The regional policy in China is shifting from solely gross domestic product (GDP) orientation to development that is more balanced between economic growth and ecological protection, as well as achieving equality among regions. Using land use maps and the adjusted value coefficients to assess ecosystem service values (ESV) for the 1980s, 1995, 2000, and 2010, we estimated the ESV in Shaanxi Province for different years, and characterized the spatial and temporal distribution of ESV and GDP. The results demonstrated that the total value of ecosystem services in Shaanxi Province increased from 208.95 billion Yuan in the 1980s to 309.76 billion Yuan in 2010. Variation Coefficient (Cv) and Theil index (T) were used to reflect the disparities of GDP or ESV within the study area. The values of Cv in descending order are GDP, ESV per capita, ESV, and GDP per capita. The Theil indexes of GDP were much greater than the ones of ESV. Variations of Cv and T showed that disparity in GDP kept increasing from the 1980s to 2000, then decreased; while no significant change in regional disparity of ESV were detected in parallel. The cities with higher GDP usually contributed little to ESV, and vice versa. The variation in GDP and ESV, in terms of the prefectural totals and per capita values, increased from the 1980s to 2010. This study provides an accessible way for local decision makers to evaluate the regional balance between economic growth and ecosystem services.

Organic matter plays an important role in soil moisture variation. In order to know the effect of organic matter on soil moisture dynamics, this study compared the infiltration and evaporation of soils with different organic matter content. The results showed that increasing the organic matter content in a certain degree can suppress evaporation and infiltration of soil moisture, and hence improving water use efficiency. When the organic matter content reaches3.2%, effect of suppressing evaporation is most obvious.

Anthropogenic N inputs have become progressively more problematic and have profoundly affected the water quality in megacities throughout China. Thus, to design and implement appropriate megalopolis watershed management, it is important to understand the relationship between N inputs and exports and to identify the N pollution sources. To that end, in this work, the net anthropogenic N inputs (NANI) in Chengdu City were estimated based on statistical data collected between 1970 and 2019. N input fluxes and pollution sources were estimated through sample collection and field measurements that were performed between 2017 and 2019, while nitrate (NO3−) was identified using stable isotope and Bayesian model (SIAR) analysis. The NANI was found to be affected primarily by livestock and poultry consumption of N rich feed. Moreover, the N export fluxes and runoff showed a high degree of correlation. Notably, NO3− fluxes exhibited a significant increase over the course of the study period, such that, by 2019, the total N fluxes (18,883.85 N kg/km2) exceeded the NANI (17,093.87 N kg/km2). The results indicate that although livestock and poultry farming were the original primary sources of NANI, their contributions declined on an annual basis. Moreover, with the emphasis placed on point source management in Chengdu City, domestic sewage discharge has been significantly reduced. Therefore, N retention in groundwater is thought to be the factor driving the N flux increase. These findings are pivotal to solving the N pollution problem in megacities like Chengdu (China).

The title of this chapter comes from the Chinese idiom "a peep at a leopard through a tubesee a spot or two" (管中窥豹，可见一斑), which means looking at an issue from a single perspective and conjuring up a bigger picture. The chapter considers the accessibility of Chinese social media platforms through a pilot research project.

The current standards used for nitrogen pollution evaluation are lacking, and scientific classification methods are needed for nitrogen pollution to improve water quality management capabilities. This study addresses the important issue of assessing surface water nitrogen pollution by utilizing two advanced multivariate statistical techniques: self-organizing maps (SOMs) obtained using the K-means algorithm and the Hasse diagram technique (HDT). The research targets of this study are the rivers of the megacity Chengdu, China. Samples were collected on a monthly basis in 2017–2020 from different sites along the rivers, and their nitrogen pollution parameters were determined. The grouping of nitrogen pollution parameters and the clustering of sampling events using SOMs facilitate the preprocessing required for the HDT, wherein clusters are ordered according to the pre-clustered water sampling events. The results indicate that nitrogen pollution in the Chengdu River Basin, which is prominent and mainly driven by nitrate nitrogen, can be categorized into five levels. The nitrogen pollution in Tuo River is serious. Although the degree of ammonia nitrogen pollution in Jin River is higher, the pollution range is smaller. Furthermore, these results were evaluated by the SOMs and HDT to be clear and reliable. Overall, these findings can provide a basis for local environmental legislation.