Evaluation and modeling of environmental stressors affecting enteric microbial survival in soil: Implications for wastewater reuse and risk management.

The agricultural reuse of wastewater is a crucial solution to water scarcity, especially in arid and semi-arid regions. However, microbial contamination poses significant health risks, necessitating a better understanding of pathogen survival in natural environmental conditions. This study aimed to investigate the survival dynamics of key enteric bacteria, Escherichia coli, Salmonella enterica, Enterococcus faecium, alongside viral particles, including human adenovirus (HAdV) and a double-stranded DNA somatic coliphage, in soil under real-world semi-arid conditions across two distinct seasons. The study further examined the influence of critical environmental variables, including temperature, relative humidity, and ultraviolet (UV) radiation intensity, on microbial survival. Die-off rate constants (k) were calculated to quantify microbial inactivation, and predictive models were developed using adaptive neuro-fuzzy inference system (ANFIS). E. coli and S. enterica exhibited the fastest die-off rates, while E. faecium demonstrated persistence comparable to viral indicators. Coliphage showed the highest T90 value, closely resembling that of HAdV, supporting its use as a reliable surrogate for adenovirus. UV radiation, elevated temperature, and low humidity significantly accelerating microbial die-off. ANFIS models demonstrated high predictive accuracy in estimating die-off rates based on environmental variables. These findings highlight the importance of semi-arid climatic conditions in rapid die-off rate of microorganisms in soil. However, the prolonged survival of microorganisms during the winter warrants greater attention to mitigate potential public health risks associated with the agricultural reuse of wastewater. Overall, the results emphasize the importance of environmental context in ensuring the safe agricultural reuse of wastewater and in refining microbial risk assessment frameworks.