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contributor authorAlfie Ningyu Song
contributor authorV. Chandramouli
contributor authorNimisha Gupta
date accessioned2017-05-08T21:49:16Z
date available2017-05-08T21:49:16Z
date copyrightAugust 2012
date issued2012
identifier other%28asce%29he%2E1943-5584%2E0000537.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/63404
description abstractInflows to reservoir systems are affected by climatic changes. In the past, regional inflow trend analyses were conducted using statistical approaches. This research made use of an artificial intelligence technique called the self-organizing map (SOM) to perform trend and cluster analysis for the inflows into the flood-control reservoirs of Indiana. Along with SOM, this research also used the Mann-Kendall test and a revised Mann-Kendall test for regional analysis. Results indicate an increasing trend in the clusters that represent days with high inflows to the northern reservoirs of Indiana when inflows to the central and southern reservoirs were low or medium. A 7% increase was noticed in the annual daily counts belonging to this cluster during the past 20 years. Similar trends were observed concerning high-inflow days to the central reservoirs of Indiana. However, they are not statistically significant at a 95% confidence level. This study concludes that SOM is a useful tool for studying the trends at a regional level.
publisherAmerican Society of Civil Engineers
titleAnalyzing Inflow Trend of Indiana Reservoirs Using SOM
typeJournal Paper
journal volume17
journal issue8
journal titleJournal of Hydrologic Engineering
identifier doi10.1061/(ASCE)HE.1943-5584.0000517
treeJournal of Hydrologic Engineering:;2012:;Volume ( 017 ):;issue: 008
contenttypeFulltext


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