A Novel Hybrid Approach for Water Resources Carrying Capacity Assessment by Integrating Fuzzy Comprehensive Evaluation and Analytical Hierarchy Process Methods with the Cloud Model

Forecasting and advancing water carrying capacity in Henan Province in China: Application of 'four determinations with water' in AHP and SD modeling

Water resources carrying capacity (WRCC) is indispensable for sustainable development, acting as a crucial determinant for harmonizing ecological preservation with socio-economic advancement. This research delineates an advanced evaluation index system for WRCC, focusing on Henan Province, China, a region straddling the Yangtze, Huaihe, Yellow, and Haihe river basins. Leveraging the analytic hierarchy process (AHP) with a system dynamics (SD) model, our analysis dissects the nonlinear interplays among demographic expansion, economic activities, land use patterns, water resources, and water environment. We introduce a novel integration of the "Four Determinations with Water" principle with sustainable development tenets, thereby sculpting six exploratory scenarios that chart Henan's potential paths from 2022 to 2035. Through these scenarios, we forecast and scrutinize the evolution of population dynamics, GDP, water supply, and sewage discharge volumes, employing rigorous quantitative analyses for a holistic evaluation. The results show that: WRCC in Henan Province becomes larger gradually, and, in Scenario 6, the WRCC indicator is the largest (0.643 in 2035) and the prediction effect is the best, while in Scenario 1, the WRCC indicator is the smallest (0.472 in 2035) and the prediction effect is the worst. Based on the prediction results, suggestions were made to adjust the industrial structure and strengthen the awareness of water conservation to improve the regional water resources carrying capacity.

Evaluation of water resource carrying capacity in the middle reaches of the Yangtze River Basin using the variable fuzzy-based method

The middle reaches of Yangtze River Basin (MYRB) are rich in water resources, with a large number of rivers and lakes. However, in recent years, water resources from this basin are no longer sufficient to support the region's rapid economic development. This study established a model to evaluate the water resource carrying capacity incorporating water resources, population, and socio-economic data. The characteristic values of water resource carrying capacity were calculated using the variable fuzzy evaluation method in MYRB from 2005 to 2020. Although both population and GDP in the MYRB showed an increasing trend between 2005 and 2020, the water supply capacity increased and then decreased. The weights of each index for evaluating the water resource carrying capacity of perennial botanical gardens were as follows: degree of water resource development (0.311) > total water resources (0.24) > population density (0.156) > GDP per capita (0.097) > water resources per capita (0.077) > water supply per capita (0.064) > water resources per unit area (0.055). Furthermore, the water resource carrying capacity in the MYRB showed an increasing trend from 2005 to 2020. In 2020, the carrying capacity of water resources in Changsha, Jingmen, Xiangtan, Hengyang, Wuhan, Xiaogan, Nanyang, and Xiangyang was attributed an evaluation grade of level 3, which indicates that the development and utilization of water resources in these areas were at their saturation point.

Evaluating the Resources and Environmental Carrying Capacity in Laos Using a Three-Dimensional Tetrahedron Model

(1) Background: The quantitative evaluation and comprehensive measurement of resources and environmental carrying capacity (RECC) are key links in the study of RECC from classification to synthesis. Laos, as the only landlocked country of Mainland Southeast Asia (MSEA), is an important economic corridor (i.e., China-MSEA Economic Corridor) of the Belt and Road Initiative (BRI). (2) Methods: Based on the human settlements index (HSI), resource carrying index (RCI), and socio-economic development index (SDI), here, a three-dimensional tetrahedron model for the comprehensive assessment of RECC with equilibrium significance was constructed, including HSI-based suitability classification, RCI-based restrictive classification, and SDI-based adaptability classification. Taking provinces as the basic unit, we quantitatively assessed and comprehensively evaluated RECC in Laos using a three-dimensional tetrahedron model. (3) Results: The human settlement environment in Laos is mainly characterized by the moderate suitable category (85%), while the high suitability area (merely 5%) supports more than 30% of the total population. Laos had over 90% of its area in good condition in resources and environmental carrying status (surplus or balanced state), translating into more than 95% of the population. The social and economic development level is mainly characterized by low-level development (43%), with nearly 30% of the population living in these low-level areas. The comprehensive bearing state of resources and environment is characterized by surplus, and 85% of the population is distributed in the surplus area, which occupies 63% of the land. (4) Conclusions: It is possible to better explore the adaptation strategies and countermeasures for enhancing RECC in Laos and provide a scientific reference for regional sustainable development. We believe that the three-dimensional tetrahedron method can be applied to quantitatively evaluate and comprehensively measure RECC at larger scale, e.g., the BRI regions.

Sustainability Assessment of Water Resources Use in 31 Provinces in China: A Combination Method of Entropy Weight and Cloud Model

As a fundamental and strategic resource, water is a crucial controlling element of ecosystem and natural environment and it plays an irreplaceable role in maintaining and promoting the sustainable development of the economy and society. To achieve the sustainable development of society, the economy and ecology, it is necessary to assess and improve the sustainability of water resources use. Based on the Human-Resource-Nature approach, this paper constructed an indicator system for the sustainability assessment of water resources use (ISSAWRU) in China from three perspectives: water resources condition, socio-economy and ecological environment. A five-level hierarchy of assessment indicators was established. Based on the entropy weight method and the cloud model which took both fuzziness and randomness into account, this paper established an entropy-cloud-based assessment model for the sustainability assessment of water resources use in 31 provinces in China in 2019. The assessment results were compared with results obtained by the TOPSIS method to test their reliability. Finally, a comprehensive and in-depth analysis of the sustainability of water resources use in China was conducted. According to the results, water resources per capita had a weighting of 0.306 and the greatest impact on the sustainable use of water resources. In addition, water structure, agricultural water use efficiency, forest coverage, and so on, had a significant impact on the sustainable use of water resources in China. The overall level of sustainability of water resources use in 31 provinces in China was not high-42% of the regions have unsustainable water resources use and there was a clear spatial distribution trend. The sustainability level of water resources use was higher in the southeast and economically developed regions. Therefore, each region should develop measures to guarantee water security based on the local conditions. This research helps policy makers to figure out the contributing factors associated with sustainability of water resources use and to set relevant rules and regulations to promote the use of water resources in a sustainable way.

Research on User Experience of Sports Smart Bracelet Based on Fuzzy Comprehensive Appraisal and SSA-BP Neural Network

Due to the marked increase in the prevalence of overweight and obesity worldwide and an environment leading to a series of chronic diseases, physical exercise is an important way to prevent chronic diseases. Additionally, a good exercise smart bracelet can bring convenience to physical exercise. Quick and accurate evaluation of smart sports bracelets has become a hot topic and draws attention from both academic researchers and public society. In the literature, the analytic hierarchy process (AHP) and entropy weight method (EWM) were used to obtain the weights from both subjective and objective perspectives, which were integrated by the comprehensive weighting method, and furthermore the performance of sports smart bracelet was evaluated through fuzzy comprehensive evaluation. Also, to avoid complex weight calculations caused by the comprehensive weighting method, machine learning methods are used to model the structure and contribute to the comprehensive evaluation process. However, few studies have investigated all previous elements in the comprehensive evaluation process. In this study, we consider all previous parts when evaluating smart sports bracelets. In particular, we use the sparrow search algorithm (SSA) to optimize the backpropagation (BP) neural network for constructing the comprehensive score prediction model of the sports smart bracelet. Results show that the sparrow search algorithm-optimized backpropagation (SSA-BP) neural network model has good predictive ability and can quickly obtain evaluation results on the premise of effectively ensuring the accuracy of the evaluation results.

Uncertain Analysis of Fuzzy Evaluation Model for Water Resources Carrying Capacity: A Case Study in Zanhuang County, North China Plain

The scientific and accurate evaluation of water resources carrying capacity has good social, environmental and resource benefits. Reasonable selection of evaluation parameters is the key step to realize efficient and sustainable development of water resources. Taking Zanhuang County in the North China Plain as the research area, this study selected fuzzy comprehensive evaluation models with different weights in the established evaluation index framework to explore the sources of uncertainty affecting the evaluation results of water resources carrying capacity. By using the sensitivity analysis method of index weight, the index with the biggest influence factor on the evaluation result is selected to reduce the uncertainty problems such as index redundancy and small correlation degree. The results show that the correlation and reliable of comprehensive evaluation value obtained by different weight methods is different. The evaluation result obtained by using the analytic hierarchy process is more relevant than the entropy weight method, and it is more consistent with the actual load-bearing situation. The study of sensitivity index shows that water area index is the biggest factor affecting the change of evaluation results, and water resources subsystem and socio-economic subsystem play a dominant role in the whole evaluation framework. The results show that strengthening the data quality control of index assignment and weight method is helpful to reduce the error of water resources carrying capacity evaluation. It can also provide scientific basis for the improvement of fuzzy evaluation model.