Wetland cities were proposed by the International Wetland Convention Organization for the protection of urban wetlands. Few studies have performed land cover classifications for internationally recognized wetland cities or explored what contribution the classification results can make to the establishment of additional wetland cities to date. Based on Sentinel-1 and 2 data, this study used a 10-fold random forest method to classify the land cover of the first six wetland cities recognized in China. A land cover dataset, which had a resolution of 10 m and included four wetland types, was obtained and the wetland area and protected wetland areas of the six cities were calculated. The results showed that (1) the classification accuracy of six cities was good, the overall accuracy was above 90%, and the Kappa coefficient was above 0.88. (2) Cropland or forested areas were the most common non-wetland land coverage type in wetland cities and accounted for more than 20% or 40% of the land coverages, while water was the most common wetland type and accounted for more than 2% of the land coverages. From 2015 to 2020, the built area in most cities increased, while cropland and forest decreased significantly. (3) The wetland rate was 6.68–37.56% and the wetland protection rate was 49.48–73.74% in the six wetland cities. From 2015 to 2020, the wetland rate of the six cities were relatively stable, and the wetland protection rate of inland cities (Yinchuan, Changde, Harbin and Changshu) increased significantly, while those of coastal cities (Haikou and Dongying) decreased, which might be related to the change in coastline. Therefore, we found that the wetlands in these cities were well protected. Land cover classification for wetland cities can provide a reference for using remote sensing techniques used to monitor internationally wetland cities while also supporting the creation of additional wetland cities.

Water pollution poses threats to urban environments and subsequently impacts the ecological health and sustainable development of urban areas. Identifying the spatiotemporal variation in non-point sources (NPS) pollution is a prerequisite for improving water quality. This paper aimed to assess the NPS pollution load and then recognized the spatiotemporal characteristics of the pollution sources in a typical urbanized area. A combination model based on land use type was used to simulate the NPS pollution load. The results showed the following: (1) ponds and farmlands had higher pollution production intensities than other land use types, but the intensity and magnitude of pollution emissions were generally greater in urban areas; (2) monthly and annual total nitrogen (TN) and total phosphorus (TP) emissions had the same pattern as rainfall, and TN and TP emissions accounted for 56.2% and 58.0%, respectively, of the total in summer; (3) TN pollution was more serious than TP pollution in the study area, especially in farmlands; (4) urban runoff (UR) and livestock and poultry breeding (LPB) were the main sources of NPS, TN and TP emissions in the study area. If these NPS pollutants cannot be removed from this area, a large amount of freshwater is needed to dilute the current rivers to meet the requirement of the fourth category of China national environmental quality standards for surface water. This problem is serious in the control of polluted rivers in many cities throughout China.

Hebei Province of China is facing a severe water resource shortage, making it urgent to formulate economical and effective water conservation policies. However, few studies have focused on analyzing the resource and economic impacts of a water policy. This study developed an improved computable general equilibrium (CGE) model with an extended water resources module as a policy analysis tool. The extended water resources module includes different water resources as commodities and water sectors, and introduces a substitution mechanism among the water resources. Policy scenarios containing different policy types and policy objects were established, including water price, technology (tech) improvement, structure adjustment, and water reuse policies in primary, secondary, and tertiary sectors. The impact on the water resource and economy of the scenarios was analyzed using the CGE model. The recommended policies include: an agricultural technology improvement policy that decreases groundwater usage by 240 hm³; an industrial technology improvement policy under which water usage per 10,000 CNY of industrial added value decreases by 13%; an industrial water reuse policy that increases unconventional water usage by 20%; and a structure adjustment policy to increase the proportion of the tertiary sector. The study provides an analysis tool for simulating and evaluating a water resource policy.