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Soil moisture (SM), an important variable in water conversion between the atmosphere and terrestrial ecosystems, plays a crucial role in ecological processes and the evolution of terrestrial ecosystems. Analyzing and exploring SM's processes and influencing factors in different permafrost regions of the Qinghai-Tibet Plateau (QTP) can better serve the regional ecological security, disaster warning, water management, etc. However, the changes and future trends of SM on the QTP in recent decades are uncertain, and the main factors affecting SM are not fully understood. The study used SM observations, the Global Land Evapotranspiration Amsterdam Model (GLEAM) SM products, meteorological and vegetation data, Mann–Kendall test, Theil–Sen estimation, Ensemble Empirical Mode Decomposition (EEMD), and correlation methods to analyze and explore the characteristics and influencing factors of SM change in different permafrost regions of the QTP. The results show that: (1) At the pixel scale, GLEAM SM products can better reflect SM changes in the QTP in the warm season. The seasonal permafrost region is closer to the real SM than the permanent region, with a median correlation coefficient (R) of 0.738, median bias of 0.043 m3 m−3, and median unbiased root mean square errors (ubRMSE) of 0.031 m3 m−3. (2) The average SM in the QTP warm season increased at a rate of 0.573 × 10−3 m3 m−3 yr−1 over the recent 40 years, and the trend accelerated from 2005–2020. In 64.31% of the region, the soil was significantly wetted, mainly distributed in the permafrost region, which showed that the wetting rate in the dry region was faster than in the wet region. However, the wetting trend does not have a long-term continuity and has a pattern of "wetting–drying-wetting" on interannual and decadal levels, especially in the seasonal permafrost region. (3) More than 65% of the SM wetting trend on the QTP is caused by temperature, precipitation, and vegetation. However, there is apparent spatial heterogeneity in the different permafrost regions and vegetation cover conditions, and the three factors have a more substantial explanatory power for SM changes in the seasonal permafrost region. With the global climate change, the synergistic SM–Climate–Vegetation effect on the QTP tends to be more evident in the seasonal permafrost region. [ABSTRACT FROM AUTHOR]

Evapotranspiration (ET) is a key component of the hydrological cycle, but traditional monitoring approaches are always based on measurements, which cannot satisfy the requirements of research on a regional scale. Hence, ET estimation by remote sensing is essential. MOD16 is a remote-sensing model based on the P-M equation and has good applicability. However, it describes soil moisture indirectly by RH, etc., which may cause uncertainties in ET estimating, so this study attempts to utilize the NDWI as a supplement to soil moisture information and makes improvements on the MOD16 model (with the resultant new model being named MOD16-sm). Specific work includes two aspects: one is model verification through making comparisons between ET estimates and measurements, and the other is a model application effect test analyzing the spatiotemporal characteristics of ET and exploring how ET responds to climate and land-use changes. Model verification indicated that the accuracy of the improved MOD16-sm model increased, with a higher R2 of 0.71, a lower RMSE 0.9 mm, and a lower MAE 0.91 mm, and that the improved MOD16-sm model was convincing. The application effect test of the MOD16-sm model showed that the average relative change rate of annual ET was 1.7%, showing an upward trend, and areas with growth trends of ET also had high vegetation coverage. As for the impacts of climate and land-use changes on ET, ET was positively correlated with precipitation, whereas it had no relevant correlation with air temperature in most areas, and the ET of all land-use types displayed significant increasing trends resulting from climate change. The application effect test demonstrated that ET estimates by the improved MOD16-sm model were reasonable. [ABSTRACT FROM AUTHOR]

Understanding the impact of climate change on terrestrial wet and dry changes and the relationship between the two is of great significance to the sustainable development of terrestrial ecosystems. The farming-pastoral ecotone of northern China (FPENC) is an area that is sensitive to climate change, suffering from perennial drought and a clear aridification trend. Unlike previous single-factor, single-timescale studies, we identified aridification in the region based on a dataset established by remote sensing and ground-based monitoring stations from a combination of two perspectives: climate and soil. The results show that, in terms of climate, the period from 2000 to 2019 was the driest in the region during the last 120 years , and the summer drought was the most severe and shifted from a summer to spring drought; in terms of soil, the soil aridification trend in the region was severe, with 16.1% of the areas becoming significantly drier (P < 0.1) among the years and 41.6% in spring, respectively. Similar to climate change, soils exhibited recessive aridification due to the counterbalancing effect of the dry and wet seasons within the year. Then the coupling relationship between climate change and soil aridification was established in time and space. Moreover, the spatiotemporal response patterns of both were obtained. The results showed that the frequency of soil drought under meteorological drought conditions showed an increasing trend and that the sensitivity of soil drought occurrence increased. Among them, the effect of precipitation on relative soil moisture (RSM) was immediate, and the effect of prolonged warming on RSM is greater. The area of soil aridification that was caused by climatic aridification in spring accounted for 13.7% of the entire area. The regional aridification research mode proposed in this paper can provide ideas for subsequent studies. [Display omitted] • A comprehensive judgment mode of the regional aridification combining climate elements, soil moisture was established. • Over the last 20 years, the central part of the FPENC showed overall warming and wetting of the climate. • Over the last 20 years, the trend of the soil aridification in the central part of the FPENC remained severe. • The counterbalancing effect of the dry and wet seasons leads to recessive aridification. • The sensitivity of the occurrences of soil drought to the climate drought anomalies continuously became stronger. [ABSTRACT FROM AUTHOR]

Soil moisture assessment on production land is gaining more attention as one of the critical factors and had a remarkable impact on agriculture production, life as well as global warming. Bibliometric analysis is performed by extracting datasets from SCOPUS from 2000 to 2020 to analyse soil moisture using remote sensing study and progress in the last two decades. The outcome indicates that study on the development of soil moisture monitoring tools using remote sensing has been increasing especially for international cooperation articles. International Geoscience and Remote Sensing Symposium (IGARSS) recorded the most productive journal published articles in this field. Among the top active countries that produce most articles were the USA followed by China. The current keywords search on soil mechanism and satellite technology frequently searched in this field. Global issues that focus on the relationship between soil moisture and environmental forecast such as drought, climate change and global warming by using remote sensing technology needed more high impact research outputs in the future. [ABSTRACT FROM AUTHOR]

In this study, a microwave-based multisatellite merged product released from the European Space Agency's Climate Change Initiative (ESA CCI) and two model-based simulations from the Community Land Model 4.5 (CLM4.5) and Global Land Data Assimilation System (GLDAS) were used to investigate interannual variations and trends of soil moisture in China between 1979 and 2010. They were also evaluated using in situ observations from the nationwide agrometeorological network. These three datasets show consistent drying trends for surface soil moisture in northeastern and central China, as well the eastern portion of Inner Mongolia, and wetting trends in the Tibetan Plateau, which are also identified by in situ observations. Trends in the root-zone soil moisture are in line with those of surface soil moisture seen in the CLM4.5 and GLDAS simulations obtained from most areas in China (78%-88%), except for northwestern China and southwest of the Tibetan Plateau. Moreover, the drying trend intensifies with increasing soil depth. Taking the in situ measurements as reference, it is found that ESA CCI has better accuracy in identifying the significant drying trends while CLM4.5 and GLDAS capture wetting trends better. Compared to temperature, precipitation is the primary factor responsible for these trends, which controls the direction of soil moisture changes, while increasing temperatures can also enhance soil drying during periods of decreased precipitation. [ABSTRACT FROM AUTHOR]

In this study, we evaluated the European Space Agency Climate Change Initiative soil moisture product v02.1 ( ESA CCI SM v02.1) using in situ observations collected at 547 stations in China from 1991 to 2013. A conventional validation was first conducted, and the triple collocation errors of ESA CCI SM and the European Centre for Medium Range Weather Forecasting reanalysis data were approximately 0.053 and 0.050 m3/m3, respectively. To obtain more reliable validation results, the average soil moisture of the in situ observations per ESA CCI SM pixel was also used as the validation sites. Variance reduction factor ( VRF) was adopted to quantify the accuracy of the soil moisture validation sites, and the average VRF was estimated at 4.88%. The validation results were enhanced by excluding validation sites with VRF errors greater than 5% from the statistical analysis. Although the ESA CCI SM underestimated the in situ observations with a Bias of 0.05 m3/m3, a moderately high correlation coefficient of 0.44 and a relatively small unbiased root-mean-square difference of 0.05 m3/m3 were observed. This study provides information on the utilization of ESA CCI SM for ecological protection, climate change, and hydrological forecasting. It also suggests the adoption of VRF for future error corrections of satellite-based products. [ABSTRACT FROM AUTHOR]