The Curriculum Network.
Ready-to-use teaching resources built on real sites, real data, and real tools. Different platforms, different pedagogies — one unified network. Jump straight to your platform's curriculum, or browse what's shared across all five.
Why this matters — strategically
The foundation beneath the network.
The first water-modeling platform where students, researchers, practitioners, and agencies operate in one continuous system. Where the next generation learns the same way they will work — and where their work, from the first investigation onward, joins the same network experts and decision-makers are using today.
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A union of communities that haven't shared one platform — until now.
Water work has historically lived in separate worlds. Classrooms have taught with simplified educational tools. Researchers have written research code. Practitioners have used commercial software. Agencies have built bespoke systems. The transition between any two of these communities has typically required years of relearning.
MAGNET is the first water-modeling platform where all four communities operate in the same environment, on the same data, against the same network of published work. A student's investigation can run on the same engine as a federal portfolio analysis. A researcher's published model can become a consultant's starting point. The boundaries between communities — long taken for granted as inherent — turn out to be artifacts of the workflows.
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The next generation is already network-native.
Today's students grew up inside networks. They expect to find what others have done, build on it, publish their own work, see who's using it, iterate. The conventional workflow — install software, download data, build from scratch, document in PDF — was designed for a different era.
The MAGNET network is designed for how the next generation already works. They don't have to be persuaded that a published-model network has value. They have been operating in similar networks their entire lives. Their adoption is not a hurdle — it is the natural state.
⏳
Today's water decisions shape what they inherit.
The extraction we permit, the contamination we delay addressing, the infrastructure we build, the systems we let degrade — these are decisions whose horizon extends decades. The next generation is who lives with them.
Giving emerging professionals the same intelligence infrastructure used by the practitioners making those decisions today — while they are still in school — is the most concrete commitment that can be made to their future. Not "education about water" as a separate activity. Full participation, from the beginning, in the work of getting water right.
What this enables
📚
Learning becomes real.
Science, engineering, and math come alive through actual water problems on actual sites — not textbook exercises. Students investigate, model, and defend their thinking the way professionals do.
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Teaching becomes fluid.
Educators assign contemporary problems with real data, watch students work in real time, connect classrooms to the live Observatory, and bridge directly to the profession their students are joining.
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The profession renews itself.
Graduates arrive project-ready. Employers see actual student work in the Observatory, not just resumes. The workforce gap shrinks. The water crisis gets the talent it needs — faster.
The educational innovation
How teaching changes with MAGNET4WATER.
A new way of teaching water — engaged, active, visual, design-driven, consequence-aware — made possible by real-time, cost-aware simulation. This is what the curriculum network is built to propagate.
Water education has always asked students to memorize what they'll eventually need to use. MAGNET4WATER flips this. Every platform is a living field site where students investigate, design, and defend their thinking in real time — with real data, real physics, and real costs. The classroom becomes the laboratory. The lecture becomes an interactive notebook. Homework becomes a design problem with consequences.
The deepest shift is pedagogical. When students are designing the lowest-cost distribution network, the most protective remediation plan, or the greenest stormwater system, they cannot separate science from engineering from economics. The problem refuses to decompose. Students learn integrated reasoning because the software won't let them do one thing at a time.
Three teaching patterns appear across all five platforms.
The live-thinking lecture.
The instructor builds a model in front of the class while students predict, propose, and observe. Intuition develops because prediction is followed immediately by simulated reality — not by the next slide.
The design competition.
Students design under budget and performance constraints. The software keeps score. The winner defends their design. Competition energy transforms routine problem sets into experiences students remember years later.
The calibration competition.
A professor builds a system with known truth, samples it sparsely, and hands the data to students to reconstruct. Students learn scientific reasoning by diagnosing their own mistakes. At its fullest expression — the IGW-NET monitoring-and-remediation competition — students don't just reconstruct given observations. They decide what to measure, at what cost, then design interventions based on their own characterization. A form of teaching architecturally impossible before this kind of platform existed.
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What this looks like, concretely.
A student's moment when memorized equations become reasons to win.
A student in a least-cost distribution design competition shrinks all the pipes to cut capital cost — she takes the lead. But when she runs the simulation, pressure collapses at the far node. Residents have no water. She adds booster pumps; pressure recovers, but annual energy cost climbs relentlessly. Over twenty years, her "cheap" system costs more than every competitor's.
And then it clicks. The Darcy-Weisbach equation she memorized last semester — head loss inversely proportional to diameter to the fifth power — stops being a formula. It becomes a reason. Halve the diameter, multiply the loss by thirty-two. That's why pressure collapsed. She learns life-cycle economics in a single afternoon — but she also learns Darcy-Weisbach in the only way that actually sticks: as the thing she needed to understand to win.
Every platform enables its own version of this moment — when formulas become reasons, when students realize what they've been learning is valuable, when engineering becomes something they do rather than something they watch.
This is why we built the Curriculum Network. A new way of teaching needs infrastructure — a place where educators can find problems that embody this pedagogy, adapt them for specific courses, and contribute their refinements back. The pedagogy is the point. The network exists to propagate it.
Jump to your platform
Teaching a specific area? Go straight to the curriculum built for it.
Each platform has distinct teaching needs — groundwater depends on physics-based characterization, stormwater emphasizes real-time engineering design, data platforms develop spatial literacy.
What the platform curricula share.
The specific problems differ. The pedagogical foundation doesn't. Every platform's curriculum leverages the same MAGNET advantages — real sites, real data, real tools, real publishing.
How the curriculum network grows.
The same evolutionary principle that drives the modeling side — but with one key difference: curriculum is always open. Every adapted problem rejoins the network for others to build on. Quality improves through collective iteration, not gatekeeping.
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Adopt a seed problem.
Browse the curriculum network. Find a problem close to what you need — a Superfund investigation, a watershed calibration exercise, a stormwater design brief, a data fusion project. Fork it into your workspace with one click.
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✏️
Adapt for your course.
Change the learning objectives. Swap the site for a local one. Adjust the difficulty. Add your rubric. Simplify for an intro course or deepen for a graduate seminar. Work in draft mode — your edits are private until you're ready.
3
🌐
Publish. It joins the network.
When you publish, your adapted version enters the open curriculum network automatically. Others can now adopt and adapt your version. The attribution chain is preserved — your name, your institution, your contribution travel with the work.
Work in draft as long as you need — private to you, visible only when you choose to publish. No half-finished materials going live. But once published, it's open to the world — that's the deal.
Every adaptation credits the full lineage: original seed → Professor A (University X) → Professor B (University Y). Your contribution is visible. Your name travels with your work through every subsequent fork.
No curriculum unit is ever "finished." Every version is a starting point for the next adaptation. Quality emerges through use and iteration — not through editorial perfection. Perpetual beta applies to teaching too.
Unlike professional modeling (where confidentiality is the default), curriculum is always open. Educational materials benefit from maximum circulation. The whole point is that quality improves through collective iteration.
Contribution isn't an extra step — it's a side effect of normal use. Adapt a problem for your course and you've already contributed.
Create. Adapt. Or both.
Most educators will start by borrowing and adapting — that's the fastest path to a working course. But you can also create entirely new problems from scratch. Either way, your published work enters the network and becomes a seed for others.
Build an entirely new problem — your site, your learning objectives, your rubric, your deliverables. It enters the network as a new seed that others can adopt and adapt.
Know a location that would teach well — a famous case, a local aquifer, an interesting watershed, a campus stormwater system? Submit it for curriculum integration.
Publish the way you structure a course around MAGNET — syllabi, weekly plans, assessment strategies. Help other instructors design theirs.
Instructor forums per platform. Share what's working, what isn't, what your students responded to. Learn from peers teaching the same material.
Discovery & recognition.
As the curriculum network grows, the best work surfaces naturally. Social tools help educators find what's working and get recognized for what they create.
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Most Adopted
Which problems are being forked most often — the crowd validates
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Featured Innovations
Editor picks for creative pedagogy — fresh approaches to teaching water
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Instructor Reviews
Peer comments on specific problems — what worked, what to improve
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Adaptation Trees
See how a seed problem branched — the full lineage of remixes and variations
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Curriculum Analytics
Which platforms are growing fastest, which topics need more content
Why this changes everything for educators.
The conventional classroom
Real sites are often hazardous, regulated, or otherwise hard to bring inside the classroom.
Fieldwork and lab setups carry significant cost and logistical overhead.
Subsurface system dynamics evolve over months and years — far longer than a semester.
Software installation, data acquisition, and post-processing consume substantial class time.
The structural shape of the work constrains what students can investigate firsthand.
MAGNET classroom
Any site in the world — accessible instantly, safely, from any browser.
No software to install. No data to download. No operating system requirements.
Real-time simulation — see groundwater dynamics unfold in minutes, not months.
Students focus on hydrology, not IT. The platform removes the "irrelevant task" overhead.
Students investigate, model, defend, and discover.
For professional practice
Where practitioners find value.
The five canonical competitions were designed for educators, but their pedagogical structure makes them directly useful for practicing professionals. MAGNET is a production tool, not just a teaching tool — and the canonical examples carry profound messages for any engineer, scientist, manager, or regulator working with water.
Five profound messages the canonical examples encode.
Every canonical competition teaches a principle that senior practitioners recognize immediately and new graduates rarely internalize:
Message 1
Water practice is a design discipline, not a calculation discipline. Consultants who can size a pipe cannot always design a system — and that gap is where professional growth lives. Most engineering education treats water as a set of calculation techniques. MAGNET teaches it as design: a space of decisions made under uncertainty with real consequences.
Message 2
The most important decisions happen under real constraints. Cost, uncertainty, stakeholder pressure, regulatory complexity. Every canonical competition is a constrained optimization, because that is how real engineering actually works. Nobody gets to pick their favorite design; professionals pick the best design within the constraints they actually face.
Message 3
Integrated thinking is the core professional competency. Single-physics models produce confident wrong answers when applied to multi-dimensional problems. Every canonical competition forces reasoning across physics, economics, ecology, regulation, and community simultaneously. This is the competency most hiring managers describe as missing in new graduates.
Message 4
Holistic characterization precedes everything — and is itself a design discipline. Good simulation depends on good characterization, and good characterization is an act of weaving heterogeneous evidence into a coherent spatial story. The discipline DataNET teaches is the foundation of every professional water decision, whether the practitioner is a consultant, an agency scientist, a utility planner, or a regulator.
Message 5
The tools to teach and practice all of this finally exist. Climate change, aging infrastructure, nonpoint source pollution, water scarcity, contaminated sites — every rising water problem demands the integrated design thinking the canonical competitions develop. The workforce pipeline matters. The moment matters. MAGNET is the tool that closes the gap between how water engineering has been taught and how it actually needs to be practiced.
What each canonical competition offers the professional world.
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IGW-NET — The monitoring and remediation competition
Onboarding junior hydrogeologists on site investigation judgment; training regulatory staff on characterization standards; sharpening a senior consultant's intuition on unfamiliar site types; expert-witness preparation where demonstrating reasoning matters as much as demonstrating conclusions.
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SwaNET — The watershed restoration design competition
Stakeholder workshops where community participants see critical-source-area concepts emerge from their own choices; continuing education for TMDL implementation teams; training new staff at conservation districts and agencies; testing restoration scenarios before committing real-world resources.
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StormNET — The circular water infrastructure design competition
Training stormwater staff on modern regulatory frameworks; running developer design charrettes where constraints-plus-cost focus conversations quickly; demonstrating LID economics to skeptical clients with quantified lifecycle numbers; supporting integrated water plans with physics-based defensibility.
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ConduitNET — The long-distance water transfer design competition
Training new utility engineers on the storage-demand decoupling insight; mid-career development for planners moving into major capital planning; demonstrating multi-billion-dollar trade-offs to utility boards and public officials; supporting bid preparation where cost optimization drives competitive proposals.
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DataNET — The site characterization design competition
Onboarding new consulting staff on the discipline of characterization; stakeholder communication where a compelling spatial story moves decisions; project scoping where fast characterization guides which simulations to run; cross-disciplinary projects where geologists, planners, ecologists, and community representatives need a shared picture.
The invitation to practitioners.
Consulting firms, utilities, regulatory agencies, and water nonprofits use MAGNET directly — for actual projects, not simulated ones. From Superfund characterization in the United States to the Cholistan groundwater recharge work in Pakistan, the same platforms that support university teaching also support real professional practice.
Professional development programs can run any of the five canonical competitions as short courses or onboarding modules. The Observatory publishing system lets practitioners publish their characterizations, model setups, and designs as living portfolios — demonstrating expertise to clients, peers, and employers. MAGNET closes the gap between how water engineering is taught and how it is actually practiced. The same tools serve both.
How the five platform curricula relate
Five platforms, parallel pedagogy.
All five platforms teach through the same pedagogical spine — real-time simulation, integrated problem-solving, design competitions, calibration exercises. But each specializes for its domain, because the teaching problem is genuinely different in each.
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IGW-NET teaches the physics of what students cannot see.
Groundwater's challenge is invisibility and slow timescales. The platform makes the subsurface observable to the instructor, who controls what students see — enabling the signature move: the monitoring and remediation competition, where students characterize an invisible plume under real cost constraints, then design cleanup based on their own characterization. The full professional workflow, compressed into a semester, with known ground truth the instructor uses to grade.
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SwaNET teaches watershed engineering as iterative design.
Watershed teaching used to be bottlenecked by data — weeks of GIS work before any meaningful analysis. SwaNET delivers a complete working model in under ten minutes, worldwide. The signature move is the watershed restoration design competition: students transform a severely degraded watershed by targeting the 15–20% of land area producing 60–80% of the loading, discovering that land-use and management changes in critical source areas matter more than scattered structural BMPs. Dramatic, visible regime change as the Sankey water balance reorganizes in real time.
⛈️
StormNET teaches students to engineer sustainability, not talk about it.
Real cities experience water as one coupled infrastructure — stormwater, sanitary, supply, and harvesting. StormNET simulates all of it in one dynamically coupled model with physics-based bottom-up cost for every component. The signature move is the circular water infrastructure design competition: a constraint-plus-cost optimization where students meet every regulatory requirement (no flooding, no downstream impact, circular water use, self-cleansing velocities) at the lowest total lifecycle cost — and discover that distributed source capture with reuse is not a sustainability premium. It's the cheapest way to meet modern requirements.
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ConduitNET teaches pressurized water engineering across scales.
Distribution design is where the three fundamental equations — Darcy-Weisbach, conservation of mass, the energy equation — each become a tool students must pick up to win. The signature move is the long-distance water transfer design competition: students engineer a complete bulk water system from source to service — transmission, storage, distribution — discovering that a single design insight (storage to decouple peaky demand from steady supply) can cut lifecycle cost by 30–50%. The physics and the economics are inseparable, and both become visible as students design.
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DataNET teaches characterization as a design discipline.
Every water professional spends their career fusing heterogeneous data to characterize sites — but no course teaches this as a named skill. DataNET does. In 2–5 minutes a default 3D model builds from global data services; students iterate from there, adding layers based on their objective. The signature move is the site characterization design competition: students pick a site, pick an objective, and must tell a convincing, actionable story that stakeholders can understand. They discover that the model is the data — that characterization is an act of modeling, and the choices they make in data fusion are the model. This is the characterization foundation that feeds every other platform's canonical competition.
Platforms are designed to be used independently (each is complete for its domain) or in combination (a capstone course might assemble a DataNET foundation, an IGW-NET regional aquifer model, a StormNET site design, and a ConduitNET distribution layout for the same location). The curriculum network supports both modes — problems tagged by platform, by interconnection, and by course level.
Every platform curriculum page follows the same pedagogical structure. An educator who has read one platform's page will find the others immediately familiar.
Explore a platform curriculum
You've read the full pedagogical approach. Now explore how it plays out in your domain.
Where this leads
The communities are converging. The work continues.
The boundaries between student, researcher, practitioner, and agency have been artifacts of incompatible workflows — not differences in the work itself. As those workflows converge on one platform, the boundaries dissolve in real time. A student's investigation joins the same network a federal program is using. A researcher's published model becomes the next learner's starting point. A consultant's calibration informs the next agency's screening.
The next generation of water professionals is already arriving network-native — given, by design and not by accident, the infrastructure their water-decision careers will require. They begin in school where they will continue in practice. The continuity is the point.
Everyone wins. Professors teach with tools that make concepts vivid. Students graduate with real-world modeling skills and a living portfolio. Employers gain project-ready hires who already know the professional platform. And practitioners benefit too — curriculum problems are formulated to highlight what's possible, often demonstrating capabilities more clearly than messy real-world projects. The curriculum network doubles as the best showcase of what MAGNET can do.
"Students don't just learn about water — they investigate it, model it, defend it."
Security & Trust
Your models, your data, your control. Every paid account on MAGNET4WATER is protected through layered security controls commonly used in modern cloud platforms — encryption in transit and at rest, enforced two-factor authentication, audit logging, and private-by-default sharing.
You choose who holds the encryption key — us, you, or your organization. For organizations whose work requires more, Enterprise extends protection into hardware-enforced confidential computing — an emerging class of cloud security architecture increasingly adopted for regulated and high-sensitivity workloads.
How your work is protected.
Every paid account on MAGNET4WATER is built on layered security controls commonly used in modern cloud platforms.
- TLS 1.3 between your browser and our servers
- AES-256 encryption at rest on every storage volume
- Enforced two-factor authentication on every account
- Audit logging of authentication and data access
- Account isolation — your work is not accessible to other users unless explicitly shared through platform controls
- Private by default — sharing happens only on your terms
These are the types of foundational controls commonly associated with SOC 2-oriented, ISO 27001-aligned, and GDPR-conscious environments. On top of them, you choose how the encryption keys themselves are managed — three modes, selected at account setup.
You own your data. Users retain ownership of all Protected Data of the User (PDY), including uploaded models, telemetry, simulation outputs, configurations, and associated metadata. MAGNET4WATER processes PDY solely for the purpose of providing requested platform services, subject to the controls and commitments described in the Privacy Policy, EULA, and applicable Enterprise Agreements.
You choose who holds the key.
Encryption keys can be managed in three modes. You pick at account setup based on your work and how much key responsibility you want to take on.
Platform-managed
The default for most professional work
MAGNET4WATER holds your encryption key. We use it to decrypt your data when our systems run models on your behalf. You don't have to think about key management. If you forget your password, you can recover access.
The cryptographic capability we possess to decrypt your data in this mode is governed by enforced authentication, audit logging, separation-of-duties controls, and the binding commitments described in our Privacy Policy and EULA — we do not sell, share, transfer, or use your content to train AI models.
User-managed
Cryptographic sovereignty
You hold your own encryption key. MAGNET4WATER never holds it. Without your key, we cannot decrypt your data. HydroSimulatics does not possess the cryptographic capability to access your PDY in this mode, and does not maintain recovery mechanisms capable of reconstructing or overriding User-managed encryption keys.
The trade-off is real and final: if you lose your key, your data is permanently inaccessible. We cannot recover it. We cannot help. That is the point. The same mathematics that protects your data from us also means we cannot save you from your own key loss. At signup, you'll confirm that you understand and accept this trade-off before User-managed mode is activated.
User-managed mode is the right choice for solo practitioners or small teams whose work demands cryptographic sovereignty — and who have a reliable plan for keeping their key safe.
Organization-managed
Through your institution's existing key infrastructure
Your organization holds the encryption key through its existing key management infrastructure. MAGNET4WATER integrates with AWS KMS, Azure Key Vault, and similar institutional systems. Your organization controls who can use the key, when, and under what conditions — and can revoke at any time.
This is the right choice when your work is governed by institutional policy — regulated research, federally-funded projects, defense-adjacent work, healthcare with PHI, corporate environmental data — where your organization's IT or security team is responsible for key custody. If your organization already operates a key management system for other regulated platforms, MAGNET4WATER integrates with the infrastructure you already have.
On the Free tier.
Free access is the right starting point for tutorials, classroom exercises, evaluation, and work with public data. Connections are protected by TLS 1.3, and accounts are isolated from one another.
Free access does not include the advanced encryption controls, key-management options, enhanced audit capabilities, or enterprise-grade protections available in Premium and Enterprise offerings. For client work, proprietary data, or any work requiring professional-grade discretion, Premium is the appropriate tier.
Three tiers of visibility.
Every model exists at the visibility level you choose. A global corporation doesn't need the world to see their models — but every engineer in the company should.
🌍 Open
Published to the global Observatory. Anyone can find, view, run, and comment.
Researchers, educators, open science
🤝 Selective
Shared with specific people or organizations. Client reviews, project teams, regulators.
Consultants, multi-stakeholder projects
🏢 Closed
Your network only. Custom access controls. Data access and sharing remain restricted to the organization's configured security and visibility controls. Confidential computing available for Enterprise customers.
Corporations, defense, sensitive data
Compliance & Governance
GDPR · CCPA · CPRA · U.S. State Privacy Laws · International Frameworks
Governance oversight is coordinated through HydroSimulatics data stewardship and security review processes. Enterprise engagements can include custom audit, sovereignty, and compliance requirements.
Enterprise: beyond industry standard.
Industry standard is encryption in transit, encryption at rest, enforced authentication, and audit logging — the protections every responsible cloud platform delivers. MAGNET4WATER meets that standard for every paid account, with three key-management modes giving you control over who holds the cryptographic keys.
Enterprise goes further. We add hardware-enforced confidential computing — your data is protected through hardware-enforced memory isolation during execution within attested Trusted Execution Environments (TEE) on Intel TDX or AMD SEV-SNP processors. This represents an emerging class of cloud security architecture increasingly adopted for regulated and high-sensitivity workloads, and is commonly required in defense, healthcare with PHI, regulated finance, and government contracts with explicit cloud-isolation requirements.
Enterprise also includes dedicated infrastructure options, remote attestation on request, and custom contracts shaped to your obligations — compliance addenda, audit rights, data residency, deployment model.
Enterprise is engaged through direct conversation with our team — not a subscription tier above Premium, but a different category of engagement. If your work has these requirements, talk to us.
No security architecture can eliminate all operational, software, hardware, legal, or human risk. The controls described on this page are intended to significantly reduce unauthorized access and improve data protection across supported deployment modes. Specific protections available to a User depend on account category, deployment configuration, and selected key-management mode.
Privacy Policy
How HydroSimulatics, Inc. collects, processes, stores, and protects your information when you use the MAGNET4WATER platform.
Effective Date: May 13, 2026 · Last Updated: May 13, 2026 · Data Controller: HydroSimulatics, Inc., State of Delaware, United States
1. Overview
HydroSimulatics, Inc. ("HydroSimulatics," "we," "us") is committed to protecting the privacy of all users of the MAGNET4WATER platform. This Privacy Policy describes what information we collect, how we use and protect it, and the rights you have regarding your data.
This Privacy Policy applies to all users of the Platform, including Free accounts, Premium subscriptions (per-platform or bundled), and Enterprise engagements. Where protections differ by category, those distinctions are noted explicitly — see §4 for the security architecture and key-management modes. For non-binding context on the security architecture, see also the Security & Trust page; binding terms appear in this Policy and in the End-User License Agreement.
This Privacy Policy governs operational data-handling practices associated with the Platform. Additional descriptive information regarding Platform security architecture is provided in the Security & Trust documentation.
2. Information We Collect
2.1 Account Information
When you register, we collect your name, email address, institutional affiliation (if applicable), and authentication credentials. This information is necessary to create and maintain your account, process payments, and provide customer support.
2.2 Protected Data of the User (PDY)
All files, inputs, outputs, models, configurations, telemetry streams, metadata, and any other content uploaded, generated, or processed by you within the platform constitutes Protected Data of the User ("PDY"). The specific protections applied to PDY depend on your account category (Free, Premium, or Enterprise) and, for Premium subscribers, on the key-management mode selected at account setup. See §4 (Data Security) for the full description of protections and key-management modes.
Users retain all ownership rights, title, and interest in PDY, including uploaded files, models, telemetry, simulation outputs, configurations, metadata, and associated content processed through the Platform. HydroSimulatics processes PDY solely for the purpose of providing requested Platform services, subject to the controls and commitments described in this Policy, the End-User License Agreement, and any applicable Enterprise Agreement.
2.3 Usage and Telemetry Data
We collect non-content metadata such as timestamps, file sizes, session durations, feature usage patterns, and transmission logs. This data is used for performance monitoring, platform improvement, and security auditing. Metadata is stored separately from PDY and is not intended to reconstruct or expose User content.
2.4 Analytics
The MAGNET4WATER website uses Google Analytics (ID: G-TBWBDDP47H) to collect anonymized usage statistics including page views, session duration, and referral sources. HydroSimulatics configures analytics services to minimize transmission of personally identifiable information to third-party analytics providers. You may opt out of analytics tracking by adjusting your browser settings or using a browser extension such as the Google Analytics Opt-out Add-on.
2.5 Cookies
The platform uses strictly necessary cookies for authentication, session management, and security. We do not use advertising cookies, behavioral tracking cookies, or third-party marketing cookies. Session tokens are encrypted, time-bound, and auto-terminate after inactivity.
3. How We Use Your Information
HydroSimulatics uses collected information solely for the following purposes:
(a) Account provisioning, authentication, and session management
(b) Subscription billing and payment processing
(c) Platform performance monitoring, debugging, and improvement
(d) Security monitoring, breach detection, and incident response
(e) Legal compliance and regulatory reporting
(f) Customer support when initiated by the user
We do not: sell, rent, or share your data with third parties for marketing, advertising, or profiling purposes. HydroSimulatics does not use PDY to train, fine-tune, or improve generalized AI models.
4. Data Security
MAGNET4WATER applies layered security controls to protect PDY across all account categories. The specific protections in effect depend on your account category and selected key-management mode.
4.1 Free Accounts
Free accounts do not include the advanced encryption controls, enhanced audit capabilities, key-management options, or enterprise-grade protections available in Premium and Enterprise offerings. Free accounts are appropriate for tutorials, evaluation, classroom use, and work with public or non-sensitive data.
4.2 Premium Subscriptions
Every Premium subscription includes the following protections, regardless of which platform(s) are subscribed to:
In Transit: TLS 1.3 encryption for all data exchanged between User devices and platform servers, and for internal service-to-service communication.
At Rest: AES-256 encryption for stored PDY, including models, telemetry, outputs, and metadata. PDY is protected through encrypted storage systems and encrypted internal communication channels designed to reduce unauthorized access during storage and processing.
Authentication: Enforced two-factor authentication on every account; encrypted, time-bound session tokens that auto-terminate after inactivity.
Audit Logging: Authentication events and data access are logged for security monitoring and compliance auditing. Logs are stored separately from PDY.
Account Isolation: Platform controls are designed to restrict User access to PDY not explicitly shared through authorized Platform mechanisms.
Privacy by Default: PDY is private by default and is not accessible to other Users unless explicitly shared through Platform controls configured by the User or organization.
4.3 Key Management (Premium Subscriptions)
Premium subscribers select one of three key-management modes at account setup. The selected mode determines who holds the encryption key and, consequently, who has the cryptographic capability to decrypt the User's PDY.
Platform-managed (default): In Platform-managed mode, HydroSimulatics possesses the cryptographic capability to decrypt PDY for the purpose of providing requested Platform services, subject to the operational controls and contractual commitments described herein and in the EULA. Password recovery is supported.
User-managed: In User-managed mode, HydroSimulatics does not possess the cryptographic capability to decrypt PDY without the User-provided encryption key. If a User loses a User-managed encryption key, associated encrypted PDY may become permanently inaccessible. HydroSimulatics does not maintain recovery mechanisms capable of reconstructing or overriding User-managed encryption keys. The User must explicitly acknowledge and accept this trade-off at account setup before User-managed mode is activated.
Organization-managed: In Organization-managed mode, encryption keys are controlled through the organization's external key-management infrastructure (e.g., AWS KMS, Azure Key Vault, or equivalent) and authorization policies. The organization retains the right to revoke key access at any time. HydroSimulatics does not store the organization's master key.
4.4 Enterprise Engagements
Enterprise engagements may include hardware-enforced confidential computing on top of the Premium protections described above. Enterprise confidential-computing environments are designed to significantly reduce the ability of infrastructure operators or unauthorized processes to inspect or extract PDY during execution within attested Trusted Execution Environments (TEE), such as Intel TDX or AMD SEV-SNP. Cryptographic attestation, dedicated infrastructure, and custom deployment options are available on request as part of the engagement. Specific Enterprise terms are governed by the customer's individual Enterprise Agreement.
5. AI Privacy & Model Isolation
MAGNET4WATER incorporates AI-assisted features for modeling, data interpretation, and platform navigation. These features are subject to the following binding commitments:
No training on User content: HydroSimulatics does not use PDY to train, fine-tune, or improve generalized AI models.
No external transmission: HydroSimulatics does not transmit PDY to external third-party AI providers for model training or inference unless explicitly authorized by the User.
Session-bounded processing: AI processing pipelines are designed not to retain PDY beyond the operational duration necessary to complete the requested task, except where temporary retention is required for security, debugging, abuse prevention, legal compliance, or explicitly enabled Platform features.
Tier-aware cryptographic scope: For Premium subscribers in Platform-managed key mode, AI inference occurs on the same procedurally-controlled infrastructure that handles model execution. For Premium subscribers in User-managed or Organization-managed key mode, AI inference requires the same authorization process as any model execution — your key, or your organization's gateway, must release the data for AI processing. For Enterprise customers with confidential computing enabled, AI inference can run inside the same hardware-attested enclave as the model execution.
6. Breach Response
HydroSimulatics maintains continuous monitoring for unauthorized access attempts and anomalous behavior. Notification timelines may vary where modified by applicable law or Enterprise Agreements. Upon confirmation of a security breach:
Affected systems are immediately isolated and contained.
Affected users are notified within 72 hours of confirmation, or sooner where required by applicable law (e.g., GDPR Article 33).
Notification includes a description of the incident, the nature and scope of the data potentially affected, the measures taken to mitigate the breach, and recommended actions for the User.
For Premium subscribers in User-managed key mode: because HydroSimulatics does not hold the User's encryption key, encrypted PDY cannot be decrypted by an attacker who compromises HydroSimulatics infrastructure alone.
For Premium subscribers in Organization-managed key mode: the User's organization's key management infrastructure governs decryption authorization; the scope of exposure depends on the organization's key custody practices.
For Premium subscribers in Platform-managed key mode (including Enterprise customers who select Platform-managed mode): incident response includes assessment of whether platform-held keys were compromised, with notification scope adjusted accordingly.
For Enterprise customers: notification and incident-response procedures may be supplemented or modified by the customer's individual Enterprise Agreement.
7. Data Retention & Deletion
Upon account termination or subscription cancellation, PDY is retained for a limited period (typically 30 days) to facilitate account recovery or subscription reactivation, unless you request immediate deletion. After this retention period, PDY is permanently deleted from our active systems and from backups during the normal backup rotation cycle.
Certain operational logs, security records, backups, and compliance-related records may persist temporarily beyond primary PDY deletion windows as part of normal operational and legal processes.
For Premium subscribers in User-managed key mode, retained PDY remains encrypted with your key during the retention period. HydroSimulatics has no means to decrypt or access this content without the User providing the key.
You may request immediate deletion of all PDY and associated metadata at any time by contacting [email protected]. We will confirm deletion within 30 days, or sooner where required by applicable law.
8. Your Rights
Depending on your jurisdiction, you may have the right to:
Access the personal data we hold about you
Correct inaccurate or incomplete personal data
Delete your personal data and all associated content
Export your data in a portable format
Restrict or object to certain processing activities
Withdraw consent where processing is based on consent
To exercise these rights, contact [email protected]. We will respond within 30 days, or sooner where required by applicable law.
9. Legal Compliance
HydroSimulatics designs Platform governance and operational practices with consideration for applicable privacy and data-protection frameworks, including, where applicable:
General Data Protection Regulation (GDPR)
California Consumer Privacy Act (CCPA) and California Privacy Rights Act (CPRA)
Applicable U.S. state privacy laws
Jurisdiction-specific frameworks required by institutional contracts
Governance oversight is coordinated through HydroSimulatics data stewardship and security review processes. Internal audits and external reviews are conducted upon request.
10. Children's Privacy
MAGNET4WATER is not directed at individuals under the age of 16. We do not knowingly collect personal information from children. If we become aware that a child under 16 has provided personal data, we will take steps to delete such information promptly.
11. Third-Party Services
MAGNET4WATER integrates with third-party data services (e.g., USGS, NASA, NOAA telemetry networks) for live data feeds. These integrations are configured to process publicly available environmental or telemetry data and are not intended to expose PDY except where explicitly initiated or authorized by the User. Payment processing is handled by third-party payment processors; HydroSimulatics does not store credit card numbers or financial account information on its servers.
12. Changes to This Policy
HydroSimulatics reserves the right to update this Privacy Policy at any time. Material changes will be communicated via the platform or email at least thirty (30) days before taking effect. Continued use of the platform following such notice constitutes acceptance of the revised policy.
13. Contact
For privacy-related inquiries, data requests, or to exercise your rights under this policy:
HydroSimulatics, Inc.
Email: [email protected]
Web: magnet4water.net
No security architecture can eliminate all operational, software, hardware, legal, or human risk. The controls described in this Policy and in HydroSimulatics's Security & Trust documentation are intended to reduce unauthorized access and improve data protection across supported deployment modes. Specific protections available to a User depend on account category, deployment configuration, and selected key-management mode.
Terms of Service
The terms and conditions governing your use of the MAGNET4WATER platform, operated by HydroSimulatics, Inc.
Effective Date: May 13, 2026 · Last Updated: May 13, 2026 · Governing Law: State of Michigan, United States
1. Acceptance of Terms
By accessing, subscribing to, or using the MAGNET4WATER platform ("the Platform"), you ("the User") expressly agree to be bound by all terms and conditions set forth herein. If you do not agree to these terms, you must not access or use the Platform.
These Terms of Service apply to all categories of access to the Platform: Free accounts, Premium subscriptions, and Enterprise engagements. They should be read in conjunction with the Privacy Policy and the End-User License Agreement (EULA). Enterprise engagements may be governed by additional or modified terms in the customer's individual Enterprise Agreement.
The Privacy Policy governs operational data-handling practices associated with the Platform. Security & Trust documentation provides descriptive information regarding Platform security architecture and controls.
2. Scope of Service
The Platform encompasses all sub-platforms (IGW-NET, SwaNET, DataNET, StormNET, ConduitNET), services, interfaces, and associated infrastructure operated by HydroSimulatics, Inc.
HydroSimulatics reserves the right to update, modify, or discontinue any part of the Platform at its sole discretion, provided that such changes do not retroactively alter the terms of this Agreement without notice. Users may be subject to additional terms if accessing the Platform through an institutional deployment, enterprise license, or third-party integration.
Certain Platform capabilities, security controls, and deployment configurations may vary by account category, subscription level, Enterprise Agreement, or regional deployment model.
3. Account Registration
You must provide accurate, complete, and current information when creating an account. You are responsible for maintaining the confidentiality of your login credentials and for all activity that occurs under your account. You must notify HydroSimulatics immediately of any unauthorized use of your account.
Additional authentication and security controls applicable to Premium and Enterprise accounts are described in the Privacy Policy and Security & Trust documentation.
4. Acceptable Use
You agree not to:
(a) Copy, modify, or create derivative works of the Platform or its components;
(b) Distribute, sell, lease, or sublicense the Platform to third parties;
(c) Use the Platform to violate applicable laws, regulations, or third-party rights;
(d) Attempt to gain unauthorized access to any portion of the Platform or its infrastructure;
(e) Circumvent or disable any security features, including 2FA, encryption boundaries, or access controls;
(f) Reverse-engineer, decompile, or attempt to extract the Platform's source code, algorithms, or internal architecture;
(g) Upload malicious code, interfere with Platform operations, conduct unauthorized automated extraction of Platform content, or use the Platform to develop competing services through unauthorized scraping, reverse engineering, or model extraction activities.
Users on any account category shall not attempt to circumvent the security controls, feature limits, or access scopes applicable to their account category.
5. Account Categories & Fees
5.1 Free
A no-cost access category to the Platform, subject to usage limits on problem size and certain feature limitations per the published feature matrix. Free accounts do not include the advanced encryption controls, enhanced audit capabilities, key-management options, or enterprise-grade protections available in Premium and Enterprise offerings. Free is appropriate for tutorials, classroom use, evaluation, and work with public or non-sensitive data.
5.2 Premium
A paid subscription granting time-limited access to the full Platform features. Premium subscriptions are sold per individual platform (IGW-NET, SwaNET, DataNET, StormNET, ConduitNET) or as bundles. Premium subscriptions include enhanced security controls, encryption protections, enforced authentication requirements, audit capabilities, and configurable sharing controls as described in the Privacy Policy and Security & Trust documentation. At account setup, Premium subscribers select one of three key-management modes (Platform-managed, User-managed, or Organization-managed) as defined in the EULA.
5.3 Enterprise
A separate category of engagement for organizations whose work requires additional protections beyond the standard Premium offering. Certain Enterprise engagements may include confidential-computing environments, dedicated infrastructure, custom deployment configurations, compliance addenda, and other negotiated operational terms. Enterprise engagements are individually negotiated and may be governed by additional or modified terms in the customer's Enterprise Agreement. Enterprise is engaged through direct conversation with HydroSimulatics, not standard subscription signup.
5.4 Payment Terms
Subscription fees shall be paid in accordance with the pricing schedule published by HydroSimulatics or agreed upon in writing in an Enterprise Agreement. All fees are non-refundable except as required by law or explicitly stated herein. HydroSimulatics may modify pricing or billing terms with thirty (30) days' notice. Continued use of the Platform after such notice constitutes acceptance of the new terms.
5.5 Non-Payment
Failure to pay applicable fees may result in suspension or termination of access to Premium subscription features or Enterprise engagement features. Suspension affects access to platform features; it does not change the User's selected key-management mode, which is governed by the EULA (see EULA §2.6 and §4.2).
6. Intellectual Property
The Platform, including all software, algorithms, interfaces, documentation, and visual design, is the exclusive property of HydroSimulatics, Inc. and is protected by copyright, trademark, and other intellectual property laws. Nothing in these Terms grants you any right to use HydroSimulatics trademarks, trade names, or service marks without prior written consent.
Users retain all ownership rights, title, and interest in Protected Data of the User (PDY), including uploaded files, models, telemetry, simulation outputs, configurations, metadata, and associated content processed through the Platform. Except as necessary to provide requested Platform services, HydroSimulatics acquires no ownership interest in PDY.
7. Termination
This Agreement shall remain in effect until terminated by either party.
7.1 By the User
You may terminate at any time by ceasing use of the Platform and, if applicable, requesting deletion of your account and associated Protected Data.
7.2 By HydroSimulatics
HydroSimulatics may terminate this Agreement or suspend access immediately, without prior notice, if: the User breaches any provision of this Agreement; required fees are unpaid or disputed; or continued access poses a security, legal, or operational risk.
7.3 Effect of Termination
Upon termination: all licenses granted shall immediately cease; and you may request deletion of all retained data, subject to applicable retention policies and legal obligations. For Premium subscribers in User-managed key mode, encrypted content retained during the deletion grace period remains inaccessible to HydroSimulatics without the User's encryption key. For Premium subscribers in Platform-managed or Organization-managed modes, retention and deletion follow the procedures described in §7 of the Privacy Policy.
HydroSimulatics may preserve operational logs, security records, backups, and legally required records following termination in accordance with the Privacy Policy and applicable legal obligations.
8. Disclaimers & Limitation of Liability
8.1 Disclaimer of Warranties
The Platform is provided "as is" and "as available," without warranties of any kind, express or implied. HydroSimulatics does not warrant that the Platform will be uninterrupted, error-free, or free of harmful components; that modeling outputs or simulations will be accurate, complete, or suitable for any specific purpose; or that encryption or security features will prevent all forms of unauthorized access or data loss. HydroSimulatics disclaims all implied warranties, including merchantability, fitness for a particular purpose, and non-infringement.
No security architecture can eliminate all operational, software, hardware, legal, or human risk.
8.2 Limitation of Liability
To the maximum extent permitted by law, HydroSimulatics shall not be liable for indirect, incidental, special, consequential, or punitive damages; loss of data, revenue, profits, or business opportunities; or damages arising from unauthorized access, use, or disclosure of Protected Data.
HydroSimulatics' total liability under this Agreement shall not exceed the amount paid by the User for the Subscription during the twelve (12) months preceding the claim.
8.3 User Acknowledgments
You acknowledge that: (a) for Premium subscribers in User-managed key mode, loss of the encryption key will result in permanent inaccessibility of the User's encrypted content, and HydroSimulatics has no means to recover it; (b) Free accounts do not include the advanced encryption controls, enhanced audit capabilities, key-management options, or enterprise-grade protections available in Premium and Enterprise offerings; and (c) use of the Platform is at your own risk.
9. Relationship Between Documents
The Privacy Policy, Security & Trust documentation, End-User License Agreement (EULA), and applicable Enterprise Agreements are incorporated into these Terms by reference.
In the event of conflict between these Terms and an applicable Enterprise Agreement, the Enterprise Agreement shall control to the extent of the conflict. In the event of conflict between these Terms and the EULA on a matter specifically addressed by the EULA (such as the license grant, security architecture, or key-management modes), the EULA shall control. In the event of conflict on operational data-handling matters specifically addressed by the Privacy Policy, the Privacy Policy shall control.
The Privacy Policy governs operational data-handling practices associated with the Platform. Security & Trust documentation provides descriptive information regarding Platform security architecture and controls but does not independently modify contractual obligations unless expressly incorporated into an Enterprise Agreement.
10. Additional Provisions
10.1 AI-Assisted Features
AI-assisted Platform features are governed by the Privacy Policy and applicable Platform security controls.
10.2 Export Controls
Users may not access or use the Platform in violation of applicable export-control, sanctions, or trade laws. Users are responsible for compliance with all such laws applicable to their use of the Platform.
10.3 Force Majeure
HydroSimulatics shall not be liable for any delay or failure to perform under this Agreement resulting from causes beyond its reasonable control, including but not limited to acts of nature, war, terrorism, civil unrest, governmental action, labor disputes, infrastructure outages, third-party service failures, or other events of force majeure.
11. Governing Law & Jurisdiction
This Agreement shall be governed by and construed in accordance with the laws of the State of Michigan, without regard to its conflict of law principles. Any disputes arising under or in connection with this Agreement shall be resolved exclusively in the state or federal courts located in Michigan, and the parties consent to personal jurisdiction therein. The United Nations Convention on Contracts for the International Sale of Goods shall not apply.
12. Changes to These Terms
HydroSimulatics reserves the right to update these Terms of Service at any time. Material changes will be communicated via the platform or email at least thirty (30) days before taking effect. Continued use of the Platform following such notice constitutes acceptance of the revised terms.
13. Contact
HydroSimulatics, Inc.
Email: [email protected]
Web: magnet4water.net
End-User License Agreement
The software license and security architecture governing the MAGNET4WATER platform and all sub-platforms.
Effective Date: May 13, 2026 · Last Updated: May 13, 2026 · Governing Law: State of Michigan, United States · Incorporation: HydroSimulatics, Inc., State of Delaware
1. Introduction
MAGNET4WATER is designed to protect User work — including model inputs, telemetry streams, simulation outputs, and decision support artifacts — through a combination of cryptographic, architectural, and operational controls. The specific protections that apply to a User's work depend on the User's account category (Free, Premium, or Enterprise) and, for Premium subscribers, on the key-management mode selected at account setup.
By accessing, subscribing to, or using the Platform, the User expressly agrees to be bound by all terms and conditions set forth herein. If the User does not agree to these terms, they must not access or use the Platform. This EULA should be read in conjunction with the Privacy Policy and Terms of Service.
2. Definitions
2.1 Platform
The MAGNET4WATER software system, including all sub-platforms (IGW-NET, SwaNET, DataNET, StormNET, ConduitNET), services, interfaces, and associated infrastructure.
2.2 Account Categories
MAGNET4WATER provides three categories of access, each with distinct rights, obligations, and protections:
Free: A no-cost access category for tutorials, evaluation, classroom use, and work with public or non-sensitive data. Free accounts have limits on problem size and certain features per the platform's published feature matrix.
Premium: A paid subscription to one or more individual platforms (IGW-NET, SwaNET, DataNET, StormNET, ConduitNET) or to bundles. Premium subscribers select a key-management mode at account setup (see §2.6).
Enterprise: A separate category of engagement for organizations whose work requires hardware-enforced confidential computing, dedicated infrastructure, custom contracts, or compliance addenda beyond the standard Premium offering. Enterprise engagements are governed by individually-negotiated Enterprise Agreements that may supplement or modify these terms.
2.3 Protected Data of the User (PDY)
All files, inputs, outputs, models, configurations, telemetry, metadata, and any other content uploaded, generated, or processed by the User within the Platform. This includes personally identifiable information (PII), modeling artifacts, and simulation outputs. The protections applied to PDY depend on the User's account category and selected key-management mode (see §4).
Users retain all ownership rights, title, and interest in PDY, including uploaded files, models, telemetry, simulation outputs, configurations, metadata, and associated content processed through the Platform. HydroSimulatics processes PDY solely for the purpose of providing requested Platform services, subject to the controls and commitments described in this Agreement, the Privacy Policy, and any applicable Enterprise Agreement.
2.4 Encryption Standards
TLS 1.3 (Transport Layer Security): A cryptographic protocol used to encrypt data exchanged between User devices and Platform servers, and between Platform internal services. Applied to all User connections regardless of account category.
AES-256 (Advanced Encryption Standard, 256-bit): A symmetric block cipher used to encrypt PDY stored on Platform servers. Applied to all PDY belonging to Premium subscribers and Enterprise customers.
2.5 Confidential Computing
Certain Enterprise engagements may include hardware-attested confidential computing environments utilizing Trusted Execution Environment (TEE) technologies such as Intel TDX or AMD SEV-SNP, as further described in applicable Enterprise Agreements and Security & Trust documentation. Confidential Computing is not included in the standard Premium subscription.
2.6 Key-Management Modes (Premium Subscribers)
Premium subscribers select one of three key-management modes at account setup: Platform-managed (the default; HydroSimulatics holds the key), User-managed (the User holds the key, with no recovery), or Organization-managed (the User's organization holds the key through its existing key management infrastructure). The selected mode determines who has the cryptographic capability to decrypt the User's PDY. See §4.2 for full definitions and operational consequences of each mode.
2.7 Additional Definitions
Trusted Execution Environment (TEE): A hardware-isolated execution environment that encrypts data in memory and prevents inspection or extraction by software running outside the enclave. Used in Enterprise engagements (see §2.5 and §4.4).
Session Token: A time-bound, encrypted credential used to authenticate User sessions. Auto-terminates after inactivity and is governed by 2FA.
Dissemination Tools: Platform features that allow Users to publish, share, or collaborate on modeling outputs, governed by User-selected visibility settings and access permissions.
Enterprise Agreement: An individually-negotiated contract between HydroSimulatics and an Enterprise customer that specifies the technical, operational, and compliance terms of that customer's engagement. Enterprise Agreements may include compliance addenda, custom audit rights, data residency commitments, dedicated infrastructure options, and other terms.
AI Support: AI-assisted Platform features are governed by §5 of the Privacy Policy and the applicable Platform security controls described in §4 of this Agreement.
3. License Grant
Subject to the terms of this Agreement, HydroSimulatics grants the User a non-exclusive, non-transferable, revocable license to access and use the Platform during the Subscription term or Free access period.
Except for the limited rights expressly granted herein, HydroSimulatics retains all rights, title, and interest in and to the Platform, associated software, algorithms, interfaces, documentation, and related intellectual property.
The license is limited to the User's internal research, modeling, and educational use unless extended commercial use rights are explicitly granted in the User's subscription terms or Enterprise Agreement. Redistribution or sublicensing is prohibited unless expressly authorized in writing by HydroSimulatics.
The license does not grant any rights to inspect, reverse-engineer, or extract the Platform's source code, algorithms, or internal architecture. HydroSimulatics's access to PDY is governed by §4 of this Agreement and the User's selected key-management mode.
4. Security Architecture
MAGNET4WATER applies layered cryptographic, operational, and contractual controls to protect PDY. The specific controls in effect depend on the User's account category and selected key-management mode.
4.1 Premium Subscriptions — Standard Protections
The following protections apply to all Premium subscriptions, regardless of which platform(s) are subscribed to:
In Transit: TLS 1.3 encrypts all data exchanged between User devices and MAGNET4WATER servers, and for all internal service-to-service communication.
At Rest: AES-256 encryption secures all stored PDY, including models, telemetry, outputs, and metadata. Continuous re-encryption is applied at internal service boundaries so that PDY exists in plaintext only during active computation.
Authentication: Two-factor authentication is enforced on every Premium account. Session tokens are encrypted, time-bound, and auto-terminate after inactivity. Anomalous login behavior triggers automated containment and User notification.
Access Controls: HydroSimulatics access to systems that handle PDY is governed by enforced authentication, role-based access control, separation-of-duties controls, code review, and recorded change management.
4.2 Premium Subscriptions — Key-Management Modes
Premium subscribers select one of three key-management modes at account setup. The selected mode determines who holds the encryption key for the User's PDY and, consequently, the cryptographic relationship between HydroSimulatics and the User's data.
Platform-managed (default): In Platform-managed mode, HydroSimulatics possesses the cryptographic capability to decrypt PDY for the purpose of providing requested Platform services, subject to the operational controls and contractual commitments described herein and in the Privacy Policy. Password recovery is supported.
User-managed: In User-managed mode, HydroSimulatics does not possess the cryptographic capability to decrypt PDY without the User-provided encryption key. If a User loses a User-managed encryption key, associated encrypted PDY may become permanently inaccessible. HydroSimulatics does not maintain recovery mechanisms capable of reconstructing or overriding User-managed encryption keys. The User must explicitly acknowledge and accept this trade-off at account setup before User-managed mode is activated.
Organization-managed: In Organization-managed mode, encryption keys are controlled through the organization's external key-management infrastructure (e.g., AWS KMS, Azure Key Vault, or equivalent) and authorization policies. The organization retains the right to revoke key access at any time. HydroSimulatics does not store the organization's master key.
4.3 Enterprise Engagements — Additional Protections
Enterprise engagements add the following protections beyond the Premium standard:
Hardware-Enforced Confidential Computing: Sensitive operations — including model execution, AI inference, and data processing — occur within hardware-attested Trusted Execution Environments (Intel TDX or AMD SEV-SNP). Within the TEE, PDY remains encrypted in memory; the data is not accessible to hypervisors, host operating systems, privileged system processes, or HydroSimulatics infrastructure personnel during execution.
Cryptographic Attestation: Available on request — provides cryptographic proof that the Customer's workload is running inside a verified TEE enclave on legitimate hardware.
Dedicated Infrastructure: Available on request — ranges from shared infrastructure with stricter access controls to fully dedicated observatory nodes never shared with other tenants, structured to the Customer's specific requirements.
Custom Contracts: Enterprise engagements may include compliance addenda, audit rights, data residency commitments, deployment models, and other terms negotiated in the individual Enterprise Agreement.
4.4 Audit Logging & Transparency
For Premium subscribers and Enterprise customers, MAGNET4WATER maintains audit logs covering authentication events, key management events, and data access. Logs are stored separately from PDY. Users may request audit summaries for their own accounts. HydroSimulatics does not retain logs that expose plaintext PDY.
4.5 Free Accounts
Free accounts do not include the advanced encryption controls, audit capabilities, key-management options, or enterprise-grade protections available in Premium and Enterprise offerings. Free accounts are appropriate for tutorials, evaluation, classroom use, and work with public or non-sensitive data. Users with proprietary or regulated work should upgrade to a Premium subscription before uploading such content.
5. Relationship Between Documents
This Agreement should be read together with the Privacy Policy, the Terms of Service, the Security & Trust documentation, and (where applicable) the User's individual Enterprise Agreement. The Privacy Policy and Security & Trust documentation are incorporated into this Agreement by reference.
The Privacy Policy governs operational data-handling practices, including collection, use, retention, disclosure, and User rights. The Security & Trust documentation provides descriptive information regarding Platform security architecture and controls but does not independently modify contractual obligations unless expressly incorporated into an Enterprise Agreement.
In the event of conflict between this Agreement and an applicable Enterprise Agreement, the Enterprise Agreement shall control to the extent of the conflict. In the event of conflict between this Agreement and the Terms of Service or Privacy Policy on a matter specifically addressed by this Agreement (such as the license grant or security architecture), this Agreement shall control. In the event of conflict on operational data-handling matters specifically addressed by the Privacy Policy, the Privacy Policy shall control.
6. Enterprise Engagements & Sovereignty
Enterprise engagements may include dedicated infrastructure, customer-controlled key management, hardware-attested confidential computing, custom audit rights, data residency commitments, and other terms negotiated in the individual Enterprise Agreement. The specific protections and rights of each Enterprise customer are governed by their Enterprise Agreement, which supplements and where applicable modifies these terms. To discuss an Enterprise engagement, contact HydroSimulatics directly through the channels listed in §10.
7. Summary of Protections by Category
The following summary is provided for clarity and does not modify the binding terms in §§1-6.
Free
TLS 1.3 in transit
Account isolation
No encryption at rest
No 2FA enforcement
No key management
For tutorials, evaluation, public data
Premium
TLS 1.3 in transit
AES-256 encryption at rest
Continuous internal re-encryption
Enforced 2FA
Audit logging
Private by default
Three key-management modes: Platform / User / Organization
For professional consulting, research, engineering
Enterprise
All Premium protections
Hardware-enforced confidential computing (TEE)
Cryptographic attestation (on request)
Dedicated infrastructure options
Custom contracts & compliance addenda
For regulated industries, sensitive corporate data, government, defense
8. Security Architecture Summary
Free accounts are protected by TLS 1.3 in transit and account isolation, with no encryption at rest.
Premium subscriptions encrypt PDY in transit and at rest. Premium subscribers choose at account setup which party holds the encryption key: HydroSimulatics (Platform-managed mode, with operational and contractual controls), the User (User-managed mode, with no key recovery), or the User's organization (Organization-managed mode, brokered through the organization's KMS).
Enterprise engagements add hardware-enforced confidential computing for protection of PDY during active processing, with cryptographic attestation, dedicated infrastructure, and custom contract terms available on request.
For all accounts, HydroSimulatics commits in §3 of the Privacy Policy not to sell, share, or use PDY to train AI models.
No security architecture can eliminate all operational, software, hardware, legal, or human risk. The controls described in this Agreement and in HydroSimulatics's Security & Trust documentation are intended to reduce unauthorized access and improve data protection across supported deployment modes. Specific protections available to a User depend on account category, deployment configuration, and selected key-management mode.
Network-Native Water Intelligence
You already have a network of problems. MAGNET is the network-scale way to solve them. Live collaborative modeling across continents. Confidential private networks for your organization. A global Observatory where every pin is a living model, every sensor is visible, every contribution compounds. This is how water intelligence actually scales.
Live global pin-based model network. Every pin is a working model. Opens in a new tab.
Everything is a network.
Data is a network. Technology is a network. Models cite and build on models. People are a network. And the problems themselves — aquifers crossing state lines, contamination crossing watersheds, climate cascading across continents — are networks. The approach must match the problem's topology.
Until now, the tools didn't support network-native work. Data had to move to a desktop. Models had to be rebuilt for each site. Collaboration happened in email. The technology forced the workflow to be siloed — not by choice, but by constraint. MAGNET4WATER removes the constraint.
Who benefits from network-native modeling?
Three very different kinds of users — all with network-shaped problems. Until now they rarely interacted. MAGNET brings them into one connected space.
🏢
Enterprises & Consulting Firms
Your portfolio is a network. Treat it like one.
Global consulting firms manage hundreds of sites. Corporate operators like BP, Coca-Cola, Google, and Microsoft have water footprints across continents. Every site shares hydrogeology, watershed context, and lessons with its neighbors. Network-native modeling turns "coordinating separate projects" into "operating one intelligence system." Knowledge compounds across your portfolio instead of walking out with departing staff. Confidential computing keeps private work private — while your internal network shares seamlessly.
Portfolio-wide intelligence
Confidential computing
Internal collaboration at scale
Knowledge retention
🏛️
Government Agencies
Your mission is inherently networked.
DOD manages installations on multiple continents. DOE runs national labs with regional water challenges. State DEQs oversee portfolios of contaminated sites. International development banks (World Bank, ADB, IDB, AfDB) evaluate infrastructure projects across dozens of countries. USGS, NASA, NOAA, USDA, EPA all generate data that belongs in the same analysis but lives in separate systems. MAGNET provides the unified operating layer — with the security and sovereignty that agency work requires.
Mission-scale operations
Multi-jurisdiction coordination
Regulatory-grade engines
Data sovereignty
👤
Individual Professionals
Your work, in action — not a bullet list.
Consultants, researchers, educators, graduate students, small firms. A resume, LinkedIn profile, or portfolio PDF describes your work in text and static images. Your Observatory node shows it in action: your model running live in 3D, animations of what you simulated, AI-generated reports explaining your assumptions and findings, and critically — the USGS sensor network rendered around your site, placing your work in its real observational context. Funders, recruiters, sponsors, peer reviewers, and potential clients can explore your thinking at any depth. Generated instantly when you publish. Your living resume.
Living interactive portfolio
AI-generated report (instant)
USGS sensor network overlay
Professional visibility
Your work, in action.
A resume is a list of claims. A LinkedIn profile is a list of claims. A portfolio PDF is a flattened snapshot. An Observatory node is your work running — the model you built, the system you understand, the thinking you did. Generated instantly when you publish.
📄 The conventional portfolio
Bullet list: "Modeled regional water system in Michigan"
Flat document: Static screenshots, paragraph descriptions
Claims communicated through text: the reader reads about the work
Substantial assembly effort: writing, formatting, version control across applications
Skim-and-file: typical attention span 30 seconds
🔭 Observatory node
Your model, running live: 3D visualization in browser
Animations: plume migration, flood propagation, recharge patterns
AI-generated report: assumptions, processes, data sourced, implications
USGS sensor overlay: the real observational context around your site
Generated effortlessly: a few keystrokes and your node is live
Explorable at any depth. Credible through context.
A prospective funder can see exactly what kind of modeling you do. A recruiter can see your technical depth. A peer reviewer can interrogate your assumptions. A potential client can evaluate fit for their site. Your best work stops living in PDFs and starts living in the Observatory.
How the network works.
Specific mechanics — not vague promises. Each capability designed to make network-scale work actually feasible.
👥
Live Collaborative Modeling
You and invited guests work on the same model simultaneously — from anywhere in the world. This isn't Google Docs for hydrology. It's shared simulation state. Changes propagate in real time. Discussions happen around the live model, not around emailed screenshots. Field staff, office team, external reviewer, international partner — all inside the same working session.
🔒
Private & Public Networks
Within your corporate or agency network, collaboration is seamless and fully confidential. Confidential computing means data and models are encrypted in transit, at rest, and during computation — even HydroSimulatics cannot access Premium-tier work. You choose what gets shared externally, when, and at what level of detail. Graduated disclosure — exploration stays private, final work can go public.
📍
Pin-Based Global Observatory
Every published model becomes a pin on the world map. Click a pin → enter that local observatory. See the model in 3D, watch auto-captured animations, browse the input data, inspect calibration results, read the AI-generated report. The pin shows not just the model but the sensor network around it — monitoring wells, stream gauges, weather stations, quality sampling points. Context travels with the work.
📄
AI-Generated Reports
When you publish, MAGNET's AI reads your complete model state — inputs, parameters, calibration, simulation results, data sources — and generates a professional technical report. Assumptions documented. Processes explained. Data sourced and cited. Implications interpreted. Something only MAGNET can do, because only MAGNET can see inside your actual model. Your publication becomes a finished deliverable, not just a file dump.
🔗
One-Click Model Adoption
Found a published model that's relevant to your work? Load it into your own platform session with one click. Fork it, refine it, adapt it to your site, extend its scope. The barrier between "I saw this model" and "I'm working with this model" disappears. Predecessor work becomes raw material for your next analysis — with attribution preserved.
📊
Social Analytics
Comments on specific aspects of a model. Endorsements from peers. Trend tracking of which models get reused or cited. Quality emerges through use, not editorial gatekeeping. Researchers see what approaches are gaining traction. Agencies see what methodologies peers are adopting. Individual professionals build reputation through visible contribution.
Your model, embedded in reality.
Every Observatory pin automatically renders the USGS sensor network around your site — monitoring wells, stream gauges, water quality sampling points, weather stations, soil moisture sensors. Whether the sensors were used in your specific model or not. Soon: national and regional sensor networks worldwide. Model is data. Data is model. They belong in the same view.
Publish at any stage you see fit — early exploration, partial models, teaching examples, work in progress, final deliverables. The sensor network overlay doesn't judge your model against the data; it gives viewers context. A model that matches nearby sensors tells one story. A model that diverges from them tells another — often more interesting — story: where the physics might be missing something, where new data would help, where a hypothesis deserves testing. Both are worth publishing. Both belong in the Observatory.
This is what makes MAGNET's Observatory structurally different from generic 3D model hosting. Anyone can render a model in 3D. What they can't do is place it automatically alongside the living observational infrastructure of that location. Your model becomes a node inside a larger conversation — between what you simulated and what's being measured nearby, right now.
🎯
Data reveals model gaps
Sensor data that the model didn't use may point to what the physics missed
📡
Model reveals data gaps
Simulations show where new sensors would add the most information — data worth
⇄
Both evolve together
As sensors and models grow, the shared representation of the system gets sharper
Communities that rarely interact — now can.
A BP hydrogeologist, a USGS scientist, a Drexel professor, a consulting firm partner, a state regulator, a graduate student — all have complementary knowledge of the same water system. Before, that knowledge lived in separate institutions. Now, at whatever level of disclosure each user chooses, it can flow.
A social layer grounded in real work.
Observatory social tools aren't generic likes on witty posts. Every interaction is anchored to a substantive technical artifact — a model someone actually built, published, and documented. The quality floor is structurally higher. Two layers serve different conversations:
Layer 1
Inside each local observatory.
When someone enters your pin, they're inside your specific model's observatory. The conversation here is intimate, technical, and specific — scholarly dialogue around a particular piece of work. Think GitHub issues meeting peer review, but around a living, runnable model.
💬
Comment
Ask about assumptions, calibration choices, interpretation
👍
Endorse
Recognize clever approaches, clear documentation, impactful findings
👥
Follow
See the author's future published models and updates
🔖
Bookmark
Save models you may adopt, reference, or revisit later
Layer 2
Across the global ecosystem.
Zoom out from any single pin to the entire Observatory. This is the bird's-eye view — where the ecosystem reveals itself. Discovery, analytics, promotion, trend-spotting across thousands of models in every water domain.
🔍
Search & Filter
By domain, region, engine, author, date, keywords
📈
Trending Now
Which models are getting attention, adopted, cited
⭐
Featured Work
Editor picks, community highlights, exemplary contributions
📊
Ecosystem Analytics
Coverage maps, domain activity, regional growth, methodological trends
🌱
An ecosystem evolves with its community.
Core publishing, the pin-based Observatory, AI-generated reports, and foundational commenting are live today. Richer social mechanics — advanced analytics, trend surfaces, featured-work curation, cross-pin discussions, notifications, following — will roll out as the community grows. We're building this with our users, not just for them. If you have ideas for what would serve the network best, we want to hear them.
Public Observatory. Private Network. Your Choice.
🌍 Public Observatory
Anyone can explore, learn, and contribute
Models published as pins on the global map
AI reports, visualizations, data fully accessible
Benchmark against published work — stop reinventing
🏢 Private Network
Secure, confidential workspace for your organization
Live collaboration within your team or across sites
Full modeling, reporting, analytics — all internal
Share selectively when ready — sovereignty preserved
AI-Powered Publication
Your model is data-rich. Let AI translate it into a professional, citable, stakeholder-ready report — instantly.
📝
Publish a Model. Get a Report.
One click transforms your published model into a professional technical document.
When you publish to the Observatory, MAGNET's AI reads everything — every data source, every parameter, every calibration target, every simulation result. It understands what went into the model because it built the model with you. Then it writes what no public AI ever could: a technically accurate, fully sourced report grounded in your actual model, not hallucinated from general knowledge.
Auto-generated narrative
Every input sourced & cited
Calibration statistics interpreted
Results visualized & explained
Assumptions documented
Stakeholder-ready language
🔍
AI Reads Your Model
Model geometry, parameters, boundary conditions, recharge, data sources — the AI knows what went in because the platform assembled it
📊
AI Interprets Results
Calibration residuals, water balance, plume extent, capture zones, head distributions — translated from numbers into professional narrative
📄
You Get a Report
Site description, conceptual model, methodology, calibration discussion, results, conclusions & recommendations — ready for clients, regulators, or journals
Why can't public AI do this?
ChatGPT and Claude are powerful — but they can't see your model. They don't know your hydraulic conductivity grid, your 47 calibration wells, your simulated PFAS plume. They would guess. MAGNET's AI doesn't guess — it reports what actually happened in your simulation, with every number traceable to its source.
The incentive is simple: publish your model → get a professional report for free. Your contribution strengthens the global base model. The report saves you hours of writing. Both sides win.
The Network Effect
Every model published to the Observatory strengthens the global base. A consultant in Michigan calibrates a water system model — a student in Germany learns from it. A government agency models PFAS contamination — every other agency facing the same crisis gains access to the methodology. Individual contributions produce collective intelligence as a side effect.
One platform. Hundreds of sites. Consistent methodology. Growing intelligence.
Modeling Philosophy
The way we use water isn't sustainable. But the deeper problem is: the way we solve water problems isn't scalable. MAGNET4WATER exists to fix both — by changing the paradigm, not just the tools.
The Setup Drain
For natural systems, most project time disappears into data wrangling before any modeling begins.
Groundwater and watershed modeling depend on massive spatial datasets — DEMs, geology, soils, land use, climate, hydrological networks. Every consultant, every researcher, every agency downloads them, cleans them, reprojects them, and assembles them from scratch for every new project. The same data. The same process. Worldwide. This isn't just inefficient — it's a systemic obstacle that prevents our community from exploiting the digital revolution. The world's best spatial data is too voluminous for the data-to-desktop workflow pattern to move, process, and integrate at the speed today's questions demand. So it stays underutilized. Experts spend their time wrangling data instead of solving problems.
For engineered systems (stormwater, distribution), the bottleneck is different. The infrastructure doesn't exist yet — you're designing it. But design tools live in one silo, hydraulic models in another, cost estimation in a third. Every change means switching contexts, re-entering data, waiting for results. Iteration dies in the gaps between tools.
The conventional paradigm
Data is downloaded from sources to local machines for each project
The model is built up from its foundation, project by project
Different tools handle design, simulation, cost, reporting
Each run is a discrete event, with data entered or re-entered between runs
Foundation work necessarily takes the largest share of every project's time.
The MAGNET paradigm
Model comes to the data: the foundation is already in place — assembled once for everyone, refined where the question demands
End-to-end on one steering surface: data → model → analytics → visualization → cost → iterate
Human in the loop: design, monitoring, refinement, results, management — all in one continuous session
Foundation work inherited: human time goes to the substance of the problem, not to rebuilding what's been built before
The shift is paradigm-level — what becomes possible when the foundation is shared.
The Core Principle
Don't move the data.
Bring the algorithms to the data.
The structural limit of the data-to-desktop workflow is that massive, connected spatial data cannot move efficiently into isolated desktop environments at the speed today's questions demand. MAGNET reverses this: the data stays on the network — pre-processed, interconnected, ready. Your algorithms, simulations, and analyses come to the data. The internet becomes the computer. The world's spatial fabric becomes the foundation — assembled once, for everyone.
The Foundational Digital Twin
A pre-processed, globally assembled digital representation of the world's water systems. For natural-system modeling, the data foundation is already in place — you zoom in and start refining, not rebuilding.
🌍
Processed Once
Assembled for everyone — not repeated by everyone
High-resolution DEMs, geology, hydrology, soils, climate, land use, drainage networks — all pre-processed and spatially interconnected. The terabytes of raw data that would take months to wrangle are already cleaned, integrated, and ready. You start where the data scientist finished.
🔬
Refined Locally
Your expertise starts at the point of highest value
The expert's work begins where it matters: filling local data gaps, calibrating against site observations, customizing for the specific scenario. No time wasted on global data acquisition. Your judgment, your local knowledge, your refinement — applied to a foundation that's already structurally sound.
📈
Improved Collectively
Every model strengthens the foundation
When you publish to the Observatory, your calibrated model improves the global base. A consultant in Ottawa County refines the glacial aquifer. A researcher in Pakistan characterizes the alluvial system. A student in China maps the urban drainage. Each contribution is a building block — the twin evolves, and the next user starts from a better foundation.
How the paradigm becomes real
The MAGNET modeling paradigm is not tied to a single tool. It becomes real through domain-specific platforms, each translating the same foundation — prepared data, cloud computation, live analysis, and local refinement — into the workflow of a specific water system.
💧
GroundwaterIGW-NET — 3D aquifer dynamics
Real-time, human-in-the-loop groundwater modeling where flow, particle tracking, and contaminant transport evolve together within 3D unsteady aquifer systems.
Explore IGW-NET →
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WatershedsSwaNET — basin water balance
Watershed-scale hydrologic modeling from global basins to local refinement, integrating land use, soils, climate, stream networks, and management scenarios.
Explore SwaNET →
⛈
StormwaterStormNET — urban flow systems
Stormwater, sewer, river, and urban drainage modeling for runoff, flooding, and infrastructure performance under real-world rainfall and design conditions.
Explore StormNET →
🚰
Water distributionConduitNET — network hydraulics
Pressurized water-distribution modeling across scales — for pipes, pumps, tanks, valves, pressure zones, water age, and operational scenarios. From a campus loop to a metropolitan supply network.
Explore ConduitNET →
📡
Data systemsDataNET — global data fabric
Integrated global data infrastructure for terrain, hydrography, climate, land use, soils, observations, WMS/WFS/WCS services, and model-ready data fusion.
Explore DataNET →
The Proof
The paradigm shift isn't theoretical. It's working — at scale, in production, with real consequences.
The Vision
Think together. Act in concert. Build on each other.
When a consultant in Michigan calibrates a glacial aquifer model and publishes it to the Observatory, a student in Germany can find it, learn from it, and build on it. When a government agency models PFAS contamination across a portfolio of sites, the methodologies become available to every other agency facing the same crisis. Individual self-interest — solving your problem, publishing your work, advancing your career — produces collective intelligence as a side effect.
This is the network effect applied to water science. The foundation improves with every model. The next user starts from a better position than the last. The living digital twin of the world's water systems emerges — not from a top-down mandate, but from thousands of individual contributions, each solving a local problem, together building planetary water intelligence.
How MAGNET is Designed
The seven design principles that make MAGNET4WATER structurally different from every other water modeling system.
01 · Structure
Three domains, one foundation
Natural systems (groundwater, watersheds). Engineered systems (stormwater, distribution). Data systems (fusion, analytics). Three domains that share one foundational digital twin — the Global Base Model. The same fabric of terrain, soils, climate, and infrastructure underlies every simulation, regardless of which platform asks the question.
02 · Philosophy
Model is data. Data is model.
A water table surface is a model — someone interpolated it from observations. A simulation output is data — a spatial field of computed values. Process-based simulations publish as WFS/WCS data layers; data layers feed new simulations. The flow is bidirectional, and that bidirectionality is what makes a network of models continuously enrich itself.
03 · Epistemology
Fusion beyond physics
The world does not just have a data scarcity problem — it also has a data utilization problem. Direct measurements of state variables (flow, head, quality, performance) are sparse. Yet large volumes of public, private, historical, and model-derived data remain unintegrated. Sparse measurements tell us what is happening; dense spatial data tells us why. Physics-based models, statistical fusion, and machine learning work together — using the controlling spatial fabric to guide interpolation, calibration, and targeted refinement where one method alone is not enough. Nonuniqueness is acknowledged, not hidden.
04 · Honest Framing
The default model enables
The base model is not a constraint. It is a starting system. MAGNET begins with what we believe is the best available top-down foundation — but nothing is locked. Refine DEMs, land use, soils, wells, climate, infrastructure, telemetry. Modify conceptual assumptions, numerical resolution, boundary conditions, calibration targets. Change visualization, analytics, reports, communication products. You begin with an end-to-end, visual, interactive system — from data to simulation to insight to publication — then take it wherever the local question demands.
05 · Paradigm
The network is the model
MAGNET4WATER is network-native. Every model published to the Observatory enriches the global foundation. Every contribution compounds. The network doesn't just host models — the network IS the model, growing more complete with every user, every refinement, every publication. A new region's calibration improves the next user's starting point.
06 · Evolution
Everything is perpetual beta
No model is ever finished. New data arrives, understanding deepens, methods improve. MAGNET treats every model as a living document — versioned, refinable, always open to the next observation. The system is designed for evolution, not completion. What was the best representation last quarter is the starting point for this quarter's improvement.
07 · Lineage
Built on what works
The global base model is possible because three streams of progress converged. Modeling frameworks — MODFLOW, SWAT, SWMM, EPANET, MT3DMS, SEAWAT, MODPATH — represent decades of community work on how water systems behave. Agency datasets — USGS, NASA, NOAA, ESA, EPA, FEMA, USDA, NRCan, monitoring networks — represent decades of work on how to measure them. And the digital revolution — geospatial web services, cloud infrastructure, sensor networks, large-scale processing, 3D visualization — represents decades of work on how to connect them. MAGNET's contribution is the convergence: the way these three streams now work together as one editable, end-to-end system where data-driven understanding and process-based modeling enrich each other live. That is the paradigm shift — not new physics, not new data, but a fundamentally faster cycle between them.
The bidirectional flow
DATA
Observations · Sensors · Remote sensing · Statistical fusion
⇄
MODEL
Process-based simulation · Calibration · Prediction · Scenarios
Published via WFS/WCS — model outputs become data services, data services feed new models. Both sides evolve together.
The Inflection Point
Why water resources sustainability transformation cannot happen without water resources digital transformation — and what that means for the organizations leading the response.
The price of civilization
8 billion people. Three faces of the same strain.
The water footprint of humanity has surged. Industrialization, urbanization, digitalization, intensive agriculture, and militarization have reshaped the planet — and strained its most vital resource. The numbers are not just alarming. They are unsustainable.
⅔
Severe Water Scarcity
Two-thirds of the world experiences severe water scarcity at least one month each year — straining agriculture, industry, and daily life.
⅓
Flood Exposure
One-third of the global population lives at risk of flooding — and climate stress widens the exposure envelope every year.
½
Sanitation Gap
Nearly half of humanity lacks access to safely managed sanitation — the public-health face of the same water-systems challenge.
Beneath the surface, one-third of the world's major aquifers are rapidly depleting — the long-term reserve quietly draining.
These are not isolated metrics. They are faces of the same strain. Population is growing. Climate is intensifying. Urban and industrial demand is accelerating. The status quo is no longer viable — humanitarian, environmental, regulatory, or economic.
The digital revolution adds to the load
AI cooling is now a water question.
The technology that promises to help solve the crisis is itself a source of it. Artificial intelligence training and cloud operations consume enormous and accelerating volumes of water for cooling and energy generation. As AI adoption accelerates, so does its water footprint — water-smart innovation is no longer optional, for sustainability or for the future of computing itself.
The fundamental challenge
We cannot understand, quantify, or manage human–water systems fast enough.
Behind every crisis above sits one root condition: our inability to understand, quantify, and manage human–water systems cost-effectively — in an uncertain world and a changing climate. The science exists. The data exists. The technology exists. What is missing is the infrastructure that turns all three into decisions at the speed and scale the problem demands.
Leaders are converging on this diagnosis. The Water Resilience Coalition — more than 100 major corporations — has pledged to become water-positive, elevating water stress to the top of the global corporate agenda. Microsoft's 2024 Environmental Sustainability Report reached four hard conclusions: the world is not on track for its water goals; traditional replenishment projects alone will not meet the required scale; the pace of action must accelerate dramatically; and decision-making with a system mindset is no longer optional. Breakthroughs are urgently needed.
The water community knows what to do. The bottleneck is the cost and the pace at which knowledge becomes action.
Where the conversation is moving
From compliance to operational infrastructure.
As the recognition broadens, the framing itself is shifting. For a generation, water sustainability sat on the CSR officer's desk as a reporting line and a compliance burden. That frame is collapsing under operational reality. AI training facilities are constraining where they can be built by water availability. Semiconductor fabs are sited by aquifer math. Beverage operations are halting in water-stressed basins. State and federal regulators are managing contamination portfolios with thousands of sites and finite budgets. Insurance and credit markets are pricing water exposure into corporate ratings.
None of this is sustainability messaging. It is operational infrastructure — the same category as power, cloud, security. And it has moved from the CSR officer's desk to the CFO's. From the regulatory compliance team to the agency director. From the sustainability report to the board agenda.
The organizations — corporate and governmental — that develop real water intelligence will out-compete and out-deliver those that treat it as compliance. This is the strategic moment.
One problem, three exhibits
Different audiences. Different dollar figures. Same structural problem.
Look closely at the largest water-related programs underway worldwide today. The actors look different. The reporting frameworks are different. But the structural challenge is identical: too many sites, unequal in risk and value, finite resources, no path to depth-everywhere.
Case · Maximum Scale
DOD's global footprint
The U.S. Department of Defense operates installations on multiple continents — thousands of sites across diverse climates, geologies, and regulatory regimes. Firefighting foam was standard issue at most of them for decades; PFAS in groundwater is a national-scale liability now measured in the hundreds of billions of dollars. DOD cannot deep-study each installation. It must triage. The decisions about where to remediate, where to monitor, and where to defer are being made right now — and they require methodology that works the same in Germany as it does in Texas.
Case · Regulatory Scale
State regulatory portfolios
Allegan County alone has 351 documented sites of concern. Multiply across a state — then across the nation — and the operational picture becomes clear. State environmental quality departments oversee contamination cases at a scale that makes site-by-site contracting structurally inefficient. The work is too important to leave inconsistent. Michigan EGLE moved from site-by-site contracting to a unified MAGNET deployment; documented savings reached $30M and methodology consistency reached every case.
Case · Corporate Scale
Fortune 500 water programs
Global manufacturers, beverage operators, semiconductor leaders, and hyperscalers operate hundreds of sites across multiple continents. Each one shares hydrogeology, watershed context, and regulatory exposure with the others. Each has different priority. After a decade of corporate water-positive programs, the pattern is unmistakable: the companies that built networked intelligence are out-pacing those that built site-by-site reports. Same structural problem the regulators face — different stakeholder set, different dollars, same answer.
The diagnostic case
PFAS makes the abstract concrete.
PFAS is the example everyone now recognizes. It crosses every actor: industry creates it, government regulates it, communities live with it, insurance prices it, capital markets factor it. It is genuinely present nearly everywhere. And it is persistent — that is what "forever chemicals" means.
But persistence is precisely why prioritization matters. Persistence doesn't mean all sites warrant the same response, the same urgency, or the same dollars. Some sites require active remediation today. Some warrant ongoing monitoring as conditions evolve. Some are best documented and prioritized below sites of greater impact on people and ecosystems. The challenge isn't whether to act — it is how to make defensible decisions about where to focus finite resources across thousands of sites where the contamination is real but the priorities are unequal.
PFAS is the canonical case for the multi-tier, multi-scale approach. It is also why a screening-then-deep paradigm with one consistent methodology is a viable response. The same question applies to other contamination classes, watershed risks, and water-resource challenges at scale.
The structural answer
One framework. Two axes.
The only response that scales is one architecture that works consistently across both axes of the problem — vertically through levels of detail, horizontally across the portfolio. Same engine. Same assumptions. Same methodology. Insights propagate naturally between sites and between depths.
↕
Vertical: depth of analysis
From screening-level analysis — the fast pass that tells you which sites warrant attention — to intermediate analysis for triage and prioritization, to deep, fully calibrated, physically-based simulation where decisions and budgets demand it. The same engine at every level.
A finding at screening depth at one site can be deepened on demand. A deep model in one watershed seeds screening analyses across the region. Insights flow between levels because the architecture is one architecture — not two disconnected tools.
↔
Horizontal: across the portfolio
Across sites. Across watersheds. Across continents. The global base model that backs every MAGNET deployment means analysis begins at a base in Germany the same way it begins at a base in Texas, at a contamination site in Allegan the same way it begins at one in California. Consistent methodology across the entire portfolio.
When sites speak the same modeling language, portfolios become navigable. A finding at one location informs decisions at others. Methodology consistency is what makes regulatory defensibility scalable.
The alternative is what every organization tries first and abandons later: site-by-site deep custom science (too expensive, too slow, doesn't scale) or broad shallow analysis across the portfolio (cheap, fast, not credible). MAGNET is neither — it is both, in one framework, with insights flowing freely between depths and across sites.
The thesis
Water resources sustainability transformation requires water resources digital transformation.
The multi-tier, multi-scale infrastructure described above is not a feature wishlist. It is the structural response the scale of the problem demands — the system-mindset breakthrough that leaders across the corporate and scientific community have called urgently necessary. The organizations that build this layer now — corporate or governmental — will define the cost structure and decision quality of their sector for the next decade. MAGNET is that infrastructure. Twenty years of research and continuing scientific work, deployed in real programs at real scale, available today.
Consulting & Training
HydroSimulatics is the consulting and engineering team that built MAGNET — and operates it daily across deployments in 43 countries. When the platform overhead disappears, the time goes to the problem itself: where contamination is moving, how a basin's water budget actually balances, which sites in a portfolio warrant action now. Deeper work. More defensible answers. Value that compounds beyond the engagement.
What makes our consulting different
Where the time goes determines what the work becomes.
In typical water-modeling consulting, the majority of an engagement disappears into platform mechanics — setting up software, troubleshooting calibration, debugging data integration, training staff on tooling. The actual water problem gets whatever's left. HydroSimulatics inverts that ratio.
The unique position
We built the platform. We operate it daily.
Operating MAGNET across thousands of deployments in 43 countries gives HydroSimulatics exposure to actual water problems at a frequency no traditional consultancy matches. We know what data MAGNET expects, where calibration drifts, which regional adaptations work, what the failure modes look like before they appear. The hours that other consultants spend learning the tool, our team spends understanding your hydrology.
The substantive consequence
Time on the problem means work that lasts.
Deeper investigation of the contaminant transport mechanism. More rigorous testing of the basin water budget. More defensible documentation of the assumptions and uncertainty. Answers that hold up in court, in regulatory hearings, in board reviews, and in front of communities. The work doesn't end when the engagement ends — your team owns the living model, your institution owns the methodology, and the substance compounds across future projects.
"We don't just hand you a model. We build your capacity to create, calibrate, interpret, and defend your own models — and to teach others to do the same. The goal is independence, not dependence."
Concrete capabilities
What we can help solve.
Every domain below builds on platform capabilities we know intimately. Whether you need a single site assessment, a multi-basin program, or a portfolio-wide strategy, the work starts from where MAGNET already is — not from a blank screen.
🌍
Sustainable Water Management
Long-horizon planning across supply, demand, quality, and ecosystem function — at site, watershed, basin, and regional scales.
💧
Water Resources System Modeling
Coupled groundwater–surface water–watershed–distribution systems modeled together, with consistent methodology from screening to deep simulation.
🛡️
Pollution Control & Aquifer Protection
Source-water protection, wellhead delineation, regulatory defensibility for drinking water supplies and groundwater dependent ecosystems.
♻️
Managed Recharge & Recovery
Site selection, operational design, recovery efficiency, regulatory framework, and long-term performance monitoring for MAR projects.
⚗️
Contaminant Fate & Transport
PFAS, TCE, nitrate, saltwater intrusion, emerging contaminants — defensible plume delineation and exposure forecasting.
🎯
Risk-Based Remediation
Site triage and prioritization, monitored natural attenuation, active treatment design, and progress assessment across portfolios.
🐟
River & Ecosystem Restoration
Hydrology–ecology integration, sediment transport, instream flow requirements, habitat connectivity, and watershed-scale outcomes.
🌊
Risk-Based Flood Protection
Probabilistic flood modeling, infrastructure design under climate uncertainty, resilience planning, and FEMA-grade documentation.
🏞️
Watershed Management
Land use impact assessment, pollutant load reduction strategies, basin-scale planning, and integrated catchment management.
🌾
Nonpoint Sources & Agricultural BMPs
Field-to-watershed nutrient and sediment modeling, conservation practice evaluation, and water quality trading frameworks.
☔
Stormwater Treatment & Harvesting
Green infrastructure design, stormwater capture and reuse, treatment train modeling, and combined-sewer overflow mitigation.
🌿
Low Impact Development
Site-scale design for LID/green infrastructure, cumulative watershed benefits, regulatory compliance, and post-construction performance.
🚰
Efficient, Resilient Water Supply Systems
Source-to-tap optimization, climate-resilient design, demand management, distribution system modeling, and integrated planning.
Don't see your specific challenge? Talk with us — most water problems map to capabilities we already operate at scale. We'd rather have an honest conversation about fit than try to be everything to everyone.
A domain where we deliver exceptionally well
Expert Witness & Litigation Support
When the deadline is the court — or the contested permit hearing, the regulatory review, the insurance dispute — water modeling has to do something traditional water consulting rarely manages: produce credible, visual, defensible insight on a schedule that doesn't move, in the working language stakeholders and decision-makers already use. This is where HydroSimulatics consistently delivers exceptional outcomes for our clients.
Visualization is the language.
Tables of contamination concentrations don't persuade juries. Spreadsheets of aquifer parameters don't move judges. Static diagrams don't carry the day in a contested permit hearing. Animated, three-dimensional, time-lapsed visualizations do. A jury that can see a contamination plume migrating from a source over decades, or watch how a marina basin's vertical leakage would alter dune-aquifer flow without a clay liner — that jury, or that regulator, or that judge, can make an informed decision. MAGNET's visualization layer is built for exactly this.
Speed
Court deadlines don't move.
When a hearing is in 8 weeks, there's no time to build a model from scratch, calibrate it, troubleshoot software, and produce exhibits. Starting from the calibrated global base model and a platform we operate daily, our team produces credible visualizations and defensible analyses on timelines that hold up against fixed legal calendars. Weeks instead of years. Cost-effective because the platform overhead disappears.
Visualization
Judges, juries, and regulators see the truth.
3D animated cross-sections of the subsurface. Time-lapse contaminant transport. Side-by-side scenario comparisons. Watershed flow paths visualized in plan and section. The science doesn't change — but the audience finally sees it. Iteration in days, not months. Exhibits the legal team and the technical expert can build together, in real time.
Defensibility
Open architecture. Survives cross-examination.
Opposing counsel will probe every assumption, every parameter, every calibration choice. MAGNET's physics-based, peer-reviewed engines and open architecture mean every input is traceable, every step is reproducible, every assumption is visible — methodology that has matured through twenty years of research and continues to advance with the broader scientific community.
Proof — two contested-case outcomes
Winning cases. And winning approvals.
Two different kinds of contested-case work, both demonstrating the same advantage: credible, visual, defensible water-resources analysis delivered in time to matter.
Case · Courtroom Victory
Mika Meyers groundwater litigation
A complex multi-year groundwater contamination case where the gap between what a hydrogeologist understands and what a judge or jury can see was where the case would be won or lost. MAGNET-generated 3D visualizations, time-lapse exhibits, and physics-based contaminant transport animations made the science visible. The client won.
"Precisely what I needed... generate very quickly visual aids in the form of exhibits and animations so that I could make complex hydrogeological concepts understandable to a judge or jury. It was the primary reason my client was very successful in the outcome of this litigation."
— Doug Donnell, Attorney · Chairman Management Committee, Mika Meyers PLC, Grand Rapids, Michigan
Read the full case →
Case · Regulatory Approval
Coastal marina development approval
A luxury waterfront marina proposed in a politically sensitive coastal dune aquifer ecosystem. State regulators (EGLE) and community stakeholders held conflicting views. MAGNET guided design at every step — identifying the vertical-leakage risk in the original plan, engineering the clay-liner solution, optimizing section-based dewatering to minimize construction impacts, and producing transparent, calibrated, defensible documentation. The client secured state approval under challenging conditions.
Transparent (every assumption visible), defensible (calibrated simulation), objective (data-driven, not political), and science-based — exactly what a contested regulatory review requires.
— Documented in case study; design and approval pathway guided by MAGNET-driven analysis
Read the full case →
If you're an attorney, in-house counsel, or litigation manager working on a water-related case — or a developer facing a contested permit review — talk with us early. The work is more effective, and more cost-effective, when MAGNET enters the analysis before the modeling deadline arrives.
Technical Services
Every service below is powered by MAGNET-based modeling — the same platform you'll use after we leave. No black boxes, no proprietary formats, no vendor lock-in. You own the model, the data, and the understanding.
💧
Water Resources Modeling
Groundwater · Watersheds · Stormwater · Distribution · Rivers
Full-spectrum modeling across all five platforms. Hierarchical, multiscale, calibrated — delivered as a living model.
⚠️
Contamination & Remediation
PFAS · TCE · Nitrate · Saltwater intrusion · Legacy plumes
Contaminant transport, risk delineation, remediation scenarios, and defensible decision support.
🌊
Watershed & Ecosystem
BMPs · Climate resilience · Nonpoint source · Habitat · Flood
Land use impacts, nutrient transport, BMP evaluation, climate scenarios, and flood modeling.
🏗️
Infrastructure & Resilience
Supply systems · Green infrastructure · LID · Recharge · Storage
Source protection, demand forecasting, managed aquifer recharge, and LID site-scale design.
🌐
Custom Observatories
Your data · Your models · Your team · Your visibility rules
A secure, branded workspace for publishing, discovering, and iterating on models.
Training & Capacity Building
The best technology creates dependency if users can't operate it independently. Our training programs transfer capability — not just knowledge. After training, your team models, calibrates, and communicates on their own.
How Our Services Are Different
The conventional consulting workflow
Each project starts by building its own modeling foundation
Deliverables are documents and figures — the model itself lives with the consultant
Data collection is typically a major project phase, often months
Models, methods, and institutional knowledge ride with the practitioner
Each engagement is independently scoped and resourced
MAGNET-Powered Services
Start from the Global Base Model — data foundation already assembled
Client owns the living model — keeps refining after we leave
Data Center provides instant access to pre-processed data
Training transfers capability — your team operates independently
Every model strengthens the observatory — institutional memory accumulates
The Result
Deeper: Time invested where it matters — the actual hydrology, the actual contamination, the actual decision
More defensible: Documentation, calibration, and uncertainty handling that stands up in regulatory and legal contexts
Lasting: Your team owns the living model — capability stays after we leave
Scalable: The same approach works for one site or one thousand
Compounding: Every engagement adds to your institutional water intelligence
Partnership Tiers
Three levels of engagement — from a private workspace to a fully customized intelligence platform tailored to your mission.
Closed Network
Private observatory for internal collaboration
Secure sharing across your teams
Full modeling and visualization
Minimal setup, fast deployment
Start modeling within days
Pre-Calibrated
Models calibrated to your geography
AI-powered reporting in multiple formats
Operational teams act on validated baselines
Spatial reasoning is the working language
Intelligence built into the workflow
Fully Customized
Interface tailored to reduce training needs
Proprietary database integration via open standards
Sector-specific dashboards and workflows
Portfolio-wide screening and simulation
Your platform, your intelligence
We work iteratively — define goals, scope collaboration, build together, launch with confidence. Whether you need a private workspace for one basin or a portfolio-wide intelligence system across continents, we scale to your ambition.
Proven Results
Enterprise & Network Solutions
Water is no longer a sustainability question — it's an infrastructure constraint on growth. AI training facilities run on water. Semiconductor fabs are sited by water availability. Beverage operations halt when regional aquifers run dry. The organizations that develop real water intelligence — across sites, basins, and jurisdictions — will out-compete the ones that treat it as compliance. MAGNET is that operating layer.
The competitive landscape has changed
Water is now operational infrastructure — not a sustainability line item.
The companies sitting at the frontier of AI, manufacturing, and consumer goods are discovering this in real time. Water risk has moved from the CSR officer's desk to the CFO's desk — and from the CFO's desk to the boardroom. The signals are everywhere; the question is whether your organization has the intelligence layer to act on them.
Signal · AI & Cloud
Hyperscaler regions are being declined on water grounds.
AI training facilities consume billions of gallons of water for cooling. Major hyperscalers have already had data center permits denied or delayed in water-stressed counties. The capacity build-out that powers modern AI now depends on water availability the way it once depended only on electricity. Companies that can model, defend, and negotiate their water demand will continue to build; those that can't will stall.
Signal · Heavy Industry
Billion-dollar siting decisions now pivot on water.
Semiconductor fabs require tens of millions of gallons of ultra-pure water per day. New facility siting now begins with watershed analysis before zoning. Heavy manufacturing, chemical processing, and energy operations face the same constraint. The organizations with credible, defensible water intelligence move faster through permitting, command better terms in negotiations, and can locate where competitors cannot.
Signal · Operational Continuity
Bottling plants halt when regional aquifers run dry.
Major beverage operators have had to suspend or relocate production in water-stressed basins. Food processing, agriculture, pharmaceutical manufacturing — any industry with water-intensive operations across many sites — is exposed to the same disruption. Insurance premiums and continuity planning now factor in basin-level water stress projections, not just facility-level inputs.
Signal · Capital Markets
Credit ratings now price water risk.
Major rating agencies have integrated water stress into corporate credit assessments. Banks, insurers, and institutional investors increasingly require disclosure of water-related operational exposure. The cost of capital itself is becoming water-aware. Companies with credible water intelligence — not vague sustainability narratives — defend better valuations and access cheaper financing.
This is the strategic moment. The frame is shifting — from compliance to competitiveness, from ESG line item to operational infrastructure, from CSR officer to CEO. The organizations that build a real water intelligence layer now will define the cost structure and growth trajectory of their entire sector for the next decade. The economics that follow describe how MAGNET delivers that layer.
The cost of doing it site-by-site
You're already paying for a network. You're just not getting one.
When water modeling is done one site at a time, three costs compound silently — and they show up everywhere in the budget. Most organizations don't see them as a category, because they're spread across consultant invoices, internal staff time, and the lost knowledge that walks out the door with every departing senior modeler.
$20–80K
Per Site, Every Time
A site-specific groundwater model typically takes weeks of data assembly, calibration, and reporting. At consultant rates of $150–300/hour, that's $20–80K every time the work is done. For an enterprise with 50+ sites, that recurs — often paying multiple firms for substantially overlapping work.
90% → 10%
Flip the Ratio
In traditional water modeling work, expert teams often spend the majority of their time — frequently estimated at ~90% — on data acquisition, cleaning, and integration, rather than on problem-solving and analysis. MAGNET flips the script. The platform handles the data foundation. Your team focuses on the expertise that creates value.
$30M
Saved — Real Case
When the Michigan Department of Environment, Great Lakes and Energy (EGLE) replaced site-by-site contracting with a unified MAGNET deployment across statewide contamination cases, the documented savings are estimated at $30M. Read the case →
The status quo isn't free — it's just unbilled. Every site re-done from scratch is a line item that doesn't appear on any single invoice. MAGNET turns those scattered costs into one connected investment that compounds.
A decade of corporate water programs — what's missing
Five gaps the status quo can't close. MAGNET was built for each one.
After a decade of corporate water-positive journeys, five gaps consistently block progress at scale. They aren't problems of effort or commitment — they're problems of infrastructure. Water sustainability transformation is not possible without water resources digital transformation. MAGNET is that infrastructure.
1
Dramatically more cost-efficient
The gap: No two watersheds are alike, no two sites identical. Custom science per site is prohibitively expensive. On-site monitoring everywhere is rarely feasible. Hiring consultants "forever" to keep the work going is not a sustainable model.
What MAGNET delivers: A global base model that gets each site 90% of the way there before a consultant ever logs in. Custom work — when needed — is focused, not foundational. Pre-calibrated observatories deliver decision-ready capability without bespoke modeling.
2
Systems-based, not low-hanging fruit
The gap: Real progress requires longer-term visions and the ability to chart paths to those visions. Attacking the easy wins doesn't add up to impact. Companies need standard models that quantify water balance and watershed outcomes — not just point measurements.
What MAGNET delivers: Physics-grounded simulators that connect water balance, quality, and watershed function. The same engines that win regulatory cases and stand up in courtrooms — now serving strategy decisions across your portfolio.
3
Multi-tiered corp-consultant collaboration
The gap: The most efficient division of labor is two-stage — corporations run holistic screening across their portfolio, then hand focused, detailed work to consultants where it matters most. But corporations need screening tools that can be directly handed off — and the unit economics must support investing across multiple basins per year.
What MAGNET delivers: The same platform serves both tiers natively. Your corporate team runs portfolio-wide screening. Your consulting partners drop in for focused engagements. One operating environment, two workflows — and the cost point that lets you invest in many basins, not just one.
4
Multiscale — telescoping from enterprise to site
The gap: Local goals must connect to basin health, and enterprise commitments must connect to local action. Teams need to navigate between enterprise portfolios and individual watersheds — and need telescoping models that work the same way at every scale, so insights flow between them.
What MAGNET delivers: One engine. Continental basin → regional watershed → local site → specific facility. Same architecture, same data fabric, same simulation logic. Zoom from your global portfolio view to a single well without changing platforms, models, or assumptions.
5
Smart, collective solutions — the network effect
The gap: Despite unprecedented interconnectedness, we work disconnected — in modern silos. Massive amounts of existing data go underutilized. Across companies, agencies, and consultancies, much of every project's effort goes into work that other teams have already done elsewhere — the data assembly, the foundational modeling, the standard analyses. The Internet became a platform, but for water work we've used it mostly as static storage.
What MAGNET delivers: A networked observatory where every model is reusable, every dataset is connectable, and your contributions compound. Selective sharing means you control what enters the network — proprietary work stays private; insights can be shared with named partners or published when you choose. The 90% duplication doesn't disappear because everyone tries harder. It disappears because the infrastructure stops requiring it.
We've reached an inflection point.
Sustainable water management is not a technology project — it is a transformation. And that transformation cannot happen without the digital infrastructure to support it. MAGNET is the answer corporate water teams have been describing for a decade.
Who benefits most
Your portfolio is already a network. Treat it like one.
Five categories of organization recognize this pattern instantly. If you're in one of them, you've felt the cost of fragmentation. MAGNET is built for the way your work actually flows — across sites, offices, jurisdictions, and decades.
🏢
Fortune 500 Operators
Water footprints across continents
Global manufacturers — the kind of organization Coca-Cola, Google, Microsoft, Dow, and DuPont represent — operate hundreds of sites with shared hydrogeology, watershed context, and regulatory exposure. Every facility's water assessment overlaps with the others. MAGNET lets your global water team operate as one network: a model built in one region becomes the starting point for the next, and a sustainability commitment in one watershed informs decisions a continent away.
Portfolio-wide intelligence
ESG & sustainability reporting
Confidential computing
Site-to-corporate visibility
🏛️
Federal Agencies
Missions that span the map
DOD operates installations on multiple continents. DOE runs national labs with regional water challenges. EPA, USGS, NOAA, USDA, USFWS each generate analyses that belong in the same view but live in separate systems. International development banks (World Bank, ADB, IDB, AfDB) evaluate infrastructure projects across dozens of countries. MAGNET provides the unified operating layer — with the data sovereignty, security posture, and regulatory-grade engines that agency work requires.
Multi-jurisdiction coordination
Data sovereignty
Regulatory-grade engines
Mission-scale operations
⚖️
State Agencies & DEQs
Your portfolio of sites is itself a network
State environmental quality departments oversee portfolios of contaminated sites, water rights claims, and regulatory compliance cases. Allegan County alone has 351 sites of concern. Multiplied across a state — the workload, the modeling, the consultant invoices — site-by-site contracting is structurally inefficient. MAGNET replaces the contracting churn with an operating system: one platform, hundreds of sites, consistent methodology, growing institutional intelligence.
Portfolio-scale oversight
Methodological consistency
Vendor-independent ownership
Defensible decisions
🏘️
County & Municipal Governments
Regional water systems cross local boundaries
A regional aquifer doesn't stop at the county line. A stormwater watershed crosses three municipal boundaries. Drinking-water distribution networks span jurisdictions. For county and municipal water managers, the budget for sophisticated modeling is constrained — but the questions are sophisticated. MAGNET makes high-fidelity, defensible water modeling accessible without a dedicated modeling team, and lets neighboring jurisdictions share work without losing local control.
Affordable enterprise tier
Cross-jurisdictional sharing
Modeling without a modeling team
Public-engagement-ready reports
🤝
Large Consulting & Engineering Firms
Your project portfolio IS a network
Every site shares hydrogeology, regulatory context, and methodology with its neighbors. MAGNET lets your firm institutionalize the knowledge that currently lives in individual modelers' heads — and deliver consistent, defensible work whether a project lands in Michigan, Texas, or Singapore. Your firm's competitive advantage stops walking out the door with every senior departure. The same screening-to-deep capability that serves your government and corporate clients also makes your delivery faster and more profitable.
Knowledge institutionalization
Cross-project methodology consistency
Multi-client portfolio support
Faster, more profitable delivery
Three tiers — meet you where you are
From private collaboration to full custom intelligence.
Pick the tier that fits your readiness today; upgrade as your network matures. Every tier runs on the same MAGNET platform — so what your team learns in Tier 1 transfers seamlessly to Tier 3.
Tier 1
Fastest deployment
Closed Network
A private observatory for your organization — secure internal sharing, full MAGNET platform capabilities, no public exposure. Best for organizations who want network-native collaboration immediately, without the customization overhead.
What's included
- ✓Private branded internal observatory
- ✓Confidential computing — encrypted in transit, at rest, during compute
- ✓Live collaborative modeling across your team
- ✓Full access to all 5 MAGNET platforms
- ✓Global base model + your private data
- ✓AI-generated reports for every model
Fits: small-to-medium consulting firms, county governments, municipal water authorities, single-mission agencies starting their network.
Most Popular
Tier 2
Decision-ready out of the box
Pre-Calibrated Observatory
A working observatory calibrated to YOUR geography and YOUR water systems before you ever log in. Your team starts from a validated baseline — not a blank canvas. Designed so analysts, planners, and decision-makers on your staff can run scenarios, generate reports, and inform decisions with full physical credibility behind them.
Everything in Tier 1, plus
- ✓Pre-calibrated models for your specific sites
- ✓Your historical data integrated and validated
- ✓Non-modeler-friendly scenario workflows
- ✓AI reports in executive / technical / public formats
- ✓Training and capacity building for your team
- ✓HydroSimulatics expert support during ramp-up
Fits: state DEQs, federal field offices, regional water authorities, Fortune 500 operators standing up a global water program.
Fully Customized Intelligence
A bespoke water-intelligence operating system for your organization — purpose-built UI, deep database integration, sector-specific dashboards, custom decision-support workflows. For agencies and enterprises whose mission warrants a system that looks and works exactly like the way they think.
Everything in Tier 2, plus
- ✓Custom UI — reduce training, fit your workflow
- ✓Deep integration: GIS, SCADA, LIMS, asset management
- ✓Sector-specific decision support dashboards
- ✓Custom reporting templates & alert workflows
- ✓Co-developed scenario library for your mission
- ✓Long-term strategic partnership engagement
Fits: DOD, DOE, EPA, large state agencies, multinational development banks, global Fortune 100 with mission-critical water exposure.
The network only works if you control it
Selective sharing. By design.
Enterprise interest in the network concept is strong — the value of shared methodology, common modeling foundation, and cross-site learning is obvious. What enterprises need to know is that the architecture gives them control over what enters the network. Three layers, one continuous spectrum:
Your team only
Proprietary modeling stays inside your private observatory — visible only to whom you authorize. Full encryption. No external exposure. The default state for sensitive work.
Invited collaborators
Selected partners inside your organization — or named external collaborators — gain visibility into specific models or datasets, at the depth you choose. A finished analysis can be shared while the underlying calibration data stays private.
Global Observatory
When you choose, your work can be published to the global Observatory — visible to the broader water community. Contribution happens on your timeline, by your explicit choice, at the level of detail you decide.
A model can be private today, shared with a named partner next quarter, and published as a final deliverable next year — all without rebuilding. You own the visibility timeline.
What makes the tiers possible
The platform capabilities your enterprise actually depends on.
Every tier above is grounded in the same platform foundation — capabilities you can hold us accountable to, in writing, in your procurement document.
🔒
Confidential Computing
An extra security measure that goes beyond industry standard. Most enterprise platforms encrypt data at rest (in storage) and in transit (over the network). MAGNET adds a third leg: encrypted during computation itself — your data and models stay protected inside hardware-backed enclaves even while they're being used. Invisible to the cloud provider, the operating system, and HydroSimulatics. Your data sovereignty is structural, not contractual.
👥
Live Collaborative Modeling
Shared simulation state across your global team. Field staff, office team, external reviewer, international partner — all inside the same working session. Not Google Docs for hydrology — live simulation state.
🌐
Open Data Integration
Standard protocols (WMS, WFS, WCS, OGC API, ArcGIS REST) connect MAGNET to your existing data infrastructure. Bring your GeoServer node, your monitoring database, your lab system — they stay on your infrastructure.
📄
AI-Generated Reports
Publish a model → get a professional technical report. Assumptions documented, parameters cited, results interpreted. Executive, technical, and public formats. The report writes itself because MAGNET sees inside your actual model.
🔗
One-Click Model Adoption
Found a relevant model — yours or a colleague's? Load it into your session in one click. Fork it, adapt it, extend it. The barrier between "I saw this model" and "I'm working with this model" disappears. Knowledge compounds across your portfolio.
⚙️
Five Specialized Platforms
IGW-NET (groundwater), SwaNET (watersheds), StormNET (urban hydrology), ConduitNET (pressurized networks), DataNET (federated data). One unified environment — five engineering depths. Use one, use all.
This is not theory
Real deployments. Real numbers.
Two case studies, two scales, same approach: replace site-by-site contracting with a unified MAGNET deployment. Both deliver the network effect — at very different orders of magnitude.
The path from inquiry to deployment
How we engage. From first call to confident launch.
Enterprise procurement has its own rhythm. We respect that. Here's the path most successful deployments follow — typically 4–12 weeks from first call to operational pilot, depending on the tier and your organization's procurement timeline.
1
30-min call
Define Goals
What does your network actually look like? What work is currently being re-done? Where is the highest-value pilot? We listen first, recommend second.
2
1–2 weeks
Scope Pilot
Pick 2–3 representative sites for an initial deployment. Define success criteria. Identify data sources to integrate. Confirm tier and scope.
3
4–10 weeks
Build Together
Iterative, transparent deployment. Your team participates from day one. Branded observatory stands up. Pre-calibrated models validate against your data. Training begins.
4
Ongoing
Confident Launch
Pilot proves the network effect. Expand across the enterprise as ROI confirms. HydroSimulatics partnership continues — through expansion, calibration refresh, and new capability rollout.
Let's talk about your network.
Schedule a 30-minute executive briefing to explore whether a MAGNET deployment fits your organization. We'll show you the platform live, walk through a relevant case study, and sketch what a pilot in your environment could look like. No commitment — just a clear conversation about the math.
Or email us directly at enterprise@magnet4water.com — typical response within one business day.
One platform. Hundreds of sites. Consistent methodology. Growing intelligence.
The status quo isn't free — it's just unbilled. The network effect isn't speculative — it's measured. The path forward isn't complicated — it's a 30-minute call.
For the broader strategic argument — why this moment, why both corporate and government leaders face the same structural challenge — read The Inflection Point →
Turn Any Location
on Earth into a
Working Groundwater Model
in Minutes.
Your local data refines the global base model. Sometimes 90% of the work is already done.
Draw a box. See what's already there.
A few keystrokes. Your base model assembles itself:
terrain (DEM) · bedrock topography · recharge · hydraulic conductivity · rivers, lakes, seeps
— all extracted automatically from open data, at the resolution your box demands.
Then you take over.
Refine with your data, customize for your question, simulate, steer.
See IGW-NET in action.
Six dimensions of groundwater modeling — recorded sessions running on real basins. Pick a category and watch.
Modeling anywhere · Multiscale flow systems · Risk-based decisions under uncertainty · Contamination & cleanup · Sustainable management · 3D visualization
What makes IGW-NET different.
📐
Grid-independent conceptual model
Wells, rivers, boundaries defined in real-world coordinates. Change resolution from 500m to 5m — features auto-remap. Dynamic aggregation when the grid is coarser than the data (15M+ wells, fine LiDAR streams, dense lake networks — their cumulative effect on regional water budget survives even when individual features can't be resolved); interpolation when finer (sparse regional features fill in onto nested child grids). This is what lets hierarchical nesting and multi-resolution Monte Carlo actually work.
🏔️
Drainage as solution, not input
Drainage networks emerge from the physics — not prescribed as boundaries. At LiDAR resolution, this resolves rivers AND seeps, wetlands, and fens — features that conventionally require expensive hand-mapping at every project. They emerge from the model itself. Scientifically correct, and fails gracefully.
🎬
In-situ streaming visualization
Visualization at the moment of computation. Plan view, cross-section, and 3D — synchronized at every time step.
🎛️
Human in the loop
Steer the model as it runs — conceptual, numerical, visual. Change boundaries, properties, sources; add a plume; swap solvers — the simulation responds without restarting.
🔄
Hierarchical nesting
Models inside models. Coarse regional context feeds fine-resolution detail — zoom in without losing the big picture.
🎲
Stochastic Monte Carlo
Generate heterogeneous aquifers from real borehole lithology. Run 1,000 realizations — memory stays constant.
Built on shoulders. Built to compound.
Standing on the shoulders of giants.
IGW-NET doesn’t reinvent the engine, generate the data, or build the network. It stands on three foundations decades of community work has produced — and connects them in a way that wasn’t possible before.
🔬 Community
Science
USGS MODFLOW family — the gold-standard open-source 3D groundwater modeling engines for flow, contaminant transport, particle tracking, and stochastic heterogeneity. Refined for decades by USGS and the international community. Taught in every hydrogeology program worldwide.
🗺️ Community
Data
USGS national water monitoring (well records, water-level observations). State Geological Surveys (well logs, lithology, hydrogeologic frameworks). Multi-resolution US and global terrain. National stream networks (US hydrography). Detailed and broad-scale US soils. US climate records and recharge forcing. Satellite groundwater storage change. International groundwater monitoring.
🌐 Community
Network
The Internet itself — the data lives there. Standard web data services (WMS/WFS/WCS) for federated data exchange across agency portals. Google Maps API for global base mapping. Cloud computing + real-time streaming 3D rendering (WebGL + VTK) make Interactive Groundwater possible in the browser — the kind of 3D groundwater modeling that previously required specialized desktop software.
🛡️Cloud security · TLS 1.3 in transit · AES-256 at rest · enforced 2FA · audit logging · three key-management modes (Platform / Customer / Organization) ·
Enterprise: hardware-enforced confidential computing (Intel TDX / AMD SEV-SNP TEEs) ·
See Security & Trust →
Water-resources sustainability transformation requires water-resources digital transformation. IGW-NET puts industry-standard engines, standardized data, and the digital network together — the way they were meant to be used.
Calibration moves into the live loop.
Conventional calibration is a phase — run, export, plot, adjust, rerun. IGW-NET puts it inside the live loop. Two fundamentally different observation paradigms feed it, and integrating both is what makes calibrate-anywhere real. Static water levels from drillers' records blanket the world — noisy as individual measurements, but many noisy measurements beat a few precise ones for resolving regional spatial pattern. Live monitoring networks add the precision of real time at sentinel sites — historical and live time series, pulled automatically into the comparison while the simulation runs.
📍
Water wells · blanket the world
15M+ water wells, where they were drilled
Practical observations from drillers' records — fundamentally different from traditional monitoring wells. Where water wells have been drilled, the data exists. Every US state and every Canadian province in the pre-integrated base (Michigan alone holds 800K+ records); static water levels, lithologies, and groundwater quality attach where state agencies provide them. Coverage isn't everywhere yet — not every state provides SWL data today — but it continuously expands through DataNET, and the principle generalizes as records become available globally. Lots of noisy data beats a few precise measurements for regional-scale pattern.
📡
Temporal · live API
National sensor networks, live-linked
Direct API into USGS National Water Information System (US) and Government of Canada monitoring well networks (Canada) — historical records and live time series at sentinel sites, pulled automatically into the comparison view. Where stations exist, the temporal pattern is fit on the fly. Hydrographs of modeled vs. observed update as the simulation advances.
What IGW-NET makes possible, end-to-end.
IGW-NET runs the entire groundwater workflow as one live system. Draw a domain anywhere — the geology, recharge, and drainage are already there at the right scale. Steer the simulation while it runs: nest a finer model around your site of interest, add a contamination source, calibrate against live well and sensor data, enable probabilistic realizations. The regional, subregional, and site models all run together, coupled live at their boundaries. Flow, transport, and water quality stream simultaneously across every realization. The plume becomes a fan of plumes; the breakthrough becomes a confidence band.
This is not faster groundwater modeling — it restructures the workflow itself. Probabilistic, time-resolved, 3D simulation across regional and site scales, on current data, with statistics and visualization streaming continuously alongside the solver. The expert is in the loop, not at the end of it.
Where IGW-NET sits in the family. Groundwater is 3D, time-resolved, and uncertainty-rich, so the live computational loop runs at the time-step level — you watch h(t) evolve while editing parameters. For watershed (SwaNET), urban stormwater (StormNET), water distribution (ConduitNET), and data fusion (DataNET), the same architectural principles produce coarser-grained continuous loops — between scenarios, design alternatives, and configurations. Same architecture. Different loop granularity. Groundwater is the most fine-grained case.
A computational steering system.
IGW-NET is not just a model that runs — it is a computational steering system. While the simulation streams forward, the user steers. Two decisions in particular: which solver, and where the recharge comes from. Both are steering surfaces, not configuration files.
Two engines. One workflow.
IGW for speed and exploration — solve equations in real time, stream results as a movie, test ideas at the speed of thought. MODFLOW 6 for regulatory validation — the industry standard, USGS-maintained, accepted by every agency worldwide. Same conceptual model. Same grid. Different solver. Switch with one click.
Three recharge sources. One workflow.
IGW-NET produces a complete groundwater solution from the base — at any given time, you have a working groundwater model with preprocessed recharge, geology, drainage, and hydraulic properties all in place. Within that complete solution you evaluate, refine, customize — including, when the question demands it, how the recharge itself is sourced.
The base ships with preprocessed long-term recharge — USGS and other agency rasters, calibrated against stream baseflow. For most groundwater questions — steady-state aquifer modeling, long-term-mean sustainability, regional resource assessment — this is what the question requires. Decades of careful statistical work already in the raster.
When local process detail matters — different soil, land cover, or climate scenarios than the static rasters reflect — IGW-NET's built-in INFIL model produces a process-based recharge boundary from local data. INFIL is a narrow USGS watershed model focused on recharge: complete enough to close the boundary, fast enough to stay inside the iteration loop, simple enough to keep the user focused on the groundwater problem.
For the deepest sustainability questions — what happens to the aquifer under decades of climate and land-use change — recharge itself has to evolve. Coupled SwaNET-IGW-NET resolves this. SwaNET reflects climate variability and land-use change in the surface water balance — different rainfall regimes, expanding impervious surfaces, shifting crops and irrigation — and computes the consequences for runoff, infiltration, and ultimately the recharge that reaches the aquifer. IGW-NET applies that recharge field with head-driven physics: cones of depression that develop one well at a time, the gradual capture-curve baseflow signature, wetlands that emerge where head meets surface and shrink as pumping grows.
Most groundwater work runs on the base. INFIL and coupled SwaNET are there when the question demands more.
The three sources, at a glance
🗺️
Base default
Preprocessed rasters
USGS and other agency products, calibrated against stream baseflow. Often what the question requires.
🌧️
Built-in process
INFIL model
USGS process-based recharge model, embedded in IGW-NET. When local detail matters.
🌊
Coupled SwaNET
Sustainability questions
Full basin water balance under climate & land-use change. When recharge itself must evolve.
Subsurface truth receives surface truth — the handshake is automatic.
What you can investigate.
From regional aquifer assessment to site-scale contamination, from sustainable yield to remediation design — all in one platform, across scales, with real-time feedback.
💧
Aquifer Dynamics
Flow, storage, water balance, sustainable yield
☠️
Contamination
Plume migration, fate & transport, PFAS, remediation
🛡️
Protection
Source water, wellhead protection, vulnerability
🌡️
Climate & Change
Withdrawal impacts, land use, saltwater intrusion
"None of the available groundwater and contaminant modeling systems has the capability of real-time visualization and simulations."
— George Yeh, Former Provost Professor, University of Central Florida
🔭
Publish to the Observatory
Publish your groundwater model to the global Observatory network. AI-generated report, USGS sensor overlay, one-click adoption by others. Your living portfolio.
Explore the Observatory
See how MAGNET4WATER solves water problems across sectors and continents — from Superfund sites to national geological surveys.
Browse Case Studies
🎓
Teaching with IGW-NET
Groundwater becomes visible.
The subsurface is the hardest topic in water education precisely because students can't see it. IGW-NET changes that. Students watch cones of depression develop, plumes advance, and capture zones shift as they work — observing the subsurface the way hydrogeologists reason about it, not just computing head values on a worksheet.
The platform enables teaching patterns that were previously impractical: design competitions with real cost feedback, live-thinking lectures where students predict and the model responds, and a capstone monitoring and remediation competition in which the plume is hidden from view — students must characterize an invisible contaminated aquifer under budget constraints, then design cleanup based on what they learn. The full professional workflow of a hydrogeologist, compressed into a semester, with the professor holding the ground truth no real-world investigator has ever had.
Ready to model groundwater? IGW-NET runs in your browser — free tier available.
Want the deeper picture?
Read the full IGW-NET overview — features, capabilities, lifecycle, and how it fits the MAGNET4WATER ecosystem.
Read the full IGW-NET overview →
Turn Any Location
on Earth into a
Working Watershed Model
in Minutes.
The world's watershed model is ready when you arrive — typically under 10 minutes. You focus on what matters.
Draw a box. Your watershed assembles itself.
What assembles
One action from you. Everything else builds automatically.
🗺️
Terrain & drainage
DEM, streams, outlets, and subwatershed boundaries — all resolved from one terrain analysis. Multi-resolution US terrain (USGS 3DEP, 10m seamless, finer where LiDAR is collected); global terrain at 30–1000m (SRTM, ASTER; next-generation 30m global terrain coming next release). Working resolution scales with basin size — 30/90/300m typical; 10m for small watersheds; 1000m for very large basins and continental drainage. Finer LiDAR detail doesn’t improve subwatershed flux accuracy at basin scale.
🌿
Land use & soil
Assembled with hydraulic lookup tables for runoff, infiltration, and water-holding capacity. US land cover at 30m (NLCD); global land cover at 30/90/300/1000m (via DataNET, direct integration coming next release). Detailed and broad-scale US soils (SSURGO + STATSGO2 gap-fill); global soils at 300m (FAO, with 90m subsets) — Hydrologic Soil Group plus runoff and infiltration parameters.
⛅
Climate forcing
Precipitation and temperature drive the water balance. US climate (PRISM, 4km historical, live-linked) for continuous simulation. Global climate (CFSR, 38km daily, 1979–2014); climate-change projections (CMIP6 via Copernicus) — SwaNET’s pathway for climate change studies. Higher-resolution US precipitation and rain-gauge time series coming next release. SwaNET does not use IDF data (SWAT does not handle event-based storms).
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HRUs configured
Land use × soil × slope grouped into Hydrologic Response Units inside each subwatershed. Heterogeneity preserved without grid refinement.
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Intelligent defaults
Curve Number, channel routing, infiltration, evapotranspiration, baseflow — calibrated starting values, ready to refine for your basin.
What you see
Three synchronized views of the same model — readable the moment the run completes.
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Signature (Sankey diagram)
The watershed's hydrologic fingerprint — in one image. The signature of its dynamics and health.
Process topology: which water processes are at work and how they feed into each other.
Interrelationships: which processes dominate, which are marginal.
Cumulative water balance: every drop accounted for, from where it fell to where it went.
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Time (hydrographs)
Streamflow at every outlet. Where USGS gauges sit near outlets, observed time series is overlaid on the fly — model vs. measurements, side by side, the moment the run completes.
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Space (maps & 3D)
Land use, soil, runoff, ET, recharge, sediment, nutrients, baseflow — as 2D maps or as live textures on an interactive 3D DEM of the watershed.
Built on shoulders. Built to compound.
SWAT (USDA) · USGS · NOAA · NASA · ESA · FAO
decades of work by national agencies and the broader scientific community
Assembled once for everyone, refined locally for you.
The conventional weeks and months of data wrangling are gone.
You arrive at a model that already shows you what matters.
The hydrographs reveal regime — and where USGS gauges exist, they show fit. The maps reveal where the action is. The Sankey ties it all together.
What you do
Then you act — anywhere in the model.
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Downstream (act)
Calibrate, test scenarios, refine, assess soil and water.
Feedback within minutes.
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Upstream (reshape)
Reach into the fabric — DEM resolution, land use, soil, HRUs, the delineated watershed itself.
Minutes more — the fabric itself is rebuilt.
Both keep you inside one continuous iteration loop — scenario after scenario, hypothesis after hypothesis. SwaNET does the heavy lifting; you stay focused on what matters.
The Sankey is what makes the loop intelligent — it shows which processes dominate, where refinement would change something, and where it wouldn't. Understand the Sankey before you calibrate. Refine what matters.
The base enables. It never constrains.
See SwaNET in action.
Six dimensions of watershed modeling — recorded sessions running on real basins. Pick a category and watch.
What makes SwaNET unique · Built fresh or imported from SWAT · United States · Worldwide · Coupled surface/subsurface with IGW-NET
What makes SwaNET different.
The architectural commitments that shape what SwaNET does, how it scales, and where it earns trust.
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Natural cells. Exact between. Tractable at scale.
Every watershed model divides into cells. Accuracy depends on quantifying the flux across cell boundaries — and that flux is exactly what the Saint-Venant equations of conventional grid-based watershed solvers exist to handle. SwaNET solves the flux problem differently: it uses natural cells — subwatersheds delineated from terrain. The boundaries are drainage divides; the overland flux across them is exactly zero by construction. Solved by geometry, not by numerics.
Modern high-resolution DEMs make this work everywhere — accurate subwatersheds delineated worldwide. No Saint-Venant to discretize, no stability constraints, no tiny cells or short time steps. Computation at basin scale stays tractable. Heterogeneity inside each subwatershed is preserved through HRUs (land use × soil × slope). This architecture is why SWAT became the global standard for watershed-scale modeling.
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Built on USDA SWAT.
The watershed-modeling engine adopted worldwide — by USDA, EPA, FAO, and watershed agencies in dozens of countries. The same engine the regulators expect, wrapped in a real-time computational steering system.
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The iteration loop lives in the platform.
No export to a separate tool. No re-import. Change a BMP, change land use, refine the DEM — the Sankey reorganizes, the water balance updates, the USGS comparison re-runs. Every iteration closes in the same environment.
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Start coarse. Refine only where it matters.
Refinement works like in any watershed model — higher-resolution DEM, lower stream-delineation threshold, more subwatersheds, more compute. The principle in SwaNET is when. Because the flux between subwatersheds is exact at any resolution, finer DEMs don't improve flux accuracy. What they do improve is the delineation itself — where the subwatershed boundaries get drawn, and the slope and stream-network structure inside each one. So begin coarse: 90m for typical watersheds, 30m where complexity warrants, 1000m for continental scale.
The initial solution shows you which subwatersheds drive the response and where finer detail would change something. Refinement becomes another dimension of steering — guided by the initial run, not by a guess. Everything has a purpose; nothing is finer than the question requires.
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Natural cells = computational cells = management cells.
Subwatersheds are how nature drains, how SwaNET computes, and how watershed management actually operates. Conservation districts plan BMPs by subwatershed. Regulators assess loads by subwatershed. Water agencies monitor flow at subwatershed outlets. SwaNET's computational unit is the same. No aggregation. No reprojection. No translation step. The model speaks the language of the people who use it.
Built on shoulders. Built to compound.
Standing on the shoulders of giants.
SwaNET doesn’t reinvent the engine, generate the data, or build the network. It stands on three foundations decades of community work has produced — and connects them in a way that wasn’t possible before.
🔬 Community
Science
USDA SWAT — the open-source watershed-modeling engine refined since the early 1990s; adopted globally by USDA, EPA, FAO, and watershed agencies in dozens of countries. The de-facto standard for watershed-scale water balance, sediment, and nutrient modeling.
🗺️ Community
Data
Multi-resolution US and global terrain. US and global land cover. Detailed and broad-scale US soils; global soils (FAO). US climate records and climate-change projections. Streamgage observations for calibration (USGS in the US; Water Survey of Canada). North America today; international gauge networks expanding.
🌐 Community
Network
The Internet itself — the data lives there. Standard web data services (WMS/WFS/WCS) and modern data APIs (USGS WaterServices, MSC GeoMet) for federated data exchange. Google Maps API for global base mapping. Cloud computing + real-time browser simulation + VTK scientific visualization make platform-scale watershed modeling possible without local install.
🛡️Cloud security · TLS 1.3 in transit · AES-256 at rest · enforced 2FA · audit logging · three key-management modes (Platform / Customer / Organization) ·
Enterprise: hardware-enforced confidential computing (Intel TDX / AMD SEV-SNP TEEs) ·
See Security & Trust →
Water-resources sustainability transformation requires water-resources digital transformation. SwaNET puts industry-standard engines, standardized data, and the digital network together — the way they were meant to be used.
Coupled to IGW-NET.
SwaNET sees the basin. IGW-NET sees the aquifer.
Recharge fields pass directly from SwaNET to IGW-NET — the same automatic handshake, the same watershed boundary, the same iteration loop. Your SwaNET model's surface water balance becomes IGW-NET's subsurface input. Rerun IGW-NET, and the aquifer responds to today's surface dynamics, not yesterday's assumptions.
Coupled, the two platforms resolve sustainability questions neither answers alone. SwaNET reflects climate and land-use change in the surface water balance — different rainfall regimes, expanding impervious surfaces, shifting crops and irrigation — and computes the consequences for runoff, infiltration, and ultimately the recharge that reaches the aquifer. IGW-NET applies that recharge with the wells, withdrawals, and head-driven physics of the aquifer itself. Together they resolve ecosystem-scale outcomes — cones of depression that fail one well at a time, baseflow depletion that follows the gradual capture-curve signature, wetlands that emerge where head meets surface and shrink as pumping grows. Outcomes the surface water balance alone cannot produce.
Surface truth flows into subsurface truth — the handshake is automatic.
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Publish to the Observatory
Publish your watershed model to the global Observatory network. AI-generated report, USGS sensor overlay, one-click adoption by others. Your living portfolio.
Explore the Observatory
See how MAGNET4WATER solves water problems across sectors and continents — from Superfund sites to national geological surveys.
Browse Case Studies
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Teaching with SwaNET
Watershed engineering as iterative design, not data preparation.
Watershed teaching has always been bottlenecked by data. A single analysis used to require weeks of GIS setup before any student saw a meaningful result. SwaNET inverts this: a working model in under ten minutes, worldwide, with real terrain, soil, land use, and climate data. What changes pedagogically is not that analysis is faster — it's that students can now iterate through dozens of scenarios in a single session, developing watershed intuition no textbook can build.
The platform enables teaching patterns that were previously impractical: the ten-minute watershed setup, land-use and climate scenario competitions, and the capstone watershed restoration design competition in which students transform a severely degraded watershed by targeting the critical source areas producing 60–80% of the load — and see dramatic, visible improvement as the Sankey water balance reorganizes in real time.
Ready to build a watershed model? SwaNET runs in your browser — free tier available.
Want the deeper picture?
Read the full SwaNET overview — features, capabilities, lifecycle, and how it fits the MAGNET4WATER ecosystem.
Read the full SwaNET overview →
