Techniques for assessing impacts of projected climate change on agrohydrological responses in the Limpopo catchment.

Abstract

Climate detection studies point to changes in global surface temperature and rainfall patterns over the past 100 years, resulting from anthropogenic influences. Studies on the analysis of rainfall patterns [1950 – 1999] in southern Africa’s summer rainfall areas show an increase in the duration of late summer dry spells, and this change is in line with expected effects of global warming. Observations of surface temperature increases are consistent with climate projections from General Circulation Models (GCMs), as well as with overall changes in climate over the past century. As such, the alterations in climate conditions have a potential to significantly impact agro-ecosystems. The changes in these climatic patterns are projected to result in a cascade of changes in crop responses, and their associated crop yield-limiting factors through altering water available for agriculture, as well as yield-reduction factors by increasing pest/disease/weed prevalence, both of which may lead to agricultural production being affected severely. The objective of this study is to explore effects of scenarios of climate change on agrohydrological responses in the Limpopo Catchment, with an emphasis on the development and application of statistical modelling and analysis techniques. The algorithms of temperature based life cycle stages of the Chilo partellus Spotted Stem Borer, those for agricultural water use and production indicators, and for net above-ground primary production (an option in the ACRU model) as a surrogate for the estimation of agricultural production. At the time that these analyses were conducted, the downscaled daily time step climate projections of the ECHAM5/MPI-OM GCM, considered to indicate projections that are midway between the extremes from other GCMs for southern Africa, were the only scenarios available at a high spatial resolution which had been configured for South Africa. Further, the statistical analysis techniques conducted in the dissertation include quantitative uncertainty analyses on the temperature and precipitation projections from multiple GCMs (the output of which subsequently became available), as well as validation analyses of various algorithms by comparing results obtained from the GCM’s present climate scenarios with those from historically obtained climates from the same time period. The uncertainty analyses suggest that there is an acceptable consistency in the GCMs’ climate projections in the Limpopo Catchment, with an overall high confidence in the changes in mean annual temperature and precipitation projections when using the outputs of the multiple GCMs analysed. However, the means of monthly projections indicated varied confidence levels in the GCMs’ output, more so for precipitation than for temperature projections. Findings from the Validation analyses of the ECHAM5/MPI-OM GCM’s present climate scenario estimations of agricultural production and the agricultural yield-reduction (Chilo partellus) factor against those from observed baseline climate conditions for the same time period indicated a positive linear relationship and a high spatial correlation. This suggests that the ECHAM5/MPI-OM GCM’s present climate scenario is relatively robust when compared with output from observed climate conditions. ECHAM5/MPI-OM GCM projections show that agricultural production in future might increase by over half in the southern and eastern parts of the Limpopo Catchment compared to that under present climate conditions. Findings from the projections of the yield-limiting factor representing water available for agriculture over the Catchment suggest increases in the agricultural water productivity indicator under future climate conditions, with pronounced increases likely in the eastern and southern periphery. On the other hand, the agricultural water use indicator maintained high crop water use over most of the Catchment under all climate scenarios, both present and future. These positive effects might be due to this particular GCM projecting wetter future climate conditions than other GCMs do. Similar increases were projected for the yield-reduction factor, viz. the development of Chilo partellus over the growing season. These results suggest an increase in the C. partellus development, and thus prevalence, over the growing season in the Catchment, and this correlates spatially with the projected rise in agricultural production. The projected positive effects on agricultural production are thus likely to be reduced by the prevalence in agricultural yield-reduction factors and restricted by agricultural yield-limiting factors. The techniques used in this study, particularly the temperature based development models for the agricultural yield-reduction factor and the agricultural water use/water productivity indicators, could be used in future climate impact assessments with availability of outputs from more and updated GCMs, and in adaptation studies. This information can be instrumental in local and national policy guidance and planning. Keywords: Climate projections (scenarios), agricultural production, agricultural yield-reduction (Chilo partellus) and -limiting factors, uncertainty analysis, validation analysis.