The Development of a Hydrodynamic and Water Quality Model to Support TMDL Determinations and Water Quality Management of a Stratified Shallow Estuary: Mobile Bay, Alabama

2003 ◽  
Vol 2003 (4) ◽  
pp. 378-392 ◽  
Author(s):  
Tim A. Wool ◽  
Steven R. Davie ◽  
Yuri M. Plis ◽  
John Hamrick
2003 ◽  
Vol 48 (10) ◽  
pp. 47-53 ◽  
Author(s):  
H. Reuter ◽  
G. Krause ◽  
A. Mönig ◽  
M. Wulkow ◽  
H. Horn

The water quality management tool RIONET for river basins has been developed with regard to the EU Water Framework Directive. The management tool can simulate the water quality in catchment basins not only in the dimension of a single river but in whole river networks. A submodel of the IWA River Water Quality Model No. 1 is used in RIONET. The river model is based on the assumption that self purification processes in the river takes place both in the benthic biofilm and the bulk water phase. Laboratory experiments with sediment cores underline the major role of the benthic biofilm. The input parameters of the management tool such as volumetric flow rates from waste water treatment plants and flow velocities and discharge in the main river and its tributaries can be loaded directly from geographic information systems (GIS). The subcatchment basin of the river Bode in Saxon Anhalt was used for test runs of RIONET.


1998 ◽  
Vol 37 (2) ◽  
pp. 369-376 ◽  
Author(s):  
Orhan Gündüz ◽  
Selçuk Soyupak ◽  
Coskun Yurteri

A two-dimensional laterally averaged hydrodynamic and water quality model (CE-QUAL-W2) is used to simulate the water quality behavior in the proposed Isikli Reservoir of the Ankara Water Supply System to determine appropriate strategies for the management of water quality. Isikli application of the model is used to demonstrate the potential water quality degradation patterns in the reservoir under different pollution loads. The results of the modeling study are compared with the drinking water quality standards currently effective in Turkey to formulate various water quality management strategies for the reservoir and its catchment area. In addition, various treatment options are evaluated considering the existing treatment system of Ankara City. Based on the findings of this study, treatment or interception of wastewaters originating from the existing pollution sources around the reservoir area are introduced as the major infrastructural control techniques. Further, establishment of protection zones around the reservoir and relocating the possible pollution sources to a point downstream of the dam axis are found to be the most applicable administrative control methods for water quality preservation in the proposed reservoir.


2010 ◽  
Vol 61 (3) ◽  
pp. 607-618 ◽  
Author(s):  
Giorgio Mannina ◽  
Gaspare Viviani

Water quality modelling is of crucial importance for the assessment of physical, chemical, and biological changes in water bodies. Mathematical approaches to water modelling have become more prevalent over recent years. Different model types ranging from detailed physical models to simplified conceptual models are available. Actually, a possible middle ground between detailed and simplified models may be parsimonious models that represent the simplest approach that fits the application. The appropriate modelling approach depends on the research goal as well as on data available for correct model application. When there is inadequate data, it is mandatory to focus on a simple river water quality model rather than detailed ones. The study presents a parsimonious river water quality model to evaluate the propagation of pollutants in natural rivers. The model is made up of two sub-models: a quantity one and a quality one. The model employs a river schematisation that considers different stretches according to the geometric characteristics and to the gradient of the river bed. Each stretch is represented with a conceptual model of a series of linear channels and reservoirs. The channels determine the delay in the pollution wave and the reservoirs cause its dispersion. To assess the river water quality, the model employs four state variables: DO, BOD, NH4, and NO. The model was applied to the Savena River (Italy), which is the focus of a European-financed project in which quantity and quality data were gathered. A sensitivity analysis of the model output to the model input or parameters was done based on the Generalised Likelihood Uncertainty Estimation methodology. The results demonstrate the suitability of such a model as a tool for river water quality management.


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