Department of Soil Science

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The contribution of indigenous vegetables to food security and nutrition within selected sites in South Africa
(Stellenbosch : Stellenbosch University, 2013-12) Mavengahama, Sydney; De Clercq, W. P.; McLachlan, Milla; Stellenbosch University. Faculty of AgriSciences. Dept. of Soil Science.
ENGLISH ABSTRACT: South Africa is rich in biodiversity among which are semi-domesticated vegetable species which are known as wild or indigenous vegetables. These wild indigenous vegetables have been reported to be good in nutritional qualities such as macro and micronutrients. However, there is still a high prevalence of malnutrition; especially micronutrient deficiencies among low or marginal income bracket of the population. The use of indigenous vegetables has been proposed as part of the solutions to the problems of micronutrient malnutrition among these populations. Indigenous vegetables are an important source of food in the maize based subsistence farming sector of rural South Africa. Their main role is as relish as they are used as an accompaniment for staple cereal based diets. They are also generally reported to be rich in micronutrients. Although they may be consumed in small quantities, they influence the intake of cereal staples, manage hunger and play a central role in household food security for the poorer rural groups. Mixing several indigenous vegetables species in one meal contributes to dietary diversity in terms of more vegetable types as well as in terms of choice of relish. For some very poor families indigenous vegetables are substitutes for some food crops. The seasonal occurrence of these vegetables leaves many families without a food source during the off-season. Indigenous vegetables increase agro-biodiversity at the household level. This agro-biodiversity helps in buffering against the accumulation and multiplication of pests and diseases and provides important cover for the soil. Further research on agronomic, social and economic dimensions is required to understand the roles of IV in subsistence farming systems in South Africa. The survey study revealed that indigenous vegetables were important in the diets of most rural people in the study area. They were consumed as relish although they were not being cultivated. Their method of acquisition was gathering from homesteads and the wild. These vegetables were also believed to be medicinal. The local naming of wild vegetables varied among villages in the same district such that a vegetable in one village was assigned to a different species of vegetable in another village. They were reportedly abundant during summer and there was a decrease in availability off-season leaving vulnerable people who rely on them with a food shortage. The utilisation of wild vegetables among South Africans is reported to be declining due to over reliance on introduced temperate species. Efforts to domesticate and cultivate wild vegetables could be hampered by several factors including seed dormancy and premature flowering. In this present study dormancy was observed in C. olitorius. The response of wild genotypes of C. olitorius with different seed sizes to various dry heat and hot water treatments was evaluated. Steeping seeds in boiling water (95oC) for ten seconds and soaking seeds in a hot water bath at 80oC for ten minutes resulted in the highest response to germination in this species. The study also recorded significant interactions between heat treatment and seed sizes. We concluded that C. olitorius seeds of different sizes require diverse durations of exposure to heat treatment methods to break dormancy caused by an impermeable seed coat. Cleome gynandra is another species that is consumed as a vegetable in various parts of the world including Africa. The plant is also used as a medicinal herb for the treatment of various human diseases. Among the wild vegetables, C. gynandra has been reported to flower prematurely, a phenomenon known as bolting and common in many vegetable crops. Premature flowering (bolting) can be as a response to temperature extremes and photoperiod and affects many other leafy vegetables such as lettuce (Lactuca sativa), spinach (Spinacea oleracea) and mustard rape (Brassica juncea). Bolting leads to production losses in leaf vegetable crops as they flower before they have produced an economic yield. The removal of flowers and nitrogen application resulted in significant increases in the fresh and dry weight of cleome leaves. Removal of flowers resulted in a 46% increase in fresh weight of leaves. The observed positive response of leaf yield to removal of flowers offers a possible way to deal with the problem of bolting. The continuous removal of the flowers leads to increased utilisable leaf yield. The application of incremental amounts of nitrogen top dressing results in increased leaf yield in C. gynandra. The response of selected indigenous vegetables (Corchorus olitorius and Amaranthus cruentus) to micronutrients added to the soil was compared with the response of a reference crop; Swiss chard (Beta vulgaris var. cicla). For all the levels of micronutrients applied, Swiss chard accumulated Cu, Zn and Mn in the leaves at significantly (p<0.01) higher concentrations than the wild vegetables. Variations between the vegetables in the micronutrients were greater for Zn (72–363 ppm) and Mn (97.9–285.9 ppm) for Cu (8.8–14 ppm). C. olitorius had the least capacity to concentrate Mn and Zn in the leaf, which suggested that this vegetable is a less attractive candidate for agronomic bio-fortification of these elements. However, C. olitorius accumulated Fe at a significantly higher concentration (327 ppm) in the leaves than did Amaranthus (222 ppm) or Swiss chard (295 ppm). Sulphur as a macronutrient varied little in the plant species tested. The mean S concentration in the leaves ranged from 0.26% in C. olitorius to 0.34% in Amaranthus cruentus and Swiss chard. We concluded that the different vegetables have different abilities to take up Cu and Zn in the order Swiss chard > Amaranthus > Corchorus, and that they responded to micronutrients added to the soil but only up to certain limits of supplementation. The results from this current study seem to contradict the belief that wild vegetables have the inherent ability to concentrate mineral micronutrients in their tissue. Factors such as environment, anti-nutrients, dietary diversity, plant parts, plant age, and varieties result in differences in reported nutritional composition of indigenous vegetables. Post-harvest handling, storage, cooking and preservation also alter the composition. The need to optimise protocols for each vegetable type and for different laboratories makes analysis expensive. Equipment and methods of analysis are varied and may not be comparable, making it difficult to generalise on the composition of these vegetables. The Agricultural Research Council of South Africa and other stake holders are conducting studies on some aspects of these vegetables. There are still many information gaps regarding many aspects of these vegetables which require research attention. These include; the selection and improvement of genotypes, seed biology and germination studies, agronomic (population, fertiliser, crop mixtures) studies and phyto-chemical evaluation of these important species in order to encourage the overall use of these important indigenous resources. Finally, there is need to promote their increased utilisation.
Digital soil mapping techniques across multiple landscape scales in South Africa
(Stellenbosch : Stellenbosch University, 2019-12) Trevan, Flynn; Clarke, Catherine E.; Rozanov, Andrei Borisovich; De Clercq, W. P.; Stellenbosch University. Faculty of Agrisciences. Dept. of Soil Science.
ENGLISH ABSTRACT: Digital soil mapping has seen increasing interest due to environmental concerns and increasing food security issues. Digital soil mapping offers a quantitative approach which is cost effective as less soil observations are needed to produce large area soil maps. However, digital soil mapping has only recently been addressed in South Africa. This research aimed to produce two digital soil mapping (DSM) frameworks with the available resources in South Africa. The methodologies incorporate advanced geostatistics and/or machine learning techniques to be able to produce quantitative soil maps from the farm to catchment scale. First, a framework that optimises both feature selection and predictive models was developed to produce farm-scale soil property maps. Four feature selection techniques and eight predictive models were evaluated on their ability to predict particle size distribution and SOC. A boosted linear feature selection produced the highest accuracy for all but one soil property. The top performing predictive models were robust linear models for gravel (ridge regression, RMSE 9.01%, R2 0.75), sand (support vector machine, RMSE 4.69%, R2 0.67), clay (quantile regression, RMSE 2.38%, R2 0.52), and SOC (ridge regression, RMSE 0.19%, R2 0.41). Random forest was the best predictive model for silt content with a recursive feature selection (RMSE 4.12%, R2 0.53). This approach appears to be robust for farm-scale soil mapping where the number of observations is often small but high-resolution soil data is required. Second, 24 geomorphons (landform classification) were evaluated on their association with soil classes. The geomorphon with the highest association was aggregated into a 5-unit system which was evaluated on how well the system stratified soil lightness, soil EC, SOC, effective rooting depth, depth to lithology, gravel, sand, silt, and clay. It was found that an aggregated geomorphon stratified all soil attributes except EC. Additionally, the aggregated geomorphon predicted 6 out of 9 soil properties with the greatest accuracy (RMSE) when compared to the original geomorphon (10-unit system) and a manually delineated system (5-unit system). This study shows that aggregating geomorphons can stratify the soil landscape even at the farm-scale and can be used as an initial indication of the soil spatial variability. Third, a framework to disaggregate the Land Type Survey (LTS) through machine learning was developed. Geomorphons, together with the original LTS were overlaid to produce terrain morphological units. The polygons were disaggregated further to produce a raster map of soil depth classes through a disaggregation algorithm known as DSMART. The first most probable class raster achieved an accuracy of 68% and for the two most probable class rasters, an accuracy of 91% was achieved. The two-step approach proved necessary for producing a farm-scale soil map. Forth, a study aimed to compare 10 algorithms, implemented through a modified DSMART model, in their ability to disaggregate two polygons into soil associations in two environmentally contrasting locations (Cathedral Peak, KwaZulu-Natal Province and Ntabelanga, Eastern Cape Province). At Cathedral Peak (high relief with clear toposequences), nearest shrunken centroid was the top performing algorithm with a kappa of 0.42 and an average uncertainty of 0.22. At Ntabelanga (low relief with strong geological control), the results were unsatisfactory. However, a regularised multinomial regression was the top performing algorithm, achieving a kappa of 0.17 and an average uncertainty of 0.84. The results of this study highlight the versatility of a technique to disaggregate South Africa’s national resource inventory. Disaggregation was then used to simultaneously disaggregate 20 land types in the Mvoti catchment covering 317 km2 in KwaZulu Natal province. First, the optimal geomorphon was chosen through a spatially resampled Cramer’s V test to determine the association between the soil legacy polygons and the geomorphon units. Second, feature selection algorithms were embedded into DSMART. Third, the feature selection techniques were compared using 25, 50, 100, and 200 resamples per polygon. The results indicate that the Cramer’s V test is a rapid method to determine the optimal input map. Feature selection algorithms achieved the same accuracy as using all covariates but had greater computational efficiency. It is recommended that 10 to 20 times the amount of soil classes be used for the number of resamples per polygon.
The effect of long-term tillage practices on selected soil properties in the Swartland wheat production area of the Western Cape
(Stellenbosch : Stellenbosch University, 2013-03) Botha, Pieter Barend; De Clercq, W. P.; Stellenbosch University. Faculty of AgriSciences. Dept. of Soil Science.
ENGLISH ABSTRACT: The effect of long-term tillage on basic soil properties with respect to sustainability was investigated in this dissertation. Over the last three decades soil conservation has become an important prerequisite for sustainable agriculture. The primary aim of this study was to evaluate the effect of different tillage practices on the physical and some of the chemical properties of soil after 37 years of continuous application. This study was conducted on the Langgewens experimental farm, 18 km north of Malmesbury in the Western Cape. The experiment was initiated in 1975 on a Glenrosa (Haploxeralf) soil form with a gravelly sandy-loam texture. It was treated with four main tillage methods, namely conventional, tine, minimum and no-tillage. Important basic soil properties studied were the electrical conductivity (EC) and total carbon percentage, water stable aggregate percentage, bulk density and hydraulic conductivity. Most of the properties were analysed for the 0-100 mm and 100-200 mm depths. Seasonal bulk density variation for the 0-100 mm soil depth was determined by a Troxler surface gamma-neutron meter for in situ measurement. ANOVA’s and Tukey’s LSD posthoc tests were computed to assess whether significant statistical differences existed between tillage treatments. No-tillage proved to be beneficial in terms of salinity and had the lowest electrical conductivity, indicating that salts leeched out of the profile. Total carbon content was in general very low and in the 0-100 mm soil depth it decreased in the order of: no (0.92%), minimum (0.86%), tine (0.83%) and conventional tillage (0.51%). Aggregate stability was significantly the lowest under conventional (47.82%) and tine tillage (45.02%) compared to minimum (61.43%) and no-tillage (78.40%) at 0-100 mm depth. This can be explained by the relatively low amount of total carbon in the soil combined with the tillage intensity. The same trend was observed for the 100-200 mm depth. Significant correlation between total carbon content and aggregate stability for the 0-100 mm confirmed that an increase in total carbon in the soil would lead to an increase in aggregate stability. Significant, increased aggregate stability under the no-tillage treatment would therefore indicate that there may be some stable structure present in the soil. Seasonal bulk density variation was the lowest in no-tillage, which supports the manifestations of stable soil structure. More intensive tillage treatments such as conventional and tine tillage initially showed lower bulk densities, but only for the first month. Thereafter it increased to significantly higher values as the season progressed. This was mainly as a result of hardsetting of the soil which is driven by natural processes and rainfall. It is also due to the sandy loam texture that is particularly prone to compaction. Hydraulic conductivity studied for conventional and no-tillage showed significant differences. No-tillage (41 mm.h-1) showed a noticeably higher conductivity, which remained constant compared to conventional tillage (20 mm.h-1) that decreased over time. The main reasons for this increased hydraulic conductivity under no-tillage was higher water stable aggregates and lower bulk density. In the long term no-tillage thus stimulated structure formation of a Glenrosa soil form that significantly improved soil properties studied. These properties may influence processes such as water infiltration, water storage, run-off and drainage positively, due to soil property interaction. No-tillage, in terms of sustainability, quantified by the soil properties studied, thus proved to be superior compared to conventional and tine tillage but to a lesser extent if compared to minimum tillage.
The effect of residue management on the nutrient cycle in the production of rooibos (Aspalathus linearis) at Nieuwoudtville, Northern Cape
(Stellenbosh : Stellenbosch University, 2017-03) Nieuwoudt, Stephanus Francois; De Clercq, W. P.; Hardie-Pieters, Ailsa G.; Stellenbosch University. Faculty of AgriScience. Dept. of Soil Science.
ENGLISH ABSTRACT: Rooibos (Aspalathus linearis) is a sensitive fynbos species with a large genetic variation, adapted to acid, nutrient poor soils, and can only be grown in certain parts of the Western- and Northern-Cape. Rooibos yields are getting poorer with increasing age of the field and the lifespan of rooibos are also just a maximum of 5 years commercially produced. A lot of medicinal/health research has been done and published on rooibos, but not much on the agricultural production aspects of rooibos. In order to increase the production and lifespan of rooibos tea further research needs to be done to better understand the rooibos plant in its cultivated environment. The role of leaf litter in fynbos, particularly in the cultivated rooibos nutrient cycle is still a grey area that could open up key management principles regarding plant water availability and plant nutrition style. The hypothesis is that the method of harvesting the rooibos seed by removing the litter layer without returning it under the plant can have a negative impact on the nutrient pools and cycle and thus lead to a shorter lifespan. The main aim was thus to look at the effect of different residue treatments on the rooibos plant nutrient cycle (uptake and nutrient pools). Four sites across the Nieuwoudtville Bokkeveld region were selected with all the rooibos plants being ± 2 years old. Four different mulch treatments; a bare soil (leaf residue removed) treatment imitating seed harvesting (A), an added rooibos mulch (B), a natural leaf mulch (C) and an enriched rooibos mulch (D) were prepared at 4 sites. The chemical properties of soil and plant tissue from rooibos plants were tested. 5TE soil probes were used to measure the volumetric water content, EC and temperature at two soil depths of each treatment. All measurements were also duplicated using near-infrared spectroscopy (NIRS), to generate a database for future reference and to build calibrations that will be able to predict the nutrient content in the soils and plants. It was found that soil chemical properties including P (mg kg-1), Na (cmolc kg-1), K (cmolc kg-1), Ca (cmolc kg-1), Mg (cmolc kg-1), Zn (mg kg-1), Mn (mg kg-1), C (%) and % Na (at pH 7); and plant chemical properties including Na (%) and plant N (%), P (%), K (%), Al (mg kg-1) and Fe (mg kg-1) all had a significant effect of the regrowth models using multiple regression analysis. Soil P, Mg and K had the biggest positive influences on the regrowth models. During this process it was found that the N:P ratio in soil plays an important role in the uptake of N and growth. Only at treatment D, with the lowest soil N:P ratio, plant N (%) had a positive influence on the regrowth multiple regression model. Plant N and P had a moderate positive correlation (R2=0.56). Nutrient uptake by the rooibos plant was very high from July 2015 to September 2015. These nutrients included N, P, K, Ca, Mg, Zn, Mn, Fe and Al. From September 2015 to January 2016 however the uptake was lower for all the nutrients, but for K and Mg the uptake was higher compared to the other nutrients. The decrease in plant nutrient concentration from September 2015 to January 2016 is a result of less nutrient uptake and nutrient dilution following rapid growth of plant. There was an increase in soil exchangeable Mg and Ca from July 2015 to September 2015 due to increase in soil pH during this time. Soil exchangeable Ca (R2=0.49) and Mg (R2=0.61) correlated positively with pH, thus the increase in soil exchangeable Ca and Mg can be due to the increase in pH. For all the treatments there was a total decrease in soil N (significant for A and B) and plant N over the one-year period. The plant Al and Zn for all the treatments also increased over the one-year period. The increase in plant Al was not significant and the increase in plant Zn was significant for all treatments. From July 2015 to January 2016 there were differences in growth between the treatments. Treatment A resulted in the lowest estimated dry matter increase during this period and for treatment B it was the highest. The difference in estimated dry matter increase between these two treatments was also statistically significant. The estimated dry matter increase for treatment C and D was higher than treatment A but it was not significant. The mulch treatments, especially treatment B, resulted in higher P, K and Mg uptake. For all the treatments, except treatment D, the soil P decreased over the one-year period. For treatment B and D the plant P increased significantly compared to treatment A and C where the increase was not significant. The mulch treatments showed an increase in plant K, but it was only significant for treatment B over the one-year period. For all the treatments there was an increase in plant Mg, but only for treatment A the increase was not significant. All the mulch treatments also conserved more water for longer compared to treatment A. The combination of nutrient leaching from the mulch (Mg and K) and the conservation of more soil water may be the reason for the higher nutrient uptake by treatment B and thus the better growth. From the NIRS study it was found that for these sandy soils it was only exchangeable Mg that could be predicted with good accuracy (RPD>2). The soil chemical properties pH, H (cmolc kg-1), K (mg kg-1), Ca (cmolc kg-1), Fe (mg kg-1) and C (%) models showed satisfactory predictability. For plant samples NIRS predicted P (%) and Mg (%) with good accuracy. The prediction models for N (%), K (%), Ca (%) and Na (mg kg-1) were only satisfactory and for the rest it was unreliable. From these results it was thus not possible to quantitatively predict all the chemical properties in the soil and plant samples but there is potential for better calibrations in the future. Differences in growth and vigour can also be attributed to location. The micro conditions in which a single plant grows, related to the impact of normal agricultural practices, was found to also determine the success of rooibos production. The hypothesis was supported by treatment C (the plant where natural mulch was not removed) having a higher estimated dry matter increase compared to treatment A (bare soil), but this difference was not significant. Treatment B (added mulch) however showed to have a significant impact. Rooibos production systems are far from being optimized and the amounts of unknown impacts were narrowed down by this work. This research indicates that the rooibos plant is genetically unrefined and that agricultural practices should focus more towards the natural state of fynbos nutrient availability and growth.
Gully erosion in the Sandspruit catchment, Western Cape, with a focus on the discontinuous split gully system at Malansdam
(Stellenbosch : Stellenbosch University, 2013-12) Olivier, George; De Clercq, W. P.; Schloms, B. H. A.; Stellenbosch University. Faculty of AgriSciences. Dept. of Soil Science.
ENGLISH ABSTRACT: Gully erosion is a major environmental problem not only having direct influences on site but also indirect influences felt further down the catchment. Combating gully erosion has proven to be elusive due to the difficulty in finding the causal factors and developing mechanisms involved. Soil is the medium in which gully erosion occurs yet few research have investigated it as a driving factor behind gully development and those that have has done it in a very elementary way. The first aim of this project was to physically and chemically characterise and classify the discontinuous gully system at Malansdam to establish the relationship between landscape hydrology and geomorphologic gully development with a focus on control factors. This was done by field observations, physical measurements and spatial and hydrological analyses with a Geographical Information System (GIS). The Malansdam gully system was the first ever recorded Strahler stream order (SSO) 5 classical gully system with the most active region being in the upper reaches where a steeper slope is experienced. Although piping was observed the V-shape channels and SAR data from traditional wet analysis indicated runoff to be the dominant formation process. A duo of factors, consisting of one anthropogenic and one natural factor respectively, was found that the major control factors behind the gully formation. A unique anthropogenic factor that has never been published beforehand was found to be the anthropogenic driving factor namely the ploughed contour cultivation technique employed by the farmers in the Sandspruit catchment. The ploughed contours act as channels firstly collecting and secondly moving water that would have drained naturally downwards in the valley to one exit point in the gully system. This allows increased erosive energy because of the larger volumes of water entering one single point in the upper reaches of the gully system where a steeper slope is experienced. The driving factor in the natural group was determined to be weak soil structure due to an abundant amount of exchangeable Mg2+ cations occupying the exchange sites on the clay fraction. This would cause soil to disperse in the presence of water even with a low amount of exchangeable Na+. Combat methods would accordingly exist in the form of rectifying the soil structure and finding an alternative to the ploughed contour system currently employed, but also planting vegetation especially grass or wheat in the gully channels. The second aim of this project was to determine the capability of Near Infrared (NIR) spectrometry, with wavenumbers 12 500 – 4 000 cm-1, to predict indicators used in soil science to establish the dispersive nature of a soil. These indices included the Exchangeable Sodium Percentage (ESP), Sodium Absorption Ratio (SAR), Magnesium Saturation Percentage (MS%), Electrical Conductivity (EC), Potential Hydrogen (pH) as well as the four main exchangeable cations namely calcium (Ca2+), potassium (K+), sodium (Na+) and magnesium (Mg2+). Surface and subsurface soil samples were collected from active gully heads. These samples were minimally pre-processed thus only dried, milled and sieved. Thereafter it was subject to NIR analysis making use of the Bruker multi-purpose FT-NIR Analyser (MPA; Bruker Optik GmbH, Germany) with a spectral range of 12 500cm-1 to 4000cm-1 which is. Partial Least Square Regression (PLSR) models were built for each index and the exchangeable cations making use of QUANT 2 utility of OPUS 6.5 (MPA; Bruker Optik GmbH, Germany) software. Five different regrssion statistics namely the coefficient of determination (r2), Root Mean Square Error of Cross Validation (RMSECV), Ratio of Performance to Deviation (RPD), Bias and the Ratio of Performance of Quartiles (RPIQ) were used to assess the legitimacy of each PLSR model. Upon validation all the PLSR models performed in line with previously published work and in certain cases better. The only exception was MS% which would require further investigation. NIR thus possess the capability to predict a soil’s dispersive nature in a fast, reliable, inexpensive and non- destructive way, thus implying whether or not it contributes to gully erosion at a significant level or only minimally.
Increased water productivity in irrigated tomato production in the smallholder farming community of Giyani
(Stellenbosch : Stellenbosch University, 2014-04) Pienaar, Cornelis Jacobus; De Clercq, W. P.; Jovanovic, Nebo Z.; Stellenbosch University. Faculty of AgriSciences. Dept. of Soil Science.
ENGLISH ABSTRACT: The availability of water for irrigation purposes is becoming a serious concern for smallholder famers in the former homeland areas of South Africa. Not only because of global weather change and the occurrence of more erratic weather events, but also due to competition for fresh water between the agricultural, industrial and domestic sectors (Hamdy et al., 2003). Food production increases in smallholder agriculture is seen as a possible solution to the food security challenges in the rural areas of the Limpopo Province (Altman et al., 2009). Smallholder farmers in Giyani mostly use traditional furrow irrigation systems and their farm crop productivity remains very low, compared to commercial farms in the same area. The objective of this study is to utilize and test various innovation technologies aimed at increasing Water Productivity (WP) in order to facilitate better irrigation management of the available water resources. The study was conducted on two farms, Zava Cooperative Garden and Mzilela Cooperative Garden, in the rural areas of Giyani over a two year period from 2012-2013. This study seeks to achieve the objective in three distinct ways. Firstly, the use of NIR technology is used to evaluate the prediction ability of soil chemical parameters for fertilizer requirement calculations. Secondly, WP trials were conducted on smallholder tomato (Solanum lycopersicum) production for three consecutive seasons, evaluating their current tomato crop production systems and also testing new innovations for WP increases. Thirdly, applying the MonQI methodology, inputs and outputs of all crop production sites were done to monitor the cropping systems throughout the period of the research. The results from this study indicate the importance of applying new innovations amongst smallholder production systems. Important findings from the NIR technologies indicated that this innovation can improve soil nutrient management in a more affordable, user friendly manner. The results showed that good prediction models were obtained for pH (KCl), electrical conductivity (EC), P, K, Mg, Na and CEC, with R2 and RPD values larger than 0.60 and 1.4 respectively. The prediction of exchangeable Ca was less successful with a R2 value of 0.43. Results from the WP trials suggest that drip irrigation performed better than furrow irrigation in terms of yield and WP. Yield and WP were very low for all treatments, being below 32 t/ha and 5.2 kg/m-3 respectively. Improved management practices, such as soil nutrient management and mulching were introduced in the 2nd and 3rd seasons of tomato trials in order to increase WP at field level at Mzilela farm. Results showed tomato yield increased from an average of 26.5 t/ha to 120.9 t/ha and WP increases from 4.61kg/m-3 to 17.69 kg/m-3. Deep drainage of water out of the rootzone decreased with better irrigation management. The results from the monitoring of inputs and output of their cropping systems revealed that smallholder farmers, using traditional farming practices, yielded very low and mostly below 5 t/ha for all crops. Some crops were totally lost due to hail and heat-waves. NPK balances for conventional cropping by the smallholder farmers at Mzilela was in the range of 0 to -70 kg/ha. The tomato production fertilized treatment of the 1st, 2nd and 3rd WP trials, showed positive nutrient balance results for P and K in the range of 80 to 140 kg/ha. N balances were mostly negative for all plots. NFI was R2768 and R4740 for season 1 and 3 respectively, while the 2nd season results showed a loss of - R5176. With the improved yield from the WP trial sites, and the fruits being sold to the Spar, the NFI increased to R42486 in the final season. The study concludes that great improvements in yield, WP and NFI are attainable and sustainable amongst smallholder farmers in the Giyani area.
Investigating the suitability of land type information for hydrological modelling in the mountain regions of Hessequa, South Africa
(Stellenbosch : Stellenbosch University, 2016-12) Malan, Gert Jacobus; De Clercq, W. P.; Rozanov, Andrei Borisovich; Stellenbosch University. Faculty of AgriScience. Dept. of Soil Science.
ENGLISH ABSTRACT: The Land Type database of South Africa combines soil associations with various terrain positions within a larger Land Type polygon. The Land Type structure provides the opportunity to unlock the terrain unit information through segmenting the larger Land Type polygon into terrain units. Geographical information systems have the capability to dissect the landscape into terrain morphological units, using remote sensing technology. There is a range of methods and software available that can be used to dissect the landscape, the challenge is to identify a method that would be compatible with Land Type terrain units. The study area is the catchment of the Korentepoort dam, north of Riversdale in the Hessequa district of the Western Cape. The Hessequa region is regularly struck with drought which leads to an investigation into the water security of the region. The investigation includes the development of a hydrological model for the Korentepoort Dam and bordering catchments. Physically based hydrological models require detailed soil distribution maps with soil physical data. The physical characteristics are used to calculate the amount of surface runoff, drainage and streamflow. Hydrologists use the Land Type information to supply soil character for modelling purposes. The most common soil type from the Land Type memoir is selected to represent the whole Land Type polygon. This representation varies depending on the homogeneity of soils within the landscape, but can be as little as 20%. The segmentation method is evaluated within the Korentepoort catchment by field observations of the terrain at 190 points in the landscape. This point data is compared to the segmentation map with a different range of acceptable error. The segmentation method is constructed on a 90-meter digital elevation model, which was refined to a 30 meter. The highest acceptable error was selected as 30 meters. At this error, the terrain map was able to predict 77% of the field observation points. Transects were created from the terrain map, which also indicates a good fit with terrain units. The Land Type information in the catchment was found to be conflicting with field observations and thus updated. The updated Land Type information was used to populate the segmented terrain map. The high resolution of the terrain map was found to be too complex for the hydrological model. A well-used method of soil type aggregation on the basis of hydrology was applied to the updated Land Types. The method divides the soil types into three hydrological response units and was found to be accurate on 10 out of 13 selected profiles. These profiles are selected as modal profiles and represent the soil types of their respective terrain units. This research made it possible to dissect the landscape into units comparable with those in the Land Type database. This increases the resolution of the Land Type information and could possibly be applied to the whole of South Africa. Methods are suggested in which these terrain maps can be aggregated in a meaningful manner which would enhance its applicability for hydrological modelling.
Mapping soil organic carbon stocks by combining NIR spectroscopy and stochastic vertical distribution models : a case study in the Mvoti River Catchment, KZN, South Africa
(Stellenbosch : Stellenbosch University, 2019-03) Wiese, Liesl; Rozanov, Andrei Borisovich; De Clercq, W. P.; Seifert, Thomas; Stellenbosch University. Faculty of AgriSciences. Dept. of Soil Science.
ENGLISH ABSTRACT: The agricultural and environmental importance of maintaining and increasing soil organic carbon (SOC) has been increasingly recognized globally. To a large extent, this recognition can be attributed to soil being the largest terrestrial carbon pool, as well as to soil’s responsiveness to land use and management. Land use and land use change are major factors affecting SOC levels with changes from natural vegetation (forests, grasslands and wetlands) to croplands, for example, causing significant SOC losses. The topsoil (0-30 cm depth) is especially sensitive to changes in land use and management and the highest variation in SOC levels is observed in this zone. In this study SOC stocks in the first meter of soil were quantified and mapped under different land uses and management systems using a vertical SOC distribution model, applying near-infrared (NIR) spectroscopy for SOC analysis and estimating the uncertainty of the maps created using different approaches. The study area was chosen as a quaternary catchment of 317 km-2 south and southeast of Greytown in the Midlands area of KwaZulu-Natal, South Africa. The catchment exhibits complex topography and predominantly shale and dolerite parent material. Soils in the area have high organic carbon content ranging from 0.08 to 22.85 % (mean = 3.48 %), with clay content ranging from 3 to 49 % (mean = 14.7 % clay) and pH(H20) between 3.3 and 6.7 (mean pH(H20) = 4.5). Vertical SOC distribution functions were developed for 69 soil profiles sampled from different land uses (mainly forestry plantations, grasslands and croplands) in and around the study catchment. Bulk density samples were taken at 2.5, 7.5, 12.5, 17.5, 30, 40, 50, 75 and 100 cm depths. The aim was to reduce the number of soil observations required for SOC accounting to one point close to the soil surface by applying negative exponential vertical depth functions of SOC distribution. To achieve this, the exponential functions were normalized using the volumetric SOC content observed close to the surface and grouped as a function of land use and soil types. Normalization reduced the number of model parameters and enabled the multiplication of the exponential decline curve characteristics with the SOC content value observed at the surface to present an adequately represented value of soil carbon distribution to 1 m at that observation point. The integral of the exponential function was used to calculate the soil carbon storage to 1 m. The vertical SOC distribution functions were refined for soils under maize production systems using reduced tillage and conventional tillage. In these soils, the vertical SOC distributions are described by piecewise, but still continuous functions where the distribution within the cultivated layer (0-30 cm) is a linear decline under reduced tillage or a constant value under conventional tillage, followed by an exponential decline to 1 m (30-100 cm). The value of predicting SOC concentrations in soil samples using wet oxidation (WalkleyBlack method) and dry near-infrared (NIR) spectrometry was assessed by comparing them to the dry combustion method. NIR spectrometry is considered to be an especially promising method, since it may be used in both proximal and remote sensing applications. In addition, the effect of using paired samples with single SOC determination versus paired samples with replicated (three times) analysis by all (reference and test) methods was tested. It was shown that the use of paired tests without replication dramatically decreases the precision of SOC predictions of all methods, possibly due to high variability of SOC content in reference values analysed by dry combustion. While reasonable figures of merit were obtained for all the methods, the analysis of non-replicated paired samples has shown that the relative RMSE for the SOC NIR method only falls below 10 % for values above ~8 % SOC. For the corrected SOC Walkley Black method the relative RMSE practically never falls below 10 %, rendering this method as semi-quantitative across the range. It was concluded that for method comparison of soil analysis, it is essential that reference sample analysis be replicated for all methods (reference and test methods) to determine the “true” value of analyte as the mean value analysed using the reference method. Finally, the above elements of vertical SOC distribution models as a function of land use and soil type, predicting SOC stocks to 1 m using only a surface (0-5 cm) sample, and the use of NIR spectroscopy as SOC analysis method were combined to assess the changes in SOC stock prediction errors through mapping. Results indicated a dramatic improvement in precision of SOC stock predictions with increasing detail in the input parameters using vertical SOC distribution functions differentiated by land use and soil grouping. Still, the relative error mostly exceeded 20 % which may be seen as unacceptably high for carbon accounting, trade and tax purposes, and the SOC stock accuracy decreased in terms of map R 2 and RMSE. The results were generally positive in terms of the progressive increase in complexity associated with SOC stock predictions and showed the need for a substantial increase in sampling density to maintain or increase map accuracy while increasing precision. This would include an increase both in surface samples for the prediction of SOC stocks using the vertical SOC distribution models, as well as an increase in the sampling of profiles to include more soil types and increase the profile density per land use to improve the vertical SOC prediction models.
Modeling and regulating hydrosalinity dynamics in the Sandspruit river catchment (Western Cape)
(Stellenbosch : Stellenbosch University, 2014-04) Bugan, Richard D. H.; De Clercq, W. P.; Jovanovic, N.; Stellenbosch University. Faculty of Agrisciences. Dept. of Soil Science.
ENGLISH ABSTRACT: Bugan, R.D.H. Modelling and regulating hydrosalinity dynamics in the Sandspruit River catchment (Western Cape). PhD dissertation, Stellenbosch University. The presence and impacts of dryland salinity are increasingly become evident in the semi-arid Western Cape. This may have serious consequences for a region which has already been classified as water scarce. This dissertation is a first attempt at providing a methodology for regulating the hydrosalinity dynamics in a catchment affected by dryland salinity, i.e. the Sandspruit catchment, through the use of a distributed hydrological model. It documents the entire hydrological modelling process, i.e. the progression from data collection to model application. A review of previous work has revealed that salinisation is a result of land use change from perennial indigenous deep rooted vegetation to annual shallow rooted cropping systems. This has altered the water and salinity dynamics in the catchment resulting in the mobilisation of stored salts and subsequently the salinisation of land and water resources. The identification of dryland salinity mitigation measures requires thorough knowledge of the water and salinity dynamics of the study area. A detailed water balance and conceptual flow model was calculated and developed for the Sandspruit catchment. The annual streamflow and precipitation ranged between 0.026 mm a-1 - 75.401 mm a-1 and 351 and 655 mm a-1 (averaging at 473 mm a- 1), respectively. Evapotranspiration was found to be the dominant component of the water balance, as it comprises, on average, 94% of precipitation. Streamflow is interpreted to be driven by quickflow, i.e. overland flow and interflow, with minimal contribution from groundwater. Quantification of the catchment scale salinity fluxes indicated the Sandspruit catchment is in a state of salt depletion, i.e. salt output exceeds salt input. The total salt input to and output from the Sandspruit catchment ranged between 2 261 - 3 684 t Catchment-1 and 12 671 t a-1 - 21 409 t a-1, respectively. Knowledge of the spatial distribution of salt storage is essential for identifying target areas to implement mitigation measures. A correlation between the salinity of sediment samples collected during borehole drilling and the groundwater EC (r2 = 0.75) allowed for the point data of salt storage to be interpolated. Interpolated salt storage ranged between 3 t ha-1 and 674 t ha-1, exhibiting generally increasing storage with decreasing ground elevation. The quantified water and salinity fluxes formed the basis for the application of the JAMS/J2000-NaCl hydrological model in the Sandspruit catchment. The model was able to adequately simulate the hydrology of the catchment, exhibiting a daily Nash-Sutcliffe Efficiency of 0.61. The simulated and observed salt outputs exhibited discrepancies at daily scale but were comparable at an annual scale. Recharge control, through the introduction of deep rooted perennial species, has been identified as the dominant measure to mitigate the impacts of dryland salinity. The effect of various land use change scenarios on the catchment hydrosalinity balance was evaluated with the JAMS/J2000-NaCl model. The simulated hydrosalinity balance exhibited sensitivity to land use change, with rooting depth being the main factor, and the spatial distribution of vegetation. Revegetation with Mixed forests, Evergreen forests and Range Brush were most effective in reducing salt leaching, when the “salinity hotspots” were targeted for re-vegetation (Scenario 3). This re-vegetation strategy resulted in an almost 50% reduction in catchment salt output. Overall, the results of the scenario simulations provided evidence for the consideration of re-vegetation strategies as a dryland salinity mitigation measure in the Sandspruit catchment. The importance of a targeted approach was also highlighted, i.e. mitigation measures should be implemented in areas which exhibit a high salt storage.
The occurrence of bleached topsoils on weakly structured subsoil horizons in the Western Cape and Mpumalanga Provinces of South Africa
(Stellenbosch : Stellenbosch University, 2015-12) Le Roux, Johannes Lukas; Clarke, Catherine E.; De Clercq, W. P.; Stellenbosch University. Faculty of Agrisciences. Dept. of Soil Science.
ENGLISH ABSTRACT: Bleaching is a topsoil discolouration phenomenon recognised at family level within certain soil forms in the South African soil classification system. These topsoil horizons derive their name from the pale greyish colouration they exhibit in the dry state which is the result of the loss of pigmentation agents, specifically Fe oxides and organic material, from the upper part of the soil profile. In recent years, discrepancies regarding both the occurrence of bleached topsoils as part of weakly structured soil profiles in the South African soil landscape, and the description of this phenomenon in the national soil classification system, have become apparent. This has accentuated the clear lack of understanding which exists regarding the genesis of bleached topsoil horizons under weakly structured subsoil conditions in South Africa. Based on the land-use and classification significance of this soil feature, this study aimed to provide clarity on the characteristics of bleached topsoils and some of the weakly structured subsoil horizons they overlie to determine by which mechanism these bleached topsoils develop and if the pedogenetic mechanisms are similar across two regions of South Africa. Due to soil colour’s obvious importance as the only feature with which to recognise topsoil bleaching, an investigation into the measurement and expression of soil colour was also deemed to be important. A total of 26 soil profiles were sampled throughout the Western Cape (WC) and Mpumalanga provinces. Colour was visually determined in the field using a Munsell soil colour chart and also by means of a spectrophotometer in the laboratory. A wide variety of soil chemical and physical properties were also determined for each sampled horizon. For comparison’s sake, the selected soil profiles needed to represent profiles that could potentially qualify as having red/yellow-brown apedal B (ferralsols) or red/yellow neocutanic B horizons (cambisols), either with or without a perceived bleached topsoil (achromic). During sampling on the Highveld, bleaching was observed to be landscape related with bleached orthic A horizons only occurring on yellow-brown apedal B subsoil horizons at lower positions along the plinthic catenas. As a result, sampling on the Mpumalanga Highveld was conducted along catenal transects. In the WC, bleached profiles did not follow a noticeable landscape pattern and subsoils comprising both red and yellow weakly structured horizons were recorded. Soil colour investigations proved Fe oxides to be the main pigmentation agents responsible for the expression of red- and yellow colours in the sampled soils, with soil samples also becoming redder with an increase in the Fe oxide content. Discrepancies were detected in the way soil colour was registered through human perception and spectrophotometer measurements. In general, the eye perceived the soils to be brighter and more chromatic and therefore was less sensitive towards detecting bleached horizon colours. The majority of the determined chemical and physical soil properties did not differ between the Western Cape and Highveld soils and did not show any relation to the bleaching phenomenon in either of the locations. In the Western Cape, profiles tended to have a greater water dispersible clay (WDC) phase, with the bleached Western Cape profiles proving to be even more unstable than the non-bleached variants. Iron oxide characterisation indicated proportionally similar amounts of crystalline and poorly-crystalline Fe oxides were present at both locations although in general bleached topsoils tended to have greater poorly-crystalline Fe contents. This trend was more pronounced in the Highveld profiles and was deemed to be indicative of a wetter soil moisture regime and alternating cycles of Fe reduction and oxide precipitation at this location. The reported poorly-crystalline nature of the Fe oxides together with the observed landscape influences, suggest Fe reduction to be the pedogenetic process responsible for bleached topsoil horizons overlying weakly structured subsoils on the Mpumalanga Highveld. The strong association between bleaching and clay dispersibility in similar profiles of the Western Cape suggest clay eluviation to be a common pedogenetic process in these soils. The presented data is this study did not provide an explanation for how clay eluviation results in bleached soil colours and no evidence was obtained to enable conclusive statements regarding the role of Fe reduction and clay eluviation as independent or complementary processes responsible for bleaching in the Western Cape soils. For the purpose of soil classification in South Africa, the inclusion of bleached orthic A horizons as family criteria in wetter variants of the yellow-brown apedal profiles is suggested. Based on the instability of the clay phase in the Western Cape profiles, it is proposed that these red or yellow weakly structured subsoils would be better classified as neocutanic B horizons and that bleached topsoils can in some instances be indicative of a more dispersive profile.
Plant water relations of Elytropappus Rhinocerotis with specific reference to soil restrictions on growth
(Stellenbosch : University of Stellenbosch, 2010-12) Vermeulen, Tarina; De Clercq, W. P.; Hoffman, J. E.; University of Stellenbosch. Faculty of Agrisciences. Dept. of Soil Science.
ENGLISH ABSTRACT: The Renosterveld of the Western Cape region is often seen as a natural occurring veld type that will very easily re-establish itself wherever land is left unattended. In this study it was firstly noted that where wheatlands of the Berg River catchment (BRC) is left bare for a number of years, the renosterbos as a pioneer is slow in its re-growth response and when it does, certain patches in the landscape are preferred. This study therefore firstly focussed on the soil restrictions that widely determined the positions in the Berg River landscape where the renosterbos will re-establish itself. Secondly we needed to know whether some of the soil restrictions encountered could be alleviated and was possibly due to cultivation of this land. Through aerial observation it was found that a general patchiness does exist in the naturally occurring Renosterveld of the Voëlvlei area and hill tops of the region and was described by others as the true nature of this veld type. Closer investigation of the soils in the Voëlvlei reserve however showed that soil type played a major role in the patchiness found here. When re-growth of the renosterbos in previously cultivated areas was investigated, it was found that the soil type played the major role in the patchiness that occurred. The most commonly found soil restriction was soil density of the lower horizons. Any soil form that prevented the renosterbos to access the perched water table, to about 15m depth could not support the renosterbos. It is however our belief that soil could be prepared for the re-growth of renosterbos and through this action; renosterbos could also be used to alleviate the salinity problems found in this region. Additionally we investigated the impact of land-use change on the soil water balance and soil salinity by comparing a mature re-established stand of Renosterveld with an adjacent wheatfield. From the results, large differences in salinity and soil water behaviour were detected between the Renosterveld and wheatfield. Modelling of soil and plant water relations was done and the results were correlated well with field observations. This research also confirmed that the renosterbos through its deep rootedness is crucial in the conservation of other species found in the Renosterveld resulting from its ability to keep the water table down and with that the salts that is so often a problem in this area.
Properties of bleached topsoils on apedal subsoils : analysis from the land type profile database
(Stellenbosch : Stellenbosch University, 2016-03) Carstens, Marilee Elizabeth; Clarke, Catherine E.; De Clercq, W. P.; Stellenbosch University. Faculty of Agrisciences. Dept. of Soil Science.
ENGLISH ABSTRACT: Bleached topsoils that occur on red and yellow-brown apedal subsoils are poorly understood and taxonomically they are not distinguishable from their non-bleached counterparts. Bleaching of soils is an important pedological indicator since it can reflect a soils water status. Bleached topsoils are more prone to erosion and degradation than their non-bleached counterparts, thus recognising these features is important. Bleaching is also identified by its colour, thus precise and objective colour measurement procedures are required to correctly identify them. The two mechanisms responsible for bleaching are proposed to be iron (Fe) reduction and clay dispersion. The overall aim of this study was to use the data available in the Profile Database to understand the spatial and geomorphic distribution of bleached apedal profiles as well as assess their lithological, chemical, physical, spectral and subsoil colour properties to provide clues on their genesis. This will allow the diagnostic criteria for their correct identification to be based on scientific understanding and also to provide a scientific basis for these bleached soils use and protection. The study made use of pre-existing data from the Agricultural Research Council (ARC) – Institute for Soil, Climate and Water (ISCW) – Soil Profile Information System. Data from 725 soil profiles, with complete chemical and physical analysis, that contained red and yellow-brown apedal and neocutanic subsoils were selected for the study. Subsamples of the A and B horizon from each profile were collected from the soil store of the ISCW. Soil colours were measured both visually with Munsell colour charts and spectroscopically with a Konica-Minolta spectrophotometer. This colour data was used to classify the soils into bleached and non-bleached categories by following the criteria outlined in the South African soil classification system. The effectiveness of visual colour measurement guidelines as outlined by the Munsell colour system and Food and Agricultural Organization (FAO) was evaluated by comparing visual measurements made in the laboratory and in natural daylight (outdoor) conditions. From the results there seems to be no great difference between soil colour measurements made in visual natural daylight and laboratory conditions. Visual colour measurements were also correlated to spectroscopic colour measurements. It was found that the spectrophotometer tended to make soil hues redder in 32% of the observations when compared to visual laboratory and natural daylight observations. Spectroscopic chroma observations showed 0% total agreement with both visual laboratory and natural daylight observations. When compared, the spectrophotometer tends to designate lower chroma values to soils than both visual laboratory and natural daylight colour measurements would. This means the human eye tends to make soil colour more colourful than the spectrophotometer. The weak relationships between soil pigmenting properties and spectroscopically measured colour components showed that soil colour is a complex expression of both physical and chemical soil components and thus cannot be related to individual soil properties. The wide geographical spread of these soils might be the cause of poor soil property-colour component relationships observed. The geographical location of the soils used for this study did not seem to play a significant role in the occurrence of bleached topsoils in different landscapes. The occurrence of topsoil bleaching seemed to be significantly related to parent materials, with the frequency of bleaching being highest in siliceous lithologies and lowest in mafic lithologies. This might explain why bleached topsoils showed the tendency to develop in soils with low reducible Fe and exchangeable magnesium percentage (EMP). Clay movement from the A to B horizon showed no significant trends in terms of bleaching, which was also the case for exchangeable sodium percentage (ESP). In this study the results for clay movement and ESP thus does not support clay dispersion as a possible mechanism for topsoil bleaching. Bleaching tended to increase with a decrease in base saturation, with the highest incidences of bleaching being on dystrophic soils, which in turn could also relate to climate and soil acidity. The highest occurrence of topsoil bleaching took place on yellow-brown apedal subsoils (66%) and in the Avalon soil form (79%). These results might provide evidence for topsoil bleaching to occur in soils with wetter water regimes, since Avalon soils are usually found in wetter landscape positions. It is recommended that the South African Soil Classification Working Group should consider adding bleaching as a family criteria to soil forms containing yellow-brown apedal subsoils.
Rain events based hillslope hydrological processes at the Langgewens Experimental Farm, Western Cape, South Africa
(Stellenbosch : Stellenbosch University, 2013-03) Wasserfall, Michiel Nicolaas; De Clercq, W. P.; Stellenbosch University. Faculty of AgriSciences. Dept. of Soil Science.
ENGLISH ABSTRACT: Hillslope hydrology represents a complex system with several interacting processes influencing the movement of water through the landscape. The Western Cape area of South Africa is expected to be impacted on by a change in climate and the importance of water management that will increase in the future. Climate, especially precipitation, is the driving factor behind the hydrological system and there are currently no predictions as to what the impact will be on the hydrological conditions. The main objective of the study is to understand the hydrological responses along a hillslope and secondly to determine the effect of climate change on the hydrology by using hydrological models. The studied system is situated on the Langgewens Experimental Farm, north of Malmesbury in the Swartland region of the Western Cape. Six sites in a range of vegetation, land use and expected soil types along a toposequence were investigated. All sites are rain fed areas with natural vegetation, seasonal or long-term shrubs. Through monitoring different components of the hydrological cycle, including rainfall, overland flow, infiltration, soil water content, base flow and water table depth at the different sites, the movement of water through the landscape can be defined. Hillslope hydrological processes at different positions on the hillslope were investigated. The baseline data obtained during this process was used in hydrological modelling for the different positions on the hillslope to determine the accuracy of model predictions. Expected future climatic conditions were emulated in this model to determine the possible effect of a change in climate on the hydrological system. The research confirmed the complex interaction between different processes within the hydrological system. At each point along the toposequence different components of the hydrological cycle contributed on a different scale to the hydrological system. Soil properties were the most significant factor influencing water movement through the landscape, directly impacting infiltration, overland flow, lateral water flow and deep percolation. This resulted in water table fluctuations through the seasons as the contribution of different components towards the hydrological cycle changed. By comparing soil water content measurements through the season with modelled water content levels, accurate hydrological models were created for different measuring points in the landscape. By using forecasted climate data of two different weather generators, accurate estimations of expected soil water content were possible. This indicated that droughts will occur on a regular basis in the future. This research made it possible to understand water movement through the landscape at hillslope level and contributed towards future water management plans by estimating future soil water content levels based on current predictions.
Remote sensing of salt-affected soils
(Stellenbosch : Stellenbosch University, 2013-03) Mashimbye, Zama Eric; De Clercq, W. P.; Van Niekerk, Adriaan; Stellenbosch University. Faculty of AgriSciences. Dept. of Soil Science.
ENGLISH ABSTRACT: Concrete evidence of dryland salinity was observed in the Berg River catchment in the Western Cape Province of South Africa. Soil salinization is a global land degradation hazard that negatively affects the productivity of soils. Timely and accurate detection of soil salinity is crucial for soil salinity monitoring and mitigation. It would be restrictive in terms of costs to use traditional wet chemistry methods to detect and monitor soil salinity in the entire Berg River catchment. The goal of this study was to investigate less tedious, accurate and cost effective techniques for better monitoring. Firstly, hyperspectral remote sensing (HRS) techniques that can best predict electrical conductivity (EC) in the soil using individual bands, a unique normalized difference soil salinity index (NDSI), partial least squares regression (PLSR) and bagging PLSR were investigated. Spectral reflectance of dry soil samples was measured using an analytical spectral device FieldSpec spectrometer in a darkroom. Soil salinity predictive models were computed using a training dataset (n = 63). An independent validation dataset (n = 32) was used to validate the models. Also, field-based regression predictive models for EC, pH, soluble Ca, Mg, Na, Cl and SO4 were developed using soil samples (n = 23) collected in the Sandspruit catchment. These soil samples were not ground or sieved and the spectra were measured using the sun as a source of energy to emulate field conditions. Secondly, the value of NIR spectroscopy for the prediction of EC, pH, soluble Ca, Mg, Na, Cl, and SO4 was evaluated using 49 soil samples. Spectral reflectance of dry soil samples was measured using the Bruker multipurpose analyser spectrometer. “Leave one out” cross validation (LOOCV) was used to calibrate PLSR predictive models for EC, pH, soluble Ca, Mg, Na, Cl, and SO4. The models were validated using R2, root mean square error of cross validation (RMSECV), ratio of prediction to deviation (RPD) and the ratio of prediction to interquartile distance (RPIQ). Thirdly, owing to the suitability of land components to map soil properties, the value of digital elevation models (DEMs) to delineate accurate land components was investigated. Land components extracted from the second version of the 30-m advanced spaceborne thermal emission and reflection radiometer global DEM (ASTER GDEM2), the 90-m shuttle radar topography mission DEM (SRTM DEM), two versions of the 5-m Stellenbosch University DEMs (SUDEM L1 and L2) and a 5-m DEM (GEOEYE DEM) derived from GeoEye stereo-images were compared. Land components were delineated using the slope gradient and aspect derivatives of each DEM. The land components were visually inspected and quantitatively analysed using the slope gradient standard deviation measure and the mean slope gradient local variance ratio for accuracy. Fourthly, the spatial accuracy of hydrological parameters (streamlines and catchment boundaries) delineated from the 5-m resolution SUDEM (L1 and L2), the 30-m ASTER GDEM2 and the 90-m SRTM was evaluated. Reference catchment boundary and streamlines were generated from the 1.5-m GEOEYE DEM. Catchment boundaries and streamlines were extracted from the DEMs using the Arc Hydro module for ArcGIS. Visual inspection, correctness index, a new Euclidean distance index and figure of merit index were used to validate the results. Finally, the value of terrain attributes to model soil salinity based on the EC of the soil and groundwater was investigated. Soil salinity regression predictive models were developed using CurveExpert software. In addition, stepwise multiple linear regression soil salinity predictive models based on annual evapotranspiration, the aridity index and terrain attributes were developed using Statgraphics software. The models were validated using R2, standard error and correlation coefficients. The models were also independently validated using groundwater hydro-census data covering the Sandspruit catchment. This study found that good predictions of soil salinity based on bagging PLSR using first derivative reflectance (R2 = 0.85), PLSR using untransformed reflectance (R2 = 0.70), a unique NDSI (R2 = 0.65) and the untransformed individual band at 2257 nm (R2 = 0.60) predictive models were achieved. Furthermore, it was established that reliable predictions of EC, pH, soluble Ca, Mg, Na, Cl and SO4 in the field are possible using first derivative reflectance. The R2 for EC, pH, soluble Ca, Mg, Na, Cl and SO4 predictive models are 0.85, 0.50, 0.65, 0.84, 0.79, 0.81 and 0.58 respectively. Regarding NIR spectroscopy, validation R2 for all the PLSR predictive models ranged from 0.62 to 0.87. RPD values were greater than 1.5 for all the models and RMSECV ranged from 0.22 to 0.51. This study affirmed that NIR spectroscopy has the potential to be used as a quick, reliable and less expensive method for evaluating salt-affected soils. As regards hydrological parameters, the study concluded that valuable hydrological parameters can be derived from DEMs. A new Euclidean distance ratio was proved to be a reliable tool to compare raster data sets. Regarding land components, it was concluded that higher resolution DEMs are required for delineating meaningful land components. It seems probable that land components may improve salinity modelling using hydrological modelling and that they can be integrated with other data sets to map soil salinity more accurately at catchment level. In the case of terrain attributes, the study established that promising soil salinity predictions could be made based on slope, elevation, evapotranspiration and terrain wetness index (TWI). Stepwise multiple linear regressions soil salinity predictive model based on elevation, evapotranspiration and TWI yielded slightly more accurate prediction of soil salinity. Overall, the study showed that it is possible to enhance soil salinity monitoring using HRS, NIR spectroscopy, land components, hydrological parameters and terrain attributes.
Using remote sensing and geographical information systems to classify local landforms using a pattern recognition approach for improved soil mapping
(Stellenbosch : Stellenbosch University, 2022-05) Atkinson, Jonathan Tom; De Clercq, W. P.; Rozanov, Andrei Borisovich; Stellenbosch University. Faculty of AgriSciences. Dept. of Soil Science.
ENGLISH ABSTRACT: Presently, a major focus of digital soil mapping (DSM) in South Africa is unlocking the soil-landscape relationships of legacy soil data by disaggregating the only source of contiguous soil information for South Africa, the National Land Type Survey (LTS) (ARC, 2003). Each land type is best defined as a homogenous mapping unit with a unique combination of terrain type, soil pattern and macroclimate properties (Paterson et al., 2015). One of the prevailing reasons for the LTS longevity and continual temporal-interoperability is that terrain description is expressly related to a suite of catenary soil property descriptions (Milne, 1936). These terrain types are further divided into terrain morphological units (TMUs) representing a sequence of patterns based on a 5-unit landscape model of 1-crest, 2-scarp, 3-midslope, 4-footslope and 5-valley bottom. Importantly, dominant soil distribution patterns are defined by terrain units relying on an elementary terrain topo-sequence pattern approach, with much of the work done on modelling soil variation related to variation in terrain (van Zijl, 2019). Whilst the LTS remains a source of national interest, there is immense opportunity to build on the existing soil inventory data rather than only focus on “breaking it down” (disaggregation). However, what is needed is a standard operating procedure that not only leverages the ability of digital elevation models (DEM) to explicate soil-landscape associations beyond the limited 5-unit landscape model but allows better refinement of soil descriptions with landscape features. Only once the nuances of optimal DEM parametrisation under controlled conditions are fully understood can the complete scope of DSM and digital geomorphological mapping (DGM) applications be explored. This dissertation attempts to synthesise knowledge on theory, methods, and applications of using remote sensing (RS) and geographical information systems (GIS) to classify local landforms using a pattern recognition approach for improved soil mapping in the context of multiscale problems of digital terrain analysis in KwaZulu-Natal. The dissertation is divided into three parts. Part one (Chapter 2) represents the DEM pre- processing and generalisation method and establishes the protocols for soil-landscape covariate application derived from various sensor platforms and spatial scales. Part two (Chapter 3) introduces the concept of improved terrain unit mapping through the geomorphon approach and describes DEM optimisation for standardised geomorphon representation for uniformly describing soil-landscape properties for inputs to DSM applications. Finally, part three (Chapters 4 & 5) looks at applications of DEM sources and geomorphons first from a holistic landscape context by linking digital terrain and soil-landscape analysis to geodiversity. Finally, the benefit of improved RS and GIS combined with quantitative modelling approaches on improving natural resource predictions are explored by modelling soil-ecotope and soil type mapping units and proposing improvements to an existing DSS designed for KwaZulu-Natal Natal. Specifically, this research is organised into four (4) research chapters with an overview of each chapter’s contribution outlined hereafter. Chapter 2 accounts for the recognition and requirements of DEM generalisation from high to medium resolution RS platforms and the influence these pre-processing approaches have on the extraction of a wide range of terrain attributes. Digital elevation data are elemental in deriving primary topographic attributes that are input variables to various regional soil-landscape models. DEMs' utility to extract different topographic indices as primary inputs to DSM allows the generalised soil-formative relationship between topography and soil characteristics to be measured quantitatively. Traditional landscape-scale approaches to extracting and analysing soils remain subjective and an expensive last resort for large-scale regional soil distribution and variability prediction. Selecting the right DEMs is a critical step in the development of any soil-landscape model. Therefore, the ability to represent soil-landscape relationships rapidly and objectively between soil properties and landscape position using emerging technologies and elevation data in a digital environment and at varying scales is fundamental for using soil-landscape mapping as a regional planning tool. There is, however, still varied consensus on the effect of DEM source and resolution on the application of these topographic attributes to landscape and geomorphic characterisation within South Africa. However, Atkinson et al. (2017) have shown that topographic variable extraction is highly dependent on the DEM source and generalisation approach. However, while higher resolution DEMs may represent the “true” landscape surface more accurately, they do not necessarily offer the best results for all extracted terrain variables for modelling soil-landscape outputs. Given the convenience of a wide range of open-source elevation data for South Africa, there is a need to quantify the impact that DEM generalisation approaches have on simplifying detailed DEMs and compare the accuracy and reliability of results between high resolution and coarse resolution data on the extraction of localised topographic variables as a primer for soil-landscape or digital soil models. Chapter 3 explores the harmonisation of geomorphons derived from various RS platforms to define the landscape character in central KwaZulu-Natal. Robust DGM approaches that can simplify and translate the inclusion of “human knowledge” to automatic terrain classification across a broader spectrum of terrain morphological units and a range of DEM spatial scales offer great potential for improved topographic and landscape analysis and must have their utility investigated. Continual advances in quantitative modelling of surface processes, combined with new spatio-temporal and geo-computational algorithms, have revolutionised the auto-classification and mapping of landform components through the automated analysis of high-quality DEMs. Therefore, a thorough assessment of the effects that different pixel resolution (grain size) and DEM sources have on replicating observed geomorphic spatial patterns and representing selected terrain parameters using advanced automated geomorphometric mapping approaches is necessary. Specifically, it would be valuable to interrogate the self-adapting ability of these automated mapping approaches under regional conditions to quantitatively analyse how the choice of terrain model and scale influences the extraction, generalisation, and representation of digitally derived terrain attributes such as slope gradient, elevation and terrain unit feature extent. Equally important is understanding how the variation in resulting terrain unit representation is limited by spatial resolution discontinuities that ultimately influence the extraction and representation of elementary soil properties. Chapter 4 is a shift from the technical aspects of digital terrain preprocessing and modelling and instead attempts to explore the contribution of gridded soil-landscape products to the abiotic landscape development agenda. It would be worthwhile to contextualise and decode these technical aspects of terrain and soil analyses to a holistic landscape development agenda. It is argued that current global environmental problems and questions demand exploration into new scientific perspectives and improved related paradigms and methodologies. Geodiversity (abiotic complexity) has not received the same level of attention as biodiversity (biotic complexity) despite its intrinsic and indivisible linkages to ecosystem and landscape richness characterisation. The ability to better describe the substrate in which biological and human activities occur is of top standing and must have its potential explored. To date, only one landmark study has successfully investigated the influence of environmental factors on geodiversity mapping in South Africa (Kori et al., 2019). Using an array of multimodal environmental covariates, including hydrographic, lithostratigraphic, pedological, climatic, topographic, solar morphometric and geomorphic variables, I aim to provide further confirmation to regional and international geodiversity research agendas. Chapter 5 culminates in applying quantitative DSM methods, with improved terrain representation, to classify productive soil units (ecotopes) as a proposed methodology to improve the current Bioresource Report Writer (BRW) soil-landscape recommendations. In KwaZulu-Natal, it has been accepted that detailed natural resource information based on scientifically accurate and relevant criteria is required to develop spatial layers that planners, developers, local government, and other stakeholders can use to guide future development. At present, the KwaZulu-Natal Department of Agriculture and Rural Development (KZNDARD) can provide high-level crop production approximations for various crops based on BioResource Units (BRU). However, the BRW has not seen a significant revision for over two decades. Still, the natural resource information it contains provides land managers, policymakers and farmers with invaluable access to regional and farm level qualitative estimations of agricultural productivity. There is a need to preserve this information while simultaneously providing modern measures of land management recommendation at multiple scales to the end-user. Against this backdrop, access to readily interpretable soil and crop information is increasingly being prioritised by provincial planning commissions as critical inputs to DSS for sustainable land management within KwaZulu-Natal.
Water- en soutbalanse van geselekteerde besproeide gronde van die benede Bergrivier opvanggebied
(Stellenbosch : Stellenbosch University, 2004-04) Engelbrecht, Hendrik Nicolaas; De Clercq, W. P.; Hoffman, E.; Stellenbosch University. Faculty of AgriSciences. Dept. of Soil Science.
ENGLISH ABSTRACT: A study was conducted between 2000 and 2002 in the lower Berg River catchment of the semi-arid Western Cape Province to investigate the effect of irrigation developments (wheat fields to table grapes) on the quality of the Berg River as well as the sustainability of these developments. This study was necessitated by the mineralisation of both the Breede and Berg River, probably due to irrigation together with the higher pressure on these water resources from the growing demand for fresh water from the Cape Town metropolitan area. Water and Salt balances of two dominant soil patterns (Glenrosa/Swartland and Oakleaf/Hutton soil forms) from the catchment area were monitored at two localities. Vineyard blocks of different ages in the same soil forms were used to study the effect of irrigation over time. The electrical conductivity of the soil water extracts (ECe) was measured three times over depth at the selected sites and the quality of irrigation and drainage return-flow were monitored. Soil water storing capacities of these stony (high rough fragment' fractions) soils were also characterised for more efficient drainage quantity prediction. Glenrosa/Swartland soils showed the highest ECe's (200-400 mx.m") that decreased significantly after four to five years of irrigation and distribution became more uniform over depth. These high salt concentrations were explained due to natural occurrence of salts, mineral weathering and salts from the irrigation water. Oakleaf/Hutton soils showed lower ECe's « 200 nfS.m") but they are subject to the quality of the irrigation water, which is not that constant over years. Localised salt accumulation was observed due to the irrigation method and became more prominent over years. Drainage quantities were under predicted because of the big/high rough fragment fractions and the occurrence of preferential-flow. This prohibited the accurate calculation of the soil water house holding characteristics. It also led to the under calculation of salt return-flow, but it was very evident that the most salt retumflow occurred from the Glenrosa/Swartland soils. Effective irrigation management to achieve and maintain optimal soil water levels and to reduce the negative impact of high ECe's is essential for the sustainability of these irrigation developments. At present it does not seem that the irrigation return-flow is causing dramatic mineralisation of the lower Berg River, but it is a situation that must be monitored as the developments extent and become older (come into production). It seems that irrigation return-flow only has an influence on the quality of the river at the beginning of such a development, but after about three years the influence directly correlates with the quality of irrigation water and mineral weathering.

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