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Space-Time Analysis of Rainfall-Runoff Relationships in Hong Kong.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Space-Time Analysis of Rainfall-Runoff Relationships in Hong Kong./
作者:	Sham, Chi Ho.
面頁冊數:	1 online resource (260 pages)
附註:	Source: Dissertations Abstracts International, Volume: 45-07, Section: B.
Contained By:	Dissertations Abstracts International45-07B.
標題:	Geography. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=8426081click for full text (PQDT)
ISBN:	9798205763714

Space-Time Analysis of Rainfall-Runoff Relationships in Hong Kong.
Sham, Chi Ho.

Space-Time Analysis of Rainfall-Runoff Relationships in Hong Kong. - 1 online resource (260 pages)

Source: Dissertations Abstracts International, Volume: 45-07, Section: B.

Thesis (Ph.D.)--State University of New York at Buffalo, 1984.

Includes bibliographical references

Prediction of the streamflow resulting from rainfall over a catchment is an important issue in applied hydrology. Catchment yields on the monthly scale is important in terms of the design and the operation of water resource projects. Effectiveness in managing water resources depends largely on the knowledge of the rainfall-runoff relationships in the associated catchments. The application and development of stochastic modeling techniques within the field of hydrology, such as the ARIMA and transfer function-noise models of Box and Jenkins, has led to the establishment of stochastic hydrology. Although stochastic models have been used successfully in describing and simulating hydrologic phenomena, there has been very limited work on the physical interpretation of the stochastic model parameters. The monthly rainfall series from 15 raingauge stations in Hong Kong were analyzed to obtain the underlying characteristics of rainfall patterns. Analytical results indicate that the spatial characteristics of monthly rainfall is consistent over time, and the monthly rainfall can be modeled adequately by a seasonal ARIMA model. The monthly runoff series from six upland-catchment gauging stations in Hong Kong were studied to reveal the underlying properties of runoff process. Analytical results indicate that natural-log transformation of non-normal runoff data has improved the goodness of fit of the final ARIMA models, and similar model structures are found for neighboring catchments of similar morphometry. Pairs of monthly rainfall and runoff series were used to investigate the rainfall-runoff relationships in the six upland catchments in Hong Kong. The transfer function-noise models of Box and Jenkins were applied to reveal the relationships between monthly rainfall and runoff volumes. A simple model structure was found to be adequate for all six catchments, as the level of explanation of this model ranges from 83 percent to 87 percent. The obtained model parameters of the transfer function-noise models were examined in relation to the morphometric properties of the study catchments. Three out of the four model parameters have significant relationships with some aspects of drainage basin morphometry. The results of this study suggest that a geographical approach can produce significant contribution to the understanding of stochastic hydrologic modeling.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798205763714Subjects--Topical Terms:

524010
Geography.
Index Terms--Genre/Form:

542853
Electronic books.

Space-Time Analysis of Rainfall-Runoff Relationships in Hong Kong.
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245 1 0 $a Space-Time Analysis of Rainfall-Runoff Relationships in Hong Kong.
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500 $a Publisher info.: Dissertation/Thesis.
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504 $a Includes bibliographical references
520 $a Prediction of the streamflow resulting from rainfall over a catchment is an important issue in applied hydrology. Catchment yields on the monthly scale is important in terms of the design and the operation of water resource projects. Effectiveness in managing water resources depends largely on the knowledge of the rainfall-runoff relationships in the associated catchments. The application and development of stochastic modeling techniques within the field of hydrology, such as the ARIMA and transfer function-noise models of Box and Jenkins, has led to the establishment of stochastic hydrology. Although stochastic models have been used successfully in describing and simulating hydrologic phenomena, there has been very limited work on the physical interpretation of the stochastic model parameters. The monthly rainfall series from 15 raingauge stations in Hong Kong were analyzed to obtain the underlying characteristics of rainfall patterns. Analytical results indicate that the spatial characteristics of monthly rainfall is consistent over time, and the monthly rainfall can be modeled adequately by a seasonal ARIMA model. The monthly runoff series from six upland-catchment gauging stations in Hong Kong were studied to reveal the underlying properties of runoff process. Analytical results indicate that natural-log transformation of non-normal runoff data has improved the goodness of fit of the final ARIMA models, and similar model structures are found for neighboring catchments of similar morphometry. Pairs of monthly rainfall and runoff series were used to investigate the rainfall-runoff relationships in the six upland catchments in Hong Kong. The transfer function-noise models of Box and Jenkins were applied to reveal the relationships between monthly rainfall and runoff volumes. A simple model structure was found to be adequate for all six catchments, as the level of explanation of this model ranges from 83 percent to 87 percent. The obtained model parameters of the transfer function-noise models were examined in relation to the morphometric properties of the study catchments. Three out of the four model parameters have significant relationships with some aspects of drainage basin morphometry. The results of this study suggest that a geographical approach can produce significant contribution to the understanding of stochastic hydrologic modeling.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2023
538 $a Mode of access: World Wide Web
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650 4 $a Physical geography. $3 516662
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773 0 $t Dissertations Abstracts International $g 45-07B.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=8426081 $z click for full text (PQDT)