2. Precipitation

Question 1

Measurement errors for point observations and magnitude:

Answer 1

1. Wind induced error
2. Losses from surface wetting
3. Evaporation from collectors

10-20% for rainfall
about 25% for snow

Question 2

Method for correction of the systematic error:

Answer 2

Richter method in Germany.

Internationally different approaches (e.g. Sevruk)

Question 3

When do we have to correct the error?

Answer 3

Water balance and continuous modelling -> always required!

Extremes and event based modelling -> not mandatory.

Question 4

Methods for areal precipitation:

Answer 4

• Aritmetic mean
• Thiessen-Polygon
• Inverse-Distance method
• Isohytal method
• Geostatistical methods

Question 5

Methods for estimation of design rainfall

Answer 5

• Design storm approach: using single events

- Derived flood frequency approach: using continuous rainfall

Question 6

Resulted graphs from statistics to derive design storms

Answer 6

Depth-Duration-Frequency curve (DDF)

Intensity-Duration-Frequency curve (IDF)

Question 7

What are the most important advantages of recording gauges compared to non-recording gauges?

Answer 7

• Higher temporal resolution

- Remote transmission for digital recording gauges possible.

Question 8

What is the time of concentration?

Answer 8

Time after the whole catchment contributes to the flood hydrograph.

Question 9

Objectives of the precipitation models

Answer 9

Forecast: real-time, flood warning

Simulation: input for rainfall-runoff models (planning and design, impact analysis.

Question 10

What are deterministic models and examples

Answer 10

Physically based weather prediction models
Focus on large scale weather, rainfall quite uncertain
Forecast: NWP - Numerical Weather Prediction Model
Simulation: GCM/ RCM – Global/ Regional climate models

Question 11

what are stochastic models and examples

Answer 11

Based on statistical laws
Forecast: e.g. MOS – Model Output Statistics (correction of RCM)
Simulation: many methods, keeping most relevant statistical
properties of rainfall process according to wanted application

Question 12

General classification of stochastic models

Answer 12

1. Single site: for one station
2. Multisite: for several stations
3. Multidimensional: space-time
4. Occurrence only; amount only;
   occurrence and amount

Question 13

Classification after the method of stochastic models:

Answer 13

I. Alternating-Renewal-Modelle (ARP)
II. Time series models: -Markov -chains (MC)
-Auto regression-Moving-Average-Models (ARMA)
III. Point process models
IV. Disaggregation models
V. Resampling models