3D Soil Images Structure Quantification using Relative Entropy

Soil voids manifest the cumulative effect of local pedogenic processes and ultimately influence soil behavior - especially as it pertains to aeration and hydrophysical properties. Because of the relatively weak attenuation of X-rays by air, compared with liquids or solids, non-disruptive CT scanning has become a very attractive tool for generating three-dimensional imagery of soil voids. One of the main steps involved in this analysis is the thresholding required to transform the original (greyscale) images into the type of binary representation (e.g., pores in white, solids in black) needed for fractal analysis or simulation with Lattice?Boltzmann models (Baveye et al., 2010). The objective of the current work is to apply an innovative approach to quantifying soil voids and pore networks in original X-ray CT imagery using Relative Entropy (Bird et al., 2006; Tarquis et al., 2008). These will be illustrated using typical imagery representing contrasting soil structures. Particular attention will be given to the need to consider the full 3D context of the CT imagery, as well as scaling issues, in the application and interpretation of this index.

Thresholding Soil Surface Images

Soil erosion is a complex phenomenon involving the detachment and transport of soil particles, storage and runoff of rainwater, and infiltration. The relative magnitude and importance of these processes depends on several factors being one of them surface micro-topography, usually quanti[U+FB01]ed trough soil surface roughness (SSR). SSR greatly affects surface sealing and runoff generation, yet little information is available about the effect of roughness on the spatial distribution of runoff and on flow concentration. The methods commonly used to measure SSR involve measuring point elevation using a pin roughness meter or laser, both of which are labor intensive and expensive. Lately a simple and inexpensive technique based on percentage of shadow in soil surface image has been developed to determine SSR in the field in order to obtain measurement for wide spread application. One of the first steps in this technique is image de-noising and thresholding to estimate the percentage of black pixels in the studied area. In this work, a series of soil surface images have been analyzed applying several de-noising wavelet analysis and thresholding algorithms to study the variation in percentage of shadows and the shadows size distribution

Evapotranspiration of grapevine trained to a gable trellis system under netting and black plastic mulching

The evapotranspiration (ET c) of a table grape vineyard (Vitis vinifera, cv. Red Globe) trained to a gable trellis under netting and black plastic mulching was determined under semiarid conditions in the central Ebro River Valley during 2007 and 2008. The netting was made of high-density polyethylene (pores of 12 mm2) and was placed just above the ground canopy about 2.2 m above soil surface. Black plastic mulching was used to minimize soil evaporation. The surface renewal method was used to obtain values of sensible heat flux (H) from high-frequency temperature readings. Later, latent heat flux (LE) values were obtained by solving the energy balance equation. For the May–October period, seasonal ET c was about 843 mm in 2007 and 787 mm in 2008. The experimental weekly crop coefficients (K cexp) fluctuated between 0.64 and 1.2. These values represent crop coefficients adjusted to take into account the reduction in ET c caused by the netting and the black plastic mulching. Average K cexp values during mid- and end-season stages were 0.79 and 0.98, respectively. End-season K cexp was higher due to combination of factors related to the precipitation and low ET o conditions that are typical in this region during fall. Estimated crop coefficients using the Allen et al. (1998) approach adjusting for the effects of the netting and black plastic mulching (K cFAO) showed a good agreement with the experimental K cexp values.