No abstract

Mediterranean vegetation is strongly subjected to the risk of wild res, which can become a major cause of land degradation. The knowledge of the spatial variations of this risk is essential, therefore, for forest resource management. Relying on the fact that diOE erent vegetation types can be associated with diOE erent risk levels, a classi cation approach based on the use of Landsat Thematic Mapper (TM) scenes is currently proposed for the generation of maps related to re risk. Hard and fuzzy classi cations were tested for this purpose on Elba island (central Italy), taking into account the eOE ects of the use of scenes from diOE erent periods (spring and summer) and of ancillary data. The re risk images obtained were evaluated by comparison with the re events that occurred on the island during the last decade. The results show that, while the acquisition period has only minor eOE ects, classi cation accuracy is strongly dependent on the inclusion of ancillary data. Moreover, the fuzzy approach better exploits the information of the integrated datasets, producing maps which are temporally stable and highly indicative of the re risk in the study area.

Abstract:In the last few years, the number of worldwide operational X-band weather radars has rapidly been growing, thanks to an established technology that offers reliability, high performance, and reduced efforts and costs for installation and maintenance, with respect to the more widespread C-and S-band systems. X-band radars are particularly suitable for nowcasting activities, as those operated by the LaMMA (Laboratory of Monitoring and Environmental Modelling for the sustainable development) Consortium in the framework of its institutional duties of operational meteorological surveillance. In fact, they have the capability to monitor precipitation, resolving very local scales, with good spatial and temporal details, although with a reduced scanning range. The Consortium has recently installed a small network of X-band weather radars that partially overlaps and completes the existing national radar network over the north Tyrrhenian area. This paper describes the implementation of this regional network, detailing the aspects related with the radar signal processing chain that provides the final reflectivity composite, starting from the acquisition of the signal power data. The network performances are then qualitatively assessed for three case studies characterised by different precipitation regimes and different seasons. Results are satisfactory especially during intense precipitations, particularly regarding what concerns their spatial and temporal characterisation.

No abstract

The current study assesses the potential of two modeling approaches to simulate the daily site water budget in Mediterranean ecosystems. Both models utilize a simplified one-bucket approach but are fed with different drivers. The first model, BIOME-BGC, simulates all main biogeochemical fluxes based on conventional meteorological and ancillary data, while the second uses evapotranspiration estimates derived from the combination of meteorological data and satellite normalized difference vegetation index (NDVI) images. The two models were tested for three Italian sites which are characterized by different vegetation types and ecoclimatic conditions: (i) low mountain coniferous forest; (ii) hilly deciduous forest; (iii) urban grassland. The soil water balance simulated by the two models was evaluated through comparison with daily measurements of soil water content (SWC) taken during a growing season. Satisfactory results were obtained in all cases by both approaches; the SWC estimates are significantly correlated with the measurements (correlation coefficient, r, higher than 0.74), and the mean errors are lower than 0.079 cm 3 cm −3. The second model, however, generally shows a higher accuracy, which is dependent on the quality of the NDVI data utilized (r higher than 0.79 and errors lower than 0.059 cm 3 cm −3). The study therefore provides useful indications for the application of these and similar simulation methods in different environmental situations.