Data Analysis to Detect Inhomogeneity, Change Points, Trends in Observations: An Application to Po River Discharge Extremes

The aim of this report within GEMINA project is to outline a procedure to detect inhomogeneity, shift, and trends in observed time series. The analysis of hydrological extremes will help to gain insight in the effects at regional/local scale of climate conditions. The same approach will be used to analyze the discharge obtained from numerical simulations that will be carried on in GEMINA project. The main tests for detecting inhomogeneity, change points, and (linear) trend will be presented and the application of tests to detect change points (SNH, Pettitt, Buishand, and Von Neumann) and trend (Mann-Kendall and Spearman) to annual maximum and minimum Po river discharge at the section of Pontelagoscuro is presented. In addition, a Literature review of the applications of the same tests to climate and hydrological variables is provided.