COVID-19 (Corona Virus Disease 2019) is globally spreading and the international cooperation is urgently required in joint prevention and control of the epidemic. Using the Maximum-Hasting (MH) parameter estimation method and the modified Susceptible Exposed Infectious Recovered (SEIR) model, the spread of the epidemic under three intervention scenarios (suppression, mitigation, mildness) is simulated and predicted in South Africa, Egypt, and Algeria, where the epidemic situations are severe. The studies are also conducted in Nigeria, Senegal and Kenya, where the epidemic situations are growing rapidly and the socioeconomic are relatively underdeveloped , resulting in more difficulties in preventing the epidemic. Results indicated that the epidemic can be basically controlled in late April with strict control of scenario one, manifested by the circumstance in the South Africa and Senegal. Under moderate control of scenario two, the number of infected people will increase by 1.43-1.55 times of that in scenario one, the date of the epidemic being controlled will be delayed by about 10 days, and Algeria, Nigeria, and Kenya are in accordance with this situation. In the third scenario of weak control, the epidemic will be controlled by late May, the total number of infected cases will double that

Research on land surface processes at the catchment scale has drawn much attention over the past few decades, and a number of watershed observatories have been established worldwide. The Heihe River Basin (HRB), which contains the second largest inland river in China, is an ideal natural field experimental area for investigation of land surface processes involving diverse landscapes and the coexistence of cold and arid regions. The Heihe Integrated Observatory Network was established in 2007. For long-term observations, a hydrometeorological observatory, ecohydrological wireless sensor network, and satellite remote sensing are now in operation. In 2012, a multiscale observation experiment on evapotranspiration over heterogeneous land surfaces was conducted in the midstream region of the HRB, which included a flux observation matrix, wireless sensor network, airborne remote sensing, and synchronized ground measurements. Under an open data policy, the datasets have been publicly released following careful data processing and quality control. The outcomes highlight the integrated research on land surface processes in the HRB and include observed trends, scaling methods, high spatiotemporal resolution remote sensing products, and model-data integration in the HRB, all of which are helpful to other endorheic basins in the "Silk Road Economic Belt." Henceforth, the goal of the Heihe Integrated Observatory Network is to develop an intelligent monitoring system that incorporates ground-based observatory networks, unmanned aerial vehicles, and multi-source satellites through the Internet of Things technology. Furthermore, biogeochemical processes observation will be improved, and the study of integrating ground observations, remote sensing, and large-scale models will be promoted further.

We introduce a multiscale dataset obtained from Heihe Watershed Allied Telemetry Experimental Research (HiWATER) in an oasis-desert area in 2012. Upscaling of eco-hydrological processes on a heterogeneous surface is a grand challenge. Progress in this field is hindered by the poor availability of multiscale observations. HiWATER is an experiment designed to address this challenge through instrumentation on hierarchically nested scales to obtain multiscale and multidisciplinary data. The HiWATER observation system consists of a flux observation matrix of eddy covariance towers, large aperture scintillometers, and automatic meteorological stations; an eco-hydrological sensor network of soil moisture and leaf area index; hyper-resolution airborne remote sensing using LiDAR, imaging spectrometer, multi-angle thermal imager, and L-band microwave radiometer; and synchronical ground measurements of vegetation dynamics, and photosynthesis processes. All observational data were carefully quality controlled throughout sensor calibration, data collection, data processing, and datasets generation. The data are freely available at figshare and the Cold and Arid Regions Science Data Centre. The data should be useful for elucidating multiscale eco-hydrological processes and developing upscaling methods.

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