In this paper we present the results of seasonal monitoring and irrigation tests performed on an experimental farm in a semiarid region of Southern Sardinia. The goal of the study is to understand the soil–vegetation interactions and how they can affect the soil water balance, particularly in view of possible climatic changes. We used long‐term electromagnetic induction (EMI) time lapse monitoring and short‐term irrigation experiments monitored using electrical resistivity tomography (ERT) and EMI, supported by time domain reflectometry (TDR) soil moisture measurements. Mapping of natural γ‐ray emission, texture analysis, and laboratory calibration of an electrical constitutive relationship on soil samples complete the dataset. We observe that the growth of vegetation, with the associated below‐ground allocation of biomass, has a significant impact on the soil moisture dynamics. It is well known that vegetation extracts a large amount of water from the soil particularly during summer, but it also reduces evaporation by shadowing the soil surface. Vegetation represents a screen for rainfall and prevents light rainfall infiltration but enhances the wetting process by facilitating the infiltration and the ground water recharge. In many cases, the vegetation creates a positive feedback system. In our study, these mechanisms are well highlighted by the use of noninvasive techniques that provide data at the scale and resolution necessary to understand the hydrological processes of the topsoil, also in their lateral and depth spatial variability. Unlike remote sensing techniques, noninvasive geophysics penetrates the soil subsurface and can effectively image moisture content in the root zone. We also developed a simple conceptual model capable of representing the vegetation–soil interaction with a simple enough parameterization that can be fulfilled by measurements of a noninvasive nature, available at a large scale and evidences possible relevant developments of our research.

Numerous applications of hydrological models have shown their capability to simulate hydrological processes with a reasonable degree of certainty. For flood modelling, the quality of precipitation data the key input parameter is very important but often remains questionable. This paper presents a critical review of experience in the EU-funded RAPHAEL project. Different meteorological data sources were evaluated to assess their applicability for flood modelling and forecasting in the Bavarian pre-alpine catchment of the Ammer river (709 km²), for which the hydrological aspects of runoff production are described as well as the complex nature of floods. Apart from conventional rain gauge data, forecasts from several Numerical Weather Prediction Models (NWP) as well as rain radar data are examined, scaled and applied within the framework of a GIS-structured and physically based hydrological model. Multi-scenario results are compared and analysed. The synergetic approach leads to promising results under certain meteorological conditions but emphasises various drawbacks. At present, NWPs are the only source of rainfall forecasts (up to 96 hours) with large spatial coverage and high temporal resolution. On the other hand, the coarse spatial resolution of NWP grids cannot yet address, adequately, the heterogeneous structures of orographic rainfields in complex convective situations; hence, a major downscaling problem for mountain catchment applications is introduced. As shown for two selected Ammer flood events, a high variability in prediction accuracy has still to be accepted at present. Sensitivity analysis of both meteo-data input and hydrological model performance in terms of process description are discussed, drawing positive conclusions for future applications of an advanced meteo-hydro model synergy.

We report an integrated ETDM receiver for 100 Gbitls, which comprises 1:2-demultiplexing and clock & data recovery on a single chip. The ETDM receiver was tested successfully in a 100 Gbitls transmission experiment over 480 km dispersion managedfiber.

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The authors demonstrate all-optical error-free demultiplexing of 10, 20 and 40 Gbit/s to 5 Gbit/s data signals by using a monolithically integrated Mach-Zehnder interferometer with two semiconductor laser amplifiers