Prediction of design flood discharge by statistical downscaling and General Circulation Models
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gp-bibliography.bib Revision:1.7970
- @Article{Tofiq:2014:JH,
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author = "F. A. Tofiq and A. Guven",
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title = "Prediction of design flood discharge by statistical
downscaling and General Circulation Models",
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journal = "Journal of Hydrology",
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year = "2014",
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volume = "517",
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month = "19 " # sep,
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pages = "1145--1153",
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keywords = "genetic algorithms, genetic programming, Linear
genetic programming, Design flood, Peak monthly
discharge, Statistical downscaling",
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ISSN = "0022-1694",
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DOI = "doi:10.1016/j.jhydrol.2014.06.028",
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URL = "http://www.sciencedirect.com/science/article/pii/S0022169414004880",
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size = "9 pages",
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abstract = "The global warming and the climate change have caused
an observed change in the hydrological data; therefore,
forecasters need re-calculated scenarios in many
situations. Downscaling, which is reduction of time and
space dimensions in climate models, will most probably
be the future of climate change research. However, it
may not be possible to redesign an existing dam but at
least precaution parameters can be taken for the worse
scenarios of flood in the downstream of the dam
location. The purpose of this study is to develop a new
approach for predicting the peak monthly discharges
from statistical downscaling using linear genetic
programming (LGP). Attempts were made to evaluate the
impacts of the global warming and climate change on
determining of the flood discharge by considering
different scenarios of General Circulation Models.
Reasonable results were achieved in downscaling the
peak monthly discharges directly from daily surface
weather variables (NCEP and CGCM3) without involving
any rainfall-runoff models.",
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notes = "Civil Engineering Department, Gaziantep University,
Gaziantep, Turkey",
- }
Genetic Programming entries for
F A Tofiq
Aytac Guven
Citations