A new method for estimating low flows in ungauged rivers from minimum discharge of perennial springs is proposed. This spring-based approach (SBA) is tested in 21 catchments from the northern Apennines, Italy. First, the hydrogeological behaviour of each geological formation and superficial deposit is related to the spatial distribution and discharge of perennial springs in a test area using a Bayesian approach, weight of evidence (WoE). Second, the observed river flow exceeded for 95% of the observation period is related to the type of geological formations outcropping within the catchment. Finally, the q95 low flows are estimated from the WoE weights. The SBA performance is assessed by leave-one-out cross-validation and compared with the results of a multiple regression (MR) model that accounts for selected catchment characteristics, but no springs. The results show that the SBA outperforms MR. The better performance of the SBA may be related to its ability to capture bedrock characteristics, which are the main controls of low flows in the study area.
Perennial springs provide information to predict low flows in mountain basins / Cervi, F.; Bloschl, G.; Corsini, A.; Borgatti, L.; Montanari, A.. - In: HYDROLOGICAL SCIENCES JOURNAL. - ISSN 0262-6667. - 62:15(2017), pp. 1-13. [10.1080/02626667.2017.1393541]
Perennial springs provide information to predict low flows in mountain basins
Corsini, A.;
2017
Abstract
A new method for estimating low flows in ungauged rivers from minimum discharge of perennial springs is proposed. This spring-based approach (SBA) is tested in 21 catchments from the northern Apennines, Italy. First, the hydrogeological behaviour of each geological formation and superficial deposit is related to the spatial distribution and discharge of perennial springs in a test area using a Bayesian approach, weight of evidence (WoE). Second, the observed river flow exceeded for 95% of the observation period is related to the type of geological formations outcropping within the catchment. Finally, the q95 low flows are estimated from the WoE weights. The SBA performance is assessed by leave-one-out cross-validation and compared with the results of a multiple regression (MR) model that accounts for selected catchment characteristics, but no springs. The results show that the SBA outperforms MR. The better performance of the SBA may be related to its ability to capture bedrock characteristics, which are the main controls of low flows in the study area.Pubblicazioni consigliate
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