Articles | Volume 20, issue 12
https://doi.org/10.5194/bg-20-2387-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-20-2387-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Water-table-driven greenhouse gas emission estimates guide peatland restoration at national scale
Geological Survey of Denmark and Greenland, Department of Hydrology, Copenhagen, Denmark
Lars Elsgaard
Aarhus University, Department of Agroecology, Tjele, Denmark
Mogens H. Greve
Aarhus University, Department of Agroecology, Tjele, Denmark
Steen Gyldenkærne
Aarhus University, Department of Environmental Science, Roskilde, Denmark
Cecilie Hermansen
Aarhus University, Department of Agroecology, Tjele, Denmark
Gregor Levin
Aarhus University, Department of Environmental Science, Roskilde, Denmark
Shubiao Wu
Aarhus University, Department of Agroecology, Tjele, Denmark
Simon Stisen
Geological Survey of Denmark and Greenland, Department of Hydrology, Copenhagen, Denmark
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Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-292, https://doi.org/10.5194/essd-2024-292, 2024
Preprint under review for ESSD
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We developed a CAMELS-style dataset in Denmark, which contains hydrometeorological time series and landscape attributes for 3,330 catchments. Many of the catchments in CAMELS-DK are small and located at low elevations. The dataset provides information on groundwater characteristics and dynamics, as well as quantities related to human impact on the hydrological system in Denmark. The dataset is especially relevant for developing data-driven and hybrid physically-informed modeling frameworks.
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Hydrol. Earth Syst. Sci., 28, 2871–2893, https://doi.org/10.5194/hess-28-2871-2024, https://doi.org/10.5194/hess-28-2871-2024, 2024
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We developed hybrid schemes to enhance national-scale streamflow predictions, combining long short-term memory (LSTM) with a physically based hydrological model (PBM). A comprehensive evaluation of hybrid setups across Denmark indicates that LSTM models forced by climate data and catchment attributes perform well in many regions but face challenges in groundwater-dependent basins. The hybrid schemes supported by PBMs perform better in reproducing long-term streamflow behavior and extreme events.
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In our study, we analysed publicly available data in order to investigate the impact of climate change on landslides in Denmark. Our research indicates that the rising groundwater table due to climate change will result in an increase in landslide activity. Previous incidents of extremely wet winters have caused damage to infrastructure and buildings due to landslides. This study is the first of its kind to exclusively rely on public data and examine landslides in Denmark.
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Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-111, https://doi.org/10.5194/hess-2024-111, 2024
Revised manuscript accepted for HESS
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We present the results of the 2022 groundwater modeling challenge, where 15 teams applied data-driven models to simulate hydraulic heads. 3 groups of models were identified: lumped models, machine learning models, and deep learning models. For all wells, reasonable performance was obtained by at least 1 team from group. There was not 1 team that performed best for all wells. In conclusion, the challenge was a successful initiative to compare different models and learn from each other.
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Hydrol. Earth Syst. Sci., 28, 441–457, https://doi.org/10.5194/hess-28-441-2024, https://doi.org/10.5194/hess-28-441-2024, 2024
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This study provides a comparison of methodologies to quantify irrigation to enhance regional irrigation estimates. To evaluate the methodologies, we compared various approaches to quantify irrigation using soil moisture, evapotranspiration, or both within a novel baseline framework, together with irrigation estimates from other studies. We show that the synergy from using two equally important components in a joint approach within a baseline framework yields better irrigation estimates.
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Hydrol. Earth Syst. Sci., 27, 2463–2478, https://doi.org/10.5194/hess-27-2463-2023, https://doi.org/10.5194/hess-27-2463-2023, 2023
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This study investigates the precision of irrigation estimates from a global hotspot of unsustainable irrigation practice, the Indus and Ganges basins. We show that irrigation water use can be estimated with high precision by comparing satellite and rainfed hydrological model estimates of evapotranspiration. We believe that our work can support sustainable water resource management, as it addresses the uncertainty of a key component of the water balance that remains challenging to quantify.
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Hydrol. Earth Syst. Sci., 26, 5859–5877, https://doi.org/10.5194/hess-26-5859-2022, https://doi.org/10.5194/hess-26-5859-2022, 2022
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Hydrological models at high spatial resolution are computationally expensive. However, outputs from such models, such as the depth of the groundwater table, are often desired in high resolution. We developed a downscaling algorithm based on machine learning that allows us to increase spatial resolution of hydrological model outputs, alleviating computational burden. We successfully applied the downscaling algorithm to the climate-change-induced impacts on the groundwater table across Denmark.
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This study explores novel modelling avenues using machine learning in combination with process-based models to predict the shallow water table at high spatial resolution. Due to climate change and anthropogenic impacts, the shallow groundwater is rising in many parts of the world. In order to adapt to risks induced by groundwater flooding, new modelling tools need to emerge. In this study, we found that machine learning is capable of reaching the required accuracy and resolution.
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Our work addresses a key challenge in earth system modelling: how to optimally exploit the information contained in satellite remote sensing observations in the calibration of such models. For this we thoroughly test a number of measures that quantify the fit between an observed and a simulated spatial pattern. We acknowledge the difficulties associated with such a comparison and suggest using measures that regard multiple aspects of spatial information, i.e. magnitude and variability.
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Satellite data offer great opportunities to improve spatial model predictions by means of spatially oriented model evaluations. In this study, satellite images are used to observe spatial patterns of evapotranspiration at the land surface. These spatial patterns are utilized in combination with streamflow observations in a model calibration framework including a novel spatial performance metric tailored to target the spatial pattern performance of a catchment-scale hydrological model.
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Hydrol. Earth Syst. Sci., 21, 6235–6251, https://doi.org/10.5194/hess-21-6235-2017, https://doi.org/10.5194/hess-21-6235-2017, 2017
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Plants are shaping the landscape and controlling the hydrological cycle, particularly in arid and semi-arid ecosystems. Remote sensing data appears as an appealing source of information for vegetation monitoring, in particular in areas with a limited amount of available field data. Here, we present an example of how remote sensing data can be exploited in a data-scarce basin. We propose a mathematical methodology that can be used as a springboard for future applications.
Gorka Mendiguren, Julian Koch, and Simon Stisen
Hydrol. Earth Syst. Sci., 21, 5987–6005, https://doi.org/10.5194/hess-21-5987-2017, https://doi.org/10.5194/hess-21-5987-2017, 2017
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The present study is focused on the spatial pattern evaluation of two models and describes the similarities and dissimilarities. It also discusses the factors that generate these patterns and proposes similar new approaches to minimize the differences. The study points towards a new approach in which the spatial component of the hydrological model is also calibrated and taken into account.
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Preprint under review for ESSD
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We developed a CAMELS-style dataset in Denmark, which contains hydrometeorological time series and landscape attributes for 3,330 catchments. Many of the catchments in CAMELS-DK are small and located at low elevations. The dataset provides information on groundwater characteristics and dynamics, as well as quantities related to human impact on the hydrological system in Denmark. The dataset is especially relevant for developing data-driven and hybrid physically-informed modeling frameworks.
Jun Liu, Julian Koch, Simon Stisen, Lars Troldborg, and Raphael J. M. Schneider
Hydrol. Earth Syst. Sci., 28, 2871–2893, https://doi.org/10.5194/hess-28-2871-2024, https://doi.org/10.5194/hess-28-2871-2024, 2024
Short summary
Short summary
We developed hybrid schemes to enhance national-scale streamflow predictions, combining long short-term memory (LSTM) with a physically based hydrological model (PBM). A comprehensive evaluation of hybrid setups across Denmark indicates that LSTM models forced by climate data and catchment attributes perform well in many regions but face challenges in groundwater-dependent basins. The hybrid schemes supported by PBMs perform better in reproducing long-term streamflow behavior and extreme events.
Kristian Svennevig, Julian Koch, Marie Keiding, and Gregor Luetzenburg
Nat. Hazards Earth Syst. Sci., 24, 1897–1911, https://doi.org/10.5194/nhess-24-1897-2024, https://doi.org/10.5194/nhess-24-1897-2024, 2024
Short summary
Short summary
In our study, we analysed publicly available data in order to investigate the impact of climate change on landslides in Denmark. Our research indicates that the rising groundwater table due to climate change will result in an increase in landslide activity. Previous incidents of extremely wet winters have caused damage to infrastructure and buildings due to landslides. This study is the first of its kind to exclusively rely on public data and examine landslides in Denmark.
Raoul Alexander Collenteur, Ezra Haaf, Mark Bakker, Tanja Liesch, Andreas Wunsch, Jenny Soonthornrangsan, Jeremy White, Nick Martin, Rui Hugman, Michael Fienen, Ed de Sousa, Didier Vanden Berghe, Xinyang Fan, Tim Peterson, Janis Bikše, Antoine Di Ciacca, Xinyue Wang, Yang Zheng, Maximilian Nölscher, Julian Koch, Raphael Schneider, Nikolas Benavides Höglund, Sivarama Krishna Reddy Chidepudi, Abel Henriot, Nicolas Massei, Abderrahim Jardani, Max Gustav Rudolph, Amir Rouhani, Jaime Gómez-Hernández, Seifeddine Jomaa, Anna Pölz, Tim Franken, Morteza Behbooei, Jimmy Lin, Bryan Tolson, and Rojin Meysami
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-111, https://doi.org/10.5194/hess-2024-111, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
We present the results of the 2022 groundwater modeling challenge, where 15 teams applied data-driven models to simulate hydraulic heads. 3 groups of models were identified: lumped models, machine learning models, and deep learning models. For all wells, reasonable performance was obtained by at least 1 team from group. There was not 1 team that performed best for all wells. In conclusion, the challenge was a successful initiative to compare different models and learn from each other.
Søren Julsgaard Kragh, Jacopo Dari, Sara Modanesi, Christian Massari, Luca Brocca, Rasmus Fensholt, Simon Stisen, and Julian Koch
Hydrol. Earth Syst. Sci., 28, 441–457, https://doi.org/10.5194/hess-28-441-2024, https://doi.org/10.5194/hess-28-441-2024, 2024
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This study provides a comparison of methodologies to quantify irrigation to enhance regional irrigation estimates. To evaluate the methodologies, we compared various approaches to quantify irrigation using soil moisture, evapotranspiration, or both within a novel baseline framework, together with irrigation estimates from other studies. We show that the synergy from using two equally important components in a joint approach within a baseline framework yields better irrigation estimates.
Hafsa Mahmood, Ty P. A. Ferré, Raphael J. M. Schneider, Simon Stisen, Rasmus R. Frederiksen, and Anders V. Christiansen
EGUsphere, https://doi.org/10.5194/egusphere-2023-1872, https://doi.org/10.5194/egusphere-2023-1872, 2023
Preprint withdrawn
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Temporal drain flow dynamics and understanding of their underlying controlling factors are important for water resource management in tile-drained agricultural areas. This study examine whether simpler, more efficient machine learning (ML) models can provide acceptable solutions compared to traditional physics based models. We predicted drain flow time series in multiple catchments subject to a range of climatic and landscape conditions.
Søren J. Kragh, Rasmus Fensholt, Simon Stisen, and Julian Koch
Hydrol. Earth Syst. Sci., 27, 2463–2478, https://doi.org/10.5194/hess-27-2463-2023, https://doi.org/10.5194/hess-27-2463-2023, 2023
Short summary
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This study investigates the precision of irrigation estimates from a global hotspot of unsustainable irrigation practice, the Indus and Ganges basins. We show that irrigation water use can be estimated with high precision by comparing satellite and rainfed hydrological model estimates of evapotranspiration. We believe that our work can support sustainable water resource management, as it addresses the uncertainty of a key component of the water balance that remains challenging to quantify.
Raphael Schneider, Julian Koch, Lars Troldborg, Hans Jørgen Henriksen, and Simon Stisen
Hydrol. Earth Syst. Sci., 26, 5859–5877, https://doi.org/10.5194/hess-26-5859-2022, https://doi.org/10.5194/hess-26-5859-2022, 2022
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Hydrological models at high spatial resolution are computationally expensive. However, outputs from such models, such as the depth of the groundwater table, are often desired in high resolution. We developed a downscaling algorithm based on machine learning that allows us to increase spatial resolution of hydrological model outputs, alleviating computational burden. We successfully applied the downscaling algorithm to the climate-change-induced impacts on the groundwater table across Denmark.
Eva Sebok, Hans Jørgen Henriksen, Ernesto Pastén-Zapata, Peter Berg, Guillaume Thirel, Anthony Lemoine, Andrea Lira-Loarca, Christiana Photiadou, Rafael Pimentel, Paul Royer-Gaspard, Erik Kjellström, Jens Hesselbjerg Christensen, Jean Philippe Vidal, Philippe Lucas-Picher, Markus G. Donat, Giovanni Besio, María José Polo, Simon Stisen, Yvan Caballero, Ilias G. Pechlivanidis, Lars Troldborg, and Jens Christian Refsgaard
Hydrol. Earth Syst. Sci., 26, 5605–5625, https://doi.org/10.5194/hess-26-5605-2022, https://doi.org/10.5194/hess-26-5605-2022, 2022
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Hydrological models projecting the impact of changing climate carry a lot of uncertainty. Thus, these models usually have a multitude of simulations using different future climate data. This study used the subjective opinion of experts to assess which climate and hydrological models are the most likely to correctly predict climate impacts, thereby easing the computational burden. The experts could select more likely hydrological models, while the climate models were deemed equally probable.
Rena Meyer, Wenmin Zhang, Søren Julsgaard Kragh, Mie Andreasen, Karsten Høgh Jensen, Rasmus Fensholt, Simon Stisen, and Majken C. Looms
Hydrol. Earth Syst. Sci., 26, 3337–3357, https://doi.org/10.5194/hess-26-3337-2022, https://doi.org/10.5194/hess-26-3337-2022, 2022
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The amount and spatio-temporal distribution of soil moisture, the water in the upper soil, is of great relevance for agriculture and water management. Here, we investigate whether the established downscaling algorithm combining different satellite products to estimate medium-scale soil moisture is applicable to higher resolutions and whether results can be improved by accounting for land cover types. Original satellite data and downscaled soil moisture are compared with ground observations.
Gasper L. Sechu, Bertel Nilsson, Bo V. Iversen, Mette B. Greve, Christen D. Børgesen, and Mogens H. Greve
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-361, https://doi.org/10.5194/hess-2020-361, 2020
Manuscript not accepted for further review
Anders Bjørn Møller, Amélie Marie Beucher, Nastaran Pouladi, and Mogens Humlekrog Greve
SOIL, 6, 269–289, https://doi.org/10.5194/soil-6-269-2020, https://doi.org/10.5194/soil-6-269-2020, 2020
Short summary
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Decision trees have become a widely adapted tool for mapping soil properties in geographic space. However, it is problematic to implement spatial relationships in the models. We present a new method which uses geographic coordinates along several axes tilted at oblique angles in the models. We test this method on four spatial datasets. The results show that the new method is at least as accurate as other proposed alternatives, has a computational advantage and is flexible and interpretable.
Raphael Schneider, Hans Jørgen Henriksen, and Simon Stisen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-685, https://doi.org/10.5194/hess-2019-685, 2020
Revised manuscript not accepted
Short summary
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For groundwater models to deliver reliable results, their parameters often have to be estimated in an optimization process guided by some measure of model performance. In this context, we suggest the use of a novel performance metric, which is less prone to a fit to inadequate observations than the most frequently used metrics based on squared errors. Hence, calibration is more robust to deficiencies in model and observational data, which are common especially in larger scale models.
Arezoo Taghizadeh-Toosi, Lars Elsgaard, Tim J. Clough, Rodrigo Labouriau, Vibeke Ernstsen, and Søren O. Petersen
Biogeosciences, 16, 4555–4575, https://doi.org/10.5194/bg-16-4555-2019, https://doi.org/10.5194/bg-16-4555-2019, 2019
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Organic soils drained for crop production or grazing land have high potential for nitrous oxide emissions. The present study investigated the regulation of N2O emissions in a raised bog area drained for agriculture. It seems that archaeal ammonia oxidation and either chemodenitrification or nitrifier denitrification were considered to be plausible pathways of N2O production in spring, whereas in the autumn heterotrophic denitrification may have been more important at arable sites.
Julian Koch, Helen Berger, Hans Jørgen Henriksen, and Torben Obel Sonnenborg
Hydrol. Earth Syst. Sci., 23, 4603–4619, https://doi.org/10.5194/hess-23-4603-2019, https://doi.org/10.5194/hess-23-4603-2019, 2019
Short summary
Short summary
This study explores novel modelling avenues using machine learning in combination with process-based models to predict the shallow water table at high spatial resolution. Due to climate change and anthropogenic impacts, the shallow groundwater is rising in many parts of the world. In order to adapt to risks induced by groundwater flooding, new modelling tools need to emerge. In this study, we found that machine learning is capable of reaching the required accuracy and resolution.
Julian Koch, Mehmet Cüneyd Demirel, and Simon Stisen
Geosci. Model Dev., 11, 1873–1886, https://doi.org/10.5194/gmd-11-1873-2018, https://doi.org/10.5194/gmd-11-1873-2018, 2018
Short summary
Short summary
Our work addresses a key challenge in earth system modelling: how to optimally exploit the information contained in satellite remote sensing observations in the calibration of such models. For this we thoroughly test a number of measures that quantify the fit between an observed and a simulated spatial pattern. We acknowledge the difficulties associated with such a comparison and suggest using measures that regard multiple aspects of spatial information, i.e. magnitude and variability.
Mehmet C. Demirel, Juliane Mai, Gorka Mendiguren, Julian Koch, Luis Samaniego, and Simon Stisen
Hydrol. Earth Syst. Sci., 22, 1299–1315, https://doi.org/10.5194/hess-22-1299-2018, https://doi.org/10.5194/hess-22-1299-2018, 2018
Short summary
Short summary
Satellite data offer great opportunities to improve spatial model predictions by means of spatially oriented model evaluations. In this study, satellite images are used to observe spatial patterns of evapotranspiration at the land surface. These spatial patterns are utilized in combination with streamflow observations in a model calibration framework including a novel spatial performance metric tailored to target the spatial pattern performance of a catchment-scale hydrological model.
Arezoo Taghizadeh-Toosi, Lars Elsgaard, Tim Clough, Rodrigo Labouriau, and Søren Ole Petersen
Biogeosciences Discuss., https://doi.org/10.5194/bg-2018-9, https://doi.org/10.5194/bg-2018-9, 2018
Revised manuscript not accepted
Short summary
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Organic soils are extensively under agricultural management which lead to high emissions of N2O. We searched for relationships between seasonal variation in N2O emissions and potential driving variables such as temperature, precipitation, water table depth, N availability, and possible decomposibility of peat. Reducing surplus N in the soil, for example by use of a plant cover, and stabilisation of water table depth during the year, appear to be keys to controlling N2O emissions.
Guiomar Ruiz-Pérez, Julian Koch, Salvatore Manfreda, Kelly Caylor, and Félix Francés
Hydrol. Earth Syst. Sci., 21, 6235–6251, https://doi.org/10.5194/hess-21-6235-2017, https://doi.org/10.5194/hess-21-6235-2017, 2017
Short summary
Short summary
Plants are shaping the landscape and controlling the hydrological cycle, particularly in arid and semi-arid ecosystems. Remote sensing data appears as an appealing source of information for vegetation monitoring, in particular in areas with a limited amount of available field data. Here, we present an example of how remote sensing data can be exploited in a data-scarce basin. We propose a mathematical methodology that can be used as a springboard for future applications.
Gorka Mendiguren, Julian Koch, and Simon Stisen
Hydrol. Earth Syst. Sci., 21, 5987–6005, https://doi.org/10.5194/hess-21-5987-2017, https://doi.org/10.5194/hess-21-5987-2017, 2017
Short summary
Short summary
The present study is focused on the spatial pattern evaluation of two models and describes the similarities and dissimilarities. It also discusses the factors that generate these patterns and proposes similar new approaches to minimize the differences. The study points towards a new approach in which the spatial component of the hydrological model is also calibrated and taken into account.
A. Henneberg, L. Elsgaard, B. K. Sorrell, H. Brix, and S. O. Petersen
Biogeosciences, 12, 5667–5676, https://doi.org/10.5194/bg-12-5667-2015, https://doi.org/10.5194/bg-12-5667-2015, 2015
R. Guzinski, H. Nieto, S. Stisen, and R. Fensholt
Hydrol. Earth Syst. Sci., 19, 2017–2036, https://doi.org/10.5194/hess-19-2017-2015, https://doi.org/10.5194/hess-19-2017-2015, 2015
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The study compared evapotranspiration (ET) modelled by two remote sensing models and one hydrological model in a river catchment in Denmark. The results show that the spatial patterns of ET produced by the remote sensing models are more similar to each other than to the fluxes produced by the hydrological model. This indicates potential benefits to the hydrological modelling community from integrating spatial information derived through remote sensing methodology into the hydrological models.
H. Ajami, J. P. Evans, M. F. McCabe, and S. Stisen
Hydrol. Earth Syst. Sci., 18, 5169–5179, https://doi.org/10.5194/hess-18-5169-2014, https://doi.org/10.5194/hess-18-5169-2014, 2014
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A new hybrid approach was developed to reduce the computational burden of the spin-up procedure by using a combination of model simulations and an empirical depth-to-water table function. Results illustrate that the hybrid approach reduced the spin-up period required for an integrated groundwater--surface water--land surface model (ParFlow.CLM) by up to 50%. The methodology is applicable to other coupled or integrated modeling frameworks when initialization from an equilibrium state is required.
J. Koch, X. He, K. H. Jensen, and J. C. Refsgaard
Hydrol. Earth Syst. Sci., 18, 2907–2923, https://doi.org/10.5194/hess-18-2907-2014, https://doi.org/10.5194/hess-18-2907-2014, 2014
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Herbivore–shrub interactions influence ecosystem respiration and biogenic volatile organic compound composition in the subarctic
Methane emissions due to reservoir flushing: a significant emission pathway?
Carbon dioxide and methane fluxes from mounds of African fungus-growing termites
Diel and seasonal methane dynamics in the shallow and turbulent Wadden Sea
Technical note: Skirt chamber – an open dynamic method for the rapid and minimally intrusive measurement of greenhouse gas emissions from peatlands
Seasonal variability of nitrous oxide concentrations and emissions in a temperate estuary
Reviews and syntheses: Recent advances in microwave remote sensing in support of terrestrial carbon cycle science in Arctic–boreal regions
Simulated methane emissions from Arctic ponds are highly sensitive to warming
Relationships between greenhouse gas production and landscape position during short-term permafrost thaw under anaerobic conditions in the Lena Delta
Carbon emissions and radiative forcings from tundra wildfires in the Yukon–Kuskokwim River Delta, Alaska
Carbon monoxide (CO) cycling in the Fram Strait, Arctic Ocean
Post-flooding disturbance recovery promotes carbon capture in riparian zones
Meteorological responses of carbon dioxide and methane fluxes in the terrestrial and aquatic ecosystems of a subarctic landscape
Carbon emission and export from the Ket River, western Siberia
Evaluation of wetland CH4 in the Joint UK Land Environment Simulator (JULES) land surface model using satellite observations
Greenhouse gas fluxes in mangrove forest soil in an Amazon estuary
Temporal patterns and drivers of CO2 emission from dry sediments in a groyne field of a large river
Nathaniel B. Weston, Cynthia Troy, Patrick J. Kearns, Jennifer L. Bowen, William Porubsky, Christelle Hyacinthe, Christof Meile, Philippe Van Cappellen, and Samantha B. Joye
Biogeosciences, 21, 4837–4851, https://doi.org/10.5194/bg-21-4837-2024, https://doi.org/10.5194/bg-21-4837-2024, 2024
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Nitrous oxide (N2O) is a potent greenhouse and ozone-depleting gas produced largely from microbial nitrogen cycling processes, and human activities have resulted in increases in atmospheric N2O. We investigate the role of physical and chemical disturbances to soils and sediments in N2O production. We demonstrate that physicochemical perturbation increases N2O production, microbial community adapts over time, and initial perturbation appears to confer resilience to subsequent disturbance.
Sigrid Trier Kjær, Sebastian Westermann, Nora Nedkvitne, and Peter Dörsch
Biogeosciences, 21, 4723–4737, https://doi.org/10.5194/bg-21-4723-2024, https://doi.org/10.5194/bg-21-4723-2024, 2024
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Permafrost peatlands are thawing due to climate change, releasing large quantities of carbon that degrades upon thawing and is released as CO2, CH4 or dissolved organic carbon (DOC). We incubated thawed Norwegian permafrost peat plateaus and thermokarst pond sediment found next to permafrost for up to 350 d to measure carbon loss. CO2 production was initially the highest, whereas CH4 production increased over time. The largest carbon loss was measured at the top of the peat plateau core as DOC.
Silvie Lainela, Erik Jacobs, Stella-Theresa Luik, Gregor Rehder, and Urmas Lips
Biogeosciences, 21, 4495–4519, https://doi.org/10.5194/bg-21-4495-2024, https://doi.org/10.5194/bg-21-4495-2024, 2024
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We evaluate the variability of carbon dioxide and methane in the surface layer of the north-eastern basins of the Baltic Sea in 2018. We show that the shallower coastal areas have considerably higher spatial variability and seasonal amplitude of surface layer pCO2 and cCH4 than measured in the offshore areas of the Baltic Sea. Despite this high variability, caused mostly by coastal physical processes, the average annual air–sea CO2 fluxes differed only marginally between the sub-basins.
Martti Honkanen, Mika Aurela, Juha Hatakka, Lumi Haraguchi, Sami Kielosto, Timo Mäkelä, Jukka Seppälä, Simo-Matti Siiriä, Ken Stenbäck, Juha-Pekka Tuovinen, Pasi Ylöstalo, and Lauri Laakso
Biogeosciences, 21, 4341–4359, https://doi.org/10.5194/bg-21-4341-2024, https://doi.org/10.5194/bg-21-4341-2024, 2024
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The exchange of CO2 between the sea and the atmosphere was studied in the Archipelago Sea, Baltic Sea, in 2017–2021, using an eddy covariance technique. The sea acted as a net source of CO2 with an average yearly emission of 27.1 gC m-2 yr-1, indicating that the marine ecosystem respired carbon that originated elsewhere. The yearly CO2 emission varied between 18.2–39.2 gC m-2 yr-1, mostly due to the yearly variation of ecosystem carbon uptake.
Ralf C. H. Aben, Daniël van de Craats, Jim Boonman, Stijn H. Peeters, Bart Vriend, Coline C. F. Boonman, Ype van der Velde, Gilles Erkens, and Merit van den Berg
Biogeosciences, 21, 4099–4118, https://doi.org/10.5194/bg-21-4099-2024, https://doi.org/10.5194/bg-21-4099-2024, 2024
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Drained peatlands cause high CO2 emissions. We assessed the effectiveness of subsurface water infiltration systems (WISs) in reducing CO2 emissions related to increases in water table depth (WTD) on 12 sites for up to 4 years. Results show WISs markedly reduced emissions by 2.1 t CO2-C ha-1 yr-1. The relationship between the amount of carbon above the WTD and CO2 emission was stronger than the relationship between WTD and emission. Long-term monitoring is crucial for accurate emission estimates.
Ingeborg Bussmann, Eric P. Achterberg, Holger Brix, Nicolas Brüggemann, Götz Flöser, Claudia Schütze, and Philipp Fischer
Biogeosciences, 21, 3819–3838, https://doi.org/10.5194/bg-21-3819-2024, https://doi.org/10.5194/bg-21-3819-2024, 2024
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Methane (CH4) is an important greenhouse gas and contributes to climate warming. However, the input of CH4 from coastal areas to the atmosphere is not well defined. Dissolved and atmospheric CH4 was determined at high spatial resolution in or above the North Sea. The atmospheric CH4 concentration was mainly influenced by wind direction. With our detailed study on the spatial distribution of CH4 fluxes we were able to provide a detailed and more realistic estimation of coastal CH4 fluxes.
Niu Zhu, Jinniu Wang, Dongliang Luo, Xufeng Wang, Cheng Shen, and Ning Wu
Biogeosciences, 21, 3509–3522, https://doi.org/10.5194/bg-21-3509-2024, https://doi.org/10.5194/bg-21-3509-2024, 2024
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Our study delves into the vital role of subalpine forests in the Qinghai–Tibet Plateau as carbon sinks in the context of climate change. Utilizing advanced eddy covariance systems, we uncover their significant carbon sequestration potential, observing distinct seasonal patterns influenced by temperature, humidity, and radiation. Notably, these forests exhibit robust carbon absorption, with potential implications for global carbon balance.
Jessica Ashley Valerie Breavington, Alexandra Steckbauer, Chuancheng Fu, Mongi Ennasri, and Carlos Manuel Duarte
EGUsphere, https://doi.org/10.5194/egusphere-2024-1831, https://doi.org/10.5194/egusphere-2024-1831, 2024
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Mangroves are known for storing large amounts of carbon in their soils, but this is lower in the Red Sea due to challenging growth conditions. We collected soil cores over multiple seasons to measure soil properties, and the greenhouse gasses (GHG) of carbon dioxide and methane. We found that GHG emissions are generally a small offset to carbon storage but punctuated by periods of very high GHG emission and this variability is linked to multiple environmental and soil properties.
Colette L. Kelly, Nicole M. Travis, Pascale Anabelle Baya, Claudia Frey, Xin Sun, Bess B. Ward, and Karen L. Casciotti
Biogeosciences, 21, 3215–3238, https://doi.org/10.5194/bg-21-3215-2024, https://doi.org/10.5194/bg-21-3215-2024, 2024
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Nitrous oxide, a potent greenhouse gas, accumulates in regions of the ocean that are low in dissolved oxygen. We used a novel combination of chemical tracers to determine how nitrous oxide is produced in one of these regions, the eastern tropical North Pacific Ocean. Our experiments showed that the two most important sources of nitrous oxide under low-oxygen conditions are denitrification, an anaerobic process, and a novel “hybrid” process performed by ammonia-oxidizing archaea.
Hella van Asperen, Thorsten Warneke, Alessandro Carioca de Araújo, Bruce Forsberg, Sávio José Filgueiras Ferreira, Thomas Röckmann, Carina van der Veen, Sipko Bulthuis, Leonardo Ramos de Oliveira, Thiago de Lima Xavier, Jailson da Mata, Marta de Oliveira Sá, Paulo Ricardo Teixeira, Julie Andrews de França e Silva, Susan Trumbore, and Justus Notholt
Biogeosciences, 21, 3183–3199, https://doi.org/10.5194/bg-21-3183-2024, https://doi.org/10.5194/bg-21-3183-2024, 2024
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Carbon monoxide (CO) is regarded as an important indirect greenhouse gas. Soils can emit and take up CO, but, until now, uncertainty remains as to which process dominates in tropical rainforests. We present the first soil CO flux measurements from a tropical rainforest. Based on our observations, we report that tropical rainforest soils are a net source of CO. In addition, we show that valley streams and inundated areas are likely additional hot spots of CO in the ecosystem.
Ihab Alfadhel, Ignacio Peralta-Maraver, Isabel Reche, Enrique P. Sánchez-Cañete, Sergio Aranda-Barranco, Eva Rodríguez-Velasco, Andrew S. Kowalski, and Penélope Serrano-Ortiz
EGUsphere, https://doi.org/10.5194/egusphere-2024-1562, https://doi.org/10.5194/egusphere-2024-1562, 2024
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Inland saline lakes are crucial in the global carbon cycle, but increased droughts may alter their carbon exchange capacity. We measured CO2 and CH4 fluxes in a Mediterranean saline lake using the Eddy Covariance method under dry and wet conditions. We found the lake acts as a carbon sink during wet periods but not during droughts. These results highlight the importance of saline lakes in carbon sequestration and their vulnerability to climate change-induced droughts.
Johnathan D. Maxey, Neil D. Hartstein, Hermann W. Bange, and Mortiz Müller
EGUsphere, https://doi.org/10.5194/egusphere-2024-1731, https://doi.org/10.5194/egusphere-2024-1731, 2024
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The distribution of N2O in fjord-like estuaries is poorly described in the southern hemisphere. Our study describes N2O distribution and its drivers in one such system Macquarie Harbour, Tasmania. Water samples were collected seasonally from 2022/2023. Results show the system is a sink for atmospheric N2O when river flow is high; and the system emits N2O when the river flow is low. N2O generated in basins is intercepted by the surface water and exported to the ocean during high river flow.
Wael Al Hamwi, Maren Dubbert, Joerg Schaller, Matthias Lueck, Marten Schmidt, and Mathias Hoffmann
EGUsphere, https://doi.org/10.5194/egusphere-2024-1806, https://doi.org/10.5194/egusphere-2024-1806, 2024
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We present a fully automatic, low-cost soil-plant enclosure system to monitor CO2 and ET fluxes within greenhouse experiments. It operates in two modes: independent, using low-cost sensors, and dependent, connecting multiple chambers to a single gas analyzer via a low-cost multiplexer. This system offers precise and accurate measurements, cost and labor efficiency, and high temporal resolution, enabling comprehensive monitoring of plant-soil responses to various treatments and conditions.
Yélognissè Agbohessou, Claire Delon, Manuela Grippa, Eric Mougin, Daouda Ngom, Espoir Koudjo Gaglo, Ousmane Ndiaye, Paulo Salgado, and Olivier Roupsard
Biogeosciences, 21, 2811–2837, https://doi.org/10.5194/bg-21-2811-2024, https://doi.org/10.5194/bg-21-2811-2024, 2024
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Emissions of greenhouse gases in the Sahel are not well represented because they are considered weak compared to the rest of the world. However, natural areas in the Sahel emit carbon dioxide and nitrous oxides, which need to be assessed because of extended surfaces. We propose an assessment of such emissions in Sahelian silvopastoral systems and of how they are influenced by environmental characteristics. These results are essential to inform climate change strategies in the region.
Zhen Zhang, Benjamin Poulter, Joe R. Melton, William J. Riley, George H. Allen, David J. Beerling, Philippe Bousquet, Josep G. Canadell, Etienne Fluet-Chouinard, Philippe Ciais, Nicola Gedney, Peter O. Hopcroft, Akihiko Ito, Robert B. Jackson, Atul K. Jain, Katherine Jensen, Fortunat Joos, Thomas Kleinen, Sara Knox, Tingting Li, Xin Li, Xiangyu Liu, Kyle McDonald, Gavin McNicol, Paul A. Miller, Jurek Müller, Prabir K. Patra, Changhui Peng, Shushi Peng, Zhangcai Qin, Ryan M. Riggs, Marielle Saunois, Qing Sun, Hanqin Tian, Xiaoming Xu, Yuanzhi Yao, Xi Yi, Wenxin Zhang, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
EGUsphere, https://doi.org/10.5194/egusphere-2024-1584, https://doi.org/10.5194/egusphere-2024-1584, 2024
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This study assesses global methane emissions from wetlands between 2000 and 2020 using multiple models. We found that wetland emissions increased by 6–7 Tg CH4 per year in the 2010s compared to the 2000s. Rising temperatures primarily drove this increase, while changes in precipitation and CO2 levels also played roles. Our findings highlight the importance of wetlands in the global methane budget and the need for continuous monitoring to understand their impact on climate change.
Merit van den Berg, Thomas M. Gremmen, Renske J. E. Vroom, Jacobus van Huissteden, Jim Boonman, Corine J. A. van Huissteden, Ype van der Velde, Alfons J. P. Smolders, and Bas P. van de Riet
Biogeosciences, 21, 2669–2690, https://doi.org/10.5194/bg-21-2669-2024, https://doi.org/10.5194/bg-21-2669-2024, 2024
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Drained peatlands emit 3 % of the global greenhouse gas emissions. Paludiculture is a way to reduce CO2 emissions while at the same time generating an income for landowners. The side effect is the potentially high methane emissions. We found very high methane emissions for broadleaf cattail compared with narrowleaf cattail and water fern. The rewetting was, however, effective to stop CO2 emissions for all species. The highest potential to reduce greenhouse gas emissions had narrowleaf cattail.
Lorena Carrasco-Barea, Dolors Verdaguer, Maria Gispert, Xavier D. Quintana, Hélène Bourhis, and Laura Llorens
EGUsphere, https://doi.org/10.5194/egusphere-2024-1320, https://doi.org/10.5194/egusphere-2024-1320, 2024
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Carbon dioxide fluxes have been measured seasonally in four plant species in a Mediterranean non-tidal salt marsh highlighting the high carbon removal potential that these species have. Carbon dioxide and methane emissions from soil showed high variability among the habitats studied and they were generally higher than those observed in tidal salt marshes. Our results are important to make more accurate predictions regarding carbon emissions from these ecosystems.
Thea H. Heimdal, Galen A. McKinley, Adrienne J. Sutton, Amanda R. Fay, and Lucas Gloege
Biogeosciences, 21, 2159–2176, https://doi.org/10.5194/bg-21-2159-2024, https://doi.org/10.5194/bg-21-2159-2024, 2024
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Measurements of ocean carbon are limited in time and space. Machine learning algorithms are therefore used to reconstruct ocean carbon where observations do not exist. Improving these reconstructions is important in order to accurately estimate how much carbon the ocean absorbs from the atmosphere. In this study, we find that a small addition of observations from the Southern Ocean, obtained by autonomous sampling platforms, could significantly improve the reconstructions.
Guilherme L. Torres Mendonça, Julia Pongratz, and Christian H. Reick
Biogeosciences, 21, 1923–1960, https://doi.org/10.5194/bg-21-1923-2024, https://doi.org/10.5194/bg-21-1923-2024, 2024
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We study the timescale dependence of airborne fraction and underlying feedbacks by a theory of the climate–carbon system. Using simulations we show the predictive power of this theory and find that (1) this fraction generally decreases for increasing timescales and (2) at all timescales the total feedback is negative and the model spread in a single feedback causes the spread in the airborne fraction. Our study indicates that those are properties of the system, independently of the scenario.
François Clayer, Jan Erik Thrane, Kuria Ndungu, Andrew King, Peter Dörsch, and Thomas Rohrlack
Biogeosciences, 21, 1903–1921, https://doi.org/10.5194/bg-21-1903-2024, https://doi.org/10.5194/bg-21-1903-2024, 2024
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Determination of dissolved greenhouse gas (GHG) in freshwater allows us to estimate GHG fluxes. Mercuric chloride (HgCl2) is used to preserve water samples prior to GHG analysis despite its environmental and health impacts and interferences with water chemistry in freshwater. Here, we tested the effects of HgCl2, two substitutes and storage time on GHG in water from two boreal lakes. Preservation with HgCl2 caused overestimation of CO2 concentration with consequences for GHG flux estimation.
Helena Rautakoski, Mika Korkiakoski, Jarmo Mäkelä, Markku Koskinen, Kari Minkkinen, Mika Aurela, Paavo Ojanen, and Annalea Lohila
Biogeosciences, 21, 1867–1886, https://doi.org/10.5194/bg-21-1867-2024, https://doi.org/10.5194/bg-21-1867-2024, 2024
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Current and future nitrous oxide (N2O) emissions are difficult to estimate due to their high variability in space and time. Several years of N2O fluxes from drained boreal peatland forest indicate high importance of summer precipitation, winter temperature, and snow conditions in controlling annual N2O emissions. The results indicate increasing year-to-year variation in N2O emissions in changing climate with more extreme seasonal weather conditions.
Matthias Koschorreck, Norbert Kamjunke, Uta Koedel, Michael Rode, Claudia Schuetze, and Ingeborg Bussmann
Biogeosciences, 21, 1613–1628, https://doi.org/10.5194/bg-21-1613-2024, https://doi.org/10.5194/bg-21-1613-2024, 2024
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We measured the emission of carbon dioxide (CO2) and methane (CH4) from different sites at the river Elbe in Germany over 3 days to find out what is more important for quantification: small-scale spatial variability or diurnal temporal variability. We found that CO2 emissions were very different between day and night, while CH4 emissions were more different between sites. Dried out river sediments contributed to CO2 emissions, while the side areas of the river were important CH4 sources.
Odysseas Sifounakis, Edwin Haas, Klaus Butterbach-Bahl, and Maria P. Papadopoulou
Biogeosciences, 21, 1563–1581, https://doi.org/10.5194/bg-21-1563-2024, https://doi.org/10.5194/bg-21-1563-2024, 2024
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We performed a full assessment of the carbon and nitrogen cycles of a cropland ecosystem. An uncertainty analysis and quantification of all carbon and nitrogen fluxes were deployed. The inventory simulations include greenhouse gas emissions of N2O, NH3 volatilization and NO3 leaching from arable land cultivation in Greece. The inventory also reports changes in soil organic carbon and nitrogen stocks in arable soils.
Sarah M. Ludwig, Luke Schiferl, Jacqueline Hung, Susan M. Natali, and Roisin Commane
Biogeosciences, 21, 1301–1321, https://doi.org/10.5194/bg-21-1301-2024, https://doi.org/10.5194/bg-21-1301-2024, 2024
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Landscapes are often assumed to be homogeneous when using eddy covariance fluxes, which can lead to biases when calculating carbon budgets. In this study we report eddy covariance carbon fluxes from heterogeneous tundra. We used the footprints of each flux observation to unmix the fluxes coming from components of the landscape. We identified and quantified hot spots of carbon emissions in the landscape. Accurately scaling with landscape heterogeneity yielded half as much regional carbon uptake.
Zhao-Jun Yong, Wei‐Jen Lin, Chiao-Wen Lin, and Hsing-Juh Lin Lin
EGUsphere, https://doi.org/10.5194/egusphere-2024-533, https://doi.org/10.5194/egusphere-2024-533, 2024
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This study is the first to simultaneously measure mangrove CH4 emissions from both stems and soils throughout tidal cycles. The stems served as both net CO2 and CH4 sources. Compared to those of the soils, the stems exhibited markedly lower CH4 emissions, but no difference in CO2 emissions. Sampling only during low tides might overestimate the stem CO2 and CH4 emissions on a diurnal scale. This study also highlights species distinctness (with pneumatophores) in the emissions.
Justine Trémeau, Beñat Olascoaga, Leif Backman, Esko Karvinen, Henriikka Vekuri, and Liisa Kulmala
Biogeosciences, 21, 949–972, https://doi.org/10.5194/bg-21-949-2024, https://doi.org/10.5194/bg-21-949-2024, 2024
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We studied urban lawns and meadows in the Helsinki metropolitan area, Finland. We found that meadows are more resistant to drought events but that they do not increase carbon sequestration compared with lawns. Moreover, the transformation from lawns to meadows did not demonstrate any negative climate effects in terms of greenhouse gas emissions. Even though social and economic aspects also steer urban development, these results can guide planning to consider carbon-smart options.
Guantao Chen, Edzo Veldkamp, Muhammad Damris, Bambang Irawan, Aiyen Tjoa, and Marife D. Corre
Biogeosciences, 21, 513–529, https://doi.org/10.5194/bg-21-513-2024, https://doi.org/10.5194/bg-21-513-2024, 2024
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We established an oil palm management experiment in a large-scale oil palm plantation in Jambi, Indonesia. We recorded oil palm fruit yield and measured soil CO2, N2O, and CH4 fluxes. After 4 years of treatment, compared with conventional fertilization with herbicide weeding, reduced fertilization with mechanical weeding did not reduce yield and soil greenhouse gas emissions, which highlights the legacy effects of over a decade of conventional management prior to the start of the experiment.
Tuula Aalto, Aki Tsuruta, Jarmo Mäkelä, Jurek Mueller, Maria Tenkanen, Eleanor Burke, Sarah Chadburn, Yao Gao, Vilma Mannisenaho, Thomas Kleinen, Hanna Lee, Antti Leppänen, Tiina Markkanen, Stefano Materia, Paul Miller, Daniele Peano, Olli Peltola, Benjamin Poulter, Maarit Raivonen, Marielle Saunois, David Wårlind, and Sönke Zaehle
EGUsphere, https://doi.org/10.5194/egusphere-2023-2873, https://doi.org/10.5194/egusphere-2023-2873, 2024
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Wetland methane responses to temperature and precipitation were studied in a boreal wetland-rich region in Northern Europe using ecosystem models, atmospheric inversions and up-scaled flux observations. The ecosystem models differed in their responses to temperature and precipitation and in their seasonality. However, multi-model means, inversions and up-scaled fluxes had similar seasonality, and they suggested co-limitation by temperature and precipitation.
Elizabeth Gachibu Wangari, Ricky Mwangada Mwanake, Tobias Houska, David Kraus, Gretchen Maria Gettel, Ralf Kiese, Lutz Breuer, and Klaus Butterbach-Bahl
Biogeosciences, 20, 5029–5067, https://doi.org/10.5194/bg-20-5029-2023, https://doi.org/10.5194/bg-20-5029-2023, 2023
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Agricultural landscapes act as sinks or sources of the greenhouse gases (GHGs) CO2, CH4, or N2O. Various physicochemical and biological processes control the fluxes of these GHGs between ecosystems and the atmosphere. Therefore, fluxes depend on environmental conditions such as soil moisture, soil temperature, or soil parameters, which result in large spatial and temporal variations of GHG fluxes. Here, we describe an example of how this variation may be studied and analyzed.
Ekaterina Ezhova, Topi Laanti, Anna Lintunen, Pasi Kolari, Tuomo Nieminen, Ivan Mammarella, Keijo Heljanko, and Markku Kulmala
EGUsphere, https://doi.org/10.5194/egusphere-2023-2559, https://doi.org/10.5194/egusphere-2023-2559, 2023
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ML models are gaining popularity in biogeosciences. They are applied as gapfilling methods and used to upscale carbon fluxes to larger areas based on local measurements. In this study, we use Explainable ML methods to elucidate performance of machine learning models for carbon dioxide fluxes in boreal forest. We show that statistically equal models treat input variables differently. Explainable ML can help scientists to make informed solutions when applying ML models in their research.
Laurie C. Menviel, Paul Spence, Andrew E. Kiss, Matthew A. Chamberlain, Hakase Hayashida, Matthew H. England, and Darryn Waugh
Biogeosciences, 20, 4413–4431, https://doi.org/10.5194/bg-20-4413-2023, https://doi.org/10.5194/bg-20-4413-2023, 2023
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As the ocean absorbs 25% of the anthropogenic emissions of carbon, it is important to understand the impact of climate change on the flux of carbon between the ocean and the atmosphere. Here, we use a very high-resolution ocean, sea-ice, carbon cycle model to show that the capability of the Southern Ocean to uptake CO2 has decreased over the last 40 years due to a strengthening and poleward shift of the southern hemispheric westerlies. This trend is expected to continue over the coming century.
Petr Znachor, Jiří Nedoma, Vojtech Kolar, and Anna Matoušů
Biogeosciences, 20, 4273–4288, https://doi.org/10.5194/bg-20-4273-2023, https://doi.org/10.5194/bg-20-4273-2023, 2023
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We conducted intensive spatial sampling of the hypertrophic fishpond to better understand the spatial dynamics of methane fluxes and environmental heterogeneity in fishponds. The diffusive fluxes of methane accounted for only a minor fraction of the total fluxes and both varied pronouncedly within the pond and over the studied summer season. This could be explained only by the water depth. Wind substantially affected temperature, oxygen and chlorophyll a distribution in the pond.
Sofie Sjögersten, Martha Ledger, Matthias Siewert, Betsabé de la Barreda-Bautista, Andrew Sowter, David Gee, Giles Foody, and Doreen S. Boyd
Biogeosciences, 20, 4221–4239, https://doi.org/10.5194/bg-20-4221-2023, https://doi.org/10.5194/bg-20-4221-2023, 2023
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Permafrost thaw in Arctic regions is increasing methane emissions, but quantification is difficult given the large and remote areas impacted. We show that UAV data together with satellite data can be used to extrapolate emissions across the wider landscape as well as detect areas at risk of higher emissions. A transition of currently degrading areas to fen type vegetation can increase emission by several orders of magnitude, highlighting the importance of quantifying areas at risk.
Cole G. Brachmann, Tage Vowles, Riikka Rinnan, Mats P. Björkman, Anna Ekberg, and Robert G. Björk
Biogeosciences, 20, 4069–4086, https://doi.org/10.5194/bg-20-4069-2023, https://doi.org/10.5194/bg-20-4069-2023, 2023
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Herbivores change plant communities through grazing, altering the amount of CO2 and plant-specific chemicals (termed VOCs) emitted. We tested this effect by excluding herbivores and studying the CO2 and VOC emissions. Herbivores reduced CO2 emissions from a meadow community and altered VOC composition; however, community type had the strongest effect on the amount of CO2 and VOCs released. Herbivores can mediate greenhouse gas emissions, but the effect is marginal and community dependent.
Ole Lessmann, Jorge Encinas Fernández, Karla Martínez-Cruz, and Frank Peeters
Biogeosciences, 20, 4057–4068, https://doi.org/10.5194/bg-20-4057-2023, https://doi.org/10.5194/bg-20-4057-2023, 2023
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Based on a large dataset of seasonally resolved methane (CH4) pore water concentrations in a reservoir's sediment, we assess the significance of CH4 emissions due to reservoir flushing. In the studied reservoir, CH4 emissions caused by one flushing operation can represent 7 %–14 % of the annual CH4 emissions and depend on the timing of the flushing operation. In reservoirs with high sediment loadings, regular flushing may substantially contribute to the overall CH4 emissions.
Matti Räsänen, Risto Vesala, Petri Rönnholm, Laura Arppe, Petra Manninen, Markus Jylhä, Jouko Rikkinen, Petri Pellikka, and Janne Rinne
Biogeosciences, 20, 4029–4042, https://doi.org/10.5194/bg-20-4029-2023, https://doi.org/10.5194/bg-20-4029-2023, 2023
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Fungus-growing termites recycle large parts of dead plant material in African savannas and are significant sources of greenhouse gases. We measured CO2 and CH4 fluxes from their mounds and surrounding soils in open and closed habitats. The fluxes scale with mound volume. The results show that emissions from mounds of fungus-growing termites are more stable than those from other termites. The soil fluxes around the mound are affected by the termite colonies at up to 2 m distance from the mound.
Tim René de Groot, Anne Margriet Mol, Katherine Mesdag, Pierre Ramond, Rachel Ndhlovu, Julia Catherine Engelmann, Thomas Röckmann, and Helge Niemann
Biogeosciences, 20, 3857–3872, https://doi.org/10.5194/bg-20-3857-2023, https://doi.org/10.5194/bg-20-3857-2023, 2023
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This study investigates methane dynamics in the Wadden Sea. Our measurements revealed distinct variations triggered by seasonality and tidal forcing. The methane budget was higher in warmer seasons but surprisingly high in colder seasons. Methane dynamics were amplified during low tides, flushing the majority of methane into the North Sea or releasing it to the atmosphere. Methanotrophic activity was also elevated during low tide but mitigated only a small fraction of the methane efflux.
Frederic Thalasso, Brenda Riquelme, Andrés Gómez, Roy Mackenzie, Francisco Javier Aguirre, Jorge Hoyos-Santillan, Ricardo Rozzi, and Armando Sepulveda-Jauregui
Biogeosciences, 20, 3737–3749, https://doi.org/10.5194/bg-20-3737-2023, https://doi.org/10.5194/bg-20-3737-2023, 2023
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A robust skirt-chamber design to capture and quantify greenhouse gas emissions from peatlands is presented. Compared to standard methods, this design improves the spatial resolution of field studies in remote locations while minimizing intrusion.
Gesa Schulz, Tina Sanders, Yoana G. Voynova, Hermann W. Bange, and Kirstin Dähnke
Biogeosciences, 20, 3229–3247, https://doi.org/10.5194/bg-20-3229-2023, https://doi.org/10.5194/bg-20-3229-2023, 2023
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Nitrous oxide (N2O) is an important greenhouse gas. However, N2O emissions from estuaries underlie significant uncertainties due to limited data availability and high spatiotemporal variability. We found the Elbe Estuary (Germany) to be a year-round source of N2O, with the highest emissions in winter along with high nitrogen loads. However, in spring and summer, N2O emissions did not decrease alongside lower nitrogen loads because organic matter fueled in situ N2O production along the estuary.
Alex Mavrovic, Oliver Sonnentag, Juha Lemmetyinen, Jennifer L. Baltzer, Christophe Kinnard, and Alexandre Roy
Biogeosciences, 20, 2941–2970, https://doi.org/10.5194/bg-20-2941-2023, https://doi.org/10.5194/bg-20-2941-2023, 2023
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This review supports the integration of microwave spaceborne information into carbon cycle science for Arctic–boreal regions. The microwave data record spans multiple decades with frequent global observations of soil moisture and temperature, surface freeze–thaw cycles, vegetation water storage, snowpack properties, and land cover. This record holds substantial unexploited potential to better understand carbon cycle processes.
Zoé Rehder, Thomas Kleinen, Lars Kutzbach, Victor Stepanenko, Moritz Langer, and Victor Brovkin
Biogeosciences, 20, 2837–2855, https://doi.org/10.5194/bg-20-2837-2023, https://doi.org/10.5194/bg-20-2837-2023, 2023
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We use a new model to investigate how methane emissions from Arctic ponds change with warming. We find that emissions increase substantially. Under annual temperatures 5 °C above present temperatures, pond methane emissions are more than 3 times higher than now. Most of this increase is caused by an increase in plant productivity as plants provide the substrate microbes used to produce methane. We conclude that vegetation changes need to be included in predictions of pond methane emissions.
Mélissa Laurent, Matthias Fuchs, Tanja Herbst, Alexandra Runge, Susanne Liebner, and Claire C. Treat
Biogeosciences, 20, 2049–2064, https://doi.org/10.5194/bg-20-2049-2023, https://doi.org/10.5194/bg-20-2049-2023, 2023
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In this study we investigated the effect of different parameters (temperature, landscape position) on the production of greenhouse gases during a 1-year permafrost thaw experiment. For very similar carbon and nitrogen contents, our results show a strong heterogeneity in CH4 production, as well as in microbial abundance. According to our study, these differences are mainly due to the landscape position and the hydrological conditions established as a result of the topography.
Michael Moubarak, Seeta Sistla, Stefano Potter, Susan M. Natali, and Brendan M. Rogers
Biogeosciences, 20, 1537–1557, https://doi.org/10.5194/bg-20-1537-2023, https://doi.org/10.5194/bg-20-1537-2023, 2023
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Tundra wildfires are increasing in frequency and severity with climate change. We show using a combination of field measurements and computational modeling that tundra wildfires result in a positive feedback to climate change by emitting significant amounts of long-lived greenhouse gasses. With these effects, attention to tundra fires is necessary for mitigating climate change.
Hanna I. Campen, Damian L. Arévalo-Martínez, and Hermann W. Bange
Biogeosciences, 20, 1371–1379, https://doi.org/10.5194/bg-20-1371-2023, https://doi.org/10.5194/bg-20-1371-2023, 2023
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Carbon monoxide (CO) is a climate-relevant trace gas emitted from the ocean. However, oceanic CO cycling is understudied. Results from incubation experiments conducted in the Fram Strait (Arctic Ocean) indicated that (i) pH did not affect CO cycling and (ii) enhanced CO production and consumption were positively correlated with coloured dissolved organic matter and nitrate concentrations. This suggests microbial CO uptake to be the driving factor for CO cycling in the Arctic Ocean.
Yihong Zhu, Ruihua Liu, Huai Zhang, Shaoda Liu, Zhengfeng Zhang, Fei-Hai Yu, and Timothy G. Gregoire
Biogeosciences, 20, 1357–1370, https://doi.org/10.5194/bg-20-1357-2023, https://doi.org/10.5194/bg-20-1357-2023, 2023
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With global warming, the risk of flooding is rising, but the response of the carbon cycle of aquatic and associated riparian systems
to flooding is still unclear. Based on the data collected in the Lijiang, we found that flooding would lead to significant carbon emissions of fluvial areas and riparian areas during flooding, but carbon capture may happen after flooding. In the riparian areas, the surviving vegetation, especially clonal plants, played a vital role in this transformation.
Lauri Heiskanen, Juha-Pekka Tuovinen, Henriikka Vekuri, Aleksi Räsänen, Tarmo Virtanen, Sari Juutinen, Annalea Lohila, Juha Mikola, and Mika Aurela
Biogeosciences, 20, 545–572, https://doi.org/10.5194/bg-20-545-2023, https://doi.org/10.5194/bg-20-545-2023, 2023
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We measured and modelled the CO2 and CH4 fluxes of the terrestrial and aquatic ecosystems of the subarctic landscape for 2 years. The landscape was an annual CO2 sink and a CH4 source. The forest had the largest contribution to the landscape-level CO2 sink and the peatland to the CH4 emissions. The lakes released 24 % of the annual net C uptake of the landscape back to the atmosphere. The C fluxes were affected most by the rainy peak growing season of 2017 and the drought event in July 2018.
Artem G. Lim, Ivan V. Krickov, Sergey N. Vorobyev, Mikhail A. Korets, Sergey Kopysov, Liudmila S. Shirokova, Jan Karlsson, and Oleg S. Pokrovsky
Biogeosciences, 19, 5859–5877, https://doi.org/10.5194/bg-19-5859-2022, https://doi.org/10.5194/bg-19-5859-2022, 2022
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In order to quantify C transport and emission and main environmental factors controlling the C cycle in Siberian rivers, we investigated the largest tributary of the Ob River, the Ket River basin, by measuring spatial and seasonal variations in carbon CO2 and CH4 concentrations and emissions together with hydrochemical analyses. The obtained results are useful for large-scale modeling of C emission and export fluxes from permafrost-free boreal rivers of an underrepresented region of the world.
Robert J. Parker, Chris Wilson, Edward Comyn-Platt, Garry Hayman, Toby R. Marthews, A. Anthony Bloom, Mark F. Lunt, Nicola Gedney, Simon J. Dadson, Joe McNorton, Neil Humpage, Hartmut Boesch, Martyn P. Chipperfield, Paul I. Palmer, and Dai Yamazaki
Biogeosciences, 19, 5779–5805, https://doi.org/10.5194/bg-19-5779-2022, https://doi.org/10.5194/bg-19-5779-2022, 2022
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Wetlands are the largest natural source of methane, one of the most important climate gases. The JULES land surface model simulates these emissions. We use satellite data to evaluate how well JULES reproduces the methane seasonal cycle over different tropical wetlands. It performs well for most regions; however, it struggles for some African wetlands influenced heavily by river flooding. We explain the reasons for these deficiencies and highlight how future development will improve these areas.
Saúl Edgardo Martínez Castellón, José Henrique Cattanio, José Francisco Berrêdo, Marcelo Rollnic, Maria de Lourdes Ruivo, and Carlos Noriega
Biogeosciences, 19, 5483–5497, https://doi.org/10.5194/bg-19-5483-2022, https://doi.org/10.5194/bg-19-5483-2022, 2022
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We seek to understand the influence of climatic seasonality and microtopography on CO2 and CH4 fluxes in an Amazonian mangrove. Topography and seasonality had a contrasting influence when comparing the two gas fluxes: CO2 fluxes were greater in high topography in the dry period, and CH4 fluxes were greater in the rainy season in low topography. Only CO2 fluxes were correlated with soil organic matter, the proportion of carbon and nitrogen, and redox potential.
Matthias Koschorreck, Klaus Holger Knorr, and Lelaina Teichert
Biogeosciences, 19, 5221–5236, https://doi.org/10.5194/bg-19-5221-2022, https://doi.org/10.5194/bg-19-5221-2022, 2022
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At low water levels, parts of the bottom of rivers fall dry. These beaches or mudflats emit the greenhouse gas carbon dioxide (CO2) to the atmosphere. We found that those emissions are caused by microbial reactions in the sediment and that they change with time. Emissions were influenced by many factors like temperature, water level, rain, plants, and light.
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Short summary
Utilizing peatlands for agriculture leads to large emissions of greenhouse gases worldwide. The emissions are triggered by lowering the water table, which is a necessary step in order to make peatlands arable. Many countries aim at reducing their emissions by restoring peatlands, which can be achieved by stopping agricultural activities and thereby raising the water table. We estimate a total emission of 2.6 Mt CO2-eq for organic-rich peatlands in Denmark and a potential reduction of 77 %.
Utilizing peatlands for agriculture leads to large emissions of greenhouse gases worldwide. The...
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