Dynamic simulation of the optimal allocation of water resources via the introduction of integrated water environmental policies in Baoding, China

Mou, Siyu; Yan, Jingjing; Sha, Jinghua; Li, Shule; Ma, Yufang; He, Gengyu; Song, Chenfei

doi:10.1007/s11356-019-05537-9

Cited by 10 publications

(2 citation statements)

References 29 publications

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“…It is particularly important to introduce comprehensive water environment policies and combine reinforcement learning technology for dynamic simulation and optimized configuration in order to achieve efficient utilization of water resources and protection of the ecological environment. Mou et al [12] explored how to combine comprehensive water environment policies with reinforcement learning to achieve a dynamic simulation of the optimal allocation of urban water resources. It utilizes reinforcement learning technology to establish a model for urban water resource management.…”

Section: Related Workmentioning

confidence: 99%

Exploration of Adaptive Environment Design Strategy Based on Reinforcement Learning in CAD Environment

Chen,

Chen

2024

CAD&A

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The main goal of this study is to combine computer-aided design (CAD) and reinforcement learning (RL) technologies to develop an adaptive water environment optimization strategy to cope with the increasingly severe water resource challenges. In this article, an intelligent decision-making system is constructed according to the actual water environment. The system can automatically adjust management strategies to maximize water quality improvement and ecosystem protection while minimizing management costs. To assess the strategy's efficacy, a range of simulation experiments have been devised to mimic its performance across varied water environmental conditions. The results show that the adaptive water environment optimization strategy is superior to the traditional management method in many key indicators, which significantly improves the efficiency and effect of water environment management. In addition, the strategy shows good adaptability and robustness and can maintain stable performance under complex and changeable water environment conditions. This study not only provides new theoretical and methodological support for the field of water environment optimization, but also points out the direction for future related research. It is expected that this strategy will play a greater role in practical application and contribute to the sustainable utilization and management of water resources.

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Section: Related Workmentioning

confidence: 99%

Exploration of Adaptive Environment Design Strategy Based on Reinforcement Learning in CAD Environment

Chen,

Chen

2024

CAD&A

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“…In recent work, fuzzy comprehensive quantitative evaluation, Drosophila optimization algorithm and Monte Carlo simulation method were used to evaluate hydrogeological risk and predict water quality evolution (Ouelhazi et al, 2014;Shojaei et al, 2015;Ruan et al, 2021), which could avoid the degradation of groundwater quality, improve the fragility of water resource systems and water ecological conditions, and improve the sustainable utilization capacity of regional water resources. Meanwhile, the coordinated development of water resources, economy and society has gradually attracted much attention (Ma et al, 2018;Song et al, 2018;Mou et al, 2019). Through multi-index dynamic comprehensive analysis and evaluation of water resources carrying capacity, including principal component analysis, system dynamics, ecological footprint, modeling studies can estimate the maximum development capacity and supporting capacity of regional water resources (Leeuwen and Sjerps 2015;Magri and Berezowska-Azzag 2019;Wang et al, 2018;Mou et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Dynamic Relationship Between Water Resources and New Urbanization Based on a Vector Autoregressive Model: A Case Study of Hebei Province, China

Yan

Pei

et al. 2022

Front. Environ. Sci.

Self Cite

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Overly rapid urban expansion in the past has significantly changed water resources, resulting in an imbalance between water resources and the sustainable development of new urbanization. To facilitate the sustainable development and utilization of water resources and promote the high-quality development of new urbanization, this study constructs evaluation index systems for water resources and new urbanization. The analytic hierarchy process, entropy method and projection pursuit method are used to determine the weight of each index, and Hebei Province is taken as an example for empirical analysis. The results indicate an upward trend for water resources in Hebei during the 2000–2019 period, while the water resources support capacity and water environmental pollution showed trends of gradual improvement but changed greatly, the water ecological carrying capacity gradually increased, and the negative impact of water disaster damage on the comprehensive situation of regional water resources gradually increased. Meanwhile, a qualitative breakthrough has been made in the development of new urbanization. Based on their evaluation results data, the long-term equilibrium relationship between water resources and new urbanization as well as the dynamics are empirically analyzed using a vector autoregressive model with a variable cointegration test, generalized impulse responses, and a decomposition prediction method using evaluation result data for the 2000–2019 period. There is indeed a supporting and inhibiting dynamic relationship between new urbanization and water resources as well as its components. At the early stage of urbanization, the endowment of water resources, the background value of the water environment, the ecological capacity of water and man-made water disasters were not fully considered, which led to the sharp contradiction between water resources and new urbanization. For a period, the decline in water resource support capacity and serious water environmental pollution have gradually become important factors limiting new urbanization in Hebei, and the constraining effects of the reduced water ecological carrying capacity and water disaster damage have gradually decreased. For future development, decision makers in Hebei should take measures such as adjusting the economic growth mode, improving resource utilization efficiency and technical level, and fully considering the positive role of new urbanization in promoting water resources and water environments. At the same time, Hebei Province should reduce the rate of water resource consumption by strengthening water conservation measures, optimizing the water utilization structure, and increasing investments in water pollution prevention and control to enhance the stability of water environments to realize the coordinated development of water resources and new urbanization.

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Drivers of dynamic evolution in provincial production water usage: perspective of regional relevance

Gao

Xie

Zhang

et al. 2020

Environ Sci Pollut Res

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Dynamic simulation of the optimal allocation of water resources via the introduction of integrated water environmental policies in Baoding, China

Cited by 10 publications

References 29 publications

Exploration of Adaptive Environment Design Strategy Based on Reinforcement Learning in CAD Environment

Exploration of Adaptive Environment Design Strategy Based on Reinforcement Learning in CAD Environment

Dynamic Relationship Between Water Resources and New Urbanization Based on a Vector Autoregressive Model: A Case Study of Hebei Province, China

Drivers of dynamic evolution in provincial production water usage: perspective of regional relevance

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