Rina Schumer | Search USGS

USGS2019

The importance of interflow to groundwater recharge in a snowmelt-dominated headwater basin

Understanding the sensitivity of groundwater generation to climate in a mountain system is complicated by the tight coupling of snow dynamics to vegetation and topography. To address these feedbacks, we combine light detection and ranging (LiDAR)-derived snow observations with an integrated hydrologic model to quantify spatially and temporally distributed water fluxes across varying climate conditions in a Colorado River headwater basin. Results indicate that annual groundwater flow is an important and stable source of stream water. However, interflow decreases during drought as a function increased plant water use and the relative fraction of groundwater to streams increases. Seasonal snowmelt and vegetation water use regulate small recharge rates in the lower portions of the basin, but snowmelt transported via interflow from high mountain ridges toward convergent topographic zones defines preferential recharge in the upper subalpine. Recharge in this zone appears decoupled from annual climate variability and resilient to drought.

Colorado↗

USGS2016

Probability distributions of bed load particle velocities, accelerations, hop distances, and travel times informed by Jaynes's principle of maximum entropy

We describe the most likely forms of the probability distributions of bed load particle velocities, accelerations, hop distances, and travel times, in a manner that formally appeals to inferential statistics while honoring mechanical and kinematic constraints imposed by equilibrium transport conditions. The analysis is based on E. Jaynes's elaboration of the implications of the similarity between the Gibbs entropy in statistical mechanics and the Shannon entropy in information theory. By maximizing the information entropy of a distribution subject to known constraints on its moments, our choice of the form of the distribution is unbiased. The analysis suggests that particle velocities and travel times are exponentially distributed and that particle accelerations follow a Laplace distribution with zero mean. Particle hop distances, viewed alone, ought to be distributed exponentially. However, the covariance between hop distances and travel times precludes this result. Instead, the covariance structure suggests that hop distances follow a Weibull distribution. These distributions are consistent with high-resolution measurements obtained from high-speed imaging of bed load particle motions. The analysis brings us closer to choosing distributions based on our mechanical insight.

Journal of Geophysical Research F: Earth Surface↗