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.

China’s economy in recent decades has developed at a very rapid speed, as evidenced by its GDP jumping to second place in the world. Although utilization of domestic water resources has helped spur economic development, sewage discharge as an undesirable output has unfortunately caused many negative effects on human health, causing concern from all walks of life. Therefore, governments in China at all levels are committed to urban sewage treatment policies in order to reduce the negative impact of water pollution on society. While most existing studies have targeted the macro-level modes of economic development and environmental pollution, their selection of research objects is too narrow by failing to adequately consider China's water pollution and the consequential national health crisis. This study takes cities in 30 provinces of China as the research objects and applies various influencing factors of urban wastewater treatment and health (as two stages) to the modified two-stage dynamic Slacks-Based Measures (SBM) Data Envelopment Analysis (DEA) model. The results reveal that the overall efficiency of each province is increasing and that the efficiency of the wastewater treatment stage is greater, thus contributing to overall efficiency. Conversely, the health stage’s efficiency is far lower than the wastewater treatment stage’s efficiency, which has a notably adverse effect on overall efficiency. In addition, most input-output variables need much improvement. Based on the findings herein, we offer specific suggestions to each province for improving sewage treatment capacity, the level of medical care, and the quality of national health.