Evidence map›Paper›PMID 33041380›Full record

ArticleWater resources research2020

The Stream Length Duration Curve: A Tool for Characterizing the Time Variability of the Flowing Stream Length.

G Botter, N Durighetto

Abstract read
In one paragraph

Article in Water resources research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Article
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  9. Ecohydrology 2.0.Rendiconti Lincei. Scienze fisiche e naturali · 2022
    Review
  10. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

G BotterDepartment of Civil, Environmental and Architectural Engineering University of Padua Padua Italy.ORCID https://orcid.org/0000-0003-0576-8847
N DurighettoDepartment of Civil, Environmental and Architectural Engineering University of Padua Padua Italy.ORCID https://orcid.org/0000-0002-6081-1580

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In spite of the importance of stream network dynamics for hydrology, ecology, and biogeochemistry, there is limited availability of analytical tools suitable for characterizing the temporal variability of the active fraction of river networks. To fill this gap, we introduce the concept of Stream Length Duration Curve (SLDC), the inverse of the exceedance probability of the total length of active streams. SLDCs summarize efficiently the effect of hydrological variability on the length of the flowing streams under a variety of settings. A set of stochastic network models is developed to link the features of the local hydrological status of the network nodes with the shape of the SLDC. We show that the mean network length is dictated by the mean persistency of the nodes, whereas the shape of the SLDC is driven by the spatial distribution of the local persistencies and their network-scale spatial correlation. Ten field surveys performed in 2018 were used to estimate the empirical SLDC of the Valfredda river (Italy), which was found to be steep and regular-indicating a pronounced sensitivity of the active stream length to the underlying hydrological conditions. Available observations also suggest that the activation of temporary reaches during network expansion is hierarchical, from the most to the least persistent stretches. Under these circumstances, the SLDC corresponds to the spatial Cumulative Distribution Function of the nodes persistencies. The study provides a sound theoretical basis for the analyses of network dynamics in temporary rivers.

Indexed as

network dynamicsSLDCstochastic modelingStream Length Duration Curvestream networktemporary streams

Identifiers

PMID33041380
PMCPMC7540174

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.