TITLE

STUDY OF IMPACT OF CLIMATE CHANGE ON WATER AVAILABILITY IN THE GUMTI HYDROPOWER PLANT, TRIPURA, INDIA USING ARTIFICIAL NEURAL NETWORK

AUTHOR(S)
Majumdar, K.; Datta, S.; Roy, P. K.; Mazumdar, A.
PUB. DATE
June 2014
SOURCE
Journal of Engineering & Applied Sciences;Jun2014, Vol. 9 Issue 6, p891
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
Electricity is recognized as fundamental to industrialization and improving the quality of life of the people. Harnessing the immense untapped hydropower potential in Tripura region opens avenues for growth and provides an opportunity to improve the well-being of the people of the region, while making substantial contribution to the national economy. Gumti hydro power plant generates power to mitigate the crisis of power in Tripura, India. The first unit of hydro power plant (5MW) was commissioned in June 1976 and another two units of 5 MW was commissioned simultaneously. But out of 15MW capacity at present only 8MW-9MW power is produced from Gumti hydro power plant during rainy season. But during lean season the production reduces to 0.5MW due to shortage of water. Hence forecasting models are necessary to predict the future available water based on past and current information. Water prediction will tell us whether the coming years will be good, bad or average. Accordingly contingency measures can be planned well in advance. The present investigation tried to analyze the impact of climate change on availability of water in the Gumti Reservoir using Artificial Neural Network. In this regard a neural network model is developed and implemented for prediction of the volume of water in the reservoir due to the change in meteorological variables which is imminent for the future climate change scenarios as predicted by the PRECIS climate models. As per the model prediction there will be a deficit in the water availability of the reservoir. The level of deficit will be 25.17% in A2 scenario under peak flow conditions and 20.52% in lean flow condition for A1B scenario.
ACCESSION #
96709040

 

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