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《水文科学杂志》2013,58(5)
Abstract Abstract A parameter estimation method is proposed for fitting the generalized extreme value (GEV) distribution to censored flood samples. Partial L-moments (PL-moments), which are variants of L-moments and analogous to ?partial probability weighted moments?, are defined for the analysis of such flood samples. Expressions are derived to calculate PL-moments directly from uncensored annual floods, and to fit the parameters of the GEV distribution using PL-moments. Results of Monte Carlo simulation study show that sampling properties of PL-moments, with censoring flood samples of up to 30% are similar to those of simple L-moments, and also that both PL-moment and LH-moments (higher-order L-moments) have similar sampling properties. Finally, simple L-moments, LH-moments, and PL-moments are used to fit the GEV distribution to 75 annual maximum flow series of Nepalese and Irish catchments, and it is found that, in some situations, both LH- and PL-moments can produce a better fit to the larger flow values than simple L-moments. 相似文献
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Ali Meshgi Davar Khalili 《Stochastic Environmental Research and Risk Assessment (SERRA)》2009,23(1):137-152
As part II of a sequence of two papers, previously developed L-moments by Hosking (1990), and the LH-moments by Wang (1997) are further investigated. The LH-moments (L to L4) are used to develop the regional parameters of the generalized extreme value distribution, generalized Pareto (GPA) distribution
and the generalized logistic (GLO) distributions. These respective probability distribution functions (PDFs) are evaluated
in terms of their performances. Flood peaks by the corresponding PDFs are compared with those generated by Monte Carlo simulation
of randomized data, considering the respective LH-moments. The influence of the LH-moments on estimated PDFs are studied by
evaluating the relative bias (RBIAS) in quantile estimation due to variability of the k parameter. Karkhe watershed located in western Iran was used as a case
study area. Part I of this study identified the study area as regions A and B. The minimum calculated relative root mean square
error (RRMSE) and RBIAS between simulated flood peaks and flood peaks by the corresponding PDFs were used in PDF selection, considering the respective
LH-moments. The boxplots of the RRMSE tests identified the L3 level of the GPA distribution as the suitable PDF for sample sizes 20 and 80; for region A. Similar results were found for
the RBIAS test. As for region B, the boxplots of the RRMSE tests indicated similar results for the three PDFs. However, the boxplots of the RBIAS tests identified the L4 level of the GLO most suitable for sample sizes 20 and 80. Relative efficiencies of the LH-moments were investigated, measured
as RRMSE ratios of L-moments over the respective LH-moments. For the most parts the findings of this part of the study were similar
to those of part I. 相似文献
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Comprehensive evaluation of regional flood frequency analysis by L- and LH-moments. I. A re-visit to regional homogeneity 总被引：1，自引：0，他引：1
Ali Meshgi Davar Khalili 《Stochastic Environmental Research and Risk Assessment (SERRA)》2009,23(1):119-135
As part I of a sequence of two papers, previously developed L-moments by Hosking (J R Stat Soc Ser B Methodol 52(2):105–124,
1990), and the LH-moments by Wang (Water Resour Res 33(12):2841–2848, 1997) are re-visited. New relationships are developed for regional homogeneity analysis by the LH-moments, and further establishment
of regional homogeneity is investigated. Previous works of Hosking (J R Stat Soc Ser B Methodol 52(2):105–124, 1990) and Wang (Water Resour Res 33(12):2841–2848, 1997) on L-moments and LH-moments for the generalized extreme value (GEV) distribution are extended to the generalized Pareto
(GPA) and the generalized logistic (GLO) distributions. The Karkhe watershed, located in western Iran is used as a case study
area. Regional homogeneity was investigated by first assuming the entire study area as one regional cluster. Then the entire
study area was designated “homogeneous” by the L-moments (L); and was designated “heterogeneous” by all four levels of the
LH-moments (L1 to L4). The k-means method was used to investigate the case of two regional clusters. All levels of the L- and LH-moments designated the
upper watershed (region A), “homogeneous”, and the lower watershed (region B) “possibly-homogeneous”. The L3 level of the GPA and the L4 level of the GLO were selected for regions A and B, respectively. Wang (Water Resour Res 33(12):2841–2848, 1997) identified a reversing trend in improved performance of the GEV distribution at the LH-moments level of L3 (during the goodness-of-fit test). Similar results were also obtained in this research for the GEV distribution. However,
for the case of the GPA distribution the reversing trend started at L4 for region A; and at L2 for region B. As for the case of the GLO, an improved performance was observed for all levels (moving from L to L4); for both regions. 相似文献
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