Assessing the Carrying Capacity of Water Resources in Wuhan City, China

Jia, Huan Huan; Yu, Guangming

doi:10.4028/www.scientific.net/amr.905.357

Cited by 4 publications

(3 citation statements)

References 15 publications

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“…Wuhan, Hubei province, China, is selected as the study area because of its numerous water bodies of different shapes and sizes, including natural lakes, small streams, and artificial ponds. Besides that, the Yangtze River also runs through it [37]. We collected 7 GaoFen-1D images (6 for training and 1 for testing) of Wuhan for 2020 as the experiment data.…”

Section: Study Area and Datementioning

confidence: 99%

A New Lightweight Convolutional Neural Network for Multi-Scale Land Surface Water Extraction from GaoFen-1D Satellite Images

et al. 2021

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Mapping land surface water automatically and accurately is closely related to human activity, biological reproduction, and the ecological environment. High spatial resolution remote sensing image (HSRRSI) data provide extensive details for land surface water and gives reliable data support for the accurate extraction of land surface water information. The convolutional neural network (CNN), widely applied in semantic segmentation, provides an automatic extraction method in land surface water information. This paper proposes a new lightweight CNN named Lightweight Multi-Scale Land Surface Water Extraction Network (LMSWENet) to extract the land surface water information based on GaoFen-1D satellite data of Wuhan, Hubei Province, China. To verify the superiority of LMSWENet, we compared the efficiency and water extraction accuracy with four mainstream CNNs (DeeplabV3+, FCN, PSPNet, and UNet) using quantitative comparison and visual comparison. Furthermore, we used LMSWENet to extract land surface water information of Wuhan on a large scale and produced the land surface water map of Wuhan for 2020 (LSWMWH-2020) with 2m spatial resolution. Random and equidistant validation points verified the mapping accuracy of LSWMWH-2020. The results are summarized as follows: (1) Compared with the other four CNNs, LMSWENet has a lightweight structure, significantly reducing the algorithm complexity and training time. (2) LMSWENet has a good performance in extracting various types of water bodies and suppressing noises because it introduces channel and spatial attention mechanisms and combines features from multiple scales. The result of land surface water extraction demonstrates that the performance of LMSWENet exceeds that of the other four CNNs. (3) LMSWENet can meet the requirement of high-precision mapping on a large scale. LSWMWH-2020 can clearly show the significant lakes, river networks, and small ponds in Wuhan with high mapping accuracy.

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Section: Study Area and Datementioning

confidence: 99%

A New Lightweight Convolutional Neural Network for Multi-Scale Land Surface Water Extraction from GaoFen-1D Satellite Images

et al. 2021

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“…(1)Relative water resources carrying capacity: (3)Synthetic carrying capacity :The synthetic carrying capacity is considering the existence of circulation and exchange of resources in the study area [14,15]. It is a regional system with development process and dynamic changes [16,17]. Moreover, water resources are an important resource for human survival and life, and the GDP that can measure the economic development of a region is the gross domestic product.…”

Section: Sichuan Water Resources Bulletin Sichuan Statisticalmentioning

confidence: 99%

Assessment of Relative Water Resources Carrying Capacity and Sustainable Development in Chengdu,China

Li¹,

Tian²

2019

Proceedings of the Sixth Symposium of Risk Analysis and Risk Management in Western China (WRARM 2019)

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Water shortage has become an important factor restricting the sustainable development of cities. This paper adopts the research ideas and methods of relative resource carrying capacity, and uses China's national and Chongqing as reference areas to evaluate the relative water resources carrying capacity, the relative economic resource carrying capacity and the synthetic carrying capacity of Chengdu from 2000 to 2015, and analyzes Chengdu's carrying capacity of water resources relative to population and economy. Using the same method, the resource carrying capacity of each district and county in Chengdu from 2000 to 2015 was evaluated, and the spatial distribution of water resources in various districts and counties was analyzed. The research shows that compared with China's national and Chongqing, the relative water resources carrying capacity of Chengdu has been overloaded for nearly 10 years. To a certain extent, this reflects that Chengdu's economic growth is not compatible with the carrying capacity of water resources, and the existing economic growth model is constantly weakening the capacity of resources. In addition, there are still problems in the imbalance of water resources and economic development in various districts and counties in Chengdu. The water resources carrying capacity in the eastern region has been seriously overloaded, with the central city being in the most severe area, and the water resources in the western region have yet to be further developed and utilized. The research results provide a reference for the grim situation faced by the government in controlling the water resources carrying capacity of Chengdu.Therefore, in order to achieve sustainable development in Chengdu, it is necessary to deal with the coordinated development of population, water resources and social economy.

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“…To date, there are a variety of methods to evaluation UWRCC, such as fuzzy comprehensive evaluation method, ecological footprint method, analytic hierarchy process (Wang et al 2013;Jia & Yu 2014;Wang et al 2017;Chi et al 2019). The above methods are static methods based on the optimal allocation of water resources.…”

Section: Introductionmentioning

confidence: 99%

Comprehensive assessment of urban water resources carrying capacity based on basin unit: a case study of Qingdao, China

Lin

Wang

2021

Water Supply

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With the quick development of social economy, the sharp contradiction between supply and demand of urban water resources is becoming much more obvious. Comprehensive assessment of urban water resources carrying capacity is of great significance to urban sustainable development planning. In this study, the urban water resources carrying capacity of Qingdao based on basin unit over 2010–2030 is predicted using analytic hierarchy process and system dynamics method. The results showed that the total water demand of all the 9 basins have an upward annual trend from 2017 to 2030, among which the domestic water consumption increase obviously. The urban water resource carrying capacity indexes in all basin over 2017–2030 show a downward annual trend under the current social development model. So it is urgent to improve the water resource carrying capacity of each river basin by means of industrial structure optimization and upgrading and active development of new water sources.

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Assessing the Carrying Capacity of Water Resources in Wuhan City, China

Cited by 4 publications

References 15 publications

A New Lightweight Convolutional Neural Network for Multi-Scale Land Surface Water Extraction from GaoFen-1D Satellite Images

A New Lightweight Convolutional Neural Network for Multi-Scale Land Surface Water Extraction from GaoFen-1D Satellite Images

Assessment of Relative Water Resources Carrying Capacity and Sustainable Development in Chengdu,China

Comprehensive assessment of urban water resources carrying capacity based on basin unit: a case study of Qingdao, China

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