Adaptable and comprehensive vulnerability assessments for water resources systems in a rapidly changing world.

Comprehensive and adaptive approaches to vulnerability assessment are crucial for guiding effective adaptation in global water resources systems. A common approach to quantify vulnerability is through indicators, which capture the 'spirit of vulnerability' while retaining practical ease-of-use benefits. However, a comprehensive meta-analysis of reveals two specific limitations of global indicator-based vulnerability assessments for water resources systems: 1) vulnerability is influenced by complex interactions among multi-domain factors, for which indicator quality and data vary; and 2) vulnerability is dynamic and evolves over time, an aspect overlooked in most approaches.

From Hydrometeorology to River Water Quality: Can a Deep Learning Model Predict Dissolved Oxygen at the Continental Scale?

Dissolved oxygen (DO) reflects river metabolic pulses and is an essential water quality measure. Our capabilities of forecasting DO however remain elusive. Water quality data, specifically DO data here, often have large gaps and sparse areal and temporal coverage.

Humidity determines snowpack ablation under a warming climate.

Climate change is altering historical patterns of snow accumulation and melt, threatening societal frameworks for water supply. However, decreases in spring snow water equivalent (SWE) and changes in snowmelt are not ubiquitous despite widespread warming in the western United States, highlighting the importance of latent and radiant energy fluxes in snow ablation. Here we demonstrate how atmospheric humidity and solar radiation interact with warming temperature to control snowpack ablation at 462 sites spanning a gradient in mean winter temperature from -8.

Hydrogeomorphology explains acidification-driven variation in aquatic biological communities in the Neversink Basin, USA.

Describing the distribution of aquatic habitats and the health of biological communities can be costly and time-consuming; therefore, simple, inexpensive methods to scale observations of aquatic biota to watersheds that lack data would be useful. In this study, we explored the potential of a simple "hydrogeomorphic" model to predict the effects of acid deposition on macroinvertebrate, fish, and diatom communities in 28 sub-watersheds of the 176-km2 Neversink River basin in the Catskill Mountains of New York State. The empirical model was originally developed to predict stream-water acid neutralizing capacity (ANC) using the watershed slope and drainage density.

Variation in root density along stream banks.

While it is recognized that vegetation plays a significant role in stream bank stabilization, the effects are not fully quantified. The study goal was to determine the type and density of vegetation that provides the greatest protection against stream bank erosion by determining the density of roots in stream banks. To quantify the density of roots along alluvial stream banks, 25 field sites in the Appalachian Mountains were sampled.