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• The relationship between the groundwater depth and grassland ecology was analysed; • Groundwater depth affected the composition and diversity of vegetation species; • A reasonable groundwater depth can buffer the impact of climate change on the vegetation to maintain grassland ecological stability; • The control of grassland degradation should include the potential exploitation of groundwater. Grassland degradation in the semiarid area of China is often attributed to overgrazing and expansion of irrigated agriculture without the consideration of groundwater. However, falling groundwater levels in the region have caused many problems for grassland ecology. In this paper,the typical sandy grassland- the Tongliao part of Horqin grassland was selected as the study area to study the spatial distribution of normalized difference vegetation index (NDVI) and the relationship between the NDVI and groundwater depth (GD) of each grassland pixel was studied. The temporal variation of the NDVI and its correlations with precipitation were investigated. The relationship between GD and vegetation species diversity in grassland was analyzed based on the vegetation survey. The results of the relation between GD and NDVI and vegetation species showed that GD can buffer the impact of increase in drought events on the vegetation because GD affected the composition and diversity of vegetation species. As the GD increases, the mean NDVI showed a trend of increasing first and then decreasing, and basically remained unchanged when the GD was greater than 3.5 m. The species diversity of grassland decreased with increasing GD and was not related to GD when GD was greater than 3.5 ∼ 4 m. Falling groundwater levels will cause great changes in the structure of grassland; specifically, azonal vegetation will gradually die and 3.5 m may be the critical GD needed to maintain the incomplete extinction of grassland azonal vegetation in the aeolian sandy soil. Correlation analysis proved that the correlation between NDVI and precipitation was significantly enhanced when GD increased sharply from 3 m to 6 m after 1999. This research indicates that the control of grassland degradation should pay attention to controlling the groundwater exploitation to recover a reasonable groundwater level, which was found to be necessary in the support of diverse and climate resilient of vegetation. [ABSTRACT FROM AUTHOR]

• The mean groundwater table depth in China dropped by approximately 0.2 m (P < 0.01) during 1979–2018. • The Noah-MP land model forced with reanalysis climate data can reasonably capture terrestrial water and radiation processes across China. • Incorporating the groundwater lateral flow process enhances the seasonality of modeled terrestrial water and radiation processes on a regional scale. Faced with intensified climate change and ever-increasing water demand, the groundwater table depth is vital to sustaining terrestrial environments in a country such as China; however, on a regional scale, insufficient research has been conducted on its variability thus far. Using a land model forced with reanalysis climate data, this paper investigates groundwater table depth changes across China for the 1979–2018 period. The results show a significant overall reduction in the groundwater table depth in China during the past 40 years without explicit consideration of direct human influence. There is an approximately 0.2 m decrease on average, but it is approximately 0.5 m in southern China and 0.8 m to the north of 35°N despite a 1.2 m rise in part of this region due to an increasingly wet climate and a topographic water convergence. The findings provide a first-order pattern of historical groundwater table responses to climate change, highlighting inherent links among subsurface-surface-atmosphere water cycles and worsened terrestrial water availability in China. A model evaluation compared with in situ observations has demonstrated the model's ability to realistically portray terrestrial water and energy balances on regional scales, as well as the enhancement of their seasonality with incorporated lateral groundwater flow processes. This ability gives us reasonable confidence in the simulated trends and spatial variability. Nonetheless, the mean groundwater table still shows large biases relative to observations, and the problems of human influence, two-way interactions between groundwater and surface water, and local topographical complexity have yet to be properly addressed in the present study and deserve further research. [ABSTRACT FROM AUTHOR]

Human activities and climate change are two key factors influencing the variation of the total amount of available surface and groundwater, hereafter termed water resources. Quantitatively separating their impacts remains a challenge. To this end, we used time-varying Budyko-type equations and a hierarchical Bayesian model in this paper to separate their impacts in 31 provincial-level divisions of China. The time-varying Budyko-type equations treat the Budyko equation parameter w as a variable, which depends on human activities (represented by per capita gross regional production) and climate change (represented by temperature and precipitation). The hierarchical model quantifies the uncertainty of parameters and the interrelation between covariates across regions in China. The results show that the time-varying Budyko-type equation can improve the fitting capability for water resources in China. The hierarchical Bayesian model, which considered spatial dependence, reduced the uncertainty of the parameters compared to spatially independent counterparts. For most regions of China, human activities reduce water resources while climate change increases them. Southeastern China is the most influenced area, and its water resources decreased approximately 50 mm because of human activities. This study can provide a basis for water resource management under climate change and human activity constraints in China. [ABSTRACT FROM AUTHOR]