Abstract: This study combines historical records of 14C and 3H in the atmosphere and soil with renewal rate and groundwater lumped parameter models to predict the abundance of 14C and 3H in groundwater over time. 624 groundwater samples from numerous studies, over four decades (1978–2019), in South Africa, Namibia, Botswana and Mozambique were collated to compare with predicted groundwater activities of 14C and 3H within the South African Development Community (SADC) region. Spatial datasets of carbonate bearing lithology, C3/C4 vegetation, summer/winter rainfall and coastal proximity were used to apply corrections to 14C and 3H data. Corrected values of 14C and 3H were compared with the theoretical abundance of these tracers, derived from the lumped parameter models, to estimate the general mean residence times and presence of groundwater mixing between modern recharge and older groundwaters. This study found that corrected values produced varying mean residence times derived from 14C ages (∼500–28500 years) and a wide range of potentially mixed waters within each aquifer system (0–100 % of tested wells) across the study area. The largest proportions of mixed groundwater, as well as the youngest mean residence times, were found in alluvial and primary fractured rock aquifers (e.g., western coast of South Africa and southern Mozambique). The smallest proportions of mixed groundwater were predicted in deep confined clay-rich aquifers as well as layered coal bearing carbonate sequences (e.g., Orapa, Malwewe and Serowe, Botswana). Insights into the proportions of mixed groundwater and mean residence times can help assess hydrological resilience on a regional scale. Such information is pertinent in promoting socio-economic development and increased water/food security in the SADC region. By understanding the resilience of groundwater resources, robust and informed strategies for water equality and GDP growth in the SADC region can be envisioned and implemented.

Abstract: Real-Time Control (RTC) technology is increasingly applied in Rainwater Harvesting (RWH) systems to optimise their performance related to water supply and flood mitigation. However, most studies to date have focussed on testing the benefits at an individual site scale, leaving the potential benefits for downstream stormwater networks largely untested. In this study, we developed a methodology to predict how at-source RTC RWH systems influence the behaviour of a stormwater network. Simulation was enabled by coupling the drainage model in SWMM with an RTC RWH model coded using the R software. We modelled two different RTC strategies across a range of system settings (e.g. storage size for RWH and proportion of storage to which RTC is applied) under two different climate scenarios—current and future climates. The simulations showed that RTC reduced flooding volume and peak flow of the stormwater network, leading to a potential mitigation of urban flooding risks, while also providing a decentralised supplementary water supply. Implementing RTC in more of RWH storages yielded greater benefits than simply increasing storage capacity, in both current and future climates. More importantly, the RTC systems are capable of more precisely managing the resultant flow regime in reducing the erosion and restoring the pre-development conditions in sensitive receiving waters. Our study suggests that RTC RWH storages distributed throughout a catchment can substantially improve the performance of existing drainage systems, potentially avoiding or deferring expensive network upgrades. Investments in real-time control technology would appear to be more promising than investments in detention volume alone.