Water resources are scarce in arid or semiarid areas,which not only limits economic development,but also threatens the survival of mankind.The local communities around the Hangjinqi gasfield depend on groundwater sour...Water resources are scarce in arid or semiarid areas,which not only limits economic development,but also threatens the survival of mankind.The local communities around the Hangjinqi gasfield depend on groundwater sources for water supply.A clear understanding of the groundwater hydrogeochemical characteristics and the groundwater quality and its seasonal cycle is invaluable and indispensable for groundwater protection and management.In this study,self-organizing maps were used in combination with the quantization and topographic errors and K-means clustering method to investigate groundwater chemistry datasets.The Piper and Gibbs diagrams and saturation index were systematically applied to investigate the hydrogeochemical characteristics of groundwater from both rainy and dry seasons.Further,the entropy-weighted theory was used to characterize groundwater quality and assess its seasonal variability and suitability for drinking purposes.Our hydrochemical groundwater dataset,consisting of 10 parameters measured during both dry and rainy seasons,was classified into 6 clusters,and the Piper diagram revealed three hydrochemical facies:Cl-Na type(clusters 1,2 and 3),mixed type(clusters 4 and 5),and HCO3-Ca type(cluster 6).The Gibbs diagram and saturation index suggested thatweathering of rock-forming mineralswere the primary process controlling groundwater chemical composition and validated the credibility and practicality of the clustering results.Two-thirds of 45 groundwater samples were categorized as excellent-or good-quality and were suitable as drinking water.Cluster changes within the same and different clusters from the dry season to the rainy season were detected in approximately 78%of the collected samples.The main factors affecting the groundwater quality were hydrogeochemical characteristics,and dry season groundwater quality was better than rainy season groundwater quality.Based on this work,such results can be used to investigate the seasonal variation of hydrogeochemical characteristics and assess water quality accurately in the others similar area.展开更多
Abstract: Enhancing the efficiency of public services is essential to residents in mountainous areas. It is also important to promote sus- tainable development of these regions. Analysing residents' satisfaction wit...Abstract: Enhancing the efficiency of public services is essential to residents in mountainous areas. It is also important to promote sus- tainable development of these regions. Analysing residents' satisfaction with public services in mountainous areas can help in evaluating outcomes of fiscal investment and identifying potential coping approaches for improving public service efficiencies. The residents' satisfaction with public services and the factors that influence such satisfaction were examined in this study. A study of 12 towns located in the southwestern Sichuan Province was performed using an entropy-weighted analytic hierarchy process (EWAHP), the technique for order preference by similarity to ideal solution (TOPSIS) and Tobit regression methods. The results indicate that: 1) the spatial distribu- tion of satisfaction with public services is non-uniform, and the spatial distribution structure varies for different types of public services. 2) Residents' satisfaction with public services is influenced by both objective and subjective factors. Population density, economic dis- tance, social and cultural divisions and elevation are the major objective factors, whereas bounded rationality, the hierarchy of needs and service expectations are the main subjective factors. The most effective strategies for enhancing residents' satisfaction with public ser- vices are likely to be clustering the population, choosing supply centres with different public services, regulating the cultural division in ethnic minority towns, selecting supply priorities in accordance with residents' needs, implementing targeted intervention policies and establishing 'bottom-up' and 'top-down' integrated decision-making mechanisms. Keywords: mountainous areas; public services; residents' satisfaction; entropy-weighted analytic hierarchy process (EWAHP); technique for order preference by similarity to ideal solution (TOPSIS); Tobit regression; southwestern Sichuan Province展开更多
This paper presents an evaluation method for the entropy-weighting of wind power clusters that comprehensively evaluates the allocation problems of wind power clusters by considering the correlation between indicators...This paper presents an evaluation method for the entropy-weighting of wind power clusters that comprehensively evaluates the allocation problems of wind power clusters by considering the correlation between indicators and the dynamic performance of weight changes.A dynamic layered sorting allocation method is also proposed.The proposed evaluation method considers the power-limiting degree of the last cycle,the adjustment margin,and volatility.It uses the theory of weight variation to update the entropy weight coefficients of each indicator in real time,and then performs a fuzzy evaluation based on the membership function to obtain intuitive comprehensive evaluation results.A case study of a large-scale wind power base in Northwest China was conducted.The proposed evaluation method is compared with fixed-weight entropy and principal component analysis methods.The results show that the three scoring trends are the same,and that the proposed evaluation method is closer to the average level of the latter two,demonstrating higher accuracy.The proposed allocation method can reduce the number of adjustments made to wind farms,which is significant for the allocation and evaluation of wind power clusters.展开更多
基金the National Natural Science Foundation of China(Nos.41972259 and 41572227)the National Key Research and Development Program of China(No.2018YFC0406404).
文摘Water resources are scarce in arid or semiarid areas,which not only limits economic development,but also threatens the survival of mankind.The local communities around the Hangjinqi gasfield depend on groundwater sources for water supply.A clear understanding of the groundwater hydrogeochemical characteristics and the groundwater quality and its seasonal cycle is invaluable and indispensable for groundwater protection and management.In this study,self-organizing maps were used in combination with the quantization and topographic errors and K-means clustering method to investigate groundwater chemistry datasets.The Piper and Gibbs diagrams and saturation index were systematically applied to investigate the hydrogeochemical characteristics of groundwater from both rainy and dry seasons.Further,the entropy-weighted theory was used to characterize groundwater quality and assess its seasonal variability and suitability for drinking purposes.Our hydrochemical groundwater dataset,consisting of 10 parameters measured during both dry and rainy seasons,was classified into 6 clusters,and the Piper diagram revealed three hydrochemical facies:Cl-Na type(clusters 1,2 and 3),mixed type(clusters 4 and 5),and HCO3-Ca type(cluster 6).The Gibbs diagram and saturation index suggested thatweathering of rock-forming mineralswere the primary process controlling groundwater chemical composition and validated the credibility and practicality of the clustering results.Two-thirds of 45 groundwater samples were categorized as excellent-or good-quality and were suitable as drinking water.Cluster changes within the same and different clusters from the dry season to the rainy season were detected in approximately 78%of the collected samples.The main factors affecting the groundwater quality were hydrogeochemical characteristics,and dry season groundwater quality was better than rainy season groundwater quality.Based on this work,such results can be used to investigate the seasonal variation of hydrogeochemical characteristics and assess water quality accurately in the others similar area.
基金Under the auspices of the National Natural Science Foundation of China(No.41601141,41471469)Humanities and Social Sciences Youth Foundation of Ministry of Education of the People’s Republic of China(No.14YJCZH130)+1 种基金Soft Science Research Projects of Science and Technology Office of Sichuan Province(No.2015ZR0115)Research Foundation of Chengdu University of Information Technology(No.KYTZ201628,J201617)
文摘Abstract: Enhancing the efficiency of public services is essential to residents in mountainous areas. It is also important to promote sus- tainable development of these regions. Analysing residents' satisfaction with public services in mountainous areas can help in evaluating outcomes of fiscal investment and identifying potential coping approaches for improving public service efficiencies. The residents' satisfaction with public services and the factors that influence such satisfaction were examined in this study. A study of 12 towns located in the southwestern Sichuan Province was performed using an entropy-weighted analytic hierarchy process (EWAHP), the technique for order preference by similarity to ideal solution (TOPSIS) and Tobit regression methods. The results indicate that: 1) the spatial distribu- tion of satisfaction with public services is non-uniform, and the spatial distribution structure varies for different types of public services. 2) Residents' satisfaction with public services is influenced by both objective and subjective factors. Population density, economic dis- tance, social and cultural divisions and elevation are the major objective factors, whereas bounded rationality, the hierarchy of needs and service expectations are the main subjective factors. The most effective strategies for enhancing residents' satisfaction with public ser- vices are likely to be clustering the population, choosing supply centres with different public services, regulating the cultural division in ethnic minority towns, selecting supply priorities in accordance with residents' needs, implementing targeted intervention policies and establishing 'bottom-up' and 'top-down' integrated decision-making mechanisms. Keywords: mountainous areas; public services; residents' satisfaction; entropy-weighted analytic hierarchy process (EWAHP); technique for order preference by similarity to ideal solution (TOPSIS); Tobit regression; southwestern Sichuan Province
基金supported by the National Natural Science Foundation of China(Grant No.52076038,U22B20112,No.52106238)the Fundamental Research Funds for Central Universities(No.423162,B230201051).
文摘This paper presents an evaluation method for the entropy-weighting of wind power clusters that comprehensively evaluates the allocation problems of wind power clusters by considering the correlation between indicators and the dynamic performance of weight changes.A dynamic layered sorting allocation method is also proposed.The proposed evaluation method considers the power-limiting degree of the last cycle,the adjustment margin,and volatility.It uses the theory of weight variation to update the entropy weight coefficients of each indicator in real time,and then performs a fuzzy evaluation based on the membership function to obtain intuitive comprehensive evaluation results.A case study of a large-scale wind power base in Northwest China was conducted.The proposed evaluation method is compared with fixed-weight entropy and principal component analysis methods.The results show that the three scoring trends are the same,and that the proposed evaluation method is closer to the average level of the latter two,demonstrating higher accuracy.The proposed allocation method can reduce the number of adjustments made to wind farms,which is significant for the allocation and evaluation of wind power clusters.