Application of ANN for the Hydrological Modeling
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2017, Vol 5, Issue 7
Abstract
Global climate change has been a burning problem for environmentalists since the middle of the 20th century. The application of artificial neural network (ANN) methodology for modeling climate change impact on river Jhelum basin in the State of Jammu & Kashmir, India is presented. In the present study ANN model was applied to monthly temperature and precipitation data for base time (1979–2009) at four different metrological stations viz. Srinagar, Pahalgam, Qazigund and Gulmarg of river Jhelum basin and then the future average annual temperature and precipitation predicted up to 2100. The large scale GCM predictors were related to observed precipitation and temperature and future projections of climate were made under A1B and A2 scenario upto 21st century. At the end of the 21st century the mean annual temperature of the Jhelum river basin is predicted to increase by 1.43°C whereas the total annual precipitation is predicted to decrease substantially by 30.88% ANN technique under A1B scenario. However, for A2 scenario average annual temperature increased by 1.56°C and total annual precipitation decreased by 35.32%.
Authors and Affiliations
Mehnaza Akhter
Keywords
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