Water resources planning based on complex system dynamics: A case study of Tianjin city

Zhang, X.H.; Zhang, Haiwei; Chen, Bin; Chen, G.Q.; Zhao, Xinhua

doi:10.1016/j.cnsns.2007.05.031

Cited by 88 publications

(42 citation statements)

References 4 publications

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“…Tianjin city is located in Haihe basin which is one of the most pollutant and thirsty river basins for water in China, and is typical region where water is a major constraint to the development. And some literature focused on the water resource issue of Tianjin city, which were mostly on the water resources planning (Zhang et al 2008b) and water resources demand forecasting (Zhang et al 2008a) based on complex system dynamics approach, and the urban water resources management (Bai and Imura 2001). While there was little work on the WRCC of Tianjin city, this paper proposed the practical method to assess the WRCC of Tianjin city based on the IWSD, CI and the CCRWR method.…”

Section: Discussionmentioning

confidence: 99%

Assessment of Water Resources Carrying Capacity in Tianjin City of China

Song

Kong

Zhan

2010

Water Resour Manage

140

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Regional sustainable development is an important focus on natural resources management, and also is a critical requirement for socio-economic system's sustainability. Water resource is one of the most important supports for the sustainable development of society and economy. The study proposed the concept of water resources carrying capacity (WRCC) to assess the scale of economy and population that the local water resources can support. And the study took Tianjin city of China for an example, and its population size and economic scale were chosen as two main indices. Based on the historical statistical datum, the carrying index (CI) and index of water supply-demand balance (IWSD) were evaluated, and then the current WRCC in Tianjin city and its dynamic tendency were evaluated by means of the method of carrying capacity of relative resources (CCRR). The results showed that the utilization of water resources in Tianjin is inefficient for now, the dynamic trend would be partly rational after the protection policy of water resource was put into practice in 2010 and 2020, and the WRCC of Tianjin city went beyond the average WRCC of China and was roughly equal to that of Beijing city. This paper showed that the rational policies and measures should be established and implemented to make sure utilize water resources efficiently in Tianjin city.Keywords Water resources carrying capacity · Carrying capacity of relative water resources · Carrying index · Index of water supply-demand balance · Tianjin City of China

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Section: Discussionmentioning

confidence: 99%

Assessment of Water Resources Carrying Capacity in Tianjin City of China

Song

Kong

Zhan

2010

Water Resour Manage

140

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“…A highly dense and fast growing urban population, an increasing consumption demand, and the increasing ability to utilize natural resources are depleting land resources (Bohnet and Pert, 2010). To satisfy city productivity, the transformation from ecological land (e.g., arable land, forest, grassland, wetlands) to constructed land (e.g., residential, commercial, industrial land) is more intense, especially in low-and middle-income countries in Asia, Africa, and Latin America facing severe urban population pressure before industrialization (Foley et al, 2005;MEA, 2005b;Zhang et al, 2008aZhang et al, , 2008b.…”

Section: Introductionmentioning

confidence: 99%

“…The top-down models include materials/energy-oriented models (material flow analysis, energy, emergy, exergy, ecological footprint and ecosystem service models) and structure-oriented models (system dynamics, ecological network analysis and exergy-network) , 2010Chen et al, , 2011Chen et al, , 2014Jiang and Chen, 2011;Jiang et al, 2009;Shao et al, 2013;Yang et al, 2010;Zhang et al, 2008aZhang et al, , 2008bZhang et al, , 2009). The bottom-up models include land use-oriented models (gravity model, market model, agentbased model, cellular model and MCRM) and infrastructureoriented models (in situ infrastructure model and life-cycle infrastructure model) (Chen et al, 2014;Knaapen, 1992).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of urban suitable ecological land based on the minimum cumulative resistance model: A case study from Changzhou, China

Feng

Song

et al. 2015

Ecological Modelling

184

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A B S T R A C TUrbanization is accompanied by the intense transformation and conflicts among different land use types that produce a series of economic, social, and environmental impacts. Ascertaining the quantity and pattern optimization of urban ecological land is critical to solving urban environmental problems and realizing urban sustainable development. Using the Chinese city of Changzhou, an important and typical city in the Yangtze River delta, as the case study, we applied the minimum cumulative resistance model (MCRM) to calculate the amount of ecological land that meets the demand of socioeconomic development and ecological protection considerating the source of ecological land and constructed land, ecosystem services, and the resistance plane. Results showed that the suitable ecological land area is about 1006.9 km 2 , which is 53.8% of the total urban area of Changzhou, and is mainly distributed in Wujin and Xinbei districts. Considering the ecological land space and functional changes of the study area and comparing the current land use status with the model simulation results, we propose three land use types. For urban ecological land, positive protection measures and prohibiting economic development initiatives are necessary. For ecotones between urban developed land and ecological land, protection should be given priority and economic development activities should be rigidly controlled. For constructed land, measurements and policies should be taken to promote reasonable development and improve land intensity.

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“…Usually, an SDM project consists of the following phases: problem definition, system conceptualization, model formulation, model evaluation/testing, policy analysis and implementation (Karavezyris et al 2002;Xu et al 2002;Ahmad and Simonovic 2004;Elmahdi et al 2007;Zhang et al 2008). It is important to determine the positive and negative relationships between variables, feedback loops, system archetypes and delays.…”

Section: System Dynamics Modellingmentioning

confidence: 98%

Water resources planning and management based on system dynamics: a case study of Yulin city

Wang

Zhang

Liu

et al. 2010

Environ Dev Sustain

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Water security is an integral aspect of the socio-economic development in China. Nevertheless, water resources are under persistent pressures because of the growing population, heavy irrigation, climate change effects and short-term policies. Traditional management approaches narrowly focus on increasing supply and reducing demand without considering the complex interactions and feedback loops that govern water resource behaviour. Whereas these approaches may provide quick fix solutions, they often lead to unanticipated, sometimes catastrophic, delayed outcomes. Therefore, water management needs to take a holistic approach that caters to the interdependent physical Readers should send their comments on this paper to BhaskarNath@aol.com within 3 months of publication of this issue.(e.g. water inflows, outflows) and behavioural (e.g. decision rules, perceptions) processes in the system. Unlike reductionist approaches, System Dynamics (SD) takes a system-level view for modelling and analysing the complex structure (cause-effect relationships, feedback loops, delays) that generates the systemic behaviour. Simulating the SD model allows assessing long-term system-wide impacts, exploring leverage points and communicating results to decision makers. In this paper, we follow an SD modelling approach to examine the future of water security in Yulin City. First, we present a conceptual model for integrating water supply and demand. Based on this, we build an SD model to simulate and analyse the dynamics of water resource over time. The model output is tested to ensure that it satisfactorily replicates the historical behaviour of the system. The model is used to quantitatively assess the effectiveness of various supply/demand management options. Three scenarios are designed and examined: business-as-usual, supply management, and demand management. Results show that current management regime cannot effectively meet the future water demand. Whereas supply acquisition provides short-term benefits, it cannot cope with the growing population. A combination of conservation measures and demand-management instruments is regarded the most effective strategy for balancing supply and demand.

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Water resources planning based on complex system dynamics: A case study of Tianjin city

Cited by 88 publications

References 4 publications

Assessment of Water Resources Carrying Capacity in Tianjin City of China

Assessment of Water Resources Carrying Capacity in Tianjin City of China

Evaluation of urban suitable ecological land based on the minimum cumulative resistance model: A case study from Changzhou, China

Water resources planning and management based on system dynamics: a case study of Yulin city

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