In the present work, preliminary results are reported from an ongoing research study aimed at developing an improved prediction model to estimate the sediment yield in Italian ungauged river basins. The statistical correlations between a set of hydro-geomorphometric parameters and suspended sediment yield (SSY) data from 30 Italian rivers were investigated. The main question is whether such variables are helpful to explain the behavior of fluvial systems in the sediment delivery process. To this aim, a broad set of variables, simply derived from digital cartographic sources and available data records, was utilized in order to take into account all the possible features and processes having some influence on sediment production and conveyance. A stepwise regression analysis pointed out that, among all possibilities, the catchment elevation range (Hr), the density of stream hierarchical anomaly (Da), and the stream channel slope ratio (∆Ss) are significantly linked to the SSY. The derived linear regression model equation was proven to be satisfactory (r2-adjusted = 0.72; F-significance = 5.7 x 10- 8; ME = 0.61), however, the percentage standard error (40%) implies that the model is still affected by some uncertainties. These can be justified, on one hand, by the wide variance and, on the other hand, by the quality of the observed SSY data. Reducing these uncertainties will be the effort in the follow-up of the research. © 2018 by the authors. Licensee MDPI, Basel, Switzerland.

Investigating the sediment yield predictability in some Italian rivers by means of hydro-geomorphometric variables

Peloso, A.;Grillini, M.;Tebano, C.;Pasanisi, F.;Grauso, S.
2018

Abstract

In the present work, preliminary results are reported from an ongoing research study aimed at developing an improved prediction model to estimate the sediment yield in Italian ungauged river basins. The statistical correlations between a set of hydro-geomorphometric parameters and suspended sediment yield (SSY) data from 30 Italian rivers were investigated. The main question is whether such variables are helpful to explain the behavior of fluvial systems in the sediment delivery process. To this aim, a broad set of variables, simply derived from digital cartographic sources and available data records, was utilized in order to take into account all the possible features and processes having some influence on sediment production and conveyance. A stepwise regression analysis pointed out that, among all possibilities, the catchment elevation range (Hr), the density of stream hierarchical anomaly (Da), and the stream channel slope ratio (∆Ss) are significantly linked to the SSY. The derived linear regression model equation was proven to be satisfactory (r2-adjusted = 0.72; F-significance = 5.7 x 10- 8; ME = 0.61), however, the percentage standard error (40%) implies that the model is still affected by some uncertainties. These can be justified, on one hand, by the wide variance and, on the other hand, by the quality of the observed SSY data. Reducing these uncertainties will be the effort in the follow-up of the research. © 2018 by the authors. Licensee MDPI, Basel, Switzerland.
River sediment yield;Prediction model;Geomorphometrics;Multivariate regression analysis
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12079/4652
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