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Empirical Estimation of Stream Discharge Using Channel Geometry in Low‐Gradient, Sand‐Bed Streams of the Southeastern Plains
Author(s) -
Sefick Stephen A.,
Kalin Latif,
Kosnicki Ely,
Schneid Brad P.,
Jarrell Miller S.,
Anderson Chris J.,
Paller Michael H.,
Feminella Jack W.
Publication year - 2015
Publication title -
jawra journal of the american water resources association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.957
H-Index - 105
eISSN - 1752-1688
pISSN - 1093-474X
DOI - 10.1111/jawr.12278
Subject(s) - streams , hydrology (agriculture) , channel (broadcasting) , akaike information criterion , flow (mathematics) , radius , environmental science , geology , statistics , geometry , mathematics , geotechnical engineering , engineering , computer science , computer network , electrical engineering , computer security
Manning's equation is used widely to predict stream discharge ( Q ) from hydraulic variables when logistics constrain empirical measurements of in‐bank flow events. Uncertainty in Manning's roughness ( n M ) is the major source of error in natural channels, and sand‐bed streams pose difficulties because flow resistance is affected by flow‐dependent bed configuration. Our study was designed to develop and validate models for estimating Q from channel geometry easily derived from cross‐sectional surveys and available GIS data. A database was compiled consisting of 484 Q measurements from 75 sand‐bed streams in Alabama, Georgia, South Carolina, North Carolina (Southeastern Plains), and Florida (Southern Coastal Plain), with six New Zealand streams included to develop statistical models to predict Q from hydraulic variables. Model error characteristics were estimated with leave‐one‐site‐out jackknifing. Independent data of 317 Q measurements from 55 Southeastern Plains streams indicated the model ( Q = A c R H 0.6906 S 0.1216 ; where A c is the channel area, R H is the hydraulic radius, and S is the bed slope) best predicted Q , based on Akaike's information criterion and root mean square error. Models also were developed from smaller Q range subsets to explore if subsets increased predictive ability, but error fit statistics suggested that these were not reasonable alternatives to the above equation. Thus, we recommend the above equation for predicting in‐bank Q of unbraided, sandy streams of the Southeastern Plains.