A broad scope of crop models with varying demands on data inputs is being used for several purposes, such as possible adaptation strategies to control climate change impacts on future crop production, management decisions, and adaptation policies. A constant challenge to crop model simulation, especially for future crop performance projections and impact studies under varied conditions, is the unavailability of reliable historical data for model calibrations. In some cases, available input data may not be in the quantity and quality needed to drive most crop models. Even when a suitable choice of a crop simulation model is selected, data limitations hamper some of the models’ effective role for projections. To date, no review has looked at factors inhibiting the effective use of crop simulation models and complementary sources for input data in South Africa. This review looked at the barriers to crop simulation, relevant sources from which input data for crop models can be sourced, and proposed a framework for collecting input data. Results showed that barriers to effective simulations exist because, in most instances, the input data, like climate, soil, farm management practices, and cultivar characteristics, were generally incomplete, poor in quality, and not easily accessible or usable. We advocate a hybrid approach for obtaining input data for model calibration and validation. Recommended methods depending on the intended outputs and end use of model results include remote sensing, field, and greenhouse experiments, secondary data, engaging with farmers to model actual on-farm conditions. Thus, employing more than one method of data collection for input data for models can reduce the challenges faced by crop modellers due to the unavailability of data. The future of modelling depends on the goodness and availability of the input data, the readiness of modellers to cooperate on modularity and standardization, and potential user groups’ ability to communicate.

Smallholder farmers in South Africa continue to be affected by the changing climate despite the existence of support to improve their adaptive capacity. This study focused on the institutional support systems and support types available to farmers in agro-ecological zones of Limpopo Province and assessed support types best suited to each area. Six hundred farmers were purposively sampled across the agro-ecological zones of Limpopo and interviewed. Support types looked at included monetary, machinery, seeds, educational support and others (irrigation scheme, animals, fertilizer, pesticides). Supporting institutions included Agro finance institutions, DAFF, Banks, and NGOs. Results showed that 70.01% of farmers received support from DAFF 25.60% from NGO's and 4.39% from Agro finance institutions. The most number of support received was two types 33.3% of the farmers. The result from the ANOVA showed that there were no significant differences in the level of difficulty experienced by farmers in accessing the various support institutions across the agro-ecological zones. In terms of the various support types received, there was a statistically significant difference in seeds (p ¼ 0.002 < α ¼ 0.05) and educational (p ¼ 0.0001 < α ¼ 0.05) support received between the different areas. Furthermore, the support needs varied across zones with farmers in arid-zone needing machinery, education, seeds and lastly monetary support while the semi-arid zone needed machinery, education, others, seeds, monetary and the humid, machinery, education, others, money and seeds. It is therefore recommended that support for farmers should be location-specific in order to enhance the adaptive capacity of an area and not be based only on the availability of certain support. There is a need for proper coordination between institutions in their aim to assist farmers to cope with climate change.

Smallholder farmers in rural communities that are prevalent in provinces such as Limpopo are not only confronted with the challenges of their direct environment but they also face new challenges in terms of the type of crops to produce in the era of climate change and variability. These challenges influence the way farmers make key decisions. Given that agricultural practices affect more than the farming unit, it is of interest to understand farmers’ behaviour. A survey was carried out across agroecological zones in Limpopo. Six hundred farmers were interviewed to establish key factors underlying their choice of oilseeds to produce. Descriptive statistics and factor analysis were used to analyse the data. Results showed that the choice of crops to produce was influenced by socioeconomic and climatic factors. Factor analysis indicated that floods were the most influential factor in the choice of oilseeds. This was followed by implements, temperature, rainfall, cash, irrigation equipment, input availability and food security. Determining factors varied amongst farmers producing groundnut, soybean and sunflower. Farmers were more hesitant to cultivate sunflower and soybean primarily because of the lack of familiarity with these crops and this in turn magnified the risk created by the uncertainty surrounding the future financial returns from these crops. Further results highlight concerns about resource and input availability in the area. The provision of support in terms of inputs availability, implements, the development of reliable networks for information dissemination and training of oilseed farmers beyond their local environment and sphere is critical. This is particularly so given there is a host of site-specific factors that have a bearing on the farmers’ decision-making processes. Stakeholders therefore need to take into account the variation in factors influencing farmers’ decisions, and put in place site specific measures to properly guide farm management choices.

Smallholder oilseed production constitutes a crucial component of rural economies and continues to face the consequences of a changing climate despite the increased levels of vulnerability. This paper assesses how smallholder oilseed farmers’ adaptive capacity in Limpopo is enhanced through various institutional support schemes within the context of increased climate extremes and their need to sustain production. Six hundred farmers were interviewed across three agro-ecological zones of Limpopo Province. Results show that some of the institutions’ current operations aimed at providing support to farmers do not adequately satisfy the farmers’ needs. A strong linear relationship was observed between the number of support types received by farmers and grain yield, suggesting that farmers who received more support types were relatively less vulnerable. Educational support is ranked as the most significant contributor to enhancing farmers’ adaptive capacity. This emphasizes the need for proper linkages between farmers’ choices of adaptive methods and the types of support needed. Therefore, this study provided a diagnosis of the gaps in essential types of institutional support needed to increase farmers’ resilience, which can be used as an input to beef up the policy and positioning to improve the adaptive capacity.

The inter-seasonal behaviour of rainfall in the Soutpansberg region of South Africa was assessed in relation to changing climate with an attempt to diagnose some of the contributing external factors. Seasonal rainfall data from 1970 to 2009 was characterised for the Soutpansberg using 23 rainfall stations distributed over the mountain range. The normality of rainfall data was quality-controlled using the Pearson correlation coefficient and a double mass curve. Composite rainfall and standardised anomaly index for the region were calculated in order to assess seasonal variability of rainfall. The results showed that the range experienced a decline in seasonal rainfall, from east to west. The North West (NW) part of the region experienced its lowest rainfall in 1985, with a standardised anomaly index (SAI) of −0.94, and its highest rainfall was experienced in 1978, with an SAI of 0.5. The North East (NE) recorded lowest rainfall in 1985 with an SAI of −1, and the highest rainfall was observed in the years ranging from 1977 to 1980 with an SAI of 1. The South East (SE) experienced lowest rainfall in 1985 with a value of −1.25 below the mean, and its highest rainfall (1.25) was experienced in 1976. The study showed that seasonal rainfall in the north-facing slope was lower than the rainfall in the south-facing slope. Trend line analysis indicated that the NW part of the Soutpansberg experienced the most substantial decrease in rainfall. The NW region was followed by the NE, SW, SE and the Central East (CE) respectively in terms of the decline in rainfall. Such behaviour and trends which varies across space and time is a cause for concern in the period of study. This period was characterised by increase in anthropogenic activities, as earlier studies prior to 1970 demonstrated a near stable pattern in terms of the cyclic activity of rainfall.