{"title":"Estimating probability of extreme rainfall over Japan using Extended Regional Frequency Analysis","authors":"M. Sugi, Y. Imada, T. Nakaegawa, K. Kamiguchi","doi":"10.3178/HRL.11.19","DOIUrl":null,"url":null,"abstract":": A method of frequency analysis, Extended Regional Frequency Analysis (ERFA), is proposed for reliable estimates of extreme daily rainfall probabilities for a long return period from relatively short daily rainfall records. The method uses combined data in a wide meteorologically homogeneous region (e.g., all Japan) to ensure a large number (order of 10,000) of data to minimize the effects of statistical sampling error in the frequency analysis. We applied the ERFA to daily rainfall data observed over Japan and to a high reso-lution atmospheric model simulation data over the meteorologically homogeneous land region of Japan. We found very good agreement between the empirical probability distribution and theoretical distribution estimated by ERFA, sug-gesting that the method is promising. However, we have noted some problems regarding ERFA: selection of the distribution, selection of the region, and model bias. These problems, along with possible solutions, are discussed.","PeriodicalId":13111,"journal":{"name":"Hydrological Research Letters","volume":null,"pages":null},"PeriodicalIF":0.6000,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3178/HRL.11.19","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Hydrological Research Letters","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3178/HRL.11.19","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"WATER RESOURCES","Score":null,"Total":0}
引用次数: 8
Abstract
: A method of frequency analysis, Extended Regional Frequency Analysis (ERFA), is proposed for reliable estimates of extreme daily rainfall probabilities for a long return period from relatively short daily rainfall records. The method uses combined data in a wide meteorologically homogeneous region (e.g., all Japan) to ensure a large number (order of 10,000) of data to minimize the effects of statistical sampling error in the frequency analysis. We applied the ERFA to daily rainfall data observed over Japan and to a high reso-lution atmospheric model simulation data over the meteorologically homogeneous land region of Japan. We found very good agreement between the empirical probability distribution and theoretical distribution estimated by ERFA, sug-gesting that the method is promising. However, we have noted some problems regarding ERFA: selection of the distribution, selection of the region, and model bias. These problems, along with possible solutions, are discussed.
期刊介绍：
Hydrological Research Letters (HRL) is an international and trans-disciplinary electronic online journal published jointly by Japan Society of Hydrology and Water Resources (JSHWR), Japanese Association of Groundwater Hydrology (JAGH), Japanese Association of Hydrological Sciences (JAHS), and Japanese Society of Physical Hydrology (JSPH), aiming at rapid exchange and outgoing of information in these fields. The purpose is to disseminate original research findings and develop debates on a wide range of investigations on hydrology and water resources to researchers, students and the public. It also publishes reviews of various fields on hydrology and water resources and other information of interest to scientists to encourage communication and utilization of the published results. The editors welcome contributions from authors throughout the world. The decision on acceptance of a submitted manuscript is made by the journal editors on the basis of suitability of subject matter to the scope of the journal, originality of the contribution, potential impacts on societies and scientific merit. Manuscripts submitted to HRL may cover all aspects of hydrology and water resources, including research on physical and biological sciences, engineering, and social and political sciences from the aspects of hydrology and water resources.
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