Observed data are essential to understand, quantify and predict the risk posed by extreme climatic events. In the case of floods or heavy precipitation, such data take the form of long series measured at stream gauging or weather stations.
“This was a 100-year event”. This type of sentence is often heard in the news after a flood or a storm hits somewhere, as it does a good job at carrying the rarity of what happened.
In a previous post, we illustrated a widely used method called principal component analysis (PCA). This method can be used as an exploratory tool to summarise a dataset made of hundreds or thousands of time series into just a few ‘summary’ time series called principal components.
In hydrology, it is frequent to analyse long time series coming from many sites. The figure below shows monthly streamflows at 207 sites in France for the period 1969-2014.
How does water end up flowing in rivers? As schematized below, it is the result of processes that have taken place in the river basin, also known as a catchment and delineated by a red line in the figure.