Regional Scale Risk to the Ecological Sustainability and Ecosystem Services of an African Floodplain System

Water and sediment chemistry drivers of chlorophyll-a dynamics within a Ramsar declared floodplain pan wetland system

Floodplain pans are hydrologically dynamic in nature and characterised by variables such as chlorophyll-a (chl-a), water, and sediment chemistry over their hydroperiods. The present study investigated the spatio-temporal variations in water and sediment physico-chemical, and chlorophyll-a concentration characteristics of six floodplain pans found in the Ramsar declared Makuleke wetlands, Kruger National Park, South Africa. The water and sediment physico-chemical variable values were generally elevated during the high-water period, whereas chlorophyll-a concentrations varied across pans and hydroperiod. Benthic chl-a concentration significantly varied across pans with concentrations ranging from 161 to 1036.2 mg m2. The two-way ANOVA showed significant differences in benthic chl-a concentration among hydroperiods, and no significant differences were observed in pelagic chl-a across pans and hydroperiods. Generally, pelagic and benthic chl-a concentration increased as water and sediment chemistry variables increased. Furthermore, three sediment variables, i.e. pH, calcium, and magnesium, and water conductivity were found to be significant in structuring benthic chlorophyll-a dynamics in pans. However, none of the sediment and water variables had a significant effect on pelagic chl-a. Hydroperiod had a significant effect on influencing chl-a concentration, with high and low water level periods being characterised by low and high chl-a concentration, respectively. The n-MDS results showed strong overlaps in chl-a biomass among the Makuleke floodplain pans across hydroperiods. The increasing chl-a concentration in these floodplain pans due to potential bioturbation effects as a result of large mammals could potentially lead to eutrophication, which in turn could affect the system's primary productivity and aquatic biota. Therefore, it is important to establish a continuous monitoring programme on these pans to inform sound management decisions.

Bayesian Network Applications for Sustainable Holistic Water Resources Management: Modeling Opportunities for South Africa

Anthropogenic transformation of land globally is threatening water resources in terms of quality and availability. Managing water resources to ensure sustainable utilization is important for a semiarid country such as South Africa. Bayesian networks (BNs) are probabilistic graphical models that have been applied globally to a range of water resources management studies; however, there has been very limited application of BNs to similar studies in South Africa. This article explores the benefits and challenges of BN application in the context of water resources management, specifically in relation to South Africa. A brief overview describes BNs, followed by details of some of the possible opportunities for BNs to benefit water resources management. These include the ability to use quantitative and qualitative information, data, and expert knowledge. BN models can be integrated into geographic information systems and predict impact of ecosystem services and sustainability indicators. With additional data and information, BNs can be updated, allowing for integration into an adaptive management process. Challenges in the application of BNs include oversimplification of complex systems, constraints of BNs with categorical nodes for continuous variables, unclear use of expert knowledge, and treatment of uncertainty. BNs have tremendous potential to guide decision making by providing a holistic approach to water resources management.