Deck 4/4

Question 1

how can we manage finite water resources

Answer 1

integrated water resources management

Question 2

systems approach to water management

Answer 2

• circular
• interdisciplinary
• participatory
• practical

Question 3

circular

Answer 3

feedbacks (closed loops), nonlinearities and time delays are considered only

Question 4

interdisciplinary

Answer 4

socio-economic and natural systems are linked in one consistent framework

Question 5

participatory

Answer 5

modelers interact directly with stakeholders at all stages of the project

Question 6

practical

Answer 6

provides quantitative decision-support tools for researchers, policy-makers, and potentially the public

Question 7

systems

Answer 7

networks of positive and negative feedbacks

Question 8

all dynamics arise from?

Answer 8

the interaction of feedback loops

Question 9

modes of behaviour in a dynamic system (multiple feedbacks all interacting)

Answer 9

• exponential growth
• goal seeking (down to a threshold line)
• s shaped growth
• oscillation
• growth with overshoot (exponential an dthen wavy at the top )
• overshoot and collapse (up and then peaks and comes down)

Question 10

exponential growth

Answer 10

• caused by positive feedback
• state of the system doubles in a fixed period of time
• doubling time can be determined by the Rule of 70

Question 11

positive feedback are powerful because?

Answer 11

their rate of increase grows as the state of the system grows

Question 12

nonlinearities ____ positive feedbacks and ____ negative feedbacks until exponential growth ____

Answer 12

weaken, strengthen, stops

Question 13

when are errors large in exponential growth

Answer 13

when growth rate increases or horizon lengthens (time scale increases)

Question 14

model integration

Answer 14

two possible approaches combined into one

Question 15

“ugly” constructs

Answer 15

constructs that are perfectly valid as software products but ugly and useless as models

Question 16

challenges to model integration

Answer 16

mismatched scales, skewed geometry, overwhelming complexity, confusion of tongues (different disciplines use different terms)

Question 17

why is it important to have valid simulation models

Answer 17

conclusions are no longer valid, misleading, and potentially dangerous

Question 18

calibration

Answer 18

range in model parameters sampled until differences between the observed and simulated are minimized

Question 19

evaluating performance of the model

Answer 19

pairwise comparisons of simulated and observed values to see how well the model represents past observed data

Question 20

why evaluate performance

Answer 20

• provide quantitative estimate of ability to reproduce and predict
• provide a means for evaluating improvements to modelling approach
• compare current modelling with previous study results

Question 21

white box models

Answer 21

causal-descriptive
- represents the theory of the real system
- must reproduce the behaviour and explain how the behaviour is generated

Question 22

black box models

Answer 22

correlational
- data driven
- don’t necessarily have physical significance

Question 23

philosophical classifications of validation

Answer 23

• reductionist: valid model as an objective representation of a real system, can be corret or incorrect, validity as accuracy not usefulness
• holistic: valid model as one of many possible ways of describing a real situation, models are not correct or incorrect but lie on continuum of usefulness

Question 24

structure validity

Answer 24

direct structure tests and structure-oriented behaviour tests

Question 25

behaviour validity

Answer 25

emphasis on pattern prediction rather than point (event) prediction

Question 26

what is the goal of modelling

Answer 26

simplification

Question 27

all models are wrong
t/f

Answer 27

true, but some are useful

Question 28

linking pre-existing models can easily lead to ____ models

Answer 28

more complex