An approach to propagate streamflow statistics along the river network

Abstract

Streamflow at ungauged sites is often predicted by means of regional statistical procedures. The standard regional approaches do not preserve the information related to the hierarchy among gauged stations deriving from their location along the river network. However, this information is important when estimating runoff at a site located immediately upstream or downstream of a gauging station. We propose here a novel approach, referred to as the Along-Stream Estimation (ASE) method, to improve runoff estimation at ungauged sites. The ASE approach starts from the regional estimate at an ungauged (target) site, and corrects it based on regional and sample estimates of the same variable at a donor site, where sample data are available. A criterion to define the domain of application around each donor site of the ASE approach is proposed, and the uncertainty inherent in the estimates obtained is evaluated. This allows one to compare the variance of the along-stream estimates to that of other models that eventually become available for application (e.g. regional models), and thus to choose the most accurate method (or to combine different estimates). The ASE model was applied in the northwest of Italy in connection with an existing regional model for flood frequency analysis. The analysed variables are the first L-moments of the annual discharge maxima. The application demonstrates that the ASE approach can be used effectively to improve the regional estimates for the L-moment of order one (the index flood), particularly when the area ratio of a pair of donor–target basins is less than or equal to ten. However, in this case study, the method does not provide significant improvements to the estimation of higher-order L-moments. Editor D. Koutsoyiannis; Associate editor S. Grimaldi Citation Ganora, D., Laio, F., and Claps, P., 2013. An approach to propagate streamflow statistics along the river network. Hydrological Sciences Journal, 58 (1), 1–13.