TY - JOUR A1 - Steidl, Jörg A1 - Lischeid, Gunnar A1 - Engelke, Clemens A1 - Koch, Franka T1 - The curse of the past BT - What can tile drain effluent tell us about arable field management? JF - Agriculture, Ecosystems & Environment N2 - One challenge for modern agricultural management schemes is the reduction of harmful effects on the envi-ronment, e.g. in terms of the emission of nutrients. Sampling the effluent of tile drains is a very efficient way to sample seepage water from larger areas directly underneath the main rooting zone. Time series of solute con-centration in tile drains can be linked to agricultural management data and thus indicate the efficacy of individual management measures. To that end, the weekly runoff and solute concentration were determined in long-term measurement campaigns at 25 outlets of artificial tile drains at 19 various arable fields in the German federal state of Mecklenburg-Vorpommern. The study sites were distributed within a 23,000 km(2) region and were deemed representative of intense arable land use. In addition, comprehensive meteorological and man-agement data were provided. To disentangle the different effects, monitoring data were subjected to a principal component analysis. Loadings on the prevailing principal components and spatial and temporal patterns of the component scores were considered indicative of different processes. Principal component scores were then related to meteorological and management data via random forest modelling. Hydrological conditions and weather were identified as primary driving forces for the nutrient discharge behaviour of the drain plots, as well as the nitrogen balance. In contrast, direct effects of recent agricultural management could hardly be identified. Instead, we found clear evidence of the long-term and indirect effects of agriculture on nearly all solutes. We conclude that tile drain effluent quality primarily reflected the soil-internal mobilisation or de-mobilisation of nutrients and related solutes rather than allowing inferences to be drawn about recent individual agricultural management measures. On the other hand, principal component analysis revealed a variety of indirect and long-term effects of fertilisation on solutes other than nitrogen or phosphorus that are still widely overlooked in nutrient turnover studies. KW - Agricultural management KW - Tile drains KW - Nitrate KW - Phosphorus KW - Water KW - pollution KW - Multivariate statistics KW - Random forest modelling Y1 - 2021 U6 - https://doi.org/10.1016/j.agee.2021.107787 SN - 0167-8809 SN - 1873-2305 VL - 326 PB - Elsevier CY - Amsterdam 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 -