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Advanced methods for improving the l...

Benavides, Jude Anthony.

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Advanced methods for improving the lead-time and accuracy of a flood alert system in an urban watershed.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Advanced methods for improving the lead-time and accuracy of a flood alert system in an urban watershed./
作者:	Benavides, Jude Anthony.
面頁冊數:	364 p.
附註:	Source: Dissertation Abstracts International, Volume: 66-03, Section: B, page: 1358.
Contained By:	Dissertation Abstracts International66-03B.
標題:	Hydrology. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3168059
ISBN:	9780542037245

Advanced methods for improving the lead-time and accuracy of a flood alert system in an urban watershed.
Benavides, Jude Anthony.

Advanced methods for improving the lead-time and accuracy of a flood alert system in an urban watershed. - 364 p.

Source: Dissertation Abstracts International, Volume: 66-03, Section: B, page: 1358.

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

The lead-time and accuracy of a flood alert system designed for a quickly responding urban watershed have been improved by incorporating a variety of new tools and methodologies. These include: the use of computer-mediated voice and data communication systems such as the Internet, high-quality hydrologic data including radar rainfall, real-time hydrologic models, assessment and use of a Quantitative Precipitation Forecast (QPF) algorithm, and the development of improved flood notification levels---providing earlier and more accurate warnings to critical institutions and emergency personnel in flood-prone areas throughout the watershed. While the research focused on one watershed in an urban setting (Brays Bayou in Houston, Texas), the results found are applicable across a broad spectrum of watershed types, provided that the need for more timely and accurate flood forecasts exists.

ISBN: 9780542037245Subjects--Topical Terms:

545716
Hydrology.

Advanced methods for improving the lead-time and accuracy of a flood alert system in an urban watershed.
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520 $a The lead-time and accuracy of a flood alert system designed for a quickly responding urban watershed have been improved by incorporating a variety of new tools and methodologies. These include: the use of computer-mediated voice and data communication systems such as the Internet, high-quality hydrologic data including radar rainfall, real-time hydrologic models, assessment and use of a Quantitative Precipitation Forecast (QPF) algorithm, and the development of improved flood notification levels---providing earlier and more accurate warnings to critical institutions and emergency personnel in flood-prone areas throughout the watershed. While the research focused on one watershed in an urban setting (Brays Bayou in Houston, Texas), the results found are applicable across a broad spectrum of watershed types, provided that the need for more timely and accurate flood forecasts exists.
520 $a System lead-time improvements were accomplished through the implementation and evaluation of a QPF algorithm increasingly used for short-term weather prediction across the United States. The Brays Bayou watershed provided an excellent test-bed for the collection and evaluation of QPF data. Algorithm accuracy and effectiveness were evaluated at various forecast times and basin sizes commonly found in urban watersheds. Generalized results of these analyses are presented.
520 $a System accuracy improvements were accomplished with improved radar-rainfall data input and the development of real-time hydrologic models. A real-time interface for the industry standard HEC-1 hydrologic model was created, allowing the hydrologic predictions developed by this model to take greater advantage of the spatial and temporal distribution of real-time radar-rainfall data. The successful implementation of this real-time hydrologic model at the scale of Brays Bayou also provided significant lead-time improvements by providing estimates to when peak flows would actually occur.
520 $a A successful validation and operational test of the entire system occurred during the November 17th, 2003 storm event. This storm event is utilized as a case study, with results illustrating wide-ranging improvements.
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