Environmental flow (EF) and its variability are needed to be assessed to maintain the freshwater ecosystems and to quantify potential water supply for human and agricultural consumption. The main aim of this study is providing guidance for EF and EF variability estimation methodologies for a particular climatological environment, the Mediterranean basin, where river networks are frequently regulated. EF has been considered as the Q347discharge value. Two different methodologies have been applied, a “regression” analysis and a “frequency” analysis, and two different river basins, with regard to geological settings, have been investigated. Regression methods provide average prediction errors of about 20% and 80% for perennial and intermittent systems, respectively. Prediction errors in case of intermittent systems can be improved if climate variability is accounted for, but are larger (50%) than the case of perennial river. Coherently, the frequency analysis indicates that for poorly-drained catchments, the choice for a particular analytical distribution function could be important to correctly assess the probability of occurrences of particular Q347values and that thelargest errors (about 20%) in distributions fitting is noted for this type of river basins.

Statistical methods to quantify environmental flow and its variability in a Mediterranean environment

LONGOBARDI, Antonia;VILLANI, Paolo
2015

Abstract

Environmental flow (EF) and its variability are needed to be assessed to maintain the freshwater ecosystems and to quantify potential water supply for human and agricultural consumption. The main aim of this study is providing guidance for EF and EF variability estimation methodologies for a particular climatological environment, the Mediterranean basin, where river networks are frequently regulated. EF has been considered as the Q347discharge value. Two different methodologies have been applied, a “regression” analysis and a “frequency” analysis, and two different river basins, with regard to geological settings, have been investigated. Regression methods provide average prediction errors of about 20% and 80% for perennial and intermittent systems, respectively. Prediction errors in case of intermittent systems can be improved if climate variability is accounted for, but are larger (50%) than the case of perennial river. Coherently, the frequency analysis indicates that for poorly-drained catchments, the choice for a particular analytical distribution function could be important to correctly assess the probability of occurrences of particular Q347values and that thelargest errors (about 20%) in distributions fitting is noted for this type of river basins.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11386/4651970
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