In the last decade the north of Italy suffered a marked hydrologic deficit as a consequence of decreasing mean annual precipitation and increasing demand from industry and agriculture. Rivers that outflow from the northern Appennines display an highly variable discharge rate that is due to inherited hydro-geological factors such as the prevalence in the mountain catchments of low permeability sedimentary rocks with low storage coefficient. The growing interest for a proper management of water courses, that has led to directives regulating the amount of minimum water that must permanently flow downstream from points of water diversions and yield, makes the prediction of hydrological indexes in ungauged basins located in the mountain areas of relevant practical importance, since it can support a sustainable planning of surface water management along the entire water course. The research has being aimed at developing a spatial analysis tool for regional-scale prediction of hydro-geological indexes in ungauged basins, that still represent the majority of cases in the upper catchment areas in the northern Appennines. This has been dealt with by linking statistical indexes of discharge calculated for gauged basins (Q95, Q7_10, Q355), to the results of spatial analysis methods (such as Weight of Evidence, Logistic Regression, Neural Networks) that allow the storage coefficient of different bedrock types to be relatively ranked by using the spatial distribution of permanent groundwater springs as main supporting evidence. The presentation summarises the main results obtained and validated in three test basis within the whole study area.
Regional-Scale prediction of hydrological indexes in ungauged basins with low-permeability sedimentary rocks8
CERVI, FEDERICO;BORGATTI, LISA;
2008
Abstract
In the last decade the north of Italy suffered a marked hydrologic deficit as a consequence of decreasing mean annual precipitation and increasing demand from industry and agriculture. Rivers that outflow from the northern Appennines display an highly variable discharge rate that is due to inherited hydro-geological factors such as the prevalence in the mountain catchments of low permeability sedimentary rocks with low storage coefficient. The growing interest for a proper management of water courses, that has led to directives regulating the amount of minimum water that must permanently flow downstream from points of water diversions and yield, makes the prediction of hydrological indexes in ungauged basins located in the mountain areas of relevant practical importance, since it can support a sustainable planning of surface water management along the entire water course. The research has being aimed at developing a spatial analysis tool for regional-scale prediction of hydro-geological indexes in ungauged basins, that still represent the majority of cases in the upper catchment areas in the northern Appennines. This has been dealt with by linking statistical indexes of discharge calculated for gauged basins (Q95, Q7_10, Q355), to the results of spatial analysis methods (such as Weight of Evidence, Logistic Regression, Neural Networks) that allow the storage coefficient of different bedrock types to be relatively ranked by using the spatial distribution of permanent groundwater springs as main supporting evidence. The presentation summarises the main results obtained and validated in three test basis within the whole study area.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
