Artificial water bodies are a major source of methane and an important contributor to flooded land greenhouse gas (GHG) emissions. Past studies focussed on large water supply or hydropower reservoirs with small artificial water bodies (ponds) almost completely ignored. This regional study demonstrated ponds accounted for one-third of flooded land surface area and emitted over 1.6 million t CO₂ eq. yr⁻¹ (10 % of land use sector emissions). Ponds should be included in regional GHG inventories.

We analyze changes in catchment evaporation estimated from the water balances of 156 catchments in Austria over 1977–2014, as well as the possible causes of these changes. Our results show that catchment evaporation increased on average by 29 ± 14 mm yr⁻¹ decade⁻¹. We attribute this increase to changes in atmospheric demand (based on reference and pan evaporation), changes in vegetation (quantified by a satellite-based vegetation index), and changes in precipitation.

Evaporation from wetlands, lakes and irrigation areas needs to be measured to understand water scarcity. So far, this has only been possible for small regions. Here, we develop a solution that can be applied at a very high resolution globally by making use of satellite observations. Our results show that 16% of global water resources evaporate before reaching the ocean, mostly from surface water. Irrigation water use is less than 1% globally but is a very large water user in several dry basins.

Groundwater is a significant water resource for humans and for groundwater-dependent vegetation. Several challenges to managing both groundwater resources and dependent vegetation include defining the location of dependent vegetation, the rate of groundwater use, and the depth of roots accessing groundwater. In this study we demonstrate a novel application of measurements of stable isotopes of carbon that can be used to identify the location, the rooting depth, and the rate of groundwater use.

Satellite soil moisture products can provide critical information on incipient droughts and the interplay between vegetation and water availability. However, time-variant systematic errors in the soil moisture products may impede their usefulness. Using a novel statistical approach, we detect such errors (associated with changing vegetation) in the SMAP soil moisture product. The vegetation-associated biases impede drought detection and the quantification of vegetation-water interactions.