27 research outputs found
Towards ecologically sustainable crop production : a South African perspective
Food production comes at an ecological cost, and the lack of sustainability of South Africa’s crop
production systems is becoming increasingly worrisome. While small scale emerging and homestead
subsistence farming are significant in the agricultural sector, food production is dominated by large scale
commercial agriculture. In this paper we analyse the ecological impact of South African commercial crop
production and what can be done about it. Impact categories considered are divided into what we
consider ‘better-researched’ problems: fresh water depletion, salinisation, soil degradation, eutrophication
and land use change; and into what we consider ‘emerging’ problems for agriculture: greenhouse gas
emissions, soil profile acidification, ecotoxicity and non-renewable resource consumption. While there is
a paucity of quantitative information, it is clear that after decades of cultivation many of our
agroecosystems are degraded or degrading. Sustainable crop production and food security are ‘wicked’
problems – containing dynamic social, economic and biophysical complexities. Increased stakeholder
engagement to better understand these problems, the tradeoffs linked to finding solutions and to involve
those with the resources to turn knowledge into action is required. Collecting key data, turning it into
information within local contexts (involving the ecology, agronomy, sociology, psychology, economics
and other disciplines simultaneously) and communicating it effectively to allow learning and adaptive
management at various spatial and temporal scales is essential. An example is the display of river flows
on a website in real-time to help farmers manage and adapt irrigation practices better, and to connect
them with other stakeholders to improve understanding of the responsibilities of managing water at
local and catchment scales.The Water Research
Commissionhttp://www.elsevier.com/locate/agee2018-01-31hb2017Plant Production and Soil Scienc
Use of the SWB-Sci model for nitrogen management in sludge-amended land
Process-based computer simulation models are often used as reasoning support tools to integrate the
complex processes involved in the soil-plant-atmosphere system. The objectives of this study were to
evaluate the performance of the SWB-Sci model as a reasoning support tool for sludge management in
agricultural lands, and use the validated model to assess the long-term agronomic and environmental
implications of water availability and crop intensity on sludge-amended land. The model was calibrated
for the test crops, maize (Zea mays Pan6966) and oats (Avena sativa L.), using data collected during the
2004/2005 growing season from irrigated plots at the East Rand Water Care Works, Gauteng, South
Africa. Model validation was performed using independent data sets collected during the 2004/2005 to
2007/2008 growing seasons. The model was successfully calibrated for maize and oats as allthe statistical
parameters were within the prescribed ranges [index of agreement (d) >0.8; relative mean absolute
error (MAE%) 0.8]. The results indicate that SWB-Sci simulated
aboveground biomass (TDM) and grain yield (GY) of maize and oats with high accuracy (d > 0.85, MAE%
≤20%, and R2 > 0.91) but with a slight overestimation by 0.2–4 Mg ha−1. The model predicted nitrate
leaching and crop N uptake reasonably well(d > 0.85,MAE% ≤14%, and R2 > 0.8), withslight overestimation
of TDM and GY N uptake by 11–57 and 4–48 kg ha−1, respectively. Long-term model simulations indicate
that fixed sludge application rate recommendations generated from laboratory incubation studies may
in the long-term result in spontaneous excessive nitrate leaching below the active root zone during high
rainfall events, if recommendations do not consider N contribution from soil organic matter. Modelling
also showed that leaving room for rain during each irrigation event may minimize the risk of nitrate
leachingThe Water Research Commission of South Africa (WRC), East Rand Water Care Works (ERWAT), and Technology and Human Resources for Industry Programme (THRIP).http://www.elsevier.com/locate/agwathb2016Plant Production and Soil Scienc
Interpretation of electrical conductivity measurements from ceramic suction cups, wetting front detectors and ECH2O-TE sensors
Electrical conductivity (EC) measurements are often used
to identify and address soil salinity issues in irrigated cropping
systems. In this study, measurements of soil solution
EC (EC-sol) collected in ceramic suction cups (SCs), wetting
front EC (EC-wf) collected in Fullstop wetting front
detectors (WFDs) and soil bulk EC (EC-bulk) measurements
made using ECH2O-TE sensors and converted to
EC-sol, were compared. As a result of different methods of
measurement and different components of soil waterflow
being sampled, variations in EC measurement between
SCs and WFDs were observed. EC-sol was usually higher
than EC-wf, as expected for this system, due to incomplete
mixing between the draining and resident soil water during
infiltration. For periods of high solute leaching, however,
the opposite can occur, indicating that WFDs are sampling
when solutes are first mobilised at the beginning of the
leaching event. The ECH2O-TE sensors were less effective
in measuring the short-term EC dynamics but were
able to detect general changes in soil salinity. This could
reflect difficulties estimating soil EC-sol from measured
EC-bulk, especially at low soil water contents. Each of
these instruments show good potential for application to
guide salinity management practices, but a more detailed
study on a range of soils subjected to different watering
regimes is needed to further improve interpretation of EC
measurements and their application.The Water Research
Commission (Project 1574), the National Research Foundation,
the Cooperative Research Centre for Irrigation Futures
and CSIRO.http://www.plantandsoil.co.zanf201
Municipal sludge as source of nitrogen and phosphorus in perennial pasture Eragrostis curvula production : agronomic benefits and environmental impacts
Land application of sludge has been shown to improve soil properties and aid crop growth, but the possibility of constituent nutrients such as nitrogen and phosphorus reaching environmentally toxic levels has caused governing authorities to set limits to how much sludge can be applied to agronomic land. The high nitrogen utilisation potential of pasture grasses suggests that more sludge can be used in this cropping system without the risk of excess nitrates. This study investigates the effect of exceeding the South African sludge application limit on hay yield, soil nitrates and phosphorus. Field plots were arranged in a complete block design comprising 4 replications of 4 treatments planted to Eragrostis curvula. The treatments consisted of 0, 4, 8 and 16 Mg·ha-1 anaerobically digested sludge. Soil samples were collected before treatment application and at the end of each growing season for N, P, NO3-, NH4+, and Bray-1P analyses. Plant samples were collected at flowering stage for hay yield and N and P uptake determination. Statistical analyses were conducted using analysis of variance (ANOVA) and general linear model (GLM) procedures of Windows SAS 9.0 to evaluate the effect of sludge application rates on hay yield. Results over 4 growing seasons indicate that exceeding the recommended limit increased hay yield by 4% in a dry season (11.7 vs. 12.36 Mg·ha-1) and by 16% in a wet season (14.19 vs. 17.31 Mg·ha-1) and also increased nitrogen uptake by 15%. Sludge applied at double the recommended limit did not cause the accumulation of nitrate and ammonium in the soil, however, both total and Bray-1P were doubled. The study shows that the potential long-term environmental risk of doubling the sludge application rate norm would be from labile P accumulation in the soil profile despite a sludge P:Fe molar ratio of less than unity.The Water Research Commission of South Africa (WRC), East Rand Water Care Works (ERWAT), and the Technology and Human Resources for Industry Programme (THRIP). .http://www.wrc.org.zaam201
Comparison of methods for determining unsaturated hydraulic conductivity in the wet range to evaluate the sensitivity of detectors
The design of passive lysimeters or wetting front detectors determines the tensions at which they collect a water sample from an unsaturated soil. When deployed in the field to help manage irrigation, it is necessary to know the minimum flux of water that can be sampled by a passive lysimeter and how this relates to the drainage flux at field capacity. This requires a good estimate of the unsaturated hydraulic conductivity characteristic, K(h), in the wet range (< 10 kPa). We compared various field, laboratory and theoretical approaches for obtaining the K(h) function and compared these to a reference K(h) function derived by applying inverse modelling approaches to field drainage experimental data. The Van Genuchten model and three of the pedotransfer models produced K(h) functions with a root mean square error of less than 5% compared to the reference, and appear to be simple methods of obtaining a reasonable estimate of unsaturated hydraulic conductivity. However, despite the goodness of fit, there can be a 10-fold difference in conductivity at a given tension < 10 kPa estimated from the different methods. Moreover, water content at field capacity depends entirely on whether field capacity is defined as time elapsed after saturation, a set tension or a minimum flux.Funding for this research was provided by the Water Research
Commission (WRC), South Africa, as part of the WRC
research project entitled ‘Adapting the wetting front detector to
the needs of small-scale furrow irrigators and providing a basis
for the interpretation of salt and nutrient measurements from
the water sample’.http://www.wrc.org.zanf201
Modelling nitrogen leaching : are we getting the right answer for the right reason?
The complexities and challenges in quantifying N leaching have led to development of a range of measurement and modelling techniques, but none are widely applied. Observations that N moves more slowly than water through the soil profile has resulted in different approaches being used to simulate impeded N movement in crop models: (i) by accounting for nitrate NO−3 adsorption to the soil, (ii) by considering incomplete mixing between resident and draining soil water fractions or (iii) a combination of both.We compare and discuss strengths and weaknesses of these approaches. Our inability to directly measure model parameters (especially with regards to simulating N dynamics), and the risk of compensating errors during model testing and calibration, often results in low confidence in simulated N leaching. We caution that our current ability to simulate N leaching is in most cases not yet well enough developed for reliable and accurate predictions. We recommend a more strategic approach involving better linking measurement and modelling to improve understanding of the critical soil processes that control N leaching as one way of further improving our understanding and quantification of N leaching.http://www.elsevier.com/locate/agwathb201
Resistência à penetração em latossolos: valor limitante à produtividade de arroz de sequeiro
Monitoring and modelling draining and resident soil water nitrate concentrations to estimate leaching losses
Quantifying nitrogen (N) losses below the root zone is highly challenging due to uncertainties associated with estimating drainage fluxes and solute concentrations in the leachate. Active and passive soil water samplers provide solute concentrations but give limited information on water fluxes. Mechanistic models are used to estimate leaching, but require calibration with measured data to ensure their reliability. Data from a drainage lysimeter trial under irrigation in which soil profile nitrate (NO3-) concentrations were monitored using wetting front detectors (passive sampler) and ceramic suction cups (active sampler) were compared to NO3- concentrations in draining and resident soil water as simulated by the research version of the Soil Water Balance model (SWB-Sci). SWB-Sci is a daily time-step, cascading soil water and solute balance model that provides draining NO3- concentrations by accounting for incomplete solute mixing. As hypothesized, suction cup concentrations aligned closely with resident soil water concentrations, while wetting front detector concentrations aligned closely with draining soil water NO3- concentrations. These results demonstrate the power of combining monitoring and modelling to estimate NO3- leaching losses. Access to measured draining and resident NO3- concentrations, especially when complemented with modelled fluxes, can contribute greatly to achieving improved production and environmental objectives.Nitrate leaching Monitoring Modelling Draining and resident soil water SWB-Sci
Irrigation scheduling research : South African experiences and future prospects
Many scheduling approaches have been developed with Water Research Commission funding over the past 4 decades and
deployed with varying levels of success; 2 approaches have won prestigious international awards. Soil-based approaches
which include measurement of matric potential (tensiometry), water content (neutron probes, capacitance sensors) and depth
of wetting (wetting front detectors) have been relatively well accepted by farmers. Atmospheric-based approaches apply,
through biophysical modelling of the soil-crop-atmosphere system, thermodynamic limits to the amount of water that can
evaporate from a cropped surface under particular environmental conditions. Modelling approaches have been quite empirical
or somewhat more mechanistic, generic or crop specific, with pre-programmed (e.g. irrigation calendars) or real-time
output. Novel mechanisms have been developed to deliver recommendations to farmers, including resource-poor irrigators.
Although general adoption of objective irrigation scheduling in South Africa is still low, the high cost of electricity and
nitrogen, and scarcity of water is reviving the interest of consultants and irrigators in the application of these tools to use
water more efficiently. Where adoption has been relatively high, intensive support and farmer-researcher-consultant interactions
have been key contributing factors. We propose 4 avenues in the R&D domain to ensure responsible water utilisation.
Firstly, there is a need to continue to advance existing soil-water measurement technology; and secondly, to further develop
new and emerging technologies, like the use of remote sensing. Thirdly, the user-friendliness should be improved as should
systems that support existing scheduling tools; and finally, we need to appreciate that farmers are intuitively adaptive managers,
and we need to develop simple monitoring tools and conceptual frameworks that enable structured learning.http://www.wrc.org.zanf201