Introduction

Natural hazards like floods, forest fires, and droughts result from a complex interaction between meteorological conditions, land surface characteristics and human intervention. They have a severe impact on human activities like agriculture, water resources management, and economic and social welfare. Often, these events have a spatial extent of several hundreds of kilometres and evolve according to very different temporal dynamics. Observations of such phenomena and measurements of relevant environmental parameters at the surface have to be carried out at corresponding spatial and temporal scales. However, maintaining a dense network of measuring stations is expensive and often not affordable. Therefore, frequently only few ground measurements are available from national networks in order to infer knowledge of the state of the environment for a whole region.

Understanding and describing the physical processes of energy exchange between the land surface and the atmosphere is an important pre-requisite to explain the processes behind such events and to monitor their spatial and temporal evolution. To this end, remote sensing can serve as a valuable tool for deriving uniform, spatially resolved observation data for an entire region. The derivation of accurate, quantitative surface parameters from remote sensing, however, is a complex issue and requires calibration and validation of relevant parameters with ground measurements in the area under investigation (e.g. Pinty et al., this volume).

The results described below are based on the surface energy balance model EVA (EVApotranspiration modelling), developed for the region of Sicily, Italy. In the past, Sicily has suffered from repeated drought periods with severe impacts on both the agricultural production and the natural environment. For a better management of the limited water resources of this region it is important to have a good knowledge of the moisture state of natural vegetation as well as of agricultural crops. The goal of this study, therefore, was to develop a system for monitoring the surface moisture status at the regional scale with adequate spatial and temporal resolutions (i.e. about 1 km spatial resolution and a daily time step). This system is based on a combination of remote sensing, meteorological and land surface information. Since no particular network of micrometeorological stations is run in Sicily, we had to rely on standard information from synoptic stations and on a single-date land cover classification. Remote sensing data have been introduced in order to improve the model, especially its spatial representativity. Sources of data for validation of the model results have been rather limited. This is, however, considered as typical for operational applications, where insight into complex environmental processes has often to be derived from very limited information.

Given this situation, the study also discusses the limitations in operational environmental monitoring with currently available remote sensing and meteorological data. From the results it can be seen how advanced remote sensing products will improve modelling results for regions that have not been studied in detail before.

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