Assessment of the impact of climate change on water quality using statistical methods and WQI

Background and Objective

Water quality assessment using quality indices is an effective approach for managing aquatic systems and safeguarding water resource quality. Historically, rivers have played a crucial role in supplying drinking and agricultural water, contributing significantly to the formation of civiliza-tions. Over the past half-century, the hydrological conditions of the Darband River, Tehran's sec-ond-largest river in terms of discharge, have been impacted by population growth and urban devel-opment in Tehran. This study aims to evaluate the current water quality of the Darband River and forecast its future condition under RCP scenarios. Monthly data on precipitation, temperature, hardness, TDS, EC, PH, and SO4 from the statistical period 1988–2005 were analyzed using the Water Quality Index (WQI). To examine the impact of climate change on river water quality, re-gression relationships were established between discharge parameters and water quality indices. Based on predicted discharge during the 2030–2047 period, water quality conditions under WQI were calculated for three scenarios: RCP2.6, RCP4.5, and RCP8.5. Statistical analyses revealed that the water quality of the river in both the baseline and future periods is expected to remain in favor-able conditions

Methodology

This section discusses the various stages of the research process. After collecting baseline in-formation and data for the Darband River basin (located in Tehran), the performance of climate models from the Fifth Assessment Report of the IPCC is evaluated. To assess the performance of these climate models, simulated climate variable results for the study area during the 17-year base-line period (1988–2005) are compared with observed recorded data. For this purpose, statistical error metrics, including Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Nash-Sutcliffe Efficiency (NSE), and the correlation coefficient (r), were employed. Subsequently, to utilize the output of AOGCM models in simulating qualitative climate variables for future periods, their com-putational grid cells, which are spatially coarse for the region, need to be downscaled to the station level. In this study, the Change Factor (CF) method was used for downscaling due to its simplicity, computational efficiency, and resulting savings in time and cost. The CF method calculates the climate change scenario based on the ratio of the long-term averages simulated by AOGCMs for the climate change period to the long-term averages simulated for the baseline period. Finally, varia-tions in water quality for both the baseline and future periods will be analyzed using the Water Quality Index (WQI). To examine changes in water quality using WQI, relevant parameters must first be measured, followed by the calculation of the WQI using a mathematical formula typically involving weighted contributions from each parameter. WQI computation will be conducted after collecting data, which includes parameters such as DO, BOD, turbidity, total suspended solids (TSS), nitrate, phosphate, pH, temperature, and fecal coliform.

Findings

Based on the results obtained from evaluating the performance of AOGCM models in estimat-ing precipitation and temperature in the region, the NSE for both climate variables is close to 1, in-dicating the successful simulation of climate variables by these models. To calculate future climate change scenarios for precipitation and temperature during the 2030–2047 period relative to the base-line period (1988–2005), GFDL-ESM2G and MIROC ESM-CHEM models were employed under RCP 2.6, RCP 4.5, and RCP 8.5 scenarios, respectively. The results indicated that all scenarios (ex-cept for RCP 2.6) show a decrease in the long-term annual mean precipitation in future years com-pared to the baseline period. The greatest reduction in long-term annual mean precipitation is pro-jected under the RCP 8.5 scenario. Similarly, all scenarios suggest an increase in the long-term an-nual mean temperature in future years compared to the baseline. The most significant increase in long-term annual mean temperature is anticipated under the RCP 8.5 scenario. The relationships between water quality parameters and climate variables, including temperature and precipitation, were examined during the baseline period. The results revealed an inverse relationship between pre-cipitation and EC, TDS, and SO4. Additionally, the impact of rising temperatures on water quality is negative. Regarding pH, it appears that higher maximum and minimum temperatures, along with increased evaporation, lead to elevated concentrations of dissolved solids in surface waters, thereby negatively affecting this parameter. However, precipitation has a positive relationship, as increased river discharge compensates for the negative impacts of temperature. Subsequently, water quality parameters during the future period were analyzed. The investigations revealed that observed changes are directly influenced by variations in climatic factors, particularly precipitation and, con-sequently, river discharge. Furthermore, the baseline water quality is in good condition, and projec-tions indicate that under all three scenarios, water quality will also remain in good condition. One key reason for this is the anticipated increase in precipitation and the river's self-purification capaci-ty in future years.

Conclusion

Projections under various RCP scenarios indicate that despite a relative decrease in precipita-tion in the future compared to the baseline period, particularly under RCP 8.5, air temperatures are expected to rise significantly. These climatic changes have a direct impact on river systems, as ob-served in the Darband River basin, where variations in precipitation and temperature influence hy-drological dynamics and water quality parameters.

Analyses also point to critical links between climatic variables and water quality. Increased precipitation leads to reduced concentrations of dissolved solids in surface waters due to enhanced discharge and dilution capacity. On the other hand, rising temperatures, while triggering snowmelt and increasing discharge, can degrade water quality through evaporation and increased concentra-tions of dissolved solids, as observed in parameters such as EC, TDS, and pH.

Nevertheless, WQI assessments reveal that the water quality of the Darband River remains cat-egorized as "good" both under baseline conditions and future scenarios. This condition is largely attributed to the river's natural self-purification capacity and relative increases in precipitation dur-ing certain future periods.