The soil moisture retention curve (MRC) is time consuming and expensive to measure directly. Several attempts have been made to establish a relation between readily available soil properties, like particle‐size distribution, organic matter content, and bulk density, and the soil moisture retention curve. Those relationships are referred to as pedotransfer functions (PTFs). The objective of this study was to evaluate some PTFs with respect to their accuracy in predicting the soil moisture retention curve. Five widely used and four more recently developed PTFs were selected for evaluation. Seven of the selected PTFs predict moisture retention function parameters, whereas the other two predict the moisture content at certain matric potentials. In order to quantify the prediction accuracy, the mean of the absolute value of mean differences (MAMD), the mean and the standard deviation of the root of mean squared differences (MRMSD and SDRMSD, respectively), and the mean of the Pearson correlation coefficient (Mr) were used. The evaluated PTFs were finally ranked based on these validation indices. The PTFs showed good to poor prediction accuracy with MAMD values ranging from 0.0312 to 0.0603 m3 m−3 and with MRMSDs between 0.0412 and 0.0774 m3 m−3 The SDRMSDs and Mrs ranged from 0.0212 to 0.0349 m3 m−3, and from 0.9468 to 0.9980, respectively. The validation indices computed by the PTF of Vereecken and coworkers gave the best results. Moreover, it predicts moisture retention function parameters, and therefore, this PTF is recommended most to predict the moisture retention curve from readily available soil properties.

No abstract

No abstract

Erosion and loss of organic carbon (OC) result in degradation of the soil surface. Rill and interrill erosion processes on a silt loam soil were examined in laboratory rainfall and flume experiments. These experiments showed that rill and interrill erosion processes have contrasting impacts on enrichment of OC in transported sediment. Rill erosion was found to be nonselective, while for interrill erosion the enrichment ratio of OC, EROC, varied between 0.9 and 2.6 and was inversely related to the unit sediment discharge. At unit sediment discharge values >0.0017 kg s−1 m−1, the EROC remained equal to 1. The enrichment process was not influenced by raindrop impact. Enrichment of OC by “aggregate stripping” was found to be unimportant in our study. This was attributed to the low aggregate stability of the soil and the equal distribution of OC within the different soil aggregate classes.

This study was conducted to evaluate ten closed‐form unimodal analytical expressions to describe the soil‐water retention curve, in terms of their accuracy, linearity, Akaike Information Criterion (AIC), and prediction potential. The latter was evaluated by correlating the model parameters to basic soil properties. Soil samples were taken in duplicate from 48 horizons of 24 soil series in Flanders, Belgium. All sample locations were under forest and hence the samples had, besides their difference in texture, a high variety in bulk density (ρb) and organic matter content (OM). The van Genuchten model with m as a free parameter showed the highest overall performance in terms of goodness‐of‐fit. It had the highest accuracy, the highest degree of linearity, and the lowest AIC value. However, it had a low prediction potential. Imposing the constraint m = 1 − 1/n and hence reducing the number of model parameters by one, increased the prediction potential of the model significantly, without loosing much of the model's accuracy and linearity. A high degree of accuracy and linearity was also observed for the two Kosugi models tested. Restricting the bubbling pressure to be equal to zero resulted in a rather high prediction potential, which was not the case when keeping the bubbling pressure as a free parameter. A major drawback of van Genuchten and Kosugi type models is that they do not define the soil‐water retention curve beyond the residual water content. We further demonstrated that the performance of all but one model in terms of their match to the data increased with increasing clay content and decreasing sand content, which is contradictory to the deterministic character of these models. Bulk density and OM did not have a significant effect on the accuracy of most models.

The macroporosity, and to a lesser extent the microporosity, of swelling and shrinking soils is affected by their shrinkage behaviour. The magnitude of the changes in bulk volume in response to changes in water content is usually described by the soil shrinkage characteristic curve (SSCC), i.e. the relation between the void ratio and the moisture ratio. At present, many techniques have been described for determination of the SSCC. We have applied the core method, the rubber-balloon method and the paraffin-coated method on respectively undisturbed soil samples, disturbed soil samples and soil clods collected from seven horizons of a Vertisol and a Lixisol under sugar cane in the Havana province, Cuba. We demonstrated that the balloon and paraffin-coated method showed similar results, whereas the core method produced less pronounced shrinkage. The latter was due to the anisotropic shrinkage as was confirmed by the change of the geometry factor with the moisture ratio, to a possible reorientation of particles when collecting undisturbed soil cores, and to the occurrence of small cracks upon drying. We have further shown that the core method produced much higher scatter, which was explained by higher measuring errors and crumbling of the samples as they dried out. Because of its superior behaviour, the balloon method was then selected to test nine different parametric models that describe the SSCC. A group of four models which performed best in terms of RMSE, coefficient of determination and Akaike Information Criterion could be distinguished.

Reliable predictions of wind erosion depend on the accuracy of determining whether erosion occurs or not. Among the several factors that govern the initiation of soil movement by wind, surface moisture is one of the most significant. Some widely used models that predict the threshold shear velocity for particle detachment of wet soils by wind were critically reviewed and evaluated. Wind‐tunnel experiments were conducted on pre‐wetted dune sand with moisture contents ranging from 0·00 to 0·04 kg kg−1. Sand samples were exposed to different wind speeds for 2 min. Moisture content was determined gravimetrically before and after each experiment, and the saltation of sand particles was recorded electronically with a saltiphone. Shear velocities were deduced from the wind speed profiles. For each moisture content, the experiments were repeated at different shear velocities, with the threshold shear velocity being determined by least‐squares analysis of the relationships between particle number rates and shear velocity. Within the 2‐min test runs, temporal changes in particle number rates and moisture contents were detected. A steep increase in the threshold shear velocity with moisture content was observed. When comparing the models, large differences between the predicted results became apparent. At a moisture content of 0·007 kg kg−1, which is half the moisture content retained to the soil matrix at a water tension (or matric potential) of −1·5 MPa, the increase in ‘wet’ threshold shear velocity predicted with the different models relative to the dry threshold shear velocity ranged from 117% to 171%. The highest care should therefore be taken when using current models to predict the threshold shear velocity of wet sediment. Nevertheless, the models of Chepil (1956; Proc. Soil Sci. Soc. Am., 20, 288–292) and Saleh & Fryrear (1995; Soil Sci., 160, 304–309) are the best alternatives available.

Field experiments were carried out to study the effects of different soil management practices on the water balance, precipitation use efficiency (PUE), and crop yield (i.e. winter wheat and peanut) on a loess soil near Luoyang (east edge of the Chinese Loess Plateau, Henan Province, China). Field plots were set up in 1999 including following soil management practices: subsoiling with mulch (SS), no-till with mulch (NT), reduced tillage (RT), two crops per year (i.e. winter wheat and peanut, TC), and a conventional tillage control (CT). The field plots were equipped to monitor all components of the soil-water balance except evapotranspiration, which was computed by solving the water balance equation. The results showed that although soil management had smaller influence on the magnitude of the water balance components than did precipitation variations, small influences of the applied soil management practices on water conservation during the fallow period can greatly affect winter wheat yield. SS increased consistently precipitation storage efficiency (PSE) and PUE over the 5 years compared to CT except during the wettest year. NT also had a noticeable effect on postharvest water storage during the fallow period; however, the influence on yield of NT depended on the amount of precipitation. TC lowered the winter wheat yield mainly due to the unfavorable soil moisture conditions after growing peanut in summer; however, the harvested peanut gained an extra profit for the local farmer. No matter which kind of soil management practices was adapted, PSE never exceeded 41.6%, which was primarily attributed to high evapotranspiration. From data of five consecutive agricultural years between 2000 and 2005, it could be concluded that SS resulted in the highest PSE, PUE and crop yield. TC also showed promising results considering the economic value of the second crop. NT performed slightly less as SS. CT gave intermediate results, whereas RT was the worst alternative. # 2007 Elsevier B.V. All rights reserved. Abbreviations: CT, conventional tillage; D, drainage; ET, evapotranspiration; I, irrigation; L i , lateral inflow; L o , lateral outflow; NT, no tillage; OC, organic carbon; P, precipitation; P f , precipitation during fallow period; P g , precipitation during growing period; PSE, precipitation storage efficiency; R, runoff; RT, reduced tillage; S, water storage; S i , water storage in the beginning of the crop year; S o , water storage at the time of winter wheat sowing; S e , water storage at the end of the crop year; SS, subsoiling; TC, two-crop rotation; PUE, precipitation use efficiency