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Structural health monitoring of bridges under the influence of natural environmental factors and geomatic technologies: a literature review and bibliometric analysis.

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Rădulescu, V.M.; Rădulescu, G.M.T.; Naș, S.M.; Rădulescu, A.T.; Rădulescu, C.M. Structural Health Monitoring of Bridges under the Influence of Natural Environmental Factors and Geomatic Technologies: A Literature Review and Bibliometric Analysis. Buildings 2024 , 14 , 2811. https://doi.org/10.3390/buildings14092811

Rădulescu VM, Rădulescu GMT, Naș SM, Rădulescu AT, Rădulescu CM. Structural Health Monitoring of Bridges under the Influence of Natural Environmental Factors and Geomatic Technologies: A Literature Review and Bibliometric Analysis. Buildings . 2024; 14(9):2811. https://doi.org/10.3390/buildings14092811

Rădulescu, Virgil Mihai, Gheorghe M. T. Rădulescu, Sanda Mărioara Naș, Adrian Traian Rădulescu, and Corina M. Rădulescu. 2024. "Structural Health Monitoring of Bridges under the Influence of Natural Environmental Factors and Geomatic Technologies: A Literature Review and Bibliometric Analysis" Buildings 14, no. 9: 2811. https://doi.org/10.3390/buildings14092811

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• Published: 04 September 2024

How to avoid sinking in swamp: exploring the intentions of digitally disadvantaged groups to use a new public infrastructure that combines physical and virtual spaces

• Chengxiang Chu 1   na1 ,
• Zhenyang Shen 1   na1 ,
• Hanyi Xu 2   na1 ,
• Qizhi Wei 1 &
• Cong Cao   ORCID: orcid.org/0000-0003-4163-2218 1  

Humanities and Social Sciences Communications volume  11 , Article number:  1135 ( 2024 ) Cite this article

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• Science, technology and society

With advances in digital technology, physical and virtual spaces have gradually merged. For digitally disadvantaged groups, this transformation is both convenient and potentially supportive. Previous research on public infrastructure has been limited to improvements in physical facilities, and few researchers have investigated the use of mixed physical and virtual spaces. In this study, we focused on integrated virtual and physical spaces and investigated the factors affecting digitally disadvantaged groups’ intentions to use this new infrastructure. Building on a unified theory of the acceptance and use of technology, we focused on social interaction anxiety, identified the characteristics of digitally disadvantaged groups, and constructed a research model to examine intentions to use the new infrastructure. We obtained 337 valid data from the questionnaire and analysed them using partial least squares structural equation modelling. The results showed positive relationships between performance expectancy, perceived institutional support, perceived marketplace influence, effort expectancy, and facilitating conditions. The influence of psychological reactance was significantly negative. Finally, social interaction anxiety had a regulatory effect on performance expectancy, psychological reactance, perceived marketplace influence, and effort expectancy. Its effects on perceived institutional support and facilitating conditions were not significant. The results support the creation of inclusive smart cities by ensuring that the new public infrastructure is suitable for digitally disadvantaged groups. Meanwhile, this study presents new theoretical concepts of new public infrastructures, mixed physical and virtual spaces, which provides a forward-looking approach to studying digitally disadvantaged groups in this field and paves the way for subsequent scholars to explore the field in theory and literature.

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Introduction.

Intelligent systems and modernisation have influenced the direction of people’s lives. With the help of continuously updated and iteratively advancing technology, modern urban construction has taken a ‘big step’ in its development. As China continues to construct smart cities, national investment in public infrastructure has steadily increased. Convenient and efficient public infrastructure has spread throughout the country, covering almost all aspects of residents’ lives and work (Guo et al. 2016 ). Previously, public infrastructure was primarily physical and located in physical spaces, but today, much of it is virtual. To achieve the goal of inclusive urban construction, the government has issued numerous relevant laws and regulations regarding public infrastructure. For example, the Chinese legislature solicited opinions from the community on the ‘Barrier-free environmental construction law of the People’s Republic of China (Draft)’.

Virtual space, based on internet technology, is a major factor in the construction of smart cities. Virtual space can be described as an interactive world built primarily on the internet (Shibusawa, 2000 ), and it has underpinned the development of national public infrastructure. In 2015, China announced its first national pilot list of smart cities, and the government began the process of building smart cities (Liu et al. 2017 ). With the continuous updating and popularisation of technologies such as the internet of things and artificial intelligence (AI) (Gu and Iop, 2020 ), virtual space is becoming widely accessible to the public. For example, in the field of government affairs, public infrastructure is now regularly developed in virtual spaces, such as on e-government platforms.

The construction of smart cities is heavily influenced by technological infrastructure (Nicolas et al. 2020 ). Currently, smart cities are being developed, and the integration of physical and virtual spaces has entered a significant stage. For example, when customers go to an offline bank to transact business, they are often asked by bank employees to use online banking software on their mobile phones, join a queue, or prove their identities. Situations such as these are neither purely virtual nor entirely physical, but in fields like banking, both options need to be considered. Therefore, we propose a new concept of mixed physical and virtual spaces in which individuals can interact, share, collaborate, coordinate with each other, and act.

Currently, new public infrastructure has emerged in mixed physical and virtual spaces, such as ‘Zheli Office’ and Alipay, in Zhejiang Province, China (as shown in Fig. 1 ). ‘Zheli Office’ is a comprehensive government application that integrates government services through digital technology, transferring some processes from offline to online and greatly improving the convenience, efficiency, and personalisation of government services. Due to its convenient payment facilities, Alipay is continuously supporting the integration of various local services, such as live payments and convenient services, and has gradually become Zhejiang’s largest living service platform. Zhejiang residents can handle almost all government and life affairs using these two applications. ‘Zheli Office’ and Alipay are key to the new public infrastructure in China, which is already leading the world in terms of a new public infrastructure that combines physical and virtual spaces; thus, China provided a valuable research context for this study.

This figure shows the new public infrastructure has emerged in mixed physical and virtual spaces.

There is no doubt that the mixing of physical and virtual spaces is a helpful trend that makes life easier for most people. However, mixed physical and virtual spaces still have a threshold for their use, which makes it difficult for some groups to use the new public infrastructure effectively. Within society, there are people whose living conditions are restricted for physiological reasons. They may be elderly people, people with disabilities, or people who lack certain abilities. According to the results of China’s seventh (2021) national population census, there are 264.02 million elderly people aged 60 years and over in China, accounting for 18.7 per cent of the total population. China is expected to have a predominantly ageing population by around 2035. In addition, according to data released by the China Disabled Persons’ Federation, the total number of people with disabilities in China is more than 85 million, which is equivalent to one person with a disability for every 16 Chinese people. In this study, we downplay the differences between these groups, focusing only on common characteristics that hinder their use of the new public infrastructure. We collectively refer to these groups as digitally disadvantaged groups who may have difficulty adapting to the new public infrastructure integrating mixed physical and virtual spaces. This gap not only makes the new public infrastructure inconvenient for these digitally disadvantaged groups, but also leads to their exclusion and isolation from the advancing digital trend.

In the current context, in which the virtual and the real mix, digitally disadvantaged groups resemble stones in a turbulent flowing river. Although they can move forward, they do so with difficulty and will eventually be left behind. Besides facing the inherent inconveniences of new public infrastructure that integrates mixed physical and virtual spaces, digitally disadvantaged groups encounter additional obstacles. Unlike the traditional public infrastructure, the new public infrastructure requires users to log on to terminals, such as mobile phones, to engage with mixed physical and virtual spaces. However, a significant proportion of digitally disadvantaged groups cannot use the new public infrastructure effectively due to economic costs or a lack of familiarity with the technology. In addition, the use of facilities in physical and virtual mixed spaces requires engagement with numerous interactive elements, which further hinders digitally disadvantaged groups with weak social or technical skills.

The United Nations (UN) has stated the creation of ‘sustainable cities and communities’ as one of its sustainable development goals, and the construction of smart cities can help achieve this goal (Blasi et al. 2022 ). Recent studies have pointed out that the spread of COVID-19 exacerbated the marginalisation of vulnerable groups, while the lack of universal service processes and virtual facilities has created significant obstacles for digitally disadvantaged groups (Narzt et al. 2016 ; C. H. J. Wang et al. 2021 ). It should be noted that smart cities result from coordinated progress between technology and society (Al-Masri et al. 2019 ). The development of society should not be at the expense of certain people, and improving inclusiveness is key to the construction of smart cities, which should rest on people-oriented development (Ji et al. 2021 ). This paper focuses on the new public infrastructure that integrates mixed physical and virtual spaces. In it, we aim to explore how improved inclusiveness can be achieved for digitally disadvantaged groups during the construction of smart cities, and we propose the following research questions:

RQ1 . In a situation where there is a mix of physical and virtual spaces, what factors affect digitally disadvantaged groups’ use of the new public infrastructure?

RQ2 . What requirements will enable digitally disadvantaged groups to participate fully in the new public infrastructure integrating mixed physical and virtual spaces?

To answer these questions, we built a research model based on the unified theory of acceptance and use of technology (UTAUT) to explore the construction of a new public infrastructure that integrates mixed physical and virtual spaces (Venkatesh et al. 2003 ). During the research process, we focused on the attitudes, willingness, and other behavioural characteristics of digitally disadvantaged groups in relation to mixed physical and virtual spaces, aiming to ultimately provide research support for the construction of highly inclusive smart cities. Compared to existing research, this study goes further in exploring the integration and interconnection of urban public infrastructure in the process of smart city construction. We conducted empirical research to delve more deeply into the factors that influence digitally disadvantaged groups’ use of the new public infrastructure integrating mixed physical and virtual spaces. The results of this study can provide valuable guidelines and a theoretical framework for the construction of new public infrastructure and the improvement of relevant systems in mixed physical and virtual spaces. We also considered the psychological characteristics of digitally disadvantaged groups, introduced psychological reactance into the model, and used social interaction anxiety as a moderator for the model, thereby further enriching the research results regarding mixed physical and virtual spaces. This study directs social and government attention towards the issues affecting digitally disadvantaged groups in the construction of inclusive smart cities, and it has practical implications for the future digitally inclusive development of cities in China and across the world.

Theoretical background and literature review

Theoretical background of utaut.

Currently, the theories used to explore user acceptance behaviour are mainly applied separately in the online and offline fields. Theories relating to people’s offline use behaviour include the theory of planned behaviour (TPB) and the theory of reasoned action (TRA). Theories used to explore users’ online use behaviour include the technology acceptance model (TAM). Unlike previous researchers, who focused on either physical or virtual space, we focused on both. This required us to consider the characteristics of both physical and virtual spaces based on a combination of user acceptance theories (TPB, TRA, and TAM) and UTAUT, which was proposed by Venkatesh et al. ( 2003 ) in 2003. These theories have mainly been used to study the factors affecting user acceptance and the application of information technology. UTAUT integrates user acceptance theories to examine eight online and offline scenarios, thereby meeting our need for a theoretical model for this study that could include both physical and virtual spaces. UTAUT includes four key factors that directly affect users’ acceptance and usage behaviours: performance expectancy, facilitating conditions, social influence, and effort expectancy. Compared to other models, UTAUT has better interpretation and prediction capabilities for user acceptance behaviour (Venkatesh et al. 2003 ). A review of previous research showed that UTAUT has mainly been used to explore usage behaviours in online environments (Hoque and Sorwar, 2017 ) and regarding technology acceptance (Heerink et al. 2010 ). Thus, UTAUT is effective for exploring acceptance and usage behaviours. We therefore based this study on the belief that UTAUT could be applied to people’s intentions to use the new public infrastructure that integrates mixed physical and virtual spaces.

In this paper, we refine and extend UTAUT based on the characteristics of digitally disadvantaged groups, and we propose a model to explore the willingness of digitally disadvantaged groups to use the new public infrastructure integrating mixed physical and virtual spaces. We categorised possible influences on digitally disadvantaged groups’ use of the new public infrastructure into three areas: user factors, social factors, and technical factors. Among the user factors, we explored the willingness of digitally disadvantaged groups to use the new public infrastructure based on their performance expectancy and psychological reactance, as performance expectations are one of the UTAUT variables. To consider situations in which some users resist using new technologies due to cognitive bias, we combined (Hoque and Sorwar, 2017 ) showing that resistance among elderly people is a key factor affecting their adoption of mobile medical services with the theory of psychological reactance and introduced psychological reactance as an independent variable (Miron and Brehm, 2006 ). Among the social factors, we expanded the UTAUT social influence variable to include perceived institutional support and perceived marketplace influence. The new public infrastructure cannot be separated from the relevant government policies and the economic development status of the society in which it is constructed. Therefore, we aimed to explore the willingness of digitally disadvantaged people to use the new public infrastructure in terms of perceived institutional support and perceived marketplace influence. Among the technical factors, we explored the intentions of digitally disadvantaged groups to use new public infrastructure based on effort expectancy and facilitating conditions—both variables taken from UTAUT. In addition, considering that users with different levels of social interaction anxiety may have different levels of intention to use the new public infrastructure, we drew on research regarding the moderating role of consumer technological anxiety in adopting mobile shopping and introduced social interaction anxiety as a moderating variable (Yang and Forney, 2013 ). Believing that these modifications would further improve the interpretive ability of UTAUT, we considered it helpful to study the intentions of digitally disadvantaged groups to use the new public infrastructure.

Intentions to use mixed physical and virtual spaces

Many scholars have researched the factors that affect users’ willingness to use intelligent facilities, which can be broadly divided into two categories: for-profit and public welfare facilities. In the traditional business field, modern information technologies, such as the internet of things and AI, have become important means by which businesses can reduce costs and expand production. Even in traditional industries, such as agriculture (Kadylak and Cotten, 2020 ) and aquaculture (Cai et al. 2023 ), virtual technology now plays a significant role. Operators hope to use advanced technology to change traditional production and marketing models and to keep pace with new developments. However, mixed physical and virtual spaces should be inclusive for all people. Already, technological development is making it clear that no one will be able to entirely avoid mixed physical and virtual spaces. The virtualisation of public welfare facilities has gradually emerged in many areas of daily life, such as electronic health (D. D. Lee et al. 2019 ) and telemedicine (Werner and Karnieli, 2003 ). Government affairs are increasingly managed jointly in both physical and virtual spaces, resulting in an increase in e-government research (Ahn and Chen, 2022 ).

A review of the literature over the past decade showed that users’ willingness to use both for-profit and public welfare facilities is influenced by three sets of factors: user factors, social factors, and technical factors. First, regarding user factors, Bélanger and Carter ( 2008 ) pointed out that consumer trust in the government and technology are key factors affecting people’s intentions to use technology. Research on older people has shown that self-perceived ageing can have a significant impact on emotional attachment and willingness to use technology (B. A. Wang et al. 2021 ). Second, social factors include consumers’ intentions to use, which may vary significantly in different market contexts (Chiu and Hofer, 2015 ). For example, research has shown that people’s willingness to use digital healthcare tools is influenced by the attitudes of the healthcare professionals they encounter (Thapa et al. 2021 ). Third, technical factors include appropriate technical designs that help consumers use facilities more easily. Yadav et al. ( 2019 ) considered technical factors, such as ease of use, quality of service provided, and efficiency parameters, in their experiments.

The rapid development of virtual technology has inevitably drawn attention away from the physical world. Most previous researchers have focused on either virtual or physical spaces. However, scholars have noted the increasing mixing of these two spaces and have begun to study the relationships between them (Aslesen et al. 2019 ; Cocciolo, 2010 ). Wang ( 2007 ) proposed enhancing virtual environments by inserting real entities. Existing research has shown that physical and virtual spaces have begun to permeate each other in both economic and public spheres, blurring the boundaries between them (K. F. Chen et al. 2024 ; Paköz et al. 2022 ). Jakonen ( 2024 ) pointed out that, currently, with the integration of digital technologies into city building, the role of urban space in various stakeholders’ lives needs to be fully considered. The intermingling of physical and virtual spaces began to occur in people’s daily work (J. Chen et al. 2024 ) during the COVID-19 pandemic, which enhanced the integration trend (Yeung and Hao, 2024 ). The intermingling of virtual and physical spaces is a sign of social progress, but it is a considerable challenge for digitally disadvantaged people. For example, people with disabilities experience infrastructure, access, regulatory, communication, and legislative barriers when using telehealth services (Annaswamy et al. 2020 ). However, from an overall perspective, few relevant studies have considered the mixing of virtual and physical spaces.

People who are familiar with information technology, especially Generation Z, generally consider the integration of physical and virtual spaces convenient. However, for digitally disadvantaged groups, such ‘science fiction’-type changes can be disorientating and may undermine their quality of life. The elderly are an important group among the digitally disadvantaged groups referred to in this paper, and they have been the primary target of previous research on issues of inclusivity. Many researchers have considered the factors influencing older people’s willingness to use emerging technologies. For example, for the elderly, ease of use is often a prerequisite for enjoyment (Dogruel et al. 2015 ). Iancu and Iancu ( 2020 ) explored the interaction of elderly with technology, with a particular focus on mobile device design. The study emphasised that elderly people’s difficulties with technology stem from usability issues that can be addressed through improved design and appropriate training (Iancu and Iancu, 2020 ). Moreover, people with disabilities are an important group among digitally disadvantaged groups and an essential concern for the inclusive construction of cities. The rapid development of emerging technologies offers convenience to people with disabilities and has spawned many physical accessibility facilities and electronic accessibility systems (Botelho, 2021 ; Perez et al. 2023 ). Ease of use, convenience, and affordability are also key elements for enabling disadvantaged groups to use these facilities (Mogaji et al. 2023 ; Mogaji and Nguyen, 2021 ). Zander et al. ( 2023 ) explored the facilitators of and barriers to the implementation of welfare technologies for elderly people and people with disabilities. Factors such as abilities, attitudes, values, and lifestyles must be considered when planning the implementation of welfare technology for older people and people with disabilities (Zander et al. 2023 ).

In summary, scholars have conducted extensive research on the factors influencing intentions to use virtual facilities. These studies have revealed the underlying logic behind people’s adoption of virtual technology and have laid the foundations for the construction of inclusive new public infrastructure. Moreover, scholars have proposed solutions to the problems experienced by digitally disadvantaged groups in adapting to virtual facilities, but most of these scholars have focused on the elderly. Furthermore, scholars have recently conducted preliminary explorations of the mixing of physical and virtual spaces. These studies provided insights for this study, enabling us to identify both relevant background factors and current developments in the integration of virtual spaces with reality. However, most researchers have viewed the development of technology from the perspective of either virtual space or physical space, and they have rarely explored technology from the perspective of mixed physical and virtual spaces. In addition, when focusing on designs for the inclusion of digitally disadvantaged groups, scholars have mainly provided suggestions for specific practices, such as improvements in technology, hardware facilities, or device interaction interfaces, while little consideration has been given to the psychological characteristics of digitally disadvantaged groups or to the overall impact of society on these groups. Finally, in studying inclusive modernisation, researchers have generally focused on the elderly or people with disabilities, with less exploration of behavioural differences caused by factors such as social anxiety. Therefore, based on UTAUT, we explored the willingness of digitally disadvantaged groups to use the new public infrastructure integrating mixed physical and virtual spaces in a Chinese context (as shown in Fig. 2 ).

This figure explores the willingness of digitally disadvantaged groups to use the new public infrastructure integrating mixed physical and virtual spaces in a Chinese context.

Research hypotheses

User factors.

Performance expectancy is defined as the degree to which an individual believes that using a system will help him or her achieve gains in job performance (Chao, 2019 ; Venkatesh et al. 2003 ). In this paper, performance expectancy refers to the extent to which digitally disadvantaged groups obtain tangible results from the use of the new public infrastructure. Since individuals have a strong desire to improve their work performance, they have strong intentions to use systems that can improve that performance. Previous studies in various fields have confirmed the view that high performance expectancy can effectively promote individuals’ sustained intentions to use technology (Abbad, 2021 ; Chou et al. 2010 ; S. W. Lee et al. 2019 ). For example, the role of performance expectancy was verified in a study on intentions to use e-government (Zeebaree et al. 2022 ). We believe that if digitally disadvantaged groups have confidence that the new public infrastructure will help them improve their lives or work performance, even in complex environments, such as mixed physical and virtual spaces, they will have a greater willingness to use it. Therefore, we developed the following hypothesis:

H1: Performance expectancy has a positive impact on digitally disadvantaged groups’ intentions to use the new public infrastructure integrating mixed physical and virtual spaces.

Brehm ( 1966 ) proposed the psychological reactance theory in 1966. According to this theory, when individuals perceive that their freedom to make their own choices is under threat, a motivational state to restore that freedom is awakened (Miron and Brehm, 2006 ). Psychological reactance manifests in an individual’s intentional or unintentional resistance to external factors. Previous studies have shown that when individuals are in the process of using systems or receiving information, they may have cognitive biases that lead to erroneous interpretations of the external environment, resulting in psychological reactance (Roubroeks et al. 2010 ). Surprisingly, cognitive biases may prompt individuals to experience psychological reactance, even when offered support with helpful intentions (Tian et al. 2020 ). In this paper, we define psychological resistance as the cognitive-level or psychological-level obstacles or resistance of digitally disadvantaged groups to the new public infrastructure. This resistance may be due to digitally disadvantaged groups misunderstanding the purpose or use of the new public infrastructure. For example, they may think that the new public infrastructure will harm their self-respect or personal interests. When digitally disadvantaged groups view the new public infrastructure as a threat to their status or freedom to make their own decisions, they may develop resistance to its use. Therefore, psychological reactance cannot be ignored as an important factor potentially affecting digitally disadvantaged groups’ intentions to use the new public infrastructure. Hence, we developed the following hypothesis:

H2: Psychological reactance has a negative impact on digitally disadvantaged groups’ intentions to use the new public infrastructure integrating mixed physical and virtual spaces.

Social factors

In many countries, the main providers of public infrastructure are government and public institutions (Susilawati et al. 2010 ). Government decision-making is generally based on laws or government regulations (Acharya et al. 2022 ). Government decision-making procedures affect not only the builders of infrastructure, but also the intentions of users. In life, individuals and social organisations tend to abide by and maintain social norms to ensure that their behaviours are socially attractive and acceptable (Bygrave and Minniti, 2000 ; Martins et al. 2019 ). For example, national financial policies influence the marketing effectiveness of enterprises (Chen et al. 2021 ). Therefore, we believe that perceived institutional support is a key element influencing the intentions of digitally disadvantaged groups to use the new public infrastructure. In this paper, perceived institutional support refers to digitally disadvantaged groups’ perceived policy state or government support for using the new public infrastructure, including institutional norms, laws, and regulations. Existing institutions have mainly been designed around public infrastructure that exists in physical space. We hope to explore whether perceived institutional support for digitally disadvantaged groups affects their intentions to use the new public infrastructure that integrates mixed physical and virtual spaces. Thus, we formulated the following hypothesis:

H3: Perceived institutional support has a positive impact on digitally disadvantaged groups’ intentions to use the new public infrastructure integrating mixed physical and virtual spaces.

Perceived marketplace influence is defined as actions or decisions that affect the market behaviour of consumers and organisations (Joshi et al. 2021 ; Leary et al. 2014 ). In this paper, perceived marketplace influence is defined as the behaviour of others using the new public infrastructure that affects the intentions of digitally disadvantaged groups to use it. Perceived marketplace influence increases consumers’ perceptions of market dynamics and their sense of control through the influence of other participants in the marketplace (Leary et al. 2019 ). Scholars have explored the impact of perceived marketplace influence on consumers’ purchase and use intentions in relation to fair trade and charity (Leary et al. 2019 ; Schneider and Leonard, 2022 ). Schneider and Leonard ( 2022 ) claimed that if consumers believe that their mask-wearing behaviour will motivate others around them to follow suit, then this belief will in turn motivate them to wear masks. Similarly, when digitally disadvantaged people see the people around them using the new public infrastructure, this creates an invisible market that influences their ability and motivation to try using the infrastructure themselves. Therefore, we developed the following hypotheses:

H4: Perceived marketplace influence has a positive impact on digitally disadvantaged groups’ intentions to use the new public infrastructure integrating mixed physical and virtual spaces.

Technical factors

Venkatesh et al. ( 2003 ) defined effort expectancy as the ease with which individuals can use a system. According to Tam et al. ( 2020 ), effort expectancy positively affects individuals’ performance expectancy and their sustained intentions to use mobile applications. In this paper, effort expectancy refers to the ease of use of the new public infrastructure for digitally disadvantaged groups: the higher the level of innovation and the more steps involved in using a facility, the poorer the user experience and the lower the utilisation rate (Venkatesh and Brown, 2001 ). A study on the use of AI devices for service delivery noted that the higher the level of anthropomorphism, the higher the cost of effort required by the customer to use a humanoid AI device (Gursoy et al. 2019 ). In mixed physical and virtual spaces, the design and use of new public infrastructure may become increasingly complex, negatively affecting the lives of digitally disadvantaged groups. We believe that the simpler the new public infrastructure, the more it will attract digitally disadvantaged groups to use it, while also enhancing their intentions to use it. Therefore, we formulated the following hypothesis:

H5: Effort expectancy has a positive impact on digitally disadvantaged groups’ intentions to use the new public infrastructure integrating mixed physical and virtual spaces.

Venkatesh et al. ( 2003 ) defined facilitating conditions as the degree to which an individual believes that an organisation and its technical infrastructure exist to support the use of a system. In this paper, facilitating conditions refer to the external conditions that support digitally disadvantaged groups in using the new public infrastructure, including resources, knowledge bases, skills, etc. According to Zhong et al. ( 2021 ), facilitating conditions can affect users’ attitudes towards the use of face recognition payment systems and, further, affect their intentions to use them. Moreover, scholars have shown that facilitating conditions significantly promote people’s intentions to use e-learning systems and e-government (Abbad, 2021 ; Purohit et al. 2022 ). Currently, the new public infrastructure involves mixed physical and virtual spaces, and external facilitating conditions, such as a ‘knowledge salon’ or a training session, can significantly promote digitally disadvantaged groups’ intentions and willingness to the infrastructure. Therefore, we developed the following hypothesis:

H6: Facilitating conditions have a positive impact on digitally disadvantaged groups’ intentions to use the new public infrastructure integrating a mixed physical and virtual spaces.

Moderator variable

Magee et al. ( 1996 ) claimed that social interaction anxiety is an uncomfortable emotion that some people experience in social situations, leading to avoidance, a desire for solitude, and a fear of criticism. In this paper, social interaction anxiety refers to the worries and fears of digitally disadvantaged groups about the social interactions they will be exposed to when using the new public infrastructure. Research has confirmed that people with high levels of dissatisfaction with their own bodies are more anxious in social situations (Li Mo and Bai, 2023 ). Moreover, people with high degrees of social interaction anxiety may feel uncomfortable in front of strangers or when observed by others (Zhu and Deng, 2021 ). Digitally disadvantaged groups usually have some physiological inadequacies and may be rejected by ‘normal’ groups. Previous studies have shown that the pain caused by social exclusion is positively correlated with anxiety (Davidson et al. 2019 ). Digitally disadvantaged groups may have higher degrees of dissatisfaction with their own physical abilities, which may exacerbate any social interaction anxiety they already have. We believe that high social interaction anxiety is a common characteristic of digitally disadvantaged groups, defining them as ‘different’ from other groups.

In mixed physical and virtual spaces, if the design of the new public infrastructure is not friendly and does not help digitally disadvantaged groups use it easily, their perceived social exclusion is likely to increase, resulting in a heightened sense of anxiety. However, compared with face-to-face and offline social communication, online platforms offer convenience in terms of both communication method and duration (Ali et al. 2020 ). Therefore, people with a high degree of social interaction anxiety frequently prefer and are likely to choose online social communication (Hutchins et al. 2021 ). However, digitally disadvantaged groups may be unable to avoid social interaction by using the facilities offered in virtual spaces. Therefore, we believe that influencing factors may have different effects on intentions to use the new public infrastructure, according to the different levels of social interaction anxiety experienced. Therefore, we predicted the following:

H7: Social interaction anxiety has a moderating effect on each path.

Research methodology

Research background and cases.

To better demonstrate the phenomenon of the new public infrastructure integrating mixed physical and virtual spaces, we considered the cases of ‘Zheli Office’ (as shown in Fig. 3 ) and Alipay (as shown in Fig. 4 ) to explain the two areas of government affairs and daily life affairs, which greatly affect the daily lives of residents. Examining the functions of ‘Zheli Office’ and Alipay in mixed physical and virtual spaces allowed us to provide examples of the new public infrastructure integrating mixed physical and virtual spaces.

This figure shows the ‘Zheli Office’, it is a comprehensive government application that integrates government services through digital technology, transferring some processes from offline to online and greatly improving the convenience, efficiency, and personalisation of government services.

This figure shows Alipay, it supports the integration of various local services, such as live payments and convenient services, and has gradually become Zhejiang’s largest living service platform.

‘Zheli Office’ provides Zhejiang residents with a channel to handle their tax affairs. Residents who need to manage their tax affairs can choose the corresponding tax department through ‘Zheli Office’ and schedule the date and time for offline processing. Residents can also upload tax-related materials directly to ‘Zheli Office’ to submit them to the tax department for preapproval. Residents only need to present the vouchers generated by ‘Zheli Office’ to the tax department at the scheduled time to manage tax affairs and undergo final review. By mitigating long waiting times and tedious tax material review steps through the transfer of processes from physical spaces to virtual spaces, ‘Zheli Office’ greatly optimises the tax declaration process and saves residents time and effort in tax declaration.

Alipay provides residents with a channel to rent shared bicycles. Residents who want to rent bicycles can enter their personal information on Alipay in advance and provide a guarantee (an Alipay credit score or deposit payment). When renting a shared bicycle offline, residents only need to scan the QR code on the bike through Alipay to unlock and use it. When returning the bike, residents can also click the return button to automatically lock the bike and pay the fee anytime and anywhere. By automating leasing procedures and fee settlement in virtual spaces, Alipay avoids the tedious operations that residents experience when renting bicycles in physical stores.

Through the preceding two examples, we demonstrate the specific performance of the integration of virtual spaces and physical spaces. The government/life affairs of residents, such as tax declarations, certificate processing, transportation, shopping, and various other affairs, all require public infrastructure support. With the emergence of new digital trends in residents’ daily lives, mixed physical and virtual spaces have produced a public infrastructure that can support residents’ daily activities in mixed physical and virtual spaces. Due to the essential differences between public infrastructure involving mixed physical and virtual spaces and traditional physical and virtual public infrastructures, we propose a new concept—new public infrastructure. This is defined as ‘a public infrastructure that supports residents in conducting daily activities in mixed physical and virtual spaces’. It is worth noting that the new public infrastructure may encompass not only the virtual spaces provided by digital applications but also the physical spaces provided by machines capable of receiving digital messages, such as smart screens, scanners, and so forth.

The UN Sustainable Development Goal Report highlights that human society needs to build sustainable cities and communities that do not sacrifice the equality of some people. Digitally disadvantaged groups should not be excluded from the sustainable development of cities due to the increasing digitalisation trend because everyone should enjoy the convenience of the new public infrastructure provided by cities. Hence, ensuring that digitally disadvantaged groups can easily and comfortably use the new public infrastructure will help promote the construction of smart cities, making them more inclusive and universal. It will also promote the development of smart cities in a more equal and sustainable direction, ensuring that everyone can enjoy the benefits of urban development. Therefore, in this article, we emphasise the importance of digitally disadvantaged groups in the construction of sustainable smart cities. Through their participation and feedback, we can build more inclusive and sustainable smart cities in the future.

Research design

The aim of this paper was to explore the specific factors that influence the intentions of digitally disadvantaged groups to use the new public infrastructure integrating mixed physical and virtual spaces, and to provide a rational explanation for the role of each factor. To achieve this goal, we first reviewed numerous relevant academic papers. This formed the basis of our research assumptions and helped determine the measurement items we included. Second, we collected data through a questionnaire survey and then analysed the data using partial least squares structural equation modelling (PLS-SEM) to explore the influence of the different factors on digitally disadvantaged groups’ intentions to use the new public infrastructure. Finally, we considered in depth the mechanisms by which the various factors influenced digitally disadvantaged groups’ intentions to use mixed physical and virtual spaces.

We distributed a structured questionnaire to collect data for the study. To ensure the reliability and validity of the questionnaire, we based the item development on the scales used in previous studies (as shown in Appendix A). The first part of the questionnaire concerned the participants’ intentions to use the new public infrastructure. Responses to this part of the questionnaire were given on a seven-point Likert scale to measure the participants’ agreement or disagreement with various statements, with 1 indicating ‘strong disagreement’ and 7 indicating ‘strong agreement’. In addition, we designed cumulative scoring questions to measure the participants’ social interaction anxiety according to Fergus’s Social Interaction Anxiety Scale (Fergus et al. 2012 ). The second part of the questionnaire concerned the demographic characteristics of the participants, including but not limited to gender, age, and education level. Participants were informed that completing the survey was voluntary and that they had the right to refuse or withdraw at any time. They were informed that the researchers would not collect any personal information that would make it possible to identify them. Only after we had obtained the participants’ consent did we commence the questionnaire survey and data collection. Since the new public infrastructure referred to in this study was quite abstract, it was not conducive to the understanding and perceptions of digitally disadvantaged groups. Therefore, to better enable the respondents to understand our concept of the new public infrastructure, we simplified it to ‘an accessible infrastructure’ and informed them about typical cases and the relevant context of this study before they began to complete the questionnaire.

Once the questionnaire design was finalised, we conducted a pretest to ensure that the questions met the basic requirements of reliability and validity and that the participants could accurately understand the questions. In the formal questionnaire survey stage, we distributed the online questionnaire to digitally disadvantaged groups based on the principle of simple random sampling and collected data through the Questionnaire Star platform. Our sampling principle was based on the following points: first, the respondents had to belong to digitally disadvantaged groups and have experienced digital divide problems; second, they had to own at least one smart device and have access to the new public infrastructure, such as via ‘Zheli Office’ or Alipay, and third, they must have used government or daily life services on ‘Zheli Office’ or Alipay at least once in the past three months. After eliminating any invalid questionnaires, 337 valid completed questionnaires remained. The demographic characteristics of the participants are shown in Table 1 . In terms of gender, 54.30% of the participants were male, and 45.70% were female. In terms of age, 64.09% of the participants were aged 18–45 years. In terms of social interaction anxiety, the data showed that 46.59% of the participants had low social interaction anxiety, and 53.41% had high social interaction anxiety.

Data analysis

PLS-SEM imposes few restrictions on the measurement scale, sample size, and residual distribution (Ringle et al. 2012 ). However, the environment in which the research object was located was relatively new, so we added two special variables—psychological reactance and perceived institutional support—to the model. The PLS-SEM model was considered suitable for conducting exploratory research on the newly constructed theory and research framework. Building on previous experience, the data analysis was divided into two stages: 1) the measurement model was used to evaluate the reliability and validity of the experiment, and 2) the structural model was used to test the study hypotheses by examining the relationships between the variables.

Measurement model

First, we tested the reliability of the model by evaluating the reliability of the constructs. As shown in Table 2 , the Cronbach’s alpha (CA) range for this study was 0.858–0.901, so both extremes were higher than the acceptable threshold (Jöreskog, 1971 ). The composite reliability (CR) scores ranged from 0.904 to 0.931; therefore, both extremes were above the threshold of 0.7 (Bagozzi and Phillips, 1982 ) (see Table 2 ).

We then assessed the validity. The test for structural validity included convergent validity and discriminant validity. Convergent validity was mainly verified by the average variance extracted (AVE) value. The recommended value for AVE is 0.5 (Kim and Park, 2013 ). In this study, the AVE values for all structures far exceeded this value (the minimum AVE value was 0.702; see Table 2 ). This result showed that the structure of this model was reliable. The Fornell–Larcker criterion is commonly used to evaluate discriminant validity; that is, the square root of the AVE should be far larger than the correlations for other constructs, meaning that each construct best explains the variance of its own construct (Hair et al. 2014 ), as shown in Table 3 . The validity of the measurement model was further evaluated by calculating the cross-loading values of the reflection construct. It can clearly be seen from Table 4 that compared with other constructs included in the structural model, the indicators of the reflection metric model had the highest loading on their potential constructs (Hair et al. 2022 ), indicating that all inspection results met the evaluation criterion for cross-loading.

In addition, we used the heterotrait-monotrait (HTMT) ratio of correlations to analyse discriminant validity (Henseler et al. 2015 ). Generally, an HTMT value greater than 0.85 indicates that there are potential discriminant validity risks (Hair et al. 2022 ), but Table 5 shows that the HTMT ratios of the correlations in this study were all lower than this value (the maximum value was 0.844).

Structural model

Figure 5 presents the evaluation results for the structural model for the whole sample. The R 2 value for the structural model in this study was 0.740; that is, the explanatory power of the model regarding intention to use was 74.00%. The first step was to ensure that there was no significant collinearity between the predicted value structures, otherwise there would be redundancy in the analysis (Hair et al. 2019 ). All VIF values in this study were between 1.743 and 2.869 and were therefore lower than the 3.3 threshold value for the collinearity test (Hair et al. 2022 ), which proved that the path coefficient had not deviated. This also proves that the model had a low probability of common method bias.

This figure shows the evaluation results for the structural model.

As shown in Fig. 5 , performance expectation ( β  = 0.505, p  < 0.001), perceived institutional support ( β  = 0.338, p  < 0.001), perceived marketplace influence ( β  = 0.190, p  < 0.001), effort expectation ( β  = 0.176, p  < 0.001) and facilitating conditions ( β  = 0.108, p  < 0.001) all had significant and positive effects on intention to use. Moreover, the results showed that the relationship between psychological reaction ( β  = −0.271, p  < 0.001) and intention to use was negative and significant. Therefore, all the paths in this paper, except for the moderator variables, have been verified.

Multi-group analysis

To study the moderating effect between the independent variables and the dependent variables, Henseler et al. ( 2009 ) recommended using a multigroup analysis (MGA). In this study, we used MGA to analyse the moderating effect of different levels of social interaction anxiety. We designed six items for social interaction anxiety (as shown in Appendix A). According to the subjects’ responses to these six items and based on the principle of accumulation, questionnaires with scores of 6–20 indicated low social interaction anxiety, while questionnaires with scores of 28–42 indicated high social interaction anxiety. Questionnaires with scores of 21–27 were considered neutral and eliminated from the analysis involving social interaction anxiety. Based on multigroup validation factor analysis, we determined the component invariance, the configurable invariance, and the equality between compound variance and mean (Hair et al. 2019 ). As shown in Formula 1 , we used an independent sample t -test as a significance test, and a p -value below 0.05 indicated the significance of the parameters.

As shown in Table 6 , under social factors, the p -value for perceived institutional support in relation to intention to use was 0.335, which failed the significance test. This showed that there were no differences between the different degrees of social interaction anxiety. For technical factors, the p -value for facilitating conditions in relation to intention to use was 0.054, which again failed the test. This showed that there were no differences between the different levels of social interaction anxiety. However, the p -values for performance expectancy, psychological reaction, perceived marketplace influence, and effort expectancy in relation to intention to use were all less than 0.05; therefore, they passed the test for significance. This revealed that different degrees of social interaction anxiety had significant effects on these factors and that social interaction anxiety moderated some of the independent variables.

Next, we considered the path coefficients and p- values for the high and low social anxiety groups, as shown in Table 6 . First, with different levels of social anxiety, performance expectation had significantly different effects on intention to use, with low social anxiety ( β  = −0.129, p  = 0.394) failing the test and high social anxiety ( β  = 0.202, p  = 0.004) passing the test. This shows that high social anxiety levels had a greater influence of performance expectations on intention to use than low social anxiety levels. Second, psychological reactance showed significant differences in its effect on intention to use under different degrees of social anxiety, with low social anxiety ( β  = 0.184, p  = 0.065) failing the test and high social anxiety ( β  = −0.466, p  = 0.000) passing the test. Third, with different levels of social anxiety, perceived marketplace influence had significantly different effects on intention to use. Of these, perceived marketplace influence had a significant effect with low social anxiety levels ( β  = 0.312, p  = 0.001) but not with high social anxiety levels ( β  = 0.085, p  = 0.189). Finally, with differing degrees of social anxiety, expected effort had significantly different effects on intention to use. Of these, expected effort was insignificant at a low social anxiety level ( β  = −0.058, p  = 0.488), but it was significant at a high social anxiety level ( β  = 0.326, p  = 0.000). Therefore, different degrees of social interaction anxiety had significantly different effects on performance expectation, psychological reactance, perceived marketplace influence, and effort expectation.

Compared with previous studies, this study constituted a preliminary but groundbreaking exploration of mixed physical and virtual spaces. Moreover, we focused on the inclusivity problems encountered by digitally disadvantaged groups in these mixed physical and virtual spaces. We focused on performance expectancy, psychological reactance, perceived institutional support, perceived marketplace influence, effort expectancy, and facilitating conditions as the six factors, with intention to use being the measure of the perceived value of the new public infrastructure. However, digitally disadvantaged groups, depending on their own characteristics or social influences, can provoke different responses from the general population in their social interactions. Therefore, we added social interaction anxiety to the model as a moderating variable, in line with the assumed psychological characteristics of digitally disadvantaged groups. The empirical results revealed a strong correlation between influencing factors and intention to use. This shows that this model has good applicability for mixed physical and virtual spaces.

According to the empirical results, performance expectancy has a significant and positive impact on intention to use, suggesting that the mixing of the virtual and the real will create usage issues and cognitive difficulties for digitally disadvantaged groups. However, if the new public infrastructure can capitalise on the advantages of blended virtual and physical spaces, it could help users build confidence in its use, which would improve their intentions to use it. Furthermore, users’ intentions to use and high social interaction anxiety are likely to be promoted by performance expectancy. In most cases, social interaction anxiety stems from self-generated avoidance, isolation, and fear of criticism (Schultz and Heimberg, 2008 ). This may result in highly anxious digitally disadvantaged groups being reluctant to engage with others when using public facilities (Mulvale et al. 2019 ; Schou and Pors, 2019 ). However, the new public infrastructure is often unattended, which could be an advantage for users with high social anxiety. Therefore, the effect of performance expectancy in promoting intentions to use would be more significant in this group.

We also found that the psychological reactance of digitally disadvantaged groups had a reverse impact on their intentions to use technology in mixed physical and virtual spaces. However, social interaction anxiety had a moderating effect on this, such that the negative effect of psychological reactance on intention to use the new public infrastructure was more pronounced in the group with high social interaction anxiety. Facilities involving social or interactive factors may make users with high social interaction anxiety think that their autonomy is, to some extent, being violated, thus triggering subconscious resistance. The communication anxiety of digitally disadvantaged groups stems not only from the new public infrastructure itself but also from the environment in which it is used (Fang et al. 2019 ). Complex, mixed physical and virtual spaces can disrupt the habits that digitally disadvantaged groups have developed in purely physical spaces, resulting in greater anxiety (Hu et al. 2022 ), while groups with high levels of social anxiety tend to remain independent because they prefer to maintain their independence. Therefore, a high degree of social interaction anxiety will induce psychological reactance towards using the new public infrastructure.

The results of this paper shed further light on the role of social factors. In particular, the relationship between perceived institutional support and intention to use reflects the fact that perceived institutional support plays a role in promoting digitally disadvantaged groups’ intentions to use the new public infrastructure. This indicates that promotion measures need to be introduced by the government and public institutions if digitally disadvantaged groups are to accept the new public infrastructure. The development of a new public infrastructure integrating mixed physical and virtual spaces requires a high level of involvement from government institutions to facilitate the inclusive development of sustainable smart cities (Khan et al. 2020 ). An interesting finding of this study was that there were no significant differences between the effects of either high or low levels of social interaction anxiety on perceived institutional support and intention to use. This may be because social interaction anxiety mainly occurs in individuals within their close microenvironments. The policies and institutional norms of perceived institutional support tend to act at the macro level (Chen and Zhang, 2021 ; Mora et al. 2023 ), so levels of social interaction anxiety do not differ insignificantly between perceived institutional support and intentions to use the new public infrastructure.

We also found that digitally disadvantaged groups with low social interaction anxiety were more influenced by perceived marketplace influence. Consequently, they were more willing to use the new public infrastructure. When the market trend is to aggressively build a new public infrastructure, companies will accelerate their infrastructure upgrades to keep up with the trend (Hu et al. 2023 ; Liu and Zhao, 2022 ). Companies are increasingly incorporating virtual objects into familiar areas, forcing users to embrace mixed physical and virtual spaces. In addition, it is inevitable that digitally disadvantaged groups will have to use the new public infrastructure due to the market influence of people around them using this infrastructure to manage their government or life issues. When digitally disadvantaged groups with low levels of social interaction anxiety use the new public infrastructure, they are less likely to feel fearful and excluded (Kaihlanen et al. 2022 ) and will tend to be positively influenced by the use behaviours of others to use the new public infrastructure themselves (Troisi et al. 2022 ). The opposite is true for groups with high social interaction anxiety, which leads to significant differences in perceived marketplace influence and intentions to use among digitally disadvantaged groups with different levels of social interaction anxiety.

Existing mixed physical and virtual spaces exhibit exceptional technical complexity, and the results of this study affirm the importance of technical factors in affecting intentions to use. In this paper, we emphasised effort expectancy as the ease of use of the new public infrastructure (Venkatesh et al. 2003 ), which had a significant effect on digitally disadvantaged groups with high levels of social interaction anxiety but no significant effect on those with low levels of social interaction anxiety. Digitally disadvantaged groups with high levels of social interaction anxiety are likely to have a stronger sense of rejection due to environmental pressures if the new public infrastructure is too cumbersome to run or operate; they may therefore prefer using simple facilities and services. Numerous scholars have proven in educational (Hu et al. 2022 ), medical (Bai and Guo, 2022 ), business (Susanto et al. 2018 ), and other fields that good product design promotes users’ intentions to use technology (Chen et al. 2023 ). For digitally disadvantaged groups, accessible and inclusive product designs can more effectively incentivise their intentions to use the new public infrastructure (Hsu and Peng, 2022 ).

Facilitating conditions are technical factors that represent facility-related support services. The study results showed a significant positive effect of facilitating conditions on intention to use. This result is consistent with the results of previous studies regarding physical space. Professional consultation (Vinnikova et al. 2020 ) and training (Yang et al. 2023 ) on products in conventional fields can enhance users’ confidence, which can then be translated into intentions to use (Saparudin et al. 2020 ). Although the form of the new public infrastructure has changed in the direction of integration, its target object is still the user in physical space. Therefore, better facilitating conditions can enhance users’ sense of trust and promote their intentions to use (Alalwan et al. 2017 ; Mogaji et al. 2021 ). Concerning integration, because the new public infrastructure can assume multiple forms, it is difficult for digitally disadvantaged groups to know whether a particular infrastructure has good facilitating conditions. It is precisely such uncertainties that cause users with high social interaction anxiety to worry that they will be unable to use the facilities effectively. They may then worry that they will be burdened by scrutiny from strangers, causing resistance. Even when good facilitating conditions exist, groups with high social interaction anxiety do not necessarily intend to use them. Therefore, there were no significant differences between the different levels of social interaction anxiety in terms of facilitating conditions and intention to use them.

Theoretical value

In this study, we mainly examined the factors influencing digitally disadvantaged groups’ intentions to use the new public infrastructure consisting of mixed physical and virtual spaces. The empirical results of this paper make theoretical contributions to the inclusive construction of mixed spaces in several areas.

First, based on an understanding of urban development involving a deep integration of physical space with virtual space, we contextualise virtual space within the parameters of public infrastructure to shape the concept of a new public infrastructure. At the same time, by including the service system, the virtual community, and other non-physical factors in the realm where the virtual and the real are integrated, we form a concept of mixed physical and virtual spaces, which expands the scope of research related to virtual and physical spaces and provides new ideas for relevant future research.

Second, this paper makes a preliminary investigation of inclusion in the construction of the new public infrastructure and innovatively examines the factors that affect digitally disadvantaged groups’ willingness to use the mixed infrastructure, considering them in terms of individual, social, and technical factors. Moreover, holding that social interaction anxiety is consistent with the psychological characteristics of digitally disadvantaged groups, we introduce social interaction anxiety into the research field and distinguish between the performance of subjects with high social interaction anxiety and the performance of those with low social interaction anxiety. From the perspective of digitally disadvantaged groups, this shows the regulatory effect of social interaction anxiety on users’ psychology and behaviours. These preliminary findings may lead to greater attention being paid to digitally disadvantaged groups and prompt more studies on inclusion.

In addition, while conducting background research, we visited public welfare organisations and viewed government service lists to obtain first-hand information about digitally disadvantaged groups. Through our paper, we encourage the academic community to pay greater attention to theoretical research on digitally disadvantaged groups in the hope that deepening and broadening such research will promote the inclusion of digitally disadvantaged groups in the design of public infrastructure.

Practical value

Based on a large quantity of empirical research data, we explored the digital integration factors that affect users’ intentions to use the new public infrastructure. To some extent, this provides new ideas and development directions for inclusive smart city construction. Inclusion in existing cities mainly concerns the improvement of specific technologies, but the results of this study show that technological factors are only part of the picture. The government should introduce relevant policies to promptly adapt the new public infrastructure to digitally disadvantaged groups, and the legislature should enact appropriate laws. In addition, the study results can guide the design of mixed physical and virtual spaces for the new public infrastructure. Enterprises can refer to the results of this study to identify inconveniences in their existing facilities, optimise their service processes, and improve the inclusiveness of urban institutions. Furthermore, attention should be paid to the moderating role of social interaction anxiety in the process. Inclusive urban construction should not only be physical but should closely consider the inner workings of digitally disadvantaged groups. The government and enterprises should consider the specific requirements of people with high social interaction anxiety, such as by simplifying the enquiry processes in their facilities or inserting psychological comfort measures into the processes.

Limitations and future research

Due to resource and time limitations, this paper has some shortcomings. First, we considered a broad range of digitally disadvantaged groups and conducted a forward-looking exploratory study. Since we collected data through an online questionnaire, there were restrictions on the range of volunteers who responded. Only if participants met at least one of the conditions could they be identified as members of digitally disadvantaged groups and participate in a follow-up survey. To reduce the participants’ introspection and painful recollections of their disabilities or related conditions, and to avoid expected deviations from the data obtained through the survey, we made no detailed distinction between the participants’ degrees of impairment or the reasons for impairment. We adopted a twofold experimental approach.: first, a questionnaire that was too detailed might have infringed on the participants’ privacy rights, and second, since little research has been conducted on inclusiveness in relation to mixed physical and virtual spaces, this work was pioneering. Therefore, we paid greater attention to digitally disadvantaged groups’ intentions to use the new public infrastructure. In future research, we could focus on digitally disadvantaged individuals who exhibit the same deficiencies, or further increase the sample size to investigate the participants’ intentions to use the new public infrastructure in more detail.

Second, different countries have different economic development statuses and numbers of digitally disadvantaged groups. Our study mainly concerned the willingness of digitally disadvantaged groups to use the new public infrastructure in China. Therefore, in the future, the intentions of digitally disadvantaged groups to use new public infrastructures involving mixed physical and virtual spaces can be further explored in different national contexts. Furthermore, in addition to the effects of social interaction anxiety examined in this paper, future researchers could consider other moderators associated with individual differences, such as age, familiarity with technology, and disability status. We also call for more scholars to explore digitally disadvantaged groups’ use of the new public infrastructure to promote inclusive smart city construction and sustainable social development.

Previous researchers have explored users’ intentions to use virtual technology services and have analysed the factors that influence those intentions (Akdim et al. 2022 ; Liébana-Cabanillas et al. 2020 ; Nguyen and Dao, 2024 ). However, researchers have mainly focused on single virtual or physical spaces (Scavarelli et al. 2021 ; Zhang et al. 2020 ), and the topic has rarely been discussed in relation to mixed physical and virtual spaces. In addition, previous studies have mainly considered the technology perspective (Buckingham et al. 2022 ; Carney and Kandt, 2022 ), and the influence of digitally disadvantaged groups’ psychological characteristics and the effect of the overall social environment on their intentions to use have largely been ignored. To fill this gap, we constructed a UTAUT-based model for intentions to use the new public infrastructure that involved a mixing of physical and virtual spaces. We considered the mechanisms influencing digitally disadvantaged groups’ use of the new public infrastructure, considering them from the perspectives of individual, social, and technical factors. We processed and analysed 337 valid samples using PLS-SEM. The results showed that there were significant correlations between the six user factor variables and intention to use the new public infrastructure. In addition, for digitally disadvantaged groups, different degrees of social interaction anxiety had significantly different effects on the impacts of performance expectancy, psychological reactance, perceived marketplace influence, and effort expectancy on intention to use, while there were no differences in the impacts of perceived institutional support and facilitating conditions on intention to use.

In the theoretical value, we build on previous scholarly research on the conceptualisation of new public infrastructures, mixed physical and virtual spaces (Aslesen et al. 2019 ; Cocciolo, 2010 ), arguing for user, social and technological dimensions influencing the use of new public infrastructures by digitally disadvantaged groups in mixed physical and virtual spaces, and for the moderating role of social interaction anxiety. Meanwhile, this study prospectively explores the new phenomenon of digitally disadvantaged groups using new public infrastructures in mixed physical and virtual spaces, which paves the way for future scholars to explore the field both in theory and literature. In the practical value, the research findings will be helpful in promoting effective government policies and corporate designs and in prompting the development of a new public infrastructure that better meets the needs of digitally disadvantaged groups. Moreover, this study will help to direct social and government attention to the problems that exist in the use of new public infrastructures by digitally disadvantaged groups. It will have a significant implication for the future development of smart cities and urban digital inclusiveness in China and worldwide.

Data availability

The datasets generated during and/or analysed during the current study are not publicly available due to the confidentiality of the respondents’ information but are available from the corresponding author upon reasonable request for academic purposes only.

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Acknowledgements

This research was supported by the National Social Science Foundation of China, grant number 22BGJ037; the Fundamental Research Funds for the Provincial Universities of Zhejiang, grant number GB202301004; and the Zhejiang Province University Students Science and Technology Innovation Activity Program, grant numbers 2023R403013, 2023R403010 & 2023R403086.

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These authors contributed equally: Chengxiang Chu, Zhenyang Shen, Hanyi Xu.

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School of Management, Zhejiang University of Technology, Hangzhou, China

Chengxiang Chu, Zhenyang Shen, Qizhi Wei & Cong Cao

Law School, Zhejiang University of Technology, Hangzhou, China

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Conceptualisation: C.C., CX.C. and ZY.S.; Methodology: CX.C. and HY.X.; Validation: ZY.S. and QZ.W.; Formal analysis: HY.X.; Investigation: CX.C., ZY.S. and HY.X.; Resources: C.C.; Data curation: CX.C. and HY.X.; Writing–original draft preparation: CX.C, ZY.S., HY.X. and QZ.W.; Writing–review & editing: CX.C and C.C.; Visualisation: ZY.S. and HY.X.; Supervision: C.C.; Funding acquisition: C.C., CX.C. and ZY.S.; all authors approved the final manuscript to be submitted.

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Chu, C., Shen, Z., Xu, H. et al. How to avoid sinking in swamp: exploring the intentions of digitally disadvantaged groups to use a new public infrastructure that combines physical and virtual spaces. Humanit Soc Sci Commun 11 , 1135 (2024). https://doi.org/10.1057/s41599-024-03684-0

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Research on Hot Deformation Behavior of Ti-5Al-5Mo-5V-1Cr-1Fe Titanium Alloy with Basket-Weave Microstructure

• Advanced Characterization on Thermodynamic and Kinetics of Complex Alloys
• Published: 05 September 2024

Cite this article

• Yingying Liu   ORCID: orcid.org/0000-0001-9185-3380 1 , 2 ,
• Siyu Tan 1 ,
• Jian Yang 3 ,
• Xuan Liu 1 ,
• Junjie Yang 1 ,
• Chun Li 2 ,
• Shifeng Liu 1 ,
• Wen Wang 1 , 4 &
• Kuaishe Wang 1 , 4  

The hot deformation behavior of Ti-5Al-5Mo-5V-1Cr-1Fe titanium alloy with basket-weave microstructure was studied by the thermal compression experiment conducted at temperatures ranging from 1073 K to 1193 K and strain rates from 0.001 s −1 to 1 s −1 . The results indicate that the stable flow state of the stress–strain curve of Ti-5Al-5Mo-5V-1Cr-1Fe alloy is rapidly reached within a small strain range (< 0.1). The majority of flow curves exhibit horizontal plateaus, which is attributed to the rapid equilibrium between dislocation accumulation and annihilation. Within the experimental parameters, the constitutive equation at ε  = 0.3, thermal activation energy of 346.017 KJ mol −1 and the strain rate sensitivity exponents between 0.25 and 0.4 for basket-weave microstructureTi-5Al-5Mo-5V-1Cr-1Fe titanium alloy with basket-weave microstructure were calculated. During hot deformation, there are phase transformations and several softening mechanisms, including lamellar spheroidization, dynamic recrystallization, dynamic recovery and their interactions. The β transition structures are cut by a large number of interleaved α lamellar structures, and the α lamellar structures are participated in coordinated deformation, which promotes the enhancement of strength and plasticity of Ti-5Al-5Mo-5V-1Cr-1Fe alloy. The model and microstructure analysis in this research can provide data reference for material selection and processing optimization of aircraft structural parts with high impact toughness and strength.

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The article is protected by copyright. This work was supported by the fund of the National Defence Key Discipline Laboratory of Light Alloy Processing Science and Technology, Nanchang Hangkong University (EG202380294), Natural Science Foundation of Shaanxi Province of China (2022GY-232) and the Xi’an Science and Technology Program (Grant No.24LLRHZDZX0008). The authors would also like to thank Lei Yang and Wenjuan Niu of Xi’an University of Architecture and Technology for their assistance.

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Liu, Y., Tan, S., Yang, J. et al. Research on Hot Deformation Behavior of Ti-5Al-5Mo-5V-1Cr-1Fe Titanium Alloy with Basket-Weave Microstructure. JOM (2024). https://doi.org/10.1007/s11837-024-06855-1

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Downstream impacts of dam breach using HEC-RAS: a case of Budhigandaki concrete arch dam in central Nepal

• Anu Awal 1 ,
• Utsav Bhattarai 2 ,
• Vishnu Prasad Pandey 3 &
• Pawan Kumar Bhattarai 4  

Environmental Systems Research volume  13 , Article number:  37 ( 2024 ) Cite this article

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Studies on concrete dam breach are limited compared to earthen and other types of dams. With an increase in the construction of concrete dams, particularly in the developing world, it is imperative to have a better understanding of the dam breach phenomena and the identification of the most influential breach parameters. This study aims to contribute to this gap by taking the case of the concrete arch dam proposed for the 1200 MW Budhigandaki Hydropower Project located in central Nepal. This study carries special significance for Nepal, primarily because of the increasing number of under construction and proposed large dams for water resources development in the country. We carry out dam breach analysis of the Budhigandaki dam using HEC-RAS 2D model to calculate the flood discharge peaks, time to peak, water surface elevation and the extent of inundation for two scenarios (with and without probable maximum flood) to estimate the damage on four downstream settlements. We carry out sensitivity analysis of the breach parameters on the flood magnitudes and severity. Results show that all the study locations lie in the high flood hazard zone. Flood peaks can reach as high as 286,000 m 3 s − 1 to 511,000 m 3 s − 1 in the considered settlements. The time to peak ranges from 11.3 to 17 h after the breach at these locations. We estimate that if a breach should happen, it would most likely inundate around 150,000 buildings, impact nearly 672,000 lives and flood 3,500 km of road downstream. Furthermore, dam breach elevation is found to be the most sensitive parameter to downstream floods. Hence, rather than structural measures, it is recommended that non-structural measures are implemented for minimizing the impacts of flood disasters at the study locations. The findings could be a useful reference for future dam projects in Nepal and other areas with similar hydrological and topographical conditions.

Introduction

Dams are storage structures providing beneficial functions such as flood control and water supply for different types of users (for example, domestic water supply, hydropower, irrigation, recreation and water transport). The construction of large dams along with generation of electricity started during the industrial revolution in Europe and America. The early 1900s ushered in an era of “big dam” building in America mostly for hydropower generation as demands for electricity increased, the Hoover Dam being regarded as an engineering marvel. The Asian region includes some of the largest dams in the world today such as Tarbela Dam and Mangla Dam in Pakistan, Nurek Dam in Tajikistan, San Rogue Dam in Phillipines and Three Gorges Dam in China, mostly for hydropower generation.

Despite the benefits, failure of dams can cause tremendous losses by generation of unforeseen flood magnitudes in downstream areas. Unfortunately, the history of dams has been studded with disasters of various types, sometimes of great magnitude, with loss of human lives and destruction of property and infrastructure (Aureli et al. 2021 ). USACE ( 2018 ) lists causes of dam breach as earthquakes, landslides, extreme storms, piping, equipment malfunction, structural damage, foundation failure, and sabotage. Regardless of the reason, almost all failures begin with a breach formation.

Basically, breach is defined as the opening formed in the dam body that leads the dam to fail and this phenomenon causes the stored water behind the dam to propagate rapidly downstream (Dincergok 2007 ). Despite piping or overtopping being the main modes of dam failure, the actual mechanics are still not completely understood for either earthen or concrete dams (USACE 2018 ). Past dam-failure disasters have shown that the majority of dams that have failed are earthen (74 dam breaks out of 7812 earthen dams) and the highest percentage of failure of rockfill dams (17 dam breaks out of 200 rockfill dams) (Fang et al. 2017 ). The world’s worst dam disaster happened in China in 1975 when the Banqiao and Shimantan dams failed killing about 171,000 people while 11 million lost their homes (Vincent et al. 2020 ). In 1979, the 25 m high Machu Dam in India, which stored 100 million m 3 , failed after several hours of over-topping causing about 10,000 deaths, 150,000 people were displaced, and 10,000 habitations were destroyed (Lempérière 2017 ). A recent case of the failure of the Rishiganga dam in Uttarakhand (India) in 2021 due to glacier avalanche caused more than 200 deaths and severely damaged infrastructure (Shugar et al. 2021 ). Similarly, failure of the Edenville dam followed by the Sanford dam downstream on the same day in 2020 due to heavy rain in Michigan USA ( Independent Forensic Team 2022 ), and failure of the Spencer Dam in Nebraska USA in 2019 due to ice run (Ettema et al. 2021 ), demonstrate the devastation that dam breaches can lead to. Thus, identification of the vulnerable areas and being aware of the likely damages are key for minimization of the adverse impacts of dam breach.

Dam breach analysis involves three key sequential steps: predicting the reservoir outflow hydrograph, determining dam breach parameters, and routing the hydrograph downstream. Essentially, the breach flood hydrograph depends on the prediction of breach geometry and breach formation time (Basheer et al. 2017 ). There have been many studies on dam breach analysis around the world from the 1980’s (Leng et al. 2023 ; Singh and Snorrason 1984 ; USACE 2024 ). Dam breach analysis is generally carried out by either numerical/computer models or scaled-down physical models. The United States Department of Interior ( 1988 ), recommends estimating a reasonable maximum breach discharge using four principal methods:

Physically Based Methods: Using erosion models based on principles of hydraulics, sediment transport and soil mechanics, development of breach and resulting breach outflow are estimated;

Parametric Models: Time to failure and ultimate breach geometry are assessed utilizing case studies; breach growth is simulated as a time-dependent linear process and breach outflows are computed using principles of hydraulics;

Predictor Equations: Using data of case studies, peak discharge is estimated from empirical equations and a reasonable shape of outflow hydrograph is assumed; and.

Comparative Analysis: Breach parameters are determined by comparison of dam under consideration and a dam that failed.

There are far fewer studies on the failures of concrete dams compared to earthen dams, especially due to breaches which leads to difficulty in determining the concrete dam breach parameters (Fang et al. 2017 ). Moreover, a study of well documented dam-failure cases showed that empirical formulas provide results closer to reality (Fang et al. 2017 ). For instance, Froehlich( 1995 ) developed a prediction equation for the average breach width based on 63 cases of embankment-dam failures and an equation for the breach-formation time based on 21 cases. Focusing on earthen dams has been driven by their historical prevalence, cost-effectiveness, and adaptability. However, studying concrete arch dams is crucial for advancing engineering practices, improving safety and efficiency in dam construction, supporting hydroelectric power generation, addressing environmental impacts, and preserving significant cultural landmarks. Many federal agencies such as FERC ( 1993 ),Office of the State Engineer( 2020 ) and USACE ( 2014 ) have published guidelines recommending possible ranges of values for breach width, side slopes, and development time for different types of dams. This study aims to investigate the breach characteristics of concrete arch dams, an area with limited existing literature. Several dam breach analysis studies have been carried out in Nepal such as in Kulekhani dam using HEC-RAS (Pandey et al. 2023 ), Kaligandaki landslide dam using BREACH (Bricker et al. 2017 ), Koshi high dam using HEC-RAS (Gyawali, D.R. and Devkota, 2015 ), among others. However, no sensitivity analysis of dam breach parameters has been carried out for the afore-mentioned studies.

The proposed Budhigandaki dam located in the transboundary Budhigandaki Basin, spread over southern China and central Nepal, is taken as a case. The Government of Nepal (GoN) has prioritized hydropower generation as the backbone of economic development to attain the goals to raise the country’s status to middle income country level by 2030 (Government of Nepal 2020 ). As a result, there are currently more than 9 planned and proposed large hydropower dam projects by the state (Nepal Electricity Authority 2022 ). The Budhigandaki Hydropower Project (BGHPP) could be the largest storage project of Nepal, if constructed, which could lead to catastrophic damages downstream in the event of a breach.

Hence, the overarching objective of this study is to assess the flood impacts of the Budhigandaki Dam on the downstream settlements due to possible dam breach scenarios. Specifically, this study intends to quantify the peak discharge, time to peak, and the water surface elevation at the downstream locations due to a dam-breach flood. Further, sensitivity analysis of five different dam breach parameters is conducted to acquire information about extent of influence of each parameter on the dam breach. The analysis is carried out in the widely-used hydraulic model Hydrologic Engineering Center’s - River Analysis System (HEC-RAS) developed by the United States Army Corps of Engineers (USACE). Furthermore, zoning of the downstream settlement areas in Geographic Information System (GIS) based on flood severity provides meaningful information to the project developers as well as planners in the impacted areas.

Materials and methods

The Budhigandaki Hydropower Project (BGHPP) is a 1200 MW storage type proposed project of Nepal located approximately 2 km upstream of the confluence of Budhigandaki River with Trishuli River as shown in Fig.  1 . The Budhigandaki Dam is a 263 m high double curvature concrete arch dam with a reservoir volume of 4.5 billion cubic meters (BCM), out of which the active storage is 2.2 BCM. The dam crest length is 737.4 m and the reservoir Full Supply Level (FSL) is at 540 m above sea level (masl) (Budhigandaki Development Committee, 14a). There are some major settlement areas nearly 110 km downstream which are susceptible to danger in case of dam breach. For this study, four major towns namely, Narayangarh, Baraghare, Divyanagar and Meghauli, have been assessed. Moreover, future risk of impact from the dam failure can be expected to increase as increased in population growth due to improved job opportunities and other economic activities in the area because of the construction of the dam. Therefore, the Budhigandaki Dam has been taken as a case in this study to assess the flooding impacts of the dam on the downstream areas through simulation of a hypothetical dam failure.

Location of Budhigandaki dam and downstream settlement areas

Methodology

Dam breach analysis of the Budhigandaki dam has been carried out in HEC-RAS using unsteady flow simulation with terrain and land cover as the geometric input data. The upstream boundary condition is the probable maximum flood (PMF) hydrograph which has been generated using an empirical method while the downstream boundary condition is normal depth. Two dam failure scenarios, namely, dam breach at reservoir full condition with PMF (Scenario I: base case) and dam breach at reservoir full condition without PMF (Scenario II), have been modelled in the study. Outputs of the simulation are used for creating flood inundation maps, flood hazard vulnerability maps and flood arrival time maps corresponding to the different scenarios. Sensitivity analysis of the dam breach parameters is also carried out to assess their impacts on the flood conditions downstream of the dam. Figure  2 summarizes the overall research methodology.

Overall research methodology of this study. DEM: Digital Elevation Model, PMP: Probable Maximum Precipitation, PMF: Probable Maximum Flood, SA: Storage Area, 2D: Two Dimensional, FSL: Full Supply Level

The spatial inputs required to model the dam breach are digital elevation model (DEM), land cover and Manning’s roughness coefficient. Rainfall and discharge are needed for generation of inflow hydrograph as upstream boundary condition to the model. In addition, infrastructure data of the downstream area is required for estimating the impacts of floods. Details of the required data and their sources are presented in Table  1 .

PMP and PMF

The probable maximum precipitation (PMP) is the theoretical maximum precipitation for a given duration under current meteorological conditions (World Meteorological Organization 2009 ). Daily maximum rainfall data of 13 surrounding stations from 1972 to 2014 has been used for the calculation of PMP. The 1-day PMP for all the stations was calculated using Hershfield formula (Hershfield 1965 ) given in Eq. ( 1 ) :

Where, PMP  = Probable maximum precipitation.

M  = mean of maximum daily rainfall sample S  = Standard deviation.

K  = Frequency factor = 15 (Hershfield 1965 ).

The calculated 1-day PMP of the point stations was further interpolated using Thiessen Polygon, Kriging, Spline and Inverse Distance Weighing (IDW) methods in GIS to compute the 1-day PMP for the Budhigandaki Basin. In order to model a worst-case scenario, the maximum value of the PMP among these methods was chosen for generating the PMF hydrograph.

Probable Maximum Flood (PMF) is theoretically the flood resulting from a combination of the most severe meteorological and hydrologic conditions that could conceivably occur in a given area (FERC 2001 ). HEC-RAS requires a flood hydrograph to be provided as input for the unsteady flow analysis in the dam breach model. Therefore, a synthetic unit hydrograph was developed using Snyder’s Method (American Geophysical Union 1938 ) using the following equations (Eq. ( 2 ) to Eq. ( 7 ) which was then transposed to generate a direct runoff hydrograph of PMF.

Mathematically,

Dam breach analysis

Dam breach analysis of the Budhigandaki dam has been carried out in HEC-RAS model under two-dimensional dynamic (unsteady-flow) mode. Hypothetical breach of the dam and its propagation downstream has been modelled using 2D Diffusion wave equations (Eq. ( 8 ) to Eq. ( 10 )).

Where, h is the water depth (m), p and q are the specific flow in the x and y directions (m 2 s − 1 ), ζ is the surface elevation (m), g is the acceleration due to gravity (9.8 m s − 2 ), n is the Manning’s coefficient, ρ is the water density (1000 kg m − 3 ), τ xx , τ yy , and τ xy are the components of the effective shear stress along x and y directions (N m − 2 ), and f is the Coriolis (s − 1 ).

Two-dimensional (2D) mesh of size 100 m x 100 m was chosen to represent the downstream land. Comparison of different mesh sizes (100 m and 200 m) indicated no significant difference in model performance. The storage areas and downstream areas are connected using an inline structure (Budhigandaki dam) as shown in Fig.  3 . “Storage Area” refers to upstream reservoir of the dam axis while “Downstream Study Area” represents the four towns (Narayangarh, Baraghare, Divyanagar, and Meghauli) located downstream which are likely to be inundated in case of dam breach (BGHP, 2015). Boundary conditions are required at the upstream and downstream ends of the model for flood routing. The upstream boundary was fixed at the reservoir extent (storage area) and the boundary condition was provided in the form of flood hydrograph generated from PMF. Outlet is the downstream boundary past the settlement areas as shown in Fig.  3 while the boundary condition of normal depth is maintained by providing the river bed-slope obtained from the DEM.

HEC-RAS 2D flow area and model schematic for the flood simulation of Budhigandaki dam breach

Scenarios and sensitivity analysis

In order to quantify the downstream effects of the Budhigandaki dam breach, the following two scenarios have been simulated:

Scenario 1: Dam breach when reservoir is at FSL with PMF. Scenario 2: Dam breach when reservoir is at FSL.

Only overtopping breach mode was analyzed as the dam is made up of concrete and there are less chances of other failure modes (Zhang et al. 2016 ). Moreover, for better understanding the Budhigandaki dam breach mechanism and impacts, sensitivity analysis of the following five important breach parameters as breach bottom elevation, breach bottom width, breach weir coefficient, breach formation time and breach side slope was carried out by varying their values over a reasonable range obtained from literature.

Scenario I have been considered as the base case. Sensitivity of the above-mentioned breach parameters on flood peak discharge, water surface elevation and flood arrival time at the four downstream locations along with inundation area are analyzed considering the base case.

The inputs for the dam break analysis adopted for the base case i.e., Scenario I is listed in the Table  2 . The values of breach parameters have been derived from FERC ( 1993 ), Office of the State Engineer ( 2020 ) and USACE ( 2014 ) specific for concrete dams.

Flood characteristics from 2D simulations

Using RAS Mapper, a series of flood maps were generated based on the outputs of the 2D simulation of the Scenario I dam breach. These maps were helpful in identifying the potentially risky and safe areas. The outputs of the HEC-RAS model were exported to GIS for further analysis and mapping.

Maximum Flood depth map

Using the simulation results, flood inundation maps were prepared illustrating the maximum flood depths across the study area for the different scenarios.

Flood Hazard Vulnerability Map : A flood hazard vulnerability map based on the product of depth and velocity was prepared using the Australian Rainfall-Runoff Guidelines (Australian Rainfall and Runoff 2019 ) which categorize the flood in six zones as: H1 ( D*V ≤  0.3, D max = 0.3 m, V max = 2.0 m/s, safe for people, vehicles and buildings); H2 ( D*V ≤  0.6, D max = 0.5 m, V max = 2.0 m/s, unsafe for small vehicles); H3 ( D*V  ≤ 0.6, D max = 1.2 m, V max = 2.0 m/s, unsafe for vehicles, children and elderly); H4 ( D*V  ≤ 1.0, D max = 2.0 m, V max = 2.0 m/s, unsafe for people and vehicles); H5 ( D*V  ≤ 4.0, D max = 4.0 m, V max = 4.0 m/s, unsafe for people and vehicles, buildings vulnerable to structural damage) ; H6 ( D*V >  4.0, unsafe for people and vehicles, all buildings vulnerable to failure) where D and V refer to the flood depth and velocity, respectively while D max and V max refers to the maximum depth and maximum velocity, respectively.

Flood arrival Time Map

Flood arrival time maps represent the computed time (in hours or days) from a specified time in the simulation when the water depth reaches a specified inundation depth. For the case of Budhigandaki dam breach, flood arrival times at the four settlement areas were calculated and mapped.

Estimated values of PMP and PMF

The 1-day PMP value using the 13 precipitation stations was calculated to be 518 mm, 530 mm, 556 mm and 485 mm using Thiessen polygon, Kriging, inverse distance weighted (IDW), and Spline interpolation methods, respectively. As a worst-case scenario, we chose the IDW method, which gave the maximum value of PMP among the four methods, for generating the PMF hydrograph. Using the input data listed in the Appendix 1, ordinates of the synthetic unit hydrograph was computed using Snyder’s method as shown in Fig.  4 .

Synthetic Unit Hydrograph and Probable Maximum Flood Hydrograph for the Budhigandaki dam

From the synthetic unit hydrograph and rainfall intensity duration curve, Direct Runoff Hydrograph was generated. The flood values are generated for a 60-minute interval by linear interpolation between the ordinates of the unit hydrograph. August is the month with the highest flows at the Budhigandaki dam site. Therefore, base flow of 441 m 3 s − 1 which is the mean August flow (during 1964–2012) was added to obtain the final hydrographs (BGHPP Development Committee 2014b ). The final results are plotted in Fig.  4 . I t can be seen that the peak discharge of 11,669 m 3 s − 1 occurs at 33.9 h after the start of rainfall for PMF + base flow.

Flood depth and flood hazard vulnerability

The river valley of 110 km length from Budhigandaki dam to Meghauli was considered for the analysis. The maximum flood depth Fig.  5 shows that the flood depth is as high as 212 m in the upstream area as the river channel is narrow whereas the depth becomes lesser in the downstream river sections where the area is relatively wide and plain. The maximum water depths at Narayangarh is estimated to be 90 m followed by 50.3 m at Baraghare.

Flood Inundation Map Based on Maximum Depths

Similarly, Flood Hazard Vulnerability Map based on the depth and velocity was prepared as shown in Fig.  6 . It can be identified from the map that all the downstream area lies in H6 zone i.e., unsafe for people and vehicles and all buildings are vulnerable to failure.

Flood Hazard Vulnerability Mapping Based on Depth and Velocity

Flood arrival time

Simulated flood peak arrival times calculated at the four downstream settlement areas are shown in Fig.  7 . It is useful in designing of early warning systems at these locations. It can be seen that the travel times range from 11.3 h (Narayangarh) to 17 h (Meghauli) immediately after the dam breach depending on the proximity from the dam.

Flood arrival time for the major downstream settlement locations; D/S is downstream

Flood inundation across different land covers

As an impact of dam breach on land cover, it is seen that the inundated type to be most likely inundated is agricultural area (538 km 2 ). Similarly, 239 km 2 of forest is likely to be inundated second in rank. Grassland, water body, barren area, built-up area and shrub land are expected to be inundated with areas of 43 km 2 , 38 km 2 , 25 km 2 , 22 km 2 and 1.5 km 2 respectively as shown in Fig.  8 .

Inundation extent due to dam breach by land cover

Flood Impact on Water Surface Elevation (WSE) and peak discharge

Water surface elevations along the modelled river reach corresponding to the two scenarios are shown in Fig.  9 . It is seen that the water surface is nearly 110 m above the bed level at immediate downstream of the dam site while it is as low as 30 m in the downstream study areas. There is an enormous volume of water flowing down in a very short time because of the breach resulting in such high values of water depths along the river reach. There is very less change in the water surface elevation between Scenario-1 and 2. Also, at the settlement areas, the flow width is large i.e., flat plain area and hence lesser change is seen on the water surface elevation at downstream areas.

Profile of water surface elevation and river bed for Scenario I and Scenario II. Scenario I: Dam Breach at FSL with PMF and Scenario II: Dam Breach at FSL without PMF

For the two scenarios (Scenario-1 and Scenario-2), the flow hydrographs have been compared at immediate downstream of the dam and at the four major settlement locations as shown in Fig.  10 . It is to be noted that the peak discharge occurs nearly at the same time for both scenarios at all locations. At Narayangarh, peak discharges for Scenarios-1 and 2 are 511,587 m 3 s − 1 and 501,479 m 3 s − 1 respectively i.e., around 2% of difference in the value. Similarly, at Baraghare, the peak discharge for Scenario-1 is 454,267 m 3 s − 1 whereas 441,862 m 3 s − 1 for Scenario-2 and for Divyanagar, the peak discharge for Scenario-1 is 364,697 m 3 s − 1 whereas 357,294 m 3 s − 1 for Scenario II respectively. Lastly for Meghauli, the peak discharge for Scenario-1 is 294,928 m 3 s − 1 whereas 286,813 m 3 s − 1 for Scenario-2. It is obvious that the peak discharge for Scenario-1 is greater than that of Scenario-2, however, the differences in the peak values between the two scenarios are quite small (in the range of 2–3%). This implies that the storage volume of the dam is the major contributor to the flood discharge rather than the PMF.

Comparison of flood hydrographs at major study locations for Scenario I and Scenario II. Scenario I: Dam Breach at FSL with PMF and Scenario II: Dam Breach at FSL without PMF

Flood impact on infrastructure

The possible impact of inundation due to dam breach on buildings and roads was assessed. The total road length includes several types of roads such as highways, feeder roads, district roads and local roads. The inundated highway road length has been computed separately and all other types of roads has been kept as other roads (Table  3 ). It can be seen that Chitwan is the most impacted district with 58.5% of buildings and 2,541 km of road likely to be inundated. Meanwhile, Gorkha is expected to be the least affected district with 2.6% buildings and 132.4 km road inundated. Also, 149,311 numbers of buildings are inundated in total. If the total number of persons on average per household is taken as 4.5 (Cental Bureau of Statisitics 2016 ), a total of about 0.7 million people are likely to be affected by inundation in the case of dam breach. This is about 2.3% of the total population of Nepal.

• Sensitivity analysis

Sensitivity analysis was performed in order to estimate the impact of the breach parameters on the simulated floods in the downstream impacted areas. The values of the input breach parameters were changed within a reasonable range, one at a time, in the dam breach model and the corresponding values of the peak discharge, water surface elevation, flood arrival time and land inundation area were recorded. Breach bottom elevation was varied from 450 masl to 525 masl. Similarly, breach width was varied from 55 m to 150 m and breach weir coefficient was varied from 0.9 to 1.7. Also, breach formation time was varied from 0.05 h to 0.3 h and breach side slope was varied from 0.7:1 to 2.5:1 ( H : V ). Results of the sensitivity analysis have been presented in Table  4 .

Breach bottom elevation

It is seen from Table  4 that as the breach bottom elevation is increased from 450 masl to 525 masl, the value of peak discharge and WSE are significantly decreased at the different downstream locations. It is observed that a 30% increase in breach bottom elevation (450 masl to 475 masl) led to 20–35% decrease in peak discharge, 20–25% decrease in WSE at different downstream locations and nearly 30% decrease in inundation area (893 km 2 to 735 km 2 ). However, the flood peak arrival time is not much altered due to change in breach bottom elevation.

Breach bottom Width

It is seen from Table  4 that an increase in breach width from 55 m to 150 m corresponds to an increase in discharge, WSE and inundation area but the change is not as significant as compared to that of change in breach bottom elevation. A 30% increase in breach width (80 m to 105 m) led to nearly 3% increase in peak discharge at all downstream locations. However, not much change is seen on the WSE, flood arrival time and inundation area due to change in breach bottom width.

Breach weir coefficient

An increase in the breach weir coefficient from 0.9 to 1.7 led to increase in discharge, WSE and inundation area but with a smaller magnitude compared to that of change in breach bottom elevation (Table  4 ). A 20% increase in breach weir coefficient (1.44 to 1.7) led to nearly 3% increase in peak discharge at all downstream locations. Also, no significant change is seen on the WSE, flood arrival time and inundation area due to change in breach weir coefficient.

Breach formation time

Interestingly, there is very insignificant change in peak discharge, WSE, flood arrival time and inundation area due to varying breach formation time (Table  4 ). The values of peak discharge, WSE, flood arrival time and inundation area remain almost unchanged despite the breach formation time is increased up to 200% (0.1 h to 0.3 h).

Breach side slope

A 50% increase in the side slope (1.3:1 to 2:1) led to nearly 2–3% increase in peak discharge as shown in Table  4 . Also, no significant change is seen on the WSE, flood arrival time and inundation area due to change in breach side slope.

Thus, results of the sensitivity analysis varying the values of the breach parameters, namely, dam breach bottom elevation, breach bottom width, breach weir coefficient, breach formation time and breach side slope on the peak discharge, WSE, flood arrival time and downstream inundation area has been summarized in Table  5 . It can be seen that dam breach bottom elevation is the most sensitive parameter with respect to output values such as peak discharge, WSE and downstream inundation area while breach formation time is the least sensitive parameter with respect to all the output parameters.

We have estimated the PMP followed by PMF which is the upstream boundary condition required for the dam breach model in HEC-RAS. The PMP value was chosen as 556 mm from the IDW method. Also, the PMP value as per the detail design report (BGHPP Development Committee 2014b ) is 594 mm. Both the values of PMP are generated using Hershfield formula. However, this slight variation in the PMP values is due to the difference in the values of frequency factor. The value of frequency factor in this study is taken as 15 (Hershfield 1965 ). Subsequently, the PMF value for this study is generated using Snyder’s Unit Hydrograph Method with peak discharge as 11,669 m 3 s − 1 . Besides, by using regional method the PMF was calculated to be 11,479 m 3 s − 1 and regional regression flood analysis method 11,957 m 3 s − 1 (Department of Electricity Development 2006 ). Hence, the PMF values considered in this study are assumed to be reliable.

Impacts of dam breach and sensitivity analysis of dam breach parameters

Simulation results of Scenario I and Scenario II showed that there is a huge peak discharge immediately downstream of the dam breach (Fig.  10 and the difference in discharge values for both scenarios is low. The reason for this is due to the large storage volume of the dam leading to minimum effect of PMF being observed. Also, the downstream tributaries are much smaller compared to the Budhigandaki mainstream river. Hence, their additional impacts on the dam breach flood magnitudes can be considered to be marginal. Additionally, the outputs such as peak discharge, WSE, flood arrival time and inundation area from the dam breach has been estimated as a standalone event. The impact of addition of inflows from the other tributaries (for example, due to localized cloudburst events) to the mainstream river in the downstream settlement area could be areas of further study.

Previous dam breach analysis on Budhigandaki dam has been carried out by Tractebel and jade consult as JV using TELEMAC software (BGHPP Development Committee 2014a ). The output results of the previous study appeared to be quite different from the study carried out using HEC-RAS. There could be various reasons for such discrepancies. The TELEMAC model has considered full dam breach whereas our study does not consider full dam breach. Also, the earlier model has considered high accuracy resolution LiDAR data and other input data (mesh size 30 m*50 m) whereas our study considers 30 m*30 m DEM data and 100 m*100 m mesh size due to model stability issues. However, the pattern of change in peak discharge and WSE at the different study locations are quite similar for both models.

Dam breach analysis has been carried out in different parts of the world using HEC-RAS adopting a methodology similar to ours. For example, simulations of the breach of Batutegi earthen Dam, Indonesia (Wahyudi 2004 ), Mosul earthen Dam, Iraq (Basheer et al. 2017 ) and the results of sensitivity analysis are found out to be quite similar to this study. All these studies showed that dam breach bottom elevation is the most sensitive parameter. Further, the trends in WSE and peak discharge with time and distance from the dam obtained in these studies are also comparable to those of our study. The WSE and peak discharge increased with the increase in the breach parameters as breach bottom elevation, breach bottom width, breach weir coefficient and breach side slope. The peak discharge decreased with increase in breach formation time and negligible change was seen on WSE. Hence, through sensitivity analysis, it is seen that dam breach bottom elevation is the most sensitive parameter while breach formation time is the least sensitive parameter with regards to the floods.

Challenges to flood management

This analysis of a hypothetical dam breach provides insight to the level of possible damage should such a breach occur. Also, it can be deduced from this study that construction of embankments along the river is not a practical mitigation measure because of the extremely high-water depths (nearly 90 m) that these structures need to retain within them. Hence, other non-structural preventive measures such as creating awareness regarding flood risks, community-based flood early warning system (CBFEWS), training and deployment of efficient disaster response teams, zoning of high-risk areas, avoiding construction/settlements in such areas, identification of evacuation centers etc. are recommended. The Yokohama Strategy and Plan of Action (World Conference on Natural Disaster Reduction 1994 ), Hyogo Framework for Action 2005–2015 (International Strategy for Disaster Reduction 2005 ), and the current Sendai Framework for Action 2015–2030 (United Nations 2015 ) highlight the importance of early warning in reducing disaster risk and enhancing the resilience of vulnerable communities. CBFEWS generates and disseminates meaningful and timely flood warnings to vulnerable communities threatened by flood, so they can prepare and act correctly in sufficient time to minimize the possibility of harm. Owing to non-structural measures, the response and adaptation to floods of the vulnerable communities vary widely and are impacted upon by various factors, such as community resilience and susceptibility to flood. Also, the effectiveness of the non-structural measures appears sensitive to the socio-economic changes and governance arrangements (Dawson et al. 2011 ). Nonetheless, non-structural measures provide flexible flood management options for adapting to the ever-changing river basins, socio-economic and climate scenarios, and are in line with the spirit of environment friendly and sustainable development (Shah et al. 2018 ). Also, research on identification of shelter areas and evacuation plan can be an extension of this study using network analysis, buffers and proximity analysis in GIS. Moreover, the sensitivity analysis depicts the most sensitive breach parameters which need to be considered with extreme importance during planning, design, construction and operation of the dam.

Conclusions

This paper simulated the dam breach scenarios of the proposed Budhigandaki dam in central Nepal using HEC-RAS and assessed the impacts on the downstream settlements. Flood peaks, water surface elevations and flood arrival times were calculated for the two scenarios with and without PMF. In addition, sensitivity analysis was carried out to examine the influence of the breach parameters on the flood characteristics.

Results show that the entire downstream area lies in high hazard zone with flood arrival times at Narayangarh, Baraghare, Divyanagar and Meghauli ranges from 11.3 h to 17 h. Moreover, a total of 1,49,311 number of buildings are prone to inundation in the case of dam breach along with 671,900 lives at risk and around 3,500 km stretch of road most likely to be severely damaged. The dam-break flood peak exceeds 650,000 m 3 s − 1 in the immediate downstream of the dam while it attenuates to 511,000 and 286,000 m 3 s − 1 at Narayangarh and Meghauli, respectively. The maximum depth of water ranges from 30 m (in the downstream flat areas) to 212 m (in the upstream steep gorges) clearly discarding the physical and economic feasibility of structural measures for flood management in this case. In addition, 538 km 2 of agricultural land and 25 km 2 of built-up land is at risk of flood inundation. Therefore, it is imperative to implement preventive and non-structural measures such as creating awareness regarding flood risks, developing community-based flood early warning system (CBFEWS), training and deployment of efficient disaster response teams, zoning of high-risk areas, avoiding construction/settlements in such areas, identification of evacuation centers, monitoring and constant auscultation of the structure and developing robust and efficient emergency and alert plans.

Furthermore, the differences in the peak discharges and water surface elevations between the two scenarios are very less at the study locations. This implies that the impact of the huge storage volume of the reservoir on the breach flood characteristics is considerably larger in comparison to the PMF. In addition, change in dam breach bottom elevation was found to be the most sensitive to floods compared to other dam breach parameters.

Additionally, the methodology applied in this study is conveniently replicable of other dams, large or small. However, the simulation run-times may vary depending upon the size of the dam, mesh size, simulation time step and other model complexities. It is to be noted that the case may change for snow fed rivers and glacier lakes. Also, while applying this method to other projects, one should always be careful about the boundary conditions and the initial values of dam breach parameters as they vary depending upon the dam under consideration.

Nepal has currently only one storage dam hydropower project (Kulekhani) in operation. With a greater number of storage projects being planned and under construction, this study could be a useful reference for such future projects. Moreover, this study provides interesting results particularly related to the sensitivity of the breach parameters of concrete arch dams, which could be applicable in study of similar dams in other regions of the world.

Data availability

No datasets were generated or analysed during the current study.

Abbreviations

Catchment Area (km2)

Peak flow coefficient (-)

Lag Coefficient (-)

Coriolis (s − 1 )

acceleration due to gravity (m s − 2 )

water depth (m)

Frequency Factor (-)

main channel length from basin outlet to upstream watershed boundary (km)

main channel length from outlet to a point nearest to centroid of watershed (km)

Mean of Maximum daily rainfall (mm)

Manning’s Coefficient (-)

Specific flow in x-direction (m 2 s − 1 )

Probable maximum precipitation (mm)

Discharge (m 3 s − 1 )

Specific flow in y-direction (m 2 s − 1 )

Unit peak discharge (m 3 s − 1 )

Standard Deviation (mm)

Base time (hours)

Rainfall excess duration time (hours)

Basin Lag time (hours)

Width of unit hydrograph at discharge value exceeded 50% of the peak discharge (hours)

Width of unit hydrograph at discharge value exceeded 75% of the peak discharge (hours)

Surface Elevation (m)

Water Density (kg m − 3 )

Effective Shear Stress (N m − 2 )

Effective Shear Stress along x direction (N m − 2 )

Effective Shear Stress along x and y direction (N m − 2 )

Effective Shear Stress along y direction (N m − 2 )

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Acknowledgements

We wish to express my very deepest thanks and gratitude to Mr. Shreeram Shrestha, Civil Engineer, Chilime Hydropower Company Limited, Nepal for his continuous guidance, inspiration and encouragement during the initial preparation of building HEC-RAS model to result interpretation and completion of this study.

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

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Vishnu Prasad Pandey

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Contributions

A.A. and P.K.B. devised the project, the main conceptual ideas, and the proof outline. A.A. worked out almost all of the technical details, prepared figures, and performed the model analysis for the suggested topics. A.A., P.K.B, and U.B. verified the numerical results. A.A. and V.P.P. interpreted the Results. A.A. with the help of U.B., P.K.B., and V.P.P. wrote the manuscript. U.B., P.K.B., and V.P.P. worked on the discussion of results and commented on the manuscript. A.A. finalizes the manuscript after all the edits.

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Correspondence to Pawan Kumar Bhattarai .

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Awal, A., Bhattarai, U., Pandey, V.P. et al. Downstream impacts of dam breach using HEC-RAS: a case of Budhigandaki concrete arch dam in central Nepal. Environ Syst Res 13 , 37 (2024). https://doi.org/10.1186/s40068-024-00358-3

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Received : 31 March 2024

Accepted : 16 July 2024

Published : 01 September 2024

DOI : https://doi.org/10.1186/s40068-024-00358-3

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