| Title | Investigating the Spatial Structure of Soil Hydraulic Properties in a Long-Term Field Experiment Using the BEST Methodology |
| Abstract | Abstract: Understanding the spatial structure of soil properties at field scale and introducing this
information into appropriate data analysis methods can help in detecting the effects of different soil
management practices and in supporting precision agriculture applications. The objectives of this
study were: (i) assessing the spatial structure of soil physical and hydraulic properties in a long-term
field experiment; (ii) defining a set of spatial indicators for gaining an integrated view of the studied
system. In seventy-two georeferenced locations, soil bulk density (BD), initial volumetric soil water
content (qi) and cumulative infiltration curve as function of the time (I(t)) were measured. The soil
water retention curve (q(h)) and the hydraulic conductivity function (K(h)) were then estimated using
the Beerkan Estimation of Soil Transfer parameters (BEST) methodology. The volumetric soil water
contents at soil matrix (h = ?10 cm), field capacity (h = ?100 cm) and wilting point (h = ?15,300 cm)
were considered. In addition, a set of capacitive indicators--plant available water capacity (PAWCe),
soil macroporosity (PMACe), air capacity (ACe) and relative field capacity (RFCe)--were computed.
The data were first analyzed for overall spatial dependence and then processed through variography
for structural analysis and subsequent spatial interpolation. Cross-correlation analysis allowed for
assessing the spatial relationships between selected physical and hydraulic properties. On average,
optimal soil physical quality conditions were recorded; only PMACe values were indicative of nonoptimal
conditions, whereas mean values of all the other indicators (BD, Ks, PAWCe, ACe, RFCe) fell
within optimal ranges. The exponential model was found to be the best function to describe the
spatial variability of all the considered variables, except ACe. A good spatial dependence was found
for most of the investigated variables and only BD, ACe and Ks showed a moderate autocorrelation. Ks
was confirmed to be characterized by a relatively high spatial variability, and thus, to require a more
intensive spatial sampling. An inverse spatial cross-correlation was observed between BD and Ks
up to a distance of 10 m; significant cross-correlations were also recorded between Ks and PMACe
and ACe. This result seems to suggest the possibility to use these soil physical quality indicators as
covariates in predictive multivariate approaches. |
| Source | Agronomy (Basel) |
| Keywords | beerkan estimation of soil transfer parameters (BEST) methodology; saturated hydraulic conductivity; soil physical quality; capacitive indicators; spatial autocorrelation; nugget-to-sill ratio; exponential model; cross-correlation |
| Journal | Agronomy (Basel) |
| Editor | Molecular Diversity Preservation International, Basel, |
| Year | 2022 |
| Type | Articolo in rivista |
| Authors | Stefano Popolizio 1 , Emanuele Barca 2,* , Mirko Castellini 3 , Francesco F. Montesano 1 and Anna Maria Stellacci 1 |
| Text | 474944 2022 beerkan estimation of soil transfer parameters BEST methodology; saturated hydraulic conductivity; soil physical quality; capacitive indicators; spatial autocorrelation; nugget to sill ratio; exponential model; cross correlation Investigating the Spatial Structure of Soil Hydraulic Properties in a Long Term Field Experiment Using the BEST Methodology Stefano Popolizio 1 , Emanuele Barca 2, , Mirko Castellini 3 , Francesco F. Montesano 1 and Anna Maria Stellacci 1 Department of Soil, Plant and Food Sciences, University of Bari Aldo Moro, Via Amendola 165/A, 70126 Bari, Italy 2 Water Research Institute IRSA National Research Council CNR , Viale Francesco de Blasio 5, 70132 Bari, Italy 3 Council for Agricultural Research and Economics Research Center for Agriculture and Environment CREA AA , Via C. Ulpiani 5, 70125 Bari, Italy Abstract Understanding the spatial structure of soil properties at field scale and introducing this information into appropriate data analysis methods can help in detecting the effects of different soil management practices and in supporting precision agriculture applications. The objectives of this study were i assessing the spatial structure of soil physical and hydraulic properties in a long term field experiment; ii defining a set of spatial indicators for gaining an integrated view of the studied system. In seventy two georeferenced locations, soil bulk density BD , initial volumetric soil water content qi and cumulative infiltration curve as function of the time I t were measured. The soil water retention curve q h and the hydraulic conductivity function K h were then estimated using the Beerkan Estimation of Soil Transfer parameters BEST methodology. The volumetric soil water contents at soil matrix h = 10 cm , field capacity h = 100 cm and wilting point h = 15,300 cm were considered. In addition, a set of capacitive indicators plant available water capacity PAWCe , soil macroporosity PMACe , air capacity ACe and relative field capacity RFCe were computed. The data were first analyzed for overall spatial dependence and then processed through variography for structural analysis and subsequent spatial interpolation. Cross correlation analysis allowed for assessing the spatial relationships between selected physical and hydraulic properties. On average, optimal soil physical quality conditions were recorded; only PMACe values were indicative of nonoptimal conditions, whereas mean values of all the other indicators BD, Ks, PAWCe, ACe, RFCe fell within optimal ranges. The exponential model was found to be the best function to describe the spatial variability of all the considered variables, except ACe. A good spatial dependence was found for most of the investigated variables and only BD, ACe and Ks showed a moderate autocorrelation. Ks was confirmed to be characterized by a relatively high spatial variability, and thus, to require a more intensive spatial sampling. An inverse spatial cross correlation was observed between BD and Ks up to a distance of 10 m; significant cross correlations were also recorded between Ks and PMACe and ACe. This result seems to suggest the possibility to use these soil physical quality indicators as covariates in predictive multivariate approaches. Published version Investigating the Spatial Structure of Soil Hydraulic Properties in a Long Term Field Experiment Using the BEST Methodology file pdf agronomy 12 02873 1 .pdf Articolo in rivista Molecular Diversity Preservation International 2073 4395 Agronomy Basel Agronomy Basel Agronomy Basel Agronomy. Basel emanuele.barca BARCA EMANUELE |
