Extremes: Flood risk & predictability

12 important questions on Extremes: Flood risk & predictability

What is the GRADE method? How is it different from the current method?

Current method: based on extrpolation, quite uncertain

GRADE:
  1. weather generator based on P and T for 50,000 yrs
  2. Use synthetic series as input into hydrological model ,output is Q
  3. Frequency analysis is done

What is the Generalized Likeliness UE method?

Gives an idea of uncertainty of parameters, basically a Monte-Carlo method

CHECK SLIDE

More parameter sets are accepted downstream, why?

More parameters when moving from up to downstream can describe the discharge being measured. There's less info in Q measurement moving from up to downstream. Downstream Q measurement doens't say a lot about the local Q measurement at the weir(?).

Min 19 - vague answer
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Why is the analysis in Switzerland very poorly, and good in Germany?

  • Rain data being used
  • Orography in Switzerland

Why overestimation from models (slide 21)?

HBV doesn't simulate when Q goes overbank/when floodplains are flooded.

P = exceedance probability (in a given year)
T = return period (years)

Slide 27

How do you calculate the exceedance probability?

Slide 28

Explain the stat theory of extreme values, based on the Gumbel distribution

Gumbel :
Parameters can be determined graphically(?) from measurements. Right side slide 31: fit on the Gumbel distribution.

Gumbel stems from GEV quantile function (generalized e.. Value? Dist). GEV has one degree of freedom more.

Explain the graph below (copy slide 38 without legend). How is this used for extreme Q prediction?

Min 38

How can GRADE be used for future climate prediction?

Taking climate scenarios to create weather for the future climate to get synthetic data for the analysis.

WHat is lead time?

From when threat is noticed to when you can still act on it.
..... Is when you have some modelling (min 58).

How to produce a forecast?

Meteo inputs +
initial conditions +
model (structure and parameters)

= forecast (simulation) and compare that to observations

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