Land use/cover change (LUCC) affects canopy interception, soil infiltration, land-surface evapotranspiration (ET), and other hydrological parameters during rainfall, which in turn affects the hydrological regimes and runoff mechanisms of river basins. Physically based distributed (or semi-distributed) models play an important role in interpreting and predicting the effects of LUCC on the hydrological processes of river basins. However, conventional distributed (or semi-distributed) models, such as the soil and water assessment tool (SWAT), generally assume that no LUCC takes place during the simulation period to simplify the computation process. When applying the SWAT, the subject river basin is subdivided into multiple hydrologic response units (HRUs) based on the land use/cover type, soil type, and surface slope. The land use/cover type is assumed to remain constant throughout the simulation period, which limits the ability to interpret and predict the effects of LUCC on hydrological processes in the subject river basin. To overcome this limitation, a modified SWAT (LU-SWAT) was developed that incorporates annual land use/cover data to simulate LUCC effects on hydrological processes under different climatic conditions. To validate this approach, this modified model and two other models (one model based on the 2000 land use map, called SWAT 1; one model based on the 2009 land use map, called SWAT 2) were applied to the middle reaches of the Heihe River in northwest China; this region is most affected by human activity. Study results indicated that from 1990 to 2009, farmland, forest, and urban areas all showed increasing trends, while grassland and bare land areas showed decreasing trends. Primary land use changes in the study area were from grassland to farmland and from bare land to forest. During this same period, surface runoff, groundwater runoff, and total water yield showed decreasing trends, while lateral flow and ET volume showed increasing trends under dry, wet, and normal conditions. Changes in the various hydrological parameters were most evident under dry and normal climatic conditions. Based on the existing research of the middle reaches of the Heihe River, and a comparison of the other two models from this study, the modified LU-SWAT developed in this study outperformed the conventional SWAT when predicting the effects of LUCC on the hydrological processes of river basins.

Wetland health assessment provides important basis for wetland restoration and management. However, it is quite tricky to select proper indicators from multiple assessment indicators that can truly reflect the health state of urban wetlands. In an attempt to address these problems, a pressure-state-response (PSR) and back propagation artificial neural network (BP) conjoined model was established for health assessment of several plateau urban wetlands in Xining City, China. The model was driven and verified through field monitoring and social questionnaire data for 4 consecutive years from 2016 to 2019. Results indicate that: (1) Eight health evaluation indexes, including population density, eutrophication level, increasing humidity, carbon dioxide absorption, air purifying, recreation, wetland management level and investment in ecological construction and protection were selected from 45 input indexes. (2) The health index of Huangshui National Wetland Park has been increasing year by year, with an average of comprehensive health score of 0.746, 0.790, 0.884, and 0.877, respectively. The indicators that contributed the most to the restoration effect were leisure and entertainment service value (2016), carbon dioxide absorption service value (2017), eutrophication (2018), and wetland management level (2019), respecially. (3) Compared with the single PSR method, the advantages of this method include; There are fewer evaluation indicators, more accurate results (excluding the interference of some highly variable indicators) and more sensitive to environmental changes. The current study proposed a novel method that may provide additional accurate and refined indicators for urban wetland health assessment.

The Huangshui National Wetland Park (HNWP) is a unique national wetland park in a city on the Qinghai-Tibetan Plateau, containing three zones: Haihu, Beichuan, and Ninghu. In this study, a total of 54 soil samples (18 sampling points with depths of 0–10 cm, 10–20 cm, and 20–30 cm) were collected in these three zones, and the contents of heavy metals (Cr, Cd, Cu, Hg, Ni, Pb, Zn, and As) of each sample were determined. The ecological risk of eight kinds of heavy metals was evaluated by using the geo–accumulation index ($I_{geo}$), and the ecological risk–controlling effect of the Xining urban wetlands on heavy metals was explored by comparative analysis, and the possible sources of heavy metals in the soil were analyzed via correlation analysis and principal component analysis (PCA). The results revealed that the total heavy metal concentration order was Haihu > Beichuan > Ninghu zone. As and Cu presented vertical accumulation characteristics in the surface and lower horizon, respectively. Cr, Cd, Hg, Ni, Pb, and Zn accumulated downwards along the depth. On the spatial scale, the enrichments of Cd and Hg brought non-negligible ecological risks in plateau urban wetlands. The results of PCA indicated that soil heavy metals mainly came from compound sources of domestic and atmospheric influences, traffic pollution sources, and industrial pollution sources. The study has revealed that human activities have inevitable negative impacts on wetland ecosystems, while the HNWP provides a significant weakening effect on heavy metal pollution.

Reservoirs are an integral part of the global carbon cycle and generally considered to be methane (CH₄) emission hot spots. Although remarkable research achievements have been made concerning CH₄ ebullition from inland waters, such as rivers, lakes, and ponds, few have been devoted to CH₄ ebullition from plateau reservoirs. The present study focused on CH₄ ebullition from the Dahejia Reservoir located in the upper reaches of the Yellow River. We analyzed the spatial and temporal characteristics of CH₄ ebullition flux across the water-atmosphere interface between July and August 2021. We also evaluated the influence of microbes on CH₄ ebullition flux. The results showed that (1) CH₄ ebullition was the dominant mode of CH₄ emissions in the study site, which contributed to 78.85 ± 20% of total CH₄ flux. (2) The mean CH₄ ebullition flux in the nighttime (0.34 ± 0.21 mg m⁻² h⁻¹) was significantly higher than that in the daytime (0.19 ± 0.21 mg m⁻² h⁻¹). The mean CH₄ ebullition flux first decreased and then increased from the upstream (0.52 ± 0.57 mg m⁻² h⁻¹) to the downstream (0.43 ± 0.3 mg m⁻² h⁻¹) of the Yellow River. (3) Sediment microbes affected the CH₄ ebullition flux primarily by changing the microbial community abundance. The regression analysis showed that CH₄ ebullition flux had a significantly linear negative correlation with microbial abundance in sediments. The redundancy analysis further showed CH₄ ebullition flux was significantly positively correlated with the abundances of Firmicutes and Actinobacteria, and negatively with that of Proteobacteria and Chloroflexi. Among abiotic variables, CH₄ ebullition flux was closely related to total phosphorus, total organic carbon, pH and nitrate nitrogen.

The Hehuang Valley (HV) is a key development area in the Qinghai Province; understanding changes in the vegetation within this area is of great significance if we are to maintain the ecological quality of this regional environment. Based on the 30 m spatial resolution Normalized difference vegetation index (NDVI) time series dataset, this paper analyzes the spatial and temporal characteristics and evolutionary trends of NDVI in the HV from 2001 to 2020 under the influences of climate change and human activities, by applying Mann-Kendall trend analysis, the Hurst index, and residual analysis. Analysis showed that firstly, high NDVI values (>0.5) were distributed in the low elevation areas of the HV except for towns and cropland, while the low NDVI values (<0.5) were mainly distributed in the high elevation regions; the NDVI exhibited an increasing trend over the study period. Second, human activities promoted NDVI growth in the HV by changing land-use types, although there is a risk of vegetation degradation in the future. Third, the proportion of NDVI changes affected by climate change and human activities was determined to be 87.24% of the HV; furthermore, the contribution of human activities was three-fold higher than that of climate change. Fourth, managers should scientifically manage grasslands and forests and implement specific anthropogenic interventions based on the characteristics of regional NDVI degradation, to improve ecosystem resilience. These results can be used to quantitatively analyze the relative contributions of natural and anthropogenic factors to the ecological changes in the HV, and provide reference guidelines for the management of ecological environments.

The water level of Qinghai Lake, the largest saltwater lake in China, has been rising consistently, which has altered the lake’s ecosystem service patterns and produced an unpredictable impact on local ecological security and sustainable development. To explore the changes in the area around Qinghai Lake’s ecosystem provisioning services that respond to the rise in water level, the spatial and temporal changes of three ecosystem services (water yield, soil conservation, and habitat quality) from 2000 to 2020 were calculated by the InVEST model. Then, the ecosystem service transformation of the rise in Qinghai Lake’s underwater level was evaluated, and the trade-off and synchrony among the three ecosystem services were discussed. Finally, Random Forest and Geographically and Temporally Weighted Regression models were used, to reveal the driving factors and spatial differentiation of ecosystem service change. Results showed that: (1) Although three ecosystem provisioning services were increased by 3.21%, 31.67%, and 6.19%, respectively, in 2000–2020, an overall change trend was observed that they increased first and then decreased. After reaching their peak values in 2005 (444.68 mm), 2015 (341.89 t·hm⁻²·a⁻¹) and 2015 (0.67), three ecosystem provisioning services decreased to 349.27 mm, 271.82 t·hm⁻²·a⁻¹, and 0.66 in 2020, respectively. (2) Three ecosystem provisioning services, as well as ecosystem services among different land use types, presented a synchronous relationship during the research periods. (3) Natural factors, such as precipitation and NDVI (Normalized Difference Vegetation Index), accounted for 30.0% of ecosystem services changes, and Social-economic factors, such as GDP (Gross Domestic Product) and population accounted for 28.0% of three ecosystem provisioning services changes. These driving factors exhibited significant spatial heterogeneity (adjusted R² > 0.6). There were limitations in the scope of ecosystem services evaluation and insufficient consideration of the value of aquatic habitats, which deserved further exploration. This study may provide a scientific basis for the evaluation and management of the plateau lake ecosystem under the background of climate change.