For a long time, the development of maritime communication has been restricted by the low data rate, high-latency and high cost of the current communication systems. The upgrade of new generation mobile communication technologies is attracting more and more attention to conduct a shore-based broadband mobile communication network with high-latency and high reliability to serve the maritime industries. This paper presents a solution by means of building a ship-to-infrastructure (S2I) and a ship-to-ship (S2S) wireless communication networks for an offshore region. We characterize the S2I and S2S channels at 5.9 GHz band based on the channel measurements in realistic environments. The channel characteristics, including power delay profile, delay spread, propagation path loss, are extracted and analyzed. In view of the difference between marine and terrestrial communications, we analyze the influencing factors of the offshore water, including effective reflection, divergence and shadowing from the water surface, and diffraction loss caused by the earth curvature. We also predict the power coverage range and the channel capacity for S2I and S2S wireless communications. Finally, the communication performance is evaluated according to the channel measurement and characterization analysis. The research results can be a reference for the construction of maritime communication networks.@en

This project explored the integrated use of satellite, ground observations and hydrological distributed models to support water resources assessment and monitoring in High Mountain Asia (HMA). Hydrological data products were generated taking advantage of the synergies of European and Chinese data assets and space-borne observation systems. Energy-budget-based glacier mass balance and hydrological models driven by satellite observations were developed. These models can be applied to describe glacier-melt contribution to river flow. Satellite hydrological data products were used for forcing, calibration, validation and data assimilation in distributed river basin models. A pilot study was carried out on the Red River basin. Multiple hydrological data products were generated using the data collected by Chinese satellites. A new Evapo-Transpiration (ET) dataset from 2000 to 2018 was generated, including plant transpiration, soil evaporation, rainfall interception loss, snow/ice sublimation and open water evaporation. Higher resolution data were used to characterize glaciers and their response to environmental forcing. These studies focused on the Parlung Zangbo Basin, where glacier facies were mapped with GaoFeng (GF), Sentinal-2/Multi-Spectral Imager (S2/MSI) and Landsat8/Operational Land Imager (L8/OLI) data. The geodetic mass balance was estimated between 2000 and 2017 with Zi-Yuan (ZY)-3 Stereo Images and the SRTM DEM. Surface velocity was studied with Landsat5/Thematic Mapper (L5/TM), L8/OLI and S2/MSI data over the period 2013–2019. An updated method was developed to improve the retrieval of glacier albedo by correcting glacier reflectance for anisotropy, and a new dataset on glacier albedo was generated for the period 2001–2020. A detailed glacier energy and mass balance model was developed with the support of field experiments at the Parlung No. 4 Glacier and the 24 K Glacier, both in the Tibetan Plateau. Besides meteorological measurements, the field experiments included glaciological and hydrological measurements. The energy balance model was formulated in terms of enthalpy for easier treatment of water phase transitions. The model was applied to assess the spatial variability in glacier melt. In the Parlung No. 4 Glacier, the accumulated glacier melt was between 1.5 and 2.5 m w.e. in the accumulation zone and between 4.5 and 6.0 m w.e. in the ablation zone, reaching 6.5 m w.e. at the terminus. The seasonality in the glacier mass balance was observed by combining intensive field campaigns with continuous automatic observations. The linkage of the glacier and snowpack mass balance with water resources in a river basin was analyzed in the Chiese (Italy) and Heihe (China) basins by developing and applying integrated hydrological models using satellite retrievals in multiple ways. The model FEST-WEB was calibrated using retrievals of Land Surface Temperature (LST) to map soil hydrological properties. A watershed model was developed by coupling ecohydrological and socioeconomic systems. Integrated modeling is supported by an updated and parallelized data assimilation system. The latter exploits retrievals of brightness temperature (Advanced Microwave Scanning Radiometer, AMSR), LST (Moderate Resolution Imaging Spectroradiometer, MODIS), precipitation (Tropical Rainfall Measuring Mission (TRMM) and FengYun (FY)-2D) and in-situ measurements. In the case study on the Red River Basin, a new algorithm has been applied to disaggregate the SMOS (Soil Moisture and Ocean Salinity) soil moisture retrievals by making use of the correlation between evaporative fraction and soil moisture.@en

Rainfall is one of the most influential climatic factors on regional development and environment, and changes in rainfall intensity are of specific concern. In the Huaihe River Valley (HRV), heavy rainfall is a primary trigger of floods. However, the difference in the origin of moisture contributed to heavy rainfall and light rainfall is rarely studied and not entirely understood. This study analyzes the rainfall moisture sources in association with different categories of rainfall intensity over the HRV during 1980–2018 using the Water Accounting Model with ERA-Interim reanalysis and precipitation observations from China Meteorological Administration. The results show that the moisture for the HRV summer rainfall is mainly from terrestrial subregion (40%), the Indian Ocean (27%), the Pacific Ocean (25%), and the local HRV (8%). In addition, moisture sources differ substantially between light and heavy rainfall. Specifically, the local HRV contributes more moisture to light rainfall (12%) compared to heavy rainfall (4%), whereas the Indian Ocean contributes more to heavy rainfall (33%) than to light rainfall (20%). The grids located in the southern source region make higher contribution ratio in heavy rainfall than in light rainfall. These results suggest that moisture from distant oceanic areas, especially the Indian Ocean, plays a crucial role in intense summer rainfall, whereas moisture from the land sources covering local grids plays a dominant role in light rainfall in the HRV.@en

This paper studies the demand-supply imbalance problem for one-way carsharing systems under a combination of pricing strategy, relocations and access trips considering stochastic demand. A novel concept of a virtual zone is utilized to capture vehicle relocation range and client walking or biking distance constraints in one-way carsharing systems. The vehicle imbalance problem is further addressed by combining a long-term pricing strategy and real-time vehicle relocations in a two-stage stochastic programming model. In the first stage, the tactical decisions including fleet size and trip price are optimized, while anticipating the operational costs from the second stage. The second stage optimizes operational decisions under uncertain demand including vehicle relocations conditional on the tactical decisions in stage one. The model aims to maximize the profit of a carsharing company considering the fleet costs calculated in stage one and the expected operational costs and revenue obtained in stage two. A dedicated gradient search algorithm is developed to solve the two-stage stochastic programming and results are compared to a genetic algorithm and an iterated local search algorithm. The proposed model and corresponding solution approach are applied to a large-scale network with 50 zones and over 1000 vehicles in Suzhou, China. The application allows us to attain additional operational insight. Results suggest that increased prices for high demand stations during peak hours reduce demand while maintaining profitability of the system. It is also found that the real-time vehicle relocations and flexibility of clients to pick up vehicles at farther stations can increase demand service rate by as much as 10%.@en

The recent growth and deepening of inland lakes in the Tibetan Plateau (TP) may be a salient indicator of the consequences of climate change. The seasonal dynamics of these lakes is poorly understood despite this being potentially crucial for disentangling contributions from glacier melt and precipitation, which are all sensitive to climate, to lake water budget. Using in situ observations, satellite altimetry and gravimetry data, we identified two patterns of lake level seasonality. In the central, northern, and northeastern TP, lake levels are characterized by considerable increases during warm seasons and decreases during cold seasons, which is consistent with regional mass changes related to monsoon precipitation and evaporation. In the northwestern TP, however, lake levels exhibit dramatic increases during both warm and cold seasons, which deviate from regional mass changes. This appears to be more connected with high spring snowfall and large summer glacier melt. The variable lake level response to different drivers indicates heterogeneous sensitivity to climate change between the northwestern TP and other regions.@en

Exploration of advanced solid electrolytes with good interfacial stability toward electrodes is a highly relevant research topic for all-solid-state batteries. Here, we report PCL/SN blends integrating with PAN-skeleton as solid polymer electrolyte prepared by a facile method. This polymer electrolyte with hierarchical architectures exhibits high ionic conductivity, large electrochemical windows, high degree flexibility, good flame-retardance ability, and thermal stability (workable at 80 °C). Additionally, it demonstrates superior compatibility and electrochemical stability toward metallic Li as well as LiFePO4 cathode. The electrolyte/electrode interfaces are very stable even subjected to 4.5 V at charging state for long time. The LiFePO4/Li all-solid-state cells based on this electrolyte deliver high capacity, outstanding cycling stability, and superior rate capability better than those based on liquid electrolyte. This solid polymer electrolyte is eligible for next generation high energy density all-solid-state batteries.@en

Full-spectrum ranging from sub-6 GHz to THz and visible light will be exploited in 6G in order to reach unprecedented key-performance-indica-tors. However, an extraordinary amount of energy will be consumed by network infrastructure, while functions of massively deployed Internet of Everything (IoE) devices are limited by embedded batteries. Therefore, energy self-sustainable (ESS) 6G is proposed in this article. First of all, it may achieve network-wide energy efficiency by exploiting cell-free and airborne access networks as well as by implementing intelligent reflecting surfaces (IRSs). Second, by exploiting radio-frequency/visible-light signals for on-demand wireless information and energy provision (WIEP) and for enabling passive backscatter communication, 'zero-energy' IoE devices may become a reality. Furthermore, IoE devices actively adapt their transceivers for better performance to a dynamic environment. Case studies of cell-free and IRS based WIEP are provided for demonstrating the advantage of our proposed architecture in terms of energy self-sustainability. This article aims to provide a first glance at primary designing principles of ESS-6G.@en