Changes in irrigation water-use efficiency are related closely to agricultural development. Clarifying the driving factors of irrigation water-use efficiency change at different agricultural development stages is beneficial for buffering the contradiction between the protection of water resources and massive agricultural water consumption. It also has theoretical and application value when it comes to elucidating the driving characteristics of spatial changes in irrigation water-use efficiency observed among the different provinces of China. This paper analyzes driving factors of irrigation water-use change based on a study of literature and a field survey. It selects 21 indices from five aspects of climatic change, resource endowment, economic situation, technological level, and management mode as the system of driving factors for irrigation water-use change. This article then uses statistical data on economic and social development in the 31 provinces of China in 2009, and applies the principal component analysis (PCA) method to extract the main driving factors affecting irrigation water-use efficiency change. After calculation of factor scores, clustering analysis is conducted on the 31 provinces to explore regional differences among the driving factors of irrigation water-use efficiency change. The results show that these can be attributed to the factors of agricultural economic development, water-saving irrigation technology, water resource endowment, and dissipation. The 31 provinces can be divided into five types: agricultural economy strong driving type; agricultural economy dominant type; industrial economy dominant type; agriculture strong development type; and coordinated driving type. In highly agricultural provinces, mature irrigation district management and water-saving measures influence the efficiency of irrigation water-use, making these strong positive driving factors. In highly industrial provinces, changes in irrigation water-use efficiency are mainly driven by economic development and structural adjustment, making these weak driving factors.

This paper introduces an integrated approach to find out the major factors influencing efficiency of irrigation water use in China. It combines multiple stepwise regression (MSR) and principal component analysis (PCA) to obtain more realistic results. In real world case studies, classical linear regression model often involves too many explanatory variables and the linear correlation issue among variables cannot be eliminated. Linearly correlated variables will cause the invalidity of the factor analysis results. To overcome this issue and reduce the number of the variables, PCA technique has been used combining with MSR. As such, the irrigation water use status in China was analyzed to find out the five major factors that have significant impacts on irrigation water use efficiency. To illustrate the performance of the proposed approach, the calculation based on real data was conducted and the results were shown in this paper.

Jiangsu is a major province located in the east of China, consuming a large amount of water resources. It is considered that improving the comprehensive water use efficiency has an important significance to achieve sustainable development of the economy in Jiangsu. Through extensive literature research and investigation of Jiangsu Province, this paper establishes comprehensive water use efficiency index system using water consumption per ten thousand dollar gross domestic product (WC/$10⁴ GDP) as the research target. In the index system, resource factors such as surface water resources (SW), groundwater resources (GW), precipitation (PT), water resources per capita (PW), water consumption per capita (PC) and irrigation area per capita (PI) cannot be artificially altered. Furthermore, the variation amplitude of resource factors is very small. It shows that the linear regression model is not suitable to analyze the resource factors by changing the independent variables. In view of this situation, this paper introduces impulse response function on the basis of vector autoregressive model (VAR) to investigate the intrinsic link between resource factors and WC/$10⁴ GDP in Jiangsu Province. The results show that resource factors have a great impact on WC/$10⁴ GDP in Jiangsu, and the per capita water resources (PW) has the most significant impact.