The application of the activated sludge model No. 1 to a river environment

1997 ◽  
Vol 36 (5) ◽  
pp. 201-208 ◽  
Author(s):  
F. Maryns ◽  
W. Bauwens
Keyword(s):  
Water Quality ◽  
Activated Sludge ◽  
River Water ◽  
Water Quality Management ◽  
River Water Quality ◽  
Sensitivity Analyses ◽  
Quality Models ◽  
Activated Sludge Model ◽  
Water Quality Models ◽  
Modelling Approach

The current tendency towards an integrated approach for water quality management gives rise to a demand for consistent methods for linking dynamic wastewater treatment models with river water quality models. Linking such models is difficult because of the mutual structural differences with regard to variable and parameter definitions as well as process descriptions. This paper proposes to use the same modelling approach for the simulation of activated sludge treatment and natural self-purification in rivers. Since the standard Activated Sludge Model No. 1 (ASM1) is found to be far more conceptual and consistent than traditional river water quality models, the suitability of the ASM1 modelling approach has been assessed. The traditional ASM1 matrix has been adapted and extended to a river environment and has subsequently served as the basis of an ASM1-type water quality model for the River Dender in Flanders. Sensitivity analyses on this model showed that the most sensitive parameters in the ASM1 formulation of biological decay are the ones determining hydrolysis. The model efficiently calculates BOD concentrations but the predicted DO concentrations are not very accurate, mainly because of the remaining uncertainty about the many ASM1-parameters in river conditions. This indicates the need for determining new typical value ranges for these parameters in a river environment.

River water quality modelling: I. State of the art

1998 ◽  
Vol 38 (11) ◽  
pp. 237-244 ◽  
Author(s):  
W. Rauch ◽  
M. Henze ◽  
L. Koncsos ◽  
P. Reichert ◽  
P. Shanahan ◽  
...  
Keyword(s):  
Water Quality ◽  
River Water ◽  
State Of The Art ◽  
Water Quality Management ◽  
Simulation Software ◽  
River Water Quality ◽  
Water Quality Modelling ◽  
Quality Models ◽  
Water Quality Models ◽  
River Water Quality Modelling

River water quality models are used extensively in research as well as in the design and assessment of water quality management measures. The application of mathematical models for that purpose dates back to the initial studies of oxygen depletion due to organic waste pollution. Since then, models have been constantly refined and updated to meet new and emerging problems of surface water pollution, such as eutrophication, acute and chronic toxicity, etc. In order to handle the complex interactions caused by the increased influence of human activities in rivers it is today mandatory to couple river water quality models with models describing emissions from the drainage and sewerage system (such as the IAWQ Activated Sludge model No. 1). In this paper-which is the first of a three-part series by the IAWQ Task Group on River Water Quality Modelling-the state of the art is summarized with the above aim in mind. Special attention is given here to the modelling of conversion processes but also the methods and tools to work with the models, i.e. parameter estimation, measurement campaign design, and simulation software, are discussed.

Identifiability analysis of the CSTR river water quality model

2006 ◽  
Vol 53 (1) ◽  
pp. 93-99 ◽  
Author(s):  
J. Chen ◽  
Y. Deng
Keyword(s):  
Water Quality ◽  
River Water ◽  
Sampling Frequency ◽  
Water Quality Model ◽  
River Water Quality ◽  
Quality Model ◽  
Identifiability Analysis ◽  
Quality Models ◽  
Observational Errors ◽  
Water Quality Models

Conceptual river water quality models are widely known to lack identifiability. The causes for that can be due to model structure errors, observational errors and less frequent samplings. Although significant efforts have been directed towards better identification of river water quality models, it is not clear whether a given model is structurally identifiable. Information is also limited regarding the contribution of different unidentifiability sources. Taking the widely applied CSTR river water quality model as an example, this paper presents a theoretical proof that the CSTR model is indeed structurally identifiable. Its uncertainty is thus dominantly from observational errors and less frequent samplings. Given the current monitoring accuracy and sampling frequency, the unidentifiability from sampling frequency is found to be more significant than that from observational errors. It is also noted that there is a crucial sampling frequency between 0.1 and 1 day, over which the simulated river system could be represented by different illusions and the model application could be far less reliable.

Similarity Metrics-Based Uncertainty Analysis of River Water Quality Models

2019 ◽  
Vol 33 (6) ◽  
pp. 1927-1945 ◽  
Author(s):  
Shirin Karimi ◽  
Bahman Jabbarian Amiri ◽  
Arash Malekian
Keyword(s):  
Water Quality ◽  
Uncertainty Analysis ◽  
River Water ◽  
River Water Quality ◽  
Similarity Metrics ◽  
Quality Models ◽  
Water Quality Models

Parameter identification of river water quality models using a genetic algorithm

2013 ◽  
Vol 69 (4) ◽  
pp. 687-693 ◽  
Author(s):  
Xiaodong Liu ◽  
Yuanyuan Zhou ◽  
Zulin Hua ◽  
Kejian Chu ◽  
Peng Wang ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Water Quality ◽  
Parameter Identification ◽  
River Water ◽  
Unsteady Flows ◽  
Water Quality Model ◽  
River Water Quality ◽  
Quality Model ◽  
Quality Models ◽  
Water Quality Models

For solving the multi-parameter identification problem of a river water quality model, analytical methods for solving a river water quality model and traditional optimization algorithms are very difficult to implement. A new parameter identification model based on a genetic algorithm (GA) coupled with finite difference method (FDM) was constructed for the determination of hydraulic and water quality parameters such as the longitudinal dispersion coefficient, the pollutant degradation coefficient, velocity, etc. In this model, GA is improved to promote convergence speed by adding the elite replacement operator after the mutation operator, and FDM is applied for unsteady flows. Moreover the influence of observation noise on identified parameters was discussed for the given model. The method was validated by two numerical cases (in steady and unsteady flows respectively) and one practical application. The computational results indicated that the model could give good identification precision results and showed good anti-noise abilities for water quality models when the noise level ≤10%.

Analysis of water pollution and evaluation of purification measures in an urban river basin

1996 ◽  
Vol 34 (12) ◽  
pp. 33-40 ◽  
Author(s):  
Y. Hosoi ◽  
Y. Kido ◽  
H. Nagira ◽  
H. Yoshida ◽  
Y. Bouda
Keyword(s):  
Water Quality ◽  
River Water ◽  
River Basin ◽  
Urban Areas ◽  
River Flow ◽  
Sea Water ◽  
Water Quality Management ◽  
River Water Quality ◽  
Urban River ◽  
Pollutant Load

The inflow of pollutant load from urban areas and the stagnation of water due to sea water intrusion cause the deterioration of river water quality in tidal zone. In order to improve water quality, various measures such as the reduction of pollutant load by sewage systems, discharge control from sewage treatment plants considering river flow, nutrient removal by aquatic plants, and the dredging of bottom sediments have been examined. The choice of these measures depends on the situation of the river environment and finances. In this study, a field survey was carried out in a typical urban river basin, first. Secondly, on the basis of this survey, a mathematical model was formed to simulate flow and water quality. Several purification alternatives designed for the investigated river basin were comparatively evaluated from the viewpoint of the effect of water quality improvement and their cost. Finally, they were prioritized. Through this case study, a planning process of river water quality management was shown.

Sign in / Sign up

Export Citation Format

Share Document