Root‐zone soil moisture variability across African savannas : from pulsed rainfall to land‐cover switches

The main source of soil moisture variability in savanna ecosystems is pulsed rainfall. Rainfall pulsing impacts water‐stress durations, soil moisture switching between wet‐to‐dry and dry‐to‐wet states, and soil moisture spectra as well as derived measures from it such as soil moisture memory. Rainfall pulsing is also responsible for rapid changes in grassland leaf area and concomitant changes in evapotranspirational (ET) losses, which then impact soil moisture variability. With the use of a hierarchy of models and soil moisture measurements, temporal variability in root‐zone soil moisture and water‐stress periods are analysed at four African sites ranging from grass to miombo savannas. The normalized difference vegetation index (NDVI) and potential ET (PET)‐adjusted ET model predict memory timescale and dry persistence in agreement with measurements. The model comparisons demonstrate that dry persistence and mean annual dry periods must account for seasonal and interannual changes in maximum ET represented by NDVI and to a lesser extent PET. Interestingly, the precipitation intensity and soil moisture memory were linearly related across three savannas with ET/infiltration ∼ 1.0. This relation and the variability of length and timing of dry periods are also discussed.National Science Foundation; European Commission; Bundesministerium für Bildung und Forschung; Academy of Finland.http://wileyonlinelibrary.com/journal/ecohj2020Geography, Geoinformatics and Meteorolog

The new WHO global air quality guidelines : what do they mean for South Africa?

Ambient air quality standards are a key policy lever in air quality management. In South Africa, the introduction of the National Ambient Air Quality Standards (NAAQS) highlighted the shift in the focus of air quality management from source to receptor that was initiated with the introduction of the NEM:AQA. NAAQS were developed considering health impacts, ambient levels at the time and South Africa’s developing economy. There is currently a process starting to review these standards, and this process aligns with the recent release of the new World Health Organization (WHO) Global Air Quality Guidelines (AQG) in September 2021 (World Health Organization, 2021). This is the first update of WHO’s AQG since 2005. The WHO’s guidelines take into account recent evidence of the effect of air pollution on human health, and many of the guidelines are substantially lower than the previous guidelines (Table 1). In this editorial, we ask what the implications of the new WHO Guidelines are for air quality management and compliance in South Africa.https://cleanairjournal.org.zaam2022Geography, Geoinformatics and Meteorolog

Evaluation of modeled actual evapotranspiration estimates from a land surface, empirical and satellite-based models using in situ observations from a South African semi-arid savanna ecosystem

Evapotranspiration (ET) plays a crucial role in the land-atmosphere interaction and climate variability, especially in arid and semi-arid areas. Accurate estimates of ET are important in hydrological and climate modeling. This study evaluates eight ET data products from different models used for ET estimation. The data products are classified into three main categories depending on the type of modeling approaches: namely process-based land surface model, empirical models, and satellite data derived estimates. The different model estimates are evaluated against in situ measurements from the Skukuza flux tower which is situated in a semi-arid savanna in South Africa. The correlation score and cantered root mean square error computed on monthly ET averages indicate that the satellite-derived model and land surface model estimates are closer to the observed ET signal for the Skukuza site, both in-phase and magnitude. The empirical models' outputs tend to reflect a relatively pronounced departure from observations in magnitude. The normalised mean bias computed for different seasons reveals that the estimates from all modeling approaches are close to the observed signal during the transition period (March–May) to the austral summer. In general, all models overestimate ET during summer and underestimate it in winter. A qualitative analysis of the year-to-year variation for different seasons reveals that all model estimates are qualitatively consistent with the observed seasonal pattern of the signal. Satellite and process-based land surface models (LSMs) also show a response to extremes events such as drought years. The study identifies satellite-derived model outputs as a candidate for understanding spatio-temporal variability of ET across different landscapes within the study region, and process-based models to potentially be used for climate change impact studies on ET.The Council for Scientific and Industrial Research [project number EEGC030].https://www.elsevier.com/locate/agrformethj2019Geography, Geoinformatics and Meteorolog

Evaluation of soil moisture from CCAM-CABLE simulation, satellite-based models estimates and satellite observations: a case study of Skukuza and Malopeni flux towers

Reliable estimates of daily, monthly and seasonal soil moisture are useful in a variety of disciplines. The availability of continuous in situ soil moisture observations in southern Africa barely exists; hence, process-based simulation model outputs are a valuable source of climate information, needed for guiding farming practices and policy interventions at various spatio-temporal scales. The aim of this study is to evaluate soil moisture outputs from simulated and satellite-based soil moisture products, and to compare modelled soil moisture across different landscapes. The simulation model consists of a global circulation model known as the conformal-cubic atmospheric model (CCAM), coupled with the CSIRO Atmosphere Biosphere Land Exchange model (CABLE). The satellite-based soil moisture data products include satellite observations from the European Space Agency (ESA) and satellite-observation-based model estimates from the Global Land Evaporation Amsterdam Model (GLEAM). The evaluation is done for both the surface (0– 10 cm) and root zone (10–100 cm) using in situ soil moisture measurements collected from two study sites. The results indicate that both the simulation- and satellite-derived models produce outputs that are higher in magnitude range compared to in situ soil moisture observations at the two study sites, especially at the surface. The correlation coefficient ranges from 0.7 to 0.8 (at the root zone) and 0.7 to 0.9 (at the surface), suggesting that models mostly are in an acceptable phase agreement at the surface than at the root zone, and this was further confirmed by the root mean squared error and the standard deviation values. The models mostly show a bias towards overestimation of the observed soil moisture at both the surface and root zone, with the CCAM-CABLE showing the least bias. An analysis evaluating phase agreement using the cross-wavelet analysis has shown that, despite the models’ outputs being in phase with the in situ observations, there are time lags in some instances. An analysis of soil moisture mutual information (MI) between CCAM-CABLE and the GLEAM models has successfully revealed that both the simulation and model estimates have a high MI at the root zone as opposed to the surface. The MI mostly ranges between 0.5 and 1.5 at both the surface and root zone. The MI is predominantly high for low-lying relative to high-lying areas.Council for Scientific and Industrial Researchhttps://www.hydrology-and-earth-system-sciences.netpm2021Geography, Geoinformatics and Meteorolog