Identifying potential hotspots for atmospheric water resource management and source-sink analysis

<p indent="0mm">Traditional water resource management is in the boundary of natural catchments. For catchment water balance, the precipitation is the amount of input, the runoff is the available water resource for society, and evaporation is considered a loss item. However, increasing evidence demonstrates that evaporation in the global terrestrial scale dominates the partition of precipitation, accounting for 60% of precipitation, which is much larger than the amount of runoff (40% of precipitation). In addition, the evaporated water vapor does not disappear, but is likely to fall as precipitation in other areas. The complex cycling and feedback between terrestrial evaporation and precipitation is called terrestrial moisture recycling. Atmospheric water resources can be defined as moisture that evaporates into the atmosphere and eventually falls as terrestrial precipitation. Theoretically, land cover change caused by human activities can directly affect land evaporation, which may affect the downwind precipitation through the terrestrial moisture cycle. However, the travel distance of atmospheric water vapor often exceeds the scale of most basins. Owing to the complexity and even the randomness of moisture recycling, the possibility of atmospheric water resource management is debated and largely untouched in traditional water management. Hence, it is important to identify the potential hotspots for atmospheric water resource management and clarify their complex source-sink relationship. Bridging this knowledge gap is beneficial to integrating atmospheric water resources into the traditional water resource management framework. In this study, based on the framework of precipitationshed, we developed the concept of “core precipitationshed”, which is the most central and influential moisture source region, contributing 40% of precipitation to the target area. The process of obtaining the core precipitation area is as follows: First, the moisture source contribution depth (mm/a) is sorted from largest to smallest, then the cumulative contribution based on this ranking is calculated, and finally the area with a cumulative contribution rate of 40% is classified as the core precipitation area. On a global scale, we used the UTrack moisture recycling dataset with a spatial resolution of 1° × 1° to calculate the core precipitationshed for each grid. Furthermore, we identified potential hotspots for atmospheric water resource management with a relatively small core precipitationshed area (less than 1.25 million km²) and dominant moisture source from the same national territory (more than 95%). The smaller the precipitationshed area, the less area required to manage land use, and the less difficult it is to manage atmospheric water resources. In the core precipitationshed, the higher the moisture contribution ratio from land in the same nation, the larger potential for land cover change, through the development and implementation of land policies. Results show that central China, southeastern Russia, central Democratic Republic of Congo, southern Brazil, western Peru, northwestern USA, and western Canada have larger potential for managing atmospheric water resources. For the potential hotspots, we further analyzed their source and sink characteristics, including national boundaries, land cover, and population. Notably, we identified that China has the largest potential hotspot area for atmospheric water resource management. China not only has the largest and most concentrated core precipitationshed area with the moisture source region from the same national territory but also the most intensive human activities that greatly influence land use and water cycle in both local and downwind regions. This study provides a new perspective to understand China’s water resources in the framework of the global water cycle and has great potential to benefit the conservation and optimization of China’s integrated water resource management.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.