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Abstract Non‐perennial streams, which lack year‐round flow, are widespread globally. Identifying the sources of water that sustain flow in non‐perennial streams is necessary to understand their potential impacts on downstream water resources, and guide water policy and management. Here, we used water isotopes (δ18O and δ2H) and two different modeling approaches to investigate the spatiotemporal dynamics of young water fractions (Fyw) in a non‐perennial stream network at Konza Prairie (KS, USA) during the 2021 summer dry‐down season, as well as over several years with varying hydrometeorological conditions. Using a Bayesian model, we found a substantial amount of young water (Fyw: 39.1–62.6%) sustained flows in the headwaters and at the catchment outlet during the 2021 water year, while 2015–2022 young water contributions estimated using sinusoidal models indicated smallerFywamounts (15.3% ± 5.7). Both modeling approaches indicate young water releases are highly sensitive to hydrological conditions, with stream water shifting to older sources as the network dries. The shift in water age suggests a shift away from rapid fracture flow toward slower matrix flow that creates a sustained but localized surface water presence during late summer and is reflected in the annual dynamics of water age at the catchment outlet. The substantial proportion of young water highlights the vulnerability of non‐perennial streams to short‐term hydroclimatic change, while the late summer shift to older water reveals a sensitivity to longer‐term changes in groundwater dynamics. Combined, this suggests that local changes may propagate through non‐perennial stream networks to influence downstream water availability and quality.
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Communication Distance and Bayesian Inference in Non‐Perennial Streams
Non‐perennial streams are receiving increased attention from researchers, however, suitable methods for measuring their hydrologic connectivity remain scarce. To address this deficiency, we developed Bayesian statistical approaches for measuring both average active stream length, and a new metric called average communication distance. Average communication distance is a theoretical increasedeffective distancethat stream‐borne materials must travel, given non‐continuous streamflow. Because it is the product of the inverse probability of surface water presence and stream length, the average communication distance of a non‐perennial stream segment will be greater than its actual physical length. As an application we considered Murphy Creek, a simple non‐perennial stream network in southwestern Idaho, USA. We used surface water presence/absence data obtained in 2019, and priors for the probability of surface water, based on predictions from an existing regional United States Geological Survey model. Average communication distance posterior distributions revealed locations where effective stream lengths increased dramatically due to flow rarity. We also found strong seasonal (spring, summer, fall) differences in network‐level posterior distributions of both average stream length and average communication distance. Our work demonstrates the unique perspectives concerning network drying provided by communication distance, and demonstrates the general usefulness of Bayesian approaches in the analysis of non‐perennial streams.
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- Award ID(s):
- 1653998
- PAR ID:
- 10527273
- Publisher / Repository:
- American Geophysical Union
- Date Published:
- Journal Name:
- Water Resources Research
- Volume:
- 59
- Issue:
- 11
- ISSN:
- 0043-1397
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Journal Article:
- https://doi.org/10.1029/2023WR034513
