12-14 September, 2011, Lucknow - Earth Science India

National Conference on Science of Climate Change and Earth’s Sustainability: Issues and Challenges ‘A Scientist-People Partnership’
12-14 September, 2011, Lucknow
(Green House Gas) or future Water availability in space and time. PRECIS (pronounced
as in the French précis - "PRAY-sea") is based on the Hadley Centre's regional climate
modelling system.
A distributed hydrological model namely Soil and Water Assessment Tool
(SWAT) has been used for study of the Bhima river basin. The framework predicts the
impact of climate change on the hydrological regime with the assumption that the land
use shall not change over time and any manmade changes are not incorporated.
Simulation at 29 sub-basins of the Bhima basin has been conducted with 30 years of
data belonging to control (present) and the reaming 30 years data (2011-2040)
corresponding to CHG (future) climate scenario. Quantification of climate change
impact has been done through the use of SWAT hydrological model . The initial
analysis has revealed that increase in precipitation has been predicted in almost half of
the month of the year, while in the remaining months decrease in precipitation has been
predicted. The magnitude of this increase/decrease in precipitation over the Bhima basin
has been variable over various months.
GROUNDWATER LEVEL PREDICTION - AN ARTIFICIAL
INTELLIGENCE APPROACH
S. Sahai and R.A. Yadav *
U.P.Jal Nigam, Lucknow
* email: ray_tiru@yahoo.co.in
Due to rapid growth in the population, urbanization, industrialisation and change
in life style in general etc. has increased the demand of water manifold which in turn
forced water level to decline. Keeping in mind the scarcity of available water resources
in the near future and its impending threats, it has become imperative on the part of
water scientists as well as planners to quantify the available water resources for its
judicial use. Thus, a ready reckoner to monitor the fluctuations in groundwater levels
well in advance is the need of the hour to devise sustainable water management
protocols. In this direction several studies were carried out for forecasting the
groundwater levels using conceptual/ physical models that are not only laborious, but
also have practical limitations, as many inter-related variables are involved. In the
recent past, artificial intelligence techniques like Artificial Neural Networks (ANNs)
and Adaptive Neuro Fuzzy Inference System (ANFIS) have been used increasingly in
various fields of science and technology for prediction purposes. In particular, these
have been found useful in the area of hydrologic time series modelling. The ANN is a
general-purpose model with a limited set of variables, and is used as a universal
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