Analysis of a probabilistic approach for modelling and assessment of the water quality of rivers

Abstract Monitoring the ecological status of water bodies is crucial to guarantee human health and economic development. However, monitoring often deficient in developing regions due high installation maintenance costs, thus it frequently supported by quality models, whose results are themselves affected lack detailed input data. A possible solution use probabilistic models that consider inherent uncertainty different inputs. In this research, we extended a simple model (QUAL-UFMG, based on Qual2E) through Monte Carlo simulations generate applied representative case study Brazil. Results showed that, depending distribution probabilities variability parameters adopted, outcome non-deterministic modelling approach may differ significantly from deterministic one regarding compliance with standards. Moreover, strategy more scientifically transparent robust, as explicitly communicates both measured data results. We conclude particularly useful low availability such countries, uncertainties insufficient monitoring, risk elevated prevalence sanitation. HIGHLIGHTS expanded simulations. Outcomes approaches compared for There be significant differences standards taken; key scarce networks.