Two new species of Pelargonium (Geraniaceae) from the Western and Northern Cape Provinces (South Africa) and their position within P. section Hoarea

Pelargonium hammansbergense and P. roseopetalum are described as new species. Both are deciduous geophytes with turnip-shaped tubers belonging to P. section Hoarea. These two species share spathulate petals with narrow cuneate claws. However, they differ in leaf shape, flower colour and markings on the petals. Their flower structure corresponds to that of P. aridicola, P. hirtipetalum, P. pubipetalum, P. reflexipetalum and P. tripalmatum. The seven species are compared with regard to the flower and leaf morphology, palynology and chromosome numbers. They all occur in the winter rainfall region along the west coast of South Africa. The two new species described here are illustrated and a key for the identification of the seven species with a P. aridicola flower type is included.

Can CHIRPS fill the gap left by the decline in the availability of rainfall stations in Southern Africa?

Rainfall is the most important input to any hydrological or water resources study. The decline in the number of suitable rainfall stations since the 1970s is a cause for concern, plus there is an additional complication in that – for a number of catchments – mean annual precipitation (MAP), as derived from a recent study by Pegram, differs substantially from those adopted by the Water Resources of South Africa, 2012 study (WR2012) (mostly as derived by Dent). Rainfall data sourced by the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) satellite database was selected as a basis for comparison, both for catchment MAP and time series of monthly rainfall as used for input to the Pitman hydrological model (WRSM/Pitman, previously called WRSM2000). The analyses revealed that the WR2012 method of constructing the time series yielded the best results overall, but the difference was not marked, except in the winter rainfall region, where CHIRPS (and to a lesser extent, Pegram) performed poorly. It is concluded that CHIRPS will have a role to play in future water resources studies. It is recommended that the study be extended to cover a larger sample of catchments with up-to-date rainfall and that the possibility of CHIRPS data being recalibrated for the winter rainfall area be investigated.

South African Land Degradation Monitor (SALDI) – An overview of recent advancements

<p>For many decades the problem of land degradation has been an issue in South Africa. This is mainly due to the high variability of the mostly semi-arid climatic conditions providing a challenging environmental setting. Strong population growth and resulting socio-economic pressure on land resources aggravate the situation. Thus, reaching a number of Sustainable Development Goals (SDGs), like achieving food security (#2), access to clean water (#6), and the sustainable use of terrestrial (#15) and marine (#14) resources represents a challenge.</p><p>In South Africa, land degradation has been linked to the terms veld degradation and soil degradation and has been addressed by numerous measures over the past decades. However, there is still uncertainty on the extent of human induced land degradation as compared to periodic climate induced land surface property changes. In cooperation with South African institutions and stakeholders the overarching goal of SALDi is to implement novel, adaptive, and sustainable tools for assessing land degradation in multi-use landscapes. Building upon the state of the art in land degradation assessments, the project aims to advance current methodologies by innovatively incorporating inter-annual and seasonal variability in a spatially explicit approach. SALDi takes advantage of the emerging availability of high spatio-temporal resolution Earth observation data (e.g. Copernicus Sentinels, DLR TanDEM-X, NASA/USGS Landsat), growing sources of in-situ data and advancements in modelling approaches.</p><p>SALDi focusses on six study sites representing a major climate gradient from the (humid) winter-rainfall region in the SW across the (semi-arid) year-round rainfall to the (very humid) summer-rainfall region in the NE. The sites cover also different geological conditions and different agricultural practices. These include commercial, rain-fed and irrigated cropland, free-range cattle and sheep farming as well as communal and subsistence farming. Protected areas within our study regions represent benchmark sites, providing a foundation for baseline trend scenarios, against which climate-driven ecosystem-service dynamics of multi-used landscapes (cropland, rangeland, forests) will be evaluated.</p><p>The aim of this presentation is to provide an overview of recent activities and advancements in the three thematic fields addressed by the project:</p><p>i) to develop an automated system for high temporal frequency (bi-weekly) and spatial resolution (10 to 30 m) change detection monitoring of ecosystem service dynamics,</p><p>ii) to develop, adapt and apply a Regional Earth System Model (RESM) to South Africa and investigate the feedbacks between land surface properties and the regional climate,</p><p>iii) to advance current soil degradation process assessment tools for soil erosion.</p><p>A number of additional SALDi team member presentations will provide detailed information on current developments.</p>

On the combination of rotated principal component analysis regionalization technique and linear regression in seasonal rainfall prediction

This study considers the selection of predictors for regional rainfall based on dynamical considerations; for this reason, a regionalization technique that can preserve the underlying physics of rainfall was used in obtaining landmasses and local oceanic domains that are spatially coherent. For the study region (Africa, south of the equator), the adjacent oceans play a vital role in the seasonal rainfall variability at the landmasses; thus uncovering the complex nature of the multivariate relationship between rainfall coherent landmasses and local oceanic domains will enhance the construction of oceanic indices as predictors of seasonal rainfall at specific landmasses using linear regression analysis. Among different cluster analysis techniques, the rotated principal component analysis (PCA) is both fuzzy and allows the overlapping of the classified data set, which makes it a better choice for geophysical research that aims to regionalize continuous data such as rainfall. 10 regions with spatially homogeneous austral summer monthly rainfall totals were classified using the rotated PCA; some classified regions featured landmasses that are spatially coherent with the adjacent ocean, which qualifies them to be further considered on how rainfall anomaly and other physical parameters related to rainfall (e.g. convergence, relative vorticity, and sea level pressure) at the adjacent oceans explain the variations in austral summer rainfall anomaly at the homogeneous landmasses. The analysis of the physical mechanisms associated with the time development of the selected rainfall regions reveals that at the west-central equatorial rainfall region, variations in relative vorticity and convergence are associated with the development of the rainfall region; whereas at the central domains of southern Africa, variations in the patterns of sea level pressure, relative vorticity and convergence at the landmasses, the tropical and the southwest Indian Ocean can be associated with the development of the distinct rainfall sub-regions. The predictability of austral summer rainfall anomaly at the homogeneous landmasses using appropriate predictors at the adjacent local oceanic domains was relatively more accurate at the deep tropics, possibly due to the dominating mechanism of convergence in controlling the tropical rainfall.

Spatial and temporal analysis of the mid-summer dry spells for the summer rainfall region of South Africa

South Africa is frequently subjected to severe droughts and dry spells during the rainy season. As such, rainfall is one of the most significant factors limiting dryland crop production in South Africa. The mid-summer period is particularly important for agriculture since a lack of rain during this period negatively affects crop yields. Dry spell frequency analyses are used to investigate the impacts of sub-seasonal rainfall variability on crop yield, since seasonal rainfall totals alone do not explain the relationship between rainfall and crop yields. This study investigated the spatial and temporal occurrences of the mid-summer dry spells based on magnitude, length and time of occurrence in the major maize growing areas of the summer rainfall region of South Africa. Three thresholds of 5 mm, 10 mm, and 15 mm total rainfall for a pentad were used for the analysis of dry spells. Dry spell analysis showed that dry pentads occur during mid-summer with differing intensity, duration and frequency across the summer rainfall region. Annual frequency of dry pentads for the mid-summer period ranged between 0 and 4 pentads for the 5 mm threshold and 1 to 7 for the 10 mm and 15 mm thresholds. The non-parametric Mann-Kendall trend analysis of the dry pentads indicates that there is no significant trend in the frequency of dry spells at a 95% confidence level. The initial and conditional probabilities of getting a dry spell using the Markov chain model also showed that there is a 32% to 80% probability that a single pentad will be dry using the 15 mm threshold. There is a 5% to 48% probability of experiencing two consecutive dry pentads and 1% to 29% probability of getting three consecutive dry pentads. The duration and intensity of dry spells, as well as the Markov chain probabilities, showed a decrease in dry spells from west to east of the maize-growing areas of the summer rainfall region of South Africa.