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2016 | OriginalPaper | Buchkapitel

A Novel Method to Downscale Daily Wind Statistics to Hourly Wind Data for Wind Erosion Modelling

verfasst von : Zhongling Guo, Chunping Chang, Rende Wang

Erschienen in: Geo-Informatics in Resource Management and Sustainable Ecosystem

Verlag: Springer Berlin Heidelberg

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Abstract

Wind is the principal driver in some wind erosion models. The hourly wind speed data were generally required for precisely wind erosion modeling. In this study, a novel method to generate hourly wind speed data from daily wind statistics (daily average and maximum wind speeds together or daily average wind speed only) was established. Two typical windy locations (Lubbock and Big Spring, Texas, USA) with measured hourly wind speed data were used to validate the downscaling method. The results showed that the overall agreement between observed and simulated cumulative wind speed probability distributions appears excellent, especially for the wind speeds greater than 5 m s−1 range (erosive wind speed). The results further revealed that the values of daily average erosive wind power density (AWPD) calculated from generated wind speeds fit the counterparts computed from measured wind speeds well with high models’ efficiency (Nash-Sutcliffe coefficient).

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Metadaten
Titel
A Novel Method to Downscale Daily Wind Statistics to Hourly Wind Data for Wind Erosion Modelling
verfasst von
Zhongling Guo
Chunping Chang
Rende Wang
Copyright-Jahr
2016
Verlag
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/978-3-662-49155-3_64

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