Groundwatersheds of protected areas reveal globally overlooked risks and opportunities

Serrano, David; Huggins, Xander; Gleeson, Tom; Zipper, Samuel C.; Jehn, Florian; Rohde, Melissa M.; Abell, Robin; Vigerstøl, Kari; Hartmann, Andreas

doi:10.31223/x59354

Cited by 1 publication

(1 citation statement)

References 39 publications

(40 reference statements)

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“…In principle, one could model subsurface to surface hydrologic fluxes (e.g., vertical connectivity) and/or subsurface flow using these approaches, by considering the presence/absence of subsurface water with respect todepth or gradient thresholds. In these efforts, the delineation of spatial network structures in the subsurface may be difficult in some locations due to the challenges of defining groundwater arcs and nodes as well as delineating the extent of watersheds (Huggins et al, 2022).…”

Section: Uncertainties and Extensionsmentioning

confidence: 99%

The Communication Distance of Non-Perennial Streams

Aho¹,

Derryberry²,

Godsey³

et al. 2023

Preprint

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We developed Bayesian statistical approaches to assess non-perennial stream network connectivity. Our new methods allow: 1) consideration of changes to both local (stream segment) and global (stream network) connectivity over time, 2) incorporation of prior information from different data sources, and 3) straightforward computation of the posterior distributions of both active stream length and a new metric called communication distance. Communication distance measures the effective stream length for the movement of materials, including water and solutes, from upstream to downstream sites. Communication distance posteriors require the inverse-beta probability density function whose form had not been previously derived. The inverse-beta distribution can be used to represent the rarity of surface water presence compared to a perennial stream, thus clarifying bottlenecking propensities for stream segments. As an application, we considered Murphy Creek, a simple stream network in southwestern Idaho, USA. Our models used surface water presence/absence data from 2019, and priors based on existing regional USGS model predictions for surface water. Murphy Creek probabilities for surface water presence were heterogeneous in space and time, and were likely driven by fine-scale spatial variations in shallow subsurface hydraulic conductivity. Strong seasonal (spring, summer, fall) temporal differences were evident in network-level posterior distributions of both stream length and communication distance. Specifically, stream lengths were shorter and more variable in the summer and fall than in the spring. The novel communication distance posteriors were multimodal, platykurtic, and negatively skewed for spring, summer and fall, respectively, revealing bottlenecking effects that varied over time.

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Section: Uncertainties and Extensionsmentioning

confidence: 99%