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Soil moisture is an important component of the soil–vegetation–atmosphere terrestrial hydrological cycle and is an important factor affecting terrestrial ecosystems. In the context of extensive vegetation greening on the Tibetan Plateau (TP), it is important to investigate the effect of vegetation greening on soil moisture to maintain ecosystem stability and protect the sustainability of ecological restoration projects. To evaluate the effect of vegetation greening on soil moisture on the TP, the spatial distribution and trends of soil moisture and vegetation on the TP were analyzed using GIMMS NDVI data and ERA5 soil moisture data from 1982 to 2015. The effects of grassland NDVI, precipitation, and temperature on SM were also explored using multiple regression apparent and SEM. The main results are as follows: from 1982 to 2015, both grassland NDVI and SM showed a stable increasing trend. Precipitation was the most important factor influencing SM changes on the TP. In the context that vegetation greening is mainly influenced by temperature increase, vegetation plays a dominant role in SM changes in soil drying and soil wetting zones. In this paper, the climate–vegetation–soil moisture coupling mechanism of grasslands on the TP is investigated, and the related results can provide some theoretical references and suggestions for global ecosystem conservation and the sustainable development of ecological restoration projects. [ABSTRACT FROM AUTHOR]

L-band passive microwave remote sensing (RS) is an important tool for monitoring global soil moisture (SM) and freeze/thaw state. In recent years, progress has been made in its in-depth application and development in the Tibetan Plateau (TP) which has a complex natural environment. This paper systematically reviews and summarizes the research progress and the main applications of L-band passive microwave RS observations and associated SM retrievals on the TP. The progress of observing and simulating L-band emission based on ground-, aircraft-based and spaceborne platforms, developing regional-scale SM observation networks, as well as validating satellite-based SM products and developing SM retrieval algorithms are reviewed. On this basis, current problems of L-band emission simulation and SM retrieval on the TP are outlined, such as the fact that current evaluations of SM products are limited to a short-term period, and evaluation and improvement of the forward land emission model and SM retrieval algorithm are limited to the site or grid scale. Accordingly, relevant suggestions and prospects for addressing the abovementioned existing problems are finally put forward. For future work, we suggest (i) sorting out the in situ observations and conducting long-term trend evaluation and analysis of current L-band SM products, (ii) extending current progress made at the site/grid scale to improve the L-band emission simulation and SM retrieval algorithms and products for both frozen and thawed ground at the plateau scale, and (iii) enhancing the application of L-band satellite-based SM products on the TP by implementing methods such as data assimilation to improve the understanding of plateau-scale water cycle and energy balance. [ABSTRACT FROM AUTHOR]

Snow plays an important role in the water cycle and global climate change, and the accurate monitoring of changes in snow depth is an important task. However, monitoring snow properties is still challenging and unclear, particularly in the Tibetan Plateau, which has rough land and uneven terrain. The traditional monitoring methods have some limitations in monitoring snow depth changes, and the Global Navigation Satellite System-Reflectometry (GNSS-R) provides a new opportunity for snow monitoring. This paper employed data from the Cyclone Global Navigation Satellite System (CYGNSS) to discover the effect of snow properties. Firstly, the observations of CYGNSS were used to find the sensitive to snow properties, and the relationships between signal to noise ratio (SNR), leading edge slope (LES), surface reflectivity (SR), and snow depth were studied and analyzed, respectively. It is found that the correlation between the first two parameters and snow depth is poor, while SR can indicate the changes in snow depth, and is proposed as an indicator of SR change, namely, surface reflectivity–difference ratio factor (SR–DR factor). Furthermore, the long-time series data in the Tibetan Plateau (2018–2019) are used to analyze its effects on the time series of the SR–DR factor, while the influences of the soil freeze/thaw (F/T) process and soil moisture are excluded during the analysis. The results indicate that the SR–DR factor can be a good indicator and discriminator for snow depth. Our work shows that space-borne GNSS-R has the potential for the monitoring of snow properties. [ABSTRACT FROM AUTHOR]

The spatiotemporal distribution of soil moisture over the Tibetan Plateau is important for understanding the regional water cycle and climate change. In this paper, the surface soil moisture in the northeastern Tibetan Plateau is estimated from time-series VV-polarized Sentinel-1A observations by coupling the water cloud model (WCM) and the advanced integral equation model (AIEM). The vegetation indicator in the WCM is represented by the leaf area index (LAI), which is smoothed and interpolated from Terra Moderate Resolution Imaging Spectroradiometer (MODIS) LAI eight-day products. The AIEM requires accurate roughness parameters, which are parameterized by the effective roughness parameters. The first halves of the Sentinel-1A observations from October 2014 to May 2016 are adopted for the model calibration. The calibration results show that the backscattering coefficient (σº) simulated from the coupled model are consistent with those of the Sentinel-1A with integrated Pearson's correlation coefficients R of 0.80 and 0.92 for the ascending and descending data, respectively. The variability of soil moisture is correctly modeled by the coupled model. Based on the calibrated model, the soil moisture is retrieved using a look-up table method. The results show that the trends of the in situ soil moisture are effectively captured by the retrieved soil moisture with an integrated R of 0.60 and 0.82 for the ascending and descending data, respectively. The integrated bias, mean absolute error, and root mean square error are 0.006, 0.048, and 0.073 m3/m3 for the ascending data, and are 0.012, 0.026, and 0.055 m3/m3 for the descending data, respectively. Discussions of the effective roughness parameters and uncertainties in the LAI demonstrate the importance of accurate parameterizations of the surface roughness parameters and vegetation for the soil moisture retrieval. These results demonstrate the capability and reliability of Sentinel-1A data for estimating the soil moisture over the Tibetan Plateau. It is expected that our results can contribute to developing operational methods for soil moisture retrieval using the Sentinel-1A and Sentinel-1B satellites. [ABSTRACT FROM AUTHOR]

The soil moisture (SM) influences tree growth with climate change. However, the spatial and temporal dynamics of tree water use strategies in climate-sensitive areas remain uncertain. Therefore, we collected the tree-ring oxygen isotope (δ18OTR) chronologies and divided the wet–dry gradients according to the precipitation on the Tibetan Plateau (TP). Further, the relationship between the δ18OTR and environmental factors was analyzed across different gradients. We found the following: (1) The SM during the growing season was the most important factor for δ18OTR. (2) The response of the δ18OTR to the SM had a lag in arid areas than in humid areas. (3) Trees absorbed the SM on the surface in humid areas (r = −0.49 to −0.41, p < 0.01), while trees absorbed the SM from deep in the soil in arid areas (r = −0.48 to −0.29, p < 0.01). The results demonstrated that trees were better able to cope with drought stress in arid regions because they used more stable deep soil water than in humid regions. Therefore, the findings will provide a scientific basis for water use of trees using the δ18OTR in complex environmental contexts. Trees with single water use strategies should be given more attention to keep ecosystems healthy. [ABSTRACT FROM AUTHOR]

As a region susceptible to the impacts of climate change, evaluating the temporal and spatial variations in ecological environment quality (EEQ) and potential influencing factors is crucial for ensuring the ecological security of the Tibetan Plateau. This study utilized the Google Earth Engine (GEE) platform to construct a Remote Sensing-based Ecological Index (RSEI) and examined the temporal and spatial dynamics of the Tibetan Plateau's EEQ from 2000 to 2022. The findings revealed that the RSEI of the Tibetan Plateau predominantly exhibited a slight degradation trend from 2000 to 2022, with a multi-year average of 0.404. Utilizing SHAP (Shapley Additive Explanation) to interpret XGBoost (eXtreme Gradient Boosting), the study identified that natural factors as the primary influencers on the RSEI of the Tibetan Plateau, with temperature, soil moisture, and precipitation variables exhibiting higher SHAP values, indicating their substantial contributions. The interaction between temperature and precipitation showed a positive effect on RSEI, with the SHAP interaction value increasing with rising precipitation. The methodology and results of this study could provide insights for a comprehensive understanding and monitoring of the dynamic evolution of EEQ on the Tibetan Plateau amidst the context of climate change. [ABSTRACT FROM AUTHOR]

Significant temporal and spatial variability in soil moisture (SM) is observed during the warm season in China and its surrounding regions. Because of the existence of two different evapotranspiration regimes, i.e., soil moisture-limited and energy-limited, averaging the land–atmosphere (L–A) coupling strength for all soil wetness scenarios may result in the loss of coupling signals. This study examines the daytime-only L–A interactions under different soil moisture conditions, by using two-legged metrics in the warm season from May to September 1981–2020, partitioning the interactions between SM and latent heat flux (SM–LH, the land leg) from the interactions between latent heat flux and the lifting condensation level (LH–LCL, the atmospheric leg). The statistical results reveal large regional differences in warm-season daytime L–A feedback in China and its surrounding areas. As the soil becomes wetter, the positive SM–LH coupling strength increases in arid regions (e.g., northwest China, Hetao, and the Great Indian Desert) and the positive feedback shifts to the negative one in semi-arid/semi-humid regions (northeast and northern China). The negative LH–LCL coupling is most pronounced in wet soil months in arid regions, while the opposite is true for the Tibetan Plateau. In terms of intraseasonal variation, the large variability of SM in north China, the Tibetan Plateau, and India due to the influence of the summer monsoon leads to the sign change in the land segment coupling index, comparing pre- and post-monsoon periods. To further examine the impact of SM anomalies on L–A coupling and to explore evapotranspiration regimes in the North China Plain, four sets of sensitivity experiments with different soil moisture levels over a period of 10 years were conducted. Under relatively dry soil conditions, evapotranspiration is dominated by the soil moisture-limited regime with positive L–A coupling, regardless of external moisture inflow. The critical soil moisture value separating a soil moisture-limited and an energy-limited regime lies between 0.24 m3/m3 and 0.29 m3/m3. Stronger positive feedback under negative soil moisture anomalies may increase the risk of drought in the North China Plain. [ABSTRACT FROM AUTHOR]

Soil moisture over the Tibetan Plateau (TP) can affect hydrological cycles on local and remote scales through land–atmosphere interactions. However, TP long-term surface soil moisture characteristics and their response to climate change are still unclear. In this study, we firstly evaluate two satellite-based products—SSM/I (the Special Sensor Microwave Imagers) and ECV COMBINED (the Essential Climate Variable combined)—and three reanalysis products—ERA5-Land (the fifth generation of the land component of the European Centre for Medium-Range Weather Forecasts atmospheric reanalysis), MERRA2 (the second version of Modern-Era Retrospective Analysis for Research and Applications), and GLDAS Noah (the Noah land surface model driven by Global Land Data Assimilation System)—against two in situ observation networks. SSM/I and GLDAS Noah outperform the other soil moisture products, followed by MERRA2 and ECV COMBINED, and ERA5-Land has a certain degree of uncertainty in evaluating TP surface soil moisture. Analysis of long-term soil moisture characteristics during 1988–2008 shows that annual and seasonal mean soil moisture have similar spatial distributions of soil moisture decreasing from southeast to northwest. Additionally, a significant increasing trend of soil moisture is found in most of the TP region. With a non-linear machine learning method, we quantify the contribution of each climatic variable to warm-season soil moisture. It indicates that precipitation dominates soil moisture changes rather than air temperature. Pixel-wise partial correlation coefficients further show that there are significant positive correlations between precipitation and soil moisture over most of the TP region. The results of this study will help to understand the role of TP soil moisture in land–atmosphere coupling and hydrological cycles under climate change. [ABSTRACT FROM AUTHOR]

Soil moisture is one of the most critical soil components for sustained plant growth and grassland management. Unmanned aerial vehicles (UAVs) are gradually replacing manual labor in various aspects of grassland management. However, their potential for monitoring soil moisture in grasslands remains largely unexplored. High vegetation coverage and frequent rainfall in the Tibetan Plateau pose a challenge for personnel working in alpine meadows. To explore the potential of UAV technology for soil moisture detection in these areas, we conducted a rainfall reduction experiment in Maqu County, China to understand the relationships among soil moisture, vegetation coverage, and visible-light images captured using UAVs. The findings indicated a significant correlation between topsoil moisture and the brightness values in visible-light images acquired by UAVs (p < 0.0001). These results demonstrated that visible-light brightness, vegetation coverage, rainfall reduction, and aboveground biomass can be utilized for estimating the topsoil moisture using these images (y = −0.2676 × Brightness + 0.2808 × Vegetation coverage −0.1862 × Rainfall reduction + 0.1357 × Aboveground biomass + 37.77). The model validation worked well (E = 0.8291, RS = −3.58%, RMA = 10.38%, RMSE = 3.5878, Pearson's r = 0.9631, PSI = 0.0125). This study further addresses the problem of topsoil moisture measurement in flat areas of mesoscale moist alpine meadows and is expected to facilitate the widespread adoption of UAV use in grassland ecology research. [ABSTRACT FROM AUTHOR]

The alpine grasslands account for approximately 54.5% of the total carbon in China's grasslands, and carbohydrate-active enzymes (CAZymes) play key roles in the turnover of carbon. However, the variation and factors influencing gene-encoding enzymes for plant- and microbial-derived carbon decomposition in alpine steppes and alpine meadows remain unclear. Here, the trends in microbial carbohydrate-active enzymes (CAZymes) and their responses to the decomposition of biomass of different origins were studied using metagenomics in the alpine steppes and alpine meadows on the Tibetan Plateau. Our results revealed the abundance of GTs and CBMs was higher in the alpine steppes than in the alpine meadows, whereas AAs were higher in the alpine steppes than in the alpine meadows. Soil properties (i.e., soil water content, soil ammonium nitrogen, and nitrate nitrogen) highly related to CAZyme genes (GTs, CBMs, and AAs) showed an abundant pattern between the alpine steppes and alpine meadows. Moreover, our results indicated that the relative abundance of genes encoding CAZymes involved in the decomposition of plant- (indicated by cellulose, hemicellulose, and lignin) and fungal-derived carbon (indicated by chitin and glucans) was higher by 8.7% and 10.1%, respectively, in the alpine steppes than in the alpine meadows, whereas bacterial-derived carbon (indicated by peptidoglycan) was lower by 7.9% in the alpine steppes than in the alpine meadows. Soil water content (SWC), nitrate nitrogen (NO3−), and pH influenced on the abundance of CAZyme genes involved in the decomposition of plant-, fungal-, bacterial-derived carbon. In addition, the dominant microbial phyla (Actinobacteria, Protebacteria, and Acidobacteria) mineralized carbon sources from plant- and microbial-derived carbon through their corresponding CAZyme families. In conclusion, our study compared plant- and microbial-derived carbon decomposition potentials and influencing factors to illustrate the contribution of dead biomass to carbon accumulation in alpine grasslands. [ABSTRACT FROM AUTHOR]

SM2RAIN is a well-established methodology for estimating precipitation from satellite or observed soil moisture and it has been applied as a complementary approach to conventional precipitation monitoring methods. However, satellite soil moisture retrievals are usually subject to various biases and limited number of retrievals (and therefore large intervals) in remote areas, such as the Tibetan Plateau (TP), and little is known about their potential impacts on precipitation estimation. This study seeks to quantify the uncertainties in Soil Moisture Active and Passive (SMAP) soil moisture estimated precipitation through the commonly used SM2RAIN by referring to in situ soil moisture observations from the central Tibetan Plateau soil moisture network. The estimated precipitation is evaluated against rain gauge observations. Additional attention is paid to different orbits of the SMAP retrievals. Results show that the original SM2RAIN algorithm tends to underestimate the precipitation amount in the central TP when using SMAP soil moisture retrievals as input. The retrieval accuracy and sampling interval of SMAP soil moisture from ascending (descending) orbits each count for 1.04 mm/5 d (−0.18 mm/5 d) and 1.67 mm/5 d (0.72 mm/5 d) of estimated precipitation uncertainties as represented by root mean square error. Besides, the descending product of SMAP with a relatively less sampling interval and higher retrieval accuracy outperforms the ascending one in estimating precipitation, and the combination of both two orbits does add value to the overall SM2RAIN estimation. This study is expected to provide guidance for future applications of SM2RAIN-derived precipitation. Meanwhile, more reliable SM2RAIN precipitation estimations are desired when using higher quality satellite soil moisture products with better retrieval accuracy and smaller intervals. [ABSTRACT FROM AUTHOR]

Accurate high-resolution soil moisture mapping is critical for surface studies as well as climate change research. Currently, regional soil moisture retrieval primarily focuses on a spatial resolution of 1 km, which is not able to provide effective information for environmental science research and agricultural water resource management. In this study, we developed a quantitative retrieval framework for high-resolution (250 m) regional soil moisture inversion based on machine learning, multisource data fusion, and in situ measurement data. Specifically, we used various data sources, including the normalized vegetation index, surface temperature, surface albedo, soil properties data, precipitation data, topographic data, and soil moisture products from passive microwave data assimilation as input parameters. The soil moisture products simulated based on ground model simulation were used as supplementary data of the in situ measurements, together with the measured data from the Maqu Observation Network as the training target value. The study was conducted in the Zoige region of the Tibetan Plateau during the nonfreezing period (May–October) from 2009 to 2018, using random forests for training. The random forest model had good accuracy, with a correlation coefficient of 0.885, a root mean square error of 0.024 m³/m³, and a bias of −0.004. The ground-measured soil moisture exhibited significant fluctuations, while the random forest prediction was more accurate and closely aligned with the field soil moisture compared to the soil moisture products based on ground model simulation. Our method generated results that were smoother, more stable, and with less noise, providing a more detailed spatial pattern of soil moisture. Based on the permutation importance method, we found that topographic factors such as slope and aspect, and soil properties such as silt and sand have significant impacts on soil moisture in the southeastern Tibetan Plateau. This highlights the importance of fine-scale topographic and soil property information for generating high-precision soil moisture data. From the perspective of inter-annual variation, the soil moisture in this area is generally high, showing a slow upward trend, with small spatial differences, and the annual average value fluctuates between 0.3741 m3/m3 and 0.3943 m3/m3. The intra-annual evolution indicates that the monthly mean average soil moisture has a large geographical variation and a small multi-year linear change rate. These findings can provide valuable insights and references for regional soil moisture research. [ABSTRACT FROM AUTHOR]

Snow on the Tibetan Plateau (TP) is an important signal for the prediction of East Asian climate. In this study, the relationship between the TP spring snowmelt and spring and summer precipitation in Northwest China (NWC) was investigated, along with the possible mechanisms linked to the impacts of snowmelt on precipitation. The results showed that the TP spring snowmelt had significant impacts on spring and summer precipitation in NWC. For example, when there was a large spring snowmelt in the central- eastern TP, the spring and summer precipitation in the Hexi Corridor and southeast NWC was excessive, especially in summer; when there was a large spring snowmelt in the northern TP, the spring and summer precipitation was deficient across the whole of NWC, while a large spring snowmelt in the western TP led to deficient spring and summer precipitation in eastern NWC but excessive precipitation in western NWC. The possible mechanisms for this included the fact that more spring snowmelt over the TP led to higher soil moisture contents, which further resulted in weakened subtropical westerly and enhanced ridge over Xinjiang. By changing the TP thermal forcing, these anomalous atmospheric circulation conditions transported water vapor into NWC, thus creating excessive summer precipitation in that region. [ABSTRACT FROM AUTHOR]

Soil freeze–thaw processes are remarkable features of the land surface across the Tibetan Plateau (TP). Soil moisture and temperature fluctuate during the freeze–thaw cycle, affecting the soil water and energy exchange between the land and atmosphere. This study investigates variations in the soil temperature, humidity, and freeze–thaw state and their responses to air temperature and precipitation on the TP from 1981 to 2016. Regional simulations of the TP using Community Land Model version 4.5 demonstrate that the climate of the TP has become warmer and wetter over the past 37 years, with increases in both regional average temperature and precipitation. Using empirical orthogonal function analysis and the Mann–Kendall trend test of air temperature, we show that 1980–1998 was relatively cold, and 1999–2016 was relatively warm. Soil temperature and moisture in most areas of the TP were affected by air temperature and precipitation, and both showed an upward trend during the past 37 years. Overall, from 1981 to 2016, the freezing date of the TP has become delayed, the thawing date has been hastened, and the duration of the freeze–thaw state has shortened. The surface soil freezes and thaws first, and these processes pervade deeper soil with the passage of time; freeze–thaw processes have an obvious hysteresis. Precipitation and air temperature had marked effects on the freeze–thaw processes. Higher air temperatures delay the freezing date, hasten the thawing date, and shorten the freeze–thaw period. Areas with the highest precipitation saw late soil freeze, early thaw, and the shortest freeze–thaw duration. Areas with less vegetation froze earlier and thawed later. The freeze–thaw duration increased in the northwest of the plateau and decreased on the rest of the plateau. This article informs research on frozen soil change in the context of global warming. [ABSTRACT FROM AUTHOR]

A simple soil moisture (SM) estimation method is proposed using apparent thermal inertia (ATI) and evapotranspiration (ET) data. Among the methods of estimating SM by using thermal infrared (TIR) remote sensing, the ATI method is widely used in bare soil and low vegetation areas. However, large surface ET will cause ATI error, resulting in lower accuracy of SM estimation. To overcome this problem, the potential of ATI-ET space for estimating the SM of bare and vegetated farmland in the dry season (no irrigation) is studied. ATI and ET data were used to construct triangle feature space, and six distance parameters are extracted from the positions of random pixels in the triangle. Some correlation estimates were made to derive those parameters that were useful for SM estimation, which were three in total. The SM estimation model consisting of these three parameters was built. Compared with the ATI model, the ATI-ET triangle model can not only be applied to areas with high ET, but also has higher accuracy in estimating SM. The ATI-ET triangle model is more suitable for application in bare soil and low vegetation areas. As the Normalized Difference Vegetation Index increases, the accuracy of the model estimates decreases. To show the high portability of the proposed model for SM estimation, we chose another set of in situ SM data acquired in Tibetan Plateau. The results proved the effectiveness of the model in other similar study regions. [ABSTRACT FROM AUTHOR]

To date, there have been few studies of the functional traits of the dioecious Hippophae tibetana Schlecht leaves, either male or female, in response to ecological factors such as altitude. Elucidating these relationships will establish an important scientific basis for vegetation restoration and reconstruction of the Tibetan Plateau ecosystem. The natural populations of H. tibetana, distributed across three field sites, at 2868 m, 3012 m and 3244 m, in Tianzhu, Gansu, were studied by field survey sampling and laboratory analysis. In particular, the adaptions of leaf functional traits to elevation in these dioecious plants were analyzed. The results show that: (1) there is no "midday depression" of photosynthetic activity in either male or female plants. Over a one-day period, the net photosynthetic rate (Pn) and transpiration rate (Tr) of H. tibetana female plants were higher than those of male plants (p < 0.05). This correlated to the period of vigorous fruit growth in the female plant. The measured Pn and Tr were maximal at the intermediate altitude (3012 m). The light compensation point (LCP) of the leaves of male and female plants were 57.6 and 43.2 μmol·m−2·s−1, respectively, and the light saturation points (LSP) of the leaves were 1857.6 and 1596.8 μmol·m−2·s−1. (2) Altitude had a significant effect on plant and leaf functional traits of male and female H. tibetana (p < 0.05), and no significant difference was noted between plants at the same altitude. The values for leaf area (LA), specific leaf weight (LMA), leaf phosphorus content per unit mass (Pmass) and leaf phosphorus content per unit area (Parea) were also maximal at the intermediate altitude. Leaf nitrogen content per unit area (Narea) and leaf nitrogen content per unit mass (Nmass) increased with altitude. This indicated that the functional traits of male and female plants and leaves of H. tibetana showed a strong "trade-off relationship" with altitude. (3) Pearson correlation analysis showed that there were significant correlations among functional traits of H. tibetana leaves. Redundancy analysis (RDA) showed that soil water content (SWC), altitude (Alt) and soil organic carbon (SOC) had significant effects on the functional traits of H. tibetana leaves (p < 0.05). [ABSTRACT FROM AUTHOR]

Using observational data of soil moisture from the third Tibetan Plateau Experiment for atmospheric science (TIPEX III), the seasonal and diurnal variations characteristics of soil moisture at different depths of 5–160 cm from seven stations were analyzed, with emphasis on the comparative analysis of the differences of soil moisture between different sites and the differences of the synergistic relationship between soil moisture and temperature. The soil moisture was wet in the southeast and dry in the northwest. The studied sites were Lhari, Biru, Nyainrong, Amdo, Nagqu, Baingoin and Seng-ge Kambab in descending order, according to the soil moisture. The seasonal variation of soil moisture at the different sites showed a significant three-peak structure, which was more obvious in the shallow layer than in the deep layer. The first peak occurred from March to May, which was mainly due to the soil thawing in spring. The other two peaks corresponded to the two rainy seasons in the plateau. Soil moisture was the greatest during this rainy period. The diurnal variations of soil moisture and temperature in Amdo, Nagqu, Nyainrong and Baingoin showed a significant positive correlation in the four seasons. The soil moisture and temperature in Lhari and Biru were significantly positively correlated in winter and spring but negatively correlated in summer and autumn. The profiles of the soil moisture with depth varied greatly at different stations in different seasons. The distribution of soil water content at each observational site did not increase or decrease with depth but showed a certain high aquifer, which might be related to the types of the underlying surface and physical properties of soil. During the summer monsoon period, soil moisture in the shallow layer of 5–10 cm was higher at all observational sites. The spatial distribution of soil moisture in the plateau was more heterogeneous than that in the plain area, and only in the central part of the Tibetan Plateau, the soil moisture varied greatly from site to site. This also indicated that it was unreasonable to only use the soil moisture of several stations to represent the overall soil moisture of the region. The results provided a multi-angle observational basis for the validation of satellite data and parameterization of the numerical model of soil moisture over the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

Soil moisture (SM), as a crucial variable in the soil–vegetation–atmosphere continuum, plays an important role in the terrestrial water cycle. Analyzing SM's variation and driver factors is crucial to maintaining ecosystem diversity on the Tibetan Plateau (TP) and ensuring food security as well as water supply balance in developing countries. Gradual wetting of the soil has been detected and attributed to precipitation in this area. However, there is still a gap in understanding the potential mechanisms. It is unclear whether the greening, glacier melting, and different vegetation degradation caused by asymmetrical climate change and intensified human activities have significantly affected the balance of SM. Here, to test the hypothesis that heterogeneous SM caused by precipitation was subject to temperatures and anthropogenic constraints, GLDAS-2.1 (Global Land Data Assimilation System-2.1) SM products combined with the statistical downscaling and Geographic detectors were applied. The results revealed that: (1) Seasonal SM gradually increased (p < 0.05), while SM deficit frequently appeared with exposure to extreme climates, such as in the summer of 2010 and 2013, and changed into a pattern of precipitation transport to western dry lands in autumn. (2) There was a synergistic reaction between greening and local moisture in autumn. SM was dominated by low temperature (TMN) in winter, warming indirectly regulated SM by exacerbating the thawing of glaciers and permafrost. The spatial coupling between the faster rising rate of TMN and the frozen soil might further aggravate the imbalance of SM. (3) The land cover's mutual transformation principally affected SM in spring and autumn, and degradation accelerated the loss of SM replenished by precipitation. (4) Land cover responses were different; SM in grassland was less affected by external disturbance, while degraded woodland and shrub performed adaptive feedback under dry environments, SM increased by 0.05 and 0.04 m3/(m3 10a), respectively. Our research provides a scientific basis for improving hydrological models and developing vegetation restoration strategies for long-term adaptation to TP-changing environments. [ABSTRACT FROM AUTHOR]

This paper presents an approach for retrieval of soil moisture in Nagqu region of Tibetan Plateau using VV-polarized Sentinel-1 SAR and MODIS optical data, by coupling the semi-empirical Oh-2004 model and the Water Cloud Model (WCM). The Oh model is first used to estimate the surface roughness parameter based on the hypothesis that the roughness is invariant among SAR acquisitions. Afterward, the vegetation water content (VWC) in the WCM is calculated from the daily MODIS NDVI data obtained by temporal interpolation. To improve the performance of the model, the parameters A, B, and α of the WCM are analyzed and optimized using randomly selected half of the sampled dataset. Then, the soil moisture is retrieved by minimizing a cost function between the simulated and measured backscattering coefficients. The comparison of the retrieved soil moisture with the ground measurements shows the determination coefficient R2 and the Root Mean Square Error (RMSE) are 0.46 and 0.08 m3/m3, respectively. These results demonstrate the capability and reliability of Sentinel-1 SAR data for estimating the soil moisture over the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

The evolution of plateau monsoons is essential to synoptic climatology processes over the Qinghai-Xizang Plateau. Based on ERA-Interim Reanalysis data covering 1979-2014 from the European Centre for Medium-Range Weather Forecasts (ECMWF), we propose a new plateau monsoon index (ZPMI) that can effectively reflect the evolution of monsoons and compare this new index with the existing Plateau Monsoon Indices (PMI), i.e., the Traditional Plateau Monsoon Index (TPMI), the Dynamic Plateau Monsoon Index (DPMI), and the PMI proposed by Qi et al. (QPMI). The results show that the onset and retreat of plateau monsoons determined by the TPMI are approximately 1-2 months earlier than those of the ZPMI and DPMI and that the ZPMI can better reflect seasonal and inter-annual variations in precipitation over the plateau. The plateau summer and winter monsoons have similar inter-annual and inter-decadal variation characteristics and show a rising trend, but the increasing trend of the summer monsoon is more significant. The ZPMI is also capable of effectively reflecting meteorological elements. In stronger plateau summer monsoon years, more (less) precipitation and a higher (lower) air temperature appear over the eastern and central (western) plateau. The ZPMI and soil moisture in April and May are used to explore the influence of soil moisture on plateau monsoons, and a significant correlation is found between the plateau soil moisture in the spring (April-May) and plateau summer monsoons. It is found that when the soil moisture over the central and eastern plateau is higher (lower) than normal (while the soil moisture over the western plateau is lower (higher)), the plateau summer monsoon may be stronger (weaker). [ABSTRACT FROM AUTHOR]

Effective soil temperature Teff is one of the basic parameters in passive microwave remote sensing of soil moisture. At present, dedicated satellite soil moisture monitoring missions use the L-band as the operating frequency. However, Teff at the L-band is strongly affected by soil moisture and temperature profiles. Recently, a two-layer scheme and a corresponding multilayer form have been developed to accommodate such influences. In this study, the soil moisture/temperature data collected and simulated by the Noah land surface model across the Maqu Network are used to verify the newly developed schemes. There are two key findings. Firstly, the new two-layer scheme is able to assess which site provides relatively higher accuracy when estimating Teff. It is found that, on average, nearly 20% of the Teff signal cannot be captured by the Maqu Network, in the currently assumed common installation configuration. This knowledge is important, since the spatial averaged brightness temperature (a function of Teff) is used to determine soil moisture. Secondly, the developed method has made it possible to identify that the optimal mounting depths for the observation pair are 5 cm and 20 cm for calculating Teff at the center station in the Maqu Network. It has been suggested that the newly developed method can provide an objective way to configure an optimal soil moisture/temperature network and improve the representativeness of the existing networks regarding the calculation of Teff. [ABSTRACT FROM AUTHOR]

The inter-comparison of different soil moisture (SM) products over the Tibetan Plateau (TP) reveals the inconsistency among different SM products, when compared to in situ measurement. It highlights the need to constrain the model simulated SM with the in situ measured data climatology. In this study, the in situ soil moisture networks, combined with the classification of climate zones over the TP, were used to produce the in situ measured SM climatology at the plateau scale. The generated TP scale in situ SM climatology was then used to scale the model-simulated SM data, which was subsequently used to scale the SM satellite observations. The climatology-scaled satellite and model-simulated SM were then blended objectively, by applying the triple collocation and least squares method. The final blended SM can replicate the SM dynamics across different climatic zones, from sub-humid regions to semi-arid and arid regions over the TP. This demonstrates the need to constrain the model-simulated SM estimates with the in situ measurements before their further applications in scaling climatology of SM satellite products. [ABSTRACT FROM AUTHOR]

Soil moisture is a key variable in the process of land–atmosphere energy and water exchange. Currently, there are a large number of operational satellite-derived soil moisture products and reanalysis soil moisture products available. However, due to the lack of in situ soil moisture measurements over the Tibetan Plateau (TP), their accuracy and applicability are unclear. Based on the in situ measurements of the soil moisture observing networks established at Maqu, Naqu, Ali, and Shiquanhe (Sq) by the Institute of Tibetan Plateau Research, the Chinese Academy of Sciences, the Northwest Institute of Eco-Environmental Resources, the Chinese Academy of Sciences and the University of Twente over the TP, the accuracy and reliability of the European Space Agency Climate Change Initiative Soil Moisture version 4.4 (ESA CCI SM v4.4) soil moisture products and the European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5) soil moisture product were evaluated. The spatiotemporal distributions and interannual variations of the soil moisture were analyzed. Further, the climatological soil moisture changing trends across the TP were explored. The results show that with regard to the whole plateau, the combined product performs the best (unbiased root-mean-square error (ubRMSE) = 0.043 m3/m3, R = 0.66), followed by the active product (ubRMSE = 0.048 m3/m3, R = 0.62), the passive product (ubRMSE = 0.06 m3/m3, R = 0.61), and the ERA5 soil moisture product (ubRMSE = 0.067 m3/m3, R = 0.52). Considering the good spatiotemporal data continuity of the ERA5 soil moisture product, the ERA5 soil moisture data from 1979 to 2018 were used to analyze the climatological soil moisture changing trend for the entire TP surface. It was found that there was an increasing trend of soil moisture across the TP, which was consistent with the overall trends of increasing precipitation and decreasing evaporation. Moreover, the shrinkage of the cryosphere in conjunction with the background TP warming presumably contribute to soil moisture change. [ABSTRACT FROM AUTHOR]