Comprehensive Scenario Research Articles

Multi-scenario prediction and path optimization of industrial carbon unlocking in China

China's industry is facing a carbon lock-in (CLI) dilemma. Based on the complexity and dynamics of CLI, exploring diversified unlocking paths is an important way to achieve emission reduction goals. This paper innovatively applies system dynamics (SD) to the study of CLI prediction and unlocking path, and systematically constructs an industrial CLI SD model, trying to break the positive feedback mechanism of CLI through multiple causality and feedback chains. This paper simulates and predicts the changing trend of the CLI level of China's industry and 8 major subsectors from 2020 to 2050. At the same time, the random forest algorithm is used to select the regulatory variables of policy analysis. Compared with the previous research methods, the accuracy and objectivity of the selection of regulatory variables are improved, so as to test the effectiveness of the unlocking path under each scenario. The results show that (1) the whole industry faces a serious CLI problem and is still in a deep lock-in state. From the perspective of subsectors, the light, electromechanical, and textile industries have achieved unlocking; the oil and extractive industries are in a moderately lock-in state; the chemical, steel, and power industries are in a deep lock-in state; and the CLI situation is serious. (2) The results of the random forest algorithm show that R&D investment, the proportion of fixed asset investments in the energy industry, car sales, energy structure, and carbon emission industry structure are the most significant factors affecting CLI in each subsystem. (3) Compared with the existing economic development model, the technological, institutional, social, and comprehensive unlocking scenarios can all enable industry to achieve carbon peak and carbon unlocking in advance. However, the effect of each scenario is as follows: comprehensive unlocking scenario > technological unlocking scenario > institutional unlocking scenario > social unlocking scenario. (4) The unlocking times of the oil, chemical, steel, and power industries are relatively late in each scenario. To realize carbon unlocking in industry, these four areas should be focused on in the future. This study helps policymakers formulate reasonable policies to accelerate industrial carbon unlocking and promote the implementation of the “dual carbon” strategy.

Accuracy of ChatGPT-Generated Information on Head and Neck and Oromaxillofacial Surgery: A Multicenter Collaborative Analysis.

To investigate the accuracy of Chat-Based Generative Pre-trained Transformer (ChatGPT) in answering questions and solving clinical scenarios of head and neck surgery. Observational and valuative study. Eighteen surgeons from 14 Italian head and neck surgery units. A total of 144 clinical questions encompassing different subspecialities of head and neck surgery and 15 comprehensive clinical scenarios were developed. Questions and scenarios were inputted into ChatGPT4, and the resulting answers were evaluated by the researchers using accuracy (range 1-6), completeness (range 1-3), and references' quality Likert scales. The overall median score of open-ended questions was 6 (interquartile range[IQR]: 5-6) for accuracy and 3 (IQR: 2-3) for completeness. Overall, the reviewers rated the answer as entirely or nearly entirely correct in 87.2% of cases and as comprehensive and covering all aspects of the question in 73% of cases. The artificial intelligence (AI) model achieved a correct response in 84.7% of the closed-ended questions (11 wrong answers). As for the clinical scenarios, ChatGPT provided a fully or nearly fully correct diagnosis in 81.7% of cases. The proposed diagnostic or therapeutic procedure was judged to be complete in 56.7% of cases. The overall quality of the bibliographic references was poor, and sources were nonexistent in 46.4% of the cases. The results generally demonstrate a good level of accuracy in the AI's answers. The AI's ability to resolve complex clinical scenarios is promising, but it still falls short of being considered a reliable support for the decision-making process of specialists in head-neck surgery.

Local Food Entrepreneurship in Rural India: Modelling the Challenges

Local food entrepreneurship plays a vital role in promoting and distributing regional foods. To link local food with the market, there is a need to develop local food systems that promote and support local food, its distribution and consumption. Local food entrepreneurs are constrained due to various factors prevailing in the entire rural ecosystem, which hinders their prospects of business expansion. This study focussed on identifying the commercially feasible local food products that can be produced and marketed by local entrepreneurs. Also, this study is an effort towards identifying and analysing the challenges perceived by local food entrepreneurs in rural India. The challenges were identified through a literature review and the personal interviews of the rural entrepreneurs and were then modelled through the DEMATEL (decision-making trial and evaluation laboratory) approach. The modelling of challenges helped in identifying the priority areas, based on which focused strategies were suggested for the promotion of local food entrepreneurs. From this study, it emerged that product quality issues, lack of buyers and inconsistent government policies are the most significant challenges perceived by entrepreneurs. This study also includes resource mapping for the local entrepreneurs to present a comprehensive scenario of the prevailing ecosystem.

Simulation and Prediction of Greenhouse Gas Emissions from Beef Cattle

Greenhouse gas emission is a key issue in the sustainable development of agriculture. To effectively predict the greenhouse gas emissions of beef cattle, a model is proposed based on system dynamics and greenhouse gas emission calculation methods, and a scenario is set as a ‘Straw to Beef’ project in Jilin Province. The model was built on a baseline emission scenario (feed precision: 60%, breeding environment: dry fattening farm, corn straw utilization: burning straw), with single- and comprehensive emission reduction scenarios considered, predicting trends and reduction potentials in greenhouse gas emissions from cattle breeding and straw burning in Jilin Province from 2013 to 2028, measured in CO2-eq (CO2 equivalent). The model also explored the impact of 11 controllable variables on greenhouse gas emissions. Results showed that (1) From 2013 to 2022, greenhouse gas emissions from straw burning and cattle breeding in Jilin Province increased significantly and had an annual growth rate of 6.51% in 2020. (2) Single emission reduction scenarios showed an increasing trend in greenhouse gas emissions, while comprehensive emission reduction scenarios showed a decreasing trend. Among them, the S2.2.1 scenario (feed precision: 80%, breeding environment: livestock barn manure pit, corn straw utilization: burning straw) had the strongest emission reduction ability in the single reduction scenario, the S3.2.2 scenario (feed precision: 80%, breeding environment: livestock barn manure pit, corn straw utilization: Feed-processing straw) had the strongest emission reduction ability in the comprehensive reduction scenario, reducing emissions by 5.10% and 69.24%, respectively, compared to the baseline scenario. This suggests that the comprehensive emission reduction scenarios which utilized straw resources reasonably can greatly reduce agricultural greenhouse gas emissions. (3) The optimal emission reduction scenario indicated that the higher the proportion of digestible energy in beef cattle’s total energy intake, the more perfect the fecal treatment process, and the higher the utilization rate of straw feed, the lower the greenhouse gas emissions. Therefore, to effectively reduce greenhouse gas emissions from cattle breeding and straw burning in Jilin Province, it is important to implement comprehensive emission reduction scenarios prioritizing the efficient utilization of straw resources and improving beef cattle management practices.

Assessing the impact of urban land expansion on ecosystem carbon storage: A case study of the Changzhutan metropolitan area, China

The extension of urban development can encroach onto ecologically important land, such as forests and farmland, and have a significant impact on regional ecosystem carbon storage. Although there has been extensive research on the carbon storage response to land use changes, limited exploration has been conducted on the changes in ecosystem carbon storage resulting from the expansion of construction land.. In the current research, we analyzed the characteristics involved in the growth related to built-up space in the Changzhutan metropolitan area from 1990 to 2020. Using the InVEST model, we evaluated the resulting effects on ecological carbon sequestration, and using the PLUS model, we simulated the effects of building land expansion under four scenarios: natural development, farmland protection, ecological protection, and comprehensive development. Additionally, our aim was to quantify the possible implications of the development of built-up areas on regional carbon storage. (1) The Changzhutan metropolitan area expanded its construction land by 721.58 km2 from 1990 to 2020, with the expansion mainly concentrated in the urban fringe areas, and the land type mainly changed from forests and farmland to construction land. (2) The ecosystem carbon sequestration in the Changsha-Zhuzhou-Xiangtan metropolitan area decreased by 22.66 × 106 t from 1990 to 2020, with the most significant decrease occurring from 2005 to 2010 when the expansion of construction land was 284.43 km2. (3)By 2030, the Changzhutan metropolitan area is projected to expand its construction land by 312.05 km2, 175.65 km2, 68.21 km2, and 68.90 km2 under the scenarios of natural development, farmland protection, ecological protection, and comprehensive development, respectively. Land use change in each scenario is expected to cause carbon storage losses of 10.01 × 106 t, 11.01 × 106 t, 2.07 × 106 t, and 1.95 × 106t, compared to 2020. (4) Over the investigation time span, expansion of construction ground in metropolitan Changzhutan had a negative impact on regional carbon storage, reaching a stable state from 2005 to 2020, and the effect pertaining to growth from the area of development upon the carbon accumulation of regional ecosystems under the comprehensive protection scenario in 2030 was −0.46. Considering the spatial heterogeneity analysis of regional carbon storage, this scenario would substantially upgrade the functional area surrounding the region and increase the biological system stabilization, which is conducive to achieving carbon neutrality goals.

Optimization Modelling of the Decarbonization Scenario of the Total Energy System of Kazakhstan until 2060

This research article provides a comprehensive scenario analysis of key structural changes in Kazakhstan’s fuel and energy complex subsectors until 2060, focusing on decarbonization efforts. The background places the issue of decarbonization in a broader context, considering the country’s vast size and sparse population. The study’s purpose involves analyzing the development of the climate agenda by comparing two scenarios: a “reference” scenario without decarbonization measures and a carbon neutrality scenario until 2060 (CN2060). A mathematical technical-economic model based on the TIMES paradigm (The Integrated MARKAL-EFOM System) serves as the method to optimize and simulate Kazakhstan’s energy system. The main findings reveal sets of policies, standards, and legislative, economic, and political decisions that are required to achieve CN2060. Additionally, the integration of a low-carbon policy, sectoral and cross-cutting approaches, the impact of the coronavirus crisis, the Russia-Ukraine conflict, and energy security issues receive a discussion. The article concludes with projected shares of generation and investment in renewable energy sources (RES) necessary for attaining CN2060. This work offers novel insights into challenges and opportunities for Kazakhstan’s transition to a low-carbon economy.

An extendable maneuver management framework with fault‐tolerant mechanism for vehicle platoon control system in highway scenario

AbstractVehicle platoons can encounter many complex scenarios in practice that were not considered in the design, which reveals the need to add new maneuvers. Platoon control system will face the challenge of the lack of maneuver scalability in practical applications. To address this problem, this study introduces an extendable maneuver management framework with fault‐tolerant mechanism on the basis of the hierarchical architecture for the platoon control system. Maneuvers and roles are two dimensions, based on which the management strategies are decoupled. They enable each vehicle in the platoon to execute management strategies of various maneuvers and make it possible to expanding new behaviors into existing strategies. The fault‐tolerant mechanism is designed as a maneuver triggered by hardware failures to remain safe before taking over. Furthermore, three typical maneuvers are selected for case studies to illustrate the management strategies in this framework. Finally, a comprehensive simulation scenario integrating different maneuvers is designed and a real‐world implementation using micro‐vehicles is conducted. The results demonstrate that the proposed two‐dimensional framework could effectively address various maneuvers and satisfy the computational real‐time requirements.

Recent Progress of Advanced Materials for Triboelectric Nanogenerators.

Triboelectric nanogenerators (TENGs) have received intense attention due to their broad application prospects in the new era of internet of things (IoTs) as distributed power sources and self-powered sensors. Advanced materials are vital components for TENGs, which decide their comprehensive performance and application scenarios, opening up the opportunity to develop efficient TENGs and expand their potential applications. In this review, a systematic and comprehensive overview of the advanced materials for TENGs is presented, including materials classifications, fabrication methods, and the properties required for applications. In particular, the triboelectric, friction, and dielectric performance of advanced materials is focused upon and their roles in designing the TENGs are analyzed. The recent progress of advanced materials used in TENGs for mechanical energy harvesting and self-powered sensors is also summarized. Finally, an overview of the emerging challenges, strategies, and opportunities for research and development of advanced materials for TENGs is provided.

Greenhouse gas emissions associated with plastics in China from 1950 to 2060

The unprecedented rise of plastics has caused substantial greenhouse gas (GHG) emissions. In this study, material flow analysis and GHG accounting models were integrated to estimate the GHG emissions of plastics in China from 1950 to 2020, and the dynamic evolution from 2021 to 2060 was tracked. The cumulative GHG emissions were 5544.0 Mt CO2eq from 1950 to 2020, and 496.8 Mt CO2eq of GHG were emitted in 2020. Monomer production stage had the highest GHG emissions (58.6%) and electricity consumption was the major emission source (69.0%). GHG emissions of baseline and comprehensive scenarios would reach a peak in 2040 and 2030, respectively. Neutral scenario was the only scenario that achieved carbon neutrality by 2060. GHG emission reduction requires reducing plastic demand, improving waste recycling, and adopting bio-based plastics and renewable energy. This study scientifically explored the path of carbon peak and carbon neutrality to combat climate change.

Case Article—Creating a Brick Empire Through Data Visualization and Analytics

This case study provides a comprehensive decision-making scenario that takes students through all three types of analytics—descriptive, predictive, and prescriptive—to provide recommendations to a decision maker. The scenario focuses on an individual investor who is purchasing LEGO sets from retailers with the goal of selling them for a higher price on the aftermarket in a few years once they retire from shelves. Students must create visualizations to generate insights from the data and develop a regression model to identify sets that represent value investment opportunities. In the extension case they must take their estimated values and optimize the decisions of which sets to purchase to meet the decision maker’s investment goals using an integer program. Students also have the opportunity to develop soft skills in problem solving and communicating results and dealing with missing data points in a data set that is larger than standard textbook data sets but is still a manageable size for introductory students. The open-ended instructions make the case appropriate for a wide range of students from the introductory undergraduate level to the advanced graduate level. Supplemental Material: Supplemental materials are available at https://doi.org/10.1287/ited.2023.0288ca . The Teaching Note and data files are available at https://www.informs.org/Publications/Subscribe/Access-Restricted-Materials .

Integrating energy retrofit with seismic upgrades to future-proof built heritage: Case studies of unreinforced masonry buildings in Aotearoa New Zealand

Deep energy retrofit can improve historic buildings’ indoor environmental quality and protect them from decay and obsolescence while reducing their energy use and related greenhouse gas emissions. Although this practice has been growing internationally, in Aotearoa New Zealand there are currently no policies or initiatives to encourage energy retrofit in historic buildings and no substantial examples of projects. Most retrofits currently focus on much-needed earthquake strengthening, due to high seismic risks and national policies which mandate all existing earthquake-prone buildings to be either structurally retrofitted or demolished over the next decades. As seismic upgrade projects are widespread, this study explores the potential of applying energy retrofit concurrently with seismic strengthening, with a focus on unreinforced masonry (URM) – the main type of earthquake-prone historic construction in the country. The research investigates three case studies of listed heritage URM buildings using Post-Occupancy Evaluation and simulation. Their current performance was investigated, and retrofit scenarios were analysed through energy and hygrothermal simulation, utilising the EnerPHit standard as a guide. The energy models demonstrated a potential reduction of up to 92% in heating demand when comparing the most comprehensive retrofit scenario with the baseline in the coldest climate. The potential energy savings from each intervention were balanced against their heritage impact, based on the standard EN16883:2017. The study provides a methodology for balancing several considerations in integrated retrofit to make historic buildings more resilient not only to seismic threats, but also to a changing climate, while keeping a respectful approach to heritage.

Carrier‐Modulated Anomalous Electron Transport in Electrolyte‐Gated SrTiO3

The anomalous transport phenomena and underlying mechanism of SrTiO3 have been long term concerned, including the Kondo physics and anomalous Hall effects to be discussed herein. Nevertheless, a clarification of the physical origins for these phenomena and their intertransitions upon varying carrier density remain to be an issue, due to the limited modulation of carrier density. Herein, the intriguing transport behaviors of electrolyte‐gated SrTiO3 in the field‐effect transistor geometry are investigated, which allows a relatively wide carrier density window. It is revealed that the remarkable Kondo‐like resistance upturn, identified at relatively low carrier density, becomes gradually disappeared and replaced by the emerging nonlinear Hall resistance with increasing gating voltage, indicating the interesting gating‐controlled transport behaviors. The detailed discussions on the underlying physics suggest that the gating‐controlled transport can be well described by the multiband transport model taking into account magnetic scattering in the channel layer, a comprehensive scenario for the emergent transport effects in carrier‐doped SrTiO3. The present work provides a promising platform for exploring novel quantum materials phenomena in SrTiO3 and analogous systems.

Spatio-temporal evolution and prediction of carbon storage in Kunming based on PLUS and InVEST models.

Carbon storage is a critical ecosystem service provided by terrestrial environmental systems that can effectively reduce regional carbon emissions and is critical for achieving carbon neutrality and carbon peak. We conducted a study in Kunming and analyzed the land utilization data for 2000, 2010, and 2020. We assessed the features of land utilization conversion and forecasted land utilization under three development patterns in 2030 on the basis of the Patch-generating Land Use Simulation (PLUS) model. We used the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model to estimate changes in carbon storage trends under three development scenarios in 2000, 2010, 2020, and 2030 and the impact of socioeconomic and natural factors on carbon storage. The results of the study indicated that (1) carbon storage is intimately associated with land utilization practices. Carbon storage in Kunming in 2000, 2010, and 2020 was 1.146 × 108 t, 1.139 × 108 t, and 1.120 × 108 t, respectively. During the 20 years, forest land decreased by 142.28 km2, and the decrease in forest land area caused a loss of carbon storage. (2) Carbon storage in 2030 was predicted to be 1.102 × 108 t, 1.136 × 108 t, and 1.105 × 108 t, respectively, under the trend continuation scenario, eco-friendly scenario, and comprehensive development scenario, indicating that implementing ecological protection and cultivated land protection measures can facilitate regional ecosystem carbon storage restoration. (3) Impervious surfaces and vegetation have the greatest influence on carbon storage for the study area. A spatial global and local negative correlation was found between impervious surface coverage and ecosystem carbon storage. A spatial global and local positive correlation was found between NDVI and ecosystem carbon storage. Therefore, ecological and farmland protection policies need to be strengthened, the expansion of impervious surfaces should be strictly controlled, and vegetation coverage should be improved.

IoT Traffic Analyzer Tool with Automated and Holistic Feature Extraction Capability.

The Internet of Things (IoT) is an emerging technology that attracted considerable attention in the last decade to become one of the most researched topics in computer science studies. This research aims to develop a benchmark framework for a public multi-task IoT traffic analyzer tool that holistically extracts network traffic features from an IoT device in a smart home environment that researchers in various IoT industries can implement to collect information about IoT network behavior. A custom testbed with four IoT devices is created to collect real-time network traffic data based on seventeen comprehensive scenarios of these devices' possible interactions. The output data is fed into the IoT traffic analyzer tool for both flow and packet levels analysis to extract all possible features. Such features are ultimately classified into five categories: IoT device type, IoT device behavior, Human interaction type, IoT behavior within the network, and Abnormal behavior. The tool is then evaluated by 20 users considering three variables: usefulness, accuracy of information being extracted, performance and usability. Users in three groups were highly satisfied with the interface and ease of use of the tool, with scores ranging from 90.5% to 93.8% and with an average score between 4.52 and 4.69 with a low standard deviation range, indicating that most of the data revolve around the mean.

Prioritizing Urban Sustainability Practices Through Comprehensive Quality Assessment and Scenario Planning

Prioritizing Urban Sustainability Practices Through Comprehensive Quality Assessment and Scenario Planning

Considering Regional Connectivity and Policy Factors in the Simulation of Land Use Change in New Areas: A Case Study of Nansha New District, China

Numerous emerging development areas worldwide are receiving attention; however, current research on land use change simulation primarily concentrates on cities, urban clusters, or larger scales. Moreover, there is a limited focus on understanding the impact of regional connectivity with surrounding cities and policy factors on land use change in these new areas. In this context, the present study utilizes a cellular automata (CA) model to investigate land use changes in the case of Nansha New District in Guangzhou, China. Three scenarios are examined, emphasizing conventional locational factors, policy considerations, and the influence of regional connectivity with surrounding cities. The results reveal several key findings: (1) Between 2015 and 2021, Nansha New District experienced significant land use changes, with the most notable shifts observed in cultivated land, water area, and construction land. (2) The comprehensive scenario exhibited the highest simulation accuracy, indicating that Nansha New District, as an emerging area, is notably influenced by policy factors and regional connectivity with surrounding cities. (3) Predictions for land use changes in Nansha by 2030, based on the scenario with the highest level of simulation accuracy, suggest an increase in the proportion of cultivated and forest land areas, alongside a decrease in the proportion of construction land and water area. This study contributes valuable insights to relevant studies and policymakers alike.

Numerical investigation on the effect of pressurization scenarios on the deformation behaviours and operating volume of a four-chambered soft actuator

PurposeSoft actuators using pneumatic-chamber (PneuNet)-based designs have been of interest in the area of soft robotics with scope of application in the area of biomedical assistance and smart agriculture. Researchers have attempted to investigate multiple chambers in parallel to examine their deformation characteristics. However, there is a lacuna for investigation of the deformation characteristics of four parallel chambered soft actuators. The purpose of this study is to comprehensively investigate the different possible actuation scenarios and the resulting bending/deformation behaviours.Design/methodology/approachTherefore, in this study, a four-chambered PneuNet actuator is numerically investigated to evaluate the effects of pressurization scenarios and pressure levels on its performance, operating reaching and working volume.FindingsThe results of this study revealed that two-adjacent chamber equal pressurization and three-chamber pressurizations result in increased bending. However, two-opposite chamber pressurization reduces the bending angle with pressure levels in the lower pressure chamber. The maximum bending angle of 97° was achieved for single-chamber pressurization of 300 kPa. The two-adjacent chamber unequal pressurization can achieve a sweeping motion in the actuator along with bending. The working volume and reaching capability analysis revealed that the actuator can reach around 71% of the dimensional operating space.Practical implicationsThe results provide fundamental guidance on the output nature of motion which can be obtained under different pressurization scenarios using the four-chambered design soft actuator, thereby making it a practical guide for implementation for useful applications.Originality/valueThe comprehensive pressurization scenarios and pressure level variations reported in this study will serve as fundamental operating guidelines for any practical implementation of the four-chambered PneuNet actuator.

An analysis of regional carbon stock response under land use structure change and multi-scenario prediction, a case study of Hefei, China

As the largest global carbon pool system, terrestrial ecosystems have an important role to maintain the stability of ecosystems. Human activities affect the structural changes in the ground surface and interfere with terrestrial ecosystem evolution, and consequently, carbon stock is changed in the region. Therefore, forecasting future carbon stock changes under different land use scenarios has important research implications for promoting stable evolution and cycling of terrestrial ecosystems. This study is conducted with the land use data from 2000 to 2020, and incorporates the Patch-generating Land Use Simulation model with the Integrated Valuation of Ecosystem Services and Trade-Offs model to analyze the changes in land use in Hefei, and its influence on the carbon stock in Hefei in various scenarios. During the study period, the mutual conversion between different land types in Hefei City made the land structure change within the study area more significant. The rapidly evolving surface structure is the reason for the decrease of carbon storage in terrestrial ecosystems, with a cumulative decrease of 1.2 × 108 t. The spatial distribution in carbon storage in the study area shows a distribution pattern of low in the north and high in the south. The high carbon storage area is obviously banded in the study area. The area with obvious changes in surface structure has more obvious changes in carbon storage. Compared with the natural development scenario, the downward trend of carbon storage in the ecological protection scenario and the comprehensive development scenario has slowed down due to the restrictions on the structural transformation of land types and the implementation of relevant ecological protection policies. Therefore, this study will support the future management and policy making of Hefei City with the background of China's “double carbon” target and the significant position of Hefei City.

A scenario process for urban forest design at the neighbourhood level

Urban forests are facing multiple future challenges. In order for urban forest designs to successfully respond to these challenges, we must explore new approaches that allow for meaningful and rich transdisciplinary conversation and assessment of the trade-offs and co-benefits of a range of options. Scenarios are increasingly being used by numerous disciplines to help understand complex futures, but to be useful they must follow a defensible design process, use consistent methods, explore plausible futures, and communicate results in an appealing, comprehensive, and insightful way. In this paper, we describe a new structured scenario design process to create distinct and holistic urban forest scenarios with detailed spatial configurations of urban vegetation. The process is replicable and integrates an iterative process of seven steps to develop a set of future urban forest scenarios. The resulting scenarios identify options with the greatest range of benefits and provide insights into forest performance when retrofitting urban forests in compact communities. In a world facing multiple simultaneous crises, local decision-makers can draw on the measured guidance provided by a robust, comprehensive scenario process such as that detailed here to create urban forest strategies that are resilient in a range of futures.

Comprehensive evaluation and scenario simulation of water resources carrying capacity: A case study in Xiong’an New Area, China

Water resources play a pivotal role in sustaining and shaping urban development. To assess the suitability of a site for urban construction, a water-resource–carrying capacity (WRCC) assessment is typically conducted. Here, we expand on the concept of the WRCC and construct an evaluation system based on the water quantity, quality, watershed and flow (WQQSF). Using this WQQSF evaluation system, we investigated the suitability of water resources for the development of the Xiong’an New Area (XNA) in China. Specifically, we evaluated the WRCC of XNA from 2010 to 2020 and identified the main obstacle factors. By building a system dynamics (SD) model, we analyzed projected changes in the carrying capacity of XNA from 2021 to 2035. The main findings were as follows:(1) the average WQQSF-index was 0.32 from 2010 to 2017, which corresponds to the overload condition, and rises to 0.41 from 2018 to 2020, which corresponds to the critical overload condition. (2) From the perspective of obstacle factors, the water quantity factor has a large influence on the water resources bearing condition of XNA accounting for about 40 %. (3) Considering that XNA is a water-scarce area, we should first ensure the balance between the supply and demand of water resources, and secondly, choose the optimal scenario for the carrying capacity. Among the five scenarios based on uncertainty, the S3 scenario not only meets the balance of water resources supply and demand but also has the best-carrying index, which is 0.7, showing a weak carrying condition. To ensure the sustainable development of WRCC in XNA, water conservation and strict control of population size should be adhered to in the future while increasing water recharge through multiple channels. This study provides a decision basis for the management, rational development, and allocation of WRCC in XNA.