automated rainfall statistics – Automate the process of post-event rainfall analysis including rainfall return periods.
  • Real-time storm tracking – Live updates and integrated graphic display of radar images, rain gauges, Thiessen polygons, and isohyetal analysis.
Dashboard map view of the collection system and facilities with pipe profile view of hydraulic grade line and critical water level indicator of the selected pipes in map view

Collection Systems

  • Data integration – Automate the process of data collection and unification of data from various sources into one single platform with georeferencing so data is contextualized efficiently.
  • System performance tracking – Actively monitor and track system performance using machine learning to classify flows and perform trend analysis to detect and address issues quickly. 
  • Storm impact prediction and analysis – Provide system level and flow predictions using digital twins and machine learning, automate correlation with rainfall and system data to analyze overall performance, and predict pollution events.
  • Integration of modeling tools – Automate model data validation, scenario modeling, and solutions optimization, and visualize results for analysis and comparison.
Intelligent Water System Central Control Room designed by Tetra Tech

Intelligent Water Management with Csoft®

  • Intelligent control – The award-winning Csoft® module provides predictive, systemwide, and coordinated real-time control to sewer networks efficiently, reliably, and safely.
  • System optimization – Maximize the use of conveyance, storage, and treatment capacities to adapt to changing conditions.
  • Cost savings – Reduce capital expenditure while meeting environmental objectives.
  • Improve water quality – Reduce sewer overflows, regulate and balance inflows for treatment with quick reaction time.
  • Build community resiliency – Forecast wet weather impact and reduce risks of flooding.
Dashboard view of water level and flow prediction based on rainfall forecast and video surveillance of multiple critical infrastructure

Flood Warning

  • Reliable data – Integration of real-time monitoring data and video feeds for accurate representation.
  • Digital twin – Integration of 1D, 2D, and 3D modeling and rapid overland flood routing.
  • Anticipation – Early flood warning based on weather forecast, historical data, and flood mapping.
  • Automate alerts – Customizable rules to trigger alerts and send automated notifications.
Dashboard map view of receiving water bodies and beaches with measured and predicted water quality parameters, such as E. Coli by location with color coding based on predetermined thresholds

Water Quality

  • Monitoring – Automate the collection, unification, and correlation of monitoring data.
  • Assessment – Rapid water quality assessment, including percentile and Fundamental Intermittent Standards.
  • Prediction – Automate the simulation of digital twins for predicting quality to generate early warning notifications.
  • Quality Alert – Automated notification based on customizable rules.
Dashboard view of automated reporting information including overflow information, pie charts, performance follow-up summary, and capture rate

Regulatory Reporting

  • Visualization – Virtually mapping out monitoring and overflow locations.
  • Validation – Ability to review, validate data, and add comments before report transmission.
  • Overflow reporting – Improve production efficiency greatly with automated calculations of overflows frequency and duration for event duration monitoring. Automate the generation and transmission of reports to meet regulatory requirements.
Dashboard graphic view of flow and level prediction using artificial intelligence by facility and by rainfall event

Powered by AI

  • Anomaly detection – Automate the detection of monitoring data anomaly with AI.
  • Early detection – Quickly identify sensors needing attention to avoid impact on operation.
  • Confidence – Increase the quality of data available for design and engineering.
  • Prediction – Predict Combined Sewer Overflow (CSO) spills up to 12 or 24 hours in advance through machine learning.
Dashboard view of selected assets, asset summary, site summary, and screening risk summary with color coded scoring results

Asset Management

  • Intuitive navigation – Visualize asset information in dynamic maps, images, tables, and charts.
  • Condition and financial tracking – Communicates and provides an understanding of infrastructure investment plans. Tracks investment and funding progress, asset conditions over time.
  • Failure assessment – Assess the consequence of failures for pump stations, sewers, and other assets. 
  • Predictive maintenance – Advanced analytics for data anomaly, alarms, and sediment accumulation detection to alert maintenance requirement and optimize maintenance planning.
Dashboard map view of systems and projects with graphic view of cumulative cost per water quality improvement and per scenarios

Stormwater and Natural Systems

  • Identification – Automate the identification of best opportunities for sustainable drainage systems and nature-based solutions.
  • Infiltration reduction – Identify opportunities based on modeled and historic data sources.
    Surface water removal – Identify opportunities and calculate water removal benefits.
  • Optimization – Iterative storage optimizer and pass-forward flow time-series assessment to achieve flow control objectives effectively.

Reach out to our experts

  • Automated rainfall statistics – Automate the process of post-event rainfall analysis including rainfall return periods.
  • Real time storm tracking – Live updates and integrated graphic display of radar images, rain gauges, Thiessen polygons and Isohyetal.
  • Data integration – Automate the process of data collection and unification of data from various sources into one single platform with georeferencing so data is contextualized efficiently.
  • System performance tracking – Actively monitor and track system performance and using machine learning to classify flows and perform trend analysis to detect and address issues quickly. 
  • Storm impact prediction and analysis – Provide system level and flow predictions using digital twins and machine learning, automate correlation with rainfall and system data to analyze overall performance and predict pollution events.
  • Integration of modeling tools – Automate model data validation, scenario modeling, solutions optimization and visualize results for analysis and comparison.
  • Intuitive navigation – visualize asset information in dynamic maps, images, tables and charts.
  • Condition and financial tracking – Communicates and provides understanding of infrastructure investment plans. Tracks investment and funding progress, asset conditions over time.
  • Failure assessment – Assess the consequence of failures for pump stations, sewers and other assets. 
  • Predictive maintenance – advanced analytics for data anomaly, alarms, and sediment accumulation detection to alert maintenance requirement and optimize maintenance planning.
  • Identification – Automate the identification of best opportunities for sustainable drainage systems and nature-based solutions.
  • Infiltration reduction – identify opportunities based on modelled and historic data sources.
    Surface water removal – identify opportunities and calculate water removal benefits.
  • Optimization – Iterative storage optimizer and pass-forward flow time-series assessment to achieve flow control objectives effectively.
  • Reliable data – integration of real time monitoring data and video feeds for accurate representation.
  • Digital twin – integration of 1D, 2D and 3D modeling and rapid overland flood routing. 
    Anticipation – Early flood warning based on weather forecast, historical data and flood mapping.
  • Automate alerts – customizable rules to trigger alerts and send automated notifications.
  • Monitoring – automate the collection, unification and correlation of monitoring data.
  • Assessment – rapid water quality assessment, including percentile and Fundamental Intermittent Standards.
  • Prediction – automate the simulation of digital twin for predicting quality to generate early warning notifications.
  • Quality Alert – automated notification based on customizable rules.
  • Visualization – virtually mapping out monitoring and overflow locations.
  • Validation – ability to review, validate data and add comments before report transmission.
  • Overflow reporting – improve production efficiency greatly with automated calculations of overflows frequency and duration for event duration monitoring and automate the generation and transmission of report to meet regulatory requirements.
  • Anomaly detection – automate the detection of monitoring data anomaly with AI
  • Early detection – quickly identify sensors needing attention to avoid impact on operation.
  • Confidence – Increase the quality of data available for design and engineering.
  • Prediction – predict CSO spills up to 12 or 24 hours in advance through machine learning.
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