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Continuous spatial-temporal stochast...

Zhang, Zepu.

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Continuous spatial-temporal stochastic rainfall models based on aggregated historical data.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Continuous spatial-temporal stochastic rainfall models based on aggregated historical data./
作者:	Zhang, Zepu.
面頁冊數:	114 p.
附註:	Source: Dissertation Abstracts International, Volume: 65-11, Section: B, page: 5605.
Contained By:	Dissertation Abstracts International65-11B.
標題:	Hydrology. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3153048
ISBN:	0496134949

Continuous spatial-temporal stochastic rainfall models based on aggregated historical data.
Zhang, Zepu.

Continuous spatial-temporal stochastic rainfall models based on aggregated historical data. - 114 p.

Source: Dissertation Abstracts International, Volume: 65-11, Section: B, page: 5605.

Thesis (Ph.D.)--Stanford University, 2005.

Rainfall modeling is the subject matter of active studies, and progress in this area has great bearing on both research and practice. The goal of the present work is to model continuous spatial-temporal rainfall characteristics on the watershed scale, and present the model as a tool for further analysis of rainfall properties and for simulating rainfall scenarios to be used by other models.

ISBN: 0496134949Subjects--Topical Terms:

545716
Hydrology.

Continuous spatial-temporal stochastic rainfall models based on aggregated historical data.
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245 1 0 $a Continuous spatial-temporal stochastic rainfall models based on aggregated historical data.
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500 $a Source: Dissertation Abstracts International, Volume: 65-11, Section: B, page: 5605.
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502 $a Thesis (Ph.D.)--Stanford University, 2005.
520 $a Rainfall modeling is the subject matter of active studies, and progress in this area has great bearing on both research and practice. The goal of the present work is to model continuous spatial-temporal rainfall characteristics on the watershed scale, and present the model as a tool for further analysis of rainfall properties and for simulating rainfall scenarios to be used by other models.
520 $a The modeled rainfall process is event-based and has a hierarchical structure, i.e., rainfall occurs in storms, which in turn consist of rain generating patches, each having a random size and a random rainfall intensity. Randomly located patches form a spatial Boolean field; the storm is modeled by a spatial field moving across the region of interest. The structure of this model is general, uncomplicated, and open to extensions.
520 $a The spatially-temporally continuous model is estimated using historical data at available stations in a rainfall region. Hourly historical data at eight stations in an Alabama region of 130km by 140km during the years of 1949--1961 are used for illustrations. The time-aggregated historical data are first processed to reconstruct a continuous-time series, which is consistent with the historical data. Storm speed statistics are estimated via the spatial-temporal cross-correlations of the time series observed at pairs of stations. The estimated storm speed is used to convert durations of events in the time-series data to lengths on transects of the spatial rain field. Fitting the spatial model makes use of relations between spatial objects and linear transects, which correspond to observation records at fixed rain stations.
520 $a Statistical precision of the model estimation is investigated through refitting the model using data from simulated storms. The model estimates are consistent in repeated refittings, but have some bias.
520 $a This model will contribute to studying the response and evolution of rainfall-sensitive processes in varying rainfall conditions. Such processes abound in the earth and environmental sciences. Possibilities in applications are illustrated by calculating various rainfall properties in simulated storms.
590 $a School code: 0212.
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