TY - JOUR A1 - Kong, Xiangzhen A1 - Ghaffar, Salman A1 - Determann, Maria A1 - Friese, Kurt A1 - Jomaa, Seifeddine A1 - Mi, Chenxi A1 - Shatwell, Tom A1 - Rinke, Karsten A1 - Rode, Michael T1 - Reservoir water quality deterioration due to deforestation emphasizes the indirect effects of global change JF - Water research : a journal of the International Association on Water Quality (IAWQ) N2 - Deforestation is currently a widespread phenomenon and a growing environmental concern in the era of rapid climate change. In temperate regions, it is challenging to quantify the impacts of deforestation on the catchment dynamics and downstream aquatic ecosystems such as reservoirs and disentangle these from direct climate change impacts, let alone project future changes to inform management. Here, we tackled this issue by investigating a unique catchment-reservoir system with two reservoirs in distinct trophic states (meso- and eutrophic), both of which drain into the largest drinking water reservoir in Germany. Due to the prolonged droughts in 2015-2018, the catchment of the mesotrophic reservoir lost an unprecedented area of forest (exponential increase since 2015 and ca. 17.1% loss in 2020 alone). We coupled catchment nutrient exports (HYPE) and reservoir ecosystem dynamics (GOTM-WET) models using a process-based modeling approach. The coupled model was validated with datasets spanning periods of rapid deforestation, which makes our future projections highly robust. Results show that in a short-term time scale (by 2035), increasing nutrient flux from the catchment due to vast deforestation (80% loss) can turn the mesotrophic reservoir into a eutrophic state as its counterpart. Our results emphasize the more prominent impacts of deforestation than the direct impact of climate warming in impairment of water quality and ecological services to downstream aquatic ecosystems. Therefore, we propose to evaluate the impact of climate change on temperate reservoirs by incorporating a time scale-dependent context, highlighting the indirect impact of deforestation in the short-term scale. In the long-term scale (e.g. to 2100), a guiding hypothesis for future research may be that indirect effects (e.g., as mediated by catchment dynamics) are as important as the direct effects of climate warming on aquatic ecosystems. KW - deforestation KW - climate change KW - temperate regions KW - reservoir KW - eutrophication KW - process-based modeling Y1 - 2022 U6 - https://doi.org/10.1016/j.watres.2022.118721 SN - 0043-1354 SN - 1879-2448 VL - 221 PB - Elsevier Science CY - Amsterdam [u.a.] ER - TY - JOUR A1 - Ghaffar, Salman A1 - Jomaa, Seifeddine A1 - Meon, Günter A1 - Rode, Michael T1 - Spatial validation of a semi-distributed hydrological nutrient transport model JF - Journal of hydrology N2 - Semi-distributed hydrological and water quality models are increasingly used as innovative and scientific-based management tools. However, their application is usually restricted to the gauging stations where they are originally calibrated, limiting their spatial capability. In this study, the semi-distributed hydrological water quality model HYPE (HYdrological Predictions for the Environment) was tested spatially to represent nitrate-N (NO3- N) and total phosphorus (TP) concentrations and loads of the nested and heterogeneous Selke catchment (463 km(2)) in central Germany. First, an automatic calibration procedure and uncertainty analysis were conducted using the DiffeRential Evolution Adaptive Metropolis (DREAM) tool to simulate discharge, NO3--N and TP concentrations. A multi-site and multi-objective calibration approach was applied using three main gauging stations, covering the most important hydro-meteorological and physiographical characteristics of the whole catchment. Second, the model's capability was tested to represent further internal stations, which were not initially considered for calibration. Results showed that discharge was well represented by the model at all three main stations during both calibration (1994-1998) and validation (1999-2014) periods with lowest Nash-Sutcliffe Efficiency (NSE) of 0.71 and maximum Percentage BIAS (PBIAS) of 18.0%. The model was able to reproduce the seasonal dynamics of NO3--N and TP concentrations with low predictive uncertainty at the three main stations, reflected by PBIAS values in the ranges from 16.1% to 6.4% and from 20.0% to 11.5% for NO3--N and TP load simulations, respectively. At internal stations, the model could represent reasonably well the seasonal variation of nutrient concentrations with PBIAS values in the ranges from 9.0% to 14.2% for NO3--N and from 25.3% to 34.3% for TP concentration simulations. Overall, results suggested that the spatial validation of a nutrient transport model can be better ensured when a multi-site and multi-objective calibration approach using archetypical gauging stations is implemented. Further, results revealed that the delineation of sub-catchments should put more focus on hydro-meteorological conditions than on land-use features. KW - HYPE model KW - Nitrate-N KW - Phosphorus KW - internal validation KW - uncertainty KW - analysis KW - archetypical gauging station Y1 - 2021 U6 - https://doi.org/10.1016/j.jhydrol.2020.125818 SN - 0022-1694 SN - 1879-2707 VL - 593 PB - Elsevier CY - Amsterdam ER -