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The monitoring of a natural resource typically involves the identification of a set of parameters, considered as representative of its underlining mechanisms, in order to extract useful information about the current status and the expected behavior of the natural process. This work is focused on the water resources destined to the drinkable water distribution, by studying possible empirical relationships between meteorological parameters and groundwater quantity indices. This activity is in the wider context of a research for the development of support tools for the management of the resource under specific climate scenarios. For what regards carbonate aquifers, the impact of climate change can be very significant, given the high sensitivity of these reservoirs caused by their karst features. Data used for this study included flowrate at springs of the karst aquifer system of the Apuan Alps (northwestern Tuscany), and meteorological timeseries (both historical and synthetic scenarios) in the relevant hydrological basin. Flowrate measurements were provided by the Tuscan Water Authority (AIT) and GAIA SpA (Integrated Water Service), while synthetic meteorological scenarios were provided by Consorzio LaMMA. This work describes the data-driven approach experimented with the collected time series, essentially based on multi-variate analysis techniques and on a simplified machine learning scheme based on neural networks. In fact, a preliminary test of a data-driven approach based on Multi Layer Perceptron Neural Networks (MLP-NN) is described here. Dedicated techniques for data pre-processing, training and validation have been experimented. In particular, a strong hypothesis of linearity and time-invariance of the system under observation was done, and MLP-NNs were essentially used as non-linear approximators. A further activity regarded the assessment of a performance metric for the evaluation of multiple MLP-NNs with respect to independent test sets, based on either historical or synthetic data. Results are shown in terms of predicted flowrates in a given time window (up to 90 days in our case study), and are organized according to different scenarios of total rainfall quantity.

Italy is one of the European nations characterized by the highest levels of ultraviolet radiation (UV) therefore it was important for both the resident population and the numerous tourists to know the risk level deriving from UV exposure. Based on these considerations starting from 2004 at the Institute of Biometorology of National Reasearch Council (IBIMET-CNR), in cooperation with the LaMMA Consortium, a continuous UV monitoring activity was started. The UV monitoring station was located in Sesto Fiorentino (43° 82' N, 11° 20' E, 40 m a.s.l.), a suburb of Florence, Tuscany (Central Italy). The radiometer used was the UVB-501 (Solar Light CO., Philadelphia, USA) with spectral response close to the erythemal action spectrum, periodically compared with a reference instruments (of the same type as the operational one) calibrated during international inter-comparison campaigns. Continuous measurements of erythemally effective UV radiation (also converted in UV Index) and averaged over 15-min intervals were performed starting from 2004 and stored in a database. On the basis of these 14 years of data an UV Index climatology was obtained. During the last few decades, weather circulation type classifications (CTCs) have been widely used to gain insight into processes at the synoptic scale, but also for studying the relationship between atmospheric circulation and surface climate variability. As at LaMMA, were evaluate the best performing CTCs based on COST733 software for the stratification of daily ground-level precipitation and surface air temperature across Italy, in this study we have done a very preliminary investigation on possible relationships between UV and such CTCs; especially in certain periods of the year a relationship between specific weather circulation and UV was present.

La conoscenza del contenuto idrico del terreno (SWC) è essenziale per la comprensione di fenomeni fisici e biologici di grande importanza per le attività gestionali ed economico-produttive legate all'ambiente. Per il settore agroforestale, in particolare, SWC influenza direttamente lo stato dei vegetali, la loro crescita e produttività, sia in termini quantitativi che qualitativi, giungendo in forma indiretta, tramite l'azione sull'attività microbica e sullo stato del terreno, a condizionare gli equilibri dell'intero ecosistema. Per tale motivo, negli ultimi anni sono state sviluppate nuove metodologie per la sua misura a scale diverse, che hanno notevolmente ampliato le conoscenze teorico-pratiche, portando allo sviluppo di applicazioni d'interesse operativo. In mancanza di misure dettagliate la stima del SWC può essere effettuata tramite modelli integrati, che tengano conto delle caratteristiche fisico-chimiche dei terreni, delle condizioni meteo-climatiche e dello stato dei vegetali (crescita, densità, efficienza, ecc.). Per le componenti relativamente stabili nel tempo, come la tipologia di suolo, le informazioni possono essere reperite dagli archivi disponibili presso i vari servizi regionali, mentre per quelle più dinamiche occorre disporre di dati meteorologici aggiornati, modelli agrometeorologici affidabili e immagini ad alta definizione, raccolte con frequenza adeguata ed elaborate secondo procedure consolidate. L'integrazione di dati satellitari a media risoluzione, come Landsat e MODIS, consentono, infatti, di migliorare la rappresentatività e affidabilità delle analisi condotte localmente, estendendone l'uso ad ambiti più ampi. Anche partendo dai metodi operativi tradizionali, come quelli basati sul concetto di coefficiente colturale, Kc, l'uso integrato dei dati terrestri e satellitari consente di ottenere stime soddisfacenti anche a scale molto ampie.Su queste basi, il nostro gruppo di ricerca ha recentemente proposto un nuovo metodo di stima (chiamato NDVI-Cws) che combina l'indice di vegetazione a differenza normalizzata (NDVI) e i dati meteorologici per valutare operativamente l'evapotraspirazione reale giornaliera (ETr), sia localmente che a scala regionale. Il lavoro mostra la possibilità di combinare diversi metodi all'interno di un sistema organico di valutazione del contenuto idrico del suolo, ottenendo vantaggi significativi in termini di validità e precisione delle stime. La procedura è stata applicata su due aree di studio in Toscana, la prima in ambito tipicamente forestale (Barbialla, Montaione) e la seconda in ambito agrario, su pomodoro da industria coltivato in pieno campo (Roselle). A livello locale, i risultati ottenuti sono confrontati con le misurazioni giornaliere del contenuto d'acqua del suolo effettuate in diversi periodi. I risultati ottenuti confermano le potenzialità applicative del metodo di stima dell'ETr a partire da immagini satellitari, anche per colture irrigate nelle quali sono presenti condizioni di disomogeneità legate a una diversa copertura del campo e/o a pratiche irrigue localizzate.

Several studies have demonstrated that Monteith's approach can efficiently predict forest gross primary production (GPP), while the modeling of net ecosystem production (NEP) is more critical, requiring the additional simulation of forest respirations. The NEP of different forest ecosystems in Italy was currently simulated by the use of a remote sensing driven parametric model (modified C-Fix) and a biogeochemical model (BIOME-BGC). The outputs of the two models, which simulate forests in quasi-equilibrium conditions, are combined to estimate the carbon fluxes of actual conditions using information regarding the existing woody biomass. The estimates derived from the methodology have been tested against daily reference GPP and NEP data collected through the eddy correlation technique at five study sites in Italy. The first test concerned the theoretical validity of the simulation approach at both annual and daily time scales and was performed using optimal model drivers (i.e., collected or calibrated over the site measurements). Next, the test was repeated to assess the operational applicability of the methodology, which was driven by spatially extended data sets (i.e., data derived from existing wall-to-wall digital maps). A good estimation accuracy was generally obtained for GPP and NEP when using optimal model drivers. The use of spatially extended data sets worsens the accuracy to a varying degree, which is properly characterized. The model drivers with the most influence on the flux modeling strategy are, in increasing order of importance, forest type, soil features, meteorology, and forest woody biomass (growing stock volume).

Solar radiation affects human beings in different ways with direct effects occurring when people are exposed outdoors during working or leisure/sport activities. Erythema is the most familiar short-term symptom of human skin associated with overexposure to unperceivable ultraviolet radiation (UV). In this study the newly developed Universal Thermal Climate Index (UTCI) will be used for the first time to investigate whether the perceived outdoor heat stress might represent a valuable proxy for the unperceivable effect of UV-induced risk of erythema in a Mediterranean city, Florence, Tuscany (Central Italy). The aim of this study is therefore to propose a real approach to link solar UV radiation and thermal factors by means of the application of two internationally recognized indices, in order to estimate their reciprocal interaction and the potential impact on human health. Meteorological data and UVB (280-320 nm) measurements were obtained for the 2004-2012 period by a weather station located in the municipality of Florence. The UTCI was assessed and continuous measurements of erythemally effective UV (UVEry) were performed by means of broadband temperature-corrected radiometers with the spectral response close to the erythemal action spectrum. Hourly UVEry doses were expressed as Standard Erythemal Doses (SEDs). Descriptive analyses of the hourly distribution per month of the frequencies of days with heat stress and UVEry exceeding 2.0, 3.0, 4.5 and 6.0 SEDs were carried out based on the general skin-type characteristics. The association between UVEry and UTCI was analyzed by a two-way contingency table approach. The probability of UVEry exceeding specific SED thresholds when heat stress occurs was often significantly higher than the same probability when no heat stress is perceived. However, during several months, too many days occur without any signs of heat discomfort, even when people may be exposed to relevant doses of harmful UVEry for the skin of various phototypes. These findings underlie the need for public health authorities to provide differentiated advice per month in relation to potential UV skin damage in the city of Florence. Such specific UV information is fundamental for educating the local population and tourists and making them aware of sun exposure.

Beside some positive effects of solar UV (280-400 nm) radiation (as the stimulation of previtamin D bio-synthesis ) it is well documented the risk associated to an overexposure to UV radiation, primarily for what concern skin damages whose first step is the onset of erythema. Based on this consideration measurements of the amount of UV radiation responsible for erythema (UVery) have been initiated in many countries. Broadband sensors with a spectral sensitivity mimicking the erythema action spectrum made possible the monitoring of this parameter in continuum day after day. On the other hand satellite-derived data of total O3 and cloud cover associated with radiative transfer model output allow an assessment of daily UVery dose as reported on the web pages of the Tropospheric Emission Monitoring Internet Service, TEMIS (www.temis.nl). The objective of this study was to compare ground-based and remotely sensed daily UVery data, to analyze the frequency distribution of the daily maximum UV-Index values and the UVery doses to which outdoor workers may be exposed to. Ground based data have been recorded in Florence up to now since 2000 with a time step of 15 minutes using a broadband sensor (Solar Light 501A) periodically calibrated during various intercomparison campaigns. Daily erythemal dose have been downloaded also from the TEMIS web pages. Results indicate that daily doses of UVery remotely sensed are in good agreement with ground-based ones both when considering all the days or only those with clear sky conditions. Nevertheless TEMIS derived data resulted always higher than ground based ones and average highest difference was reached in June (0.7 KJm2 , a 15% less than satellite-derived data). Daily UV-Index maximum (UV-Imax) values analyzed according to the WHO classification reported as "protection required", "moderate" and "high" showed an occurrence respectively of 54.7%, 71.3% and 26.8% . Days classifiable as "very high" accounted for 1.9%. Results are also illustrated in terms of daily UVery doses occurring during the working hours of different months indicating the high level of UVery to which outdoor workers are exposed to respect to 30 Jm2 , the limit still proposed by ICNIRP.

La consapevolezza dei cambiamenti globali e dell'importanza delle risposte locali spingono oggi gli enti locali a giocare un ruolo attivo nella messa in opera delle strategie di adattamento e mitigazione dei cambiamenti climatici. Un requisito indispensabile per implementare politiche efficaci ed appropriate rispetto al territorio è quello di disporre di un quadro conoscitivo dettagliato. In questo contesto la Regione Toscana ha attivato, a partire dal 2004, il progetto Osservatorio Kyoto che ha come obiettivo il monitoraggio del bilancio della CO2 a scala regionale. Il bilancio fornisce uscite periodiche delle emissioni dei principali settori produttivi e degli assorbimenti operati dagli ecosistemi forestali, questi ultimi anche con cadenza trimestrale. In particolare, la misura degli assorbimenti forestali si basa su un approccio multiscala che integra misure di flusso puntuali da torri eddy covariance e da piattaforma aerea, che vengono impiegate per calibrare e validare un modello biogeochimico a scala regionale. Nel progetto è stata applicata una metodologia di misura degli assorbimenti, integrando le tecnologie di misura state-of-the-art del mondo scientifico per trasferirle in modo operativo all'Amministrazione Regionale Toscana, attraverso la redazione di un bilancio a scala comunale, consultabile ed interrogabile attraverso un'applicazione WebGIS.

L'obiettivo principale di questo lavoro è presentare una metodologia messa a punto nell'ambito del progetto "Osservario Kyoto" finanziato dalla Regione Toscana e coordinato dall'Istituto di Biometeorologia del CNR di Firenze. Tra gli obiettivi di tale progetto vi eè qeullo di quantificare i flussi netti di carbonio degli ecosistemi forestali regionali. L'area di studio infatti è costituita dal territorio della regione che, per circa metà della sua estensione, è coperto da foreste con specie sia decidue che sempreverdi. I principali dati utilizzati sono: dati meteorologici (temperature minima e massima e precipitazione giornalieri) spazializzati su tutto il territorio regionale alla risoluzione spaziale di 1 km, informazioni relative alla stazione considerata (es. profondità e tessitura dei suoli, specie forestale dominante, volume, etc.) e dati telerilevati a media risoluzione. La metodologia applicata prevede l'uso integrato di un modello parametrico, C-Fix, e di uno biogeochimico, BIOME-BGC, per ottenere stime di flusso netto dell'ecosistema (NEE). I dati prodotti sono stati confrontati con misure di NEE raccolte con tecniche eddy-covariance da torri di misura a terra e da piattaforma aerea Sky-Arrow.

Recent studies have demonstrated that accurate estimates of forest gross primary production (GPP) can be obtained by the use of a parametric model (C-Fix) which combines ground and remotely sensed data. A methodology is presented to convert these GPP estimates into values of net ecosystem exchange (NEE). It is based on the use of a process model, BIOME-BGC, which, after proper calibration, simulates all main functions of forest ecosystems at climax condition. The estimated photosynthesis and respirations are transformed into net carbon fluxes of actual forests by using a simplified approach which considers the difference between actual and potential woody biomass as an indicator of ecosystem distance from climax. The methodology was applied to all Tuscany forests for an eight-year period (1999-2006). Its validation was performed by comparing the NEE estimates to the ground data collected in San Rossore, a pine forest site for which eddy covariance measurements are available. The results obtained indicate the potential of the approach, which is finally applied to yield inputs for the analysis of forest NEE trends at regional scale.

La presente ricerca ha sviluppato e testato una metolodologia capace di simulare i principali termini che compongono il bilancio del carbonio di un ecosistema forestale (GPP, NPP, NEE) per l'intera regione Toscana. Preliminarmente sono stati raccolti dati per effettuare una caratterizzarione climatica ed ecologica delle foreste della Toscana: dati meteorolgoci spazializzati, stime mensili di FAPAR derivate da immagini VGT NDVI e dati sul tipo e volume della copertura forestale. Successivamente sono state ottenute stime mensili di GPP, NPP e NEE a condizioni climax. Queste sono poi state corrette per ottenere stime di flussi delle foreste reali, che sono state validate ocn misure raccolte a terra. I risultati della validazione indicano che la metodologia sviluppata è capace di produrre stime accurate del bilancio del carbonio forestale.

Notevole è stato negli ultimi anni lo sforzo dell'intera comunità scientifica nel valutare l'impatto dei cambiamenti climatici nel ciclo dell'acqua soprattutto a scala regionale e locale. L'interesse pratico infatti risiede a scala di bacino laddove la gestione della risorsa acqua è più critica. Questo lavoro rappresenta lo sforzo congiunto di stimare i cambiamenti climatici in atto e futuri sul bacino del fiume Arno a partire dai dati in situ, dataset globali e scenari climatici in relazione al fenomeno climatico del Monsone dell'Africa occidentale. In particolare si è cercato di caratterizzare la distribuzione di precipitazione stagionale nella sua evoluzione passata e futura.

Il presente lavoro ha lo scopo di calibrare in ambiente Mediterraneo un modello bio-geochimico (BIOME-BGC) usando un modello parametri (C-Fix) basato su profili NDVI. Quest'ultimo è in grado di stimare con buona approssimazione la Gross Primary Productivity (GPP) di un ecosistema ed è stato quindi utilizzato per la parmaetrizzazione di BIOME-BGC utilizzando questo parametro come base di confronto. Una volta calibrato e validato, BIOME-BGC è stato applicato per fornire ulteriori informazioni su Net Primary Productivity (NPP) e Net Ecosystem Exchange (NEE) delle foreste Toscane.

This paper presents a preliminary evaluation of hyperspectral data to estimate the basic forest parameters, such as LAI, that are strictly related with the relevant rnain ecophysiological processes (i.e. photosynthesis, respiration, transpiration, etc.). Additionally an application of these datato determine and quantify the carbon cycle of a pine forest has been performed. In particular, previously collected AISA images were processed and analysed to extract information on spatial LA1 variations within the study area and subsequently evaluated to determine their influence on the carbou budget assessment. The study area is a Mediterranean pine forest within the Park of San Rossore which was widely characterised during previous investigations. The results obtained showed that a correct assessment of forest carbon budget requires the correct estimation not only of ecophysiological parameters but also of forest strutture.