NAPSEA Transfer of model results

DELIVERABLE 3.6 TRANSFER OF MODEL RESULTS DELIVERABLE 3.6 TRANSFER OF MODEL RESULTS Work Package 3 Measures & Pathways 30-04-2025 Work Package 3 Measures & Pathways 30-04-2025 www.napsea.eu Page 2 of 16 Deliverable D3.6 Grant Agreement number 101060418 Project title NAPSEA: the effectiveness of Nitrogen And Phosphorus load reduction measures from Source to Sea, considering the effects of climate change Project DOI 10.3030/101060418 Deliverable title Transfer of model results Deliverable number 3.6. Deliverable version 1 Contractual date of delivery 31.03.2025 Actual date of delivery 30.04.2025 Document status Prepared Document version 1 Online access Yes Diffusion Public (PU) Nature of deliverable Report Work Package WP3: Measures and Pathways Partner responsible Helmholtz Centre for Environmental Research Contributing Partners Umweltbundesamt (UBA) Author(s) Musolff, Andreas Editor Joachim Rozemeijer Approved by Luuk H. van der Heijden Project Officer Blanca Saez Lacave Abstract Modelled results of scenarios of nutrient reduction measures in demonstrator basins Rhine and Elbe and selected subcatchments within the basins are transferred to other basins contributing to riverine nutrient inputs into the Wadden Sea. Keywords Climate change, nitrogen, nutrient reduction, phosphorus Page 3 of 16 Deliverable D3.6 Contents Deliverable 3.6 .........................................................................................................................................................1 Transfer of model results .........................................................................................................................................1 LIST OF ABBREVIATIONS .....................................................................................................................................4 1. EXECUTIVE SUMMARY ................................................................................................................................5 2. INTRODUCTION ............................................................................................................................................6 3. METHODS ......................................................................................................................................................7 3.1. Data sources to characterize reference nutrient conditions in additional basins ....................................7 3.2. Similarity analysis of new basins and modelled basins and subcatchments ..........................................7 3.3. Transfer of modelling results ..................................................................................................................8 4. RESULTS .......................................................................................................................................................9 4.1. Results of the catchment similarity analysis ...........................................................................................9 4.2. Transferred results for nitrate-N exports to the Wadden Sea ............................................................... 10 4.3. Transferred results for TP .................................................................................................................... 10 4.4. All results for Nitrate-N ......................................................................................................................... 11 4.5. All results for TP ................................................................................................................................... 13 5. CONCLUSIONS............................................................................................................................................ 15 6. REFERENCES ............................................................................................................................................. 16 Page 4 of 16 Deliverable D3.6 LIST OF ABBREVIATIONS CnANDY ................................................................................................. Coupled Complex Algal-Nutrient Dynamics mHM ............................................................................................................................ Mesoscale Hydrologic Model mQM ......................................................................................................................... Multiscale water Quality Model N ................................................................................................................................................................ Nitrogen NECD .................................................................................. National Emissions Reduction Commitments Directive P .......................................................................................................................................................... Phosphorus SRP .......................................................................................................................... Soluble Reactive Phosphorus TP ................................................................................................................................................Total Phosphorus UWWTD ...................................................................................................... Urban Wastewater Treatment Directive WWTP ........................................................................................................................... wastewater treatment plant Page 5 of 16 Deliverable D3.6 1. EXECUTIVE SUMMARY D3.6 reports on the projected nitrogen (N) and phosphorus (P) exports for all major rivers draining into the Wadden Sea to allow a complete picture of nutrient exports to this valuable coastal ecosystem. These results are based on the mQM model for N and the CnANDY model for P applied to the Elbe, Rhine and Hunze demonstrator basins, evaluated under different scenarios of measures and under the influence of future climate change (reported in D3.5). The model results for the demonstrator basins are transferred to the basin of the Ems, Weser and Eider by a similarity analysis by the modelled basins and subcatchments. More specifically, percentages of nutrient reductions from Elbe and Rhine compared to the reference conditions (2010-2020) are transferred to report exports and concentrations for the years 2030 and 2050 in all major rivers that are contributing to Wadden Sea eutrophication. We found that Elbe and Rhine basins exports around 70% of the Nitrate-N loads and 90% of the TP loads exported by rivers to the Wadden Sea while the Weser basin is ranked third. The fraction delivered by the Rhine basin will increase under the future climate and nutrient reduction scenarios while the fraction delivered by the Elbe will decrease. Page 6 of 16 Deliverable D3.6 2. INTRODUCTION To provide a comprehensive understanding of nutrient input into the Wadden Sea, deliverable 3.6 outlines anticipated nitrogen and phosphorus contributions from its major inflowing rivers. These projections utilize the mQM model for nitrogen and the CnANDY model for phosphorus, applied to the Elbe, Rhine, and Hunze demonstrator basins as detailed in deliverable 3.5. By transferring the nutrient reduction scenarios under future climate change conditions, this deliverable allows to rank the different river basin by their exported N and P loads and therefore support water management in their decision processes. Page 7 of 16 Deliverable D3.6 3. METHODS 3.1. Data sources to characterize reference nutrient conditions in additional basins In this deliverable three basins are considered that have been not explicitly modelled using mQM and CnANDY (see deliverables D3.2 and D3.5). Table 1 gives an overview of catchment sizes for all basins and data sources for the newly added ones. Figure 1 shows all considered basins and subregions in relation to the Wadden Sea. In total we consider more than 38,000 km2 of catchment area draining and delivering nutrients into the Wadden Sea. The newly added area of Ems, Weser and Eider represent 13% of this total considered area. Table 1. Basins and data sources for nutrient concentrations and discharge. Newly added basins are printed in bold. For other basin data sources refer to D3.1. Name Area [km2] Data source nutrients Data source discharge Dutch Maas 7222 See D3.1 See D3.1 Rhine 163141 See D3.1 See D3.1 Dutch Rhine 23526 See D3.1 See D3.1 Ems 9207 UBA, https://gis.uba.de/maps/resources/apps/acp GR See D3.1DC, https://grdc.bafg.de/ Weser 38455 UBA, https://gis.uba.de/maps/resources/apps/acp GRDC, https://grdc.bafg.de/ Elbe 138383 See D3.1 See D3.1 Eider 2044 UBA, https://gis.uba.de/maps/resources/apps/acp Landesamt für Umwelt SchleswigHolstein, Hochwasser-SturmflutInformation Figure 1. Considered basins contributing to the Wadden Sea eutrophication. Light grey lines are modelled subcatchments in Elbe and Rhine basin and modelled subregions of Rhine and Maas in The Netherlands. The additional nutrient data were provided by the UBA at an annual averaged basis for Nitrate-N and total phosphorous (TP). Similar to the data handling described in D3.2 and modelling results in D3.5, we refer to a reference period averaged for the years 2010 to 2020. Discharge data from the global runoff data center and Hochwasser-Sturmflut-Information was aggregated from daily to annual values and used to derive annual exported fluxes of Nitrate-N and TP. 3.2. Similarity analysis of new basins and modelled basins and subcatchments To transfer results for the export of N from the modelled basins to the new basin we performed a similarity analysis based on catchment attributes that are provided in the QUADICA database (Ebeling et al. 2022). More Page 8 of 16 Deliverable D3.6 specifically, we used attributes that characterize the nutrient inputs into the catchment (fraction of agricultural land, average nitrogen surplus in the years 2000-2015 representing diffuse nutrient inputs and population density representing wastewater nutrient inputs) on the one hand. On the other hand, we used the fraction of unconsolidated aquifers in the catchment representing nutrient retention. This fraction is the form of the dominant aquifer – being unconsolidated sediments with porous materials or hard-rock aquifers with fissured material. More specifically, this fraction proved to be the best predictor for the subsurface denitrification potential of central European landscapes due to its higher likelihood to contain organic matter and pyrite enabling the denitrification reaction (Ebeling et al 2021). To transfer the modelling results for P to the new basin, we relied on a different approach than for N. For the reduction of P, the main factor is the fraction of wastewater P inputs into the network as largest part of the reduction is realized by the implementation of the new urban wastewater directive (see deliverable D3.5). As a second factor the size of the catchment is relevant – we prefer transferring from large basins, where pelagic algal developments dominate over benthic processes which is true for stream orders larger than 2 (Yang et al. 2021). We therefore selected the results from the Rhine at Lobith as a blueprint for the P reduction in the Ems (high population density) and the Elbe outlet as a blueprint for the Weser (similar to N) and the Eider. 3.3. Transfer of modelling results The transfer of modelling results from mQM for Nitrate-N and from CnANDY for total P has a focus on the exports into the Wadden Sea and the reductions of these exports achieved in the scenarios. We therefore used the percentage reduction of nutrient fluxes relative to the reference years 2010-2020 modelled in different scenarios and applied the average across the similar catchments (section 3.2) to the observed nutrient fluxes 2010-2020 in Ems, Weser and Eider for N and additionally for the Dutch parts of Maas (NLMS) and Rhine (sum of NLRNNO, NLRNOO, NLRNWE) for P. We account for an uncertainty of this transfer for N by using the range of reductions across the selected similar subcatchments. In the case of the Weser catchment, where modelled results of the Elbe outlet are taken as a reference, we used the 5th -95th percentiles among the best 100 modelled solutions for mQM for Nitrate-N but lack a comparable value for CnANDY and TP. As scenarios the combined effects of measures in scenario 5 (combined planned measures), 7A (strengthening policies), 7B (exploring synergies) and 7C (drastic societal changes) for the time frames 2030 (averaging 2028-2032) and 2050 (averaging 2046-2050) were considered. This selection was made to transfer the combined effect of climate change and combined measures for all relevant nutrient input pathways while not given the details of climate change (scenario 6) and each pathway separately (scenarios 1, 2, 3 and 4). Page 9 of 16 Deliverable D3.6 4. RESULTS 4.1. Results of the catchment similarity analysis Table 2 gives an overview of the catchment properties of the three new basins and the properties of the choice of similar basins. For the Ems we found four subcatchments of the Rhine with similar catchment properties. For the basin of the Weser, the Elbe basin (outlet) itself has a large similarity while no other comparable catchment was found. Especially catchments with a similar share of unconsolidated aquifers could not be found among the modelled subcatchments. For the basin of the Eider, four subcatchments of the Elbe were found with similar properties. Table 2. Results of the similarity analysis of new basins with modelled catchments from D3.5. Data are derived from Ebeling et al. (2022). Station – name of the station in Ebeling et al. (2022), f_agric – fraction of agricultural land use, Pdens – population density, N input – nitrogen surplus average 2000-2015, f_unconsol – fraction of unconsolidated aquifers. Note that the Elbe station name refers to the number used by the global runoff data center. Properties of the target basins are printed bold. River Station f_agric [%] Pdens [inh/km2] N input [kg/ha yr] f_unconsol [%] Ems NW_803182 72 368 74 83 BW_CSN014 62 136 80 100 BW_CSN021 65 235 78 100 BW_CAR028 68 136 78 76 BW_CAS014 66 152 55 86 Weser NI_49112010 55 189 47 34 6340110 39.7 180 40 32 Eider SH_120215 83 128 69 100 SN_OBF54610 76 132 45 46 BB_STEP_0040 83 34 48 100 BB_STEP_0020 84 36 49 100 ST_2170040 87 126 43 63 The tables 3 and 4 report the percentage of load reduction in 2030 and 2050 under the considered scenarios as reported in deliverable 3.5. Table 3. Percentage of modelled Nitrate-N load reduction from the catchments of the similarity analysis taken from deliverable 3.5. Mean, minimum and maximum values are given. Note that for the Weser catchment values from the Elbe model are taken where uncertainty refers to 5th and 95th percentiles of 100 best modelled solutions. Numbers in headers refer to scenario number and year. All percentage are relative to the reference year 20102020. Name 5 5 7A 7A 7B 7B 7C 7C Year 2030 2050 2030 2050 2030 2050 2030 2050 Ems Best 17.1 16.9 21.4 25.3 21.4 25.3 23.8 35.6 Min 11.9 1.4 14.2 7.7 14.2 7.7 18.9 5.4 Max 20.9 26.2 28.3 32.7 28.3 32.7 29.3 42.4 Weser Best 33.4 20.6 40.8 30.7 57.1 46.9 59.8 61.6 5th 25.5 16.1 33.3 28.5 49.6 44.8 54.0 61.6 95th 47.2 25.0 55.1 50.4 71.3 66.7 76.8 84.7 Eider Best 60.9 48.0 62.1 52.0 62.1 52.0 69.7 73.8 Min 52.5 44.2 53.2 48.3 53.2 48.3 56.8 70.9 Max 69.5 53.7 70.7 57.2 70.7 57.2 77.6 75.6 Page 16 of 16 Deliverable D3.6 6. REFERENCES Ebeling, P., Kumar, R., Lutz, S. R., Nguyen, T., Sarrazin, F., Weber, M., Buttner, O., Attinger, S., & Musolff, A. (2022). QUADICA: water QUAlity, Discharge and Catchment Attributes for large-sample studies in Germany. Earth System Science Data, 14(8), 3715-3741. https://doi.org/10.5194/essd-14-3715-2022 Ebeling, P., Kumar, R., Weber, M., Knoll, L., Fleckenstein, J. H., & Musolff, A. (2021). Archetypes and controls of riverine nutrient export across german catchments. Water Resources Research, 57(4). https://doi.org/10.1029/2020WR028134 Gericke, A. & Leujak, W. (2024). Model input of selected scenarios. EC report of grant 101060418 Deliverable 3.4. https://napsea.eu/wp-content/uploads/2024/10/D3.4_Model-input-of-selected-scenarios.pdf Gericke, A., Leujak, W., Musolff, A. & Geidel, T. (2024). Set of Scenarios. EC report of grant 101060418 Deliverable 3.3. https://napsea.eu/wp-content/uploads/2024/04/D3.3-Set-of-Scenarios_NAPSEA.pdf Jomaa, S. & Musolff, A. (2023). Data collection. EC report of grant 101060418 Deliverable 3.1. https://napsea.eu/wp-content/uploads/2024/02/D3.1_Data_overview_NAPSEA_final.pdf Musolff, A. & Ledesma, J. (2024). Calibrated models. EC report of grant 101060418 Deliverable 3.2. https://napsea.eu/wp-content/uploads/2024/04/D3.2.-DEM_Calibrated_models_NAPSEA.pdf Musolff, A. & Ledesma, J. (2024). Effectiveness of scenarios. EC report of grant 101060418 Deliverable 3.5. https://napsea.eu/wp-content/uploads/2025/02/D3.5_Effectiveness-of-scenarios_incl_appendix.pdf Yang, S., Bertuzzo, E., Büttner, O., Borchardt, D., & Rao, P. S. C. (2021). Emergent spatial patterns of competing benthic and pelagic algae in a river network: A parsimonious basin-scale modeling analysis. Water Research, 193. https://doi.org/10.1016/j.watres.2021.116887