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Soil moisture and soil temperature (SMST) are important state variables for quantifying the exchange of heat and water between land and atmosphere. Yet, long-term, regional-scale in situ SMST measurements are scarce on the Tibetan Plateau (TP), with even fewer are available for multiple soil depths. Tibet-Obs is such a long-term, regional-scale SMST observatory in the TP that has been established 10 years ago and includes three SMST monitoring networks, i.e. Maqu, Naqu, and Ngari (including Ali and Shiquanhe), located in the cold humid area covered by grassland, the cold semiarid area dominated by tundra, and the cold arid area dominated by desert, respectively. This paper presents a long-term (∼ 10 years) SMST profile dataset collected from the Tibet-Obs, which includes the original in situ measurements at a 15 min interval collected between 2008 and 2019 from all the three networks and the spatially upscaled data (SMups and STups) for the Maqu and Shiquanhe networks. The quality of the upscaled data is proved to be good, with errors that are generally better than the measured accuracy of adopted SMST sensors. Long-term analysis of the upscaled SMST profile data shows that the amplitudes of SMST variations decrease with increasing soil depth, and the deeper soil layers present a later onset of freezing and an earlier start of thawing and, thus, a shorter freeze–thaw duration in both the Maqu and Shiquanhe networks. In addition, there are notable differences between the relationships of SMups and STups under freezing conditions for the Maqu and Shiquanhe networks. No significant trend can be found for the SMups profile in the warm season (from May to October) for both networks that is consistent with the tendency of precipitation. A similar finding is also found for the STups profile and air temperature in the Shiquanhe network during the warm season. For the cold season (from November to April), a drying trend is noted for the SMups above 20 cm in the Maqu network, while no significant trend is found for those in the Shiquanhe network. Comparisons between the long-term upscaled data and five reanalysis datasets, including the ECMWF reanalysis v5 (ERA5), Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2), Global Land Data Assimilation System version 2 Catchment Land Surface Model (GLDAS-2.1 CLSM), GLDAS-2.1 Noah, and GLDAS-2.1 variable infiltration capacity (GLDAS-2.1 VIC), indicate that none of the current model-based products can reproduce the seasonal variations and interannual trend changes in the measured SMST profile dynamics in both networks. All the products underestimate the STups at every depth, leading to an earlier onset of freezing and a later onset of thawing, which essentially demonstrates that the current models are not able to adequately simulate winter conditions on the TP. In short, the presented dataset would be valuable for evaluation and improvement in long-term satellite- and model-based SMST products on the TP, enhancing the understanding of TP hydrometeorological processes and their response to climate change. The dataset is available in the 4TU.ResearchData repository at https://doi.org/10.4121/20141567.v1 (Zhang et al., 2022).

The soil moisture observation data from the Qinghai-Tibetan Plateau permafrost and alpine wetland (PAW) monitoring network and from the National Centers for Environmental Prediction Final (NCEP-FNL) from 1989 to 2019 were adopted to drive the Lagrangian backward trajectory model to simulate the water vapour transportation paths and source regions to the three-river source region during dry and wet episodes. The results showed that the water vapour transport paths mainly came from the land and ocean in the west during the extreme drought episodes based on the standardized precipitation index (SPI), including the northern African continent, the eastern European plains, and the mid-latitudes of the Atlantic Ocean. The water vapour source regions were mainly concentrated in the Kashmir region, northeast India and southern Motuo on the Qinghai-Tibet Plateau. When the SPI indicated an extremely wet state, the transport mainly occurred to the east and south, including the Pacific Ocean and the South China Sea, where water vapour entered the mainland from East/South China, passed through the Yangtze River Basin, and finally reached the three-river source region from east or south of the Qinghai-Tibet Plateau, while the water vapour from the Indian Ocean and Arabian Sea passed through the Indian Peninsula and the Bay of Bengal and entered the three-river source region from the western and southern sides of the Qinghai-Tibet Plateau.

Active and passive microwave characteristics of diurnal soil freeze-thaw transitions and their relationships are crucial for developing retrieval algorithms of the soil liquid water content (θliq) and freeze/thaw state, which, however, have been less explored. This study investigates these microwave characteristics and relationships via analysis of ground-based measurements of brightness temperature (TB) and backscattering coefficients (σ⁰) in combination with simulations performed with the Tor Vergata discrete radiative transfer model. Both an L-band (1.4 GHz) radiometer ELBARA-III and a wide-band (1-10 GHz) scatterometer are installed in a seasonally frozen Tibetan meadow ecosystem to measure diurnal variations of TB and copolarized σ⁰ at both hh (σhh⁰) and vv (σ vv⁰) polarizations. Analysis of measurements collected between December 2017 and March 2018 shows that 1) diurnal cycles are observed in both TB and σ ⁰ due to the change in surface θliq caused by diurnal soil freeze-thaw transitions; 2) a negatively linear relationship is found between e and σ⁰ regardless of frequency, polarization combinations, and observation angles; 3) slopes (β ) of linearly fit equations between eH and σhh⁰ decrease with increasing observation angles of ELBARA-III, while the ones between eV and σvv⁰ increase with increasing observation angles; and 4) correlations between e and σ⁰ increase with decreasing microwave frequency of σ⁰ measurements and ELBARA-III observation angles, and magnitudes of diurnal σ⁰ cycles also increase with decreasing microwave frequency. Moreover, the calibrated Tor Vergata model shows capability to reproduce both diurnal e and σ⁰ variations as well as to quantify their relationships at different frequencies and observation angles.

TA-CS@SAA (tartaric acid modified calcium carbide slag doped with aluminum ash) with a large specific surface area was prepared by calcination and modification with tartaric acid and used as an adsorbent for removing fluoride from wastewater.

In this paper, the standardized precipitation evapotranspiration index (SPEI) at the monthly scale was calculated based on ground observations to obtain different drought and wet events at the surface of the Loess Plateau in summer from 2000-2017. Using the NECP FNL (National Centers for Environmental Prediction Final) data for the same period, backward simulations with the FLEXPART model were performed to obtain the water vapor transport characteristics and potential evaporative sources corresponding to different dry and wet events. Finally, the contribution of water vapor sources to precipitation on the Loess Plateau was obtained. The results show that the primary sources of water vapor on the Loess Plateau during dry and wet summer events are concentrated in the Loess Plateau and the Yunnan-Kweichow Plateau regions and sporadically distributed in the Altay region of Xinjiang, as well as at the junction of China, Kazakhstan and Mongolia. The evaporation extent and intensity in northern Xinjiang and Mongolia increase when the surface experiences wet-normal-dry events. The local internal circulation on the Loess Plateau contributes to 31.3% and 36.8% of the water vapor in drought and wet events, respectively. Influenced by the westerly wind belt and southwest monsoon, the precipitation contributions of the Yunnan-Kweichow Plateau are 11.2% and 13.1%, respectively, and those of Mongolia are 14.6% and 11.9%, respectively. The water vapor contributions from the Arabian Sea and Bay of Bengal in the south are insignificant. The results aid in understanding the mechanisms of drought and wet events on the Loess Plateau.

Stored-product pests are a major problem in food production and storage. Essential oils (EOs) have been reported to have a wide range of insecticidal activities. In this study, the EOs of flowers and leaves from Elsholtzia stauntoni were analyzed for their chemical composition by GC–MS. The two EOs and their two common main components (cuminol and caryophyllene) were evaluated for their bioactivities against T. castaneum adults. Results of GC–MS analysis indicated that the chemical composition of EOs of flowers and leaves from E. stauntoni had certain similarity and diversity. The two same major components of EOs of flowers and leaves were cuminol (27.81% and 27.62%, respectively) and caryophyllene (5.78% and 10.95%, respectively). The results of bioassays indicated that the EOs of flowers and leaves possessed obvious contact toxicities (LD50 = 19.05 and 18.75 µg/Adult, respectively) and repellent activities against T. castaneum. In addition, the EOs of flowers (LC50 = 16.26 mg/L Air) showed the higher fumigant toxicity than that of leaves (LC50 = 44.42 mg/L Air). Cuminol and caryophyllene exhibited contact toxicity and repellency against T. castaneum, but showed no fumigant toxicity. In particular, cuminol was still significantly repellent to T. castaneum within the testing concentration range of 78.63–0.13 nL/cm2 after 48 h. Furthermore, cuminol and caryophyllene exhibited synergistic contact activity against T. castaneum in all experimental ratios. Altogether, it suggests that EOs of E. stauntoni and their two major monomers have promising potential to serve as bio-insecticides for controlling T. castaneum.

The Tibetan Plateau observatory of plateau scale soil moisture and soil temperature (Tibet-Obs) was established ten years ago, which has been widely used to calibrate/validate satellite- and model-based soil moisture (SM) products for their applications to the Tibetan Plateau (TP). This paper reports on the status of the Tibet-Obs and presents a 10-year (2009–2019) surface SM dataset produced based on in situ measurements taken at a depth of 5 cm collected from the Tibet-Obs that consists of three regional-scale SM monitoring networks, i.e. the Maqu, Naqu, and Ngari (including Ali and Shiquanhe) networks. This surface SM dataset includes the original 15-min in situ measurements collected by multiple SM monitoring sites of the three networks, and the spatially upscaled SM records produced for the Maqu and Shiquanhe networks. Comparisons between four spatial upscaling methods, i.e. arithmetic averaging, Voronoi diagram, time stability and apparent thermal inertia, show that the arithmetic average of the monitoring sites with long-term (i.e. ≥ six years) continuous measurements are found to be most suitable to produce the upscaled SM records. Trend analysis of the 10-year upscaled SM records using the Mann-Kendall method shows that the Maqu network area in the eastern part of the TP is drying while the Shiquanhe network area in the west is getting wet that generally follow the change of precipitation. To further demonstrate the uniqueness of the upscaled SM records in validating existing SM products for long term period (~ 10 years), comparisons are conducted to evaluate the reliability of three reanalysis datasets for the Maqu and Shiquanhe network areas. It is found that current model-based SM products still show deficiencies in representing the trend and variation of measured SM dynamics in the Tibetan grassland (i.e. Maqu) and desert ecosystems (i.e. Shiquanhe) that dominate the landscape of the TP. The dataset would be also valuable for calibrating/validating long-term satellite-based SM products, evaluation of SM upscaling methods, development of data fusion methods, and quantifying the coupling strength between precipitation and SM at 10-year scale. The dataset is available in the 4TU.ResearchData repository at https://doi.org/10.4121/uuid:21220b23-ff36-4ca9-a08f-ccd53782e834 (Zhang et al., 2020).

A ground-based scatterometer was installed on an alpine meadow over the Tibetan Plateau to study the soil moisture and temperature dynamics of the top soil layer and air–soil interface during the period August 2017–August 2018. The deployed system measured the amplitude and phase of the ground surface radar return at hourly and half-hourly intervals over 1–10 GHz in the four linear polarization combinations (vv, hh, hv, vh). In this paper we describe the developed scatterometer system, gathered datasets, retrieval method for the backscattering coefficient (σ0), and results of σ0. The system was installed on a 5 m high tower and designed using only commercially available components: a vector network analyser (VNA), four coaxial cables, and two dual-polarization broad-band gain horn antennas at a fixed position and orientation. We provide a detailed description on how to retrieve the backscattering coefficients for all four linear polarization combinations σpq0, where p is the received and q the transmitted polarization (v or h), for this specific scatterometer design. To account for the particular effects caused by wide antenna radiation patterns (G) at lower frequencies, σ0 was calculated using the narrow-beam approximation combined with a mapping of the function G2/R4 over the ground surface. (R is the distance between antennas and the infinitesimal patches of ground surface.) This approach allowed for a proper derivation of footprint positions and areas, as well as incidence angle ranges. The frequency averaging technique was used to reduce the effects of fading on the σpq0 uncertainty. Absolute calibration of the scatterometer was achieved with measurements of a rectangular metal plate and rotated dihedral metal reflectors as reference targets. In the retrieved time series of σpq0 for L-band (1.5–1.75 GHz), S-band (2.5–3.0 GHz), C-band (4.5–5.0 GHz), and X-band (9.0–10.0 GHz), we observed characteristic changes or features that can be attributed to seasonal or diurnal changes in the soil: for example a fully frozen top soil, diurnal freeze–thaw changes in the top soil, emerging vegetation in spring, and drying of soil. Our preliminary analysis of the collected σpq0 time-series dataset demonstrates that it contains valuable information on water and energy exchange directly below the air–soil interface – information which is difficult to quantify, at that particular position, with in situ measurement techniques alone. Availability of backscattering data for multiple frequency bands (raw radar return and retrieved σpq0) allows for studying scattering effects at different depths within the soil and vegetation canopy during the spring and summer periods. Hence further investigation of this scatterometer dataset provides an opportunity to gain new insights in hydrometeorological processes, such as freezing and thawing, and how these can be monitored with multi-frequency scatterometer observations. The dataset is available via https://doi.org/10.17026/dans-zfb-qegy (Hofste et al., 2021). Software code for processing the data and retrieving σpq0 via the method presented in this paper can be found under https://doi.org/10.17026/dans-xyf-fmkk (Hofste, 2021).

Fluorine pollution has become one of the key issues of water pollution, and the adsorption materials for efficient removal of fluorine ions have attracted much attention. It is rarely reported that the self-synthesized biomass materials were functionalized by the β-CD@Ce(NO)

An unexplored aspect of L-band microwave emission is the impact of soil moisture and soil temperature (SMST) profile dynamics on diurnal brightness temperature ( $T_{\mathrm {B}}$ ) signatures of frozen soil. This study investigates this effect by comparing the $T_{\mathrm {B}}$ simulations of layered ( $T_{\mathrm {B,l}}$ ) and uniform ( $T_{\mathrm {B,u}}$ ) soils using a newly developed integrated land emission model. The multilayer Wilheit model and the single-layer Fresnel model are adopted to compute the smooth soil reflectivity for the layered and uniform soils, respectively. A four-phase dielectric mixing model is used to calculate the soil permittivity ( $\varepsilon _{s}$ ). A data set of concurrent ELBARA-III $T_{\mathrm {B}}$ and SMST profile measurements performed in a seasonally frozen Tibetan meadow ecosystem is used for the analysis. The simulated $T_{\mathrm {B,l}}$ considering SMST profile information captures well the ELBARA-III measurements with low biases (≤6 K) and high correlations ( $R^{2}\ge0.88$ ). $T_{\mathrm {B,u}}$ produced based on the Fresnel model using the soil moisture of 2.5 cm is more consistent with the $T_{\mathrm {B,l}}$ . The sensitivity test of averaging SMST profile below 2.5 cm leads to maximum differences of 2 K in $T_{\mathrm {B,l}}$ simulations, indicating that the $T_{\mathrm {B}}$ variations are primary dominated by the SMST dynamics at the surface layer. A sensitivity test of the Wilheit model to different $\varepsilon _{s}$ parameterizations shows that the dielectric model of Zhang et al. is comparable to the four-phase dielectric model in simulating $T_{\mathrm {B,l}}$ , while the Mironov et al. ’s model demonstrates larger biases for frozen soil with, on average, 2.2% clay content, 49.7% sand content, and a bulk density of 1 $\text{g}\cdot $ cm−3.

Considerable progress has been made in understanding the variation rules of the freezing/thawing period and soil water-heat exchange. With the use of meteorological and soil observation data, this study highlighted the importance of vegetation cover and soil moisture for the beginning of the freezing/thawing period, and an improved calculation equation of the soil moisture content was presented, which could be used to simulate the variation in soil moisture during the freezing/thawing period. Our analyses showed that the temperature changes at the beginning of the soil freezing month (December) and the soil thawing month (February) were significantly different from 2009 to 2018. The rate of air temperature increase in December reached 0.38 °C/a. However, the air temperature in February changed little. As a result, the beginning of the soil freezing period was clearly lagged, while the beginning of the soil thawing period fluctuated little. The total soil thawing time increased by 25 days over 10 years. Furthermore, it was shown that the surface vegetation cover and soil moisture affected the beginning of the freezing/thawing time. In general, the soil freezing/thawing state at sites with low vegetation cover and soil moisture content was more likely to change. To further study the freezing/thawing mechanism, the relationship between the soil temperature and soil moisture during the freezing/thawing period was expressed as a fitting function of the relationship between soil water and heat. It was shown that the relationship between the soil moisture and soil temperature followed the new fitting function in both warm and cold years.

We report a unique multiyear L-band microwave radiometry dataset collected at the Maqu site on the eastern Tibetan Plateau and demonstrate its utilities in advancing our understandings of microwave observations of land surface processes. The presented dataset contains measurements of L-band brightness temperature by an ELBARA-III microwave radiometer in horizontal and vertical polarization, profile soil moisture and soil temperature, turbulent heat fluxes, and meteorological data from the beginning of 2016 till August 2019, while the experiment is still continuing. Auxiliary vegetation and soil texture information collected in dedicated campaigns are also reported. This dataset can be used to validate the Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) satellite based observations and retrievals, verify radiative transfer model assumptions and validate land surface model and reanalysis outputs, retrieve soil properties, as well as to quantify land-atmosphere exchanges of energy, water and carbon and help to reduce discrepancies and uncertainties in current Earth System Models (ESM) parameterizations. Measurement cases in winter, pre-monsoon, monsoon and post-monsoon periods are presented., Measurement(s) microwave radiation • soil moisture • atmospheric wind • Solar Radiation • rain • soil • CO2/H2O flux • thermal radiation • temperature of soil Technology Type(s) Radiometry (Microwave) • Sensor Device • pyranometer • Gauge or Meter Device • particle size analyzer • pyrgeometer Sample Characteristic - Environment land Sample Characteristic - Location Tibetan Plateau Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12818261

The spatial variation of surface net radiation, soil heat flux, sensible heat flux, and latent heat flux at different times of the day over the northern Tibetan Plateau were estimated using the Surface Energy Balance System algorithm, data from the FY-2G geostationary meteorological satellite, and microwave data from the FY-3C polar-orbiting meteorological satellite. In addition, the evaporative fraction was analyzed, and the total evapotranspiration (ET) was obtained by the effective evaporative fraction to avoid the error from accumulation. The hourly change of latent heat flux presented a sound unimodal diurnal variation. The results showed the regional ET ranged between 2.0 and 4.0 mm over the Source Region of the Yellow River. The conditional expectations of surface energy components during the experimental period of the study area were statistically analyzed, and the correspondence between different surface temperatures and the effective energy distribution was examined. The effective energy distribution of the surface changed significantly with the increase in temperature; in particular, when the surface temperature exceeded 290 K, the effective energy was mainly used for surface ET. The aim of this study was to avoid the use of surface meteorological observations that are not readily available over large areas, and the findings lay a foundation for the commercialization of land surface evapotranspiration.

This letter presents the results evaluating retrievals of liquid water content ( $\theta _{\mathrm {liq}}$ ) performed with a zero-order radiative transfer ( $\tau $ – $\omega$ ) model under frozen and thawed soil conditions from Soil Moisture Active Passive (SMAP) and ELBARA-III brightness temperature ( $T_{\mathrm {B}}^{p}$ ) measurements collected over a Tibetan meadow ecosystem. A good agreement is found between time series of the SMAP and ELBARA-III measured $T_{\mathrm {B}}^{p}$ resulting in a Pearson product-moment coefficient ( $R$ ) larger than 0.87. Differences noted between the two data sets can be associated with discrepancies in $\theta _{\mathrm {liq}}$ measured in the specific footprints, whereby the SMAP measurements are best explained by the in situ $\theta _{\mathrm {liq}}$ . Furthermore, the in situ $\theta _{\mathrm {liq}}$ has a better agreement with the horizontally polarized SMAP and ELBARA-III measurements ( $T_{\mathrm {B}}^{\mathrm {H}}$ ) in the cold season, whereas the vertically polarized measurements ( $T_{\mathrm {B}}^{\mathrm {V}}$ ) are better correlated with $\theta _{\mathrm {liq}}$ in the warm season. With the implementation of new vegetation and surface roughness parameterizations for the $\tau $ – $\omega $ model, the dynamics of in situ $\theta _{\mathrm {liq}}$ is better reproduced by corresponding retrievals for both frozen and thawed soil conditions, leading to the reduction in the unbiased root-mean-square error (ubRMSE) by more than 31% in comparison with these retrievals using SMAP default parameterizations. Notably, the single-channel algorithm configured with the new parameterizations using SMAP $T_{\mathrm {B}}^{\mathrm {V}}$ measured during the ascending overpass provides the best $\theta _{\mathrm {liq}}$ retrievals with a ubRMSE of 0.035 $\text{m}^{3}\cdot \text{m}^{-3}$ that is well within the SMAP mission requirements.

The Ramsar Convention on Wetlands is an international framework through which countries identify and protect important wetlands. Yet Ramsar wetlands are under substantial anthropogenic pressure worldwide, and tracking ecological change relies on multitemporal data sets. Here, we evaluated the spatial extent, temporal change, and anthropogenic threat to Ramsar wetlands at a national scale across China to determine whether their management is currently sustainable. We analyzed Landsat data to examine wetland dynamics and anthropogenic threats at the 57 Ramsar wetlands in China between 1980 and 2018. Results reveal that Ramsar sites play important roles in preventing wetland loss compared to the dramatic decline of wetlands in the surrounding areas. However, there are declines in wetland area at 18 Ramsar sites. Among those, six lost a wetland area greater than 100 km 2 , primarily caused by agricultural activities. Consistent expansion of anthropogenic land covers occurred within 43 (75%) Ramsar sites, and anthropogenic threats from land cover change were particularly notable in eastern China. Aquaculture pond expansion and Spartina alterniflora invasion were prominent threats to coastal Ramsar wetlands. The observations within China’s Ramsar sites, which in management regulations have higher levels of protection than other wetlands, can help track progress towards achieving United Nations Sustainable Development Goals (SDGs). The study findings suggest that further and timely actions are required to control the loss and degradation of wetland ecosystems.

Topsoil structures and inhomogeneous distribution of moisture in the soil volume will induce dielectric discontinuities from air to bulk soil, which in turn may induce multiple and volume scattering and affect the microwave surface emission. In situ ELBARA-III L-band radiometer observations of brightness temperature T B p ( p =H or V polarization) at the Maqu site on the Eastern Tibetan Plateau are exploited to understand the effect of surface roughness on coherent and incoherent emission processes. Assisted with in situ soil moisture (SM) and temperature profile measurements, this study develops an air-to-soil transition (ATS) model that incorporates the dielectric roughness (i.e., resulted from fine-scale topsoil structures and the soil volume) characterized by SM and geometric roughness effects, and demonstrates the necessity of the ATS model for modelling L-band T B p . The Wilheit (1978) coherent and Lv et al. (2014) incoherent models are compared for determining the dielectric constant of bulk soil in the ATS zone and for calculating soil effective temperature T eff . The Tor Vergata discrete scattering model (TVG) integrated with the advanced integral equation model (AIEM) is used as the baseline model configuration for simulating L-band T B p . Whereafter, the ATS model is integrated with the foregoing model for assessing its performance. Results show the ATS-based models reduce the underestimation of T B p (≈20-50 K) by the baseline simulations. Being dynamic in nature, the proposed dielectric roughness parameterization in the ATS model significantly improves the ability in interpreting T B p dynamics, which is important for improving SM retrieval at the global scale.

The variation trends of sensible heat (SH) and latent heat (LH) flux over the alpine wetlands in the source region of the Yellow River (SRYR) have been altered in the past 30 years. The variations in the surface heat source and its influence on the plateau summer monsoon have become attractive and important. The Community Land Model version 4.5 (CLM4.5), driven by the forcing data from CRUNCEP, was used to simulate the spatio-temporal variation characteristics of the SH and LH from 1980 to 2010 over the SRYR. The simulated SH and LH are compared to the situ measurements of the Maduo climatic monitoring station from the Northwest Institute of Eco-Environment and Resources. In addition, the relationships between the SH, LH and plateau summer monsoon have also been analysed. The results show that the seasonal mean SH reaches its maximum in spring and its minimum in winter. For the annual SH, there is an increasing trend in the early period and then a decreasing trend, while the variation trends of the LH are opposite to those of the SH flux. In addition, the LH transfer in summer reaches a maximum; the SH flux in the northern SRYR was higher in spring and summer. The SH of the two lakes, Lake Gyaring and Lake Ngoring, are significantly smaller than those of the surrounding areas. For the spatial distributions of the annual mean flux, the SH flux presented larger values over the central SRYR, while it presented smaller values in the southern areas. The LH shows an increasing trend from the northwest to the southeast of the SRYR. Meanwhile, the LH transport over the two lakes is notably higher than those of the surrounding areas. The time series of SH amplitude shows that it changes every 6–10 a. The SH amplitude is a mostly positive anomaly in the spatial distribution of the first pattern. EOF2 shows a high west of 101°E and a low centre east of 101°E; the relationship between the SH in spring and the different plateau summer monsoon indices are negatively correlated over SRYR. The negative correlations between the SH flux and ZPMI, DPMI, and QPMI are more remarkable in the northeast of the region.

In this paper, the ground observations were compared to the ERA-Interim, NCEP-DOE AMIP-II Reanalysis, MODIS ET product, and emerging offline SEBS ET data sets in the Yellow River source region of the Tibet Plateau. In general, the slopes of linear least squares exhibit differences, with ERA-Interim, NCEP–DOE, MOD16, and SEBS slopes of 0.88 ± 0.05, 0.64 ± 0.07, 0.66 ± 0.17, and 1.24 ± 0.97 respectively. ERA-Interim was found superior with ground observations to others; therefore, it provided a good representation of the study area. Based on the ERA-Interim ET product, the Sen's slope estimator and the Mann–Kendall (MK) test were applied to quantify the significance of the shifts in trends, while the moving t-test and MK test characterized abrupt changes. The results show that the Yellow River source region experienced a statistical increase in evapotranspiration (ET) in the northern part and a decrease in the southern part of the region from 1979 to 2014 at rates of approximately 1.65 and −0.50 mm/yr, respectively. The shift in the annual ET trend was more pronounced, and abrupt changes were detected in the 1980s. Precipitation was the most dominant factor affecting ET variation, whereas surface temperature was the least influential.

Soil freeze–thaw transition monitoring is essential for quantifying climate change and hydrologic dynamics over cold regions, for instance, the Third Pole. We investigate the L-band (1.4 GHz) microwave emission characteristics of soil freeze–thaw cycle via analysis of tower-based brightness temperature ( $T_{{{{\mathrm {B}}}}}^{p}$ ) measurements in combination with simulations performed by a model of soil microwave emission considering vertical variations of permittivity and temperature. Vegetation effects are modeled using Tor Vergata discrete emission model. The ELBARA-III radiometer is installed in a seasonally frozen Tibetan grassland site to measure diurnal cycles of L-band $T_{{{{\mathrm {B}}}}}^{p}$ every 30 min, and supporting micrometeorological as well as volumetric soil moisture ( $\theta $ ) and temperature profile measurements are also conducted. Soil freezing/thawing phases are clearly distinguished by using $T_{{{{\mathrm {B}}}}}^{p}$ measurements at two polarizations, and further analyses show that: 1) the four-phase dielectric mixing model is appropriate for estimating permittivity of frozen soil; 2) the soil effective temperature is well comparable with the temperature at 25 cm depth when soil liquid water is freezing, while it is closer to the one measured at 5 cm when soil ice is thawing; and 3) the impact on $T_{{{{\mathrm {B}}}}}^{p}$ caused by diurnal changes of ground permittivity is dominating the impact of changing ground temperature. Moreover, the simulations performed with the integrated Tor Vergata emission model and Noah land surface model indicate that the $T_{{{{\mathrm {B}}}}}^{p}$ signatures of diurnal soil freeze–thaw cycle is more sensitive to the liquid water content of the soil surface layer than the in situ measurements taken at 5 cm depth.

This study uses the brightness temperature at the given microwave frequency (18.7 GHz) from the Microwave Radiation Imager (MWRI) on-board the Fengyun-3B (FY-3B) satellite to improve the τ-ω model by considering the radiative contribution from waterbody in the pixels over the wetland of the Yellow River source region, China. In order to retrieve vegetation optical depth (VOD), a dual-polarization slope parameter is defined to express the surface emissivity in the τ-ω model as the sum of soil emissivity and waterbody emissivity. In the regions with no waterbody, the original τ-ω model without considering waterbody impact is used to derive VOD. With use of the field observed vegetation water content (VWC) in the source region of the Yellow River during the summer of 2012, a regression relationship between VOD and VWC is established and then the vegetation parameter b is estimated. The relationship is employed to derive the spatial VWC during the entire vegetation growing period. The VOD retrieved is invalid and failed in some part of the study area by using the previous τ-ω model, while the results from the improved τ-ω model indicate that the VOD is in the range of 0.20 to 1.20 and the VWC is in the range of 0.20kg/m2 to 1.40kg/m2 in the entire source region of the Yellow River in 2012. Both VOD and VWC exhibit a pattern of low values in the west part and high values in the east part. The largest regional variations appear along the Yellow River. The comparison between the remote-sensing-estimated VWC and the ground-measured VWC gives the root mean square error of 0.12kg/m2. These assessments reveal that with considering the fractional seasonal wetlands in the source region of the Yellow River, the microwave remote sensing measurements from the FY-3B MWRI can be successfully used to retrieve the VWC in the source region of the Yellow River.

Knowing the exact sampling depth of microwave radiometry is essential for quantifying the performance and appreciation of the applicability of satellite soil moisture products. We investigate in this study the sampling depth (δ SM ) of the L-band microwave emission under frozen and thawed soil conditions on the Tibetan Plateau. Two years of diurnal brightness temperature (T B p ) measurements at a time interval of 30 min are collected by the ELBARA-III radiometer deployed at a Tibetan meadow site. Vertical profiles of soil temperature and volumetric liquid water content (θ liq ) are measured simultaneously at soil depths up to 1 m below the surface. The impact of the θ liq measured at different depths on the microwave emission simulations is assessed using the τ-ω emission model, whereby the permittivity of frozen and thawed soil is estimated by the four-phase dielectric mixing model. It is found that: 1) the sampling depth for the effective temperature depends on the magnitude of θ liq , and is estimated to be, on average, about 50 and 15 cm for the cold dry and wet warm period, respectively, because of the seasonality in θ liq ; 2) the δ SM is determined at 2.5 cm for both frozen and thawed soil conditions during both cold and warm periods, which is shallower than the commonly used θ liq measurement depth (i.e. 5 cm) adopted for the in-situ monitoring networks across the globe; 3) the T B p simulations performed with the θ liq measurements taken at the estimated δ SM of 2.5 cm result in lower unbiased root mean squared errors, about 14% (3.16 K) and 22% (3.36 K) for the horizontal and vertical polarizations respectively, in comparison to the simulations with the θ liq measurements taken from 5 cm soil depth; and 4) the θ liq retrieved with the single channel algorithm from the ELBARA-III measured vertically polarized T B p are in better agreement with the θ liq measured at 2.5 cm than the one measured at 5 cm. These findings are crucial for developing strategies for the calibration/validation as well as the application of satellite based soil moisture products relying on the L-band radiometry.

The brightness temperature (T B p) observed by the Soil Moisture Active Passive (SMAP) satellite mission is significantly affected by the soil permittivity (ε s), surface roughness and vegetation opacity (τ p). This study assesses the impact of these factors on simulating the SMAP horizontally (p = H) and vertically (p = V) polarized T B p measurements and retrieving the liquid soil water content (θ liq) for both frozen and thawed soils in the typical Tibetan desert and meadow ecosystems. For this investigation, the zero-order approximation of the radiative transfer equations, i.e., τ-ω emission model, is configured with surface roughness and τ p parameterizations adopted by current SMAP soil moisture retrieval algorithms, and the ε s is computed with the four-phase dielectric mixing model that is applicable for both frozen and thawed soils. For the Tibetan desert site, the τ-ω emission model with above configurations underestimates year-round the SMAP T B H measurements (bias > 20 K), while T B V are underestimated during the cold season. Implementation of a new surface roughness parameterization reduces the T B H underestimation, and the improved T B p simulations lead to better θ liq retrievals produced by the single channel algorithm (SCA) using the T B V as well as T B H measurements. The remaining T B H and T B V underestimations are removed by further adopting a new ε s parameterization. For the Tibetan meadow site, the τ-ω emission model overestimates both T B H and T B V during the warm season and underestimates T B H during the cold season when the vegetation is sparse. Implementation of the new surface roughness parameterization reduces the T B H underestimation, and further the T B p overestimation is mitigated by adopting a new τ p parameterization derived from a discrete radiative transfer model previously developed and tested for the same site. The in-situ measured θ liq dynamics are better captured by corresponding retrievals for both frozen and thawed soils with implementation of the new surface roughness and τ p parameterizations, which reduces the unbiased RMSEs by more than 40%. The parameterizations developed in this study are useful to provide consistent and reasonable T B p simulations and θ liq retrievals over the Tibetan Plateau for both frozen and thawed soils based on both SMAP T B H and T B V measurements.

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 (σ°) 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.