Intercontinental sampling campaign of river GHG fluxes

This study investigated river GHG fluxes in four rivers: the Cuenca River in Ecuador (South America), the Gilgel Gibe River in Ethiopia (Africa), the Cau River in Vietnam (Asia), and the Zwalm River in Belgium (Europe). These rivers span diverse hydroclimatic zones, geomorphological characteristics, land use and cover (LULC) types, and population densities. The Cuenca and Zwalm Rivers shared similar mean annual precipitations and temperatures (MAP and MAT, respectively), however the Cuenca experiences higher PET and lower minimum temperatures than Zwalm due to its higher altitude. A similar pattern is observed between the Gilgel Gibe and Cau Rivers, with the former’s higher altitude leading to increased PET and a drier ecosystem, while the latter’s lower altitude leads to higher maximum temperatures. Sampling points were classified based on surrounding LULC within a 1 km radius using the European Space Agency (ESA) LULC map (Zanaga et al., 2022). Sampling point distributions by LULC classes are described in the database. Five sampling campaigns were performed between February 2022 and October 2023. An equal number of sampling sites (~39) were investigated for the Gilge Gibe, Cau and Cuenca Rivers, while for the Zwalm River, two seasonal campaigns (winter and summer) were conducted across 20 sites. Gas samples were collected by using the floating chamber (FC) technique for analyzing riverine GHG emissions as described in Ho et al. (2021). At each site, three gas samples were collected from the FC’s headspace at 0, 20, and 40 min after its placement. These samples were extracted through a butyl rubber stopper with a 20 ml syringe and immediately transferred into pre-conditioned 12-ml Exetainer® vials (purged three times with helium and evacuated). Vials were stored in dark containers before being transported and analyzed at the ISOFYS in Ghent University and in ETH Zurich. GHG fluxes were estimated from the slope of the linear regression of measured concentrations versus time, and the properties of the FC, using the following equation (Ho et al., 2021): (1) In addition to GHG fluxes, we also collected biochemical, geomorphic, LULC and meteorological data. In-situ measurements of water temperature, pH, electroconductivity (EC), salinity, and dissolved oxygen (DO) were recorded using a WTW-3430 multiprobe (WTW GmbH, Weilheim, Germany). Turbidity was measured with a YSI 6920V2-2 multiprobe (YSI Xylem Inc., Yellow Springs, Ohio, USA). Both multiprobes were calibrated prior to sampling. Flow velocity was determined using a Handheld flowtherm NT.2 (Höntzsch, Germany). Water samples from all sites were collected, stored in cool, dark containers, and refrigerated until analysis. Ammonium (NH4+), nitrate (NO3-), nitrite (NO2-) and total nitrogen (TN) concentrations were measured using Spectroquant® Kits. Total organic carbon (TOC) and total inorganic carbon (TIC) were analyzed with a Shimadzu TOC V CPN-analyzer and autosampler. Meteorological data was initially gathered from stations near the sampling sites. In case of missing meteorological data, we supplemented with information from the ERA5-Land dataset (Muñoz Sabater, 2019). Basin areas, river slopes, and topography were obtained via Digital Elevation Maps from the Shuttle Radar Topography Mission (SRTM) (USGS, 2020). References: Ho, L., Jerves-Cobo, R., Eurie Forio, M.A., Mouton, A., Nopens, I., Goethals, P., 2021. Integrated mechanistic and data-driven modeling for risk assessment of greenhouse gas production in an urbanized river system. J. Environ. Manage. 294. https://doi.org/10.1016/j.jenvman.2021.112999 Muñoz Sabater, 2019. ERA5-Land hourly data from 1950 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). https://doi.org/10.24381/cds.e2161bac USGS, 2020. Digital Elevation Shuttle Radar Topography Mission (SRTM) 1 Arc-Second Global Non-Void Filled United States Geological Surv. https://doi.org/10.5066/F7K072R7 Zanaga, Van Den Kerchove, Daems, De Keersmaecker, Brockmann, Kirches, Wevers, Cartus, Santoro, Fritz, Lesiv, Herold, Tsendbazar, Xu, Ramoino, Arino, 2022. ESA WorldCover 10 m 2021 v200. https://doi.org/10.5281/zenodo.7254221本研究针对四条河流的温室气体（GHG, Greenhouse Gas）通量展开调查，分别是南美洲厄瓜多尔的昆卡河（Cuenca River）、非洲埃塞俄比亚的吉尔杰尔吉贝河（Gilgel Gibe River）、亚洲越南的Cau河，以及欧洲比利时的Zwalm河。上述河流涵盖了多样的水文气候区、地貌特征、土地利用与覆被（LULC, Land Use and Cover）类型以及人口密度。昆卡河与Zwalm河的年平均降水量（MAP, Mean Annual Precipitation）和年平均气温（MAT, Mean Annual Temperature）较为相近，但昆卡河海拔更高，因此潜在蒸散量（PET, Potential Evapotranspiration）更高，最低气温更低。吉尔杰尔吉贝河与Cau河之间也呈现类似规律：前者海拔更高，导致潜在蒸散量更高、生态系统更干旱；而后者海拔更低，最高气温更高。采样点基于其周边1公里半径范围内的土地利用与覆被类型，采用欧洲空间局（ESA, European Space Agency）的LULC地图（Zanaga等，2022）进行分类。数据库中记载了按LULC类别划分的采样点分布情况。 2022年2月至2023年10月期间共开展了5次采样作业。吉尔杰尔吉贝河、Cau河与昆卡河的采样点数量相近（约39个），而Zwalm河则在20个采样点上开展了冬、夏两季的季节性采样。气体样品采用浮箱法（FC, Floating Chamber）采集，用于分析河流温室气体排放，具体方法参照Ho等（2021）的研究。在每个采样点，于浮箱放置后的0、20、40分钟分别从其顶空采集3份气体样品。通过丁基橡胶塞配合20ml注射器抽取样品，并立即转移至预先处理过的12ml Exetainer®瓶中（先用氦气吹扫3次后抽真空）。样品瓶避光保存，随后运往根特大学ISOFYS实验室与苏黎世联邦理工学院进行分析。温室气体通量通过实测浓度随时间变化的线性回归斜率，结合浮箱的相关参数进行估算，计算公式如下（Ho等，2021）： （1） 此外，本研究还同步采集了生化、地貌、土地利用与覆被以及气象相关数据。采用WTW-3430多参数水质分析仪（WTW GmbH，德国魏尔海姆）原位测定水温、pH值、电导率（EC, Electroconductivity）、盐度与溶解氧（DO, Dissolved Oxygen）。采用YSI 6920V2-2多参数水质分析仪（YSI Xylem Inc.，美国俄亥俄州耶洛斯普林斯）测定浊度。两台分析仪均在采样前完成校准。流速采用Handheld flowtherm NT.2手持流速温度计（Höntzsch，德国）测定。采集所有采样点的水样，储存在阴凉避光容器中并冷藏以待分析。采用Spectroquant®试剂盒测定铵态氮（NH₄⁺）、硝态氮（NO₃⁻）、亚硝态氮（NO₂⁻）与总氮（TN）浓度。总有机碳（TOC, Total Organic Carbon）与总无机碳（TIC, Total Inorganic Carbon）采用岛津（Shimadzu）TOC-V CPN分析仪及自动进样器进行分析。气象数据最初采集自采样点附近的气象站，若存在数据缺失，则补充使用ERA5-Land数据集（Muñoz Sabater，2019）的相关信息。流域面积、河道坡度与地形数据通过航天飞机雷达地形测绘任务（SRTM, Shuttle Radar Topography Mission）的数字高程地图获取（美国地质调查局，2020）。 参考文献： Ho, L., Jerves-Cobo, R., Eurie Forio, M.A., Mouton, A., Nopens, I., Goethals, P., 2021. 城市化河流系统温室气体产生风险评估的机理与数据驱动整合模型. J. Environ. Manage. 294. https://doi.org/10.1016/j.jenvman.2021.112999 Muñoz Sabater, 2019. ERA5-Land 1950年至今逐小时气象数据集. 哥白尼气候变化服务局（C3S）气候数据存储库（CDS）. https://doi.org/10.24381/cds.e2161bac USGS, 2020. 航天飞机雷达地形测绘任务（SRTM）1弧秒全球无空洞填充数字高程地图. 美国地质调查局. https://doi.org/10.5066/F7K072R7 Zanaga, Van Den Kerchove, Daems, De Keersmaecker, Brockmann, Kirches, Wevers, Cartus, Santoro, Fritz, Lesiv, Herold, Tsendbazar, Xu, Ramoino, Arino, 2022. ESA WorldCover 10 m 2021 v200. https://doi.org/10.5281/zenodo.7254221