Satellite-based monitoring of pasture degradation on the Tibetan Plateau: A multi-scale approach

The Tibetan Plateau has been entitled Third-Pole-Environment'' because of its outstanding importance for the global climate and the hydrological system of East and Southeast Asia. Its climatological and hydrological influences are strongly affected by the local vegetation which is supposed to be subject to ongoing degradation. The degradation of the Tibetan pastures was investigated on the local scale by numerous studies. However, because methods and scales substantially differed among the previous studies, the overall pattern of degradation on the Tibetan Plateau is hitherto unknown. Consequently, the aims of this thesis are to monitor recent changes in the grassland degradation on the Tibetan Plateau and to detect the underlying driving forces of the observed changes. Therefore, a comprehensive remote sensing based approach is developed. The new approach consists of three parts and incorporates different spatial and temporal scales: (i) the development and testing of an indicator system for pasture degradation on the local scale, (ii) the development of a MODIS-based product usable for degradation monitoring from the local to the plateau scale, and (iii) the application of the new product to delineate recent changes in the degradation status of the pastures on the Tibetan Plateau. The first part of the new approach comprised the test of the suitability of a new two-indicator system and its transferability to spaceborne data. The indicators were land-cover fractions (e.g.,~green vegetation, bare soil) derived from linear spectral unmixing and chlorophyll content. The latter was incorporated as a proxy for nutrient and water availability. It was estimated combining hyperspectral vegetation indices as predictors in partial least squares regression. The indicator system was established and tested on the local scale using a transect design and textit{in situ} measured data. The promising results revealed clear spatial patterns attributed to degradation, indicating that the combination of vegetation cover and chlorophyll content is a suitable indicator system for the detection of pasture degradation on local scales on the Tibetan Plateau. To delineate patterns of degradation changes on the plateau scale, the green plant coverage of the Tibetan pastures was derived in the second part. Therefore, an upscaling approach was developed. It is based on satellite data from high spatial resolution sensors on the local scale (WorldView-type) via medium resolution data (Landsat) to low resolution data on the plateau scale (MODIS). The different spatial resolutions involved in the methodology were incorporated to enable the cross-validation of the estimations in the new product against field observations (over 600 plots across the entire Tibetan Plateau). Four methods (linear spectral unmixing, spectral angle mapper, partial least squares regression, and support vector machine regression) were tested on their predictive performance for the estimation of plant cover and the method with the highest accuracy (support vector machine regression) was applied to 14 years of MODIS data to generate a new vegetation coverage product. In the third part, the changes in vegetation cover between the years 2000 and 2013 and their driving forces were investigated by comparing the trends in the new vegetation coverage product against climate variables (precipitation from tropical rainfall measuring mission and 2 m air temperature from ERA-Interim reanalysis data) on the entire Tibetan Plateau. Large areas in southern Qinghai were identified where vegetation cover increased as a result of positive precipitation trends. Thus, degradation did not proceed in these regions. Contrasting with this, large areas in the central and western parts of the Tibetan Autonomous Region were subject to an ongoing degradation. This degradation can be attributed to the coincidence of rising temperatures and anthropogenic induced increases in livestock numbers as a consequence of local land-use change. In those areas, the ongoing degradation influenced local precipitation patterns because sensible heat fluxes were accelerated above degraded pastures. In combination with advected moist air masses at higher atmospheric levels, the accelerated heat fluxes led to an intensification of local convective rainfall. The ongoing degradation detected by the new remote sensing approach in this thesis is alarming. The affected regions encompass the river systems of the Indus and Brahmaputra Rivers, where the ongoing degradation negatively affects the water storage capacities of the soils and enhances erosion. In combination with the feed-back mechanisms between plant coverage and the changed precipitation on the Tibetan Plateau, the reduced water storage capacity will exacerbate runoff extremes in the middle and lower reaches of those important river systems

Recent Ice Trends in Swiss Mountain Lakes: 20-year Analysis of MODIS Imagery

Depleting lake ice is a climate change indicator, just like sea-level rise or glacial retreat. Monitoring Lake Ice Phenology (LIP) is useful because long-term freezing and thawing patterns serve as sentinels to understand regional and global climate change. We report a study for the Oberengadin region of Switzerland, where several small- and medium-sized mountain lakes are located. We observe the LIP events, such as freeze-up, break-up and ice cover duration, across two decades (2000–2020) from optical satellite images. We analyse the time series of MODIS imagery by estimating spatially resolved maps of lake ice for these Alpine lakes with supervised machine learning. To train the classifier we rely on reference data annotated manually based on webcam images. From the ice maps, we derive long-term LIP trends. Since the webcam data are only available for two winters, we cross-check our results against the operational MODIS and VIIRS snow products. We find a change in complete freeze duration of −0.76 and −0.89 days per annum for lakes Sils and Silvaplana, respectively. Furthermore, we observe plausible correlations of the LIP trends with climate data measured at nearby meteorological stations. We notice that mean winter air temperature has a negative correlation with the freeze duration and break-up events and a positive correlation with the freeze-up events. Additionally, we observe a strong negative correlation of sunshine during the winter months with the freeze duration and break-up events

Institutional mapping and causal analysis of avalanche vulnerable areas based on multi-source data

Avalanche disaster is a major natural disaster that seriously threatens the national infrastructure and personnel's life safety. For a long time, the research of avalanche disaster prediction in the world is insufficient, there are only some basic models and basic conditions of occurrence, and there is no long series and wide range of avalanche disaster prediction products. Based on 7 different bands and different types of multi-source remote sensing data,this study combined with existing avalanche occurrence models, field investigation and statistical data to analyze the causes of avalanche. The U-net convolutional neural network and threshold analysis were used to extract the distribution of long time series avalanch-prone areas in two study areas, Heiluogou in Sichuan Province and along the Zangpo River in Palong, Tibet Autonomous Region. In addition, the relationship between earthquake magnitude and spatial distribution and avalanche occurrence is also analyzed in this study. This study will also continue to build a prior knowledge base of avalanche occurrence conditions, improve the prediction accuracy of the two methods, and produce products in long time series interannual avalanch-prone areas in southwest China, including Sichuan Province, Yunnan Province, and Tibet Autonomous Region. The resulting products will provide high-precision avalanche prediction and safety assurance for engineering construction and mountaineering activities in Southwest China.Comment: 19 pages, 13 figure

A new 2010 permafrost distribution map over the Qinghai–Tibet Plateau based on subregion survey maps: a benchmark for regional permafrost modeling

Permafrost over the Qinghai–Tibet Plateau (QTP) has received increasing attention due to its high sensitivity to climate change. Numerous spatial modeling studies have been conducted on the QTP to assess the status of permafrost, project future changes in permafrost, and diagnose contributors to permafrost degradation. Due to the scarcity of ground stations on the QTP, these modeling studies are often hampered by the lack of validation references, calibration targets, and model constraints; however, a high-quality permafrost distribution map would be a good option as a benchmark for spatial simulations. Existing permafrost distribution maps for the QTP can poorly serve this purpose. An ideal benchmark map for spatial modeling should be methodologically sound, of sufficient accuracy, and based on observations from mapping years rather than all historical data spanning several decades. Therefore, in this study, we created a new permafrost distribution map for the QTP in 2010 using a novel permafrost mapping approach with satellite-derived ground surface thawing and freezing indices as inputs and survey-based subregion permafrost maps as constraints. This approach accounted for the effects of local factors by incorporating (into the model) an empirical soil parameter whose values were optimally estimated through spatial clustering and parameter optimization constrained by survey-based subregion permafrost maps, and the approach was also improved to reduce parametric equifinality. This new map showed a total permafrost area of about 1.086×106 km2 (41.2 % of the QTP area) and seasonally frozen ground of about 1.447×106 km2 (54.9 %) in 2010, excluding glaciers and lakes. Validations using survey-based subregion permafrost maps (κ=0.74) and borehole records (overall accuracy =0.85 and κ=0.43) showed a higher accuracy of this map compared with two other recent maps. Inspection of regions with obvious distinctions between the maps affirms that the permafrost distribution on this map is more realistic than that on the Zou et al. (2017) map. Given the demonstrated excellent accuracy, this map can serve as a benchmark map for constraining/validating land surface simulations on the QTP and as a historical reference for projecting future permafrost changes on the QTP in the context of global warming. The dataset is available from the repository hosted on Figshare (Cao et al., 2022): https://doi.org/10.6084/m9.figshare.19642362.</p

Energy and Water Cycles in the Third Pole

As the most prominent and complicated terrain on the globe, the Tibetan Plateau (TP) is often called the “Roof of the World”, “Third Pole” or “Asian Water Tower”. The energy and water cycles in the Third Pole have great impacts on the atmospheric circulation, Asian monsoon system and global climate change. On the other hand, the TP and the surrounding higher elevation area are also experiencing evident and rapid environmental changes under the background of global warming. As the headwater area of major rivers in Asia, the TP’s environmental changes—such as glacial retreat, snow melting, lake expanding and permafrost degradation—pose potential long-term threats to water resources of the local and surrounding regions. To promote quantitative understanding of energy and water cycles of the TP, several field campaigns, including GAME/Tibet, CAMP/Tibet and TORP, have been carried out. A large amount of data have been collected to gain a better understanding of the atmospheric boundary layer structure, turbulent heat fluxes and their coupling with atmospheric circulation and hydrological processes. The focus of this reprint is to present recent advances in quantifying land–atmosphere interactions, the water cycle and its components, energy balance components, climate change and hydrological feedbacks by in situ measurements, remote sensing or numerical modelling approaches in the “Third Pole” region

Carbon translocation from glacial and terrestrial to aqueous systems – characteristics and processing of dissolved organic matter in the endorheic Tibetan Lake Nam Co watershed

The Tibetan Plateau (TP) comprises sensitive alpine environments such as grassland biomes. Climatic changes and intensifying land use threaten these ecosystems. Therefore, it is important to understand the response of ecosystems to changing biotic and abiotic factors. The translocation of dissolved organic matter from glacial and terrestrial to aqueous systems is an important aspect of this response, specifically when characterizing changing conditions of freshwater resources and sensitive limnic ecosystems on the TP. Via changes in its chemical composition, characteristics, transformation and processing of DOM can be tracked. Three catchments of the Nam Co watershed of the TP (Niyaqu, Qugaqie and Zhagu) and the lake were investigated to understand how site specific terrestrial processes and seasonality affect the composition of DOM and alteration of organic compounds in streams and the lake of this endorheic basin. Four hypotheses were tested: H1 The natural diversity in the Nam Co watershed controls site specific effects on DOM composition. H2 Seasonal effects on DOM composition are driven by warm and moist summers influenced from the Indian summer monsoon (ISM) and cold and dry winters. H3/ H4a Site specific effects on DOM diminish by means of biological decomposition and photooxidation of DOM during the stream path / in the lake. Alongside H4b organic matter of the Nam Co Lake is independent from catchment influences, given by an autochthonous source of DOM. A multi-parameter approach was applied, consitsing of water chemistry parameters (pH, electric conductivity, cations and anions, dissolved inorganic carbon), concentration of dissolved organic carbon (DOC), DOM characteristics (chromophoric DOM, fluorescence DOM and δ13C of DOM) and DOM ultra-high resolution Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). Sampling was conducted for three seasons, freshet in 2018, the phase of the ISM in 2019 and post-ISM baseflow in 2019. Alongside a watershed-wide plant cover estimate was composed, to explore the link between differences in DOM characteristics and degree of green plant cover. Sampling covers stream water, as well as endmember samples such as: glacial effluents, water of springs and water from an alpine wetland. The lake was covered by sampling the brackish zone and the lake pelagial and the lake surface. The composition of DOM differed between the three endmember groups and between stream samples of catchments. Glaciers showed a dual DOM source, indicating a glacial microbiome and compounds derived from burned fossil fuels. Springs differed based on their geographic location. Upland waters showed limited inputs of alpine pastures: lowland springs displayed influences of yak faeces with microbial reworked DOM, indicated by less negative δ13C and nitrogen. Wetlands were distinguished by more eutrophic conditions by highest concentrations in DOC and high amounts in N-heteroatoms. Streams were site specific with input sources derived from glaciers, wetlands, groundwater, intense animal husbandry and a plant-derived phenolic signature from alpine pastures aligned to the degree of plant cover. Seasonality affected DOM characteristics in stream water. During freshet, DOM was plant-derived, as was during baseflow conditions. A flush of dissolved organic carbon, accompanied by a compositional shift towards more microbial derived DOM was observed during the ISM season. Processing of DOM in streams was limited to the biolabile fraction of DOM of the glacial biome. Transformation of DOM was overruled by the constant input of plant derived phenolic DOM compounds from alpine pastures. Consequentially, the brackish intermixing zone showed the inflow of terrestrial DOM into the lake. In contrast, lake water exhibited distinct DOM characteristics, by lowest amounts in aromatic molecular compounds and DOM rich in 13C. This suggested intense processing of phenolic, terrestrial derived DOM by photooxidation, as well as a seasonally stable autochthonous DOM source derived from algae and microorganisms in lake water. In conclusion, DOM characteristics are largely influenced by local endmembers such as glaciers, springs and wetlands. Seasonality shows that shifts in the onset, and changes in the intensity of the ISM can largely modify DOM composition. Processing of DOM took place mainly in the lake. The study revealed that DOM is suited to function as a monitoring agent in this lake watershed. Hence, DOM is a helpful tool to understand changes in ecosystems, and forthcoming, to safeguard sensitive ecosystems of the TP.Deutsche Forschungsgemeinschaft (DFG)/International Research Training Group (GRK 2309/1)/317513741/E

Vegetation Dynamics Revealed by Remote Sensing and Its Feedback to Regional and Global Climate

This book focuses on some significant progress in vegetation dynamics and their response to climate change revealed by remote sensing data. The development of satellite remote sensing and its derived products offer fantastic opportunities to investigate vegetation changes and their feedback to regional and global climate systems. Special attention is given in the book to vegetation changes and their drivers, the effects of extreme climate events on vegetation, land surface albedo associated with vegetation changes, plant fingerprints, and vegetation dynamics in climate modeling

Intercomparison of Gridded Precipitation Datasets over a Sub-Region of the Central Himalaya and the Southwestern Tibetan Plateau

Precipitation is a central quantity of hydrometeorological research and applications. Especially in complex terrain, such as in High Mountain Asia (HMA), surface precipitation observations are scarce. Gridded precipitation products are one way to overcome the limitations of ground truth observations. They can provide datasets continuous in both space and time. However, there are many products available, which use various methods for data generation and lead to different precipitation values. In our study we compare nine different gridded precipitation products from different origins (ERA5, ERA5-Land, ERA-interim, HAR v2 10 km, HAR v2 2 km, JRA-55, MERRA-2, GPCC and PRETIP) over a subregion of the Central Himalaya and the Southwest Tibetan Plateau, from May to September 2017. Total spatially averaged precipitation over the study period ranged from 411 mm (GPCC) to 781 mm (ERA-Interim) with a mean value of 623 mm and a standard deviation of 132 mm. We found that the gridded products and the few observations, with few exceptions, are consistent among each other regarding precipitation variability and rough amount within the study area. It became obvious that higher grid resolution can resolve extreme precipitation much better, leading to overall lower mean precipitation spatially, but higher extreme precipitation events. We also found that generally high terrain complexity leads to larger differences in the amount of precipitation between products. Due to the considerable differences between products in space and time, we suggest carefully selecting the product used as input for any research application based on the type of application and specific research question. While coarse products such as ERA-Interim or ERA5 that cover long periods but have coarse grid resolution have previously shown to be able to capture long-term trends and help with identifying climate change features, this study suggests that more regional applications, such as glacier mass-balance modeling, require higher spatial resolution, as is reproduced, for example, in HAR v2 10 km.Peer Reviewe

Remote Sensing of Land Surface Phenology

Land surface phenology (LSP) uses remote sensing to monitor seasonal dynamics in vegetated land surfaces and retrieve phenological metrics (transition dates, rate of change, annual integrals, etc.). LSP has developed rapidly in the last few decades. Both regional and global LSP products have been routinely generated and play prominent roles in modeling crop yield, ecological surveillance, identifying invasive species, modeling the terrestrial biosphere, and assessing impacts on urban and natural ecosystems. Recent advances in field and spaceborne sensor technologies, as well as data fusion techniques, have enabled novel LSP retrieval algorithms that refine retrievals at even higher spatiotemporal resolutions, providing new insights into ecosystem dynamics. Meanwhile, rigorous assessment of the uncertainties in LSP retrievals is ongoing, and efforts to reduce these uncertainties represent an active research area. Open source software and hardware are in development, and have greatly facilitated the use of LSP metrics by scientists outside the remote sensing community. This reprint covers the latest developments in sensor technologies, LSP retrieval algorithms and validation strategies, and the use of LSP products in a variety of fields. It aims to summarize the ongoing diverse LSP developments and boost discussions on future research prospects