SENSITIVITY ANALYSIS OF SOIL HYDROLOGICAL BEHAVIOR AT FIELD-SCALE: A STOCHASTIC APPROACH APPLIED TO MEASURED AND ESTIMATED HYDRAULIC PROPERTIES (Abstract/Poster in convegno)

Type
Label
  • SENSITIVITY ANALYSIS OF SOIL HYDROLOGICAL BEHAVIOR AT FIELD-SCALE: A STOCHASTIC APPROACH APPLIED TO MEASURED AND ESTIMATED HYDRAULIC PROPERTIES (Abstract/Poster in convegno) (literal)
Anno
  • 2013-01-01T00:00:00+01:00 (literal)
Alternative label
  • P. Manna,(1) A. Basile(2), A. Bonfante(2), A. Coppola(3), R. De Mascellis(2), G. Langella(2), F. Terribile(1) (2013)
    SENSITIVITY ANALYSIS OF SOIL HYDROLOGICAL BEHAVIOR AT FIELD-SCALE: A STOCHASTIC APPROACH APPLIED TO MEASURED AND ESTIMATED HYDRAULIC PROPERTIES
    in International Conference on Monitoring and Modeling Soil-Plant-Atmosphere Processes, Naples (Italy), 19-21 June 2013
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • P. Manna,(1) A. Basile(2), A. Bonfante(2), A. Coppola(3), R. De Mascellis(2), G. Langella(2), F. Terribile(1) (literal)
Note
  • Poster (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • (1) Department of Agriculture, University of Napoli Federico II, Italy. (2) Institute for Agricultural and Forestry Systems in the Mediterranean, National Research Council of Italy (CNR). (3) Department of European Cultures and the Mediterranean: Architecture, Environment, Cultural Heritage - Hydraulic Section - Univ. of Basilicata, Italy. (literal)
Titolo
  • SENSITIVITY ANALYSIS OF SOIL HYDROLOGICAL BEHAVIOR AT FIELD-SCALE: A STOCHASTIC APPROACH APPLIED TO MEASURED AND ESTIMATED HYDRAULIC PROPERTIES (literal)
Abstract
  • Soil water processes control soil hydrological behavior in the vadose zone at a wide range of scales. At local scale, flux and storage of water in the unsaturated zone is adequately described by the classical nonlinear Richards' equation. Extrapolating the theory to a larger-scale system for modeling field-scale water flows is ordinary practice (scale-invariant equation) but its application set two major and strictly related problems; namely (i) the characterization and parameterization of soil hydraulic properties and (ii) their inherent variability at the field scale. In order to address the first issue, the soils hydraulic properties are typically derived either through expensive laboratory and/or field experiments or with alternative approaches like pedotranfer functions in order to increase cost effectiveness. On the other side the variability of soil hydraulic properties at the field scale can be treated by a feasible approach, considering soils in the field as an ensemble of parallel and statistically independent tubes, assuming only vertical flows. Each stream tube defines local flow properties that are assumed to vary randomly between the different stream tubes. We used the Monte Carlo technique, which treats any uncertain parameter as a random variable that obeys a given probabilistic distribution, for analyzing soil hydraulic properties probabilistic uncertainty (second issue). The goals of this work, placed at the core of the issues (i) and (ii), are the following: o recognize the sensitivity of a Richard-based model to the measured variability of ?(h) and k(?) parameters; o establish the predictive capability and effectiveness of PTFs by using measured data and independent and spatially distributed information (NDVI) as data quality control. The study area is located in the Po plain (Lodi) in Northern Italy and it has an extension of approximately 2000 hectares; most of the area has corn land use. A considerable number (about 100) of topsoil sample sites, throughout the whole study site, were identified for hydropedological analysis. All samples were analyzed for texture, bulk density, organic matter content and other chemical properties, and for about 60 samples water retention curves and saturated hydraulic conductivities were determined and parameterized following the Mualem-van Genuchten functional relationships. Several pedotransfer functions were tested on the 60 measured hydraulic properties; then the PTF HYPRES was applied to derive hydraulic properties of the entire soil database. The data from the PTF showed a good agreement with the measured one and, as expected, a smoothing effect was recognized. Furthermore, a site was also settled within the area, for continuous monitoring of soil water variables for model calibration and validation. The model was applied and the Monte Carlo approach was used to analyze the sensitivity of the applied model to two measured input parameters: the slope of water retention curve (n) and the saturated hydraulic conductivity (k0). The analysis was performed singularly for each parameter and jointly for both. The analysis has shown that the \"n\" parameter affects the variability of the process simulated to an extent significantly higher than the k0 parameter, although the former is much less variable. Despite only slight differences arise between measurements and estimated data, the sensitivity analysis of the applied model underline the absolute need for a correct assessment of the \"n\" parameters. In fact, while direct and significant correlations were found between the \"n\" hydraulic parameter obtained from measured water retention curves and the NDVI (Normalized Difference Vegetation Index) using high resolution remotely sensed data on maize cultivation, this relationship does not occur with estimated water retention curves. (literal)
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