scholarly journals Water Quality Modeling Using Artificial Intelligence-Based Tools

2012 ◽  
pp. 177-186
Author(s):  
C. Couto ◽  
H. Vicente ◽  
J. Machado ◽  
A. Abelha ◽  
J. Neves
Keyword(s):  
Artificial Intelligence ◽  
Water Quality ◽  
Water Quality Modeling ◽  
Quality Modeling

scholarly journals Water quality modeling using artificial intelligence-based tools

2012 ◽  
Vol 7 (3) ◽  
pp. 300-309 ◽  
Author(s):  
C. Couto ◽  
H. Vicente ◽  
J. Machado ◽  
A. Abelha ◽  
J. Neves
Keyword(s):  
Artificial Intelligence ◽  
Water Quality ◽  
Water Quality Modeling ◽  
Quality Modeling

scholarly journals Water quality modeling using artificial intelligence-based tools

2012 ◽  
Vol 7 (3) ◽  
pp. 299-308 ◽  
Author(s):  
C. Couto ◽  
H. Vicente ◽  
J. Machado ◽  
A. Abelha ◽  
J. Neves
Keyword(s):  
Artificial Intelligence ◽  
Water Quality ◽  
Water Quality Modeling ◽  
Quality Modeling

Hydrodynamic and Water Quality Modeling of Lake Eğirdir

2014 ◽  
Vol 42 (11) ◽  
pp. 1573-1582 ◽  
Author(s):  
Meltem Kaçıkoç ◽  
Mehmet Beyhan
Keyword(s):  
Water Quality ◽  
Water Quality Modeling ◽  
Quality Modeling

Water quality modeling in the watershed-based approach for waste load allocations

1998 ◽  
Vol 38 (10) ◽  
pp. 165-172 ◽  
Author(s):  
Ruochuan Gu ◽  
Mei Dong
Keyword(s):  
Water Quality ◽  
Point Source ◽  
Water Quality Modeling ◽  
Point Sources ◽  
Low Flow ◽  
Quality Analysis ◽  
Management Approach ◽  
Water Quality Control ◽  
Quality Modeling ◽  
Waste Load

The conventional method for waste load allocations (WLA) employs spatial-differentiation, considering individual point sources, and temporal-integration, using a constant flow, typically 7Q10 low flow. This paper presents a watershed-based seasonal management approach, in which non-point source as well as point sources are incorporated, seasonal design flows are used for water quality analysis, and WLA are performend in a watershed scale. The strategy for surface water quality modeling in the watershed-based approach is described. The concept of seasonal discharge management is discussed and suggested for the watershed-based approach. A case study using the method for the Des Moines River, Iowa, USA is conducted. Modeling considerations and procedure are presented. The significance of non-point source pollutant load and its impact on water quality of the river is evaluated by analyzing field data. A water quality model is selected and validated against field measurements. The model is applied to projections of future water quality situations under different watershed management and water quality control scenarios with respect to river flow and pollutant loading rate.

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