The dynamics of plants’ carbon and water use efficiency and their responses to drought are crucial to the sustainable development of arid and semi-arid environments. This study used trend analysis and partial correlation analysis to examine the carbon use efficiency (CUE) and water use efficiency (WUE) of Inner Mongolia’s vegetation from 2001 to 2020. MODIS data for gross primary productivity (GPP), net primary productivity (NPP), potential evapotranspiration (PET), evapotranspiration (ET), drought severity index (DSI), and plant type were used. Altered trends were observed for drought during 2001–2020 in the study area. The results revealed that 98.17% of the research area’s drought trend was from dry to wet and 1.83% was from wet to dry, and the regions with decreased drought regions were broadly dispersed. In 2001–2020, CUE in Inner Mongolia declined by 0.1%·year⁻¹, whereas WUE reduced by 0.008 g C·mm⁻¹·m⁻²·year⁻¹, but the total change was not significant. CUE decreased from west to east, whereas WUE increased from southwest to northeast. DSI and CUE had the highest negative connection, accounting for 97.96% of the watershed area, and 71.6% passed the significance test. The correlation coefficients of DSI and WUE were spatially opposite to those of CUE and DSI. In total, 54.21% of the vegetation cover exhibited a negative connection with DSI. The CUE and WUE of different vegetation types in Inner Mongolia were negatively correlated with the DSI index except for grasslands (GRA). Drought in Inner Mongolia mostly influenced the CUE of different plant types, which had a higher negative correlation than WUE. The study’s findings can inform climate change research on Inner Mongolia’s carbon and water cycles.

Soil moisture plays an important role in hydrology, climate, agriculture, and ecology, and remote sensing is one of the most important tools for estimating the soil moisture over large areas. Soil moisture, which is calculated by remote sensing inversion, is affected by the uneven distribution of vegetation and therefore the results cannot accurately reflect the spatial distribution of the soil moisture in the study area. This study analyzes the soil moisture of different vegetation covers in the Wushen Banner of Inner Mongolia, recorded in 2016, and using Landsat and MODIS images fused with multispectral bands. Firstly, we compared and analyzed the ability of the visible optical and short-wave infrared drought index (VSDI), the normalized differential infrared index (NDII), and the short-wave infrared water stress index (SIWSI) in monitoring the soil moisture in different vegetation cover soils. Secondly, we used the stepwise multiple regression analysis method in order to correlate the multispectral fusion bands with the field-measured soil water content and established a soil moisture inversion model based on the multispectral fusion bands. As the results show, there was a strong correlation between the established model and the measured soil water content of the different vegetation cover soils: in the bare soil, R2 was 0.86; in the partially vegetated cover soil, R2 was 0.84; and in the highly vegetated cover soil, R2 was 0.87. This shows that the established model could better reflect the actual condition of the surface soil moisture in the different vegetation covers.

Sand prevention and control are the main tasks of desertification control. The MU Us Sandy Land (MUSL), one of China’s four main deserts, frequently experiences droughts and has a very fragile biological environment. Climate change is the main factor leading to drought, and it may result in more serious drought situations in the future. The Temperature Vegetation Dryness Index (TVDI) was established using land surface temperature and normalized difference vegetation index data. In this paper, we investigate spatial and temporal change characteristics, future change trends, and the time-lag effect of TVDI on climate factors at different scales in MUSL from 2001 to 2020 using Sen + Mann–Kendall trend analysis, Hurstexponent, partial correlation analysis, and lag analysis methods. The results show that (1) the overall drought shows a spatial characteristic of gradually alleviating from west to east (TVDI = 0.6). A significant drying trend dominated 38.5% of the pixels in the fall (Z = 1.99), and a highly significant drying trend dominated the rest of the three seasons (Z average = 2.95) and the whole year (Z = 3.47). (2) In the future, dry autumn, winter, and the whole year will be dominated by continuous drying, and spring and summer will mainly change from dry to wet. The main relationships between winter TVDI and temperature (−0.06) and precipitation (−0.07) were negative, while evapotranspiration (0.18) showed a positive correlation. The six land use types in spring, summer, fall, and the whole year were primarily non-significantly positively correlated with temperature and evapotranspiration. (3) At the seasonal scale, the sensitive factors in spring and autumn were opposite, with spring TVDI responding quickly to precipitation (0.3 months) and being less sensitive to temperature (1.8 months) and evapotranspiration (2 months). At the interannual scale, desert land TVDI was most sensitive to precipitation (2.6 months) and least responsive to temperature (3 months).

Ecosystem water use efficiency (eWUE) is a useful metric to examine the interactions between water and carbon cycles in ecosystems. To reveal the response and adaptation characteristics of different vegetation types within the context of global warming on a regional scale, the spatiotemporal characteristics and influencing factors of the seasonal eWUE of various vegetation types in Inner Mongolia from 2001 to 2020 were explored. Based on MODIS gross primary productivity (GPP), evapotranspiration (ET) data and meteorological data, in this study, we estimated eWUE in different seasons in Inner Mongolia and used trend analysis and correlation analysis methods to analyze the relationship between eWUE in spring, summer and autumn and the temperature–precipitation. From 2001 to 2020, in this region, the GPP and ET in spring, summer and autumn showed increasing trends. In addition, the growth rates of GPP and ET in spring and summer were higher than those in autumn. Under the combined effect of GPP and ET, eWUE in different seasons showed a significant decreasing trend (p < 0.05)—this is ascribed to the extent of ET increasing more than GPP, especially in summer, with the most obvious decreasing rate. In terms of spatial trend, in spring and summer, there is a decreasing trend from northeast to southwest. The effects of precipitation and temperature on the eWUE in Inner Mongolia were mainly negatively correlated in the northeastern part of Inner Mongolia with higher altitudes during the spring and autumn seasons. In total, 95.096% of the total area had positive correlations between eWUE and temperature in spring. In summer, the region in which the WUE of the vegetation had an inverse relationship with both the temperature and the amount of precipitation was the largest compared to these regions in spring and autumn.