(untitled) (Nigerian Journal of Technology, 2022)
Solar water disinfection (SODIS) is recognised and promoted as a simple and low-cost method for water quality improvement and diarrhoea prevention. However, there is potential for underexposure and incomplete disinfection due to the uncertainty arising from variable weather/exposure period. This study presents a probabilistic methodology for obtaining exposure periods from time series of historical solar energy data capable of resolving this uncertainty. To do this, SODIS exposure period was interpreted and computed in agreement with the underlying physical processes that govern geometric distribution. The methodology was illustrated by using geometric distribution to predict monthly exposure periods at 5% exceedance probability for 324 locations in Southeastern Nigeria. The parameter of the geometric distribution was estimated from solar radiation data obtained from NASA geo-satellite database. The results revealed both spatial and temporal variation of exposure period. Two days of exposure would ensure complete disinfection 95% of the days in November to May in virtually all the locations of the region. June to September is the least favourable period for SODIS application in Southeastern Nigeria, mostly requiring more than 2 days of exposure to ensure treatment. Performance validation of the model using confusion matrix showed an overall prediction accuracy of 83%, suggesting a reliable model for the prediction of exposure period. The exposure periods were presented in the form of monthly maps to serve as a tool for guarding against underexposure.