Articles | Volume 11, issue 3
https://doi.org/10.5194/gmd-11-903-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-11-903-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
09 Mar 2018
Development and technical paper |
| 09 Mar 2018
| 09 Mar 2018
Autocalibration of a one-dimensional hydrodynamic-ecological model (DYRESM 4.0-CAEDYM 3.1) using a Monte Carlo approach: simulations of hypoxic events in a polymictic lake
Liancong Luo
CORRESPONDING AUTHOR
State Key Laboratory of Lake Science and Environment, Nanjing
Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing,
210008, China
David Hamilton
Australian Rivers Institute, Griffith University, Queensland, Australia
Jia Lan
Chunan Environmental Protection Bureau, Chunan, 311700, Zhejiang
Province, China
Chris McBride
Environmental Research Institute, Waikato University, Hamilton 3240,
New Zealand
Dennis Trolle
Department of Bioscience, Aarhus University, Aarhus 8000, Denmark
Related authors
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Ida Karlsson Seidenfaden, Torben Obel Sonnenborg, Jens Christian Refsgaard, Christen Duus Børgesen, Jørgen Eivind Olesen, and Dennis Trolle
Hydrol. Earth Syst. Sci., 26, 955–973, https://doi.org/10.5194/hess-26-955-2022, https://doi.org/10.5194/hess-26-955-2022, 2022
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This study investigates how the spatial nitrate reduction in the subsurface may shift under changing climate and land use conditions. This change is investigated by comparing maps showing the spatial nitrate reduction in an agricultural catchment for current conditions, with maps generated for future projected climate and land use conditions. Results show that future climate flow paths may shift the catchment reduction noticeably, while implications of land use changes were less substantial.
Wei Liu, Seonggyu Park, Ryan T. Bailey, Eugenio Molina-Navarro, Hans Estrup Andersen, Hans Thodsen, Anders Nielsen, Erik Jeppesen, Jacob Skødt Jensen, Jacob Birk Jensen, and Dennis Trolle
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-232, https://doi.org/10.5194/hess-2019-232, 2019
Manuscript not accepted for further review
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We compared the performance of SWAT and SWAT-MODFLOW and assessed the simulated streamflow signals in response to a range of groundwater abstraction scenarios for irrigation and drinking water. The SWAT-MODFLOW complex was further developed to enable the application of the Drain Package and an auto-irrigation routine. A PEST-based approach was developed to calibrate the coupled SWAT-MODFLOW. The SWAT-MODFLOW model produced more realistic results on groundwater abstraction effects on streamflow.
Matthew R. Hipsey, Louise C. Bruce, Casper Boon, Brendan Busch, Cayelan C. Carey, David P. Hamilton, Paul C. Hanson, Jordan S. Read, Eduardo de Sousa, Michael Weber, and Luke A. Winslow
Geosci. Model Dev., 12, 473–523, https://doi.org/10.5194/gmd-12-473-2019, https://doi.org/10.5194/gmd-12-473-2019, 2019
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The General Lake Model (GLM) has been developed to undertake simulation of a diverse range of wetlands, lakes, and reservoirs. The model supports the science needs of the Global Lake Ecological Observatory Network (GLEON), a network of lake sensors and researchers attempting to understand lake functioning and address questions about how lakes around the world vary in response to climate and land use change. The paper describes the science basis and application of the model.
Fenjuan Hu, Karsten Bolding, Jorn Bruggeman, Erik Jeppesen, Morgens R. Flindt, Luuk van Gerven, Jan H. Janse, Annette B. G. Janssen, Jan J. Kuiper, Wolf M. Mooij, and Dennis Trolle
Geosci. Model Dev., 9, 2271–2278, https://doi.org/10.5194/gmd-9-2271-2016, https://doi.org/10.5194/gmd-9-2271-2016, 2016
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We present a redesign and further development of a complex and well-known aquatic ecosystem model (PCLake) into the Framework for Aquatic Biogeochemical Models (FABM). So PCLake can run in different hydrodynamic environments, ranging from 0-D to 3-D. We introduce the methods and technical details about how the model was re-designed into a modular structure and the new features of PCLake enabled by FABM. We further present a benchmark test case to verify the new model implementation.
Jonathan M. Abell, David P. Hamilton, and Christopher G. McBride
Hydrol. Earth Syst. Sci., 20, 2395–2401, https://doi.org/10.5194/hess-20-2395-2016, https://doi.org/10.5194/hess-20-2395-2016, 2016
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We comment on "Using groundwater age and hydrochemistry to understand sources and dynamics of nutrient contamination through the catchment into Lake Rotorua, New Zealand" by Morgenstern et al. (2015). They propose that "the only effective way to limit algae blooms and improve lake water quality in such environments is by limiting the nitrate load". We outline four reasons why it is important to instead limit both phosphorus and nitrogen loads to this iconic lake, consistent with current policy.
Related subject area
Biogeosciences
The Permafrost and Organic LayEr module for Forest Models (POLE-FM) 1.0
CompLaB v1.0: a scalable pore-scale model for flow, biogeochemistry, microbial metabolism, and biofilm dynamics
Validation of a new spatially explicit process-based model (HETEROFOR) to simulate structurally and compositionally complex forest stands in eastern North America
Global agricultural ammonia emissions simulated with the ORCHIDEE land surface model
ForamEcoGEnIE 2.0: incorporating symbiosis and spine traits into a trait-based global planktic foraminiferal model
FABM-NflexPD 2.0: testing an instantaneous acclimation approach for modeling the implications of phytoplankton eco-physiology for the carbon and nutrient cycles
Evaluating the vegetation–atmosphere coupling strength of ORCHIDEE land surface model (v7266)
Non-Redfieldian carbon model for the Baltic Sea (ERGOM version 1.2) – implementation and budget estimates
Implementation of a new crop phenology and irrigation scheme in the ISBA land surface model using SURFEX_v8.1
Simulating long-term responses of soil organic matter turnover to substrate stoichiometry by abstracting fast and small-scale microbial processes: the Soil Enzyme Steady Allocation Model (SESAM; v3.0)
Modeling demographic-driven vegetation dynamics and ecosystem biogeochemical cycling in NASA GISS's Earth system model (ModelE-BiomeE v.1.0)
Forest fluxes and mortality response to drought: model description (ORCHIDEE-CAN-NHA r7236) and evaluation at the Caxiuanã drought experiment
Matrix representation of lateral soil movements: scaling and calibrating CE-DYNAM (v2) at a continental level
CANOPS-GRB v1.0: a new Earth system model for simulating the evolution of ocean–atmosphere chemistry over geologic timescales
Low sensitivity of three terrestrial biosphere models to soil texture over the South American tropics
FESDIA (v1.0): exploring temporal variations of sediment biogeochemistry under the influence of flood events using numerical modelling
Impact of changes in climate and CO2 on the carbon storage potential of vegetation under limited water availability using SEIB-DGVM version 3.02
Implementation of trait-based ozone plant sensitivity in the Yale Interactive terrestrial Biosphere model v1.0 to assess global vegetation damage
FORCCHN V2.0: an individual-based model for predicting multiscale forest carbon dynamics
Climate and parameter sensitivity and induced uncertainties in carbon stock projections for European forests (using LPJ-GUESS 4.0)
Modeling the role of livestock grazing in C and N cycling in grasslands with LPJmL5.0-grazing
Use of genetic algorithms for ocean model parameter optimisation: a case study using PISCES-v2_RC for North Atlantic particulate organic carbon
SurEau-Ecos v2.0: a trait-based plant hydraulics model for simulations of plant water status and drought-induced mortality at the ecosystem level
Improved representation of plant physiology in the JULES-vn5.6 land surface model: photosynthesis, stomatal conductance and thermal acclimation
Representation of the phosphorus cycle in the Joint UK Land Environment Simulator (vn5.5_JULES-CNP)
CLM5-FruitTree: a new sub-model for deciduous fruit trees in the Community Land Model (CLM5)
The impact of hurricane disturbances on a tropical forest: implementing a palm plant functional type and hurricane disturbance module in ED2-HuDi V1.0
A validation standard for area of habitat maps for terrestrial birds and mammals
Soil Cycles of Elements simulator for Predicting TERrestrial regulation of greenhouse gases: SCEPTER v0.9
Using terrestrial laser scanning to constrain forest ecosystem structure and functions in the Ecosystem Demography model (ED2.2)
A map of global peatland extent created using machine learning (Peat-ML)
Implementation and evaluation of the unified stomatal optimization approach in the Functionally Assembled Terrestrial Ecosystem Simulator (FATES)
ECOSMO II(CHL): a marine biogeochemical model for the North Atlantic and the Arctic
Water Ecosystems Tool (WET) 1.0 – a new generation of flexible aquatic ecosystem model
Development of an open-source regional data assimilation system in PEcAn v. 1.7.2: application to carbon cycle reanalysis across the contiguous US using SIPNET
Predicting global terrestrial biomes with the LeNet convolutional neural network
KGML-ag: a modeling framework of knowledge-guided machine learning to simulate agroecosystems: a case study of estimating N2O emission using data from mesocosm experiments
Assessing methane emissions for northern peatlands in ORCHIDEE-PEAT revision 7020
A dynamic local-scale vegetation model for lycopsids (LYCOm v1.0)
Soil-related developments of the Biome-BGCMuSo v6.2 terrestrial ecosystem model
Global evaluation of the Ecosystem Demography model (ED v3.0)
A new snow module improves predictions of the isotope-enabled MAIDENiso forest growth model
Calibrating the soil organic carbon model Yasso20 with multiple datasets
The PFLOTRAN Reaction Sandbox
A new approach to simulate peat accumulation, degradation and stability in a global land surface scheme (JULES vn5.8_accumulate_soil) for northern and temperate peatlands
Definitions and methods to estimate regional land carbon fluxes for the second phase of the REgional Carbon Cycle Assessment and Processes Project (RECCAP-2)
Locating trees to mitigate outdoor radiant load of humans in urban areas using a metaheuristic hill-climbing algorithm – introducing TreePlanter v1.0
Sensitivity of asymmetric oxygen minimum zones to mixing intensity and stoichiometry in the tropical Pacific using a basin-scale model (OGCM-DMEC V1.4)
The importance of turbulent ocean–sea ice nutrient exchanges for simulation of ice algal biomass and production with CICE6.1 and Icepack 1.2
Modeling symbiotic biological nitrogen fixation in grain legumes globally with LPJ-GUESS (v4.0, r10285)
Winslow D. Hansen, Adrianna Foster, Benjamin Gaglioti, Rupert Seidl, and Werner Rammer
Geosci. Model Dev., 16, 2011–2036, https://doi.org/10.5194/gmd-16-2011-2023, https://doi.org/10.5194/gmd-16-2011-2023, 2023
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Permafrost and the thick soil-surface organic layers that insulate permafrost are important controls of boreal forest dynamics and carbon cycling. However, both are rarely included in process-based vegetation models used to simulate future ecosystem trajectories. To address this challenge, we developed a computationally efficient permafrost and soil organic layer module that operates at fine spatial (1 ha) and temporal (daily) resolutions.
Heewon Jung, Hyun-Seob Song, and Christof Meile
Geosci. Model Dev., 16, 1683–1696, https://doi.org/10.5194/gmd-16-1683-2023, https://doi.org/10.5194/gmd-16-1683-2023, 2023
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Microbial activity responsible for many chemical transformations depends on environmental conditions. These can vary locally, e.g., between poorly connected pores in porous media. We present a modeling framework that resolves such small spatial scales explicitly, accounts for feedback between transport and biogeochemical conditions, and can integrate state-of-the-art representations of microbes in a computationally efficient way, making it broadly applicable in science and engineering use cases.
Arthur Guignabert, Quentin Ponette, Frédéric André, Christian Messier, Philippe Nolet, and Mathieu Jonard
Geosci. Model Dev., 16, 1661–1682, https://doi.org/10.5194/gmd-16-1661-2023, https://doi.org/10.5194/gmd-16-1661-2023, 2023
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Spatially explicit and process-based models are useful to test innovative forestry practices under changing and uncertain conditions. However, their larger use is often limited by the restricted range of species and stand structures they can reliably account for. We therefore calibrated and evaluated such a model, HETEROFOR, for 23 species across southern Québec. Our results showed that the model is robust and can predict accurately both individual tree growth and stand dynamics in this region.
Maureen Beaudor, Nicolas Vuichard, Juliette Lathière, Nikolaos Evangeliou, Martin Van Damme, Lieven Clarisse, and Didier Hauglustaine
Geosci. Model Dev., 16, 1053–1081, https://doi.org/10.5194/gmd-16-1053-2023, https://doi.org/10.5194/gmd-16-1053-2023, 2023
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Ammonia mainly comes from the agricultural sector, and its volatilization relies on environmental variables. Our approach aims at benefiting from an Earth system model framework to estimate it. By doing so, we represent a consistent spatial distribution of the emissions' response to environmental changes.
We greatly improved the seasonal cycle of emissions compared with previous work. In addition, our model includes natural soil emissions (that are rarely represented in modeling approaches).
Rui Ying, Fanny M. Monteiro, Jamie D. Wilson, and Daniela N. Schmidt
Geosci. Model Dev., 16, 813–832, https://doi.org/10.5194/gmd-16-813-2023, https://doi.org/10.5194/gmd-16-813-2023, 2023
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Planktic foraminifera are marine-calcifying zooplankton; their shells are widely used to measure past temperature and productivity. We developed ForamEcoGEnIE 2.0 to simulate the four subgroups of this organism. We found that the relative abundance distribution agrees with marine sediment core-top data and that carbon export and biomass are close to sediment trap and plankton net observations respectively. This model provides the opportunity to study foraminiferal ecology in any geological era.
Onur Kerimoglu, Markus Pahlow, Prima Anugerahanti, and Sherwood Lan Smith
Geosci. Model Dev., 16, 95–108, https://doi.org/10.5194/gmd-16-95-2023, https://doi.org/10.5194/gmd-16-95-2023, 2023
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In classical models that track the changes in the elemental composition of phytoplankton, additional state variables are required for each element resolved. In this study, we show how the behavior of such an explicit model can be approximated using an
instantaneous acclimationapproach, in which the elemental composition of the phytoplankton is assumed to adjust to an optimal value instantaneously. Through rigorous tests, we evaluate the consistency of this scheme.
Yuan Zhang, Devaraju Narayanappa, Philippe Ciais, Wei Li, Daniel Goll, Nicolas Vuichard, Martin G. De Kauwe, Laurent Li, and Fabienne Maignan
Geosci. Model Dev., 15, 9111–9125, https://doi.org/10.5194/gmd-15-9111-2022, https://doi.org/10.5194/gmd-15-9111-2022, 2022
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There are a few studies to examine if current models correctly represented the complex processes of transpiration. Here, we use a coefficient Ω, which indicates if transpiration is mainly controlled by vegetation processes or by turbulence, to evaluate the ORCHIDEE model. We found a good performance of ORCHIDEE, but due to compensation of biases in different processes, we also identified how different factors control Ω and where the model is wrong. Our method is generic to evaluate other models.
Thomas Neumann, Hagen Radtke, Bronwyn Cahill, Martin Schmidt, and Gregor Rehder
Geosci. Model Dev., 15, 8473–8540, https://doi.org/10.5194/gmd-15-8473-2022, https://doi.org/10.5194/gmd-15-8473-2022, 2022
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Marine ecosystem models are usually constrained by the elements nitrogen and phosphorus and consider carbon in organic matter in a fixed ratio. Recent observations show a substantial deviation from the simulated carbon cycle variables. In this study, we present a marine ecosystem model for the Baltic Sea which allows for a flexible uptake ratio for carbon, nitrogen, and phosphorus. With this extension, the model reflects much more reasonable variables of the marine carbon cycle.
Arsène Druel, Simon Munier, Anthony Mucia, Clément Albergel, and Jean-Christophe Calvet
Geosci. Model Dev., 15, 8453–8471, https://doi.org/10.5194/gmd-15-8453-2022, https://doi.org/10.5194/gmd-15-8453-2022, 2022
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Crop phenology and irrigation is implemented into a land surface model able to work at a global scale. A case study is presented over Nebraska (USA). Simulations with and without the new scheme are compared to different satellite-based observations. The model is able to produce a realistic yearly irrigation water amount. The irrigation scheme improves the simulated leaf area index, gross primary productivity, evapotransipiration, and land surface temperature.
Thomas Wutzler, Lin Yu, Marion Schrumpf, and Sönke Zaehle
Geosci. Model Dev., 15, 8377–8393, https://doi.org/10.5194/gmd-15-8377-2022, https://doi.org/10.5194/gmd-15-8377-2022, 2022
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Soil microbes process soil organic matter and affect carbon storage and plant nutrition at the ecosystem scale. We hypothesized that decadal dynamics is constrained by the ratios of elements in litter inputs, microbes, and matter and that microbial community optimizes growth. This allowed the SESAM model to descibe decadal-term carbon sequestration in soils and other biogeochemical processes explicitly accounting for microbial processes but without its problematic fine-scale parameterization.
Ensheng Weng, Igor Aleinov, Ram Singh, Michael J. Puma, Sonali S. McDermid, Nancy Y. Kiang, Maxwell Kelley, Kevin Wilcox, Ray Dybzinski, Caroline E. Farrior, Stephen W. Pacala, and Benjamin I. Cook
Geosci. Model Dev., 15, 8153–8180, https://doi.org/10.5194/gmd-15-8153-2022, https://doi.org/10.5194/gmd-15-8153-2022, 2022
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We develop a demographic vegetation model to improve the representation of terrestrial vegetation dynamics and ecosystem biogeochemical cycles in the Goddard Institute for Space Studies ModelE. The individual-based competition for light and soil resources makes the modeling of eco-evolutionary optimality possible. This model will enable ModelE to simulate long-term biogeophysical and biogeochemical feedbacks between the climate system and land ecosystems at decadal to centurial temporal scales.
Yitong Yao, Emilie Joetzjer, Philippe Ciais, Nicolas Viovy, Fabio Cresto Aleina, Jerome Chave, Lawren Sack, Megan Bartlett, Patrick Meir, Rosie Fisher, and Sebastiaan Luyssaert
Geosci. Model Dev., 15, 7809–7833, https://doi.org/10.5194/gmd-15-7809-2022, https://doi.org/10.5194/gmd-15-7809-2022, 2022
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To facilitate more mechanistic modeling of drought effects on forest dynamics, our study implements a hydraulic module to simulate the vertical water flow, change in water storage and percentage loss of stem conductance (PLC). With the relationship between PLC and tree mortality, our model can successfully reproduce the large biomass drop observed under throughfall exclusion. Our hydraulic module provides promising avenues benefiting the prediction for mortality under future drought events.
Arthur Nicolaus Fendrich, Philippe Ciais, Emanuele Lugato, Marco Carozzi, Bertrand Guenet, Pasquale Borrelli, Victoria Naipal, Matthew McGrath, Philippe Martin, and Panos Panagos
Geosci. Model Dev., 15, 7835–7857, https://doi.org/10.5194/gmd-15-7835-2022, https://doi.org/10.5194/gmd-15-7835-2022, 2022
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Currently, spatially explicit models for soil carbon stock can simulate the impacts of several changes. However, they do not incorporate the erosion, lateral transport, and deposition (ETD) of soil material. The present work developed ETD formulation, illustrated model calibration and validation for Europe, and presented the results for a depositional site. We expect that our work advances ETD models' description and facilitates their reproduction and incorporation in land surface models.
Kazumi Ozaki, Devon B. Cole, Christopher T. Reinhard, and Eiichi Tajika
Geosci. Model Dev., 15, 7593–7639, https://doi.org/10.5194/gmd-15-7593-2022, https://doi.org/10.5194/gmd-15-7593-2022, 2022
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A new biogeochemical model (CANOPS-GRB v1.0) for assessing the redox stability and dynamics of the ocean–atmosphere system on geologic timescales has been developed. In this paper, we present a full description of the model and its performance. CANOPS-GRB is a useful tool for understanding the factors regulating atmospheric O2 level and has the potential to greatly refine our current understanding of Earth's oxygenation history.
Félicien Meunier, Wim Verbruggen, Hans Verbeeck, and Marc Peaucelle
Geosci. Model Dev., 15, 7573–7591, https://doi.org/10.5194/gmd-15-7573-2022, https://doi.org/10.5194/gmd-15-7573-2022, 2022
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Drought stress occurs in plants when water supply (i.e. root water uptake) is lower than the water demand (i.e. atmospheric demand). It is strongly related to soil properties and expected to increase in intensity and frequency in the tropics due to climate change. In this study, we show that contrary to the expectations, state-of-the-art terrestrial biosphere models are mostly insensitive to soil texture and hence probably inadequate to reproduce in silico the plant water status in drying soils.
Stanley I. Nmor, Eric Viollier, Lucie Pastor, Bruno Lansard, Christophe Rabouille, and Karline Soetaert
Geosci. Model Dev., 15, 7325–7351, https://doi.org/10.5194/gmd-15-7325-2022, https://doi.org/10.5194/gmd-15-7325-2022, 2022
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The coastal marine environment serves as a transition zone in the land–ocean continuum and is susceptible to episodic phenomena such as flash floods, which cause massive organic matter deposition. Here, we present a model of sediment early diagenesis that explicitly describes this type of deposition while also incorporating unique flood deposit characteristics. This model can be used to investigate the temporal evolution of marine sediments following abrupt changes in environmental conditions.
Shanlin Tong, Weiguang Wang, Jie Chen, Chong-Yu Xu, Hisashi Sato, and Guoqing Wang
Geosci. Model Dev., 15, 7075–7098, https://doi.org/10.5194/gmd-15-7075-2022, https://doi.org/10.5194/gmd-15-7075-2022, 2022
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Plant carbon storage potential is central to moderate atmospheric CO2 concentration buildup and mitigation of climate change. There is an ongoing debate about the main driver of carbon storage. To reconcile this discrepancy, we use SEIB-DGVM to investigate the trend and response mechanism of carbon stock fractions among water limitation regions. Results show that the impact of CO2 and temperature on carbon stock depends on water limitation, offering a new perspective on carbon–water coupling.
Yimian Ma, Xu Yue, Stephen Sitch, Nadine Unger, Johan Uddling, Lina Mercado, Cheng Gong, Zhaozhong Feng, Huiyi Yang, Hao Zhou, Chenguang Tian, Yang Cao, Yadong Lei, Alexander Cheesman, Yansen Xu, and Maria Duran Rojas
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-227, https://doi.org/10.5194/gmd-2022-227, 2022
Revised manuscript accepted for GMD
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Plants have been found to respond differently to O3, but the variations in the sensitivities have rarely been explained, neither fully implemented in large scale assessment. This study proposes a new O3 damage scheme with leaf mass per area to unify varied sensitivities for all plant species. Our assessment reveals an O3-induced reduction of 4.8 % in global GPP with the highest reduction of >10 % for cropland, suggesting an emerging risk of crop yield loss under the threat of O3 pollution.
Jing Fang, Herman H. Shugart, Feng Liu, Xiaodong Yan, Yunkun Song, and Fucheng Lv
Geosci. Model Dev., 15, 6863–6872, https://doi.org/10.5194/gmd-15-6863-2022, https://doi.org/10.5194/gmd-15-6863-2022, 2022
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Our study provided a detailed description and a package of an individual tree-based carbon model, FORCCHN2. This model used non-structural carbohydrate (NSC) pools to couple tree growth and phenology. The model could reproduce daily carbon fluxes across Northern Hemisphere forests. Given the potential importance of the application of this model, there is substantial scope for using FORCCHN2 in fields as diverse as forest ecology, climate change, and carbon estimation.
Johannes Oberpriller, Christine Herschlein, Peter Anthoni, Almut Arneth, Andreas Krause, Anja Rammig, Mats Lindeskog, Stefan Olin, and Florian Hartig
Geosci. Model Dev., 15, 6495–6519, https://doi.org/10.5194/gmd-15-6495-2022, https://doi.org/10.5194/gmd-15-6495-2022, 2022
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Understanding uncertainties of projected ecosystem dynamics under environmental change is of immense value for research and climate change policy. Here, we analyzed these across European forests. We find that uncertainties are dominantly induced by parameters related to water, mortality, and climate, with an increasing importance of climate from north to south. These results highlight that climate not only contributes uncertainty but also modifies uncertainties in other ecosystem processes.
Jens Heinke, Susanne Rolinski, and Christoph Müller
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-176, https://doi.org/10.5194/gmd-2022-176, 2022
Revised manuscript accepted for GMD
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We develop a livestock module for the global vegetation model LPJmL5.0 to simulate the impact of grazing dairy cattle on carbon and nitrogen cycles in grasslands. A novelty of the approach is that it accounts for the effect of feed quality on feed uptake and feed utilisation by animals. The portioning of dietary nitrogen into milk, feces, and urine shows very good agreement with estimates obtained from animal trials.
Marcus Falls, Raffaele Bernardello, Miguel Castrillo, Mario Acosta, Joan Llort, and Martí Galí
Geosci. Model Dev., 15, 5713–5737, https://doi.org/10.5194/gmd-15-5713-2022, https://doi.org/10.5194/gmd-15-5713-2022, 2022
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This paper describes and tests a method which uses a genetic algorithm (GA), a type of optimisation algorithm, on an ocean biogeochemical model. The aim is to produce a set of numerical parameters that best reflect the observed data of particulate organic carbon in a specific region of the ocean. We show that the GA can provide optimised model parameters in a robust and efficient manner and can also help detect model limitations, ultimately leading to a reduction in the model uncertainties.
Julien Ruffault, François Pimont, Hervé Cochard, Jean-Luc Dupuy, and Nicolas Martin-StPaul
Geosci. Model Dev., 15, 5593–5626, https://doi.org/10.5194/gmd-15-5593-2022, https://doi.org/10.5194/gmd-15-5593-2022, 2022
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A widespread increase in tree mortality has been observed around the globe, and this trend is likely to continue because of ongoing climate change. Here we present SurEau-Ecos, a trait-based plant hydraulic model to predict tree desiccation and mortality. SurEau-Ecos can help determine the areas and ecosystems that are most vulnerable to drying conditions.
Rebecca J. Oliver, Lina M. Mercado, Doug B. Clark, Chris Huntingford, Christopher M. Taylor, Pier Luigi Vidale, Patrick C. McGuire, Markus Todt, Sonja Folwell, Valiyaveetil Shamsudheen Semeena, and Belinda E. Medlyn
Geosci. Model Dev., 15, 5567–5592, https://doi.org/10.5194/gmd-15-5567-2022, https://doi.org/10.5194/gmd-15-5567-2022, 2022
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We introduce new representations of plant physiological processes into a land surface model. Including new biological understanding improves modelled carbon and water fluxes for the present in tropical and northern-latitude forests. Future climate simulations demonstrate the sensitivity of photosynthesis to temperature is important for modelling carbon cycle dynamics in a warming world. Accurate representation of these processes in models is necessary for robust predictions of climate change.
Mahdi André Nakhavali, Lina M. Mercado, Iain P. Hartley, Stephen Sitch, Fernanda V. Cunha, Raffaello di Ponzio, Laynara F. Lugli, Carlos A. Quesada, Kelly M. Andersen, Sarah E. Chadburn, Andy J. Wiltshire, Douglas B. Clark, Gyovanni Ribeiro, Lara Siebert, Anna C. M. Moraes, Jéssica Schmeisk Rosa, Rafael Assis, and José L. Camargo
Geosci. Model Dev., 15, 5241–5269, https://doi.org/10.5194/gmd-15-5241-2022, https://doi.org/10.5194/gmd-15-5241-2022, 2022
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In tropical ecosystems, the availability of rock-derived elements such as P can be very low. Thus, without a representation of P cycling, tropical forest responses to rising atmospheric CO2 conditions in areas such as Amazonia remain highly uncertain. We introduced P dynamics and its interactions with the N and P cycles into the JULES model. Our results highlight the potential for high P limitation and therefore lower CO2 fertilization capacity in the Amazon forest with low-fertility soils.
Olga Dombrowski, Cosimo Brogi, Harrie-Jan Hendricks Franssen, Damiano Zanotelli, and Heye Bogena
Geosci. Model Dev., 15, 5167–5193, https://doi.org/10.5194/gmd-15-5167-2022, https://doi.org/10.5194/gmd-15-5167-2022, 2022
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Soil carbon storage and food production of fruit orchards will be influenced by climate change. However, they lack representation in models that study such processes. We developed and tested a new sub-model, CLM5-FruitTree, that describes growth, biomass distribution, and management practices in orchards. The model satisfactorily predicted yield and exchange of carbon, energy, and water in an apple orchard and can be used to study land surface processes in fruit orchards at different scales.
Jiaying Zhang, Rafael L. Bras, Marcos Longo, and Tamara Heartsill Scalley
Geosci. Model Dev., 15, 5107–5126, https://doi.org/10.5194/gmd-15-5107-2022, https://doi.org/10.5194/gmd-15-5107-2022, 2022
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We implemented hurricane disturbance in a vegetation dynamics model and calibrated the model with observations of a tropical forest. We used the model to study forest recovery from hurricane disturbance and found that a single hurricane disturbance enhances AGB and BA in the long term compared with a no-hurricane situation. The model developed and results presented in this study can be utilized to understand the impact of hurricane disturbances on forest recovery under the changing climate.
Prabhat Raj Dahal, Maria Lumbierres, Stuart H. M. Butchart, Paul F. Donald, and Carlo Rondinini
Geosci. Model Dev., 15, 5093–5105, https://doi.org/10.5194/gmd-15-5093-2022, https://doi.org/10.5194/gmd-15-5093-2022, 2022
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This paper describes the validation of area of habitat (AOH) maps produced for terrestrial birds and mammals. The main objective was to assess the accuracy of the maps based on independent data. We used open access data from repositories, such as ebird and gbif to check if our maps were a better reflection of species' distribution than random. When points were not available we used logistic models to validate the AOH maps. The majority of AOH maps were found to have a high accuracy.
Yoshiki Kanzaki, Shuang Zhang, Noah J. Planavsky, and Christopher T. Reinhard
Geosci. Model Dev., 15, 4959–4990, https://doi.org/10.5194/gmd-15-4959-2022, https://doi.org/10.5194/gmd-15-4959-2022, 2022
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Increasing carbon dioxide in the atmosphere is an urgent issue in the coming century. Enhanced rock weathering in soils can be one of the most efficient C capture strategies. On the basis as a weathering simulator, the newly developed SCEPTER model implements bio-mixing by fauna/humans and enables organic matter and crushed rocks/minerals at the soil surface with an option to track their particle size distributions. Those features can be useful for evaluating the carbon capture efficiency.
Félicien Meunier, Sruthi M. Krishna Moorthy, Marc Peaucelle, Kim Calders, Louise Terryn, Wim Verbruggen, Chang Liu, Ninni Saarinen, Niall Origo, Joanne Nightingale, Mathias Disney, Yadvinder Malhi, and Hans Verbeeck
Geosci. Model Dev., 15, 4783–4803, https://doi.org/10.5194/gmd-15-4783-2022, https://doi.org/10.5194/gmd-15-4783-2022, 2022
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We integrated state-of-the-art observations of the structure of the vegetation in a temperate forest to constrain a vegetation model that aims to reproduce such an ecosystem in silico. We showed that the use of this information helps to constrain the model structure, its critical parameters, as well as its initial state. This research confirms the critical importance of the representation of the vegetation structure in vegetation models and proposes a method to overcome this challenge.
Joe R. Melton, Ed Chan, Koreen Millard, Matthew Fortier, R. Scott Winton, Javier M. Martín-López, Hinsby Cadillo-Quiroz, Darren Kidd, and Louis V. Verchot
Geosci. Model Dev., 15, 4709–4738, https://doi.org/10.5194/gmd-15-4709-2022, https://doi.org/10.5194/gmd-15-4709-2022, 2022
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Peat-ML is a high-resolution global peatland extent map generated using machine learning techniques. Peatlands are important in the global carbon and water cycles, but their extent is poorly known. We generated Peat-ML using drivers of peatland formation including climate, soil, geomorphology, and vegetation data, and we train the model with regional peatland maps. Our accuracy estimation approaches suggest Peat-ML is of similar or higher quality than other available peatland mapping products.
Qianyu Li, Shawn P. Serbin, Julien Lamour, Kenneth J. Davidson, Kim S. Ely, and Alistair Rogers
Geosci. Model Dev., 15, 4313–4329, https://doi.org/10.5194/gmd-15-4313-2022, https://doi.org/10.5194/gmd-15-4313-2022, 2022
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Stomatal conductance is the rate of water release from leaves’ pores. We implemented an optimal stomatal conductance model in a vegetation model. We then tested and compared it with the existing empirical model in terms of model responses to key environmental variables. We also evaluated the model with measurements at a tropical forest site. Our study suggests that the parameterization of conductance models and current model response to drought are the critical areas for improving models.
Veli Çağlar Yumruktepe, Annette Samuelsen, and Ute Daewel
Geosci. Model Dev., 15, 3901–3921, https://doi.org/10.5194/gmd-15-3901-2022, https://doi.org/10.5194/gmd-15-3901-2022, 2022
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We describe the coupled bio-physical model ECOSMO II(CHL), which is used for regional configurations for the North Atlantic and the Arctic hind-casting and operational purposes. The model is consistent with the large-scale climatological nutrient settings and is capable of representing regional and seasonal changes, and model primary production agrees with previous measurements. For the users of this model, this paper provides the underlying science, model evaluation and its development.
Nicolas Azaña Schnedler-Meyer, Tobias Kuhlmann Andersen, Fenjuan Rose Schmidt Hu, Karsten Bolding, Anders Nielsen, and Dennis Trolle
Geosci. Model Dev., 15, 3861–3878, https://doi.org/10.5194/gmd-15-3861-2022, https://doi.org/10.5194/gmd-15-3861-2022, 2022
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We present the Water Ecosystems Tool (WET) – a new modular aquatic ecosystem model configurable to a wide array of physical setups, ecosystems and research questions based on the popular FABM–PCLake model. We aim for the model to become a community staple, thus helping to consolidate the state of the art under a few flexible models, with the aim of improving comparability across studies and preventing the
re-inventions of the wheelthat are common to our scientific modeling community.
Hamze Dokoohaki, Bailey D. Morrison, Ann Raiho, Shawn P. Serbin, Katie Zarada, Luke Dramko, and Michael Dietze
Geosci. Model Dev., 15, 3233–3252, https://doi.org/10.5194/gmd-15-3233-2022, https://doi.org/10.5194/gmd-15-3233-2022, 2022
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We present a new terrestrial carbon cycle data assimilation system, built on the PEcAn model–data eco-informatics system, and its application for the development of a proof-of-concept carbon
reanalysisproduct that harmonizes carbon pools (leaf, wood, soil) and fluxes (GPP, Ra, Rh, NEE) across the contiguous United States from 1986–2019. Here, we build on a decade of work on uncertainty propagation to generate the most complete and robust uncertainty accounting available to date.
Hisashi Sato and Takeshi Ise
Geosci. Model Dev., 15, 3121–3132, https://doi.org/10.5194/gmd-15-3121-2022, https://doi.org/10.5194/gmd-15-3121-2022, 2022
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Accurately predicting global coverage of terrestrial biome is one of the earliest ecological concerns, and many empirical schemes have been proposed to characterize their relationship. Here, we demonstrate an accurate and practical method to construct empirical models for operational biome mapping via a convolutional neural network (CNN) approach.
Licheng Liu, Shaoming Xu, Jinyun Tang, Kaiyu Guan, Timothy J. Griffis, Matthew D. Erickson, Alexander L. Frie, Xiaowei Jia, Taegon Kim, Lee T. Miller, Bin Peng, Shaowei Wu, Yufeng Yang, Wang Zhou, Vipin Kumar, and Zhenong Jin
Geosci. Model Dev., 15, 2839–2858, https://doi.org/10.5194/gmd-15-2839-2022, https://doi.org/10.5194/gmd-15-2839-2022, 2022
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By incorporating the domain knowledge into a machine learning model, KGML-ag overcomes the well-known limitations of process-based models due to insufficient representations and constraints, and unlocks the “black box” of machine learning models. Therefore, KGML-ag can outperform existing approaches on capturing the hot moment and complex dynamics of N2O flux. This study will be a critical reference for the new generation of modeling paradigm for biogeochemistry and other geoscience processes.
Elodie Salmon, Fabrice Jégou, Bertrand Guenet, Line Jourdain, Chunjing Qiu, Vladislav Bastrikov, Christophe Guimbaud, Dan Zhu, Philippe Ciais, Philippe Peylin, Sébastien Gogo, Fatima Laggoun-Défarge, Mika Aurela, M. Syndonia Bret-Harte, Jiquan Chen, Bogdan H. Chojnicki, Housen Chu, Colin W. Edgar, Eugenie S. Euskirchen, Lawrence B. Flanagan, Krzysztof Fortuniak, David Holl, Janina Klatt, Olaf Kolle, Natalia Kowalska, Lars Kutzbach, Annalea Lohila, Lutz Merbold, Włodzimierz Pawlak, Torsten Sachs, and Klaudia Ziemblińska
Geosci. Model Dev., 15, 2813–2838, https://doi.org/10.5194/gmd-15-2813-2022, https://doi.org/10.5194/gmd-15-2813-2022, 2022
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A methane model that features methane production and transport by plants, the ebullition process and diffusion in soil, oxidation to CO2, and CH4 fluxes to the atmosphere has been embedded in the ORCHIDEE-PEAT land surface model, which includes an explicit representation of northern peatlands. This model, ORCHIDEE-PCH4, was calibrated and evaluated on 14 peatland sites. Results show that the model is sensitive to temperature and substrate availability over the top 75 cm of soil depth.
Suman Halder, Susanne K. M. Arens, Kai Jensen, Tais W. Dahl, and Philipp Porada
Geosci. Model Dev., 15, 2325–2343, https://doi.org/10.5194/gmd-15-2325-2022, https://doi.org/10.5194/gmd-15-2325-2022, 2022
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A dynamic vegetation model, designed to estimate potential impacts of early vascular vegetation, namely, lycopsids, on the biogeochemical cycle at a local scale. Lycopsid Model (LYCOm) estimates the productivity and physiological properties of lycopsids across a broad climatic range along with natural selection, which is then utilized to adjudge their weathering potential. It lays the foundation for estimation of their impacts during their long evolutionary history starting from the Ordovician.
Dóra Hidy, Zoltán Barcza, Roland Hollós, Laura Dobor, Tamás Ács, Dóra Zacháry, Tibor Filep, László Pásztor, Dóra Incze, Márton Dencső, Eszter Tóth, Katarína Merganičová, Peter Thornton, Steven Running, and Nándor Fodor
Geosci. Model Dev., 15, 2157–2181, https://doi.org/10.5194/gmd-15-2157-2022, https://doi.org/10.5194/gmd-15-2157-2022, 2022
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Biogeochemical models used by the scientific community can support society in the quantification of the expected environmental impacts caused by global climate change. The Biome-BGCMuSo v6.2 biogeochemical model has been created by implementing a lot of developments related to soil hydrology as well as the soil carbon and nitrogen cycle and by integrating crop model components. Detailed descriptions of developments with case studies are presented in this paper.
Lei Ma, George Hurtt, Lesley Ott, Ritvik Sahajpal, Justin Fisk, Rachel Lamb, Hao Tang, Steve Flanagan, Louise Chini, Abhishek Chatterjee, and Joseph Sullivan
Geosci. Model Dev., 15, 1971–1994, https://doi.org/10.5194/gmd-15-1971-2022, https://doi.org/10.5194/gmd-15-1971-2022, 2022
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We present a global version of the Ecosystem Demography (ED) model which can track vegetation 3-D structure and scale up ecological processes from individual vegetation to ecosystem scale. Model evaluation against multiple benchmarking datasets demonstrated the model’s capability to simulate global vegetation dynamics across a range of temporal and spatial scales. With this version, ED has the potential to be linked with remote sensing observations to address key scientific questions.
Ignacio Hermoso de Mendoza, Etienne Boucher, Fabio Gennaretti, Aliénor Lavergne, Robert Field, and Laia Andreu-Hayles
Geosci. Model Dev., 15, 1931–1952, https://doi.org/10.5194/gmd-15-1931-2022, https://doi.org/10.5194/gmd-15-1931-2022, 2022
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We modify the numerical model of forest growth MAIDENiso by explicitly simulating snow. This allows us to use the model in boreal environments, where snow is dominant. We tested the performance of the model before and after adding snow, using it at two Canadian sites to simulate tree-ring isotopes and comparing with local observations. We found that modelling snow improves significantly the simulation of the hydrological cycle, the plausibility of the model and the simulated isotopes.
Toni Viskari, Janne Pusa, Istem Fer, Anna Repo, Julius Vira, and Jari Liski
Geosci. Model Dev., 15, 1735–1752, https://doi.org/10.5194/gmd-15-1735-2022, https://doi.org/10.5194/gmd-15-1735-2022, 2022
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We wanted to examine how the chosen measurement data and calibration process affect soil organic carbon model calibration. In our results we found that there is a benefit in using data from multiple litter-bag decomposition experiments simultaneously, even with the required assumptions. Additionally, due to the amount of noise and uncertainties in the system, more advanced calibration methods should be used to parameterize the models.
Glenn E. Hammond
Geosci. Model Dev., 15, 1659–1676, https://doi.org/10.5194/gmd-15-1659-2022, https://doi.org/10.5194/gmd-15-1659-2022, 2022
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This paper describes a simplified interface for implementing and testing new chemical reactions within the reactive transport simulator PFLOTRAN. The paper describes the interface, providing example code for the interface. The paper includes several chemical reactions implemented through the interface.
Sarah E. Chadburn, Eleanor J. Burke, Angela V. Gallego-Sala, Noah D. Smith, M. Syndonia Bret-Harte, Dan J. Charman, Julia Drewer, Colin W. Edgar, Eugenie S. Euskirchen, Krzysztof Fortuniak, Yao Gao, Mahdi Nakhavali, Włodzimierz Pawlak, Edward A. G. Schuur, and Sebastian Westermann
Geosci. Model Dev., 15, 1633–1657, https://doi.org/10.5194/gmd-15-1633-2022, https://doi.org/10.5194/gmd-15-1633-2022, 2022
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We present a new method to include peatlands in an Earth system model (ESM). Peatlands store huge amounts of carbon that accumulates very slowly but that can be rapidly destabilised, emitting greenhouse gases. Our model captures the dynamic nature of peat by simulating the change in surface height and physical properties of the soil as carbon is added or decomposed. Thus, we model, for the first time in an ESM, peat dynamics and its threshold behaviours that can lead to destabilisation.
Philippe Ciais, Ana Bastos, Frédéric Chevallier, Ronny Lauerwald, Ben Poulter, Josep G. Canadell, Gustaf Hugelius, Robert B. Jackson, Atul Jain, Matthew Jones, Masayuki Kondo, Ingrid T. Luijkx, Prabir K. Patra, Wouter Peters, Julia Pongratz, Ana Maria Roxana Petrescu, Shilong Piao, Chunjing Qiu, Celso Von Randow, Pierre Regnier, Marielle Saunois, Robert Scholes, Anatoly Shvidenko, Hanqin Tian, Hui Yang, Xuhui Wang, and Bo Zheng
Geosci. Model Dev., 15, 1289–1316, https://doi.org/10.5194/gmd-15-1289-2022, https://doi.org/10.5194/gmd-15-1289-2022, 2022
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The second phase of the Regional Carbon Cycle Assessment and Processes (RECCAP) will provide updated quantification and process understanding of CO2, CH4, and N2O emissions and sinks for ten regions of the globe. In this paper, we give definitions, review different methods, and make recommendations for estimating different components of the total land–atmosphere carbon exchange for each region in a consistent and complete approach.
Nils Wallenberg, Fredrik Lindberg, and David Rayner
Geosci. Model Dev., 15, 1107–1128, https://doi.org/10.5194/gmd-15-1107-2022, https://doi.org/10.5194/gmd-15-1107-2022, 2022
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Exposure to solar radiation on clear and warm days can lead to heat stress and thermal discomfort. This can be alleviated by planting trees providing shade in particularly warm areas. Here, we use a model to locate trees and optimize their blocking of solar radiation. Our results show that locations can differ depending, e.g., tree size (juvenile or mature) and number of trees that are positioned simultaneously. The model is available as a tool for accessibility by researchers and others.
Kai Wang, Xiujun Wang, Raghu Murtugudde, Dongxiao Zhang, and Rong-Hua Zhang
Geosci. Model Dev., 15, 1017–1035, https://doi.org/10.5194/gmd-15-1017-2022, https://doi.org/10.5194/gmd-15-1017-2022, 2022
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We use observational data of dissolved oxygen (DO) and organic nitrogen to calibrate a basin-scale model (OGCM-DEMC V1.4) and then evaluate model capacity for simulating mid-depth DO in the tropical Pacific. Sensitivity studies show that enhanced vertical mixing combined with reduced biological consumption performs well in reproducing asymmetric oxygen minimum zones (OMZs). We find that DO is more sensitive to biological processes in the upper OMZs but to physical processes in the lower OMZs.
Pedro Duarte, Philipp Assmy, Karley Campbell, and Arild Sundfjord
Geosci. Model Dev., 15, 841–857, https://doi.org/10.5194/gmd-15-841-2022, https://doi.org/10.5194/gmd-15-841-2022, 2022
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Sea ice modeling is an important part of Earth system models (ESMs). The results of ESMs are used by the Intergovernmental Panel on Climate Change in their reports. In this study we present an improvement to calculate the exchange of nutrients between the ocean and the sea ice. This nutrient exchange is an essential process to keep the ice-associated ecosystem functioning. We found out that previous calculation methods may underestimate the primary production of the ice-associated ecosystem.
Jianyong Ma, Stefan Olin, Peter Anthoni, Sam S. Rabin, Anita D. Bayer, Sylvia S. Nyawira, and Almut Arneth
Geosci. Model Dev., 15, 815–839, https://doi.org/10.5194/gmd-15-815-2022, https://doi.org/10.5194/gmd-15-815-2022, 2022
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The implementation of the biological N fixation process in LPJ-GUESS in this study provides an opportunity to quantify N fixation rates between legumes and to better estimate grain legume production on a global scale. It also helps to predict and detect the potential contribution of N-fixing plants as
green manureto reducing or removing the use of N fertilizer in global agricultural systems, considering different climate conditions, management practices, and land-use change scenarios.
Cited articles
Alarcon, V. J., Johnson, D., McAnally, W. H., van der Zwagg, J., Irby, D.,
and Cartwright, J.: Nested hydrodynamic modelling of a coastal river applying
dynamic-coupling, Water Resour. Manag., 28, 3227–3240, 2014.
Antenucci, J. P., Alexander, R., Romero, J. R., and Imberger, J.: Management
stategies for eutrophic water supply reservior–San Roque, Argentina, Water
Sci. Technol., 47, 149–155, 2003.
Arhonditsis, G. B., Adams-VanHarn, B. A., Nielsen, L., Stow, C. A., and
Reckhow, K. H.: Evaluation of the current state of mechanistic aquatic
biogeochemical modeling: citation analysis and future perspectives, Environ.
Sci. Technol., 40, 6547–6554, 2006.
Asaeda, T., Pham, H. S., Nimal Priyantha, D. G., Manatunge, J., and Hocking,
G. C.: Control of algal blooms in reservoirs with a curtain: a numerical
analysis, Ecol. Eng., 16, 395–404, 2001.
Bergin, M. S. and Milford, J. B.: Application of Bayesian Monte Carlo
analysis to a Lagrangian photochemical air quality model, Atmos. Environ.,
34, 781–792, 2000.
Beven, K.: Prophesy, reality and uncertainty in distributed hydrological
modelling, Adv. Water Resour., 16, 41–51, 1993.
Beven, K.: A manifesto for the equifinality thesis, J. Hydrol., 320, 18–36,
2006.
Beven, K.: Comment on “Equifinality of formal (DREAM) and informal (GLUE)
Bayesian approaches in hydrologic modeling?” by: Jasper A. Vrugt, Cajo J. F.
ter Braak, Hoshin V. Gupta and Bruce A. Robinson, Stoch. Environ. Res. Risk
Assess., 23, 1059–1060, 2009.
Beven, K. and Binley A.: The future of distributed models: model calibration
and uncertainty prediction, Hydrol. Process., 6, 279–298, 1992.
Beven, K. and Freer, J.: Equifinality, data assimilation, and uncertainty
estimation in mechanistic modelling of complex environmental systems using
the GLUE methodology, J. Hydrol., 249, 11–29, 2001.
Burger, D. F., Hamilton, D. P., and Pilditch, C. A.: Modelling the relative
importance of internal and external nutrient loads on water column nutrient
concentrations and phytoplankton biomass in a shallow polymictic lake, Ecol.
Modell., 211, 411–423, 2008.
Chung, E. G., Bombardelli, F. A, and Schladow, S. G.: Modeling linkages
between sediment resuspenstion and water quality in a shallow, eutrophic,
wind-exposed lake, Ecol. Modell., 220, 1251–1265, 2009.
Chung, S. W., Imberger, J., Hipsey, M. R., and Lee, H. S.: The influence of
physical and physiological processes on the spatial heterogeneity of a
Microcystis bloom in a stratified reservoir, Ecol. Modell., 289, 133–149,
2014.
Copetti, D., Tartari, G., Morabito, G., Oggioni, A., Legnani, E., and
Imberger, J.: A biogeochemical model of Lake Pusiano (North Italy) and its
use in the predictability of phytoplankton blooms: first preliminary results,
J. Limnol., 65, 59–64, 2006.
Cox, B. A.: A review of currently available in-stream water-quality models
and their applicability for simulating dissolved oxygen in lowland rivers,
Sci. Total Environ., 314–316, 335–377, 2003.
Cui, Y., Zhu, G., Li, H., Luo, L., Cheng, X., Jin, Y., and Trolle, D.:
Modeling the response of phytoplankton to reduced external nutrient load in a
subtropical Chinese reservoir using DYRESM-CAEDYM, Lake Reserv. Manag., 32,
146–157, 2016.
Dilks, D. W., Canale, R. P., and Meier, P. G.: Development of Bayesian
Monte-Carlo techniques for water-quality model uncertainty, Ecol. Modell.,
62, 149–162, 1992.
Duan, Q., Gupta, V. K., and Sorooshian, S.: Effective and efficient global
optimization for conceptual rainfall-runoff models, Water Resour. Res., 28,
1015–1031, 1992.
Duan, Q., Gupta, V. K., and Sorooshian, S.: A shuffled complex evolution
approach for effective and efficient global minimization, J. Optim Theory
Appl., 76, 501–521, 1993.
Elliott, J. A.: Is the future blue-green? A review of the current model
predictions of how climate change could affect pelagic freshwater
cyanobacteria, Water Res., 46, 1364–1371, 2012.
Fekete, B. M., Wollheim, W. M., Wisser, D., and Vörösmarty, C. J.:
Next generation framework for aquatic modeling of the Earth System, Geosci.
Model Dev. Discuss., 2, 279–307, https://doi.org/10.5194/gmdd-2-279-2009,
2009.
Finkelstein, R. and McCall, P. L.: Some components of sediment oxygen demand
in Lake Erie sediments, Project Completion Report No. 714436, Ohio State
University, Water Resources Centre, USA, 1981.
Gal, G., Makler-Pick, V., and Shachar, N.: Dealing with uncertainty in
ecosystem model scenarios: Application of the single-model ensemble approach,
Environ. Modell. Softw., 61, 360–370, 2014.
Gan, T. Y. and Biftu, G. F.: Automatic calibration of conceptual
rainfall-runoff models: optimization algorithms, catchment conditions, and
model structure, Water Resour. Res., 32, 3512–3524, 1996.
Gelda, R. K., Auer, M. T., and Effler, S. W.: Determination of sediment
oxygen demand by direct measurement and by inference from reduced species
accumulation, Mar. Freshw. Res., 46, 81–88, 1995.
Gelfand, A. E. and Smith, A. F. M.: Sampling-based approaches to calculating
marginal densities, J. Am. Stat. Assoc., 85, 398–409, 1990.
Gelfand, A. E., Hills, S. E., Racin-poon, A., and Smith, A. F. M.:
Illustration of Bayesian inference in normal data models using Gibbs
sampling, J. Am. Stat. Assoc. 85, 972–985, 1990.
Gilks, W. R., Thomas, A., and Spiegelhalter, D. J.: A language and program
for complex Bayesian modelling, Statistician, 43, 169–177, 1994.
Green, C. H. and van Griensven A.: Autocalibration in hydrologic modelling:
using SWAT2005 in small-scale watersheds, Environ. Modell. Softw., 23,
422–434, 2008.
Hamilton, D. P.: Numerical modelling and lake management: Applications of the
DYRESM model, in: Theoretical Reservoir Ecology and its Applications, edited
by: Tundisi, J. G. and Straškraba, M., Backhuys Publ., the Netherlands,
153–174, 1999.
Hamilton, D. P. and Schladow, S. G.: Controlling the indirect effects of flow
diversions on water quality in an Australian reservoir, Environ. Int., 21,
583–590, 1995.
Hamilton, D. P. and Schladow, S. G.: Prediction of water quality in lakes and
reservoirs, Part I – Model description, Ecol. Modell., 96, 91–110, 1997.
Han, B., Armengol, J., Garcia, J. C., Comerma, M., Roura, M., Dolz, J., and
Straskraba, M.: The thermal structure of Sau Reservoir (NE: Spain): a
simulation approach, Ecol. Modell., 125, 109–122, 2000.
Heathman, G. C., Flanagan, D. C., Larose, M., and Zuercher, B. W.:
Application of the soil and water assessment tool and annualized agricultural
non-point source models in the St. Joseph River watershed, J. Soil Water
Conserv., 63, 552–568, 2008.
Hession, W. C., Storm, D. E., and Hann, C. T.: Two-phase uncertainty
analysis: an example using the universal soil loss equation, T. ASAE, 39,
1309–1319, 1996.
Hipsey, M. R., Antenucci, J. P., Romero, J. R., and Hamilton, D. P.:
Computational aquatic ecosystem dynamics model: CAEDYM v3 (Science Manual),
Centre for Water Research, University of Western Australia, 2007.
Hu, F., Bolding, K., Bruggeman, J., Jeppesen, E., Flindt, M. R., van Gerven,
L., Janse, J. H., Janssen, A. B. G., Kuiper, J. J., Mooij, W. M., and Trolle,
D.: FABM-PCLake – linking aquatic ecology with hydrodynamics, Geosci. Model
Dev., 9, 2271–2278, https://doi.org/10.5194/gmd-9-2271-2016, 2016.
Hu, W. F., Lo, W., Chua, H., Sin, S. N., and Yu, P. H. F.: Nutrient release
and sediment oxygen demand in a eutrophic land-locked embayment in Hong Kong,
Environ. Int., 26, 369–375, 2001.
Jackson, L. J., Trebitz, A. S., and Conttingham, K. L.: An introduction to
the practice of Ecological Modeling, Bioscience, 50, 694–706, 2000.
Jayakrishnan, R., Srinivasan, R., Santhic, C., and Arnold, J. G.: Advances in
the application of the SWAT model for water resources management, Hydrol.
Process., 19, 749–762, 2005.
Jorgensen, S. E.: State of the art of Ecological Modelling in limnology,
Ecol. Modell., 78, 101–115, 1995.
Kannel, P. R., Lee, S., Kanel, S. R., Lee, Y., and Anh, K.: Application of
QUAL2Kw for water quality modelling and dissolved oxygen control in the river
Bagmati, Environ. Monit. Assess., 125, 201–207, 2007a.
Kannel, P. R., Lee, S., Lee, Y. S., Kanel, S. R., and Pelletier, G. L.:
Application of automated QUAL2Kw for water quality modelling and management
in the Bagmati River, Nepal, Ecol. Modell., 202, 503–517, 2007b.
Kim, T. and Sheng, Y. P.: Estimation of water quality model parameters, KSCE
J. Civ. Eng., 14, 421–437, 2010.
Krajewski, W. F., Lakshimi, V., Georgakakos, K. P., and Jain, S. J.: A Monte
Carlo study of rainfall sampling effect on a distributed catchment model,
Water Resour. Res., 27, 119–128, 1991.
Li, Y., Tang, C., Wang, C., Anim, D. O., Yu, Z., and Acharya, K.: Improved
Yangtze River diversions: are they helping to solve algal bloom problems in
Lake Taihu, China, Ecol. Eng., 51, 104–116, 2013a.
Li, X., Wang, C., Fan, W., and Lv, X.: Optimization of the spatiotemporal
parameters in a dynamical marine ecosystem model based on the adjoint
assimilation, Math. Probl. Eng., 2013, 1–12, 2013b.
Liang, S., Han, S., and Sun, Z.: Parameter optimization method for the water,
quality dynamic model based on data-driven theory, Mar. Pollut. Bull., 98,
137–147, 2015.
Liu, Y.: Automatic calibration of a rainfall–runoff model using a fast and
elitist multi-objective particle swarm algorithm, Expert. Syst. Appl., 36,
9533–9538, 2009.
Madsen, H.: Automatic calibration of a conceptual rainfall-runoff model using
multiple objectives, J. Hydrol., 235, 276–288, 2000.
Makler-Pick, V., Gal, G., Gorfine, M., Hipsey, M. R., and Carmel, Y.:
Sensitivity analysis for complex ecological models – A new approach,
Environ. Modell. Softw., 26, 124–134, 2011.
Marsili-Libelli, S. and Giusti, E.: Water quality modelling for small river
basins, Environ. Modell. Softw., 23, 451–463, 2008.
Mosley, L. M., Daly, R., Palmer, D., Yeates, P., Dallimore, C., Biswas, T.,
and Simpson, S. L.: Predictive modelling of pH and dissolved metal
concentrations and speciation following mixing of acid drainage with river
water, Appl. Geochem., 59, 1–10, 2015.
Ng, A. W. M. and Perera, B. J. C.: Selection of genetic algorithm operators
for river water quality model calibration, Eng. Appl. Artif. Intell., 16,
529–541, 2003.
Nunez, M., Davies, J. A., and Robinson, P. J.: Surface albedo at a tower site
in Lake Ontario, Bound.-Lay. Meteorol., 3, 1573–1472, 1972.
Pelletier, G. J., Chapra, S. C., and Tao, H.: QUAL2Kw – a framework for
modelling water quality in streams and rivers using a genetic algorithm for
calibration, Environ. Modell. Softw., 21, 419–425, 2006.
Pierson, D. C, Samal, N. R., Owens, E. M., Schneiderman, E. M., and Zion, M.
S.: Changes in the timing of snowmelt and the seasonality of nutrient
loading: can models simulate the impacts on freshwater trophic status?,
Hydrol. Process., 27, 3083–3093, 2013.
Qian, S. S, Stow, C. A., and Borsuk, M. E.: On Monte Carlo methods for
Bayesian inference, Ecol. Modell., 159, 269–277, 2003.
Read, J. S., Hamilton, D. P., Jones, I. D., Muraoka, K., Winslow, L. A.,
Kroiss, R., Wu, C. H., and Gaiser, E.: Derivation of lake mixing and
stratification indices from high-resolution lake buoy data, Environ. Modell.
Softw., 26, 1325–1336, 2011.
Refsgaard, J. C., van der Sluijs, J. P., Hojberg, A. L., and Vanrolleghem, P.
A.: Uncertainty in the environmental modelling process – a framework and
guidance, Environ. Modell. Softw., 22, 1543–1556, 2007.
Riley, J. P. and Skirrow, G.: Chemical Oceanography, Academic Press, London,
1974.
Robson, B. J. and Hamilton, D. P.: Three-dimensional modelling of a
Microcystis bloom event in the Swan River estuary, Western Australia, Ecol.
Modell., 174, 203–222, 2004.
Romero, J. R., Antenucci, J. P., and Imberger, J.: One- and three-dimensional
biogeochemical simulations of two differing reservoirs, Ecol. Modell., 174,
143–160, 2004.
Rose, K. A., Megrey, B. A., Werner, F. E., and Ware, D. M.: Calibration of
the NEMURO nutrient-phytoplankton-zooplankton food web model to a coastal
ecosystem: Evaluation of an automated calibration approach, Ecol. Modell.,
202, 38–51, 2007.
Santhi, C., Arnold, J. G., Williams, J. R., Dugas, W. A., and Hauck, L. M.:
Application of a watershed model to evaluate management effects on point and
nonpoint pollution, T. ASAE, 44, 1559–1770, 2001.
Schmolke, A., Thorbek, P., DeAngelis, D. L., and Grimm, V.: Ecological models
supporting environmental decision making: a strategy for the future, Trends
Ecol. Evol., 25, 479–486, 2010.
Seppelt, R. and Voinov, A.: Optimization methodology for land use patters
using spatially explicit landscape models, Ecol. Modell., 151, 125–142,
2002.
Solomatine, D. P.: Genetic and other global optimization
algorithms–comparison and use in calibration problems, Proc. 3rd
International Conference on Hydroinformatics, Copenhagen, Denmark,
1021–1028, 1998.
Solomatine, D. P., Dibike, Y. B., and Nukuric, N.: Automatic calibration of
groundwater models using global optimization techniques, Hydrol. Sci. J., 44,
879–894, 1999.
Stow, C. A., Reckhow, K. H., Qian, S. S., and Conrad, E.: Approaches to
estimate water quality model parameter uncertainty for adaptive TMDL
implementation, J. Am. Water Resour. Assoc., 43, 1499–1507, 2007.
Strauss, T. and Ratte, H. T.: Modelling the vertical variation of temperature
and dissolved oxygen in a shallow, eutrophic pond as a tool for analysis of
the internal phosphorus fluxes, Verh. Internat. Verein. Limnol., 28, 1–4,
2002.
Tanentzap, A. J., Yan, N. D., Keller, B., Girard, R., Heneberry, J., Gunn, J.
M., Hamilton, D. P., and Taylor, P. A.: Cooling lakes while the world warms:
effects of forest regrowth and increased dissolved organic matter on the
thermal regime of a temperate, urban lake, Limnol. Oceanogr., 53, 404–410,
2008.
Takkouk, S. and Casamitjana, X.: Application of the DYRESM–CAEDYM model to
the Sau Reservoir situated in Catalonia, Spain, Desalination Water Treat.,
57, 12453–12466, 2016.
Tang, C., Li, Y., Jiang, P., Yu, Z., and Acharya, K.: A couple modelling
approach to predict water quality in Lake Taihu, China: linkage to climate
change projections, J. Freshw. Ecol., 30, 59–73, 2015.
Trolle, D., Jorgensen, T. B., and Jeppesen, E.: Predicting the effects of
reduced external nitrogen loading on the nitrogen dynamics and ecological
state of deep Lake Ravn, Denmark, using the DYRESM-CAEDYM model, Limnologica
38, 220–232, 2008a.
Trolle, D., Skovgaard, H., and Jeppesen, E.: The water framework directive:
setting the phosphorus loading target for a deep lake in Denmark using the 1D
lake ecosystem model DYRESM-CAEDYM, Ecol. Modell., 219, 138–152, 2008b.
Van der Perk, M. and Bierkens, M. F. P.: The identifiability of parameters in
a water quality model of the Biebrza River, Poland, J. Hydrol., 200,
307–322, 1997.
Van Griensven, A. and Bauwens, W.: Multiobjective autocalibration for
semidistributed water quality models, Water Resour. Res., 39, 1348–1356,
2003.
Van Griensven, A., Francos, A., and Bauwens, W.: Sensitivity analysis and
auto-calibration of an integral dynamic model for river water quality, Water
Sci. Technol., 45, 325–332, 2002.
Veenstra, J. N. and Nolen, S.L.: In-situ sediment oxygen demand in five
southwestern U.S. lakes, Water Res., 25, 351–354, 1991.
Vilhena, L. C., Hillmer, I., and Imberger, J.: The role of climate change in
the occurrence of algal blooms: Lake Burragorang, Australia, Limnol.
Oceanogr., 55, 1188–1200, 2010.
Vrugt, J. A., Gupta, H. V., Bouten, W., and Sorooshian, S.: A shuffled
complex evolution metropolis algorithm for optimization and uncertainty
assessment of hydrologic model parameters, Water Resour. Res., 39,
1201–1214, 2003.
Vrugt, J. A., ter Braak, C. J. F., Gupta, H. V., and Robinson, B. A.:
Equifinality of formal (DREAM) and informal (GLUE) Bayesian approaches in
hydrological modeling?, Stoch. Environ. Res. Risk Assess., 23, 1011–1026,
2009a.
Vrugt, J. A., ter Braak, C. J. F., Gupta, H. V., and Robinson, B. A.:
Response to comment by Keith Beven on “Equifinality of formal (DREAM) and
informal (GLUE) Bayesian approaches in hydrologic modeling?”, Stoch.
Environ. Res. Risk Assess., 23, 1061–1062, 2009b.
Wanninkhof, R.: Relationship between windspeed and gas exchange over the
ocean, J. Geophys. Res.-Oceans, 97, 7373–7382, 1992.
Whitehead, P. G., Wilby, R. L., Battarbee, R. W., Kernan, M., and Wade, A.
J.: A review of the potential impacts of climate change on surface water
quality, Hydrolog. Sci. J., 54, 101–123, 2009.
Wu, Y., Liu, S., Li, Z., Dahal, D., Young, C. J., Schmidt, G. L., Liu, J.,
Davis, B., Sohl, T. L., Werner, J. M., and Oeding, J.: Development of a
generic auto-calibration package for regional ecological modeling and
application in the Central Plains of the United States, Ecol. Inform., 19,
35–46, 2014.
Yeates, P. S. and Imberger, J.: Pseudo two-dimensional simulations of
internal and boundary fluxes in stratified lakes and reservoirs, Int. J.
River Basin Manage., 1, 297–319, 2003.
Zhang, L., Xu, M., Huang, M., and Yu, G.: Reducing impacts of systematic
errors in the observation data on inversing ecosystem model parameters using
different normalization methods, Biogeosciences Discuss., 6, 10447–10477,
https://doi.org/10.5194/bgd-6-10447-2009, 2009.
Zobitz, J. M., Desai, A. R., Moore, D. J. P., and Chadwick, M. A.: A primer
for data assimilation with ecological models using Markov Chain Monte Carlo
(MCMC), Oecologia, 167, 599–611, 2011.
Short summary
We developed an autocalibration software for the hydrodynamic-ecological lake model DYRESM-CAEDYM with a massive number of water quality parameters, using a Monte Carlo sampling method, in order to reduce time-consuming iterative simulations with empirical judgements and find optimal model parameter set. The successful applications to Lake Rotorua suggest this software is much more efficient than traditional methods and of wide applicability to other water quality models.
We developed an autocalibration software for the hydrodynamic-ecological lake model...
