Ulansuhai, the largest shallow lake of the Yellow River of China, is an important component of the Hetao region irrigation system. Many concerns have concentrated on its water quality, which affects the local water security and sustainable economic development. In this study, the water pollution index (WPI), an effective water quality evaluation method, was used to compare the pollution levels among pollution indicators and to determine the major pollution indicators. The regime shift index (RSI) approach was employed to identify the water quality trends. Cluster analysis and Daniel trend test methods were employed to analyse the inner-annual and inter-annual spatio-temporal trends of the typical water quality indicators (e.g., total nitrogen (TN), total phosphorus (TP), dissolved oxygen (DO), and chemical oxygen demand (COD)) in Lake Ulansuhai. The results show that the water quality of Ulansuhai improved from 1998 to 2017; spatial variations in the WPI_TN, WPI_TP, and WPI_DO followed the order of inlet > centre and outlet, while spatial variations in the WPI_COD showed the order of outlet > inlet > centre. TN was the critical pollution indicator throughout the year. In 2017, the dry season and wet season were determined using cluster analysis. The WPI_COD was higher than the WPI_TN, WPI_TP, and WPI_DO in the dry season, while the WPI_TN, WPI_TP, and WPI_DO were higher than the WPI_COD in the wet season. WPI was grouped into three clusters: highly polluted regions, moderately polluted regions, and less polluted regions, However, there is a discrepancy between the three polluted regions that were divided into the dry season and the wet season. The WPI_COD was highest among all pollution indicators in 2017. Major sources of pollution that contribute to the deterioration of water quality include inner-annual or inter-annual pollution, agricultural non-point pollution, point source pollution, and internal pollution. This study provides useful information for authorities to effectively manage water quality and control water pollution.

Wetlands are one of the most critical resources in Inner Mongolia Plateau. However, the region has experienced severe wetland loss in the context of global change. To quantify the dynamic change and the related driving forces, we extracted wetland information using multi-temporal Landsat images between 1993 and 2013 using ArcGIS platform and man-machine interactive interpretation. Dynamically changing characteristics for the past 20 years were analyzed, including wetland types and spatial distribution patterns of the wetlands in Inner Mongolia. We also performed correlation analysis and generalized linear models to quantify the contribution of natural and human factors to the changes in natural wetland area. Our results indicated that the total area of wetlands was 42421.2 km² in 1993, and decreased to 38912.4 km² in 2013, a decline ratio of 8.3%. Meanwhile, all types of wetlands showed a trend of transformation into non-wetlands. Anthropogenic factors led to the loss of natural wetlands in Inner Mongolia. In grasslands, mining coal was the dominant driver for natural wetland loss, while in arable lands, agricultural encroachment and irrigation were the primary driving forces. These findings can provide meaningful information for improving sustainable wetlands management strategies according to local conditions in different sub-regions.

The Yellow River Basin of Inner Mongolia has significant ecological advantages, and it is critical to research the landscape pattern of its watershed wetland ecosystem and the changes in its service value in order to protect the environment and develop the region in a high-quality manner. In this paper, we use the landscape index method, the equivalent factor method, and a field survey to investigate changes in wetland landscape patterns and the dynamics of wetland ecosystem service values in the Yellow River Basin of Inner Mongolia from 1990 to 2020, and then examine the impact of landscape pattern evolution on wetland ecosystem service values in the region. The study’s findings indicate that rivers, lakes, and herbaceous marshes are the most common types of wetland landscapes in Inner Mongolia’s Yellow River Basin. The landscape types in the research area are diverse, and landscape fragmentation is increasing. In the Yellow River Basin of Inner Mongolia, the overall value of wetland ecosystem benefits is negatively connected with Patch Density and the Shannon Diversity Index, and positively correlated with the Contagion Index.

Accurate monitoring of grassland vegetation dynamics is essential for ecosystem restoration and the implementation of integrated management policies. A lack of information on vegetation changes in the Wulagai River Basin restricts regional development. Therefore, in this study, we integrated remote sensing, meteorological, and field plant community survey data in order to characterize vegetation and ecosystem changes from 1997 to 2018. The residual trend (RESTREND) method was utilized to detect vegetation changes caused by human factors, as well as to evaluate the impact of the management of pastures. Our results reveal that the normalized difference vegetation index (NDVI) of each examined ecosystem type showed an increasing trend, in which anthropogenic impact was the primary driving force of vegetation change. Our field survey confirmed that the meadow steppe ecosystem increased in species diversity and aboveground biomass; however, the typical steppe and riparian wet meadow ecosystems experienced species diversity and biomass degradation, therefore suggesting that an increase in NDVI may not directly reflect ecosystem improvement. Selecting an optimal indicator or indicator system is necessary in order to formulate reasonable grassland management policies for increasing the sustainability of grassland ecosystems.