Framework to assess sources controlling soil salinity resulting from irrigation using recycled water: an application of Bayesian Belief Network

Abstract

Past literature suggests that the irrigation using recycled water over long period of time can lead to accumulation of salt in the soil. In this study, an assessment framework is proposed to evaluate the salinity sources that can have significant impact on the vadose zone salinity when recycled water is used for irrigating sporting ovals. The framework is constructed with a probabilistic expert system, namely, Bayesian Belief Network (BBN). The BBN model analyses the exposure pathways of salt arising from households to its final destination, i.e., accumulation in the soil via the recycled water irrigation. The salt transport modelling indicated a general trend of increase in both total dissolved solids (TDS) and Na+ concentration in the root zone for a simulation period of 1277 days. The BBN analyses indicated that the wastewater stream from washing machines was the major salt source influencing soil salinity, closely followed by the wastewater stream from toilets. Results show that by reducing TDS load by 50% from washing machine alone, reduces the TDS concentration in soil by about 9% and this can be increased to 19% by reducing the TDS loads from both washing machine and toilet water, simultaneously. The study highlighted that any strategies that help in the reduction of salt in the wastewater stream from washing machine will be beneficial in managing the soil salinity as a result of recycled water use for irrigation. Thus, the proposed framework can help to develop recycled water irrigation schemes which are sustainable over the long-run.