Climate change impact on water treatment plants: analysis of chlorophyll-a levels and process performance.

Climate change significantly impacts the risk of eutrophication and, consequently, chlorophyll-a (Chl-a) concentrations. Understanding the impact of water flows is a crucial first step in developing insights into future patterns of change and associated risks. In this study, the Statistical DownScaling Model (SDSM)-a widely used daily downscaling method-is implemented to produce downscaled local climate variables, which serve as input for simulating future hydro-climate conditions using a hydrological model. The vulnerability of water quality, particularly Chl-a concentrations in the Latyan Dam and Tehranpars Water Treatment Plant (TWTP) is assessed through six fuzzy regression models under three scenarios: RCP2.6, RCP4.5, and RCP8.5. Projections indicate an increase in minimum temperatures for the Jajrood watershed ranging from 92 to 93%. Seasonal forecasts suggest significant precipitation during the dry season. The HYMOD model predicts increases in streamflow of approximately 97%, 90%, and 92% by 2050 under RCP2.6, RCP4.5, and RCP8.5, respectively, indicating a heightened risk of flooding that poses economic, health, and environmental concerns. Among the six fuzzy regression models, FGR1, FGR3, and FGR4 demonstrated the most favorable results in modeling Chl-a output from the TWTP. In conclusion, while Chl-a concentrations in the effluent of the TWTP are only slightly influenced by climate change, the effects on streamflow patterns are significant. These findings highlight serious future water quality challenges and increased vulnerability of water resources due to climate change.