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Floods in India
to be Avoided Using Fuzzy Logic
IF A washing
machine can figure out how dirty the laundry is, then it can
calculate how long it should wash, how much detergent to add
and how much water is needed. This is called the fuzzy logic
technology and it works on a simple "if-then" principle.
At present machines like air conditioners or microwave ovens
have fuzzy logic technology operating them. Researchers from
India have now suggested using fuzzy logic to improve dam
operations.
Experts attribute unprecedented floods,
like the one in Orissa last year, to a sudden release of water
from reservoirs (see 'The right level', Down To Earth, October
16-31, 2008). They blame this on lack of appropriate operational
policies for multi-purpose dams. During monsoons, water level
of the rivers is high and release of excess water from dams
exacerbates the problem.
A team of researchers suggested a system
to operate dams that uses fuzzy logic technology with artificial
intelligence which works like our nervous system. It converts
various signals like water level, expected inflow and expected
demand into a single input. The technology then takes the
input as "if" and predicts how much water to release
(output) as "then".
The team applied its model to the reservoir
across Ramganga river, a tributary of the Ganga. With a storage
capacity of 2,448 million cubic metre, the reservoir is used
for power generation, drinking water supply to Delhi, irrigation
and flood control downstream during the monsoon.
According to present operational procedures,
water released from the reservoir depends upon its level in
the reservoir and time. Reservoir level from June to October
should not go beyond 361.95 m. The level in the month of October
should not rise above 362.86 m and the level from November
to May should not fall below 316.99 m.
The amount of water allocated for power
generation is also supposed to cover irrigation needs. Therefore,
at times of water crisis, the entire water released through
the powerhouse goes into hydropower generation and irrigation
demand is considered zero. The agricultural sector suffers.
"We need a procedure which can determine
releases against different demands using data on current state
of the reservoir," said Rama Devi Mehta, a scientist
at the Roorki-based National Institute of Hydrology and the
lead author of the paper. For the model the researchers used
four sets of data from previous years: reservoir levels (during
monsoon and dry period) water inflow and demands. Using the
new technology the model converted these inputs into a single
output in the form of amount of water to be released from
reservoir. The results were consistent with the actual release
value. The study was published in the February 2009 issue
of Water Resource Management.
"Theoretically, models based
on fuzzy logic will show improved results. But in reality
the changes will be minor and not have much practical use,"
said Rajib Kumar Bhattacharjya, assistant professor at the
Indian Institute of Technology, Guwahati. The team is hopeful
that the new model will manage dam operations despite uncertainty
in water inflow and demand, which may worsen with climate
change, allowing operators to take quick decisions.
Source:
Down To Earth, March 2009

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