1,177 research outputs found
Discriminating low frequency components from long range persistent fluctuations in daily atmospheric temperature variability
No full textThis study originated from recent results reported in literature, which support the existence of long-range (power-law) persistence in atmospheric temperature fluctuations on monthly and inter-annual scales. We investigated the results of Detrended Fluctuation Analysis (DFA) carried out on twenty-two historical daily time series recorded in Europe in order to evaluate the reliability of such findings in depth. More detailed inspections emphasized systematic deviations from power-law and high statistical confidence for functional form misspecification. Rigorous analyses did not support scale-free correlation as an operative concept for Climate modelling, as instead suggested in literature. In order to understand the physical implications of our results better, we designed a bivariate Markov process, parameterised on the basis of the atmospheric observational data by introducing a slow dummy variable. The time series generated by this model, analysed both in time and frequency domains, tallied with the real ones very well. They accounted for both the deceptive scaling found in literature and the correlation details enhanced by our analysis. Our results seem to evidence the presence of slow fluctuations from another climatic sub-system such as ocean, which inflates temperature variance up to several months. They advise more precise re-analyses of temperature time series before suggesting dynamical paradigms useful for Climate modelling and for the assessment of Climate Change
TEMPORAL PERSISTENCE IN VEGETATION COVER CHANGES OBSERVED FROM SATELLITE: DEVELOPMENT OF AN ESTIMATION PROCEDURE IN THE TEST SITE OF THE MEDITERRANEAN ITALY
No full textComment on "Variations in northern vegetation activity inferred from satellite data of vegetation index during 1981 to 1999" by L. Zhou et al.
No full textWatershed influence on fluvial ecosystems: a methodology for river water quality management
No full textThe EU Water Framework Directive 2000/60 (Integrated River Basin Management for Europe) establishes the importance of preserving water quality through policies applied at watershed level given the strong links existing among ecological, hydrological, and hydrogeological systems. Therefore, monitoring campaigns of river water quality should be planned with multidisciplinary approaches starting from a landscape perspective. In this paper, the effects of the basin hydrology on the river water quality and, in particular, the impacts caused by the runoff production coming from agricultural areas are investigated. The fluvial segments receiving consistent amount of pollutant loads (due to the runoff routing over agricultural areas) are assumed more critical in terms of water quality and thus, they require more accurate controls. Starting from this perspective, to evaluate the runoff productions coming from agricultural areas, we applied a semi-distributed hydrological model that adopts satellite data, pedological and morphological information for the watershed description. Then, the river segments receiving critical amount of runoff loads from the surrounding cultivated areas were identified. Finally, in order to validate the approach, water quality for critical and non critical segment was investigated seasonally, by using river macroinvertebrates as indicators of water quality because of their effectiveness in preserving in time a memory of pollution events. Biomonitoring data showed that river water quality strongly decreases in correspondence of fluvial segments receiving critical amount of runoff coming from agricultural areas. The results highlight the usefulness of such a methodology to plan monitoring campaigns specifically devoted to non-point pollution sources and suggest the possibility to use this approach for water quality management and for planning river restoration policies
Identification of homogeneous phenological patterns for the characterization of vegetation recovery times on climatic scales
No full text
Assessment of spatially distributed values of Kc using vegetation indices derived from medium resolution satellite data
No full textIn the last years, the theme of suitable assessment of irrigation water supply has been raised relevant interest
for both general principles of sustainable development and optimization of water resources techniques and
management. About 99% of the water used in agriculture is lost by crops as evapotranspiration (ET). Thus, it
becomes crucial to drive direct or indirect measurement in order to perform a suitable evaluation of water loss by
evapotranspiration (i.e. actual evapotranspiration) as well as crop water status and its effect on the production.
The main methods used to measure evapotranspiration are available only at field scale (Bowen ratio, eddy
correlation system, soil water balance) confined to a small pilot area, generally due to expense and logistical
constraints. This led over the last 50 years to the development of a large number of empirical methods to estimate
evapotranspiration through different climatic and meteorological variables as well as combining models, based
on aerodynamic theory and energy balance, taking into account both canopy properties and meteorological
conditions. Among these, the Penman-Monteith equation seems to give the best results providing a robust and
consistent method world wide accepted.
Such conventional methods only provide accurate evapotranspiration assessment for a homogeneous region nearby
the meteorological gauge station and cannot be extrapolated to other different sites; whereas remote sensing
techniques allow for filling up such a gap. Some of these satellite techniques are based on the use of thermal band
signals as inputs for energy balance equations. Another common approach is mainly based on the FAO method
for estimating crop evapotranspiration, in which evapotranspiration data are multiplied by crop coefficients, Kc,
derived from satellite multispectral vegetation indices obtained. The rationale behind such a link considers that Kc
and vegetation indices are sensitive to both leaf area index and fractional ground cover.
Thermal-based energy balance models are more suitable than the FAO-Kc model for estimating crop ET, especially
under moisture stress conditions, but they require many inputs and detailed theoretical background knowledge;
so they can be only used in regions where high quality, hourly agricultural weather data are readily available
providing instantaneous values of heat fluxes corresponding to the time of the satellite overpass. Thus, FAO-Kc
approach is widely used in research activities and real-time irrigation scheduling for several water applications
since it does not require temporal upscaling for obtaining daily values and satellite imagery in the reflective bands
used for vegetation index computation are more readily available at higher spatial resolution than thermal band
data.
There is no simple way to compute crop coefficients because they depend on climate, soil type, crop and its
varieties, irrigation method, soil water, nutrient content and plant phenology. Consequently, specific calibrations
of crop coefficient are required in various climatic regions. Many authors suggested a linear relationship between
Kc and vegetation indices, but non-linear relationships have been proposed too. However, according to the
radiative transfer theory, the nature of such relationships depends on the crop architecture and the definition of
the adopted vegetation index, but the linear assumption can be adopted as first. Such studies, mainly investigated
the possibility to use high resolution satellite data, such as Quickbird, Ikonos, TM, which are not suitable for
operational purposes since in spite of the high spatial sampling they have an inadequate revisiting time over a
given area. To obtain adequate temporal sampling, some authors proposed the use of a virtual constellation made
by all currently available high-resolution satellites (e.g., DEMETER project). However the joint use of data from
different satellites requires a carefully inter-satellite cross-calibration and co-registration.
In order to avoid such problems and to generate spatially distributed values of Kc capturing field-specific crop
development, the employment of vegetation indices derived from medium resolution MODIS data having a
higher temporal sampling has been investigated. The spatial and temporal correlation between NDVI (Normalized
Difference Vegetation Index) and crop coefficients for different herbaceous and arboreal cultivations has been
investigated to define their relationships. Through this approach site-specific crop coefficients were derived taking
into account the effective ground coverage and status. The analysis has been applied on the 2005-2008 time series
for the Basilicata region, Southern Italy
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