Modellers and practitioners: consultants, researchers, software developers, plant managers/operators of water resource recovery facilities. Advanced knowledge on the areas of process modelling technology, data collection, handling and management is expected
This webinar discusses two common challenges in the application of modelling and integrated assessment.
The 1st topic of this webinar “Overcoming data issues in process modelling” discusses the challenges related to recognizing and obtaining good quality data. In fact, modellers spend a significant part of their time on data screening and collecting additional measurements instead of developing new models and providing solutions for process optimisation. Specific attention will be paid to typical fault patterns and the selection of proper tools for their detection.
The 2nd topic “Integrated modelling in practice” aims to discuss the barriers that are preventing the application of an integrated model for decision support in urban water management. The webinar will focus on the diverse nature of these barriers, provide some examples of potential strategies and introduce a systematic way to increase receptivity towards integrated models.
Data issues segment:
- Learning objective 1: Recognize typical fault patterns in online and offline data (e.g., outlier, offset, lack of sensitivity, drift)
- Learning objective 2: Identify the nature of available information regarding normal and abnormal data behaviour, e.g. first principles knowledge (flow or material balance, smoothness) or historical data (patterns)
- Learning objective 3: Match a typical fault pattern with a proper tool for its detection
Integrated modelling segment:
- Learning objective 1: Improve understanding of the past and present barriers to integrated model adoption in practice (e.g. model usability, policy/regulation, communication, etc.)
- Learning objective 2: Gain insight into some of the strategies used to overcome past challenges and improve current receptivity towards integrated models
- Learning objective 3: Systematically identify current major challenges for integrated model adoption in your local context and develop steps towards overcoming these.