Cognition of modernization degree of irrigation district and its influencing factors analysis
ZENG Zhongyi1, SHAO Guangcheng1*, DING Mingming2, YAO Junqi3
1. College of Agricultural Engineering, Hohai University, Nanjing, Jiangsu 210098, China; 2. Water Conservancy Bureau of Nanjing City, Nanjing, Jiangsu 210036, China; 3. Development Center for Science and Technology of Rural Water Resources of Jiangsu, Nanjing, Jiangsu 210029, China
Abstract：To determine the content and key points of irrigation modernization,taking the sample data of 35 irrigation districts in Jiangsu Province as examples, the cognition of modernization degree of irrigation district and its influencing factors were studied by structural equation model. The data analysis shows that the standard factor loading coefficient is about 0.75, the Kaiser-Meyer-Olkin value is 0.973 and the Bartlett′s spherical test statistic is 1 682, indicating that the sample data are highly effective and relevant. The results indicate that irrigation and drainage system, water resources measurement and informatization, management system, service assurance, ecological environment, living environment, disaster prevention and mitigation, water resources security, economic efficiency and water efficiency all affect the cognitive degree of irrigation district modernization in various degrees. Among them, irrigation and drainage system has the greatest impact on the cognitive degree of irrigation district modernization, while service guarantee has the least impact on it. The modernization of irrigation district should be comprehensive and integral. It is necessary to make an overall plan for the comprehensive development of irrigation district infrastructure system, management and service system, ecological health system, security system, and efficiency and benefit system.
曾忠义,邵光成*,丁鸣鸣,姚俊琪. 灌区现代化程度认知及其影响因素分析[J]. 排灌机械工程学报, 2020, 38(4): 409-414.
ZENG Zhongyi,SHAO Guangcheng*,DING Mingming,YAO Junqi. Cognition of modernization degree of irrigation district and its influencing factors analysis. Journal of Drainage and Irrigation Machinery Engin, 2020, 38(4): 409-414.
