As basic data, the river networks and water resources zones (WRZ) are critical for planning, utilization, development, conservation and management of water resources. Currently, the river network and WRZ of world are most obtained based on digital elevation model data automatically, which are not accuracy enough, especially in plains. In addition, the WRZ code is inconsistent with the river network, hindering the efficiency of data in hydrology and water resources research. Based on the global 90-meter DEM data combined with a large number of auxiliary data, this paper proposed a series of methods for generating river network and water resources zones, and then obtained high-precision global river network and corresponding WRZs at level 1 to 4. The dataset provides generated rivers with high prevision and more accurate position, reasonable basin boundaries especially in inland and plain area, also the first set of global WRZ at level 1 to 4 with unified code. It can provide an important basis and support for reasonable use of water resources and sustainable social development in the world.
The freezing–thawing cycle is a basic feature of a frozen soil ecosystem, and it affects the growth of alpine vegetation both directly and indirectly. As the climate changes, the freezing–thawing mode, along with its impact on frozen soil ecosystems, also changes. In this research, the freezing–thawing cycle of the Nagqu River Basin in the Qinghai–Tibet Plateau was studied. Vegetation growth characteristics and microbial abundance were analyzed under different freezing–thawing modes. The direct and indirect effects of the freezing–thawing cycle mode on alpine vegetation in the Nagqu River Basin are presented, and the changing trends and hazards of the freezing–thawing cycle mode due to climate change are discussed. The results highlight two major findings. First, the freezing–thawing cycle in the Nagqu River Basin has a high-frequency mode (HFM) and a low-frequency mode (LFM). With the influence of climate change, the LFM is gradually shifting to the HFM. Second, the alpine vegetation biomass in the HFM is lower than that in the LFM. Frequent freezing–thawing cycles reduce root cell activity and can even lead to root cell death. On the other hand, frequent freezing–thawing cycles increase microbial (Bradyrhizobium, Mesorhizobium, and Pseudomonas) death, weaken symbiotic nitrogen fixation and the disease resistance of vegetation, accelerate soil nutrient loss, reduce the soil water holding capacity and soil moisture, and hinder root growth. This study provides a complete response mechanism of alpine vegetation to the freezing–thawing cycle frequency while providing a theoretical basis for studying the change direction and impact on the frozen soil ecosystem due to climate change.
Population and water withdrawal data sets are currently faced with difficulties in collecting, processing and verifying multi-source time series, and the spatial distribution characteristics of long series are also relatively lacking. Time series is the basic guarantee for the accuracy of data sets, and the production of long series spatial distribution is a realistic requirement to expand the application scope of data sets. Through the time-consuming and laborious basic processing work, this research focuses on the population and water intake time series, and interpolates and extends them to specific land uses to ensure the accuracy of the time series and the demand of spatially distributed data sets. This research provides a set of population density and water intensity products from 1960 to 2020 distributed to the administrative units or the corresponding regions. The data set fills the gaps in the multi-year data set for the accuracy of population density and the intensity of water withdrawal.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.