Simulation and optimization of water supply and demand balance in Shenzhen: A system dynamics approach

Li, Tianhong; Yang, Songnan; Tan, Mingxin

doi:10.1016/j.jclepro.2018.10.052

Cited by 64 publications

(42 citation statements)

References 18 publications

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“…The research on regulation refers to planning, such as water environment protection planning and water resources development planning, and then the target of WRCC is set. The positive and negative feedback effects in the HWRS are used to regulate the activities of social and economic, and finally, the carrying capacity is in line with the expected target [29]. In general, whether it is evaluation, prediction or regulation, the results of WRCC research can provide reference for regional socio-economic development and water resources protection, but the scope is limited.…”

Section: Literature Reviewmentioning

confidence: 99%

A Three-Stage Hybrid Model for Space-Time Analysis of Water Resources Carrying Capacity: A Case Study of Jilin Province, China

Liu

Yang

et al. 2020

Water

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Water shortage, water pollution, shrinking water area and water mobility are the main contents of the water resources crisis, which are widespread in the social and economic development of Jilin Province. In this paper, a three-stage hybrid model integrating evaluation, prediction and regulation is constructed by combining the load-balance method and the system dynamics method. Using this model, the current states of water resources carrying capacity (WRCC) in 2017 and the trend of water demand/available from 2018 to 2030 were obtained. Using the orthogonal test method, the optimal combination program of agricultural and industrial water efficiency regulation and water resources allocation was selected. The results show that the pressure of the human–water resources system in Changchun, Liaoyuan and Baicheng is greater than the support, and the other six cities are not overloaded. The water demand in Jilin Province and its nine cities will increase from 2018 to 2030, if the current socio-economic development pattern is maintained. Therefore, we change the water quantity carrying capacity index by controlling agriculture, industrial water efficiency and trans-regional water transfer. Compared with 2015, among the optimal program obtained, the change range of the water use per 10,000 RMB of agricultural output is (−5%, 25%), and the water use per 10,000 RMB of industrial added value is (−45%, −35%), and the maximum water transfer is 1.5 billion m3 per year in 2030. This study analyzes the development pattern of WRCC in the process of water conservancy modernization in Jilin Province and provides reference for other provinces to make the similar plan.

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Section: Literature Reviewmentioning

confidence: 99%

A Three-Stage Hybrid Model for Space-Time Analysis of Water Resources Carrying Capacity: A Case Study of Jilin Province, China

Liu

Yang

et al. 2020

Water

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“…The main research content of water resources operation in large-scale cities focuses on how to conduct the unified dispatching for different water sources under the present hydraulic engineering structure of the water supply system, and how to formulate the optimal operation schemes to meet the raw water demand of waterworks, considering the complex structure and uneven spatial and temporal distribution of water resources. A large number of case studies showed that the dynamic simulation of the water resources supply-demand balance can comprehensively use advanced technologies, such as a system analysis and computer simulation, to describe the complex internal relations and external boundaries of the water resources system in detail [33,34]. This paper will take the raw water dispatching system of Shenzhen as its research object.…”

Section: Plane Water Supply Unitmentioning

confidence: 99%

Study on the Raw Water Allocation and Optimization in Shenzhen City, China

Jiang

Wang

Liu

et al. 2019

Water

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In order to allocate the raw water of the complex water supply system in Shenzhen reasonably, this paper studied the complex network relationship of this large-scale urban water supply system, which consists of 46 reservoirs, 67 waterworks, 2 external diversion water sources, 14 pumping stations and 9 gates, and described each component of the system with the concepts of point, line and plane. Using the topological analysis technology and graph theory, a generalized model of the network topological structure of the urban water allocation system was established. On this basis, combined with the water demand prediction and allocation model of waterworks, a water resources allocation model was established, aiming at satisfying the guaranteed rate of the water supply. The decomposition and coordination principle of the large-scale system and the dynamic simulation technology of the supply-demand balance were adopted to solve the model. The forward calculation mode of controlling waterworks and pumps, and the reverse calculation mode of controlling reservoirs and waterworks were designed in solving the model, and a double-layer feedback mechanism was formed, which took the reverse calculation mode as outer feedback and the reservoir water level constraint or pipeline capacity constraint as inner feedback. Through the verification calculation of the case study, it was found that the proposed model can deal well with the raw water allocation of a large-scale complex water supply system, which had an important application value and a practical significance.

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“…In the past few decades, the SD model has been widely applied in sustainability to facilitate a holistic analysis of complex human–environmental systems [35,36]. Among them, human–water systems in various spatial scales such as countries, regions, cities, river basins or watersheds have formed a large amount of literatures [37,38,39,40,41,42,43,44]. The diversity of SD model applications has improved understanding of the complex interactions between human–water systems.…”

Section: Introductionmentioning

confidence: 99%

“…Meanwhile, few studies focused on the impacts of urbanization, or the urban–rural structure of population and economy, on water demand. Besides, the impacts of water pollution were often ignored when quantitatively modelling the relationship between urbanization and water scarcity [44]. As a consequence, the SD model approaches in urban agglomeration are scarce, and there is limited knowledge and understanding about the interaction and feedback behaviors of human–water systems in urban agglomeration.…”

Section: Introductionmentioning

confidence: 99%

Scenario Modeling of Urbanization Development and Water Scarcity Based on System Dynamics: A Case Study of Beijing–Tianjin–Hebei Urban Agglomeration, China

Bao

2019

IJERPH

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Due to the accelerated process of urbanization in China, urban agglomerations have become the core areas for human settlement and economic development. High population and economic density has brought great pressure on water supply. Water scarcity is increasingly becoming one of the most important issues for the sustainable and healthy development of China’s urban agglomerations. In this paper, a system dynamics model was constructed to simulate the current conditions and future scenarios of urbanization development and water scarcity in the Beijing–Tianjin–Hebei (BTH) urban agglomeration in 2000–2030, by examining the interaction and feedback between the six major subsystems: water supply, water demand, water pollution, population urbanization, economic urbanization, and land urbanization. It is found that the South-to-North Water Diversion Project and the improved Reclaimed Water Reuse System may greatly increase the water supply. However, the speed of population urbanization and economic growth, the spatial structure of urban agglomeration and the water consumption pattern may determine the water demand. Although all scenarios may risk water scarcity in the future at some point, we could detect a comprehensive and relatively rational scenario to balance water scarcity, regional equity, and efficiency. It might help to synthetically understand the coordinated development mode between urbanization and water resources in Beijing–Tianjin–Hebei (BTH) urban agglomeration, and provide a useful analytical and decision support tool for scientists and policy-makers to achieve the sustainable urbanization development and water resource management.

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Simulation and optimization of water supply and demand balance in Shenzhen: A system dynamics approach

Cited by 64 publications

References 18 publications

A Three-Stage Hybrid Model for Space-Time Analysis of Water Resources Carrying Capacity: A Case Study of Jilin Province, China

A Three-Stage Hybrid Model for Space-Time Analysis of Water Resources Carrying Capacity: A Case Study of Jilin Province, China

Study on the Raw Water Allocation and Optimization in Shenzhen City, China

Scenario Modeling of Urbanization Development and Water Scarcity Based on System Dynamics: A Case Study of Beijing–Tianjin–Hebei Urban Agglomeration, China

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