Characterizing Space‐Time Channel Network Dynamics in a Mediterranean Intermittent Catchment of Central Italy Combining Visual Surveys and Cameras

Water Resources Research, Journal Year: 2024, Volume and Issue: 60(1)

Published: Jan. 1, 2024

Abstract Non‐perennial streams have a global prevalence, but quantitative knowledge of the temporal dynamics their flowing length—namely extent wet portion stream network—remains limited, as monitoring spatiotemporal configuration channels is challenging in most settings. This work combines high spatial resolution visual surveys and camera‐based approaches to reconstruct space‐time network 3.7 km 2 Mediterranean catchment central Italy. Information on hydrological status derived from 40 field sub‐hourly images collected with 21 stage‐cameras are combined exploiting hierarchical principle. The latter postulates existence Bayesian chain, defined local persistence nodes that dictates wetting/drying order during expansion/retraction cycles network. Our results highlight complexity study area: while number decreases dry season increases season, persistency exhibits highly heterogeneous non‐monotonic pattern, originating dynamically disconnected Despite this heterogeneity, model well approximates evolution state nodes, an accuracy exceeds 99%. Crucially, allows reconstruction even cases which part was not observed. provides novel conceptual approach for poorly accessible sites.

Language: Английский

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Mapping Surface Water Presence and Hyporheic Flow Properties of Headwater Stream Networks With Multispectral Satellite Imagery

Water Resources Research, Journal Year: 2023, Volume and Issue: 59(9)

Published: Aug. 16, 2023

Abstract Growth and contraction of headwater stream networks determine habitat extent, open a window to the hyporheic zone. A fundamental challenge is observation this process: wetted channel extent dynamic in space time, with length varying by orders magnitude over course single storm event catchments. To date, observational data sets are produced from boots‐on‐the‐ground campaigns, drone imaging, or flow presence sensors, which often laborious limited their spatial temporal extents. Here, we evaluate satellite imagery as means detect via machine learning methods trained on local surveys extent. Even where features smaller than imagery's resolution, surface water may be imprinted upon spectral signature an individual pixel. For two catchments northern California minimal riparian canopy cover highly train random forest model RapidEye captured contemporaneously existing predict (accuracy >91%). The used produce length‐discharge (L‐Q) relations calculate spatially distributed estimates capacity exchange. sharp break occurs main stem channels lower order tributaries, resulting stepped L‐Q relationship that cannot traditionally power law models. Remotely sensed powerful tool for mapping at high resolution.

Language: Английский

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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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Integrating spatially-and temporally-heterogeneous data on river network dynamics using graph theory

iScience, Journal Year: 2023, Volume and Issue: 26(8), P. 107417 - 107417

Published: July 23, 2023

The study of non-perennial streams requires extensive experimental data on the temporal evolution surface flow presence across different nodes channel networks. However, consistency and homogeneity available datasets is threatened by empirical burden required to map stream network expansions contractions. Here, we developed a data-driven, graph-theory framework aimed at representing hierarchical structuring dynamics (i.e., order node activation/deactivation during expansion/retraction) through directed acyclic graph. method enables estimation configuration active portion based limited number observed nodes, can be utilized combine with resolutions spatial coverage. A proof-of-concept application seasonally-dry catchment in central Italy demonstrated ability approach reduce effort for monitoring efficiently extrapolate observations space time.

Language: Английский

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Improving calibration of groundwater flow models using headwater streamflow intermittence

Hydrological Processes, Journal Year: 2024, Volume and Issue: 38(6)

Published: June 1, 2024

Abstract Non‐perennial streams play a crucial role in ecological communities and the hydrological cycle. However, key parameters processes involved stream intermittency remain poorly understood. While climatic conditions, geology land use are well identified, assessment modelling of groundwater controls on streamflow intermittence challenge. In this study, we explore new opportunities to calibrate process‐based 3D flow models designed simulate hydrographic network dynamics groundwater‐fed headwaters. Streamflow measurements maps considered together constrain effective hydraulic properties aquifer hydrogeological models. The simulations were then validated using visual observations water presence/absence, provided by national monitoring France (ONDE). We tested methodology two pilot unconfined shallow crystalline catchments, Canut Nançon catchments (Brittany, France). found that both expansion/contraction required simultaneously estimate conductivity porosity with low uncertainties. calibration allowed good prediction intermittency, terms spatial extent. For studied, Nançon, is close reaching 1.5 × 10 −5 m/s 4.5 m/s, respectively. they differ more their storage capacity, estimated at 0.1% 2.2%, Lower capacity leads higher level fluctuations, shorter response times, an increase proportion intermittent reduction perennial flow. This framework for predicting headwater can be deployed improve our understanding different geomorphological, geological contexts. It will benefit from advances remote sensing crowdsourcing approaches generate observational data products high temporal resolution.

Language: Английский

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Eco-hydrological modelling of channel network dynamics—part 2: application to metapopulation dynamics

Royal Society Open Science, Journal Year: 2022, Volume and Issue: 9(11)

Published: Nov. 1, 2022

Temporal variations in the configuration of flowing portion stream networks are observed large majority rivers worldwide. However, ecological implications river network expansions/retractions remain poorly understood, owing to lack computationally efficient modelling tools conceived for long-term simulation dynamics. Here, we couple a stochastic approach channel expansion and retraction (described companion paper) with dynamic version occupancy metapopulation model. The coupled eco-hydrological model is used analyse impact pulsing on species persistence under different hydroclimatic scenarios. Our results unveil existence climate-dependent detrimental effect dynamics spread persistence. This enhanced by dry climates, where flashy expansions retractions channels induce extinction. Survival probabilities particularly reduced settings spatial heterogeneity connectivity pronounced. analysis indicates that accounting temporal variability its fundamental prerequisite analysing in-stream

Language: Английский

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Extending Active Network Length Versus Catchment Discharge Relations to Temporarily Dry Outlets

Water Resources Research, Journal Year: 2024, Volume and Issue: 60(1)

Published: Jan. 1, 2024

Abstract River networks are not steady blue lines drawn in a map, since they continuously change their shape and extent response to climatic drivers. Therefore, the flowing length of rivers ( L ) corresponding catchment‐scale streamflow Q sur co‐evolve dynamically. This paper analyzes relationship between wet channel river basin, formulating general analytical model that includes case temporarily dry outlets. In particular, framework relaxes common assumption when discharge at outlet tends zero upstream approaches zero. Different expressions for law derived cases (a) perennial outlet; (b) non‐perennial dries out only whole network is dry; (c) outlet, experiences surface flow less time than other nodes. all cases, controlled by distribution specific subsurface capacity along network. For outlets, however, relation might depend on an unknown shifting factor. Three real‐world examples presented demonstrate flexibility robustness theory. Our results indicate be empirically observable if significant fraction or some reaches experience longer gauging station. The study provides basis integrating empirical data gathered diverse sites.

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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Statistical evaluation of a long‐memory process using the generalized entropic value‐at‐risk

Environmetrics, Journal Year: 2023, Volume and Issue: 35(4)

Published: Dec. 25, 2023

Abstract The modeling and identification of time series data with a long memory are important in various fields. streamflow discharge is one such example that can be reasonably described as an aggregated stochastic process randomized affine processes where the probability measure, we call it reversion for randomization not directly observable. Accurate measure critical because its omnipresence process. However, accuracy commonly limited by available real‐world data. We resolve this issue proposing novel upper lower bounds statistic interest subject to ambiguity measure. Here, use Tsallis value‐at‐risk (TsVaR) convex risk functional generalize widely used entropic (EVaR) sharp statistical indicator. demonstrate EVaR cannot evaluating key statistics, mean variance, due blowup some exponential integrand. theoretically show TsVaR avoid requires only existence polynomial moment, moment. As demonstration, apply semi‐implicit gradient descent method calculate corresponding Radon–Nikodym derivative actual discharges mountainous river environments.

Language: Английский

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