Multi-model approach in flood forecasting systems and flood hazard mappreparation at the local and regional scale

As stated by the new EU flood directive “Member States should base their assessments, maps and plans on appropriate 'best practice' and 'best available technologies' ....” From an hydrological point of view this could suggest the use of the 'best model' both in the simulation of prefixed flood scenarios and in flood forecasting systems. Actually plenty of hydrological models were created and applied for this purpose in the past, especially in the last decades, but the definition of an 'optimal model' is still an unresolved problem. The multi model approach, considering a weighted combination of hydrological models to define the most probable response of the basin, might be a suitable solution. The application of this approach and its advantages were investigated in this work, focusing on the mountain areas of Northern Apennines (Italy), contributing to the Po river. To this aim, the Taro river watershed was selected as a case study. The drained area is about 2˙000 km2 wide at the junction with the Po river. In the last decade the basin has been monitored through a dense hydro-meteorological network. Distributed, semi-distributed and lumped hydrological models were used to simulate or hind-cast (using real time meteorological forecasts) the flood events that occurred during the monitoring period and their performance was measured

Hydrologic vulnerability to climate change of the Mandrone glacier (Adamello-Presanella group, Italian Alps)

In order to assess the annual mass balance of the Mandrone glacier in the Central Alps an energy- balance model was applied, supported by snowpack, meteorological and glaciological observations, together with satellite measurements of snow covered areas and albedo. The Physically based Distributed Snow Land and Ice Model (PDSLIM), a distributed multi-layer model for temperate glaciers, which was previously tested on both basin and point scales, was applied. Verification was performed with a network of ablation stakes over two summer periods. Satellite images processed within the Global Land Ice Measurements from Space (GLIMS) project were used to estimate the ice albedo and to verify the position of the simulated transient snowline on specific dates. The energy balance was estimated for the Mandrone and Presena glaciers in the Central Italian Alps. Their modeled balances (-1439 and -1503 mm w.e. yr-1, respectively), estimated over a fifteen year period, are in good agreement with those obtained with the glaciological method for the Caresèr glacier, a WGMS (World Glacier Monitoring Service) reference located in the nearby Ortles- Cevedale group. Projections according to the regional climate model COSMO-CLM (standing for COnsortium for Small-scale MOdeling model in CLimate Mode) indicate that the Mandrone glacier might not survive the current century and might be halved in size by 2050

Snow precipitation measured by gauges: Systematic error estimation and data series correction in the central Italian Alps

Precipitation measurements by rain gauges are usually affected by a systematic underestimation, which can be larger in case of snowfall. The wind, disturbing the trajectory of the falling water droplets or snowflakes above the rain gauge, is the major source of error, but when tipping-bucket recording gauges are used, the induced evaporation due to the heating device must also be taken into account. Manual measurements of fresh snow water equivalent (SWE) were taken in Alpine areas of Valtellina and Vallecamonica, in Northern Italy, and compared with daily precipitation and melted snow measured by manual precipitation gauges and by mechanical and electronic heated tipping-bucket recording gauges without any wind-shield: all of these gauges underestimated the SWE in a range between 15% and 66%. In some experimental monitoring sites, instead, electronic weighing storage gauges with Alter-type wind-shields are coupled with snow pillows data: daily SWE measurements from these instruments are in good agreement. In order to correct the historical data series of precipitation affected by systematic errors in snowfall measurements, a simple ‘at-site’ and instrument-dependent model was first developed that applies a correction factor as a function of daily air temperature, which is an index of the solid/liquid precipitation type. The threshold air temperatures were estimated through a statistical analysis of snow field observations. The correction model applied to daily observations led to 5–37% total annual precipitation increments, growing with altitude (1740 ÷ 2190 m above sea level, a.s.l.) and wind exposure. A second ‘climatological‘ correction model based on daily air temperature and wind speed was proposed, leading to errors only slightly higher than those obtained for the at-site corrections