Abstract
Regional flood frequency analysis based on an index flood assumption and a two-parameter Weibull distribution was studied and simulation experiments were performed to compare the sample properties of quantile estimates based on the maximum likelihood (ML), moments (MOM), and probability weighted moments (PWM) methods, and to determine the applicability of the asymptotic variances of quantile estimators obtained for each method for finite samples. Results of these experiments showed biases and mean square errors vary with sample size, number of sites, non-exceedance probability, shape parameter, and estimation method. The ratio of the asymptotic variance (Avar) and the mean square error has been examined to see how well Avar represents the variability of quantile estimators for finite samples. In general, asymptotic formulas are quite good even for samples of size 25. The proposed regional model and estimation procedures are illustrated by analyzing some actual flood data from Illinois and Wisconsin.
| Original language | English |
|---|---|
| Pages (from-to) | 171-182 |
| Number of pages | 12 |
| Journal | Journal of Hydrology |
| Volume | 242 |
| Issue number | 3-4 |
| DOIs | |
| Publication status | Published - 2001 Feb 28 |
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All Science Journal Classification (ASJC) codes
- Water Science and Technology
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Regional flood frequency analysis based on a Weibull model : Part 2. Simulations and applications. / Heo, Jun Haeng; Salas, J. D.; Boes, D. C.
In: Journal of Hydrology, Vol. 242, No. 3-4, 28.02.2001, p. 171-182.Research output: Contribution to journal › Article
TY - JOUR
T1 - Regional flood frequency analysis based on a Weibull model
T2 - Part 2. Simulations and applications
AU - Heo, Jun Haeng
AU - Salas, J. D.
AU - Boes, D. C.
PY - 2001/2/28
Y1 - 2001/2/28
N2 - Regional flood frequency analysis based on an index flood assumption and a two-parameter Weibull distribution was studied and simulation experiments were performed to compare the sample properties of quantile estimates based on the maximum likelihood (ML), moments (MOM), and probability weighted moments (PWM) methods, and to determine the applicability of the asymptotic variances of quantile estimators obtained for each method for finite samples. Results of these experiments showed biases and mean square errors vary with sample size, number of sites, non-exceedance probability, shape parameter, and estimation method. The ratio of the asymptotic variance (Avar) and the mean square error has been examined to see how well Avar represents the variability of quantile estimators for finite samples. In general, asymptotic formulas are quite good even for samples of size 25. The proposed regional model and estimation procedures are illustrated by analyzing some actual flood data from Illinois and Wisconsin.
AB - Regional flood frequency analysis based on an index flood assumption and a two-parameter Weibull distribution was studied and simulation experiments were performed to compare the sample properties of quantile estimates based on the maximum likelihood (ML), moments (MOM), and probability weighted moments (PWM) methods, and to determine the applicability of the asymptotic variances of quantile estimators obtained for each method for finite samples. Results of these experiments showed biases and mean square errors vary with sample size, number of sites, non-exceedance probability, shape parameter, and estimation method. The ratio of the asymptotic variance (Avar) and the mean square error has been examined to see how well Avar represents the variability of quantile estimators for finite samples. In general, asymptotic formulas are quite good even for samples of size 25. The proposed regional model and estimation procedures are illustrated by analyzing some actual flood data from Illinois and Wisconsin.
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UR - http://www.scopus.com/inward/citedby.url?scp=0035961568&partnerID=8YFLogxK
U2 - 10.1016/S0022-1694(00)00335-8
DO - 10.1016/S0022-1694(00)00335-8
M3 - Article
AN - SCOPUS:0035961568
VL - 242
SP - 171
EP - 182
JO - Journal of Hydrology
JF - Journal of Hydrology
SN - 0022-1694
IS - 3-4
ER -