title: [Multiple pattern inverse water quality modeling approach for predicting the water quality consequence of Lake Chenghai water elevation control].
abstract: A water quality model was developed through incorporating the water surface elevation and water quality data of Lake Chenghai into the CE-QUAL-W2 computational platform. The model integrates the water surface elevation and water quality into a holistic dynamic system based on the data of Lake Chenghai, and was calibrated against observed data using a multiple pattern inverse water quality modeling technology, which was driven by a robust genetic algorithm (GA). After the model was calibrated, it was used to produce robust predictions of the lake water quality in response to various water elevation controlled scenarios. The model established a basis for quantifying the water quality responses under uncertainty, and is valuable for supporting effective and reliable management decision making. The results of this research suggest that various water elevation control scenarios only result in insignificant water quality improvement in terms of TN, TP, and COD concentrations, therefore, it does not recommend to consider water elevation control to be the major water quality management option for Lake Chenghai.
authors.affiliation: Tetra Technologies Incorporated Company, 10306 Eaton Place, Ste 340, Fairfax, VA 22030, USA. rz5q@yahoo.com
authors.forename: Rui
authors.initials: R
authors.lastname: Zou
authors.forename: Yun-Xian
authors.initials: YX
authors.lastname: Dong
authors.forename: Xiao-Pin
authors.initials: XP
authors.lastname: Yan
authors.forename: Lei
authors.initials: L
authors.lastname: Zhao
authors.forename: Bin
authors.initials: B
authors.lastname: He
authors.forename: Yong
authors.initials: Y
authors.lastname: Liu
mesh_terms: D002681:China; D004784:Environmental Monitoring / Q000379:methods*; D060106:Lakes; D008962:Models, Theoretical; D014876:Water Pollution / Q000517:prevention & control*; D060753:Water Quality