Accurate Computation of a Streamflow Drought Index

In this study we investigated an approach to the calculation of a Standardized Streamflow Index (SSI) that allows accurate spatial and temporal comparison of the hydrological conditions of a stream or set of streams. For this purpose the capability of six three-parameter distributions (lognormal, Pearson type III, log-logistic, General Extreme Value, Generalized Pareto and Weibull) and two different approaches to select the most suitable distribution: the Best Monthly Fit (BMF) and the Minimum orthogonal Distance (MD), was tested using a monthly streamflow dataset for the Ebro basin (Spain). This large Mediterranean basin is characterized by high variability in the magnitude of streamflows and in seasonal regimes. The results show that the most commonly used probability distributions for flow frequency analysis provided good fits to the streamflow series. Thus, visual inspection of the L-moment diagrams and the results of the Kolmogorov-Smirnov test did not enable selection of a single optimum probability distribution. However, no single probability distribution for all the series was suitable for obtaining a robust standardized streamflow series, as each of the distributions had one or more limitations. The BMF and MD approaches provided improved results in terms of the expected average, standard deviation and frequencies of extreme events of the SSI series in relation to the selection of a unique distribution for each station. The BMF and MD approaches involved using different probability distributions for each gauging station and month of the year to calculate the SSI. Both approaches are easy to apply and they provide very similar results in terms of the quality of the obtained hydrological drought indices. The proposed procedures are very flexible for analyses involving contrasting hydrological regimes and flow characteristics.