Structural characteristics and spatiotemporal changes of a reticular river network based on complex network theory

Journal of Hydrology, Journal Year: 2024, Volume and Issue: 638, P. 131577 - 131577

Published: June 24, 2024

Language: Английский

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STICr: An open-source package and workflow for Stream Temperature, Intermittency, and Conductivity (STIC) data

Environmental Modelling & Software, Journal Year: 2025, Volume and Issue: unknown, P. 106484 - 106484

Published: April 1, 2025

Language: Английский

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Short‐term dynamics of drainage density based on a combination of channel flow state surveys and water level measurements

Hydrological Processes, Journal Year: 2023, Volume and Issue: 37(12)

Published: Dec. 1, 2023

Abstract Headwater streams often experience intermittent flow. Consequently, the flowing drainage network expands and contracts density (DD) varies over time. Monitoring DD dynamics is essential to understand processes controlling it. However, our knowledge of event‐scale limited because high spatial temporal resolution data on remain sparse. Therefore, team monitored hydrologic variables in two 5‐ha headwater catchments Swiss pre‐Alps summer 2021, through mapping surveys flow state a wireless streamwater level sensor network. We combined sources calculate at event‐time scale. Our so‐called CEASE method assumes that channel reach occurs above set water thresholds, it determined DDs with accuracies >94%. responses events differed for catchments, despite their proximity similar size. ranged from 2.7 32.2 km −2 flatter catchment (average slope: 15°). For this catchment, discharge‐DD relationship became steeper when exceeded 20 increased substantially relatively small increases discharge. rainfall during dry conditions, showed counterclockwise hysteresis, likely due initially groundwater discharge area near outlet; once stopped, remained streamflow recession rising levels throughout catchment. wet responded synchronously. In 24°), varied only 7.8 14.6 there was no hysteresis or threshold behaviour relationship, multiple springs maintained monitoring period. These results highlight variability its across catchments.

Language: Английский

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Communication Distance and Bayesian Inference in Non‐Perennial Streams

Water Resources Research, Journal Year: 2023, Volume and Issue: 59(11)

Published: Nov. 1, 2023

Abstract 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 both average active stream length, and a new metric called communication distance. Average distance is theoretical effective that stream‐borne materials must travel, given non‐continuous streamflow. Because it the product of inverse probability surface water presence non‐perennial segment will be greater than its actual physical length. As an application considered Murphy Creek, simple network in southwestern Idaho, USA. We used presence/absence data obtained 2019, priors water, based on predictions existing regional United States Geological Survey model. posterior distributions revealed locations where lengths dramatically due to flow rarity. also found strong seasonal (spring, summer, fall) differences network‐level length Our work demonstrates unique perspectives concerning drying provided by distance, general usefulness analysis streams.

Language: Английский

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streamDAG: Analytical Methods for Stream DAGs

Published: Aug. 21, 2023

Language: Английский

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