M. Hensley

SOILS: THE FREE STATE'S AGRICULTURAL BASE

ABSTRACT At least one third of South Africas total grain crop, mainly maize and wheat, is produced in the Free State. Crop production potential and sensitivity to degradation depend largely on the interaction of climate and soil. Climatic conditions vary from arid in the south and southwestern region to nearly sub-humid in the extreme east on the edge of the Drakensberg escarpment. A map of soil distribution in the Province shows groups of land types, each one characterised by a particular soil distribution pattern. The soil components of the map units is also presented. The crop production potential of the Province is presented in the form of a map. Delineations are based on interpretation of land type data and range from arable to non-arable. The total potentially arable area of the Free State is 3.82 million ha. In spite of a detailed understanding of the Free States soils, degradation continues to occur, especially on cultivated land, where the most serious forms are erosion, acidification and organic matter decline.

Soil indicators of hillslope hydrology in the Bedford catchments, South Africa.

Water plays a primary role in soil genesis and soil strongly influences hydrological processes (flowpaths, residence times and storage). Morphological soil properties serve as indicators of hillslope hydrological behaviour and can facilitate hydrological predictions. Three catchments in the Bedford district (B3, B4 and B5) were surveyed for hydropedological purposes and the observed soil indicators and related geological, topographical and vegetation features were interpreted. I n B4 & B5 shallow soils are the dominant factor governing overland flow promoting short residence times. Deeper soils and fractured bedrock in B3 facilitate bedrock flow and recharge of regional and phreatic water tables. The presence of lime and mottles in the subsoils of valley bottom soils confirm flow in the phreatic zone.

Advances in soil physics and soil water management research in South Africa, 1979–2003

(2004). Advances in soil physics and soil water management research in South Africa, 1979–2003. South African Journal of Plant and Soil: Vol. 21, No. 5, pp. 268-277.

Development of a simple empirical model for predicting maize yields in a semi-arid area

A yield prediction model is necessary, together with long-term climate data, to calculate the long-term yields needed for making a quantitative productivity evaluation of a crop ecotope in the form of a cumulative probability function (CPF). In this study the development of such a model for maize grown on two semi-arid ecotopes, i.e. the Glen/Hutton-Ventersdorp and Glen/Oakleaf-Dipene ecotopes, located in the Free State Province, is described. A fairly reliable empirical relationship was obtained between the total above ground biomass and a water stress index using the results of 22 field experiments on these ecotopes. The model consists of the regression equation which describes this relationship viz. Yb = 15238 ISI + 1067 (R = 0.69) where Yb is the predicted total above ground biomass in kg ha−1 and ISI is an integrated stress index for a particular growing season. The stress index is based on the ET/Eo relationship during the growing season.

Soil water variability in the Weatherley grassland catchment, South Africa: II. Soil water content

Abstract Soil water content is a major factor that affects the hydrological response of a hillslope or catchment. It is therefore important to have reliable soil water content data to estimate catchment water yield. Daily soil water content (θ) data was calculated based on weekly measured and other data for the Weatherley grassland catchment in South Africa. A modelling procedure, based on the soil water balance equation and the interpretation of the physical properties of soils was used to calculate daily θ for all 28 sites for the six-year period. A statistical model performance indicated that the mean index of agreement was 0.88, root mean square error (RMSE) was 6.8 mm water per 300 mm soil and mean unsystematic RMSE to total RMSE was 93%. These results indicated that the calculated soil water contents agreed well with the measured values and could therefore be used with reasonable confidence to fill data gaps. The proposed procedure therefore affords the possibility to increase the resolution of irregular measured soil water content data. This would significantly advance the usability of such data, because the influence of rainfall events on soil water content is frequently missed by manual soil water content measurements.

Duration of water saturation in selected soils of Weatherley, South Africa

Soil water contents were measured weekly for six years (1997–2005) in the Weatherley catchment in the northern Eastern Cape Province of South Africa, and used to calculate average duration of water saturation above 70% of porosity (ADs>0.7). Data were used to determine wetness in soils, representative of midslopes, foot-slopes and valley bottoms. Hutton soils (Typic Ustorthents), representative of midslopes, had ADs>07 = 17 days year−1 in the subsoil. Westleigh soils (Aerie Endoaquents), representative of footslopes, had ADs>07 = 175 days year−1 in the subsoil. Katspruit soils (Typic Endoaqualfs), representative of valley bottoms, had ADs>07 = 334 days year−1 in the subsoil. These differences were highly significant. It was hypothesised that Hutton soils drained fastest (within half a month), and would contribute to interflow; Westleigh and Katspruit soils would drain slower (over a period of 6 and 11 months respectively) and would not contribute to interflow, but would rather contribute to peak flow during rainfall events. This hypothesis was tested against flow data from the Weatherley and Cathedral Peak VI catchments, during a rain-free period following prolonged rain. Total outflow during the rain-free periods was 4 362 m3 (2.7 mm) for Weatherley and 52 093 m3 (76.9 mm) for Cathedral Peak VI. The difference in outflow was attributed to the larger water storage capacity, from a larger area of midslope soils in Cathedral Peak catchment VI, compared to the relatively small area of midslope soils in the Weatherley catchment.

Soil Indicators of Hillslope Hydrology

The demand for water doubles every 20 years which is more than twice the rate of the world’s population growth. New water resources are becoming scarcer and to treat and remediate existing sources more expensive (Clothier et al., 2008). The protection and management of surface and groundwater resources, especially in the highly variable water regime of semi-arid areas, requires accurate analysis of hydrological processes. This involves the identification, definition and quantification of the pathways, connectivities, thresholds and residence times of components of flow making up stream discharge. It is essential that these aspects be efficiently captured in hydrological models for accurate water resource predictions, estimating the hydrologic sensitivity of the land for cultivation, contamination and development, and for quantifying low flow mechanisms (Lorentz et al., 2007; Uhlenbrook et al., 2005; Wenninger et al., 2008). Ideally these hydrological models can best be developed using measurements of the surface and subsurface lateral flow paths, water table fluctuations, connectivity of the various water bodies and the residence flow time of water through the landscape. The landscape unit that is of particular importance is the hillslope (Karvonen et al., 1999; Lin et al., 2006; Ticehurst et al., 2007), hence the accent here on this landscape unit. The measurements named are however expensive and time consuming since these processes are dynamic in nature with strong temporal and spatial variation (McDonnell et al., 2007; Park & Van de Giesen, 2004; Ticehurst et al., 2007). The need for predictions of the named hydrological processes is becoming increasingly important and led to the launch an International Association of Hydrological Sciences (IAHS) initiative called Predictions in Ungauged Basins or PUB (Sivapalan 2003; Sivapalan et al., 2003) encouraging researchers and modellers to focus their efforts on predicting the hydrological behaviour of catchments based on physical principles without relying on calibrations of hydrological models. Soils integrate the influences of parent material, topography, vegetation/land use, and climate and can therefore act as a first order control on the partitioning of hydrological flow paths, residence time distributions and water storage (Park et al., 2001; Soulsby et al. 2008). The influence of soil on hydrological processes is due to the ability of soil to transmit, store and react with water (Park et al., 2001). Hydrologists agree that the spatial variation of soil properties significantly influences hydrological processes but that hydrologists lack the skill to gather and interpret soil information (Lilly et al., 1998). The relationship between soil and hydrology is interactive. Water is a primary agent in soil genesis, resulting in the formation of soil properties containing unique signatures of the way they formed. Almost every hydrological process of interest to hydrologists is difficult to observe and measure

Interpretation of digital soil photographs using spatial analysis: I. Methodology

Systems for the evaluation of soil wetness use soil colour extensively. The determination of soil colour normally relies on the users perception of colour and usually employs a colour matching system, e.g. Munsell Soil Color Charts. The South African soil classification system distinguishes between diagnostic grey, yellow-brown and red colours. This paper proposes a computerised methodology for the quantitative determination of diagnostic soil colour using spatial analysis. To achieve this, soil colour definitions had to be converted from Munsell colour notation to the RGB colour notation employed in digital cameras. The conversion also aided in the mathematical manipulation of colour data during spatial analysis. In this study the relationships between photographed and calculated RGB values were as follows: Calculated Red = 0.9238 ¥ Photographed Red −37.24 (R2 = 0.99); Calculated Green = 0.9975 ¥ Photographed Green −38.96 (R2 = 0.99); Calculated Blue = 0.9841 ¥ Photographed Blue −35.74 (R2 = 0.99). The following equations can be used to differentiate between diagnostic grey, yellow and red, as defined in Soil Classification—A Taxonomic System for South Africa, using the RGB values obtained from digital photographs and after correction using the equations given above: Between grey and yellow: Green = 0.88 ¥ Red 5; Between yellow and red: Green = 0.79 ¥-11. The methodology showed a 19% misclassification when tested against photographed Munsell sheets. It was, however, a huge improvement when compared to visual methods. The number of chips classified as grey, yellow-brown or red were equal to the number of chips defined as grey, yellow-brown or red. The misclassification was attributed to the discrete nature of the diagnostic colour definitions in contrast to the continuous nature of the differentiating equations.

The relationship between soil morphology and soil water regime: preliminary results in the Weatherley catchment

Soil water contents were measured for five years at Weatherley, an intensively instrumented catchment in the north eastern part of the Eastern Cape Province. Soil water contents are expressed in terms of average duration of saturation with water above 0.7 of porosity (ADS>07 in days per year) and is related to soil morphology. Preliminary results indicate that different orthic A horizons can have ADS>0.7 from 3 to 356 days per year, depending on the nature of the underlying horizons. The E and soft plinthic B horizons in the Longlands profile had ADS>0.7 of 21 and 92 days per year, respectively. In the Kroonstad profile ADS>0.7 is 351 days in the E and 330 days per year in the G horizon. The red apedal B in the Bloemdal profile had ADS>0.7. = 0, while the underlying unspecified material with signs of wetness had ADS>0.7 of 203 days per year. Initial indications are that ADS>0.7 less than 10 days per year does not lead to mottling, while ADS>0.7 larger than 13 days per year results in mottling.

Redox conditions related to interflow in a soil of the Kroonstad form in the Weatherley catchment

Abstract The Kroonstad soil form, in the Weatherley catchment, Eastern Cape Province consists of an orthic A / E / G horizon sequence, and is a typical gleyed soil of South Africa. The profile has an uncommon diffuse E / G transition. Water contents from weekly neutron water meter readings and redox response as indicated by dissolved Fe2+ concentration were correlated with daily rainfall data from automated weather stations. Results showed that reducing conditions were more pronounced in the E horizon than in the orthic A or G horizon as indicated by the Fe2+ concentration. This is contradictory to what is normally expected. Response in soluble iron concentration in the orthic A horizon was largely associated with rainfall events. Responses in the E horizon could not be linked to current rain events. A time lag was found to exist between a response in the A and the E horizon. The G horizon responded to seasonal changes. The inability to relate current rainfall events to redox conditions as indicated by soluble Fe2+ response in the E horizon could be attributed to water entering the E horizon laterally through interflow. This would also explain the observed time lag. This is typical of perched water tables. The lack of response in the G-horizon is an indication of a year round flow pattern controlled by seasonal changes and is typical of phreatic water tables. It is postulated that the non-abrupt E / G transition is an indication of the dominant role of the phreatic water table during pedogenesis, with upwards and lateral movement of water into the E horizon. It is further postulated that the nature of the E / G transition could serve as a valuable criterion to distinguish between the wetter and drier soils of the Kroonstad form.