An ensemble modeling framework to study the effects of climate change on the trophic state of shallow reservoirs

Our understanding of the potential impact of climatic change on catchment hydrology and aquatic system dynamics has been advanced over the past decade, but there are still considerable knowledge gaps with respect to its effects on water quality vis-à-vis the increasing demands for drinking water. In this study, we developed an integrated hydrological-water quality (SWAT-YRWQM) model to elucidate the effects of a changing climate on the trophic state of the shallow Yuqiao Reservoir. Using a two-step downscaling process, we reproduced the prevailing meteorological conditions, as well as the streamflows in three major tributaries of the study area. A sensitivity analysis exercise showed that the nature of the calibration dataset used, namely the range of flows (i.e., dry versus wet years) included, can profoundly influence the predictive power of our modeling framework. Our climatic scenarios projected a minor change of the streamflow rates, but a variant degree of increase of the riverine total phosphorus (TP) concentrations and associated loading rates into the reservoir. Consequently, a significant rise of in-lake TP concentrations is projected for the near (2016-2030) and distant (2031-2050) future compared to the reference (2006-2015) conditions. Interestingly, the ambient TP levels appear to be lower in the distant relative to the near future, owing to changes in the magnitude and relative contribution of both external and internal nutrient loading sources. Our analysis also highlights the importance of reservoir operation practices to regulate water levels as a means for mitigating the climate change impact on the trophic status of the Yuqiao Reservoir, given that the diversion of low-nutrient water from the upstream basin can significantly reduce (30-40%) the TP concentrations. Our findings are highly relevant to the on-going debate about the potential implications of climate change for water availability, highlighting the importance of adaptation strategies to optimize the water resources management.