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    Climate Change Impacts on Catchment-Scale Extreme Rainfall Variability: Case Study of Rize Province, Turkey

    Source: Journal of Hydrologic Engineering:;2017:;Volume ( 022 ):;issue: 003
    Author:
    Ali Danandeh Mehr
    ,
    Ercan Kahya
    DOI: 10.1061/(ASCE)HE.1943-5584.0001477
    Publisher: American Society of Civil Engineers
    Abstract: This paper conducts a catchment-scale analysis of extreme rainfall events of the reference (1961–1990) and three future climate periods (2013–2039, 2040–2070, and 2071–2100) for Rize Province, Turkey. The extreme value theory (EVT) is applied to analyze observational and projected extreme rainfall data including regional climate model (RCM) outputs guided by two general circulation models (GCM) under SRES-A2 and RCP8.5 greenhouse gas scenarios. A new rapid and effective bias correction method is also developed and applied to adjust the climate models simulations. The EVT analysis results demonstrated significant differences between the model runs for both the reference and future periods with considerable spatial variability in rainfall extremes. Based upon the assembled mean results, approximately a 30% decrease in the median value of extreme rainfall events is projected over the study region for the near future, 2013–2039, and middle of the century. This change dramatically decreases to 15% of its historic value at the end of the century. The results from the implemented GCM-RCM combinations revealed that more intense rainfalls are produced by the combination forced by the RCP8.5 scenario. In addition, the results from goodness-of-fit tests among different distribution models showed that general extreme value distribution can be used appropriately to characterize the behavior of projected extreme rainfalls over the study region.
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      Climate Change Impacts on Catchment-Scale Extreme Rainfall Variability: Case Study of Rize Province, Turkey

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4243594
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    contributor authorAli Danandeh Mehr
    contributor authorErcan Kahya
    date accessioned2017-12-30T12:56:08Z
    date available2017-12-30T12:56:08Z
    date issued2017
    identifier other%28ASCE%29HE.1943-5584.0001477.pdf
    identifier urihttp://138.201.223.254:8080/yetl1/handle/yetl/4243594
    description abstractThis paper conducts a catchment-scale analysis of extreme rainfall events of the reference (1961–1990) and three future climate periods (2013–2039, 2040–2070, and 2071–2100) for Rize Province, Turkey. The extreme value theory (EVT) is applied to analyze observational and projected extreme rainfall data including regional climate model (RCM) outputs guided by two general circulation models (GCM) under SRES-A2 and RCP8.5 greenhouse gas scenarios. A new rapid and effective bias correction method is also developed and applied to adjust the climate models simulations. The EVT analysis results demonstrated significant differences between the model runs for both the reference and future periods with considerable spatial variability in rainfall extremes. Based upon the assembled mean results, approximately a 30% decrease in the median value of extreme rainfall events is projected over the study region for the near future, 2013–2039, and middle of the century. This change dramatically decreases to 15% of its historic value at the end of the century. The results from the implemented GCM-RCM combinations revealed that more intense rainfalls are produced by the combination forced by the RCP8.5 scenario. In addition, the results from goodness-of-fit tests among different distribution models showed that general extreme value distribution can be used appropriately to characterize the behavior of projected extreme rainfalls over the study region.
    publisherAmerican Society of Civil Engineers
    titleClimate Change Impacts on Catchment-Scale Extreme Rainfall Variability: Case Study of Rize Province, Turkey
    typeJournal Paper
    journal volume22
    journal issue3
    journal titleJournal of Hydrologic Engineering
    identifier doi10.1061/(ASCE)HE.1943-5584.0001477
    page05016037
    treeJournal of Hydrologic Engineering:;2017:;Volume ( 022 ):;issue: 003
    contenttypeFulltext
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