Fractal scaling of apparent soil moisture estimated from vertical planes of Vertisol pit images

Image analysis could be a useful tool for investigating the spatial patterns of apparent soil moisture at multiple resolutions. The objectives of the present work were (i) to define apparent soil moisture patterns from vertical planes of Vertisol pit images and (ii) to describe the scaling of apparent soil moisture distribution using fractal parameters.

Fractal scaling of apparent soil moisture estimated from vertical planes of Vertisol pit images

Image analysis could be a useful tool for investigating the spatial patterns of apparent soil moisture at multiple resolutions. The objectives of the present work were (i) to define apparent soil moisture patterns from vertical planes of Vertisol pit images and (ii) to describe the scaling of apparent soil moisture distribution using fractal parameters. Twelve soil pits (0.70 m long × 0.60 m width × 0.30 m depth) were excavated on a bare Mazic Pellic Vertisol. Six of them were excavated in April/2011 and six pits were established in May/2011 after 3 days of a moderate rainfall event. Digital photographs were taken from each Vertisol pit using a Kodak™ digital camera. The mean image size was 1600 × 945 pixels with one physical pixel ≈373 μm of the photographed soil pit. Each soil image was analyzed using two fractal scaling exponents, box counting (capacity) dimension (DBC) and interface fractal dimension (Di), and three prefractal scaling coefficients, the total number of boxes intercepting the foreground pattern at a unit scale (A), fractal lacunarity at the unit scale (Λ1) and Shannon entropy at the unit scale (S1). All the scaling parameters identified significant differences between both sets of spatial patterns. Fractal lacunarity was the best discriminator between apparent soil moisture patterns. Soil image interpretation with fractal exponents and prefractal coefficients can be incorporated within a site-specific agriculture toolbox. While fractal exponents convey information on space filling characteristics of the pattern, prefractal coefficients represent the investigated soil property as seen through a higher resolution microscope. In spite of some computational and practical limitations, image analysis of apparent soil moisture patterns could be used in connection with traditional soil moisture sampling, which always renders punctual estimates

Fractal scaling of apparent soil moisture estimated from vertical planesof Vertisol pit images

Image analysis could be a useful tool for investigating the spatial patterns of apparent soil moisture at multiple resolutions. The objectives of the present work were (i) to define apparent soil moisture patterns from vertical planes of Vertisol pit images and (ii) to describe the scaling of apparent soil moisture distribution using fractal parameters. Twelve soil pits (0.70 m long × 0.60 m width × 0.30 m depth) were excavated on a bare Mazic Pellic Vertisol. Six of them were excavated in April/2011 and six pits were established in May/2011 after 3 days of a moderate rainfall event. Digital photographs were taken from each Vertisol pit using a Kodak? digital camera. The mean image size was 1600 × 945 pixels with one physical pixel ?373 ?m of the photographed soil pit. Each soil image was analyzed using two fractal scaling exponents, box counting (capacity) dimension (DBC) and interface fractal dimension (Di), and three prefractal scaling coefficients, the total number of boxes intercepting the foreground pattern at a unit scale (A), fractal lacunarity at the unit scale (?1) and Shannon entropy at the unit scale (S1). All the scaling parameters identified significant differences between both sets of spatial patterns. Fractal lacunarity was the best discriminator between apparent soil moisture patterns. Soil image interpretation with fractal exponents and prefractal coefficients can be incorporated within a site-specific agriculture toolbox. While fractal exponents convey information on space filling characteristics of the pattern, prefractal coefficients represent the investigated soil property as seen through a higher resolution microscope. In spite of some computational and practical limitations, image analysis of apparent soil moisture patterns could be used in connection with traditional soil moisture sampling, which always renders punctual estimates.

Soil moisture content determines the effect of the urease inhibitor NBPT on N2O emissions

Among the mitigation strategies to prevent nitrogen (N) losses from ureic fertilizers, urease inhibitors (UIs) have been demonstrated to promote high N use efficiency by reducing ammonia (NH3) volatilization. In the last few years, some field experiments have also shown its effectiveness in reducing nitrous oxide (N2O) losses from fertilized soils under conditions of low soil moisture. An incubation experiment was carried out with the aim of assessing the main biotic mechanisms behind N2O emissions once that the UIs N-(n-butyl) thiophosphoric triamid (NBPT) and phenil phosphorodiamidate (PPDA) were applied with Urea (U) under different soil moisture conditions (40, 60 and 80 % water-filled pore space, WFPS). In the same study we tried to analyze to what extent soil WFPS regulates the effect of these inhibitors on N2O emissions. The use of PPDA in our study allowed us to compare the effect of NBPT with that of another commercially available urease inhibitor, aiming to see if the results were inhibitor-specific or not. Based on the results from this experiment, a WFPS (i.e. 60 %) was chosen for a second study (i.e. mesocosm experiment) aiming to assess the efficiency of the UIs to indirectly affect N2O emissions through influencing the pool of soil mineral N. The N2O emissions at 40 % WFPS were almost negligible, being significantly lower from all fertilized treatments than that produced at 60 and 80 % WFPS. When compared to U alone, NBPT+U reduced the N2O emissions at 60 % WFPS but had no effect at 80 % WFPS. The application of PPDA significantly increased the emissions with respect to U at 80 % WFPS whereas no significant effect was found at 60 %. At 80 % WFPS, denitrification was the main source of N2O emissions for all treatments. In the mesocosm study, the application of NBPT+U was an effective strategy to reduce N2O emissions (75 % reduction compared to U alone), due to a lower soil ammonium (NH4 +) content induced by the inhibitor. These results suggest that adequate management of the UI NBPT could provide, under certain soil conditions, an opportunity for mitigation of N2O emissions from fertilized soils.

The NH3-Abating effect of Slurry Injection as Influenced by Soil Moisture in a Semiarid Arable Soil

Accumulation of large volumes of dilute slurries is considered one of the major problems related to intensive farming (Sommer et al., 2004). In the EU-27, more than half of the total N excretion is applied to croplands due to technical advantages for farmers (e.g. reuse of nutrients). However, the N use efficiency of slurries produced by livestock is low, i.e. only 20-52% of the excreted N is recovered by crops. Much of the remainder can be lost into the atmosphere as ammonia (NH3), nitrous oxide (N2O), dinitrogen (N2) and nitrogen oxides (NOx).

Polarimetric SAR model for soil moisture estimation over vineyards at C-band

In this paper we propose a two-component polarimetric model for soil moisture estimation on vineyards suited for C-band radar data. According to a polarimetric analysis carried out here, this scenario is made up of one dominant direct return from the soil and a multiple scattering component accounting for disturbing and nonmodeled signal fluctuations from soil and short vegetation. We propose a combined X-Bragg/Fresnel approach to characterize the polarized direct response from soil. A validation of this polarimetric model has been performed in terms of its consistency with respect to the available data both from RADARSAT-2 and from indoor measurements. High inversion rates are reported for different phenological stages of vines, and the model gives a consistent interpretation of the data as long as the volume component power remains about or below 50% of the surface contribution power. However, the scarcity of soil moisture measurements in this study prevents the validation of the algorithm in terms of the accuracy of soil moisture retrieval and an extensive campaign is required to fully demonstrate the validity of the model. Different sources of mismatches between the model and the data have been also discussed and analyzed.

The measurement of soil moisture and density by neutron and gamma-ray scattering,

Cover title.

Soil moisture measurement with the neutron method /

Mode of access: Internet.

List and location of snow courses and soil moisture stations.

At head of title: Federal-State cooperative snow surveys and water supply forecasts.