Environment & Research

We use downscaled climate projections to model future changes in rainfall, temperature, and evaporation. These drive hydrological models that predict changes in streamflow, groundwater recharge, and drought frequency. Results help planners prepare for conditions outside historical experience.

Environmental flows are the water quantity and timing needed to sustain healthy river ecosystems. We assess requirements using hydrological methods (percentage of natural flow) and ecological methods (habitat needs of key species). Environmental flows are increasingly required in water allocation decisions.

Flood forecasting integrates real-time rainfall data, river level monitoring, and hydrological models to predict flood peaks hours to days in advance. Warnings are issued when predicted levels exceed thresholds. We design forecasting systems and train operators for effective flood early warning.

A water quality index combines multiple parameters (DO, BOD, pH, nutrients, etc.) into a single score for easy communication. We calculate indices using standard methods like the National Sanitation Foundation WQI or develop custom indices for specific applications. Indices enable tracking water quality trends over time and across locations.

Wetland monitoring includes hydrology (water levels, flow patterns), water quality, vegetation mapping, and biodiversity surveys. We use remote sensing to track vegetation changes over time and field sampling for detailed assessment. Monitoring reveals impacts of development, climate change, or restoration efforts.

Drought monitoring tracks rainfall deficits, streamflow, groundwater levels, and vegetation stress to assess drought conditions. Early warning systems combine these indicators with forecasts to predict developing droughts. We help agencies establish monitoring networks and response triggers.

Satellites provide data on water bodies, soil moisture, vegetation water stress, snow cover, and even groundwater storage changes. We process satellite imagery to map water resources across large areas, detect changes over time, and fill gaps where ground monitoring is limited.

Many basins lack streamflow measurements. We estimate flows using rainfall-runoff models calibrated from similar gauged basins, regionalization techniques, and satellite-derived data. These estimates support water resource planning in data-scarce regions common across India.

Monitoring program design defines what to measure, where, how often, and with what methods to answer specific questions cost-effectively. We consider statistical power needed to detect changes, practical constraints, and long-term sustainability. Well-designed programs provide reliable data for decades of adaptive management.

In three places, all of them about the data rather than about the hydrology. Downscaling takes global climate model output, which is far too coarse to say anything about a single catchment, and learns the statistical relationship between those large-scale fields and local station observations, so a projection can be expressed at a scale a planner can act on. Gap-filling reconstructs the missing stretches that every long gauge record contains, using neighbouring stations and satellite-derived signals, which is often the difference between a usable record and a discarded one. Classification of satellite imagery maps surface water extent, wetland boundaries and land cover change over areas too large to survey on foot. The rainfall-runoff and routing stays with physical models, because adaptation work asks what happens under conditions no historical record contains, and a model that has only ever seen the past has no basis for answering that.