The Role of Real-Time Forecasting and Control in Water Quality Management

The traditional view of water quality management in a river basin concerns itself with determining an optimal allocation of capital investment in facilities for storage and treatment of water and wastewater. If these investments do not permit the desired water quality standards to be achieved, it is usual to question, for example, whether the treatment plant configuration was correctly designed in the first place with the appropriate contaminant removal technologies. It is not common practice at the "design" stage of water quality management to consider how the system will perform at the "operational" stage of management. Neither is it customary, when standards are not met, to ask whether the design/operational requirements are incompatible, and to enquire whether standards could not in fact be achieved, if the system were to be operated more effectively. About five or six years ago the first few articles on river water quality control began to appear in the literature of control theory. It has been a relatively easy exercise to show that, in principle, many aspects of river water quality -- better to say, river water quality models -- are amenable to the techniques of real-time control system synthesis. But that does not resolve the major practical issues of day-to-day operation in water quality management. Thus, more recently, it has been evident that on-line instrumentation and especially the use of the information so derived for management decisions, is receiving more detailed attention. Again, in principle, algorithms are available for real-time estimation, forecasting, and associated on-line data analysis. It has also been duly recognised, in view of the lack of operating flexibility in pollutant removal unit processes, that for river water quality control the storage and manipulation of flows, be they sewage discharges, stream discharges, or flows routed through treatment plants, is vitally important. But these considerations do not resolve the issues of whether real-time forecasting and control are desirable, inevitable, or necessary. This paper takes another step backwards from the original control theoretic approaches to river water quality control. It is apparent, for instance, that laws, economics and institutions all partly determine the nature of technological innovation in the water and wastewater industries. That, then, is the more "macroscopic" environment in which the paper examines the relevance of real-time forecasting and control to river water quality management. It would be of great benefit to the author if the reader would be generous enough to offer his criticisms of the discussion. In this way the arguments will become clearer, more relevant and more coherent

Applications of System Identification and Parameter Estimation in Water Quality Modeling

Applications of techniques of system identification and parameter estimation in water quality modeling are surveyed. This survey of the literature covers three areas: river water quality, lake water quality, and wastewater treatment plant modeling. The applications cited are classified according to the type of algorithm used for calibration, the type of model, and the field data used. Two broad distinctions are made between: (a) off-line and recursive methods of parameter estimation; and (b) internally descriptive (state-space) and black box (input/output) model types. In order to assist the classification, a number of estimation algorithms are very briefly introduced. Although there are clearly different lines of development in each area of water quality modeling, it is possible to identify problems common to all three areas. The major problems discussed concern the availability of field data, levels of noise in the data, and model structure identification

Time-Variable Water Quality Management - A Policy Study

Interactions between the long-term (planning) and short-term (operational) functions of stream water quality management are considered in this paper. It is argued that the problems and, therefore, the strategies of water quality management do not remain constant with time. In particular, the paper identifies what may be an important change of emphasis in water quality management from the essentially curative strategy of the past 20-30 years to a preventive strategy for the coming years. This change of emphasis suggests that more attention in research and development should be given to matters associated with the operational aspects of management. The analysis of the paper is undertaken from several different perspectives, for example, from the perspectives of economics, innovation, legislation, and institutional arrangements. The areas in which interaction between long-term and short-term management is likely to be most pronounced are: in changing the way in which water quality can be monitored, and thus in changing the way in which water quality objectives can be specified; and in increasing the range of options available to management

Mathematical Modeling of Water Quality: Summary Report of a IIASA Workshop, September 13-16, 1977

This report summarizes the proceedings of an IIASA Workshop on Water Quality Modeling held at Laxenburg, Austria, September 13-16, 1977. The Workshop was held as an initial activity within IIASA's research Task on Models for Environmental Quality Control and Management. In convening the Workshop, the organizers invited participants to express their views on the current state of mathematical modeling of water quality. They were also encouraged to speculate on future directions for the subject and to make recommendations for the ways in which such research could be organized in collaboration with IIASA. The report on the Workshop divides broadly into two sections: the first deals with key themes and salient problems of water quality modeling; the second reproduces the concluding statements of nine ad hoc working groups established during the Workshop. These working groups considered a number of specific areas such as deep lakes and reservoirs, the impact of toxic pollutants, systems methods in model development and analysis, and so forth. An intermediate section of the report looks briefly as future perspectives in water quality modeling, and in the final section particular reference is made to the Institute's plans for water quality model development and application in particular case studies

Real-Time Control of Water Quality and Quantity

The paper considers the application of estimation, forecasting, and control techniques to the problem of combined real-time control of stream discharge and water quality in a river basin. A simple recursive estimation procedure is presented for the on-line estimation of pollutant movement and dispersion in a reach of a river. Some important features of the linear multivariable control system design problem are then considered in the context of controlling downstream discharge and quality given an upstream effluent discharge and surface storage facility as input control variables. Because of the very basic difficulties of visualizing water quality regulation according to most conventional control engineering approaches, a final section of the paper offers a speculative examination of the possibilities for fuzzy control applications in operational river basin management

Model Structure Identification: Development and Assessment of a Recursive Prediction Error Algorithm

The paper aims to develop a more systematic approach to the problem of model structure identification for continuous time (physically based) mathematical models with discrete observations. An introduction to the model structure identification problem is first presented. The approach to this problem is the application of a modified version of the extended Kalman filter, originally defined in [23]. This filter is tested using artificial data. The results obtained lead to a further discussion of the filter's stability properties and also to a metaphor for model structures. Further study of the numerical properties of the algorithm reveal that its stability can be improved. An alternative algorithm, the so called recursive prediction error algorithm, is modified to a Kalman-like algorithm in continuous-discrete formulation. This algorithm is also tested using artificial data. The RPE-type of filter has better stability properties and appears to be very robust to initial conditions. Its applicability to environmental case studies is set out through the application of the filter to a familiar case study. Applications of this type of filter is valuable for validation/verification of environmental and/or economical models that include a set of ordinary differential equations

Coping with change: urban resilience, sustainability, adaptability and path dependence. Future of cities: working paper

Comprises output from the Foresight future of cities project looking at the opportunities and challenges facing cities over the next 50 years. Specifically looks at how solutions can be found to complex problems faced by cities by allowing conflicting voices to be heard and by not imposing a single consensus or measure of success. Also considers how these methods affect our understanding of urban resilience, sustainability, adaptability and 'path dependence'

No Primordial Magnetic Field from Domain Walls

It is pointed out that, contrary to some claims in the literature, the domain walls cannot be a source of a correlated at large scales primordial magnetic field, even if the fermionic modes bound on the wall had ferromagnetic properties. In a particular model with massive (2+1) dimensional fermions bound to a domain wall, previously claimed to exhibit a ferromagnetic behavior, it is explicitly shown that the fermionic system in fact has properties of a normal diamagnetic with the susceptibility vanishing at high temperature.Comment: 8 pages. Modified discussion of the baryon density on an axion domain wal

Modelling and Operational Control of the Activated Sludge Process in Wastewater Treatment

A report is presented on a collaborative study of dynamic modelling and control of the activated sludge process in wastewater treatment. The report divides into four major parts, the first of which presents and discusses the time-series of field data from the Norwich Sewage Works in England. The second part of the paper is concerned with the identification of a model for nitrification in the activated sludge process from the given field data; the technique used for this purpose is an extended Kalman filtering algorithm. A third section deals with the construction of a detailed simulation model which has been used for control system design and evaluation. The final major part of the report introduces some basic ideas of fuzzy control, suggests why conventional control schemes may be of limited value in wastewater treatment systems, and proceeds to define a fuzzy controller developed from the empirical experience of the Norwich Treatment Plant manager. The paper also offers some thoughts on future perspectives for the study and for the use of mathematical models as aids to the operational control of wastewater treatment