Human pressures intensify stochiometric nitrogen excess in flowing waters (water quality variables and catchment attributes)
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Human pressures intensify stochiometric nitrogen excess in flowing waters (water quality variables and catchment attributes) Alexander Bartusch1, Felipe Saavedra2, Anika Große1,3, Carolin Winter4, Pia Ebeling5, Julia Pasqualini6, Michele Meyer6, Lindsey N. Aman Cromwell8, Linus Silvester Schauer5, Alexander Hubig5, Yao Li1, Andreas Musolff5, Rohini Kumar7, and Daniel Graeber1,✉ 1 Dep. Aquatic Ecosystem Analysis, Helmholtz-Centre for Environmental Research – UFZ2 Dep. Catchment Hydrology, Helmholtz-Centre for Environmental Research – UFZ3 Department of Ecoscience, Aarhus University4 Chair of Environmental Hydrological Systems, University Freiburg5 Dep. Hydrogeology, Helmholtz-Centre for Environmental Research – UFZ6 Dep. River Ecology, Helmholtz-Centre for Environmental Research – UFZ7 Dep. Computational Hydrosystems, Helmholtz-Centre for Environmental Research – UFZ8 School of Forest, Fisheries, and Geomatics Sciences, University of Florida ✉ Correspondence: Daniel Graeber <daniel.graeber@ufz.de> Description This repository includes the following datasets: Seven water quality datasets with observational data of C, N and P concentrations in streams were collected and downloaded from the original databases. Details regarding the corresponding dataset and original data source can be found below. Additionally, the repository contains the HydroATLAS and the HydroRIVERS databases, both of which were downloaded from the HYDROSHEDS project website (www.hydrosheds.org) in May 2024. The global map of the topographic wetness index, was caclulated using a void-filled digital elevation model DEM (resolution 15 arc-seconds) and a flow accumulation map (ACA upstream area in hectares; 15 arc-seconds). Both, on a global scale, were obtained from the core data products of the HydroSHEDS project1. Finally, the repository provides the processed dataset of exported rC:rN:rP ratios from 3,496 hydrological catchments and their corresponding hydro-environmental attributes. Overview Raw data: 1. 7 water quality datasets 2. 7 files containing the corresponding station IDs with coordinates 3. HYDROATLAS: BasinATLAS_v10_lev12 4. HYDRORIVERS: HydroRIVERS_v10 5. Topographic wetness index (TWI): TWI_global.tif (calculated using QGIS) Processed datasets and model parameters 1. Stoichiometric rOC:rN:rP export from the hydrological catchments with the corresponding catchment attributes: – median_cnp_export_abs_conc_and_rfr_and_basin_feat.csv – A table with full variable names and units of the processed data is contained within Bartusch_etal_Zenodo.pdf. 2. The optimized model parameter set for the Gradient Boosting Regression Tree (GBRT) model: – optimized_model_parms_GBRT_models.csv Detailed description of the 7 water quality datasets Denmark The dataset of Danish river water quality data was downloaded from the Overfladevandsdatabasen webpage (“Overfladevandsdatabasen”), and includes dissolved inorganic nitrogen (nitrate, nitrite and ammonium), organic carbon (total organic carbon TOC, dissolved organic carbon DOC) and phosphorus (total phosphorus TP, dissolved inorganic phosphorus DIP). Observations cover the period from 1970 until 2022 with different timespans and temporal resolution, depending on the parameter. The data contains NO3–N and NO2--N (combined). Germany The water quality database Germany 2.0 was collected and put together at the UFZ and constitutes an update of the QUADICA data set version 12. The dataset is compiled from water quality data provided by the German federal state authorities. The dataset provides DOC, NO3--N, and TP concentrations at 3,965 sites across Germany. All stations have at least these three fractions, but if available, NO2--N, NH4+-N, dissolved inorganic P (DIP) and TOC are additionally included. Samples cover the period from 1982 to 2020, but with varying temporal coverage between sites, ranging from 1 to 37 years. Arctic deltas The ArcticGRO Water Quality Dataset3 (version 2024) is a subset of the Arctic Great Rivers Observatory database and consists of water quality measurements from six Arctic river deltas. The data are freely available at the ArcticGRO webpage (ArcticGRO Water Quality Dataset, 2024) and frequently updated. The dataset provides NO3--N, NH4+-N, DOC, and PO43–-P concentrations for 6 stations along each of the Arctic great rivers from 2003-2021. The temporal resolution is 5–7 observations per year. The average time series length per site is 17 years. France The French dataset provides NO3--N, DOC and PO43--P observations for 486 French stations of the French water quality database. The stations were preselected for long-term water quality analysis, as for the work published in4 and5. Therefore, only stations with available long-term water quality data are included here. Samples cover the period from 1969 to 2016, but temporal coverage ranges between stations from at least 17 years up to maximum 46 years. The mean time series length per site is 31 years. GRQA The Global River Water Quality Archive (GRQA)6 (downloaded version: GRQA v1.2, March 11, 2022) is a harmonized and aggregated water quality dataset, based on five national, continental and global datasets: CESI (Canadian Environmental Sustainability Indicators program), GEMStat (Global Freshwater Quality Database), GLORICH(GLObal RIver CHemistry), Waterbase and WQP (Water Quality Portal). The dataset contains 42 water quality parameters from which a subset of NO2--N, NO3--N, NH4--N, DOC, DIP, TOC and TP was selected. The samples of this subset were observed between 1900 and 2020. Sweden The dataset comprises data from the Swedish CLEO database (Temnerud et al. 2014)(https://www.slu.se/cleo/data, original link not active anymore). The observed water quality data originate from forested headwater streams within the boreal Krycklan catchment in Sweden. The dataset contains data on NO2--N and NO3-–N (combined), NH4+-N, DIN, TOC, DOC, TP and DIP for 27 sites. Observations cover the period from 1985 to 2022 with varying temporal coverage between four and 35 years per site. The average time series length is 14 years. USGS The United States Geological Survey (USGS) dataset was published in 2017 along with scientific investigations report ”Water-Quality Trends in the Nation’s Rivers and Streams, 1972-2012”7. From the provided parameters NH4+-N, NO3-–N, PO43–-P and TOC were extracted. Observed concentrations were available for 764 sites across the United States. Samples cover the period from 1965 to 2013, but temporal coverage ranges between stations from at least nine years up to maximum 49 years. The average time series length per site is 25 years. References 1. Lehner, B., Verdin, K. & Jarvis, A. New Global Hydrography Derived From Spaceborne Elevation Data. Eos, Transactions American Geophysical Union 89, 93–94 (2008). 2. Ebeling, P. et al. QUADICA: Water QUAlity, DIscharge and Catchment Attributes for large-sample studies in Germany. Earth System Science Data 14, 3715–3741 (2022). 3. Holmes, R. M. et al. Climate Change Impacts on the Hydrology and Biogeochemistry of Arctic Rivers. in Climatic Change and Global Warming of Inland Waters 1–26 (John Wiley & Sons, Ltd, 2012). doi:10.1002/9781118470596.ch1. 4. Ebeling, P. et al. Long-Term Nitrate Trajectories Vary by Season in Western European Catchments. Global Biogeochemical Cycles 35, e2021GB007050 (2021). 5. Ehrhardt, S. et al. Nitrate Transport and Retention in Western European Catchments Are Shaped by Hydroclimate and Subsurface Properties. Water Resources Research 57, e2020WR029469 (2021). 6. Virro, H., Amatulli, G., Kmoch, A., Shen, L. & Uuemaa, E. GRQA: Global River Water Quality Archive. Earth System Science Data 13, 5483–5507 (2021). 7. Oelsner, G. P. et al. Water-quality trends in the nation’s rivers and streams, 1972–2012—Data preparation, statistical methods, and trend results. Scientific Investigations Report (2017) doi:10.3133/sir20175006.
人类活动压力加剧流动水体的化学计量氮盈余（含水质变量与集水区属性） ## 作者与单位 Alexander Bartusch¹, Felipe Saavedra², Anika Große¹,³, Carolin Winter⁴, Pia Ebeling⁵, Julia Pasqualini⁶, Michele Meyer⁶, Lindsey N. Aman Cromwell⁸, Linus Silvester Schauer⁵, Alexander Hubig⁵, Yao Li¹, Andreas Musolff⁵, Rohini Kumar⁷, and Daniel Graeber¹,✉ ¹ 水生生态系统分析部，亥姆霍兹环境研究中心（UFZ） ² 集水区水文学部，亥姆霍兹环境研究中心（UFZ） ³ 生态科学系，奥胡斯大学 ⁴ 环境水文系统讲席，弗莱堡大学 ⁵ 水文地质学部，亥姆霍兹环境研究中心（UFZ） ⁶ 河流生态学部，亥姆霍兹环境研究中心（UFZ） ⁷ 计算水系统学部，亥姆霍兹环境研究中心（UFZ） ⁸ 森林、渔业与地理空间科学学院，佛罗里达大学 ✉ 通讯作者：Daniel Graeber <daniel.graeber@ufz.de> ## 数据集说明 本数据集仓库包含如下内容： 研究团队从原始数据库中搜集并下载了7套包含溪流碳（C）、氮（N）、磷（P）浓度观测数据的水质数据集，各数据集及原始数据来源的详细信息见下文。 此外，本仓库还包含2024年5月从HYDROSHEDS项目官网（www.hydrosheds.org）下载的HydroATLAS与HydroRIVERS数据库。 研究团队采用经空隙填充的数字高程模型（Digital Elevation Model, DEM）（分辨率15弧秒）与汇流累积量图（上游集水区面积，单位：公顷；分辨率15弧秒），在全球尺度上计算得到地形湿度指数（Topographic Wetness Index, TWI）；上述两类基础数据均来源于HydroSHEDS项目的核心数据产品¹。 最后，本仓库提供了来自3496个水文集水区的输出比有机碳/比氮/比磷（rOC:rN:rP）比值的处理后数据集，以及对应的水文环境属性。 ## 数据集概览 ### 原始数据 1. 7套水质数据集 2. 7份包含对应监测站ID与坐标的文件 3. HYDROATLAS：BasinATLAS_v10_lev12 4. HYDRORIVERS：HydroRIVERS_v10 5. 地形湿度指数（TWI）：TWI_global.tif（使用QGIS计算得到） ### 处理后数据集与模型参数 1. 水文集水区输出的化学计量比rOC:rN:rP数据集及对应集水区属性： – median_cnp_export_abs_conc_and_rfr_and_basin_feat.csv 处理后数据的完整变量名与单位说明详见"Bartusch_etal_Zenodo.pdf"文件。 2. 梯度提升回归树（Gradient Boosting Regression Tree, GBRT）模型的优化参数集： – optimized_model_parms_GBRT_models.csv ## 7套水质数据集详细说明 ### 丹麦数据集 丹麦河流水质数据集下载自Overfladevandsdatabasen网页，包含溶解性无机氮（硝酸盐、亚硝酸盐与铵态氮）、有机碳（总有机碳Total Organic Carbon, TOC、溶解性有机碳Dissolved Organic Carbon, DOC）与磷（总磷Total Phosphorus, TP、溶解性无机磷Dissolved Inorganic Phosphorus, DIP）的观测数据。观测时段为1970年至2022年，不同参数的时间跨度与时间分辨率存在差异。数据中包含合并后的NO₃–N与NO₂--N数据。 ### 德国数据集 德国水质数据库2.0由亥姆霍兹环境研究中心（UFZ）搜集整理，是QUADICA数据集第12版的更新版本。该数据集整合了德国联邦各州管理机构提供的水质数据，覆盖德国境内3965个监测点的DOC、NO₃--N与TP浓度数据；所有监测点均至少包含上述三类参数，若有额外数据则一并包含NO₂--N、NH₄+-N、溶解性无机磷（DIP）与总有机碳（TOC）。样本采集时段为1982年至2020年，各监测点的时间覆盖范围为1年至37年不等。 ### 北极三角洲数据集 北极大型河流观测站（ArcticGRO）水质数据集³（2024版）是北极大型河流观测站数据库的子集，包含6个北极河流三角洲的水质监测数据。该数据集可在ArcticGRO官网（ArcticGRO Water Quality Dataset, 2024）免费获取并定期更新，包含2003年至2021年间北极各大型河流沿线6个监测点的NO₃--N、NH₄+-N、DOC与PO₄³–-P浓度数据。年观测频次为5~7次，单个监测点的平均时间序列长度为17年。 ### 法国数据集 法国数据集包含法国水质数据库中486个监测点的NO₃--N、DOC与PO₄³--P观测数据；这些监测点均为前期筛选出的适合长期水质分析的站点，与文献⁴、⁵中的研究一致，因此本数据集仅包含具备长期水质数据的监测点。样本采集时段为1969年至2016年，各监测点的时间覆盖范围为17年至46年不等，单个监测点的平均时间序列长度为31年。 ### GRQA数据集 全球河流水质档案库（Global River Water Quality Archive, GRQA）⁶（下载版本：GRQA v1.2，2022年3月11日）是一套经过标准化整合的水质数据集，基于5套国家级、大陆级与全球级数据集构建：CESI（加拿大环境可持续性指标计划）、GEMStat（全球淡水水质数据库）、GLORICH（全球河流化学数据库）、Waterbase与水质门户（Water Quality Portal, WQP）。该数据集包含42项水质参数，本次研究选取其中的NO₂--N、NO₃--N、NH₄--N、DOC、DIP、TOC与TP作为分析子集，样本观测时段为1900年至2020年。 ### 瑞典数据集 瑞典数据集来源于瑞典CLEO数据库（Temnerud等，2014）（https://www.slu.se/cleo/data，原链接现已失效），观测水质数据采自瑞典北方针叶林带Krycklan集水区内的森林源头溪流。该数据集包含27个监测点的NO₂--N与NO₃-–N（合并数据）、NH₄+-N、DIN、TOC、DOC、TP与DIP数据。观测时段为1985年至2022年，各监测点的时间覆盖范围为4年至35年不等，单个监测点的平均时间序列长度为14年。 ### USGS数据集 美国地质调查局（United States Geological Survey, USGS）数据集于2017年随科学调查报告《美国河流与溪流的水质变化趋势，1972-2012》⁷一同发布。本次研究从其提供的参数中选取了NH₄+-N、NO₃-–N、PO₄³–-P与TOC，数据覆盖美国境内764个监测点。样本采集时段为1965年至2013年，各监测点的时间覆盖范围为9年至49年不等，单个监测点的平均时间序列长度为25年。 ## 参考文献 1. Lehner, B., Verdin, K. & Jarvis, A. 基于星载高程数据的新型全球水文制图. 《美国地球物理联合会汇刊》（Eos, Transactions American Geophysical Union）, 89, 93–94 (2008). 2. Ebeling, P. et al. QUADICA：德国大样本研究用水质、径流与集水区属性数据集. 《地球系统科学数据》, 14, 3715–3741 (2022). 3. Holmes, R. M. et al. 气候变化对北极河流水文与生物地球化学的影响. 收录于《内陆水域的气候变化与全球变暖》, 1–26 (John Wiley & Sons, Ltd, 2012). doi:10.1002/9781118470596.ch1. 4. Ebeling, P. et al. 西欧集水区的硝酸盐长期轨迹存在季节差异. 《全球生物地球化学循环》, 35, e2021GB007050 (2021). 5. Ehrhardt, S. et al. 西欧集水区的硝酸盐输运与滞留受水文气候与地下属性调控. 《水资源研究》, 57, e2020WR029469 (2021). 6. Virro, H., Amatulli, G., Kmoch, A., Shen, L. & Uuemaa, E. GRQA：全球河流水质档案库. 《地球系统科学数据》, 13, 5483–5507 (2021). 7. Oelsner, G. P. et al. 美国河流与溪流的水质变化趋势，1972–2012：数据准备、统计方法与趋势结果. 科学调查报告 (2017) doi:10.3133/sir20175006.
