Ecohydrologic Modeling for Investigating the Effects of Human-Induced Environmental Stressors on Freshwater Resources

Water quality degradation caused by anthropogenic activities is a crucial global issue, that results in biodiversity loss in freshwater ecosystems. The study of the potential effects of human-induced environmental stressors on water quality is critical for the maintenance of freshwater communities. Nutrients and global warming are two important water quality stressors that contribute to river ecosystem degradation. Thus, the objective of the present work is to develop an ecohydrological modeling approach to investigate the ecological responses of stream networks to water quality deterioration under current water management and future climate conditions using a case study of a Mediterranean region, the Albaida Valley in Spain. The valley consists of the Clariano and Albaida Rivers Watersheds that are severely impacted by human activities. High values of nutrient compounds, primarily from effluents of wastewater treatment plants, have led to water quality degradation and biodiversity loss in these rivers. The Soil and Water Assessment Tool (SWAT) is employed in this work for discharge and nutrient modeling. The SWAT model is calibrated by using the Sequential Uncertainty FItting (SUFI-2) algorithm in the SWAT Calibration and Uncertainty Program (SWAT-CUP) software. Nitrate, ammonium, phosphorus, and macroinvertebrates are used as chemical and biological indicators of stream health in this study. The concentrations of nutrients simulated with SWAT model are used to evaluate chemical water quality. Biological water quality is assessed by coupling SWAT generated concentrations with the results of correlations between measured nutrient concentrations and sampled macroinvertebrates at different sites within the study area. The spatio-temporal assessment of the ecological conditions of streams is then carried out using simulated chemical and biological quality indicators. To study climate change impact on the valley, outputs of five Global Climate Models (GCMs) under four carbon emission scenarios in three future periods (Near Future: 2025–2049, Mid Future: 2050–2074, and Far Future: 2075–2099) are used. The model successfully simulates water quantity and quality variables, indicating that it has the potential to be used to achieve the objectives of this research, i.e., for investigating possible responses of the Albaida Valley ecosystem to current water management and expected changes in climate. The model classifies the ecological status of the Clariano and Albaida Rivers as poor at nearly all representative sites in baseline period (2005–2017) and projects that ecological status in the valley may worsen in the future (2025–2099). These results underscore the apparent necessity for local strategies to manage and improve rivers environmental conditions in the Albaida Valley. This research demonstrates the ability of computer models to inform water management at watershed scales and provides an integrated modeling approach that could be used as supplement to field monitoring to gain a better understanding of possible relationships between river streamflow, nutrient, and biodiversity.