Articles | Volume 27, issue 8
https://doi.org/10.5194/hess-27-1683-2023
© 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/hess-27-1683-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Dynamically coupling system dynamics and SWAT+ models using Tinamït: application of modular tools for coupled human–water system models
Joel Z. Harms
CORRESPONDING AUTHOR
Department of Bioresource Engineering, McGill University,
Sainte-Anne-de-Bellevue H9X 3V9, Canada
Julien J. Malard-Adam
Department of Bioresource Engineering, McGill University,
Sainte-Anne-de-Bellevue H9X 3V9, Canada
Institut de recherche pour le développement (IRD), UMR G-EAU,
Université de Montpellier, Montpellier 34000, France
Jan F. Adamowski
Department of Bioresource Engineering, McGill University,
Sainte-Anne-de-Bellevue H9X 3V9, Canada
Ashutosh Sharma
Department of Hydrology, Indian Institute of Technology Roorkee,
Uttarakhand 247667, India
Albert Nkwasa
Hydrology and Hydraulic Engineering Department, Vrije Universiteit
Brussel (VUB), 1050 Brussels, Belgium
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Mohammad Sina Jahangir, John Quilty, Chaopeng Shen, Andrea Scott, Scott Steinschneider, and Jan Adamowski
EGUsphere, https://doi.org/10.5194/egusphere-2025-846, https://doi.org/10.5194/egusphere-2025-846, 2025
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This study presents a novel hybrid approach to streamflow prediction, significantly improving the efficiency and accuracy of fine-tuning deep learning models for hydrological prediction. Tested across numerous catchments in the U.S. and Europe, this method accelerates the fine-tuning process and improves prediction accuracy in locations beyond the training data. This innovative approach sets the stage for future hydrological models leveraging transfer learning.
Albert Nkwasa, Celray James Chawanda, Maria Theresa Nakkazi, and Ann van Griensven
EGUsphere, https://doi.org/10.5194/egusphere-2025-703, https://doi.org/10.5194/egusphere-2025-703, 2025
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Limited monitoring data make it difficult to assess human impacts on freshwater quality, especially in low-income regions. To address this, we developed a global water quality model that simulates river nutrient loads (Total Nitrogen and Total Phosphorus). The model provides high-resolution insights into freshwater pollution, supporting ecological risk assessments and policy decisions. While some uncertainties remain, this model offers a crucial tool for addressing global water quality.
Celray James Chawanda, Ann van Griensven, Albert Nkwasa, Jose Pablo Teran Orsini, Jaehak Jeong, Soon-Kun Choi, Raghavan Srinivasan, and Jeffrey G. Arnold
EGUsphere, https://doi.org/10.5194/egusphere-2025-188, https://doi.org/10.5194/egusphere-2025-188, 2025
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Water resources face more challenges from climate change and human activities. We improved global water modeling by developing a high-resolution system using SWAT+, using automated reproducible workflow. This approach simplifies tracking the progress of global impact assessment modelling efforts. The global model will further help assess water stress hotspots and inform sustainable water management as further improvements come.
Celray James Chawanda, Albert Nkwasa, Wim Thiery, and Ann van Griensven
Hydrol. Earth Syst. Sci., 28, 117–138, https://doi.org/10.5194/hess-28-117-2024, https://doi.org/10.5194/hess-28-117-2024, 2024
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Africa's water resources are being negatively impacted by climate change and land-use change. The SWAT+ hydrological model was used to simulate the hydrological cycle in Africa, and results show likely decreases in river flows in the Zambezi and Congo rivers and highest flows in the Niger River basins due to climate change. Land cover change had the biggest impact in the Congo River basin, emphasizing the importance of including land-use change in studies.
Mohammad Reza Alizadeh, Jan Adamowski, and Manzoor Qadir
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-297, https://doi.org/10.5194/hess-2022-297, 2022
Preprint withdrawn
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This study aims to support robust policy development in human-water systems with scenario analysis of downscaled shared socio-economic pathways (SSPs) scenarios under deep uncertainty. An integrated dynamic simulation-optimization model is developed to evaluate policy alternatives and their robustness. We found many distinct combinations of outcomes with varying robustness, suggesting that the implementation of a range of development processes can lead to a particular outcome of interest.
Anna Msigwa, Celray James Chawanda, Hans C. Komakech, Albert Nkwasa, and Ann van Griensven
Hydrol. Earth Syst. Sci., 26, 4447–4468, https://doi.org/10.5194/hess-26-4447-2022, https://doi.org/10.5194/hess-26-4447-2022, 2022
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Studies using agro-hydrological models, like the Soil and Water Assessment Tool (SWAT), to map evapotranspiration (ET) do not account for cropping seasons. A comparison between the default SWAT+ set-up (with static land use representation) and a dynamic SWAT+ model set-up (with seasonal land use representation) is made by spatial mapping of the ET. The results show that ET with seasonal representation is closer to remote sensing estimates, giving better performance than ET with static land use.
Albert Nkwasa, Celray James Chawanda, Jonas Jägermeyr, and Ann van Griensven
Hydrol. Earth Syst. Sci., 26, 71–89, https://doi.org/10.5194/hess-26-71-2022, https://doi.org/10.5194/hess-26-71-2022, 2022
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We present an approach on how to incorporate crop phenology in a regional hydrological model using decision tables and global datasets of rainfed and irrigated cropland with the associated cropping calendar and management practices. Results indicate improved temporal patterns of leaf area index (LAI) and evapotranspiration (ET) simulations in comparison with remote sensing data. In addition, the improvement of the cropping season also helps to improve soil erosion estimates in cultivated areas.
Jessica A. Bou Nassar, Julien J. Malard, Jan F. Adamowski, Marco Ramírez Ramírez, Wietske Medema, and Héctor Tuy
Hydrol. Earth Syst. Sci., 25, 1283–1306, https://doi.org/10.5194/hess-25-1283-2021, https://doi.org/10.5194/hess-25-1283-2021, 2021
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Our research suggests a method that facilitates the inclusion of marginalized stakeholders in model-building activities to address problems in water resources. Our case study showed that knowledge produced by typically excluded stakeholders had significant and unique contributions to the outcome of the process. Moreover, our method facilitated the identification of relationships between societal, economic, and hydrological factors, and it fostered collaborations across different communities.
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Short summary
To facilitate the meaningful participation of stakeholders in water management, model choice is crucial. We show how system dynamics models (SDMs), which are very visual and stakeholder-friendly, can be automatically combined with physically based hydrological models that may be more appropriate for modelling the water processes of a human–water system. This allows building participatory SDMs with stakeholders and delegating hydrological components to an external hydrological model.
To facilitate the meaningful participation of stakeholders in water management, model choice is...