Circumpolar Scaling Layer for downscaling of Scatterometer derived soil moisture with links to geotiff images and NetCDF files (2005-01 to 2011-12)

This dataset provides scaling information applicable to satellite derived coarse resolution surface soil moisture datasets following the approach by Wagner et al. (2008). It is based on ENVISAT ASAR data and can be utilized to apply the Metop ASCAT dataset (25 km) for local studies as well as to assess the representativeness of in-situ measurement sites and thus their potential for upscaling. The approach based on temporal stability (Wagner et al. 2008) consists of the assessment of the validity of the coarse resolution datasets at medium resolution (1 km, product is the so called 'scaling layer').

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.