Storage & inflow
Track changing reservoir, river and canal conditions over time.
Water Agent
Basin-scale intelligence
Track water stress across a basin, season by season.
Understand how surface water, rainfall, drought, land use and vegetation interact across a basin, then turn physical change into action.
Models: availableAgent: in development
Questions
Four questions for water managers.
Each uses satellite, weather and land-use data across the basin.
Demand
Estimate irrigated area and water demand across a basin or portfolio.
Stress & recharge
Combine soil moisture, groundwater context, rainfall and drought signals.
Allocation risk
Surface where shortage may affect communities, industry or agricultural supply.
Proven basin-scale work
Narmada basin: how tree cover and water extent change together.
Cropin applied Sentinel imagery, weather signals and geospatial AI to monitor surface-water extent, tree density and land-use change across 12 districts in Madhya Pradesh.
What Cropin connected
Water extent alone can mislead.
The analysis combined NDWI, NDVI, precipitation, drought and tree-density signals so changing water conditions could be interpreted in context, not treated as a single satellite observation.
Decision value
Find where interventions are working, and where they are not.
The model identified positive relationships between tree-density change and water-body area in Jabalpur, Seoni, Narsinghpur and Mandla, helping direct monitoring and policy attention.
STUDY-SPECIFIC RESULT · ASSOCIATION, NOT A UNIVERSAL CAUSAL CLAIM · OUTCOMES DEPEND ON WEATHER, DROUGHT, LAND USE AND IMPLEMENTATION CONTEXT
Water intelligence for Food-Ag.
From crop-level stress to regional drought, Cropin connects satellite, climate and farm intelligence to show where water is constraining crop performance, and which sourcing areas need attention.
Food-Ag is one proven application. The same intelligence architecture extends to basins, utilities and water-dependent industry.MODEL OUTPUTS · CROPIN CLOUDSCROLL OR SELECT A VIEW
See where crops are under water stress.
Classify no, mild, moderate and severe stress across fields, quantify affected area and track how exposure changes through the season.
Track moisture deficit across a sourcing region with SPEI.
Use observed and projected SPEI conditions to understand moisture deficit across an agricultural region and anticipate where production risk is building.
Move from a regional signal to the exposed crop.
Filter drought intelligence to a crop, in this example, table grapes, to identify affected production areas and prioritize agronomy, irrigation or sourcing action.
Measure the physical signal
Water stress, soil moisture, rainfall and drought conditions.
Connect it to crop exposure
Crop, field, region, season and contracted-supply context.
Prioritize the response
Agronomy, irrigation, field verification and sourcing decisions.
Water system intelligence
Read water supply and demand as one connected system.
Combine reservoir storage, river and canal flow, groundwater, irrigated area, crop water demand, soil moisture and recharge to anticipate pressure before allocation decisions become urgent.
- Reservoir and storage
- River and canal flow
- Irrigated area and demand
- Soil moisture and recharge
Scope
This concept extends Cropin’s existing land, crop and climate intelligence to water systems. It does not replace utility control systems or hydrological field instrumentation.