Predictive Groundwater Intelligence

Quantify the capital risk
beneath your operations.

AquaRisk transforms groundwater monitoring data into probabilistic risk intelligence — giving large-scale operators and asset managers the clarity to act before risk materializes.

2,000+Monte Carlo simulations
4Stress-tested scenarios
24 moForecast horizon
ACEI™Proprietary risk index
Risk Intelligence Framework

Three metrics that define your exposure.

Groundwater risk is not a geological abstraction — it is a capital allocation problem. AquaRisk quantifies it in terms that boards can act on.

Probability of Operational Impairment

Likelihood that groundwater levels breach critical thresholds within a defined horizon, expressed as exceedance probability across 2,000 simulations.

Monte Carlo engine

Water Value at Risk (W-VaR)

Maximum expected financial loss attributable to groundwater stress under adverse scenarios, modeled at the 95th percentile confidence interval.

Downside exposure metric

Asset Capital Exposure Index (ACEI™)

Proprietary composite index combining exceedance probability, decline rate, proximity to threshold, and forecast volatility into a single 0–100 score.

Proprietary AquaRisk index
Interactive Demo

See the platform in action.

Live simulation with real model outputs. No login required — explore the full risk dashboard below.

app.aquarisk.io — Demo Mode
Advanced Plan
Navigation
Dashboard
My Wells
Data Entry
Account
Well
GW-01 — North Field
GW-02 — South Basin
GW-03 — East Sector
Scenario
Baseline Operating
Climatic Stress
Production Expansion
Sustainability Strategy
Well GW-01 · Baseline Operating Scenario
Current Level
28.4 m
Exceedance Prob.
34.2%
Risk Level
Moderate
Threshold Cross
18.3 mo
ACEI™
52.4 /100
Groundwater Forecast — 24 Month Horizon
Threshold
Historical
Forecast
P5–P95
Threshold

Simulated data for demonstration. Access the full platform with your own well data.

Platform Capabilities

From raw monitoring data
to strategic intelligence.

A ten-stage analytical pipeline that transforms well-level time series into probabilistic risk intelligence and capital optimization guidance.

01

Multi-Model Predictive Engine

Three parallel forecasting approaches combined via weighted ensemble for robust, bias-corrected projections.

02

Monte Carlo Uncertainty Quantification

2,000 AR(1)-correlated simulations per asset generating P5–P95 bands and probabilistic breach timelines.

03

Scenario Stress Testing

Four defined scenarios — Baseline, Climatic Stress, Production Expansion, Sustainability — for comparative risk ranking.

04

Pumping Optimization Solver

Determines the minimum pumping reduction required to achieve a target risk level with quantified confidence.

05

Portfolio-Level ACEI™ Aggregation

Scores aggregated across all monitored assets providing a single portfolio exposure metric for executive oversight.

06

Executive PDF Reporting

Automated institutional-grade reports with key metrics, visualizations, and structured summaries ready for board presentation.

How It Works

Intelligence in four steps.

01

Upload or enter your monitoring data

Submit historical groundwater level data directly via our interactive entry form or upload a CSV. No proprietary sensor required.

02

The engine runs your risk model

Our multi-model ensemble and Monte Carlo engine processes your data through all four scenarios, generating probabilistic forecasts and ACEI™ scores within minutes.

03

Review your risk intelligence dashboard

Explore scenario comparisons, uncertainty bands, threshold crossing probabilities, and portfolio-level exposure in a clean executive interface.

04

Act on structured recommendations

Each ACEI™ category carries a specific operational advisory with quantified pumping optimization guidance — from monitoring to immediate capital review.

Model Validation

We tested the model
against a drought it
never saw coming.

We trained AquaRisk exclusively on 10 years of pre-drought data from a Kaweah Subbasin well in Tulare County, California — then asked it to forecast what would happen during the 2020–2021 drought resurgence. The model had zero knowledge of what was coming.

0.43 m
Mean Absolute Error
Over 24-month blind forecast
0.999
Forecast Correlation
Trajectory match vs. actual
18+ mo
Early Warning Lead Time
Before threshold approach
100%
Actual Within P5–P95
Calibrated uncertainty bands
Download Full Validation Report (PDF) View CASGEM Source Data
Kaweah Subbasin · Tulare County, CA · CASGEM Public Data
Threshold Training 2010–2019 Forecast (blind) ▲ Actual CASGEM
Historical AquaRisk Forecast CASGEM Actual
10y
Model trained on 2010–2019
10 years of semi-annual CASGEM measurements. No drought data included. Model learns the aquifer's baseline behavior.
AquaRisk generates 24-month blind forecast
Drought scenario applied. 2,000 Monte Carlo simulations run. Model flags 18+ months of early warning before threshold approach.
Actual 2020–2021 measurements released
MAE = 0.43 m. Correlation = 0.999. All actual measurements within the P5–P95 uncertainty band. Direction correct.
Pricing

Structured for serious operators.

Subscription plans designed for agricultural enterprises, industrial operators, and institutional asset managers with material groundwater exposure.

Professional
$499 / month
Minimum commitment: 3 months
  • Up to 2 monitored wells
  • 24-month forecast horizon
  • Groundwater level analysis
  • Automated PDF report
  • Email support
Enterprise
From $1,800 / month
Minimum commitment: 12 months
  • Up to 5 monitored wells
  • Portfolio-level ACEI™
  • Full Monte Carlo modeling
  • Excel data export
  • Strategic advisory sessions
  • Dedicated support & SLA
Get Started

Your groundwater risk is quantifiable.
Now it's visible.

Join operators who have moved from passive monitoring to active, intelligence-driven groundwater risk management.