Hydrological Hazards Flood Hazards 5-7

flood likelihood lecture 5

Extreme event probability = what is the probability of a natural event occurring?- stated as annual probability and minor floods to be more common then major floods.

OBSERVING FLOODS- the flood probability is often defined using past observations of river flow - river flow observations are often daily averaged --- this may not be the same as the flood level

two types of series of data for flood likelihood assessment= 1. Annual series - better for long series

  1. Partial duration series - for shorter series

RAIN VS FLOOD: EXTREME EVENT PROBABILITY = 25 year rain fall event is not the same of a 25 year flood event

defining probability - Annual exceedance probability = The probability that a flood will exceed a given level in any year ---- Return period (or recurrence interval) = the average frequency of occurrence of an event of a particular magnitude 1-100 year event

Consequences of climate change - as well as changing averages climate change is likely to effect extremes of distributions

RETURN PERIODS - the return period of the maximum flood in our observation will be equal to the number of years of observations plus 1
however, this is likely to be an inaccurate estimation of that events actual probability

smoothing and extrapolating = In order to estimate probabilities of more extreme events, and smooth out variability, we need to fit a model to the observed data and extrapolate

issues with flood frequency analysis - a major assumption is that the observation record should be from homogeneous conditions: this means each flood needs to occur under the same type of conditions

  • massive changes eg chch earthquakes
    -globally worlds/ cites are increasing
  • more and more people are moving into cites

flood mapping lecture 6

approaches to flood mapping - possible aims- to determine the impact area of a flood event - during event for emergency management
post-event for damage or impact assessment
mapping is best when the flood is actually happening eg-in the bad weather

mapping floods using social media - "crowdsourcing" of data
-eg publicly getting photos

using drones planes gis ect

Remote sensing - acquisition of data at some distance from the object of interest -using drones planes ect

MAPPING USING DRONES - relative recent development - drones now being used for rapid acquisition of flood impacts

MAPPING USING AERIAL IMAGERY- digital air photos acquired then georectified onto map grid, mosaicked togther

MAPPING USING SATELLITE IMAGERY- optical imagery tend to be less useful for flood mapping

SAR: the all weather solution - SAR= synthetic Radar - active remote sensing: sends out its own electronic signal rather then relying on the sun - rough areas of landscape send ack more signals then smooth areas

Flood loss estimation- pre-property damage potential estimation

flood modelling lecture 7

assessing flood risk - relate river flow and rain fall and how much flooding is actually going to happen
flood modelling can go at various different scales

Principals of flood modelling -1. a flood model is usually developed initially for a past flood event for which observational data are available.

  1. model variation the should be completed
  2. once calibrated and validated, a model can be reliably used for prediction of unseen events.

Flood inundation modelling - what can a flood inundation give us ?

  • inundation extent (what area the flood goes over)
  • inundation depth
  • flow rates
  • flood timings

flow rate which id drived from slopes and friction coefficient

Hydraulic model - breaks up the land into complicated shapes and different elevations however predicts floods in real time