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| Titel |
Spatio-temporal analysis of the extreme precipitation by the L-moment-based index-flood method in the Yangtze River Delta region, China |
| VerfasserIn |
Yixing Yin, Haishan Chen, Chongyu Xu, Wucheng Xu, Changchun Chen |
| Konferenz |
EGU General Assembly 2014
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 16 (2014) |
| Datensatznummer |
250090270
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| Publikation (Nr.) |
 EGU/EGU2014-4493.pdf |
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| Zusammenfassung |
| The regionalization methods which “trade space for time” by including several at-site data
records in the frequency analysis are an efficient tool to improve the reliability of
extreme quantile estimates. With the main aims of improving the understanding of the
regional frequency of extreme precipitation and providing scientific and practical
background and assistance in formulating the regional development strategies for
water resources management in one of the most developed and flood-prone regions
in China, the Yangtze River Delta (YRD) region, in this paper, L-moment-based
index-flood (LMIF) method, one of the popular regionalization methods, is used in the
regional frequency analysis of extreme precipitation; attention was paid to inter-site
dependence and its influence on the accuracy of quantile estimates, which hasn’t been
considered for most of the studies using LMIF method. Extensive data screening of
stationarity, serial dependence and inter-site dependence was carried out first. The
entire YRD region was then categorized into four homogeneous regions through
cluster analysis and homogenous analysis. Based on goodness-of-fit statistic and
L-moment ratio diagrams, Generalized extreme-value (GEV) and Generalized Normal
(GNO) distributions were identified as the best-fit distributions for most of the sub
regions. Estimated quantiles for each region were further obtained. Monte-Carlo
simulation was used to evaluate the accuracy of the quantile estimates taking inter-site
dependence into consideration. The results showed that the root mean square errors
(RMSEs) were bigger and the 90% error bounds were wider with inter-site dependence
than those with no inter-site dependence for both the regional growth curve and
quantile curve. The spatial patterns of extreme precipitation with return period
of 100 years were obtained which indicated that there are two regions with the
highest precipitation extremes (southeastern coastal area of Zhejiang Province and the
southwest part of Anhui Province) and a large region with low precipitation extremes
in the north and middle parts of Zhejiang Province, Shanghai City and Jiangsu
Province. However, the central areas with low precipitation extremes are the most
developed and densely populated regions in the study area, thus floods will cause
great loss of human life and property damage. These findings will contribute to
formulating the regional development strategies for policymakers and stakeholders in
water resource management against the menaces of frequently emerged floods. |
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