Reservoirs provide water for irrigation, industrial use and hydropower generation in many parts of the country and their storage levels depend on rainfall in catchment areas, among other factors.
Advance warning about likely deficit in reservoir storage could help in water management during droughts.
But, at present, there is no such system available.
Researchers at the Indian Institute of Technology, Gandhinagar, have developed a statistical framework which they say “provides the first assessment of reservoir storage anomaly forecast at 1‐ to 3‐month lead for the dry season that can be valuable for decision‐making.
The framework is based several parameters – observed accumulated rainfall, standardized precipitation index (SPI), standardized precipitation evapotranspiration index (SPEI), standardized stream flow index (SSI), and observed storage data.
For developing their model, researchers analyzed observed precipitation, air temperature, and data from catchment areas of 91 major reservoirs in the country, and developed a regression‐based statistical model to predict reservoir storage anomalies at three months lead.
Reservoirs in the country have considerable variation in terms of water surface area, storage capacity, command area and installed capacity to produce hydropower.
The total storage capacity of 91 major reservoirs is about 238.4 billion cubic meter.
Researchers have validated the model for reservoir levels 2002 onwards and have found that the model really works well.
This period has had dry, wet and normal monsoon years.
However they need to incorporate the information on the state of catchments of various reservoirs plus should also take into account the upstream and reservoir water use data to make the model more robust.
This is a ‘India Science Wire story; edited by Clean-Future Team