Estimating 7Q10 Confidence Limits from Data: A Bootstrap ApproachSource: Journal of Water Resources Planning and Management:;2006:;Volume ( 132 ):;issue: 003Author:Daniel P. Ames
DOI: 10.1061/(ASCE)0733-9496(2006)132:3(204)Publisher: American Society of Civil Engineers
Abstract: 7Q10 streamflow estimates used to support modeling and data analysis under the Clean Water Act national pollution discharge elimination system and total maximum daily load programs can have direct environmental and economic impacts. Thus it is important that 7Q10 streamflow always be reported together with confidence limits indicating the reliability of the estimate. In practice this is rarely done. This technical note presents a bootstrap approach for computing 7Q10 confidence limits from data and compares it to an empirical method. A case study using randomly selected subsets of data from five rivers in Idaho is used to evaluate the two methods. While both methods exhibit the expected increase in confidence interval as fewer years of data used, the bootstrap approach generally results in wider confidence intervals than does the empirical method. The opposite appears to be true in cases where fewer than
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contributor author | Daniel P. Ames | |
date accessioned | 2017-05-08T21:08:07Z | |
date available | 2017-05-08T21:08:07Z | |
date copyright | May 2006 | |
date issued | 2006 | |
identifier other | %28asce%290733-9496%282006%29132%3A3%28204%29.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/40007 | |
description abstract | 7Q10 streamflow estimates used to support modeling and data analysis under the Clean Water Act national pollution discharge elimination system and total maximum daily load programs can have direct environmental and economic impacts. Thus it is important that 7Q10 streamflow always be reported together with confidence limits indicating the reliability of the estimate. In practice this is rarely done. This technical note presents a bootstrap approach for computing 7Q10 confidence limits from data and compares it to an empirical method. A case study using randomly selected subsets of data from five rivers in Idaho is used to evaluate the two methods. While both methods exhibit the expected increase in confidence interval as fewer years of data used, the bootstrap approach generally results in wider confidence intervals than does the empirical method. The opposite appears to be true in cases where fewer than | |
publisher | American Society of Civil Engineers | |
title | Estimating 7Q10 Confidence Limits from Data: A Bootstrap Approach | |
type | Journal Paper | |
journal volume | 132 | |
journal issue | 3 | |
journal title | Journal of Water Resources Planning and Management | |
identifier doi | 10.1061/(ASCE)0733-9496(2006)132:3(204) | |
tree | Journal of Water Resources Planning and Management:;2006:;Volume ( 132 ):;issue: 003 | |
contenttype | Fulltext |