Bernardo Gozzini

Uncertainties and trends in extreme rainfall series in Tuscany, Italy: effects on urban drainage networks design

Sound basin management at urban or greater scale needs reliable design storm definition. A statistical analysis is carried out on extreme annual rainfall series for durations of 1, 3, 6 and 12 hours occurring at two gauges in Tuscany, Italy. Kendalls test is applied to the extremal series to detect a definite increasing (or decreasing) trend. A special form of an ARIMA model is also fitted to the series to quantify possible linear trends and their respective significance. Results show a clearly increasing trend at shortest duration at both gauges, no trend at longer ones. Time evolution of design storms for all durations and return periods up to 25 years is derived and analysed based on Gumbel distribution. Applications are presented concerning impacts of uncertainties for the design of urban drainage networks.

Evaluation of empirical and semi-analytical chlorophyll algorithms in the Ligurian and North Tyrrhenian Seas

Abstract. The estimation of chlorophyll concentration in marine waters is fundamental for a number of scientific and practical purposes. Standard ocean color algorithms applicable to moderate resolution imaging spectroradiometer (MODIS) imagery, such as OC3M and MedOC3, are known to overestimate chlorophyll concentration ([CHL]) in Mediterranean oligotrophic waters. The performances of these algorithms are currently evaluated together with two relatively new algorithms, OC5 and SAM_LT, which make use of more of the spectral information of MODIS data. This evaluation exercise has been carried out using in situ data collected in the North Tyrrhenian and Ligurian Seas during three recent oceanographic campaigns. The four algorithms perform differently in Case 1 and Case 2 waters defined following global and local classification criteria. In particular, the mentioned [CHL] overestimation of OC3M and MedOC3 is not evident for typical Case 1 waters; this overestimation is instead significant in intermediate and Case 2 waters. OC5 and SAM_LT are less sensitive to this problem, and are generally more accurate in Case 2 waters. These results are finally interpreted and discussed in light of a possible operational utilization of the [CHL] estimation methods.

Improved simulation of soil water content by the combination of ground and remote sensing data

Abstract The simulation of site water balance requires the assessment of actual evapotranspiration (ETA), which is highly variable both in space and in time depending on several factors (climate, soil, vegetation). In a recent work we proposed a new method based on remotely sensed NDVI data which can estimate daily ETA operationally over large areas. The current paper utilizes these ETA estimates to drive two crop coefficient models, WinEtro and FAO56, in the prediction of soil water content (SWC). The outputs of the simulations are evaluated versus daily measurements of SWC taken in a Tuscany forest site (Barbialla) during four years. The results obtained indicate the efficiency of the proposed data combination, which improves the SWC simulations of both models examined. Recommendations are finally expressed for the possible extension and enhancement of the method described.

Combination of ground and satellite data for the operational estimation of daily evapotranspiration

Abstract A recent paper of our research group has proposed a simplified “water balance” model which predicts actual evapotranspiration (ETA) based on ground and remotely sensed data. The model combines estimates of potential evapotranspiration (ET0) and of fractional vegetation cover derived from NDVI in order to separately simulate transpirative and evaporative processes. The new method, named NDVI-Cws, was validated against latent heat measurements taken by the eddy covariance technique over various vegetation types in Central Italy. The current paper extends this validation to three other test sites in Tuscany for which reference data are obtained from different sources. In the first two sites (non-irrigated winter wheat and irrigated maize fields) seasonal reference ETA data series are obtained by the WinEtro model. In situ transpiration measurements are instead used as reference data for a deciduous oak forest stand. The ETA and transpiration estimates of the NDVI-Cws method are very similar to the reference data in terms of both annual totals and seasonal evolutions. Examples are finally provided of the model application for operationally monitoring ETA in Tuscany.

Sensitivity Analysis for Shallow Landsliding Susceptibility Assessment in Northern Tuscany

In two areas located in the north-western part of Tuscany, central Italy, Lunigiana and Garfagnana, noticeable heavy rainfall events occurred in the last years. During these events, the rainfall amounts and intensities triggered a great number of shallow landslides, causing damages, injuries and human losses. Steep slopes and deep valleys induced a persistently high relief of energy and high shallow landsliding susceptibility. In the present paper, the authors considered 4 heavy rainfall events that affected the area in 2009–2011. They carried out an analysis including a statistical modelling of spatial landslide occurrence by using Random Forest classifiers (RFc) after model selection by means of a stepwise AIC (Akaike Information Criterion) procedure. Event landslides occurrences permitted to build four event-specific RFc training sets, considering a large number of predictors reliable to characterize landslide susceptibility. Furthermore, the analysis took into account some relevant meteorological variables directly linked to the events themselves. An exploratory evaluation of the skills of a numerical weather prediction (NWP) model was conducted, to give a reliable supply to the RFc framework by using its weather forecast. For one selected event, a shallow landslide hazard model with meteorological inputs was validated. The preliminary results are shown and discussed.