Frequently Asked Questions

Smart Bhujal builds digital twins for water: calibrated groundwater, flood and network models connected to your data, with the dashboards your team uses to decide. Founded by Dr. Jagadeesh Gaddam (PhD, IIT Tirupati), the team combines water science and software engineering to make water decisions data-driven.

A water digital twin is a calibrated model of your aquifer, river or network, kept current with the data you have, from monitoring wells and SCADA to satellite observations, and wrapped in the tools your team uses to decide. Where live sensors exist, we connect them. Where they do not yet, the twin starts from the data you have and updates as monitoring grows. The same kind of system is also called a water decision support system (DSS).

We build the four layers of a water digital twin, combining whichever a problem needs.

• Remote Sensing & AI: extracting water insights from satellite and geospatial data
• Numerical Modeling: simulating groundwater, surface water and networks (MODFLOW, HEC-RAS, EPANET)
• Software & AI Agents: custom web platforms that make models and data usable
• Monitoring & Sensors: field measurements that keep the picture current

GWPilot is our AI-powered groundwater intelligence platform, built on public CGWB data. It offers groundwater level analysis, geological context, trend insights and location-specific intelligence: an example of the Software & AI Agents layer, making groundwater data usable for decisions rather than leaving it locked in raw tables.

We work with established methods across the four layers of a water digital twin:

• Numerical modeling: MODFLOW (groundwater), HEC-RAS (surface water and floods), EPANET (water distribution networks)
• Remote sensing & AI applied to satellite and geospatial datasets
• Modern web stacks for the dashboards and software your team uses to decide
• Field monitoring and sensors to keep models grounded in current conditions

We build on established, peer-reviewed modeling methods and public datasets such as CGWB groundwater data, calibrate models against observed measurements, and pair them with field monitoring so the picture stays current. Reliability depends on the data and calibration available for each site, so we scope and validate every system to the conditions on the ground rather than quoting blanket figures.

We combine CGWB groundwater data, remote sensing and numerical models (MODFLOW) to map aquifers, analyze trends and test management scenarios, so recharge, abstraction and monitoring can be planned with evidence rather than guesswork, and reviewed through dashboards your team can use.

Yes. We pair hydrologic and hydraulic modeling (HEC-RAS) with remote sensing to simulate flows, map flood extents and evaluate interventions, delivered through dashboards that make the results usable for planning and response.

Yes. For irrigation, we combine remote sensing and field data to inform scheduling and allocation decisions. For water distribution networks, we use hydraulic modeling (EPANET) to analyze pressure, demand and losses, turning network data into decisions operators can act on.

Most engagements start with the water decision you need to make. We scope the right mix of the four layers of a water digital twin (remote sensing, modeling, software and monitoring), build against your data, and deliver a twin your team can keep using and extending, not a one-off report.

Yes. GWPilot, our groundwater intelligence platform, is free to use. It reflects our belief that better water decisions start with open access to data and analysis. For organizations that need a digital twin of their own aquifer, river or network, we build one across the four layers.

Yes. A digital twin stays useful only if it stays current, so we support the data, models and software over time (updates, monitoring integration and technical assistance) as your needs and datasets evolve.