Model-based knowledge acquisition in environmental decision support system for wastewater integrated management

2012 ◽  
Vol 65 (6) ◽  
pp. 1123-1129 ◽  
Author(s):  
Pau Prat ◽  
Lorenzo Benedetti ◽  
Lluís Corominas ◽  
Joaquim Comas ◽  
Manel Poch

The main goal of the Water Framework Directive is to achieve good chemical and ecological status of water bodies by 2015. The implementation of integrated river basin management, including sewer systems, wastewater treatment plants and receiving water bodies, is essential to accomplishing this objective. Integrated management is complex and therefore the implementation of control systems and the development of decision support systems are needed to facilitate the work of urban wastewater system (UWS) managers. Within this context, the objective of this paper is to apply integrated modelling of an UWS to simulate and analyse the behaviour of the ‘Congost’ UWS in Spain, and to optimize its performance against different types of perturbations. This analysis results in optimal operating set-points for each perturbation, improves river water quality, minimizes combined sewer overflows and optimizes flow lamination from storm water tanks. This is achieved by running Monte Carlo simulations and applying global sensitivity analysis. The set-points will become part of the knowledge base composed of a set of IF-THEN rules of the environmental decision support system being developed for this case study.

Weed Science ◽  
2015 ◽  
Vol 63 (3) ◽  
pp. 676-689 ◽  
Author(s):  
Myrtille Lacoste ◽  
Stephen Powles

RIM, or “Ryegrass Integrated Management,” is a model-based software allowing users to conveniently test and compare the long-term performance and profitability of numerous ryegrass control options used in Australian cropping systems. As a user-friendly decision support system that can be used by farmers, advisers, and industry professionals, RIM can aid the delivery of key recommendations among the agricultural community for broadacre cropping systems threatened by herbicide resistance. This paper provides advanced users and future developers with the keys to modify the latest version of RIM in order to facilitate future updates, modifications, and adaptations to other situations. The various components of RIM are mapped and explained, and the key principles underlying the construction of the model are explained. The implementation of RIM into a Microsoft Excel® software format is also documented, with details on how user inputs are coded and parameterized. An overview of the biological, agronomic, and economic components of the model is provided, with emphasis on the ryegrass biological characteristics most critical for its effective management. The extreme variability of these parameters and the subsequent limits of RIM are discussed. The necessary compromises were achieved by emphasizing the primary end-use of the program as a decision support system for farmers and advisors.


Author(s):  
Yue-Ping Xu ◽  
Martijn J. Booij

This paper describes validation of an appropriateness framework, which has been developed in a former study, to determine appropriate models under uncertainty in a decision support system for river basin management. Models are regarded as ‘appropriate’ if they produce final outputs within adequate uncertainty bands that enable decision-makers to distinguish or rank different river engineering measures. The appropriateness framework has been designed as a tool to stimulate the use of models in decision-making under uncertainty and to strengthen the communication between modelers and decision-makers. Through the application to a different river with different objectives in this validation study from the river used in the development stage, this paper investigates whether the appropriateness framework works in a different situation than it was designed for. Recommendations from the development stage are taken into account in this validation case study as well. The final results from the study showed a successful validation of the appropriateness framework and suggested further possibilities for the application in decision support systems for river basin management.


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