Articles | Volume 15, issue 11
https://doi.org/10.5194/gmd-15-4503-2022
© Author(s) 2022. 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-15-4503-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
13 Jun 2022
Model description paper |
| 13 Jun 2022
| 13 Jun 2022
ANEMI_Yangtze v1.0: a coupled human–natural systems model for the Yangtze Economic Belt – model description
Haiyan Jiang
CORRESPONDING AUTHOR
Department of Civil and Environmental Engineering, Western University,
London, Ontario, Canada
College of Urban Construction, Nanjing Tech University, Nanjing,
211816, China
State Key Laboratory of Hydrology-Water Resources and Hydraulic
Engineering, Hohai University, Nanjing, 210098, China
Slobodan P. Simonovic
Department of Civil and Environmental Engineering, Western University,
London, Ontario, Canada
Zhongbo Yu
State Key Laboratory of Hydrology-Water Resources and Hydraulic
Engineering, Hohai University, Nanjing, 210098, China
Joint
International Research Laboratory of Global Change and Water Cycle, Hohai
University, Nanjing, 210098, China
Yangtze Institute for Conservation and Development, Hohai University,
Nanjing, 210098, China
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Zhongbo Yu, Chunhui Lu, Jianyuan Cai, Dazheng Yu, Gil Mahe, Anil Mishra, Christophe Cudennec, Henny A. J. Van Lanen, Didier Orange, and Abou Amani
Proc. IAHS, 383, 3–4, https://doi.org/10.5194/piahs-383-3-2020, https://doi.org/10.5194/piahs-383-3-2020, 2020
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The 8th Global FRIEND conference highlighted the advance in hydrological science and innovation in water management. 52 accepted papers cover study areas in precipitation and climate impact; observation, analysis and simulations of hydrologic processes; floods in the changing environments; drought monitoring and analysis; water resources and environmental impacts. The outcome of the conference presented in the proceedings will be shared and discussed widely among UNESCO IHP networks.
Franklin W. Schwartz, Ganming Liu, and Zhongbo Yu
Hydrol. Earth Syst. Sci., 24, 489–500, https://doi.org/10.5194/hess-24-489-2020, https://doi.org/10.5194/hess-24-489-2020, 2020
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We are concerned about the sad state of affairs around groundwater in the developing countries of Asia and the obvious implications for sustainability. Groundwater production for irrigated agriculture has led to water-level declines that continue to worsen. Yet in the most populous countries, China, India, Pakistan, and Iran, there are only token efforts towards evidence-based sustainable management. It is unrealistic to expect evidence-based groundwater sustainability to develop any time soon.
Huanghe Gu, Zhongbo Yu, Chuanguo Yang, Qin Ju, Tao Yang, and Dawei Zhang
Hydrol. Earth Syst. Sci., 22, 3087–3103, https://doi.org/10.5194/hess-22-3087-2018, https://doi.org/10.5194/hess-22-3087-2018, 2018
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An ensemble simulation of five RCMs from CORDEX in East Asia was evaluated and used for future regional climate change projection in China. In addition, the contributions of model uncertainty and internal variability are identified. We found that the multi-model ensemble outperforms the individual RCMs in historical climate simulation. The future climate projections show significant inter-RCM differences and the model uncertainty increases with prediction lead time over all subregions.
S. P. Simonovic and R. Arunkumar
Proc. IAHS, 373, 13–17, https://doi.org/10.5194/piahs-373-13-2016, https://doi.org/10.5194/piahs-373-13-2016, 2016
X. Chen, L. Chen, J. Zhao, and Z. Yu
Nat. Hazards Earth Syst. Sci., 15, 2161–2172, https://doi.org/10.5194/nhess-15-2161-2015, https://doi.org/10.5194/nhess-15-2161-2015, 2015
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This study applied the two-dimensional AdH (adaptive hydraulics) hydrodynamic model to a river reach to analyze flood hydraulics on complex floodplains. A detailed analysis of the floodwater dynamics was conducted using the modeling approach to examine the hydraulic linkage between the main channel and floodplains.
Z. Yu, W. Dong, and P. Jiang
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-12-6505-2015, https://doi.org/10.5194/hessd-12-6505-2015, 2015
Revised manuscript not accepted
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This study simulates paleolake extent in Owens Valley, California in the last 18ka. A coupled catchment-lake model is developed which is capable of accurately simulating lake extent as a function of modern climate and paleoclimate. Through these simulations, the paleoclimate information including annual precipitation and temperature can be quantitatively estimated against field evidence in a catchment-lake hydrologic system.
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Integrated assessment modeling
GCAM–GLORY v1.0: representing global reservoir water storage in a multi-sector human–Earth system model
CLASH – Climate-responsive Land Allocation model with carbon Storage and Harvests
Carbon Monitor Power-Simulators (CMP-SIM v1.0) across countries: a data-driven approach to simulate daily power generation
Intercomparison of multiple two-way coupled meteorology and air quality models (WRF v4.1.1–CMAQ v5.3.1, WRF–Chem v4.1.1, and WRF v3.7.1–CHIMERE v2020r1) in eastern China
MESSAGEix-GLOBIOM nexus module: integrating water sector and climate impacts
Minimum-variance-based outlier detection method using forward-search model error in geodetic networks
Modelling long-term industry energy demand and CO2 emissions in the system context using REMIND (version 3.1.0)
Bidirectional coupling of the long-term integrated assessment model REgional Model of INvestments and Development (REMIND) v3.0.0 with the hourly power sector model Dispatch and Investment Evaluation Tool with Endogenous Renewables (DIETER) v1.0.2
GCAM-CDR v1.0: enhancing the representation of carbon dioxide removal technologies and policies in an integrated assessment model
The IPCC Sixth Assessment Report WGIII climate assessment of mitigation pathways: from emissions to global temperatures
Cyclone generation Algorithm including a THERmodynamic module for Integrated National damage Assessment (CATHERINA 1.0) compatible with Coupled Model Intercomparison Project (CMIP) climate data
A tool for air pollution scenarios (TAPS v1.0) to enable global, long-term, and flexible study of climate and air quality policies
Improved CASA model based on satellite remote sensing data: simulating net primary productivity of Qinghai Lake basin alpine grassland
Pixel-level parameter optimization of a terrestrial biosphere model for improving estimation of carbon fluxes with an efficient model–data fusion method and satellite-derived LAI and GPP data
Climate Services Toolbox (CSTools) v4.0: from climate forecasts to climate forecast information
TIM: modelling pathways to meet Ireland's long-term energy system challenges with the TIMES-Ireland Model (v1.0)
Nested leave-two-out cross-validation for the optimal crop yield model selection
GCAM-USA v5.3_water_dispatch: integrated modeling of subnational US energy, water, and land systems within a global framework
GOBLIN version 1.0: a land balance model to identify national agriculture and land use pathways to climate neutrality via backcasting
Globally consistent assessment of economic impacts of wildfires in CLIMADA v2.2
REMIND2.1: transformation and innovation dynamics of the energy-economic system within climate and sustainability limits
Parallel gridded simulation framework for DSSAT-CSM (version 4.7.5.21) using MPI and NetCDF
Estimating global land system impacts of timber plantations using MAgPIE 4.3.5
Mengqi Zhao, Thomas B. Wild, Neal T. Graham, Son H. Kim, Matthew Binsted, A. F. M. Kamal Chowdhury, Siwa Msangi, Pralit L. Patel, Chris R. Vernon, Hassan Niazi, Hong-Yi Li, and Guta W. Abeshu
Geosci. Model Dev., 17, 5587–5617, https://doi.org/10.5194/gmd-17-5587-2024, https://doi.org/10.5194/gmd-17-5587-2024, 2024
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The Global Change Analysis Model (GCAM) simulates the world’s climate–land–energy–water system interactions , but its reservoir representation is limited. We developed the GLObal Reservoir Yield (GLORY) model to provide GCAM with information on the cost of supplying water based on reservoir construction costs, climate and demand conditions, and reservoir expansion potential. GLORY enhances our understanding of future reservoir capacity needs to meet human demands in a changing climate.
Tommi Ekholm, Nadine-Cyra Freistetter, Aapo Rautiainen, and Laura Thölix
Geosci. Model Dev., 17, 3041–3062, https://doi.org/10.5194/gmd-17-3041-2024, https://doi.org/10.5194/gmd-17-3041-2024, 2024
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CLASH is a numerical model that portrays land allocation between different uses, land carbon stocks, and agricultural and forestry production globally. CLASH can help in examining the role of land use in mitigating climate change, providing food and biogenic raw materials for the economy, and conserving primary ecosystems. Our demonstration with CLASH confirms that reduction of animal-based food, shifting croplands and storing carbon in forests are effective ways to mitigate climate change.
Léna Gurriaran, Yannig Goude, Katsumasa Tanaka, Biqing Zhu, Zhu Deng, Xuanren Song, and Philippe Ciais
Geosci. Model Dev., 17, 2663–2682, https://doi.org/10.5194/gmd-17-2663-2024, https://doi.org/10.5194/gmd-17-2663-2024, 2024
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We developed a data-driven model simulating daily regional power demand based on climate and socioeconomic variables. Our model was applied to eight countries or regions (Australia, Brazil, China, EU, India, Russia, South Africa, US), identifying influential factors and their relationship with power demand. Our findings highlight the significance of economic indicators in addition to temperature, showcasing country-specific variations. This research aids energy planning and emission reduction.
Chao Gao, Xuelei Zhang, Aijun Xiu, Qingqing Tong, Hongmei Zhao, Shichun Zhang, Guangyi Yang, Mengduo Zhang, and Shengjin Xie
Geosci. Model Dev., 17, 2471–2492, https://doi.org/10.5194/gmd-17-2471-2024, https://doi.org/10.5194/gmd-17-2471-2024, 2024
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A comprehensive comparison study is conducted targeting the performances of three two-way coupled meteorology and air quality models (WRF-CMAQ, WRF-Chem, and WRF-CHIMERE) for eastern China during 2017. The impacts of aerosol–radiation–cloud interactions on these models’ results are evaluated against satellite and surface observations. Further improvements to the calculation of aerosol–cloud interactions in these models are crucial to ensure more accurate and timely air quality forecasts.
Muhammad Awais, Adriano Vinca, Edward Byers, Stefan Frank, Oliver Fricko, Esther Boere, Peter Burek, Miguel Poblete Cazenave, Paul Natsuo Kishimoto, Alessio Mastrucci, Yusuke Satoh, Amanda Palazzo, Madeleine McPherson, Keywan Riahi, and Volker Krey
Geosci. Model Dev., 17, 2447–2469, https://doi.org/10.5194/gmd-17-2447-2024, https://doi.org/10.5194/gmd-17-2447-2024, 2024
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Climate change, population growth, and depletion of natural resources all pose complex and interconnected challenges. Our research offers a novel model that can help in understanding the interplay of these aspects, providing policymakers with a more robust tool for making informed future decisions. The study highlights the significance of incorporating climate impacts within large-scale global integrated assessments, which can help us in generating more climate-resilient scenarios.
Utkan M. Durdağ
Geosci. Model Dev., 17, 2187–2196, https://doi.org/10.5194/gmd-17-2187-2024, https://doi.org/10.5194/gmd-17-2187-2024, 2024
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This study introduces a novel approach to outlier detection in geodetic networks, challenging conventional and robust methods. By treating outliers as unknown parameters within the Gauss–Markov model and exploring numerous outlier combinations, this approach prioritizes minimal variance and eliminates iteration dependencies. The mean success rate (MSR) comparisons highlight its effectiveness, improving the MSR by 40–45 % for multiple outliers.
Michaja Pehl, Felix Schreyer, and Gunnar Luderer
Geosci. Model Dev., 17, 2015–2038, https://doi.org/10.5194/gmd-17-2015-2024, https://doi.org/10.5194/gmd-17-2015-2024, 2024
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We extend the REMIND model (used to investigate climate mitigation strategies) by an industry module that represents cement, chemical, steel, and other industries. We also present a method for deriving scenarios of industry subsector activity and energy demand, consistent with established socioeconomic scenarios, allowing us to investigate the different climate change mitigation challenges and strategies in industry subsectors in the context of the entire energy–economy–climate system.
Chen Chris Gong, Falko Ueckerdt, Robert Pietzcker, Adrian Odenweller, Wolf-Peter Schill, Martin Kittel, and Gunnar Luderer
Geosci. Model Dev., 16, 4977–5033, https://doi.org/10.5194/gmd-16-4977-2023, https://doi.org/10.5194/gmd-16-4977-2023, 2023
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To mitigate climate change, the global economy must drastically reduce its greenhouse gas emissions, for which the power sector plays a key role. Until now, long-term models which simulate this transformation cannot always accurately depict the power sector due to a lack of resolution. Our work bridges this gap by linking a long-term model to an hourly model. The result is an almost full harmonization of the models in generating a power sector mix until 2100 with hourly resolution.
David R. Morrow, Raphael Apeaning, and Garrett Guard
Geosci. Model Dev., 16, 1105–1118, https://doi.org/10.5194/gmd-16-1105-2023, https://doi.org/10.5194/gmd-16-1105-2023, 2023
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GCAM-CDR is a variant of the Global Change Analysis Model that makes it easier to study the roles that carbon dioxide removal (CDR) might play in climate policy. Building on GCAM 5.4, GCAM-CDR adds several extra technologies to permanently remove carbon dioxide from the air and enables users to simulate a wider range of CDR-related policies and controls.
Jarmo S. Kikstra, Zebedee R. J. Nicholls, Christopher J. Smith, Jared Lewis, Robin D. Lamboll, Edward Byers, Marit Sandstad, Malte Meinshausen, Matthew J. Gidden, Joeri Rogelj, Elmar Kriegler, Glen P. Peters, Jan S. Fuglestvedt, Ragnhild B. Skeie, Bjørn H. Samset, Laura Wienpahl, Detlef P. van Vuuren, Kaj-Ivar van der Wijst, Alaa Al Khourdajie, Piers M. Forster, Andy Reisinger, Roberto Schaeffer, and Keywan Riahi
Geosci. Model Dev., 15, 9075–9109, https://doi.org/10.5194/gmd-15-9075-2022, https://doi.org/10.5194/gmd-15-9075-2022, 2022
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Assessing hundreds or thousands of emission scenarios in terms of their global mean temperature implications requires standardised procedures of infilling, harmonisation, and probabilistic temperature assessments. We here present the open-source
climate-assessmentworkflow that was used in the IPCC AR6 Working Group III report. The paper provides key insight for anyone wishing to understand the assessment of climate outcomes of mitigation pathways in the context of the Paris Agreement.
Théo Le Guenedal, Philippe Drobinski, and Peter Tankov
Geosci. Model Dev., 15, 8001–8039, https://doi.org/10.5194/gmd-15-8001-2022, https://doi.org/10.5194/gmd-15-8001-2022, 2022
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The CATHERINA model produces simulations of cyclone-related annualized damage costs at a country level from climate data and open-source socioeconomic indicators. The framework couples statistical and physical modeling of tropical cyclones to bridge the gap between general circulation and integrated assessment models providing a precise description of tropical-cyclone-related damages.
William Atkinson, Sebastian D. Eastham, Y.-H. Henry Chen, Jennifer Morris, Sergey Paltsev, C. Adam Schlosser, and Noelle E. Selin
Geosci. Model Dev., 15, 7767–7789, https://doi.org/10.5194/gmd-15-7767-2022, https://doi.org/10.5194/gmd-15-7767-2022, 2022
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Understanding policy effects on human-caused air pollutant emissions is key for assessing related health impacts. We develop a flexible scenario tool that combines updated emissions data sets, long-term economic modeling, and comprehensive technology pathways to clarify the impacts of climate and air quality policies. Results show the importance of both policy levers in the future to prevent long-term emission increases from offsetting near-term air quality improvements from existing policies.
Chengyong Wu, Kelong Chen, Chongyi E, Xiaoni You, Dongcai He, Liangbai Hu, Baokang Liu, Runke Wang, Yaya Shi, Chengxiu Li, and Fumei Liu
Geosci. Model Dev., 15, 6919–6933, https://doi.org/10.5194/gmd-15-6919-2022, https://doi.org/10.5194/gmd-15-6919-2022, 2022
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The traditional Carnegie–Ames–Stanford Approach (CASA) model driven by multisource data such as meteorology, soil, and remote sensing (RS) has notable disadvantages. We drove the CASA using RS data and conducted a case study of the Qinghai Lake basin alpine grassland. The simulated result is similar to published and measured net primary productivity (NPP). It may provide a reference for simulating vegetation NPP to satisfy the requirements of accounting carbon stocks and other applications.
Rui Ma, Jingfeng Xiao, Shunlin Liang, Han Ma, Tao He, Da Guo, Xiaobang Liu, and Haibo Lu
Geosci. Model Dev., 15, 6637–6657, https://doi.org/10.5194/gmd-15-6637-2022, https://doi.org/10.5194/gmd-15-6637-2022, 2022
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Parameter optimization can improve the accuracy of modeled carbon fluxes. Few studies conducted pixel-level parameterization because it requires a high computational cost. Our paper used high-quality spatial products to optimize parameters at the pixel level, and also used the machine learning method to improve the speed of optimization. The results showed that there was significant spatial variability of parameters and we also improved the spatial pattern of carbon fluxes.
Núria Pérez-Zanón, Louis-Philippe Caron, Silvia Terzago, Bert Van Schaeybroeck, Llorenç Lledó, Nicolau Manubens, Emmanuel Roulin, M. Carmen Alvarez-Castro, Lauriane Batté, Pierre-Antoine Bretonnière, Susana Corti, Carlos Delgado-Torres, Marta Domínguez, Federico Fabiano, Ignazio Giuntoli, Jost von Hardenberg, Eroteida Sánchez-García, Verónica Torralba, and Deborah Verfaillie
Geosci. Model Dev., 15, 6115–6142, https://doi.org/10.5194/gmd-15-6115-2022, https://doi.org/10.5194/gmd-15-6115-2022, 2022
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CSTools (short for Climate Service Tools) is an R package that contains process-based methods for climate forecast calibration, bias correction, statistical and stochastic downscaling, optimal forecast combination, and multivariate verification, as well as basic and advanced tools to obtain tailored products. In addition to describing the structure and methods in the package, we also present three use cases to illustrate the seasonal climate forecast post-processing for specific purposes.
Olexandr Balyk, James Glynn, Vahid Aryanpur, Ankita Gaur, Jason McGuire, Andrew Smith, Xiufeng Yue, and Hannah Daly
Geosci. Model Dev., 15, 4991–5019, https://doi.org/10.5194/gmd-15-4991-2022, https://doi.org/10.5194/gmd-15-4991-2022, 2022
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Ireland has significantly increased its climate mitigation ambition, with a recent commitment to reduce greenhouse gases by an average of 7 % yr-1 in the period to 2030 and a net-zero target for 2050. This article describes the TIMES-Ireland model (TIM) developed to inform Ireland's energy system decarbonisation challenge. The paper also outlines a priority list of future model developments to better meet the challenge, taking into account equity, cost-effectiveness, and technical feasibility.
Thi Lan Anh Dinh and Filipe Aires
Geosci. Model Dev., 15, 3519–3535, https://doi.org/10.5194/gmd-15-3519-2022, https://doi.org/10.5194/gmd-15-3519-2022, 2022
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We proposed the leave-two-out method (i.e. one particular implementation of the nested cross-validation) to determine the optimal statistical crop model (using the validation dataset) and estimate its true generalization ability (using the testing dataset). This approach is applied to two examples (robusta coffee in Cu M'gar and grain maize in France). The results suggested that the simple models are more suitable in crop modelling where a limited number of samples is available.
Matthew Binsted, Gokul Iyer, Pralit Patel, Neal T. Graham, Yang Ou, Zarrar Khan, Nazar Kholod, Kanishka Narayan, Mohamad Hejazi, Son Kim, Katherine Calvin, and Marshall Wise
Geosci. Model Dev., 15, 2533–2559, https://doi.org/10.5194/gmd-15-2533-2022, https://doi.org/10.5194/gmd-15-2533-2022, 2022
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GCAM-USA v5.3_water_dispatch is an open-source model that represents key interactions across economic, energy, water, and land systems in a global framework, with subnational detail in the United States. GCAM-USA can be used to explore future changes in demand for (and production of) energy, water, and crops at the state and regional level in the US. This paper describes GCAM-USA and provides four illustrative scenarios to demonstrate the model's capabilities and potential applications.
Colm Duffy, Remi Prudhomme, Brian Duffy, James Gibbons, Cathal O'Donoghue, Mary Ryan, and David Styles
Geosci. Model Dev., 15, 2239–2264, https://doi.org/10.5194/gmd-15-2239-2022, https://doi.org/10.5194/gmd-15-2239-2022, 2022
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The GOBLIN (General Overview for a Backcasting approach of Livestock INtensification) model is a new high-resolution integrated
bottom-upbiophysical land use model capable of identifying broad pathways towards climate neutrality in the agriculture, forestry, and other land use (AFOLU) sector. The model is intended to bridge the gap between hindsight representations of national emissions and much larger globally integrated assessment models.
Samuel Lüthi, Gabriela Aznar-Siguan, Christopher Fairless, and David N. Bresch
Geosci. Model Dev., 14, 7175–7187, https://doi.org/10.5194/gmd-14-7175-2021, https://doi.org/10.5194/gmd-14-7175-2021, 2021
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In light of the dramatic increase in economic impacts due to wildfires, the need for modelling impacts of wildfire damage is ever increasing. Insurance companies, households, humanitarian organisations and governmental authorities are worried by climate risks. In this study we present an approach to modelling wildfire impacts using the open-source modelling platform CLIMADA. All input data are free, public and globally available, ensuring applicability in data-scarce regions of the Global South.
Lavinia Baumstark, Nico Bauer, Falk Benke, Christoph Bertram, Stephen Bi, Chen Chris Gong, Jan Philipp Dietrich, Alois Dirnaichner, Anastasis Giannousakis, Jérôme Hilaire, David Klein, Johannes Koch, Marian Leimbach, Antoine Levesque, Silvia Madeddu, Aman Malik, Anne Merfort, Leon Merfort, Adrian Odenweller, Michaja Pehl, Robert C. Pietzcker, Franziska Piontek, Sebastian Rauner, Renato Rodrigues, Marianna Rottoli, Felix Schreyer, Anselm Schultes, Bjoern Soergel, Dominika Soergel, Jessica Strefler, Falko Ueckerdt, Elmar Kriegler, and Gunnar Luderer
Geosci. Model Dev., 14, 6571–6603, https://doi.org/10.5194/gmd-14-6571-2021, https://doi.org/10.5194/gmd-14-6571-2021, 2021
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This paper presents the new and open-source version 2.1 of the REgional Model of INvestments and Development (REMIND) with the aim of improving code documentation and transparency. REMIND is an integrated assessment model (IAM) of the energy-economic system. By answering questions like
Can the world keep global warming below 2 °C?and, if so,
Under what socio-economic conditions and applying what technological options?, it is the goal of REMIND to explore consistent transformation pathways.
Phillip D. Alderman
Geosci. Model Dev., 14, 6541–6569, https://doi.org/10.5194/gmd-14-6541-2021, https://doi.org/10.5194/gmd-14-6541-2021, 2021
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This paper documents a framework for accessing crop model input data directly from spatially referenced file formats and running simulations in parallel across a geographic region using the Decision Support System for Agrotechnology Transfer Cropping Systems Model (a widely used crop model system). The framework greatly reduced the execution time when compared to running the standard version of the model.
Abhijeet Mishra, Florian Humpenöder, Jan Philipp Dietrich, Benjamin Leon Bodirsky, Brent Sohngen, Christopher P. O. Reyer, Hermann Lotze-Campen, and Alexander Popp
Geosci. Model Dev., 14, 6467–6494, https://doi.org/10.5194/gmd-14-6467-2021, https://doi.org/10.5194/gmd-14-6467-2021, 2021
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Timber plantations are an increasingly important source of roundwood production, next to harvest from natural forests. However, timber plantations are currently underrepresented in global land-use models. Here, we include timber production and plantations in the MAgPIE modeling framework. This allows one to capture the competition for land between agriculture and forestry. We show that increasing timber plantations in the coming decades partly compete with cropland for limited land resources.
Cited articles
Akhtar, M. K., Wibe, J., Simonovic, S. P., and MacGee, J.: Integrated assessment
model of society-biosphere-climate-economy-energy system, Environ. Modell.
Softw., 49, 1–21, https://doi.org/10.1016/j.envsoft.2013.07.006,
2013.
Akhtar, M. K., Simonovic, S. P., Wibe, J., and MacGee, J.: Future realities of
climate change impacts: An integrated assessment study of Canada, Int. J.
Global Warm., 17, 59–88, https://doi.org/10.1504/IJGW.2019.10017598, 2019.
Allen, C., Metternicht, G., and Wiedmann, T.: National pathways to the
Sustainable Development Goals (SDGs): A comparative review of scenario
modelling tools, Environ. Sci. Policy, 66, 199–207, https://doi.org/10.1016/j.envsci.2016.09.008, 2016.
Bauer, N., Baumstark, L., and Leimbach, M.: The REMIND-R model: The role of
renewables in the low-carbon transformation – first-best vs. second-best
worlds, Clim. Change, 114, 145–168, https://doi.org/10.1007/s10584-011-0129-2, 2012.
Bazilian, M., Rogner, H., Howells, M., Hermann, S., Arent, D., Gielen, D., Steduto, P., Mueller, A., Komor, P., Tol, R. S., and Yumkella, K. K.: Considering the energy,
water and food nexus: Towards an integrated modelling approach, Energ.
Policy, 39, 7896–7906, https://doi.org/10.1016/j.enpol.2011.09.039, 2011.
Breach, P.: Water Supply Capacity Development in the Context of Global
Change, Electronic Thesis and Dissertation Repository, 6930, https://ir.lib.uwo.ca/etd/6930 (last access: 8 June 2022), 2020.
Breach, P. A. and Simonovic, S. P.: ANEMI: A tool for global change
analysis, Plos One, 16, 0251489,
https://doi.org/10.1371/journal.pone.0251489, 2021.
Calvin, K. and Bond-Lamberty, B.: Integrated human-earth system modeling –
state of the science and future directions, Environ. Res. Lett., 13, 063006,
https://doi.org/10.1088/1748-9326/aac642, 2018.
Calvin, K., Patel, P., Clarke, L., Asrar, G., Bond-Lamberty, B., Cui, R. Y., Di Vittorio, A., Dorheim, K., Edmonds, J., Hartin, C., Hejazi, M., Horowitz, R., Iyer, G., Kyle, P., Kim, S., Link, R., McJeon, H., Smith, S. J., Snyder, A., Waldhoff, S., and Wise, M.: GCAM v5.1: representing the linkages between energy, water, land, climate, and economic systems, Geosci. Model Dev., 12, 677–698, https://doi.org/10.5194/gmd-12-677-2019, 2019.
Cao, L., Zhang, Y., and Shi, Y.: Climate change effect on hydrological
processes over the Yangtze River basin, Quaternary Int., 244, 202–210,
https://doi.org/10.1016/j.quaint.2011.01.004, 2011.
Chen, D., Xiong, F., Wang, K., and Chang, Y.: Status of research on Yangtze
fish biology and fisheries, Environ. Biol. Fish., 85, 337–357, https://doi.org/10.1007/s10641-009-9517-0, 2009.
Clark, W. A. V., Yi, D., and Zhang, X.: Do house prices affect fertility
behavior in China? An empirical examination, Int. Regional Sci. Rev., 43,
423–449, https://doi.org/10.1177/0160017620922885, 2020.
Davies, E. G. R. and Simonovic, S. P.: ANEMI: A new model for integrated
assessment of global change, Int. Environ. Rev., 11,
127–161, https://doi.org/10.1504/IER.2010.037903, 2010.
Davies, E. G. R. and Simonovic, S. P.: Global water resources modeling with
an integrated model of the social-economic-environmental system, Adv. Water
Resour., 34, 684–700, https://doi.org/10.1016/j.advwatres.2011.02.010, 2011.
Department of Energy at National Bureau of Statistics (DENBS): China Energy
Statistical Yearbook in 2015, China Statistics Press, Beijing, 2016 (in
Chinese).
Dermody, B. J., Sivapalan, M., Stehfest, E., van Vuuren, D. P., Wassen, M. J., Bierkens, M. F. P., and Dekker, S. C.: A framework for modelling the complexities of food and water security under globalisation, Earth Syst. Dynam., 9, 103–118, https://doi.org/10.5194/esd-9-103-2018, 2018.
Dettling, L. J. and Kearney, M. S.: House prices and birth rates: The impact of
the real estate market on the decision to have a baby, J. Public Econ., 1,
82–100, https://doi.org/10.1016/j.jpubeco.2013.09.009, 2014.
Dinar, A., Tieu, A., and Huynh, H.: Water scarcity impacts on global food
production, Glob. Food Secur., 23, 212–226, https://doi.org/10.1016/j.gfs.2019.07.007, 2019.
D'Odorico, P., Davis, K. F., Rosa, L., Carr, J. A., Chiarelli, D., Dell’Angelo, J., Gephart, J., MacDonald, G. K., Seekell, D. A., Suweis, S., and Rulli, M. C.: The global food©/energy©/water nexus, Rev. Geophys., 56,
456–531, https://doi.org/10.1029/2017RG000591, 2018.
European Commission: Energy in Europe, European energy to 2020: A scenario
approach, Belgium, Directorate general for energy, 1996.
Fang, Y., Zhang, W., Cao, J., and Zhu, L.: Analysis on the current situation
and development trend of energy resources in China, Conservation and
Utilization of Mineral Resources, 4, 34–42, 2018 (in Chinese).
Fiddaman, T. S.: Feedback complexity in integrated climate-economy models, PhD thesis,
Department of Operations Management and System Dynamics, Massachusetts
Institute of Technology, Cambridge, Massachusetts, 360 pp., 1997.
Fisher-Vanden, K. and Weyant, J.: The evolution of integrated assessment:
Developing the next generation of use-inspired integrated assessment tools,
Annu. Review Resour. Econ., 12, 471–487, https://doi.org/10.1146/annurev-resource-110119-030314, 2020.
Forrester, J. W.: Industrial dynamics, Cambridge The M.I.T. press, Cambridge, MA, https://ocul-uwo.primo.exlibrisgroup.com/permalink/01OCUL_UWO/r0c2m8/alma991020555339705163 (last access: 8 June 2022), 1961.
Fu, B.: Promoting geography for sustainability, Geogr.
Sustain., 1, 1–7, https://doi.org/10.1016/j.geosus.2020.02.003, 2020.
Giorgi, F., Im, E. S., Coppola, E., Diffenbaugh, N. S., Gao, X. J., Mariotti, L., and Shi, Y.: Higher hydroclimatic
intensity with global warming, J. Climate, 24, 5309–5324, https://doi.org/10.1175/2011JCLI3979.1, 2011.
Gilbert, D. J., McKenzie, J. R., Davies, N. M., and Field, K. D.: Assessment of
the SNA 1 stocks for the 1999–2000 fishing year, New Zealand Fisheries
Assessment Report, 38, 52, 2000.
Goudriaan, J. and Ketner, P.: A simulation study for the global carbon
cycle, including man's impact on the biosphere, Clim. Change, 6,
167–192, 1984.
Gu, H., Yu, Z., Wang, G., Wang, J., Ju, Q., Yang, C., and Fan, C.: Impact of climate change on
hydrological extremes in the Yangtze river basin, China, Stoch. Env. Res.
Risk A., 29, 693–707, https://doi.org/10.1007/s00477-014-0957-5, 2015.
Henze, M. and Comeau, Y.: Wastewater Characterization, in: Biological
Wastewater Treatment: Principles Modelling and Design, IWA Publishing,
London, UK, 33–52, 2008.
Hertwich, E. G., Gibon, T., Bouman, E. A., Arvesen, A., Suh, S., Heath, G. A., Bergesen, J. D., Ramirez, A., Vega, M. I., and Shi, L.: Integrated life-cycle
assessment of electricity-supply scenarios confirms global environmental
benefit of low-carbon technologies, P. Natl. Acad. Sci. USA, 112, 6277–6282,
https://doi.org/10.1073/pnas.1312753111, 2015.
Holman, I. P., Rounsevell, M. D. A., Cojacaru, G., Shackley, S., McLachlan, C., Audsley, E., Berry, P. M., Fontaine, C., Harrison, P. A., Henriques, C., and Mokrech, M.: The concepts
and development of a participatory regional integrated assessment tool,
Clim. Change, 90, 5–30, https://doi.org/10.1007/s10584-008-9453-6, 2008.
Hopwood, B., Mellor, M., and O'Brien, G.: Sustainable development: Mapping
different approaches, Sustain. Dev., 13, 38–52, https://doi.org/10.1002/sd.244, 2005.
Hui, E., Xian, Z., and Jiang, H.: Housing price, elderly dependency and
fertility behaviour, Habitat Int., 36, 304–311, https://doi.org/10.1016/j.habitatint.2011.10.006, 2012.
Jeon, S., Roh, M., Oh, J., and Kim, S.: Development of an integrated
assessment model at provincial level: GCAM-Korea, Energies, 13, 2565,
https://doi.org/10.3390/en13102565, 2020.
Jia, B., Zhou, J., Zhang, Y., Tian, M., He, Z., and Ding, X.: System dynamics model for the
coevolution of coupled water supply – power generation – environment
systems: Upper Yangtze river Basin, China, J. Hydrol., 593, 125892,
https://doi.org/10.1016/j.jhydrol.2020.125892, 2021.
Jiang, H. and Simonovic, S. P.: ANEMI_Yangtze – A regional
integrated assessment model for the Yangtze Economic Belt in China, Water
Resources Research Report no. 110, Facility for Intelligent Decision
Support, Department of Civil and Environmental Engineering, London, Ontario,
Canada, 75 pp., ISBN 978-0-7714-3155-5, 2021.
Jiang, H., Simonovic, S. P., Yu, Z., and Wang, W. G.: System dynamics simulation
model for flood management of the three gorges reservoir, J. Water Res.
Plan. Man., 146, 05020009, https://doi.org/10.1061/(ASCE)WR.1943-5452.0001216, 2020.
Jiang, H., Simonovic, S. P., and Yu, Z.: ANEMI_Yangtze (v1.0), Zenodo [code and data set], https://doi.org/10.5281/zenodo.4764138, 2021a.
Jiang, H., Simonovic, S. P., Yu, Z., and Wang, W. G.: What are the main
challenges facing the sustainable development of China's Yangtze Economic
Belt in the future? An integrated view, Environ. Res. Commun., 3, 115005,
https://doi.org/10.1088/2515-7620/ac35bd, 2021b.
Ju, H., Liu, Q., Li, Y., Long, X., Liu, Z., and Lin, E.: Multi-stakeholder efforts to adapt to
climate change in China's agricultural sector, Sustainability, 12, 8076,
https://doi.org/10.3390/su12198076, 2020.
Klein, J. T.:
Transdisciplinarity: Joint problem solving among science, technology, and
society: An effective way for managing complexity, Springer Science &
Business Media, Basel, Switzerland, Boston, MA, ISBN 9783764362485, 2001.
Kong, L., Zheng, H., Rao, E., Xiao, Y., Ouyang, Z., and Li, C.: Evaluating indirect and direct
effects of eco-restoration policy on soil conservation service in Yangtze
River Basin, Sci. Total Environ., 631, 887–894, https://doi.org/10.1016/j.scitotenv.2018.03.117, 2018.
Kriegler, E., Bauer, N., Popp, A., Humpenöder, F., Leimbach, M., Strefler, J., Baumstark, L., Bodirsky, B. L., Hilaire, J., Klein, D., Mouratiadou, I., Weindl, I., Bertram, C., Dietrich, J.-P., Luderer, G., Pehl, M., Pietzcker, R., Piontek, F., Lotze-Campen, H., Biewald, A., Bonsch, M., Giannousakis, A., Kreidenweis, U., Müller, C., Rolinski, S., Schultes, A., Schwanitz, J., Stevanovic, M., Calvin, K., Emmerling, J., Fujimori, S., and Edenhofer, O.: Fossil-fueled development
(SSP5): An energy and resource intensive scenario for the 21st century,
Global Environ. Chang., 42, 297–315,
https://doi.org/10.1016/j.gloenvcha.2016.05.015, 2017.
Lee, E. S.: A Theory of Migration, Demography, 3, 47–57, 1966.
Lei, G., Fu, C., Zhang, L., Zeng, X., and Wang, W.: The changes in population floating
and their influencing factors in China based on the sixth census, Northwest
Population Journal, 34, 1–8, https://doi.org/10.15884/j.cnki.issn.1007-0672.2013.05.017, 2013 (in
Chinese).
Li, Y., Acharya, K., and Yu, Z.: Modeling impacts of Yangtze River water
transfer on water ages in Lake Taihu, China, Ecol. Eng., 37, 325–334,
https://doi.org/10.1016/j.ecoleng.2010.11.024, 2011.
Li, Z., He, Y., Pu, T., Jia, W., He, X., Pang, H., Zhang, N., Liu, Q., Wang, Sh., Zhu, G., Wang, Sh., Chang, L., Du, J., and Xin, H.: Changes of climate, glaciers and runoff
in China's monsoonal temperate glacier region during the last several
decades, Quaternary Int., 218, 13–28, https://doi.org/10.1016/j.quaint.2009.05.010, 2010.
Liu, J. G., Dietz, T., Carpenter, S. R., Alberti, M., Folke, C., Moran, E., Pell, A. N., Deadman, P., Kratz, T., Lubchenco, J., Ostrom, E., Ouyang, Z., Provencher, W., Redman, C. L., Schneider, S. H., and Taylor, W. W.: Complexity of coupled
human and natural systems, Science, 317, 1513–1516, https://doi.org/10.1126/science.1144004, 2007.
Liu, L. and Ding, Y.: Hydraulic resources and hydropower planning in the
Yangtze River Basin, Yangtze River, 44, 69–71, 2013 (in Chinese).
Loulou, R.: ETSAP-TIAM: The TIMES integrated assessment model. Part II:
Mathematical formulation, Comput. Manag. Sci., 5, 41–66, https://doi.org/10.1007/s10287-007-0045-0, 2007.
Ma, L. and Yu, Z.: Influencing factors of Chinese average life expectancy,
Economic Research Guide, 01, 161–162, 2009.
Mackenzie, F. T., Ver, L. M., Sabine, C., and Lane, M.: C, N, P, S global
biogeochemical cycles and modeling of global change, in: Interactions of C, N, P
and S Biogeochemical Cycles and Global Change, edited by: Wollast, R., Mackenzie, F. T., and Chou, L., North Atlantic Treaty Organization Scientific Affairs Division, NATO advanced research workshop on interactions of C, N, P, and S biogeochemical cycles, Springer Verlag, New York, 1–61, ISBN 0387531262, 1991.
Matsuoka, Y., Kainuma, M., and Morita, T.: Scenario analysis of global
warming using the Asian-Pacific integrated model (AIM), Energ. Policy, 23,
357–371, https://doi.org/10.1016/0301-4215(95)90160-9, 1995.
Meadows, D. L.: The Dynamics of growth in a finite world, Wright-Allen Press, Inc. Cambrigde, Massachusetts, ISBN 0960029443,
1974.
Messner, S. and Schrattenholzer, L.: MESSAGE-MACRO: linking an energy
supply model with a macroeconomic module and solving it iteratively, Energy,
25, 267–282, https://doi.org/10.1016/S0360-5442(99)00063-8,
2000.
Messner, S. and Strubegger, M.: User's Guide for MESSAGE III, Working Paper
WP-95-069, International Institute for Applied Systems Analysis (IIASA),
Laxenburg, Austria, 164 pp., 1995.
MIIT: Innovation-driven industrial transformation and upgrading plan for the
Yangtze River Economic Belt, Ministry of Industry and Information Technology
of the People's Republic of China, 2016.
National Development and Reform Commission (NDRC): Development and planning
outline of the Yangtze River Economic Belt officially released,
http://www.sc.gov.cn/10462/10758/10760/10765/2016/9/20/10396398.shtml (last access: 8 June 2022), 2016.
Niva, V., Cai, J., Taka, M., Kummu, M., and Varis, O.: China's sustainable
water-energy-food nexus by 2030: Impacts of urbanization on sectoral water
demand, J. Clean. Prod., 251, 119755, https://doi.org/10.1016/j.jclepro.2019.119755, 2020.
Nordhaus, W. D. and Boyer, J.: Warming the world: Economic models of global
warming, The MIT Press, Cambridge, Massachusetts, USA, ISBN 0-262-14071-3, 2000.
Pautrel, X.: Pollution and life expectancy: How environmental policy can
promote growth, Ecol. Econ., 68, 1040–1051, https://doi.org/10.1016/j.ecolecon.2008.07.011, 2009.
Pedercini, M., Arquitt, S., Collste, D., and Herren, H.: Harvesting synergy from
sustainable development goal interactions, P. Natl. Acad. Sci. USA, 46,
23021–23028, https://doi.org/10.1073/pnas.1817276116, 2019.
Qin, B. Q., Wang, X. D., Tang, X. M., Feng, S., and Zhang, Y. L.: Drinking water crisis
caused by eutrophication and cyanobacterial bloom in Lake Taihu: cause and
measurement, Adv. Earth Sci., 22, 896–906, https://doi.org/10.3321/j.issn:1001-8166.2007.09.003, 2007 (in Chinese).
Qu, W., Barney, G., Symalla, D., and Martin, L.: Threshold 21: National
sustainable development model, Integrated Global Models of Sustainable
Development, 2, 78–87, 1995.
Qu, W., Shi, W., Zhang, J., and Liu, T.: T21 China 2050: A tool for national
sustainable development planning, Geogr. Sust., 1, 33–46,
https://doi.org/10.1016/j.geosus.2020.03.004, 2020.
Shen, J.: Increasing internal migration in China from 1985 to 2005:
Institutional versus economic drivers, Habitat Int., 39, 1–7, https://doi.org/10.1016/j.habitatint.2012.10.004, 2013.
Shi, W., Ou, Y., Smith, S. J., Ledna, C. M., Nolte, C. G., and Loughlin, D. H.: Projecting state-level air
pollutant emissions using an integrated assessment model: GCAM-USA, Appl.
Energ., 208, 511–521, https://doi.org/10.1016/j.apenergy.2017.09.122, 2017.
Shiklomanov, I. A.: Appraisal and assessment of world water resources, Water
Int., 25, 11–32, https://doi.org/10.1080/02508060008686794,
2000.
Simonovic, S. P.: Global water dynamics: Issues for the 21st century,
J. Water Sci. Technol., 45, 53–64, https://doi.org/10.2166/wst.2002.0143, 2002a.
Simonovic, S. P.: World water dynamics: Global modeling of water resources,
J. Environ. Manage., 66, 249–267, https://doi.org/10.1006/jema.2002.0585, 2002b.
Simonovic, S. P.: Managing water resources: Methods and tools for a systems
approach, Earthscan James & James, London, ISBN 9231040782, 2009.
Song, Q.: Study on the wind resource distribution and wind power planning in
China, North China Electric Power University, 2013 (in Chinese).
State Grid Energy Research Institution (SGERI), and China Nuclear Power
Development Center (CNPD): Research on nuclear power development planning in
China, China Atomic Energy Press, 2019 (in Chinese).
Stehfest, E., van Vuuren, D., Kram, T., and Bouwman, L.: Integrated assessment of
global environmental change with IMAGE 3.0: Model description and policy
applications, PBL Netherlands Environmental Assessment Agency, ISBN
978-94-91506-71-0, 2014.
Su, B., Huang, J., Zeng, X., Gao, C., and Jiang, T.: Impacts of climate change on
streamflow in the upper Yangtze River basin, Clim. Change, 141, 533–546,
https://doi.org/10.1007/s10584-016-1852-5, 2017.
Su, M.: Research on the coordinated development of energy in the Yangtze
River Economic Zone, Macroeconomic Manage., 12, 37–41, 2019 (in Chinese).
Su, Y., Tesfazion, P., and Zhao, Z.: Where are the migrants from? Inter- vs. intra-provincial rural-urban migration in China, China Econ. Rev., 47,
142–155, https://doi.org/10.1016/j.chieco.2017.09.004, 2018.
Sullivan, P., Krey, V., and Riahi, K.: Impacts of considering electric
sector variability and reliability in the MESSAGE model, Energy Strateg.
Rev., 1, 157–163, https://doi.org/10.1016/j.esr.2013.01.001,
2013.
van Beek, L., Hajer, M., Pelzer, P., van Vuuren, D., and Cassen, C.: Anticipating futures
through models: the rise of Integrated Assessment Modelling in the climate
science-policy interface since 1970, Global Environ. Chang., 65, 102191,
https://doi.org/10.1016/j.gloenvcha.2020.102191, 2020.
van Vuuren, D. P., Kok, M., Lucas, P. L., Prins, A. G., Alkemade, R., van den Berg, M., Bouwman, L., van der Esch, S., Jeuken, M., Kram, T., and Stehfest, E.: Pathways to achieve a
set of ambitious global sustainability objectives by 2050: Explorations
using the IMAGE integrated assessment model, Technol. Forecast. Soc., 98,
303–323, https://doi.org/10.1016/j.techfore.2015.03.005, 2015.
Wang, H.: Yangtze Yearbook, Changjiang Water Resources Commission of Ministry
of Water Resources, 2015 (in Chinese).
Wang, H., Liu, L., Yang, F., and Ma, J.: System dynamics modeling of China's
grain forecasting and policy simulation, J. Syst. Simul., 21,
3079–3083, 2009 (in Chinese).
Wang, Z., Nguyen, T., and Westerhoff, P.: Food-energy-water analysis at
spatial scales for districts in the Yangtze river basin (China), Environ.
Eng. Sci., 36, 789–797, https://doi.org/10.1089/ees.2018.0456,
2019.
Xie, H. and Wang, B.: An empirical analysis of the impact of agricultural
product price fluctuations on China's grain yield, Sustainability, 9, 906,
https://doi.org/10.3390/su9060906, 2017.
Xu, X., Yang, G., Tan, Y., Liu, J., and Hu, H.: Ecosystem services trade-offs and
determinants in China's Yangtze River Economic Belt from 2000 to 2015, Sci.
Total Environ., 634, 1601–1614, https://doi.org/10.1016/j.scitotenv.2018.04.046, 2018.
Yangtze River Water Resources Commission (YRWRC): Water resources bulletin
of the Yangtze river basin and the southwest rivers in China 2015, Yangtze
River Press, Wuhan, 2016 (in Chinese).
Yao, G., Gao, Z., and Li, X.: Evaluation of coal resources bearing capacity
in China, China Mining Magazine, 29, 1–7, 2020 (in Chinese).
Ye, L., Wei, X., Li, Z., Yang, P., Wu, W., Yang, G., Fu, Y., Zou, J., Chen, Z., Ranst, E. V., and Tang, H.: Climate change impact on China food
security in 2050, Agron. Sustain. Dev., 33, 363–374, https://doi.org/10.1007/s13593-012-0102-0, 2013.
Yi, B. L., Yu, Z. T., and Liang, Z. S.: Gezhouba Water Control Project and
four famous fishes in the Yangtze River, Hubei Science and Technology
Press, Wuhan, edited by: Huang, X., ISBN 7-5352-0334-2/s.36, 1988, (in Chinese with English abstract).
Yu, S., Yarlagadda, B., Siegel, J. E., Zhou, S., and Kim, S.: The role of nuclear in
China's energy future: Insights from integrated assessment, Energ. Policy,
139, 111344, https://doi.org/10.1016/j.enpol.2020.111344, 2020.
Yu, Z., Gu, H., Wang, J., Xia, J., and Lu, B.: Effect of projected climate change on
the hydrological regime of the Yangtze River Basin, China, Stoch. Env. Res.
Risk A., 32, 1–16, https://doi.org/10.1007/s00477-017-1391-2,
2018.
Zeng, Y. and Hesketh, T.: The effects of China's universal two-child
policy, The Lancet, 388, 1930–1938, https://doi.org/10.1016/S0140-6736(16)31405-2, 2016.
Zhang, C., Zhong, L., Fu, X., Wang, J., and Wu, Z.: Revealing water stress by the
thermal power industry in China based on a high spatial resolution water
withdrawal and consumption inventory, Environ. Sci. Technol., 50, 1642–1652,
https://doi.org/10.1021/acs.est.5b05374, 2016.
Zhang, H., Li, J. Y., Wu, J. M., Wang, C. Y., Du, H., Wei, Q. W., and Kang, M.: Ecological effects of the first
dam on Yangtze main stream and future conservation recommendations: A review
of the past 60 years, Appl. Ecol. Env. Res., 15, 2081–2097, https://doi.org/10.15666/aeer/1504_20812097, 2017.
Zhang, H., Kang, M., Shen, L., Wu, J., Li, J., Du, H., Wang, C., Yang, H., Zhou, Q., Liu, Z., Gorfine, H., and Wei, Q.: Rapid change in Yangtze fisheries
and its implications for global freshwater ecosystem management, Fish Fish.,
21, 601–620, https://doi.org/10.1111/faf.12449, 2020.
Zhao, F. and Fan, Z.: The inhibitory effect of high housing prices on
population inflows in the megacities: Based on the empirical evidence from
the four cities of Beijing, Shanghai, Guangzhou and Shenzhen, Urban Studies,
26, 41–48, 2019 (in Chinese).
Zhu, R., Ma, S., Yang, Z., and Zhou, C.: Atlas of solar energy resources by
province in China, China Meteorological Administration, Beijing, 2006 (in
Chinese).
Short summary
The Yangtze Economic Belt is one of the most dynamic regions of China. The fast urbanization and strong economic growth in the region pose severe challenges for its sustainable development. To improve our understanding of the interactions among coupled human–natural systems in the Belt and to provide the foundation for science-based policy-making for the sustainable development of the Belt, we developed an integrated system-dynamics-based simulation model (ANEMI_Yangtze) for the Belt.
The Yangtze Economic Belt is one of the most dynamic regions of China. The fast urbanization and...
