DOI: 10.5194/hess-21-2463-2017
Scopus记录号: 2-s2.0-85019201006
论文题名: Regionalizing nonparametric models of precipitation amounts on different temporal scales
作者: Mosthaf T ; , Bardossy A
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2017
卷: 21, 期: 5 起始页码: 2463
结束页码: 2481
语种: 英语
Scopus关键词: Distribution functions
; Gages
; Interpolation
; Rain
; Rain gages
; Stochastic systems
; Exponential distributions
; Interpolation schemes
; Kernel density estimate
; Non-parametric model
; Nonparametric methods
; Parametric distributions
; Stochastic rainfalls
; Temporal resolution
; Precipitation (meteorology)
; flood
; interpolation
; numerical model
; precipitation (climatology)
; raingauge
; spatiotemporal analysis
; Germany
英文摘要: Parametric distribution functions are commonly used to model precipitation amounts corresponding to different durations. The precipitation amounts themselves are crucial for stochastic rainfall generators and weather generators. Nonparametric kernel density estimates (KDEs) offer a more flexible way to model precipitation amounts. As already stated in their name, these models do not exhibit parameters that can be easily regionalized to run rainfall generators at ungauged locations as well as at gauged locations. To overcome this deficiency, we present a new interpolation scheme for nonparametric models and evaluate it for different temporal resolutions ranging from hourly to monthly. During the evaluation, the nonparametric methods are compared to commonly used parametric models like the two-parameter gamma and the mixed-exponential distribution. As water volume is considered to be an essential parameter for applications like flood modeling, a Lorenz-curve-based criterion is also introduced. To add value to the estimation of data at sub-daily resolutions, we incorporated the plentiful daily measurements in the interpolation scheme, and this idea was evaluated. The study region is the federal state of Baden-WÃ1/4rttemberg in the southwest of Germany with more than 500Â rain gauges. The validation results show that the newly proposed nonparametric interpolation scheme provides reasonable results and that the incorporation of daily values in the regionalization of sub-daily models is very beneficial. © 2017 Author(s). Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79176
Appears in Collections: 气候变化事实与影响
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作者单位: Institute for Modeling Hydraulic and Environmental Systems, Universität Stuttgart, Stuttgart, Germany
Recommended Citation:
Mosthaf T,, Bardossy A. Regionalizing nonparametric models of precipitation amounts on different temporal scales[J]. Hydrology and Earth System Sciences,2017-01-01,21(5)