Developing a Conceptual Model for Sustainable water Resource Management and Agricultural Development: the Case of the Breede River Catchment Area, South Africa

Nyam, Yong Sebastian; Kotir, Julius H.; Jordaan, Andries; Ogundeji, Abiodun A.

doi:10.1007/s00267-020-01399-x

Cited by 14 publications

(5 citation statements)

References 76 publications

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“…Research on water resources focuses on water resource management (Talebmorad et al 2022;Varis and Vakkilainen 2001), water security (Ghashghaie et al 2022;Van Ginkel et al 2018), and water resource and sustainable development direction (Ostad-Ali-Askari 2022a, b, c;Nyam et al 2021). Yuan et al (2006) proposed that WRCC is the scale of water resources' support for economic and social growth and that the concept has obvious spatial and temporal connotations.…”

Section: Literature Reviewmentioning

confidence: 99%

Water resource carrying capacity and obstacle factors in the Yellow River basin based on the RBF neural network model

Sun

Zhou

Wang

2022

Environ Sci Pollut Res

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The Yellow River basin (YRB) plays an important role in China's economic and social growth. Based on different dimensions, we adopted the radial basis function (RBF) neural network model and the obstacle degree model to examine the water resource carrying capacity (WRCC) of the YRB. From 2005 to 2020, the WRCC of the entire YRB, as well as the upstream and midstream regions, improved, but the WRCC of the downstream region remained poor, revealing spatial differences. The overall improvement in the WRCC of the Yellow River's nine provinces is good, but the WRCC of Inner Mongolia and Henan is poor, suggesting regional differences. From the standpoint of obstacle factors, the development and usage rate of surface water resources are the main challenges. In 2020, the obstacle degree of the YRB reached 87.4871%. The irrigated area rate in Gansu was the primary obstacle factor, and the obstacle degree reached 73.0238%. Qinghai's industrial aspects mostly hindered the improvement of its WRCC, with an obstacle degree of 31.36%. The results provide a theoretical reference for the high-quality development of the YRB.

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Section: Literature Reviewmentioning

confidence: 99%

Water resource carrying capacity and obstacle factors in the Yellow River basin based on the RBF neural network model

Sun

Zhou

Wang

2022

Environ Sci Pollut Res

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“…Despite cognitive mapping being used to study various complex socio-environmental systems, such as water resource management (Inam et al, 2015;Bakhshianlamouki et al, 2020;Zhang et al, 2021;Nyam et al, 2021), water pollution (Diwakar and Thakur, 2012;Belayutham et al, 2016), and flood disasters (Rehman et al, 2019;Dzulkarnain et al, 2019), there is a limited number of research studies that have used this approach to assess specific issues in coastal systems. For example, Vasslides and Jensen (2016) conducted a study that mapped the estuarine system with the main focus on ecological function, while Furman et al (2021) mapped the coastal system and assessed various stakeholder groups' perceptions of the main components of the system.…”

Section: Bridging the Gapmentioning

confidence: 99%

A Participatory Modelling Approach to Cognitive Mapping of the Socio-Environmental System of Sandy Anthropogenic Shores in the Netherlands

Bakhshianlamouki¹,

Augustijn²,

Brugnach

et al. 2022

SSRN Journal

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“…However, despite its strategic importance, too little attention is still paid to building the key elements in creating value and establishing sustainable practices in business processes [1]. The key elements of strategic planning, decision-making, and management in complex systems such as agriculture are (i) using and integrating the emerging digital technologies; (ii) the circular approach and participation; (iii) transferring the knowledge and the appropriate policies into agricultural business process practices [1][2][3][4][5][6]. An approach that combines these key features improves the business performance [5] but also creates sustainable agricultural value [1].…”

Section: Introductionmentioning

confidence: 99%

“…Sustainable data-based value creation is a common approach that allows different stakeholders to influence decisions at different governmental levels of a complex structure [2]. In this research, we focused the circular perspective of the agricultural data ecosystem on the cooperation of all stakeholders and investigated data sharing needs based on the key characteristics and role of individual stakeholders in the sector and their role in the supply and demand for data.…”

Section: Introductionmentioning

confidence: 99%

“…It also contributes to the promotion of best management practices, the ones crucial for sustainable development and promoting effective resource management [3-5, 14, 15-17]. However, despite the focus on joint planning and management in agricultural operations, at the moment the effective cooperation remains limited [2]. The reasons are the complexity of the agricultural system, the large number of stakeholders with different perspectives, interests, values and concerns regarding business processes [2] which operate in an ecosystem where data and information exchange is lacking or is decentralized [6].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Towards Digital Innovation: Stakeholder Interactions in Agricultural Data Ecosystem in Croatia

Hrustek¹,

Furjan²,

Varga³

et al. 2022

Interdisciplinary Description of Complex Systems

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The successful adoption of digital innovations in agricultural production systems is based on the proactive participation of all stakeholders and represents an important step in establishing resilient agri-food chains and creating sustainable value. The key tool for the creation of sustainable value is integrating the nine aspects of the business process (cooperation; inclusion; financing; diversification; communication; policies; knowledge with entrepreneurship; and production) by re-using of open governmental and public endeavours data as well as by the contractual sharing. The objectives of this research are to identify stakeholders in the Croatian agricultural system, and to explore their roles and their potential for data supply and needs for data uptake. Open access repositories were queried to identify stakeholders. Direct observation methods and semi-structured conservational qualitative interviews were used for stakeholder characterisation and data flow detection. Stakeholder importance with respect to current data supply was analysed. Underdeveloped data flow relationships in the agricultural data ecosystem in Croatia could be built in a spontaneous process following the data opening of the Research and Consumer group of stakeholders and promoting data sharing initiatives of the early adopters in the Supplier group. In that way, data opening would be the driver of the effective cooperation creation required for sustainable value creation but also the adoption of the best management practices, sustainable solutions and digital development.

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Developing a Conceptual Model for Sustainable water Resource Management and Agricultural Development: the Case of the Breede River Catchment Area, South Africa

Cited by 14 publications

References 76 publications

Water resource carrying capacity and obstacle factors in the Yellow River basin based on the RBF neural network model

Water resource carrying capacity and obstacle factors in the Yellow River basin based on the RBF neural network model

A Participatory Modelling Approach to Cognitive Mapping of the Socio-Environmental System of Sandy Anthropogenic Shores in the Netherlands

Towards Digital Innovation: Stakeholder Interactions in Agricultural Data Ecosystem in Croatia

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