Application of Harvey-Garabedian model for describing bacterial removal in Sand Abstraction Systems associated with ephemeral rivers

There have been concerted efforts to find alternative sources of water for small rural communities in the Southern Africa region, and one such initiative is Sand Abstraction Systems (SAS) or infiltration galleries. The sand formation of the riverbed of an ephemeral river is utilised as a natural filter giving potable water of high quality, but is prone to pathogenic contamination. The main objective of our study was to test the suitability of Harvey and Garabedian model for describing bacterial removal in SAS. The Harvey and Garabedian model with some modifications was adopted due to the few parameters required in applying the model. The coefficients and media properties were established from laboratory experiments and field studies. The implicit finite difference method was applied to solve the numerical model equation and to simulate the aquifer response to Escherichia coli for Nkayi SAS. The results of the bacterial simulation from the model fitted well with measured field data and with a small margin of error between the field results and the model (+/-5 coliform count/100 ml).     

The impact of climate change on global energy use

Robust decision making, a growing approach to infrastructure planning under climate change uncertainty, aims to evaluate infrastructure performance across a wide range of possible conditions and identify the most robust strategies and designs. Robust decision making seeks to find potential weaknesses in systems in order to gird these through a combination of policy, infrastructure, and, in some cases, resilient or recovery strategies. A system can be explored by simulating many combinations of uncertain climatic and economic parameters; statistical clustering can identify parameter thresholds that lead to unacceptable performance. Often, however, uncertain variables are correlated, complicating the robustness analysis and casting doubt upon the thresholds identified. Here, we evaluate the impact of ordinary, hidden correlations in uncertainty parameters that drive simulation in robust decision making. We induced correlations between temperature and key climatic and economic parameters. We tested correlations of 0%, 30%, 60%, and 90% between temperature and the absolute value of precipitation, coefficient of variation, and downward surface solar radiation, and negative correlations between temperature and net variable benefit and the discount rate. We used a calibrated simulation model of a dam system regulating Lake Tana, Ethiopia, to compute the agricultural supply and net present value of the reservoirs. As the correlation strength increased, the results converged in a smaller region. We found that strong correlations depressed robustness scores of lower-performing alternatives and conversely increased results of the higher-performing alternatives. As the correlations increased in favorable alternatives, the failure thresholds became more extreme, speciously suggesting that only intense changes would result in poor performance. This overall analysis highlights the degree to which correlations of an interconnected climatic and economic system can impact outcomes of robust decision making and suggests methods to avoid confounding results.