Estimation of low-flow statistics for drought identification through regional relationships

This work focuses on rivers low flow indices on the basis of which it is possible to identify the occurrence, the extent and magnitude of the hydrological droughts that mainly affect water supply systems. Low flow characteristics are usually estimated from rivers flow gauging stations. However hydrological data are not always available at the site of interest. Regional frequency analysis is commonly used for the estimation of flow characteristics at sites where little or no data exists. L-moments applied to the 7-day annual minima and to the Q70 annual series are used to subdivide the area of study into homogeneous sub regions. Low flow indices at ungauged basins are firstly evaluated with deterministic (Inverse Weighted Distance) and geostatistical (Universal Kriging) methods. In order to improve the capability of low flow statistics in ungauged sites a multivariate modelling is also assessed. The study is applied to Tuscany rivers discharge dataset. For each catchment area upstream a gauge station, a set of geomorphoclimatic characteristics is determined. For each sub-region a novel relation connecting low flow indices and geomorphoclimatic characteristics is finally found. The results are validated using the jack-knife method. The RMSE – Root Mean Square Error and the relative error are assessed in order to compare the results, to quantify the accuracy of the different techniques and to define the most suitable procedure for low flow regionalization.