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Development of hydraulic relationshi...

Bjerklie, David Michael.

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Development of hydraulic relationships for estimating in-bank river discharge using remotely sensed data.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Development of hydraulic relationships for estimating in-bank river discharge using remotely sensed data./
Author:	Bjerklie, David Michael.
Description:	181 p.
Notes:	Source: Dissertation Abstracts International, Volume: 65-05, Section: B, page: 2310.
Contained By:	Dissertation Abstracts International65-05B.
Subject:	Hydrology. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3132783
ISBN:	0496800235

Development of hydraulic relationships for estimating in-bank river discharge using remotely sensed data.
Bjerklie, David Michael.

Development of hydraulic relationships for estimating in-bank river discharge using remotely sensed data. - 181 p.

Source: Dissertation Abstracts International, Volume: 65-05, Section: B, page: 2310.

Thesis (Ph.D.)--University of New Hampshire, 2004.

An evaluation of river hydraulic data currently or potentially available from satellite and other remote platforms was completed, and a set of discharge estimation models proposed that can use the remotely sensed information to estimate discharge with reasonable accuracy. Reasonable accuracy is defined as within +/-20% of the observed on average for a large number of estimates. The proposed estimation models are based on the Manning and Chezy flow resistance equations, and utilize combinations of potentially observable variables including water-surface width, maximum-channel (or bankfull) width, mean water depth, mean maximum-channel depth, mean water velocity, and channel slope. Both statistically and rationally derived prediction models are presented, developed and calibrated on a data base of river discharge measurements and a quasi-theoretical data base of synthetic data. It was found that the channel slope can be used in lieu of a measured water surface slope with very little reduction in prediction accuracy when considering many estimates. Notably absent from this list is a resistance variable, which is included in both the Manning and Chezy equations, because this variable cannot be observed or directly measured. One of the key outcomes of the research is that an exponent of 0.33 on the slope explains much of the variability in the resistance variable, and provides better predictive qualities than the traditional value of 0.5. A dimensionally homogeneous form of the Manning equation was developed which derives the slope exponent of 0.33 based on stable-bed grain size considerations. The prediction models were tested on two data sets of remotely sensed hydraulic information that included width, maximum channel width, and channel slope. Predictions were also made from a single radar image that also included remotely sensed surface velocity, demonstrating the potential for greatly improved accuracy with this additional information. Additionally, the prediction models were tested with channel slope information derived from a digital elevation model, and used to define river channel geometry for a continental scale runoff model.

ISBN: 0496800235Subjects--Topical Terms:

545716
Hydrology.

Development of hydraulic relationships for estimating in-bank river discharge using remotely sensed data.
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100 1 $a Bjerklie, David Michael. $3 1930872
245 1 0 $a Development of hydraulic relationships for estimating in-bank river discharge using remotely sensed data.
300 $a 181 p.
500 $a Source: Dissertation Abstracts International, Volume: 65-05, Section: B, page: 2310.
500 $a Director: S. Lawrence Dingman.
502 $a Thesis (Ph.D.)--University of New Hampshire, 2004.
520 $a An evaluation of river hydraulic data currently or potentially available from satellite and other remote platforms was completed, and a set of discharge estimation models proposed that can use the remotely sensed information to estimate discharge with reasonable accuracy. Reasonable accuracy is defined as within +/-20% of the observed on average for a large number of estimates. The proposed estimation models are based on the Manning and Chezy flow resistance equations, and utilize combinations of potentially observable variables including water-surface width, maximum-channel (or bankfull) width, mean water depth, mean maximum-channel depth, mean water velocity, and channel slope. Both statistically and rationally derived prediction models are presented, developed and calibrated on a data base of river discharge measurements and a quasi-theoretical data base of synthetic data. It was found that the channel slope can be used in lieu of a measured water surface slope with very little reduction in prediction accuracy when considering many estimates. Notably absent from this list is a resistance variable, which is included in both the Manning and Chezy equations, because this variable cannot be observed or directly measured. One of the key outcomes of the research is that an exponent of 0.33 on the slope explains much of the variability in the resistance variable, and provides better predictive qualities than the traditional value of 0.5. A dimensionally homogeneous form of the Manning equation was developed which derives the slope exponent of 0.33 based on stable-bed grain size considerations. The prediction models were tested on two data sets of remotely sensed hydraulic information that included width, maximum channel width, and channel slope. Predictions were also made from a single radar image that also included remotely sensed surface velocity, demonstrating the potential for greatly improved accuracy with this additional information. Additionally, the prediction models were tested with channel slope information derived from a digital elevation model, and used to define river channel geometry for a continental scale runoff model.
590 $a School code: 0141.
650 4 $a Hydrology. $3 545716
650 4 $a Engineering, Environmental. $3 783782
650 4 $a Remote Sensing. $3 1018559
690 $a 0388
690 $a 0775
690 $a 0799
710 2 0 $a University of New Hampshire. $3 1017788
773 0 $t Dissertation Abstracts International $g 65-05B.
790 1 0 $a Dingman, S. Lawrence, $e advisor
790 $a 0141
791 $a Ph.D.
792 $a 2004
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3132783