As one of the largest agricultural countries in the world, China has always paid close attention to the sustainable development of agricultural production efficiency. However, with global climate change, extreme weather has become an exogenous factor that cannot be ignored, as it affects agricultural production. Most of the existing studies only consider the domestic natural resources and economic factors, without fully considering the external climate factors. This paper uses the super undesirable dynamic Slacks-Based Measures (SBM) under an exogenous variable model to simulate the external environmental factors by adding extreme weather days. The Dagum Gini coefficient and kernel density estimation are used to explore the regional differences in agricultural production in China. The results show that the agricultural production efficiency is higher in the eastern region, and the difference in agricultural production efficiency among the provinces in the middle and western regions is large, showing a trend of polarization. The difference in the Gini coefficient between the middle and western regions is more significant. The main contribution factor of the Dagum Gini coefficient is the inter-regional difference. The regional concentration degree of agriculture in China is decreasing, the regional distribution of agricultural water resources is more balanced, and the national regional difference gradually decreases. Finally, some suggestions are put forward, such as extreme weather control, agricultural water supply, and water-saving measures.

As the modern economy develops rapidly, environmental pollution and human health have also been threatened. In recent years, relevant research has focused on subjects such as energy and economic, environmental pollution and health issues. Yet this has not considered the use of water resources and the impact of wastewater pollutant emissions on the economy and health. This article has combined the following factors like water consumption with wastewater discharge, pollutant concentration in sewage and local medical care expenditure and put them into the model of water resources, energy and health measurement, and a two-stage dynamic data envelopment analysis (DEA) model considering undesirable outputs is applied to 30 provinces (including autonomous regions and municipalities) to calculate the total efficiency, production efficiency and health efficiency in 2014–2017.The results show that the total efficiency values of most provinces are between 0.2 and 0.4, providing large room for improvement. Production efficiency and health efficiency have increased in recent years, but the health efficiency values of most provinces are still so low that they have dragged back the overall efficiency. The key impact indicators of different provinces are different, and each province should formulate different policies according to its own specific conditions so as to purposefully to deepen the energy, economic and medical reforms in each province, and also to promote sustainable economic development while improving health efficiency.

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