Assessment of Microbial Contamination in the Infulene River Basin, Mozambique

Water microbial contamination is one of the major threats to human health. The study focus is on Infulene River Basin, a urban catchment with mainly informal settlements, with limited water supply and sanitation. In the catchment there are two wastewater treatment plants, one hospital and beer factory located on the banks of the main stream; water from this stream is used for urban agriculture and domestic uses by some dwellers. These factors present a significant health risk from water-borne diseases. At the moment there is limited knowledge about the level of microbial contamination of the different sources of water at the disposal of the communities. Thus, a preliminary study on fecal microbial contamination was conducted targeting the Infulene River and the drainage system from the nearby Maputo city draining into the system, with additional investigation on the drinking water provided by the city water supply company. The quantification of Total Coliforms (TC) and Escherichia coli (EC) was conducted at several sampling locations. Results were compared with official drinking water standards. Eighty two percent (82%) and 61% of Infulene river water and drainage water samples were positive for TC (105 to 109 NPN/100 mL) and EC (105 to 107 NPN/100 mL), respectively. For drinking water samples, 63% and 23% were positive for TC (up to 6000 NPN/100 mL) and EC (up to 1000 NPN/100 mL), respectively. Higher microbial contamination was found in neighborhoods with the poorest sanitation and shallow groundwater, i.e., Chamanculo, Xipamanine, Mafalala, Aeroporto and Maxaquene, a situation that was more expressive during the rainy season. Overall, the study confirmed the high vulnerability to microbial contamination of all sources investigated due to poor sanitation and lack of drainage infrastructure. The risks to human health might be even higher considering that contaminated water is used for gardening of vegetable watering and domestic use

Applicability of a processes-based model and artificial neural networks to estimate the concentration of major ions in rivers

Modelling is an alternative solution to reduce the cost of water quality monitoring. Commonly, concentration of pollutants is estimated based on limited sampling information. Concentration of ions in rivers can be estimated using modelling strategies that involve statistics and artificial intelligence as well as the understanding of physical processes. Therefore, the performance of feedforward neural networks that employs the Levenberg-Marquardt optimization method was compared to the PPBM recently proposed. Both ANN and PPBM were used to estimate the concentration of major ions (Na+, K+, Mg2+, Ca2+, HCO3 −, SO4 2−, Cl−, and NO3 −) in river water based on pH, alkalinity, and temperature. Root-mean-square error and Pearson correlation coefficient (R) together with its p-value were used to evaluate the quality of results of both models. The ANN model provides better estimates compared to the PPBM in most cases. However, the PPBM has the possibility to evaluate its predictions by using the difference between the estimated and measured electrical conductivity. If the predictions are not good the PPBM can be recalibrated, whereas the ANN model is limited in this respect. Another disadvantage of ANN models is that they are developed based on historical data and if limited data are available, such models cannot be used. This latter disadvantage makes the PPBM superior in developing countries, where often little or no consistent historical data exist

A Simplified Model to Estimate the Concentration of Inorganic Ions and Heavy Metals in Rivers

This paper presents a model that uses only pH, alkalinity, and temperature to estimate the concentrations of major ions in rivers (Na+, K+, Mg2+, Ca2+, HCO3−, SO42−, Cl−, and NO3−) together with the equilibrium concentrations of minor ions and heavy metals (Fe3+, Mn2+, Cd2+, Cu2+, Al3+, Pb2+, and Zn2+). Mining operations have been increasing, which has led to changes in the pollution loads to receiving water systems, meanwhile most developing countries cannot afford water quality monitoring. A possible solution is to implement less resource-demanding monitoring programs, supported by mathematical models that minimize the required sampling and analysis, while still being able to detect water quality changes, thereby allowing implementation of measures to protect the water resources. The present model was developed using existing theories for: (i) carbonate equilibrium; (ii) total alkalinity; (iii) statistics of major ions; (iv) solubility of minerals; and (v) conductivity of salts in water. The model includes two options to estimate the concentrations of major ions: (1) a generalized method, which employs standard values from a world-wide data base; and (2) a customized method, which requires specific baseline data for the river of interest. The model was tested using data from four monitoring stations in Swedish rivers with satisfactory results

Assessment of Microbial Contamination in the Infulene River Basin, Mozambique

Water microbial contamination is one of the major threats to human health. The study focus is on Infulene River Basin, a urban catchment with mainly informal settlements, with limited water supply and sanitation. In the catchment there are two wastewater treatment plants, one hospital and beer factory located on the banks of the main stream; water from this stream is used for urban agriculture and domestic uses by some dwellers. These factors present a significant health risk from water-borne diseases. At the moment there is limited knowledge about the level of microbial contamination of the different sources of water at the disposal of the communities. Thus, a preliminary study on fecal microbial contamination was conducted targeting the Infulene River and the drainage system from the nearby Maputo city draining into the system, with additional investigation on the drinking water provided by the city water supply company. The quantification of Total Coliforms (TC) and Escherichia coli (EC) was conducted at several sampling locations. Results were compared with official drinking water standards. Eighty two percent (82%) and 61% of Infulene river water and drainage water samples were positive for TC (105 to 109 NPN/100 mL) and EC (105 to 107 NPN/100 mL), respectively. For drinking water samples, 63% and 23% were positive for TC (up to 6000 NPN/100 mL) and EC (up to 1000 NPN/100 mL), respectively. Higher microbial contamination was found in neighborhoods with the poorest sanitation and shallow groundwater, i.e., Chamanculo, Xipamanine, Mafalala, Aeroporto and Maxaquene, a situation that was more expressive during the rainy season. Overall, the study confirmed the high vulnerability to microbial contamination of all sources investigated due to poor sanitation and lack of drainage infrastructure. The risks to human health might be even higher considering that contaminated water is used for gardening of vegetable watering and domestic use