| contributor author | James E. Palumbo | |
| contributor author | Linfield C. Brown | |
| date accessioned | 2017-05-08T21:42:44Z | |
| date available | 2017-05-08T21:42:44Z | |
| date copyright | March 2014 | |
| date issued | 2014 | |
| identifier other | %28asce%29ei%2E1943-5541%2E0000006.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/60259 | |
| description abstract | The overall performance of 18 commonly used reaeration rate coefficient prediction equations was evaluated using statistical metrics of prediction accuracy and bias by comparing predicted reaeration coefficients to a database of values measured using gas tracer techniques. Adapting a commonly applied concept, predictive equations were evaluated in discrete regions of the velocity-depth space. Results indicate that rarely is there a single best prediction equation in a given velocity-depth region, rather there usually is a group of statistically indistinguishable top-performing equations. Also, no single reaeration equation performed well over all hydraulic conditions. Prediction equations, which include slope as a variable are more accurate and have lower bias than those that do not. However, even the top-performing equations exhibited large prediction errors of at least 40–50% and exceeded 100% in some regions. This level of error in predicting reaeration rate coefficients will continue to have a major impact on the uncertainty of dissolved oxygen forecasts from receiving water quality models. | |
| publisher | American Society of Civil Engineers | |
| title | Assessing the Performance of Reaeration Prediction Equations | |
| type | Journal Paper | |
| journal volume | 140 | |
| journal issue | 3 | |
| journal title | Journal of Environmental Engineering | |
| identifier doi | 10.1061/(ASCE)EE.1943-7870.0000799 | |
| tree | Journal of Environmental Engineering:;2014:;Volume ( 140 ):;issue: 003 | |
| contenttype | Fulltext | |