GOATAI
Systems Intelligence
goatai.io/climate/varuna
Water Intelligence Engine
Cascading hazard analysis for groundwater stress, contamination propagation, and coastal salinity risk. Physics-informed. Fully auditable. India-native.
Wells Monitored
13,506
National
Coverage
India
CGWB 2022
Approach
CBE
Rule-based
Platform
Live
Deployed
Capabilities
Each module maps to a specific operational problem. The modules share a common physics-informed reasoning layer — outputs from one feed boundary conditions for the next.
Problem
No unified visibility into national groundwater quality and contamination patterns across India's 13,506 monitored wells.
Solution
Interactive WQI map with spatial contaminant tracking, coverage audit, and data quality validation layer.
Problem
Pre-filtered or biased datasets conceal real contamination signals and introduce systematic error into downstream analysis.
Solution
CBE-based statistical rigor (Hounslow 1995 standard, <5% threshold) flags samples with ionic imbalance before any inference runs.
Problem
Smart city construction at Dholera requires water security assessment as coastal aquifers face rising salinity pressure.
Solution
Distance-to-coast + EC + Cl/TH ratio composite scoring. Physics-informed sampling plan identifies where risk is highest and data is thinnest.
Problem
Flood intelligence is incomplete without modeling how inundation events cascade into aquifer recharge dynamics.
Solution
Inundation zone mapping coupled with aquifer recharge event analysis — flood peak triggers recharge boundary condition update.
Problem
Sparse sensor networks leave critical blind spots. Statistical sampling is insufficient for heterogeneous aquifer systems.
Solution
IDW interpolation + advection-diffusion transport physics + greedy uncertainty maximization selects optimal next-well locations.
Data & Methodology
Every score in Varuna is traceable to its source data and formula. Institutional buyers and regulators can audit the full inference chain.
Data Source
CGWB 2022Central Groundwater Board 2022 national survey. 13,506 wells across all states. Data quality varies by region — the CBE audit systematically identifies and quarantines unreliable samples before analysis proceeds.
Validation Standard
Hounslow 1995Charge Balance Error threshold of <5% is applied to all samples. Samples outside this range are flagged as statistically questionable. This prevents biased data from propagating through the risk scoring pipeline.
Risk Scoring
Rule-BasedComposite risk scores are computed using physics-grounded weighting: distance-to-coast, EC concentration, chloride/total hardness ratio, and WQI. No black-box ML. Every score is traceable to source data and formula.
Sampling Optimization
Physics + UncertaintyIDW spatial interpolation estimates contaminant fields from known sample points. Advection-diffusion physics models transport pathways. Greedy uncertainty maximization selects locations that reduce prediction variance most efficiently.
Validation methodology follows Hounslow (1995) ionic balance standards. Risk scoring formulas are documented in the CGWB 2022 audit preprint — available prior to EarthArXiv submission on request.
Request methodology docLive Platform
Explore the national groundwater audit, Dholera coastal risk scoring, and physics-informed sampling plan in the live deployment.
The live deployment includes the national WQI map, CBE audit layer, Dholera coastal salinity risk visualisation, floodplain coupling overlay, and physics-informed sampling plan.
Explore Varuna Platform →National Overview
13,506 well WQI map with contaminant filtering and state-level drill-down
Dholera Coastal
Salinity risk composite scoring with sampling plan output for the AOI
Floodplain Coupling
Inundation zone overlay with aquifer recharge event timeline
Systems Context
Varuna is the water module within GoatAI's larger systems intelligence platform. Each coupling below is a live interface — outputs from one domain become boundary conditions for the next.
Flood peak → inundation → soil saturation → aquifer recharge boundary update. Excess precipitation does not leave the system at the surface.
Earth-2 downscaled precipitation forecast (Phase 2) feeds as recharge boundary condition. 30-day climate forcing drives water table projections.
Power plants, irrigation networks, and smart cities draw from shared aquifer systems. Infrastructure stress propagates to groundwater availability timelines.
Steel plants, refineries, and thermal power require water security planning. Industrial contamination events trigger cascading WQI degradation downstream.
Partnership Pathways
Varuna is built for institutional credibility, commercial deployment, and research validation simultaneously. Choose your engagement model.
State Boards · NDMA · Utilities
Integrate Varuna into your state water stress monitoring framework. Dholera pilot (Phase 1 proposal submitted via Poornima College) demonstrates the coastal salinity workflow.
business@goatai.io
Start integration discussionRenewable · Real Estate · Industry
90-day pilot pathway for operational water intelligence. ReNew Power, Lodha Palava, and thermal plant operators are target deployment contexts for CSR, ESG, and operational risk.
Culturiq Research Pvt. Ltd.
Discuss pilot scopeIWMI · IIT Delhi · ICIMOD
Validate Varuna's forecasting across new regions and aquifer types. IWA SCED-2026 and RCRM 2026 abstracts are active credibility markers. Open methodology, open invitation.
business@goatai.io
Propose validation studyRoadmap
Ambitious but grounded. Each phase is gated on real validation — no timeline slips from overcommitting on features.
Phase 1
Current
CGWB 2022 national groundwater audit, CBE-based data validation, Dholera coastal salinity risk scoring, and floodplain-aquifer coupling prototype. Live at varuna.goatai.io.
Phase 2
Q3 2026
30-day precipitation-driven aquifer recharge forecast using NVIDIA Earth-2 downscaling. Climate forcing becomes a Varuna boundary condition for water table projections.
Phase 3
Q4 2026
Real-time sensor network integration with anomaly detection for contamination onset. Early warning when EC or ion concentrations deviate beyond safe thresholds.
Phase 4
2027
Full NVIDIA Omniverse integration for Dholera: 3D groundwater model with interactive scenario testing, coastal salinity propagation visualization, and infrastructure impact overlay.
Research & Publications
Varuna is grounded in peer-reviewed validation standards and active conference submissions. Open-source tools underpin the inference layer.
CGWB 2022 National Groundwater Audit
PreprintEarthArXiv — in preparation
Statistical audit and WQI analysis of India's 13,506-well national monitoring dataset. CBE-based validation, contaminant spatial analysis, and sampling plan methodology.
Watershed-to-Coast Hazard Cascade Framework
ConferenceIWA SCED-2026 — submitted
Cascading water systems analysis from upstream aquifer stress through floodplain coupling to coastal salinity intrusion.
RCRM 2026 — IIT Jammu
ConferenceJuly 2026
Water systems cascade reasoning under compound climate stress. Validation methodology for physics-informed groundwater inference.
wie-api
Open Sourcegithub.com/prabhat284/wie-api
Open-source Water Intelligence Engine — geospatial reasoning API powering Varuna's spatial analysis and sampling optimization.
github.com/prabhat284/wie-api ↗ATOM OSS SDK
Open Sourcegithub.com/culturiqai/atom-oss-sdk
Geospatial AI and multiphysics toolkit. Open development. Core infrastructure for Varuna's physics-informed inference layer.
github.com/culturiqai/atom-oss-sdk ↗Varuna — Water Intelligence Engine
National groundwater audit, coastal salinity risk, floodplain coupling, and physics-informed sampling plan — live and accessible now.
Partnership, research collaboration, or deployment inquiries: business@goatai.io
