On the diurnal soil water content dynamics during evaporation using dielectric methods

The water content dynamics in the upper soil surface during evaporation is a key element in land-atmosphere exchanges. Previous experimental studies have suggested that the soil water content increases at the depth of 5 to 15 cm below the soil surface during evapo- ration, while the layer in the immediate vicinity of the soil surface is drying. In this study, the dynamics of water content profiles exposed to solar radiative forcing was monitored at a high temporal resolution using dielectric methods both in the presence and absence of evaporation. A 4-d comparison of reported moisture content in coarse sand in covered and uncovered buckets using a commercial dielectric-based probe (70 MHz ECH2O-5TE, Decagon Devices, Pullman, WA) and the standard 1-GHz time domain reflectometry method. Both sensors reported a positive correlation between temperature and water content in the 5- to 10-cm depth, most pronounced in the morning during heating and in the afternoon during cooling. Such positive correlation might have a physical origin induced by evaporation at the surface and redistribution due to liquid water fluxes resulting from the temperature- gradient dynamics within the sand profile at those depths. Our experimental data suggest that the combined effect of surface evaporation and temperature-gradient dynamics should be considered to analyze experimental soil water profiles. Additional effects related to the frequency of operation and to protocols for temperature compensation of the dielectric sensors may also affect the probes' response during large temperature changes.

Robust Nonlinear Mapping of Soil Contamination Using Support Regression

Spatial data analysis mapping and visualization is of great importance in various fields: environment, pollution, natural hazards and risks, epidemiology, spatial econometrics, etc. A basic task of spatial mapping is to make predictions based on some empirical data (measurements). A number of state-of-the-art methods can be used for the task: deterministic interpolations, methods of geostatistics: the family of kriging estimators (Deutsch and Journel, 1997), machine learning algorithms such as artificial neural networks (ANN) of different architectures, hybrid ANN-geostatistics models (Kanevski and Maignan, 2004; Kanevski et al., 1996), etc. All the methods mentioned above can be used for solving the problem of spatial data mapping. Environmental empirical data are always contaminated/corrupted by noise, and often with noise of unknown nature. That's one of the reasons why deterministic models can be inconsistent, since they treat the measurements as values of some unknown function that should be interpolated. Kriging estimators treat the measurements as the realization of some spatial randomn process. To obtain the estimation with kriging one has to model the spatial structure of the data: spatial correlation function or (semi-)variogram. This task can be complicated if there is not sufficient number of measurements and variogram is sensitive to outliers and extremes. ANN is a powerful tool, but it also suffers from the number of reasons. of a special type ? multiplayer perceptrons ? are often used as a detrending tool in hybrid (ANN+geostatistics) models (Kanevski and Maignank, 2004). Therefore, development and adaptation of the method that would be nonlinear and robust to noise in measurements, would deal with the small empirical datasets and which has solid mathematical background is of great importance. The present paper deals with such model, based on Statistical Learning Theory (SLT) - Support Vector Regression. SLT is a general mathematical framework devoted to the problem of estimation of the dependencies from empirical data (Hastie et al, 2004; Vapnik, 1998). SLT models for classification - Support Vector Machines - have shown good results on different machine learning tasks. The results of SVM classification of spatial data are also promising (Kanevski et al, 2002). The properties of SVM for regression - Support Vector Regression (SVR) are less studied. First results of the application of SVR for spatial mapping of physical quantities were obtained by the authorsin for mapping of medium porosity (Kanevski et al, 1999), and for mapping of radioactively contaminated territories (Kanevski and Canu, 2000). The present paper is devoted to further understanding of the properties of SVR model for spatial data analysis and mapping. Detailed description of the SVR theory can be found in (Cristianini and Shawe-Taylor, 2000; Smola, 1996) and basic equations for the nonlinear modeling are given in section 2. Section 3 discusses the application of SVR for spatial data mapping on the real case study - soil pollution by Cs137 radionuclide. Section 4 discusses the properties of the modelapplied to noised data or data with outliers.

Bioindicators of soil quality in coffee organic cultivation systems

The objective of this work was to assess the effect of different coffee organic cultivation systems on chemical and biological soil characteristics, in different seasons of the year. The following systems were evaluated: coffee intercropped with one (CJ1), two (CJ2) or three (CJ3) pigeon pea (Cajanus cajan) alleys; coffee planted under full sun (CS); area planted with sweet pepper and snap bean in a conventional tillage system (AC); and secondary forest area (FFR). Row spacing in CJ1, CJ2, CJ3 and CS was 2.0x1.0, 2.8x1.0, 3.6x1.0, and 2.8x1.0 m, respectively. Soil samples were collected at 10-cm depth, during the four seasons of the year. The results were subjected to analysis of variance, principal component analysis, and redundancy analysis. There was an increase in edaphic macrofauna, soil basal respiration, and microbial quotient in the summer. Total macrofauna density was greater in CJ2 followed by CJ3, CS, CJ1, AC and FFR; Coleoptera, Formicidae, and Isoptera were the most abundant groups. There are no significant differences among the areas for soil basal respiration, and the metabolic quotient is higher in CJ1, CJ3, and FFR. Microbial biomass carbon and the contents of K, pH, Ca+Mg, and P show greater values in AC.

Soil biological attributes in pastures of different ages in a crop-livestock integrated system

The objective of this work was to evaluate the effect of the pasture (Urochloa brizantha) component age on soil biological properties, in a crop-livestock integrated system. The experiment was carried out in a Brazilian savannah (Cerrado) area with 92 ha, divided into six pens of approximately 15 ha. Each pen represented a different stage of the pasture component: formation, P0; one year, P1; two years, P2; three years, P3; and final with 3.5 years, Pf. Samples were taken in the 0-10 cm soil depth. The soil biological parameters - microbial biomass carbon (MBC), microbial biomass respiration (C-CO2), metabolic quotient (qCO2), microbial quotient (q mic), and total organic carbon (TOC) - were evaluated and compared among different stages of the pasture, and between an adjacent area under native Cerrado and another area under degraded pasture (PCD). The MBC, q mic and TOC increased and qCO2 reduced under the different pasture stages. Compared to PCD, the pasture stages had higher MBC, q mic and TOC, and lower qCO2. The crop-livestock integrated system improved soil microbiological parameters and immobilized carbon in the soil in comparison to the degraded pasture.

Winter pasture and cover crops and their effects on soil and summer grain crops

The objective of this work was to evaluate the effect of winter land use on the amount of residual straw, the physical soil properties and grain yields of maize, common bean and soybean summer crops cultivated in succession. The experiment was carried out in the North Plateau of Santa Catarina state, Brazil, from May 2006 to April 2010. Five strategies of land use in winter were evaluated: intercropping with black oat + ryegrass + vetch, without grazing and nitrogen (N) fertilization (intercropping cover); the same intercropping, with grazing and 100 kg ha-1 of N per year topdressing (pasture with N); the same intercropping, with grazing and without nitrogen fertilization (pasture without N); oilseed radish, without grazing and nitrogen fertilization (oilseed radish); and natural vegetation, without grazing and nitrogen fertilization (fallow). Intercropping cover produces a greater amount of biomass in the system and, consequently, a greater accumulation of total and particulate organic carbon on the surface soil layer. However, land use in winter does not significantly affect soil physical properties related to soil compaction, nor the grain yield of maize, soybean and common bean cultivated in succession.

Soil Stabilization With Chemicals, Iowa Highway Research Board Bulletin No. 22, 1960

In the search for new soil stabilizing agents the effects of six organic cations on plastic limit, liquid limit, shrinkage limit, air-dry strength and rate of slaking of a highly plastic clay subsoil were studied. In all cases the plasticity index and shrinkage were reduced by the treatments. The air-dry strength was lowered in varying degree, which was the only undesirable effect noted. With one exception resistance to slaking was improved. It is concluded that large organic cations show promise as possible stabilizing agents for highly plastic fine-grained soils.

Correlation of physical and chemical attributes of soil with sugarcane yield

The objective of this work was to evaluate the correlation between sugarcane yield and some physical and chemical attributes of soil. For this, a 42‑ha test area in Araras, SP, Brazil, was used. Soil properties were determined from samples collected at the beginning of the 2003/2004 harvest season, using a regular 100x100 m grid. Yield assessment was done with a yield monitor (Simprocana). Correlation analyses were performed between sugarcane yield and the following soil properties: pH, pH CaCl2, N, C, cone index, clay content, soil organic matter, P, K, Ca, Mg, H+AL, cation exchange capacity, and base saturation. Correlation coefficients were respectively ‑0.05, ‑0.29, 0.33, 0.41, ‑0.27, 0.22, 0.44, ‑0.24, trace, ‑0.06, 0.01, 0.32, 0.14, and 0.04. Correlations of chemical and physical attributes of soil with sugarcane yield are weak, and, per se, they are not able to explain sugarcane yield variation, which suggests that other variables, besides soil attributes, should be analysed.

Reproducing the organic matter model of anthropogenic dark earth of Amazonia and testing the ecotoxicity of functionalized charcoal compounds

The objective of this work was to obtain organic compounds similar to the ones found in the organic matter of anthropogenic dark earth of Amazonia (ADE) using a chemical functionalization procedure on activated charcoal, as well as to determine their ecotoxicity. Based on the study of the organic matter from ADE, an organic model was proposed and an attempt to reproduce it was described. Activated charcoal was oxidized with the use of sodium hypochlorite at different concentrations. Nuclear magnetic resonance was performed to verify if the spectra of the obtained products were similar to the ones of humic acids from ADE. The similarity between spectra indicated that the obtained products were polycondensed aromatic structures with carboxyl groups: a soil amendment that can contribute to soil fertility and to its sustainable use. An ecotoxicological test with Daphnia similis was performed on the more soluble fraction (fulvic acids) of the produced soil amendment. Aryl chloride was formed during the synthesis of the organic compounds from activated charcoal functionalization and partially removed through a purification process. However, it is probable that some aryl chloride remained in the final product, since the ecotoxicological test indicated that the chemical functionalized soil amendment is moderately toxic.