Conference Agenda

Vegetation and soil moisture are key parameters in the studies of global water and carbon cycles. In this study, based on the commonly used zero-order radiative transfer model ( model), a two-step approach for retrieving vegetation optical depth (VOD) and soil moisture using only SMOS H-polarized multi-angular measurements was presented. At a first step, VOD is estimated by minimizing the soil signal and separating the vegetation signal from the multi-angular brightness temperature. In the retrieval, the angular feature of soil emission is used and the VOD is retrieved directly from the refined H-polarized multi-angular brightness temperature without any field correction or auxiliary soil or vegetation data. This retrieved algorithm is first validated by theoretical modeling and experimental data. The results demonstrate that VOD can be reliably estimated using this algorithm. The retrieved VOD is then compared with aboveground biomass, which shows strong correlation. Global mean VOD for the years of 2010 to 2011 generally shows a clear global pattern and corresponds well to the land cover types. The VOD of nine representative regions that are homogeneously covered with different vegetation types is compared with Normalized Difference Vegetation Index (NDVI). The results indicate that the VOD can generally reveal vegetation seasonal changes and can provide unique information for vegetation monitoring. At a second step, after estimating VOD, soil moisture can be retrieved based on model using H-polarized multiangular brightness temperature. By analyzing a simulated database using the advanced integral equation model (AIEM), an effective surface roughness parameter that considers the influence of rms height, correlation length and correlation function shape on surface reflectivity was presented. Using this effective surface roughness parameter, a new parameterized surface reflectivity model is based on a simple-empirical model, the Hp model, is developed. Comparison with AIEM simulations over a wide range of soil conditions indecates a good performance of this model. This approach is then applied on SMOS data, retrieved soil moisture in Africa exhibitus reasonable patterns and temporal changes. Validation using in situ soil moisture from two soil moisture monitoring networks of Yanco Region and Little Washita watershed over 2010-2011 indicates that this approach performs well in surface soil moisture retrieval. Retrieved soil moisture agrees well with the in situ measurements with the RMSE of about 0.04 m³/m³.

Soil Moisture Content (SMC) is a key parameter in the study of agriculture and the global water cycle. In recent years, with the development of Global Navigation Satellite System, a new SMC remote sensing technique called GNSS-Interferometry and Reflectometry (GNSS-IR) was proposed by K. M. Larson et al. Compared with traditional remote sensing technique, it can provide retrievals at intermediate spatial scales with high time resolution, and is easier in its operation and management.

The GNSS-IR technique utilizes the composite signals formed by the interference effect occurred between the direct and the ground reflected navigation signals. These signals, which contain the physical information of the soil, are routinely recorded in a normal geodetic receiver in the form of Signal-to-Noise Ratio (SNR) data. Part of the efforts made in this field are to model SNR more accurately and extract SMC-related metrics from the SNR data. Recent contributions made by our group were to propose a semi-empirical SNR model which aimed at reconstructing the direct and reflected signal from SNR data and at the same time extracting frequency and phase information that is affected by soil moisture as proposed by K. M. Larson et al. This model worked as a curve-fitting model, and it was built through approximating the direct and reflected signal by a second-order and fourth-order polynomial, respectively, based on the well-established SNR model. Compared with other models (K. M. Larson et al. 2008, T. Yang et al. 2017), this model can improve the Quality of Fit (QoF) with little prior knowledge needed and can allow soil permittivity to be extracted from the reconstructed signals.

In this oral presentation, we will showed how this model was validated through simulation and experimental data processing. The data we used were collected by previous researchers at Lamasquère, France. Main results and finding are as follows:

Firstly, the QoF obtained using this model was improved by around 40%. It could ensure good fitting quality even in the case of irregular SNR variation. This advantage also results in better estimation of the frequency and phase information. However, we found that the improvement on phase estimation could be neglected.

Secondly, SMC could be retrieved from reconstructed signals. The results were satisfactory when the satellite elevation angle is between 5 degrees and 15 degrees. Additionally, the soil moisture calculated from the reconstructed signals was about 15% closer in relation to the ground truth measurements.

Finally, some phenomena were discovered regarding retrieval ambiguity and error sensitivity. These will also be stated and discussed in this oral presentation.

Microwave (active and passive) and optical sensors are and will be deployed at an alpine meadow test site near Maqu city (China) on the Tibetan Plateau to study soil-vegetation-atmosphere processes and to validate physically based earth observation models used for retrievals from satellite data. Presented will be details and first results of a broad band full polarimetric scatterometer. The purpose of the scatterometer is to retrieve soil moisture content (SMC) and basic vegetation properties (vegetation water content, biomass, leaf area index) of the alpine meadow. This retrieval is done through inversion of backscattering models that link the measured backscattering coefficient σ⁰ to the SMC and aforementioned vegetation properties.

The scatterometer consists of a vector network analyser (VNA) connected to two dual polarization broadband antennas elevated 5 m above the surface. The radar return for co- and cross- polarization is measured over a 1 – 10 GHz frequency range (3 MHz resolution). The scatterometer calibration and validation was performed by means of a rectangular metal plate and metal dihedral reflector. For the co-polarization channels the measured radar cross section of the dihedral reflector matched a theoretical model within ±1 dB for 3 – 10 GHz. The calculation of σ⁰ from the measured radar return for the given site geometry and the frequency dependent radiation patterns will be explained as well.

Two experiments were performed. With the first experiment the antenna azimuth- and zenith angles were varied so that σ⁰ was measured over different parts of the surface under various angles of incidence θ_i. The azimuth range was -20° to 20° with 5° increments and the antenna zenith angles were varied such that θ_i varied from 35° to 70° with 5° increments. For the second experiment the orientation of the antennas were fixed and σ⁰ was recorded every hour during a long period (August 2017 – February 2018).

Analysis of the results from the first experiment will be presented to demonstrate the electromagnetic homogeneity of the ground surface. Since for the second experiment the antenna orientations were fixed it was not possible to measure multiple non-overlapping spatial samples of the surface. Therefore, to decrease the inherent uncertainty of the measured σ⁰ due to fading, frequency averaging will be applied to the data of the second experiment. A first glance at the results of the second experiment shows that during a 12 day period in August 2017 σ⁰ changed in parallel to in-situ measured SMC at 5 cm depth. We observe a decay of the σ⁰ during dry days and a sudden increase of σ⁰ after rainfall. The temporal behaviour of σ⁰ holds for most of the frequencies with all polarization channels.

TheOcean and Land Color Imager (OLCI) on the Sentinel-3A satellite, which was launched by the European Space Agency in 2016, is a new-generation water color sensor with a spatial resolution of 300 m and 21 bands in the range of 400–1020 nm. The OLCI is important to the expansion of remote sensing monitoring of inland waters using water color satellite data. In this study, we developed a dual band ratio algorithm for the downwelling diffuse attenuation coefficient at 490 nm (K_d(490)) for the waters of Lake Taihu, a large shallow lake in China, based on data measured during seven surveys conducted between 2008 and 2017 in combination with Sentinel-3A-OLCI data. The results show that: (1) Compared to the available K_d(490) estimation algorithms, the dual band ratio (681 nm/560 nm and 754 nm/560 nm) algorithm developed in this study had a higher estimation accuracy (N = 26, coefficient of determination (R²) = 0.81, root-mean-square error (RMSE) = 0.99 m⁻¹ and mean absolute percentage error (MAPE) = 19.55%) and validation accuracy (N = 14, R² = 0.83, RMSE = 1.06 m⁻¹ and MAPE = 27.30%), making it more suitable for turbid inland waters; (2) A comparison of the OLCI K_d(490) product and a similar Moderate Resolution Imaging Spectroradiometer (MODIS) product reveals a high consistency between the OLCI and MODIS products in terms of the spatial distribution of K_d(490). However, the OLCI product has a smoother spatial distribution and finer textural characteristics than the MODIS product and contains notably higher-quality data; (3) The K_d(490) values for Lake Taihu exhibit notable spatial and temporal variations. K_d(490) is higher in seasons with relatively high wind speeds and in open waters that are prone to wind- and wave-induced sediment resuspension. Finally, the Sentinel-3A-OLCI has a higher spatial resolution and is equipped with a relatively wide dynamic range of spectral bands suitable for inland waters. The Sentinel-3B satellite will be launched soon and, together with the Sentinel-3A satellite, will form a two-satellite network with the ability to make observations twice every three days. This satellite network will have a wider range of application and play an important role in the monitoring of inland waters with complex optical properties.

The identification of spatial and temporal dynamics of phytoplankton and macrophytes is crucial for deepening the knowledge of lake primary productivity and shifts in trophic status of inland water bodies. Earth Observation (EO) can provide sensitive information on both groups of primary producers, but their possible coexistence within the same site is often not taken into account by satellite-based analyses. Indeed, macrophyte and phytoplankton coexistence is not rare event, especially in shallow eutrophic lakes subject to cyanobacteria blooms, and common methods based on optical VNIR spectral response features for estimating water constituents often fail in distinguishing dense surface accumulation of cyanobacteria forming at peak of bloom events with floating and emergent macrophyte cover. Few authors have tackled this issue in scientific literature, the most effective approach to our knowledge being the one proposed by Oyama et al. (2015; Remote Sensing of Environment, 157: 35-47), based on the exploitation of SWIR range reflectance. On this topic, Bresciani et al. (2014; Remote Sensing of Environment, 146: 124-135) have demonstrated the potential of combined optical and SAR data in delivering accurate information on algae blooms and scum events in Curonian lagoon (Lithuania).

In this work, we take advantage of new generation EO sensors (i.e. ESA-Copernicus Sentinel-1 and -2) for investigating the capabilities of optical (broadband multi-spectral) and SAR (C-band) data integration in providing an effective method for distinguishing cyanobacteria scum and floating macrophytes in Lake Taihu (Jiangsu, China). Matchup pairs of Sentinel-2 and Sentinel-1 data acquired with less than 5 day difference have been pre-processed to derive surface reflectance and backscattering coefficient (sigma0), respectively. Statistics of spectral reflectance and Water Adjusted Vegetation Index (WAVI; Villa et al., 2014; Int. J. Appl. Earth. Obs. Geoinf., 30: 113-127) derived from Sentinel-2 data, as well as sigma0 in VV and VH polarization combinations derived from Sentinel-1 data, have been calculated and used to assess the separability of cyanobacteria scum and floating macrophyte pixels response. Finally, a rule-based framework has been designed, parametrized and applied to Sentinel-1 and -2 data to produce maps of algae scum and macrophytes on Lake Taihu in different times of the primary producers cycle, spanning from April to October.

In China, freshwater is an increasingly scarce resource. Study location Dongting Lake is China’s second largest freshwater lake in the middle reaches of Yangtze River catchment. Its wetlands deliver important ecosystem functions such as freshwater supply, water purification, flood and climate regulation to name only a few. The development of comprehensive water resource management and nature conservation strategies requires detailed mapping and monitoring of inland waters. The generation of such information requires either large human resources for conventional ground surveying or expensive data. In addition to costly methods, the monitoring of large wetlands such as the Dongting Lake study site with a water surface of up to 3.200 km² is difficult due to its inaccessibility during annual flood period.

Remote sensing offers a mature and comprehensive tool to solve this task with large area coverage at very low costs. Until today, in addition to satellite data with lower temporal resolution such as Envisat ASAR or Landsat, daily MODIS satellite data are a frequently selected source for capturing lake dynamics with medium spatial resolution of 250 m up to 1 km. Satellite data from the new European Sentinel fleet has been available since 2014 and provides high-resolution information free of costs. In this study we present the application of Sentinel-1 time series data for spatio-temporal high-resolution wetland mapping. New is the level of detail that can be achieved with Sentinel-1 data. Potential and limitations are analyzed and mid-term results presented.

In recent years, the climate change and human activities have a great influence on lake environments and ecosystem^[1]. As the second largest freshwater lake of Yunnan Province, Erhai Lake, is the indispensable drinking water source in Dali. However, due to the increasing human activities, Erhai lake have suffered a great deal of environmental stressors, such as eutrophication, heavy metal pollution, etc^[2]. Water quality deterioration and eutrophication led to the occurrence of algal blooms and affected the normal ecological function of lakes^[3]. Thus, the primary task for protecting Erhai Lake is monitoring and risk pre-warning of blooms. When algal bloom occurs, the content of chlorophyll a in the water increases, resulting in significant differences in the spectral characteristics between the bloom and non-bloom waters, so that cyanobacterial bloom can be detected by remote sensing.

The launch of MultiSpectral Instrument (MSI) orbited on Sentinel-2A (S2) and Ocean and Land Colour Instrument (OLCI) and Sea and Land Surface Temperature Radiometer (SLSTR) on board ESA Sentinel-3A (S3) opened a new world in water environmental remote sensing^[4]. Lacking of in situ data and complexity of air and water conditions are the challenges of validating and evaluating S2 and S3 products. It provides multispectral data at high, medium and low resolution to meet different purposes by combinating S2 and S3 missions.

The aims of the study are: 1) to find out how Senitnel 2 MSI contributes to the long-term monitoring of algal blooms in inland lakes, 2) to get distribution of algal bloom and water surface temperature (WST) in spatial and temporal scales, 3) to figure out how Sentinel 3 plays a role in inland water monitoring and the driving factors of algal bloom, with the combination of high resolution MSI images.

In this study, a total of 22 Sentinel-2A MSI images with 50% cloud cover combining with Landsat OLI images (a total of 13 images) were used to monitoring algal blooms in Erhai Lake during November 2016 and December 2017. The VB-FAH (Virtual-Baseline Floating microalgae Height) index was used to identify and extract water bloom by using Sentinel-2A MSI and Landsat OLI sensors. Besides, 84 images of Sentinel-3 SLSTR level-1 products (from October 2016 to December 2017) and MODIS Terra Global 1Km Grid (short as MOD11A1, from January 2003 to December 2016) were used to analyze the relationship between WST and algal bloom. The SLSTR WST Products were processed by using split-window algorithm^[5].

Accompany with Landsat OLI and Sentinel-2A algal bloom maps, the processes of algal bloom development during October 2016 to December 2017 was presented. It’s apparently indicated that algal bloom was first observed in October 2016, located in the central of lake and then move to north Erhai Lake from October 2016 to the late spring of 2017. In order to describe the continuous process of algal bloom, the occurrence and duration of the algal bloom are set as follows: if the algal bloom is observed in two scenes within 3-5 days, and during this time the meteorological conditions are stable, then these two observation can be treat as one observation of bloom, and the time of first scene is recorded as the start of this algal bloom. Following the rules that mentioned above, with the aid of Sentinel 2 MSI monitoring on 22 and 24 November ,the three observations of algal bloom in November 2016 (11-20, 11-23, 11-27, detected by Landsat ) should be synthesized as one large scale bloom, which means Sentinel 2 MSI has a greater contribution to the long-term monitoring of algal blooms in Erhai lake^[6,7].

To demonstrate the spatial variability of the SLSTR maps, WST in Erhai Lake present a typical seasonal changes with the lowest temperature apparent in December 2016 and the highest temperature apparent in April 2017. A south to north difference was observed in every climatological monthly mean WST maps. Water temperature in south lake is 0.03K lower than what in north lake for the total of 70 images. The year 2016 had a relatively cool October according to SLSTR L1B result, which is consistent with the metrological air temperature record by Chinese metrological centre.

The monthly average WST in 2016 and 2017 were calculated from the MOD11A and Sentinel 3. Comparing with the 14years average monthly WST from MOD11A during 2003-2017. The monthly average WST in Erhai in 2016 is 0.9-2.5°C higher than 14 years average value. In autumn and early winter of 2016, there was a wide range of algal bloom, indicating that the higher WST was a favorable factor for the propagation and eruption of algal bloom. Otherwise, in 2017, the monthly mean WST of SLSTR is 0.5-3.5°C higher than 14 years average WST of MOD11A (2003-2017), higher WST was found in January and February when algal bloom occurred.

SLSTR can help finding relationship between algal bloom and water surface temperature. Higher water surface temperature is incentive to the eruption of algal bloom.

Wetlands are an important natural resource that requires monitoring. Water area is an important factor to the wetland monitoring. Methods of water extraction from optical images were very mature, such as NDWI, MNDWI and etc. But in rainy and cloudy area, there are always no enough optical images could be used while the underlying surface keeps in a highly dynamic changing speed. Synthetic Aperture Radar(SAR) data are helpful in these conditions and they could be used to map and monitor changes in surface water extent and flooded vegetation areas. These two factors are very helpful for the wetland management to understand the wetland vegetation distributions and changes. We reviewed a few techniques to extract water from optical and SAR images, including NDWI for the optical images and grey-level thresholding for SAR images and compared their differences in different seasons. Since the penetration character in SAR images, We compared the difference water extraction results from optical images and SAR images. And then, We used the polarimetric decompositions to map flooded vegetation to distinguish it from the surface water area. We used H/alpha composition method to detect the flooded vegetation area and found that it is useful to improve the accuracy of water area extraction from SAR images. We recommend that SAR data are very important to acquire the water area in the delta of wetland and differences from Optical and SAR images are very helpful to the wetland management to obtain the accurate water area data.

Global warming has increased the frequency of algal blooms in internal water bodies. The algal blooms are an unpleasant sight and hinder various recreational and economic. The increase in the anthropogenic load of nutrients (eutrophication) has led to an increase in the presence of toxic algae, the blue-green algae in the coastal and internal water bodies. A mature flowering of blue-green algae often emerges on top like a layer of foam containing high concentrations of toxins. Contact with these toxins poses a direct health risk for both humans and animals. Therefore, monitoring the concentration of algae and the occurrence of scum in lakes has become a topic of interest for management and science.

Optical remote sensing is a validated tool for sensing, monitoring and developing better understanding of the state of lakes. However, it is highly hindered by clouds. For regions with frequent cloud cover, this means loss of data, which derails the purpose of sensing. This makes difficult to spatially and temporally characterize scum area for a comprehensive ecological analysis. Combining data obtained using different types of sensor can be an option worth investigating, and a good candidate for this purpose is the synthetic aperture radar (SAR), due partly to its capacity to collect data independent of cloudy cover.

We use a synergistic approach involving optical and SAR images together with meteorological parameters to monitor algal cyanobacteria blooms over Tai Hu and Chaohu lakes and Curonian Lagoon. The satellite images are provided by the Sentinel 1, 2 and 3 satellites. Meteorological parameters come from in situ stations or from the European Centre for Medium-Range Weather Forecasts (ECMWF) database. With respect to optical data, the scum index was developed using ratio of TOA reflectance in NIR and RED bands exploiting the high difference in backscattering and absorption between water with and without scum. For S1 imagery, a polarimetric index is defined and results able to identify anomalies on the lakes surface. The use of Google Earth Engine helped with the images selection and the time series analysis of the indexes. A preliminary study suggests that this index combined with the knowledge of wheatear variables, such as wind speed and the 2 meters air temperature, can reliably detect the occurrences of algal blooms.

Biodiversity stakes within Yangtze watershed are very important at national level by also international ones. These very rich ecosystems, being key wintering areas for many waterfowl of SE Asia, are suffering from rapidly changing environments due to human activities. It’s crucial to understand what the key factors and their effects are. As data within large spatial and temporal scales are difficult to get, remote sensing and spatial analysis technology turns out to be a useful tool to access information. Works are on progress over Poyang Lake, in regards to vegetation recognition and dynamic particularly within the core of the Poyang Lake natural Reserve, but also over smaller and less known sensitive areas such as Wuchang and Shengjin lakes (Anhui Province).

Since its launch in 2015, the Sentinel-2 mission is capturing the world with an unprecedented combination of spatial and temporal resolutions, going from 10 to 60 m of spatial resolution and 5 days of revisit time at the equator, all in free access. The interval of spectral bands monitored goes from coastal blue at 443 nm to Short-Wave InfraRed (SWIR) at 2190 nm, divided in 13 bands. The mission is composed of 2 identical satellites, Sentinel-2A sent on June 2015, and Sentinel-2B sent on March 2017. Sentinel-2 allows a precise and systematic follow-up of hydrological systems regarding water surface area or vegetation coverage.

The water extents of Wuchang and Shengjin lakes have been extracted from Sentinel-2 time series, using all exploitable images since the beginning of the acquisitions in 2015. Being an optical sensor not all images are usable due to potential high cloud coverage. A total of 32 dates have been used and 10 Landsat 8 (Libra) have been added to try to reduce the temporal gaps in the Sentinel-2 acquisitions caused by cloudy conditions. The final time series have an average of 1 image every 22 days, going from the 20^th October of 2015 to the 7^th of April 2018. The number of available images is higher since March 2017, thanks to the launch of the Sentinel-2B satellite. Extractions were done using a SERTIT-ICube automatized routine based on a supervised Maximum Likelihood Classification, trained with Pekel water occurrence product. These extractions allow to recreate the dynamic of the two lakes and show the drought and wet periods. During the 3 years interval, the surface peaks on July 2016 for both lakes. The lowest level appears at two different dates for each lake; on January 2018 for Wuchang, on February 2017 for Shengjin. Wuchang Lake surface area appears to be more variable than Shengjin Lake, with many local maximum and minimum between the end of 2017 and April 2018.

In addition to Sentinel-2 and Landsat 8, SPOT images have been downloaded from the Theia-world website through the SPOT World Heritage program. The latter gives access to archive data from satellites SPOT 1-2-3-4-5 and extents the study duration span. A total of 19 images were either completely or partially available over Shengjin and Wuchang lakes; 2 SPOT-1, 2 SPOT-3, 13 SPOT-4 and 2 SPOT-5, from December 1987 to April 2009. The time between two images during this period is too large to capture the lakes dynamic but can be used to calculate a total water occurrence product.

In the case of Wuchang Lake, floating vegetation is a problem for automatic water surface extraction. The lake is covered by vegetation during long periods of time and the water below can’t be detected by automatic radiometric means. Nevertheless, Sentinel-2 stays a pertinent and powerful tool for hydrological monitoring of lakes confirming the expectation from the remote sensing wetland community before launch. The presence of IR and SWIR bands induces a strong discrimination between water and other classes, and the systematic acquisitions create dense time series, making analysis more consistent. It makes possible to sensor events occurring over short periods of time. These midterm results illustrate the pertinence and power of multi-source optical satellite data for environmental analysis and confirm the expectations in the Sentinel- 2 constellation.

Colored dissolved organic matter (CDOM), the key component in aquatic environment, plays an important role in biogeochemical processing. The optical characteristics of CDOM potentially permit remote sensing of CDOM. However, retrieval of CDOM for inland turbid water is challenging because of CDOM absorption at blue spectral range overlapped by the absorption caused by chlorophyll a and amounts of total suspended matter contained in turbid water. CDOM inversion algorithms developed and applied to specific regional locations may not be directly applicable for other water environment. Moreover, various CDOM sources present distinct CDOM absorption characteristics spatially and spectrally. In this study, in situ reflectance and water samples were used to develop models for estimating CDOM absorption in a complex freshwater environment in Poyang Lake, China. Poyang Lake is the largest fresh water lake in China. It is a complex flood-path lake with significant annual water level variations caused by hydrological conditions and monsoon climate. The lake also exerts an irreplaceable role for drinking water supply, flood control, waterway shipping and conservation of biological diversity. However, in recent years, the water environment of Poyang Lake has been affected by anthropogenic impacts such as sand mining and major hydrologic engineering. The in situ water reflectance spectra, CDOM absorption spectra and other water-color parameters from 92 samples collected in four representative study areas between 2015 and 2016 were analyzed. Band ratio models were established to estimate CDOM absorption coefficient at 355 nm [ag(355)] based on the correlation analysis between reflectance and ag(355). The results indicated that the band ratio models performed well for estimating ag(355) when the 92 samples were divided into two datasets with the threshold of concentration of total suspended matter (TSM) as 10 mg/L. The band ratios of R(689) / R(497) and R(767) / R(826) were selected to establish model for retrieval of ag(355) in clean water (TSM < 10 mg/L) and turbid water (TSM ≥ 10 mg/L), respectively. The determination coefficients (r2) of calibration models for clean and turbid water were 0.70 and 0.73, respectively. The percentage root-mean-square errors (%RSME) of validation models for clean and turbid water were 13.2% and 11.6%, respectively. The simulated Sentinel-2 and Landsat-8 bands based on reflectance spectra were used to examine potential capability for retrieving CDOM using these sensors. The results indicated that Sentinel-2 would perform better than Landsat-8 for estimating ag(355). The Sentinel-2 band ratio of B4 / B2 or B5 / B2 and B7 / B8 or B7 / B8A would be useful for retrieval CDOM in clean and in turbid water of Poyang Lake, respectively. The performance of the models for Sentinel-2 image acquired on July 26, 2016 was stable both in clean and turbid water. Further evaluate performance for extended temporal application is required in Poyang Lake. The findings from this study provide algorithms foundation for monitoring spatial and temporal dynamic of CDOM in Poyang Lake using remote sensing.

A watershed, regarded as the best unit for practicing hydrological cycle and water resource research, possesses all of the complexities of the land surface system. Thus, integrating multi-source observations, hydrological modeling into a model-data assimilation framework at watershed scale is the most comprehensive way to understand the complexities of process of hydrological cycle, and is of utmost significance to provide insight into water resource management. This study presents a comprehensive overview on the progress of observation, modeling and data assimilation of watershed scale hydrological cycle. Specifically, several key progresses have been observed at: 1) development of an integrated watershed system model and closure of hydrological cycle at watershed scale, 2) improvement data assimilation algorithm and development data assimilation system, and 3) development of key water cycle elements estimating algorithms and products.

To understand complex watershed systems and to support integrated river basin management, we proposed a new modeling framework to incorporate emerging knowledge into integrated models through data exchange interfaces [1]. The model is expected to represent the coevolution of the water-land-air-plant-human nexus in a watershed and provide capability of decision-making support and to provide an overarching framework for linking natural and social sciences. Based on the framework of the watershed system model, we analyzed the hydrological cycle in the Heihe River Basin [2]. The water budget was closed for different landscapes, river channel sections, and irrigation districts of the basin from 2001 to 2012.

We proposed soil moisture assimilation scheme that jointly assimilated the brightness temperature of Advanced Microwave Scanning Radiometer-Earth Observing System and Land Surface Temperature products of Moderate Resolution Imaging Spectroradiometer [3]. The data assimilation scheme could correct model bias by simultaneously updating model states and parameters with a dual ensemble Kalman filter. In addition, we developed a physically based hydrological data assimilation system using the gridded and parallelized Soil and Water Assessment Tool distributed hydrological model [4]. The system integrated remotely sensed and ground-based observational data with the Parallel Data Assimilation Framework. The system could accurately characterize watershed hydrological states and fluxes. As to the application of data assimilation to hydrological flux, significant progress has been obtained as well. For instance. Pan et al. [5] assimilated the two satellite precipitation products (The Tropical Rainfall Measuring Mission: TRMM and Fengyun-2D: FY-2D) into the weather research and forecasting model under framework of the 4D-Var data assimilation method in Heihe River Basin. The improved precipitation forecasting has been observed.

Remote sensing retrieval algorithms for key hydrological elements, such as soil moisture, evapotranspiration, have been witnessed progress. For instance, Li et al. [6] estimated continuous daily evapotranspiration at a 90-m spatial resolution using the Surface Energy Balance System (SEBS) by fusing high-temporal resolution Moderate Resolution Imaging Spectroradiometer and high spatial-resolution Advanced Space-borne Thermal Emission Reflectance Radiometer images. Ma et al. [7] proposed a probabilistic inversion algorithm for soil moisture estimation based on Bayes’ theorem and the Markov Chain Monte Carlo technique. They not only obtained highly accurate soil moisture estimation, but also quantified the uncertainties in the inversion algorithm.

Overall, significant progress has been made in the hydrological observation, modeling and data assimilation at watershed scale in recent year. We believe that more fruitful results would be expected in near future under these bases.

References

[1] X. Li, G. Cheng, H. Lin et al., “Watershed system model: the essentials to model complex human‐nature system at the river basin scale,” Journal of Geophysical Research Atmospheres, vol. 123, no. 6, pp. 3019-3034, 2018.

[2] X. Li, G. Cheng, Y. Ge et al., “Hydrological Cycle in the Heihe River Basin and Its Implication for Water Resource Management in Endorheic Basins,” Journal of Geophysical Research Atmospheres, vol. 123, no. 2, pp. 890-914, 2018.

[3] W. Chen, H. Shen, C. Huang et al., “Improving soil moisture estimation with a dual ensemble Kalman smoother by jointly assimilating AMSR-E brightness temperature and MODIS LST,” Remote Sensing, vol. 9, no. 3, pp. 273, 2017.

[4] Y. Zhang, J. Hou, J. Gu et al., “SWAT‐Based Hydrological Data Assimilation System (SWAT‐HDAS): Description and Case Application to River Basin‐Scale Hydrological Predictions,” Journal of Advances in Modeling Earth Systems, vol. 9, no. 8, 2017.

[5] X. D. Pan, X. Li, G. D. Cheng et al., “Effects of 4D-Var Data Assimilation Using Remote Sensing Precipitation Products in a WRF Model over the Complex Terrain of an Arid Region River Basin,” Remote Sensing, vol. 9, no. 9, pp. 963, 2017.

[6] Y. Li, C. Huang, J. Hou et al., “Mapping daily evapotranspiration based on spatiotemporal fusion of ASTER and MODIS images over irrigated agricultural areas in the Heihe River Basin, Northwest China,” Agricultural & Forest Meteorology, vol. 244, pp. 82-97, 2017.

[7] C. Ma, X. Li, C. Notarnicola et al., “Uncertainty Quantification of Soil Moisture Estimations Based on a Bayesian Probabilistic Inversion,” IEEE Transactions on Geoscience & Remote Sensing, vol. 55, no. 6, pp. 3194-3207, 2017.

The surface energy balance of glaciers and snowpack is the main driver of the mass balance. A detailed analysis of Landsat images of the entire Qinghai – Tibet Plateau over the period 1995 – 2015 has documented a large variability of glacier spectral reflectance and albedo in relation with surface materials. The area of debris-covered glaciers accounted for approximately 20% of the total glacial area, and slightly decreased between 1995 and 2015. The area of glaciers at elevation under 5800 m decreased significantly over 20 years. The number of small glaciers, i.e. < 1 km², decreased most, while the largest contribution to the reduction in glacial area was due to the larger glaciers, i.e. > 10 km². To understand how closely glacier melting is related to surface properties, we need to map changes in glacier volume at high spatial resolution. A few satellites acquire stereo – images at high spatial resolution, i.e. ALOS / PRISM and Zi Yuan-3/ TLC, but spatial and temporal coverage is far from satisfactory. We focused on two case – studies on the Zhadang and Parlong nr.4 glaciers, where concurrent ground measurements are available. Preliminary results show that melting rate of glaciers correlates with the albedo and surface temperature. Decrease in glacier thickness over multiple years was clearly related with the mean surface temperature over the same period of time. The quality and spatial resolution of ground measurements of mass balance in the Parlong glaciers gave the opportunity to evaluate the relationship between the mean surface temperature and changes in glacier thickness over the entire glacier. This analysis gave an estimate of the mean surface temperature at which glacier melting starts.

At the same time, glacier surface velocity has been estimated and mapped using high resolution images, i.e. Gao Fen – 1. High spatial resolution maps of surface velocity can be related to maps of albedo and surface temperature and of glacier melt (change in thickness) at comparable spatial resolution.

Atmospheric forcing of the surface energy balance in glacial and snow – covered areas is being characterized using WRF fields generated at multiple spatial resolutions by applying a nested implementation with the inner domain having a 500 m x 500 m grid size. The accuracy of air temperature and wind speed is being evaluated with ground measurements at the Parlong 4 glacier. Radiative interactions of the land surface, particularly the glacial and snow – covered areas, with clouds and aerosols are being evaluated under a new project.

Quantitative information on water losses is important to understanding the global terrestrial water cycle and land – atmosphere interactions. Following the former study of last year, the ETMonitor estimated global evapotrasnspiration in 2008-2013 with a spatial resolution of 1 km was carefully validated mainly based on ground observation from FLUXNET, spatial variaiton was also cross-compared with other available global evapotranspiration products. The estimated ET agreed well with the in situ observations at site scale, with overall high correlation, low bias, and low root mean square error. Meanwhile, the estimated ET variation could capture the expected overall global ET patterns, and its spatial and temporal patterns were consistent with the current available global ET products such as the upscaled ET dataset from FLUXNET observations and GLEAM ET product, but is superior by high spatial and temporal resolutions. The separation between plant transpiraiton and soil evaporation made by the ETMonitor was also validated based on ground observation based on isotope technique and showed overall good agreement between ETMonitor estimation and isotope observation in partitioning transpiration and evaporation. In details, the ratio of transpiration and evaporation to the total ET generally agreed well with the isotope observation in the growing season in 2012 in one of the ground site of HiWATE experiment, while relative large bias was found in the beginning of the growing season when the soild surface was covered by mulching film.

Precipitation was the major regional water source and precipitaion based indocators were widely adopted in drought monitoring. However, large differene could be found among different earth observation based precipiation products. We evaluated the accuracy of multiple satellite-based precipitation products including the tropical rainfall measuring mission multisatellite precipitation analysis (TMPA) (TMPA 3B42RT and TMPA 3B42 version 7) and the Climate Prediction Center MORPHing technique (CMORPH) (CMORPH RAW and CMORPH BLD version 1.0) datasets and evaluated the impact of the accuracy and temporal coverage of these data products on the reliability of the standardized precipitation index (SPI) estimates for drought monitoring. The satellite-based SPI was compared with the SPI estimate using in situ precipitation observations from 2221 meteorological observation sites across China from 1998 to 2014. The SPI values calculated from the products calibrated with rain gauge measurementswere generally more consistent with the SPI obtained with in situ measurements than those obtained using noncalibrated products. The short data record of satellite precipitation data products was not the primary source of large errors in the SPI estimates, suggesting that the SPI estimate using satellite precipitation data products can be applied to drought assessment and monitoring. The satellite-based SPI can capture typical drought events throughout China, with the limitation that it is based on precipitation only and that different durations of antecedent precipitation are only suitable for specific drought conditions.

The water reource of different basins in China was also obstaind based on ETMonitor estimated ET combing with CMORPH precipitation data. ETMonitor was applied to obtaind regional ET dataset in China and southeast Asia in 2001 -2015 focusing on the key study region, the estimation adopted the ESA-CCI (European Space Agency - Climate Change Initiative) soil moisture data product as one of the inputs. The estimated ET agreed well with flux tower based observations from AsiaFLUX and the estimated ET from water balance method in basin scale. The obtained precipitaiton - ET showed strong correlation with the statistical data of differnet basins from Chinese Water Resource Department, while relative large disagreement mainly occurred at the region with large ground water consumption. Both precipitation and ET presented increasing trends in China, and it generally resulted in a non-significant increasing of available water resource in China. It may benefit the overall water resource supply nowadays, however increasing wate shortage were aslo found in the major grain producing regions and dense population regions. The results were partly contributed to the National Remote Sensing Monitoring for Sustainable Devepoment Report in China (2017).

Evapotranspiration (ET) is a key terrestrial water cycle at the land-atmosphere interface, and the earth observation are expected to provide spatially and temporally continuous information on large scale ET variation. In currenty study, ETMonitor was applied to obtaind regional daily ET dataset in China and southeast Asia in 2001 -2015, and the estimation adopted the ESA-CCI (European Space Agency - Climate Change Initiative) soil moisture data product as one of the key inputs. To validate the estimated ET, in situ flux tower oberservations from AsiaFLUX datasets were first colleted. The quility of colleted latent heat flux at 30min inteval was carefully checked to obtain observed daily ET. Generally, high correlation coefficient was found escept in tropical humidity forest, where relative low correlation coefficient could be found mostly due to the unclear seasonal ET variation, while the low root mean squre error suggest the good agreement between our estimation and the flux tower observation. Meanwhile, the estimated ET was also compared with the water balance method estimated annual ET (ET_wb) at basin scale. ET_wb of the major basins in mainland of China was estimated as the the precipitation minus the sum of observed runoff and total water storage by GRACE. Their good agreement hilight the good potential of earth observation in basin water source evaluation. Furthermore, the spatial pattern of estimated ET was compared with other ET products, e.g. the MODIS official ET product, Global Land Evaporation Amsterdam Model (GLEAM v3a) ET products, the FLUXNET observations upscaled ET products, Surface Energy Balance System (SEBS) ET products. The estimated ET dataset can represent overall reasonable geographical patterns and seasonality, and it agrees well with other ET products in terms of spatial variation, however with the advantage of either high spatial-temporal resolution or high accuracy.

The main objective of this project is to improve the estimate of water balance under natural and human pressure on the Heihe basin in China by using MOST, ESA and NASA satellite data coupled with three distributed hydrological models (FEST-EWB & SHAW-DBHM, HeiFLOW). This will be achieved simulating evapotranspiration, soil moisture, discharge, SWE and groundwater dynamic at different spatial and temporal scales.

Multi-source remote sensing data, from visible to thermal infrared and microwave, will be used for forcing, calibration, validation and data assimilation of/into basin scale hydrological models. Vegetation parameters, snow coverage, LST and soil water content, lakes extent and water level height, and meteorological forcings will be retrieved.

In this year presentation, FEST-EWB model is run for the whole Heihe River basin at spatial resolution of 0.05° and temporal resolution of 1 hour. Results are provided in terms of hourly evapotranspiration, soil moisture and land surface temperature maps for the 2012.

FEST-EWB model algorithm solves the system of energy and mass balances in terms of a representative equilibrium temperature (RET) that is the land surface temperature that closes the energy balance equation and so governs the fluxes of energy and mass over the basin domain. This equilibrium surface temperature, which is a critical model state variable, is comparable to LST as retrieved from operational remote sensing data (MODIS, LANDSAT) which is used for the calibration of soil and vegetation parameters at pixel scale.

Evapotranspiration estimates are then compared at local scale with two eddy covariance data and at basin scale with the estimates from the ETMonitor model.

Surface radiation balance is a very important energy source in study of the third pole region ’s evapotranspiration, snow and glacier melting. It is a controlling factor in characterizing the regional energy and water cycle’s system and it’s change. However, all currently available radiation products in this area are not suitable for regional scale study of water and energy exchange and snow/glacier melting due to their coarse resolution and low accuracies, such as the re-analyses data. The study summarizes our recent progress on the all-sky surface radiation estimation with high spatial-temporal resolution remote sensing techniques. The significant improvement of these products is the full consideration of the effect of clouds and topography on derived radiation. Our goal is to produce high-resolution (< 2km, half-hour) short- and long-wave radiation (downward and net components) to drive high-resolution hydrological model’s application and to improve our understanding the third pole region’s energy and water cycle’s system.

Glacier-climate interaction and its spatial variability over the Tibetan Plateau is still poorly understood. We present a new distributed glacier mass balance model applied on two glaciers of the Tibetan Plateau: Parlung No. 4 Glacier, 11.7 km², a temperate-maritime glacier, and Zhadang Glacier, 2.0 km², a sub-continental glacier. Enthalpy, rather than temperature, is used in the energy budget equations to simplify the computation of latent heat fluxes from water phase changes and the movement of liquid water in the snow. Two novel methods are used to distribute near-surface air temperature and wind speed from a set of Automatic Weather Stations (AWS). Further, we apply a new method to discriminate between solid and liquid precipitation based on daily mean air temperature, relative humidity, and elevation. Model results are evaluated by in-situ mass balance observations of the Parlung No. 4 Glacier and remote sensing products.

Our aims are to: i) develop a novel enthalpy-based model and test its performance on the distributed simulations of glacier mass balance and energy budget; ii) compare the physical processes typical of the summer season on two different types of glaciers on the Tibetan Plateau; iii) identify the key model sensitivities at both study sites. We present the interplay of precipitation thresholds, albedo and net radiation at these different glaciers and discuss their implications for future mass balance modelling on the Tibetan Plateau.

The response of glaciers to climate in the high-elevation Tibetan Plateau (TP) is generally poorly understood and is highly variable in space and time. A key influence on glaciers of the TP and surrounding mountain ranges is the monsoon, which for a large majority of TP glaciers overlaps with the main melting season and determines a very specific regime of mixed accumulation and ablation in summer. Monsoon effects on glacier mass balance however are still little understood. We use a distributed energy balance model, combined with high-resolution meteorological observations and new schemes for precipitation discrimination and albedo evolution to understand the effect of rain events and monsoon precipitation on the summer mass balance of a monsoon-dominated glacier of the TP. The main effect of precipitation events is to considerably alter surface conditions, maintaining higher reflectivity surface for most of the season. We show that it is challenging to reproduce this effect with traditional approaches based on simple discrimination of solid/liquid precipitation. The glacier summer mass balance is highly sensitive to precipitation thresholds discriminating between rain, sleet or snow. Precipitation acts both on the actual mass balance as well as the surface albedo. Adjustment of albedo during sleet events is crucial to correctly reproduce the glacier mass balance, and neglecting it leads to much higher mass losses and more negative mass balance over the entire glacier but especially at higher elevations, with a similar negative impact on summer mass balance than prescribing ~69% less snow accumulation for the upper-glacier. Based on static air temperature shifts of +1.5°C, it is found that the dynamic precipitation discrimination approach based on wet bulb temperatures results in a monsoon period mass balance up to 36% more sensitive than if assuming a single value threshold for solid and liquid precipitation. Our work identifies a key and complex role of precipitation events on the glacier mass balance, and a strong need for improving the modelling of local precipitation gradients and thresholds based on observations of a high spatio-temporal resolution.

Hydrologic model is a simplification of a real-world system that aids in understanding, predicting, and managing regional water resources. The quality of driving data greatly influences the accuracy of model simulation. Red River a China-Laos-Vietnam transboundary river. The upstream and middle stream of which are dry-hot valley regions with large altitude difference(1893-1916). The water resources simulation and management are difficult and complex. The new version of Chinese Land Data Assimilation Systems(CLDAS-V2) integrated advantages of point-based ground meteorological observations and remote sensing products. The products have higher 6km spatial resolution and higher quality within the China boundary. In this study, we simulated the soil moisture and runoff in Red River Basin(RRB) in 2017-2018 by using The Variable Infiltration Capacity (VIC) model based on CLDAS-V2.0 products, as well as state data (e.g. 250m DEM, MODIS 500m LAI products). The prelimary result show that the daily runoff simulation fits well with actual runoff observation in Yuanjiang station and Tukahe station in early 2018. There are several big rivers derived from Asia high plain. This study reveals the usefulness of CLDAS-V2 product in similar transboundary river basin for flood and drought management. There are good water level-runoff regression relation in RRB. Our results will be validated with water level of small water body by SAR altimetry and 1km spatial resolution downscaled SMOS Soil Moisture products[Gao et al. 2018].

Water balance in red river basin is very complex. Due to complex topography, total drop of red river is high (2574m). One of the greatest challenges for flood prediction and integrated water management in the Red River basin is a lack of information on reservoir management, as a consequence, it is not easy to estimate the water resources. Since it is a transboundary river, there are difficulties to manage the area as a whole, and the information might not be in time for flood and drought early warning.
Thanks to Microwave Remote Sensing, water resources can be monitored within any weather conditions remotely. The main objective of this project is to develop the algorithms and synergies between different Microwave Remote Sensing sensors to be able to monitor water resources in the Red River Basin. Accounting with water level products over Redriver basin, soil moisture products and runoff, can help improving water resource management in this area.
SAR altimetry with the slicing of the altimeter footprint that the SAR mode performs, allows the separate computation of all the elementary reflectors, in particular the wet ones. In this project, we took advantage of SAR altimetry to monitor small water bodies in Red River basin.
However, satellite altimeters are initially designed to monitor homogeneous surfaces such as oceans or ice sheets, which results in poor performance over small inland water bodies because of the land contamination contribution in the returned waveforms. To improve altimeter range accuracy which relates to water level measurement accuracy, the waveform needs to be retracked precisely to find out the accurate tracking point which locates on the leading edge [Deng and Featherstone, 2006]. In our study, we use the Sentinel-3 satellite with data available from June 2016 to retrieve the water level in Red river basin. The new retrackers [Makhoul e al., 2018] including the threshold, OCOG, and 2-step analytical retracker are introduced to find the tracking points precisely from the land contaminated waveforms. The waveform portion selection is applied for the water level retrieval using DEM information to locate the waveform portion which comes from nadir.
The aim of the study is to retrack water level more precisely by comparing the threshold, OCOG and 2-step analytical retracker performance along with the waveform portion selection approach performance over Red river. It is a challenging task since the water bodies are very small, the widths of which we studied are mostly around 200m to 500m, which means there are only one or two signals in the water for Sentinel-3 whose spatial resolution is 300m along track. For Redriver basin, Sentinel-3 works in closed loop tracking, which means the altimeter range window is autonomously positioned based on on-board NRT analysis of previous SRAL waveform. With the mountainous topography, it is more challenging to locate the leading-edge position of the waveform.
The water level results of the three retrackers with waveform portion selection are then compared with the onboard ocean retracker. Over places with land contamination, the analytical 2-step retracker with waveform portion selection has shown better performances than ESA L2.
The preliminary results show a smoothly time series over several water bodies in Red river basin, and waveform portion selection works much better than using the whole waveform since the DEM information is introduced to eliminate land contamination. Retracking water level from Level-1 waveforms using the combination of the retrackers and waveform portion selection is more robust to land contamination than using Level-2 data directly.
We will be producing Soil Moisture products at 1km spatial resolution for the entire Red River basin for the 2010-2017 period. The Soil Moisture products will be SMOS based and we will use the DisPATCh disaggregation scheme to increase SMOS coarse resolution. DisPATCh provides 1 km resolution SM data from coarse-scale microwave derived SM. In DisPATCh, the soil evaporation from the 0-5 cm soil layer and the vegetation transpiration from the root zone soil layer are partitioned by separating MODIS LST (Land Surface Temperature) into its soil and vegetation components. The partitioning method relies on a contextual interpretation of MODIS LST and MODIS NDVI [Moran et al. 1994]. MODIS-derived soil temperature is first used to estimate Soil Evaporative Efficiency (SEE defined as a ratio of actual to potential soil evaporation), which is known to be relatively constant during the day on clear sky conditions. DisPATCh then distributes high-resolution soil moisture around the low-resolution observed mean value using the instantaneous spatial link between optical-derived SEE and near-surface soil moisture [Merlin et al. 2013].
These soil moisture estimates will be validated against output from modeling [Rui et al. 2018].
With water level products and soil moisture products over Redriver basin, the hydrological model for water resource estimation can be improved in future steps.

Abstract:

Soil moisture (SM) is a significant determinant of crop growth and a useful indicator of drought. It is important to evaluate and analyze existing soil moisture products for environmental monitoring and protection of the Belt and Road region. At present, there are many global soil moisture products, such as the ones retrieved from the data collected by AMSR-E (the Advanced Microwave Scanning Radiometer-Earth Observing System), AMSR-2(the Advanced Microwave Scanning Radiometer 2), FY3B/C (the Feng Yun 3rd Satellite), LPDR (the Daily Global Land Parameters Derived from AMSR-E andAMSR-2) and ESA CCI (the ESA Climate Change Initiative) at a coarse resolution of ~0.25◦.

In this study, the 8 soil moisture products were selected (AMSR-E/JAXA, AMSR-E/NASA, AMSR-2/JAXA, AMSR-2/NASA, FY3B/C, LPDR and ESA CCI). The approximate ascending and descending equator crossing time, channel and incident angle, except LPDR and ESA CCI are indicated. Among them, the LPDR product is derived from other three soil moisture products (AMSR-E, AMSR-2 and FY3B). LPDR soil moisture product was developed by using the double difference and inter-calibration methods from AMSR-2, AMSR-E and FY3B. The ESA CCI product was developed by merging many passive and active soil moisture products, such as AMSR-2, SMOS, MetOp-A and so on. In this study, the JAXA and NASA soil moisture products AMSR-E and AMSR-2 were selected. The overlapping time of AMSR-E, FY3B, LPDR and EAS CCI is 2011. The overlapping time of AMSR-2, FY3B/C, LPDR and EAS CCI is from 2014 to 2016. According to the overlapping time of soil moisture products, the comparison and validation of different soil moisture products was supported with in-situ data from ISMN (the International Soil Moisture Network) and ERA Interim/Land (0-7cm soil depth). Secondly, soil moisture content is influenced by various factors, such as soil type, land-use type, climate type and so on. The climate type implies patterns in rainfall and temperature that affect the retrievals, but also closely related to surface types. These effect factors also influence the soil moisture content. Therefore, in this study, the climate type is introduced in soil moisture product analysis at the Belt and Road region.

Keywords— soil moisture product, Belt and Road, comparison, validation

The Earth Observation (EO) mission for mapping global surface soil moisture and generating related satellite products have been witnessed a great progress in the last several decades. Among several global soil moisture products, the soil moisture products developed based on the European Space Agency Climate Change Initiative (ESA CCI) are the most complete and longest temporal serial soil moisture data records.

The latest versions (v04.2 v03.3) of CCI soil moisture products were released on Jan. 17, 2018 and Nov. 27, 2017, respectively. These two versions of the products cover the temporal range from October of 1978 to the end pf 2016. The previous versions of the products have been intensively validated. However, the evaluation of the latest version has not been reported yet. The main aim of this study is to provide an in-deep evaluation of the latest CCI soil moisture products using ground observations. To this end, ground observation from three soil moisture observation networks distributed in Tibetan Plateau, namely BBHNet, MAQU and CTP-SMTMN, are used as the reference data. The results show that the products present a little underestimation of the soil moisture over the three regions. But both versions of the products show good agreement with the temporal variation of the ground observations. Relatively, the v03.3 product is a little better than the v04.2 product.

Glaciers in the Tibetan Plateau are important climate indicators due to their rapid response to climate variability. Therefore, it is crucial to understand glacier changes and their response to climate change. Long-term series of satellite data can provide such information. The complexity of observing and understanding changes in glacier conditions is augmented by the spatial heterogeneity of the glacier surface. Automatic glacier mapping utilizing remote sensing data is even more challenging due to the spectral similarity of supraglacial debris and the adjacent bedrock, orographic clouds and highly variable snow conditions. The vast majority of the available glacier datasets only provide the total glacier area, which means that the boundary between clean ice and debris-covered glacier is not clear. Different glacier elements have different melt rates and densities. This discrimination plays a key role in mass balance research and improved hydrological modeling.

The aim of this study was to distinguish ice cover types on a given date in a subregion of the Parlung Zangbo basin in the southeastern Tibetan Plateau. Multitemporal analyses will be dealt with in a later study. The classification was carried out by employing an automated machine learning approach – Random Forests in combination with the analysis of topographic and textural features based on Landsat-8 image and ASTER GDEM data. The Gao Fen-1 (GF-1) PMS image was used to validate classification results. In this study, all the glacierized terrain types were classified with very high overall accuracy (>98%). The results indicated that debris-covered glaciers accounted for approximately 15.86% of the total glacier area in this region and debris covered glaciers were mainly distributed between 4600 m and 4800 m a.s.l. Additionally, analysis of the results clearly revealed that the number proportion of small glaciers (<1 km²) was 92.18%, which were distributed at lower elevation than large glaciers. In future work, the recognition of debris-free and debris-covered glaciers require further studies with more field observations and higher resolution DEM dataset.

Keywords: Automatic glacier mapping; Random Forests; Landsat; Parlung Zangbo basin

Locates at central Himalaya, Mt. Everest (Qomolangma) is the highest peak in the world. Famous glaciers such as Rongbuk glacier and Khumbu glacier were studied by for several long decades. Satellite geodetic observation provides important observation on glacier mass balance in the high-mountain area and plays an essential alternative to in-situ observations given the cold and harsh environment. In this research, we collected SRTM DEM observed in 2000, and bistatic TerraSAR-X/TanDEM-X SAR images observed in around 2013 and 2017. By referring SRTM as reference DEM, we obtained topographic changes between 2000 and 2013, also 2000 and 2017 by using an iterative D-InSAR method. Penetration depth differences between C- and X-band microwave on snow and ice were evaluated and corrected by comparing C- and X-band SRTM DEMs. Glacier mass balance between 2000 and 2013 was -0.38 ± 0.04 m w.e. (water equivalent) a-1, and was -0.75 ± 0.08 m w.e. a-1 between 2013 and 2017. The spatial pattern of the glacier mass loss was heterogeneous. The regional heterogeneity may possibly reflect debris-covering rates, terminating type, temperature rising rates and glacier flow rates. However, the spatial pattern in two periods kept constant. Glaciers without debris-cover at Chinese side present the slowest losing rate while lacustrine-terminating glaciers with heavy debris-covers show quickest lost rates.

Field observations and geodetic measurements suggest that glaciers in the Karakoram Range are either stable or have been expanding since 1990 and present positive or less negative mass changes. This situation is called the “Karakoram anomaly”. Previous studies found that the Central Karakoram has experienced a slight gain in glacier mass at the beginning of the 21st century. Glacier surface velocity is one of the key parameters of glacier dynamics and mass balance. The spatial-temporal characteristics of the glacier velocity in the Central Karakoram are essential to improve our understanding of glacier dynamics and the glacier responses to climate change and influences on regional water sources.

The inter-annual glacier velocity results during 1999-2003 are achieved by using a cross-correlation algorithm in the frequency domain with four pairs of Landsat-7 Enhanced Thematic Mapper Plus panchromatic images. The images were co-registered first, and the horizontal displacements were calculated with the COSI-Corr software package. Due to a lack of in situ measurements of the glacier velocity in the Central Karakoram, it was difficult to directly assess the results of the cross-correlation algorithm. Considering the stable properties of off-glacier areas that should not be displaced, the displacements of the off-glacier area have been widely used to evaluate the cross-correlation performance.

The results show that the variations in ice velocities during 1999–2003 are not obvious for most of the studied glaciers in the Central Karakoram. This indicates that the glacier velocities were quasi-stable during the study period. The uncertainty of the velocity results based on the off-glacier statistics was approximately 7 m/year in the four epochs of observation, which is less than one-half a pixel. We find that most of the glaciers on the southern slope flowed faster than those on the northern slope, which might be attributed to the differences in glacier sizes. From the transverse velocity profiles of seven typical glaciers, we infer that basal sliding is the predominant motion mechanism of the middle and upper glaciers, whereas internal deformation dominates closest to the glacier terminus.

By combusting surface vegetation and soil organic matter, wildfires can have a strong impact on tundra environment. Disturbed vegetation may need many years to recover to pre-fire phase or a mature stage. In this study, we quantified changes of C- and L-band SAR backscatter over 15 years (2002–2016) and used them to investigate vegetation regrowth affected by the Anaktuvuk River Fire in Arctic tundra environment. After the fire, C- and L-band backscatter coefficients increased by up to 5.5 and 4.4 dB in the severely burned areas compared to the unburned areas, respectively. Beyond 5 years after the fire, the C-band backscatter differences diminished between the burned and unburned areas, indicating that vegetation level in burned sites had recovered to the unburned level. This duration is longer than the 3-year recovery suggested by optical-based NDVI observations. Moreover, the L-band backscatter remained about 2 dB higher in the severely burned area than the unburned area after 10-year recovery. Such sustained differences are probably contributed by increased roughness of the surface. Our analysis indicates that long records of space-borne SAR backscatter can quantify post-fire vegetation recovery in arctic tundra environment and complement optical observations.

Snow depth derived from passive microwave (PMW) with spatial resolution of 25 km is difficult to describe the snow condition and has been generally overestimated in the Qinghai-Tibetan plateau (QTP) which is characterized by patchy snow cover. The main reason for such overestimation is the contribution of low-temperate snow-free ground to the brightness temperature difference between K and Ka bands (TBD). Therefore, in this study, a new method combining MODIS snow cover fraction (SCF) and land surface temperature (LST) and PMW brightness temperature data is developed to derive snow depth at cell size of 0.005^o. MODIS’S SCF is used to identify the snow cover portion of a PMW pixel, and its LST is applied to calculate the TBD contributed from snow-free portion of the PMW pixel. Result shows that after removing such contribution, the TBD value of the PMW pixel is more reasonable and the derived snow depth exhibits relatively smaller errors. The bias and RMSE are 23.4% and 37.3%, respectively, as compared with the 48.5% and 60.5% before such contribution was removed, when using meteorological station observations (2003-2010) as reference. They are 22.5% and 76.1%, respectively, compared with 54.9% and 107.0%, when using field observations (March 2014) as reference. The remaining bias (i.e., overestimation) is mostly due to the TBD contribution (up to 10K) from the low temperature of frozen ground underlying the thin and patchy snow cover (or area). This phenomenon also exists in other cold areas, such as eastern Russia, although not as obvious as on the QTP, because the overall thin and patchy snow cover in QTP could not shield the underling soil from the impact of low air temperature.

Meltwater from rock glaciers could provide a relevant contribution to water supply especially in dry regions. Moreover, rock glaciers could have serious hazard potentials when located at or above steep slopes or when damming lakes. Existing investigations about rock glaciers in High Mountain Asia indicate that the landforms are abundant but information is rare for the Tibetan Plateau and the northern slopes of the Himalaya.

We compiled a rock glacier inventory for the Poiqu region (28° 17´N, 85°58´E) – Central Himalaya/Tibet. The mapping was mainly based on optical images from Sentinel 2 and Google Earth. In addition, we used a hillshade calculated from the new 8 m High Mountain Asia DEM where we filled existing gaps with the 12 m TanDEM-X DEM. Rock glaciers were identified based on their characteristic shape and surface structure. Additional information on the occurrence and activity of the rock glaciers was provided by the InSAR technique using ALOS-1 data.

The preliminary results of the inventory reveal 362 rock glaciers covering an area of about 42 km². The largest one has an area of 2 km² and four have an area of around 1 km². The rock glaciers are located between ~4100 m and ~ 5700 m with a mean altitude of ~5040 m a.s.l.. The mean slope of all rock glaciers is close to 20° (min. 8°, max. 35°). Most of the rock glaciers face towards the Northeast (19%) and West (18.5%). Our study indicates that 158 rock glaciers can be classified as active. We also found rock glaciers damming lakes and infrastructure (streets), which could be threatened by the instability from rock glaciers above.

Future work will concentrate on additional datasets like Sentinel 1 for the improvement of the rock glacier inventory in the Poiqu region.

A group of tongue-shaped periglacial landforms near Jingxian Valley (35°40´N, 94° 00´E) in eastern Kunlun Shan have been reported 20 years ago and classified as “Kunlun-type” rock glaciers due to their unique morphology and slow creeping rates. However, the nature of the northern slopes has remained contentious and later been interpreted as gelifluction deposits. Moreover, the kinematic features of the landform had not been fully investigated or understood. Here, we use satellite SAR interferometry to quantitatively characterize the spatial and temporal changes of the surface movement of these landforms. Five ALOS-1 PALSAR images acquired between 2008 to 2009 over eastern Kunlun Shan area have been used to generate three interferograms to measure the surface movement velocities of the landform. One interferogram records the kinematic information during winter/early spring and the other two are averaged to represent the surface movement during summer. We observe that: (1) the eastern slope is also active with a summer velocity of 20­–60 cm/yr (in the satellite line-of-sight direction, same for all the velocities reported here); (2) the northern lobes moved at 20 to 50 cm/yr in summer, which are much larger than the field measured velocities of less than 3 cm/yr near the front as reported in a previous study conducted from 1980 to 1982; and (3) both the northern lobes and eastern slope are inactive during winter.

The seasonal acceleration in movement of rock glaciers during summer have been observed and, in some cases, no movement can be detected in winter. Gelifluction processes can also trigger seasonal velocity variations. However, creeping rates during summer are typically smaller than 20 cm/yr in cold and dry climate conditions such as Jingxian Valley. Several key pieces of evidence, such as (1) the widespread and relatively fast movement and (2) the large-scale tongue-shaped morphology, suggest that the northern lobes are rockglaciers. The lack of oversteepened fronts presumably results from gelifluction processes of the fine-grained deposits covering the slopes, which smooths out the surface of the landform. The eastern slope shows a similar pattern of seasonal surface kinematic variations to the northern lobes. However, the different morphologic characteristics of the two groups of targets indicate different types of periglacial landforms. With a relatively high surface moving speed and large geometry scale, the northern lobes are unique parts of the alpine permafrost in Eastern Kunlun Shan, representing a mixed type of rock glaciers and gelifluction deposits.

There are approximately 1200 lakes whose area is greater than 1 km² on the Tibetan Plateau (TP), the highest plateau of the world. These lakes are important indicators of environment change because they integrate the basin-wide variations of climate, cryosphere and ecosystems. Previous work on lake changes on the TP during the last several decades have focused on surface area because volume variations need information about lake levels — either in-situ or by satellite altimetry data. However, in-situ measurements are very limited and altimetry data such as ICESat-1 and CryoSat-2 are available at a short term. Here, we present an innovative and robust method that combines digital elevation data and multispectral images to estimate water volume changes for the two largest lakes on the TP, Selin Co and Nam Co from the 1970s to 2015. In addition, the contribution of glacier mass changes to lake volume change between 2000 and 2015 is examined at lake-basin scale using existing estimates based on ICESat and ASTER DEM data. The lake storage changes for Selin Co and Nam Co between 1970s and 2015 are 18.8 and 7.0 Gt. Combining with previous studies of glacier mass balances, the lake volume increase from glacier contribution for two largest lakes, Selin Co and Nam Co, are approximately 28% and 8%, respectively. The future research will extend the estimates of glacier contribution to early 1970s combining declassified satellite data, SRTM and TanDEM-X DTMs and other data sources.

Rock glaciers are important periglacial phenomena in high mountain regions. The Yarlung Tsangpo River basin in the Tibet Autonomous Region of China, the distribution of rock glaciers and their hydrological and environmental effects are poorly understood in the basin. We have produced the first comprehensive inventory of rock glaciers in the Yarlung Tsangpo River basin through the fine spatial resolution satellite data that is freely available on Google Earth, we identified 372 rock glaciers based on their morphological features. We then generated attributes of these rock glaciers including the average length, width, slope, orientation, average elevations of the upper and lower limits, their average elevation and median elevation, as well as hypsometry of each glacier. Through statistical analysis, we show that rock glaciers are situated between 4307 and 5814m a.s.l, with the mean minimum elevation at the front estimated to be 4427 m a.s.l, and the mean maximum elevation at the front estimated to be 5731 m a.s.l. The majority (53%) were found to have a northerly aspect (NE, N, and NW).It provided an important basis for our further understanding of the rock glacier in the Yarlung Tsangpo River basin.

Glacier mass balance, as a direct indicator of climate change, attracted increasing attention in the field of cryosphere. Measuring the region-wide glacier mass balance plays a significant role in understanding the response of glaciers to climate change and their influence on water resources and glacial hazards. In this paper, we derived the mass changes of glaciers according to the geodetic method based on three DEMs representing status of glaciers in different years. These DEMs were generated from declassified Hexagon images (1973-1980), SRTM DEM with 30 m resolution (2000) and TerraSAR-X/TanDEM-X data (2012). All DEMs were co-registered by eliminating errors resulted from horizontal difference and removal of the elevation anomalies. We also took into account errors in the glacier boundary delineation, the seasonal fluctuation in surface elevation, snow and ice density and penetration depth of radar beam. Our expected result is that glaciers mass budgets are negative in the Mt. Xixiabangma during the past period.