Temporal and spatial variation characteristics of surface water area in the Yellow River Basin from 1986 to 2021.

The Yellow River Basin is short of water resources. The dynamic monitoring of surface water area is helpful to clarify the distribution and change trend of water resources in this area. It is of great scientific significance to deeply understand the impacts of climate change and human activities on water resources and ensure the ecological security of the basin. Based on the Google Earth Engine (GEE) cloud platform, we analyzed the spatial variations of surface water area in the Yellow River Basin from 1986 to 2021 by using the mixed index algorithm, and revealed the driving factors of surface water area change in the Yellow River Basin. The results showed that the overall recognition accuracy of the water extraction algorithm based on mixing index was 97.5%. Compared with available water data products, the proposed algorithm can guarantee the integrity of the whole water area to a certain extent. The surface water area in the upper, middle, and lower reaches of the Yellow River Basin was 71.7%, 18.4%, and 9.9% of the total surface water area, respectively. From 1986 to 2021, the surface water area of the basin showed an overall upward trend, with a total increase of 3163.6 km2. The surface water area of the upper, middle, and downstream regions increased by 72.0%, 22.4%, and 5.6%, respectively. The increase of precipitation was the main reason for the increase of water area, with a contribution of 55%. Vegetation restoration and construction of water conservancy projects had increased the water area of the basin. The intensification of human water extraction activity reduced the water area of the basin.

[Identification of Nitrate Source of Surface Water in a Typical Peri-urban Watershed in the Tableland of the Loess Plateau, China].

With the rapid development of industry and agriculture, nitrate pollution in surface water has become one of the serious environmental problems in the Loess Plateau region. In this study, Yanwachuan watershed, a typical suburban watershed in the gully region of a loess plateau, was selected as the research area. Using hydrochemical data and nitrogen and oxygen bistable isotopes, combined with the SIAR model, the contribution rates of different pollution sources of nitrate in surface water in the dry season and wet season were quantitatively identified, and the main reasons for seasonal differences in different pollution sources were clarified. The results showed that inorganic nitrogen mainly existed in the form of NO3--N and NO2--N, and the average concentration of NO3--N and NO2--N in the wet season was higher than that in the dry season, whereas NH4+-N showed the opposite characteristics. Nitrification was the main process of nitrate transformation in the surface water of the basin. In the wet season, the main sources of nitrate were manure and sewage, whereas in the dry season, manure, sewage, and soil N leaching were the dominant sources, followed by ammonium fertilizer. The contribution proportion of different pollution sources to nitrate in surface water of the watershed showed significant seasonal differences. The sewage had the highest contribution, accounting for 31.40% and 65.66% in the dry season and rainy season, respectively, and the contribution of sewage to NO3- in the wet season was much higher than that in the dry season. The increase in residential water consumption in summer led to a large amount of sewage discharge into the watershed.