Decision Support for Water Resources Management

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General information

This course will use groundwater flow and transport models as an example, but the concepts are general and can be applied to all water resources models. The course will start with a revision of hydrogeological modelling theory and concepts. An example subsurface model will be introduced with a purpose of prediction and management. Model predictive uncertainty will be quantified and parameter estimation techniques will be used to inform models with measurements. Model uncertainty will be propagated all the way to economic decision criteria used in practical management. Optimization methods will be employed to find sets of Pareto-optimal decisions. Sequential decision problems will be addressed with dynamic optimization methods. The value of additional measurements will be determined from their impact on decision making. All concepts will be applied to example problems which will be solved by the students during the course in hands-on workshops.

The course material includes lecture notes, book chapters, journal articles and computer code. The preparatory reading assignment will be communicated to the students via campusnet before May 1st, 2014. As soon as possible after the evaluation of the course you will receive a course certificate in Danish and English. More information about guest PhD students that want to follow a course at DTU, is available here.

Content:

• Principles of subsurface flow and transport modeling 
• Model uncertainty 
• Sensitivity analysis 
• Parameter estimation methods 
• Model predictions and prediction uncertainty 
• Decisions under uncertainty 
• Multi-objective optimization 
• Dynamic optimization methods 
• Data value analysis

Learning outcome:

A student who has met the objectives of the course will be able to:

  • Evaluate model uncertainty and sensitivity to parameters and inputs
  • Analyze data worth, and apply parameter estimation to calibrate models
  • Synthesize uncertain model predictions with economic analyses for decision making
  • Develop tools to evaluate best (optimal) outcomes while satisfying multiple objectives
  • Analyze decisions in dynamic, or time varying problems
  • Apply the modelling concept from the course to groundwater models
Contact Person: Peter Bauer-Gottwein (pbau@env.dtu.dk)

Content

The highlighted icons, represent the fields of education (in compliance with ISCED Classification) engaged during this course/programme.

Venue

Venue: Technical University of Denmark
Lyngby, Denmark

Department of Environmental Engineering
Campus Lyngby

 

Application


Cost:
<p class="rtejustify">Guest PhD students from EU and the Nordic countries do not have to pay tuition fees although there may be fees for materials.&nbsp;There is a tuition fee for non-EC students.</p> <div>&nbsp;</div>

Prerequisites:

Participants are expected to have a background in earth/environmental science/engineering. Basic MATLAB skills and access to a MATLAB license are required. PhD students from other universities fulfil the general entry qualifications required by DTU.


Application Procedure:

Sign up with Mette Topp Hansen.

Qualification

Academic level: PhD

Assessment:

Report/dissertation


Credits:
Scheme: 
ECTS
Value: 
5
Occupations (not validated):

This course will use groundwater flow and transport models as an example, but the concepts are general and can be applied to all water resources models. The course will start with a revision of hydrogeological modelling theory and concepts. An example subsurface model will be introduced with a purpose of prediction and management. Model predictive uncertainty will be quantified and parameter estimation techniques will be used to inform models with measurements. Model uncertainty will be propagated all the way to economic decision criteria used in practical management. Optimization methods will be employed to find sets of Pareto-optimal decisions. Sequential decision problems will be addressed with dynamic optimization methods. The value of additional measurements will be determined from their impact on decision making. All concepts will be applied to example problems which will be solved by the students during the course in hands-on workshops.

The course material includes lecture notes, book chapters, journal articles and computer code. The preparatory reading assignment will be communicated to the students via campusnet before May 1st, 2014. As soon as possible after the evaluation of the course you will receive a course certificate in Danish and English. More information about guest PhD students that want to follow a course at DTU, is available here.

Content:

• Principles of subsurface flow and transport modeling 
• Model uncertainty 
• Sensitivity analysis 
• Parameter estimation methods 
• Model predictions and prediction uncertainty 
• Decisions under uncertainty 
• Multi-objective optimization 
• Dynamic optimization methods 
• Data value analysis

Application procedure: 

Sign up with Mette Topp Hansen.

Assessment: 

Report/dissertation

Attendance mode: 
Campus
Attendance pattern: 
Daytime
Cost: 
<p class="rtejustify">Guest PhD students from EU and the Nordic countries do not have to pay tuition fees although there may be fees for materials.&nbsp;There is a tuition fee for non-EC students.</p> <div>&nbsp;</div>
Duration: 
40 hours
Start/End: 
Monday, May 19, 2014 - 02:00 to Friday, May 23, 2014 - 02:00
Language of assessment: 
English
Language of instruction: 
English
Learning outcome: 

A student who has met the objectives of the course will be able to:

  • Evaluate model uncertainty and sensitivity to parameters and inputs
  • Analyze data worth, and apply parameter estimation to calibrate models
  • Synthesize uncertain model predictions with economic analyses for decision making
  • Develop tools to evaluate best (optimal) outcomes while satisfying multiple objectives
  • Analyze decisions in dynamic, or time varying problems
  • Apply the modelling concept from the course to groundwater models
Places: 
Minimum: 15, Maximum: 30
Prerequisite: 

Participants are expected to have a background in earth/environmental science/engineering. Basic MATLAB skills and access to a MATLAB license are required. PhD students from other universities fulfil the general entry qualifications required by DTU.

Study mode: 
Full time
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