Protocol for extracting flow hydrograph shape metrics for use in time-series flood hydrology analysis.

The shape characteristics of flow hydrographs hold essential information for understanding, monitoring and assessing changes in flow and flood hydrology at reach and catchment scales. However, the analysis of individual hydrographs is time consuming, making the analysis of hundreds or thousands of t...

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Main Authors: Amir Mohammad Arash, Kirstie Fryirs, Timothy J Ralph
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2025-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0315796
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author Amir Mohammad Arash
Kirstie Fryirs
Timothy J Ralph
author_facet Amir Mohammad Arash
Kirstie Fryirs
Timothy J Ralph
author_sort Amir Mohammad Arash
collection DOAJ
description The shape characteristics of flow hydrographs hold essential information for understanding, monitoring and assessing changes in flow and flood hydrology at reach and catchment scales. However, the analysis of individual hydrographs is time consuming, making the analysis of hundreds or thousands of them unachievable. A method or protocol is needed to ensure that the datasets being generated, and the metrics produced, have been consistently derived and validated. In this lab protocol, we present workflows in Python for extracting flow hydrographs with any available temporal resolution from any Open Access or publicly available gauging station records. The workflow identifies morphologically-defined flow and flood types (i.e. in-channel fresh, high flow and overbank flood) and uses them to classify hydrographs. It then calculates several at-a-station and upstream-to-downstream hydrograph shape metrics including kurtosis, skewness, peak hydrograph stage, peak arrival time, rate-of-rise, peak-to-peak travel time, flood wave celerity, flood peak attenuation, and flood wave attenuation index. Some metrics require GIS-derived data, such as catchment area and upstream-to-downstream channel distance between gauges. The output dataset provides quantified hydrograph shape metrics which can be used to track changes in flow and flood hydrographs over time, or to characterise the flow and flood hydrology of catchments and regions. The workflows are flexible enough to allow for additional hydrograph shape indicators to be added or swapped out, or to use a different hydrograph classification method that suits local conditions. The protocol could be considered a change detection tool to identify where changes in hydrology are occurring and where to target more sophisticated modelling exercises to explain the changes detected. We demonstrate the workflow using 117 Open Access gauging station records that are available for coastal rivers of New South Wales (NSW), Australia.
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spelling doaj-art-ae3bc4a5ec7b4a8280be72e7e37da5132025-01-17T05:31:20ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01201e031579610.1371/journal.pone.0315796Protocol for extracting flow hydrograph shape metrics for use in time-series flood hydrology analysis.Amir Mohammad ArashKirstie FryirsTimothy J RalphThe shape characteristics of flow hydrographs hold essential information for understanding, monitoring and assessing changes in flow and flood hydrology at reach and catchment scales. However, the analysis of individual hydrographs is time consuming, making the analysis of hundreds or thousands of them unachievable. A method or protocol is needed to ensure that the datasets being generated, and the metrics produced, have been consistently derived and validated. In this lab protocol, we present workflows in Python for extracting flow hydrographs with any available temporal resolution from any Open Access or publicly available gauging station records. The workflow identifies morphologically-defined flow and flood types (i.e. in-channel fresh, high flow and overbank flood) and uses them to classify hydrographs. It then calculates several at-a-station and upstream-to-downstream hydrograph shape metrics including kurtosis, skewness, peak hydrograph stage, peak arrival time, rate-of-rise, peak-to-peak travel time, flood wave celerity, flood peak attenuation, and flood wave attenuation index. Some metrics require GIS-derived data, such as catchment area and upstream-to-downstream channel distance between gauges. The output dataset provides quantified hydrograph shape metrics which can be used to track changes in flow and flood hydrographs over time, or to characterise the flow and flood hydrology of catchments and regions. The workflows are flexible enough to allow for additional hydrograph shape indicators to be added or swapped out, or to use a different hydrograph classification method that suits local conditions. The protocol could be considered a change detection tool to identify where changes in hydrology are occurring and where to target more sophisticated modelling exercises to explain the changes detected. We demonstrate the workflow using 117 Open Access gauging station records that are available for coastal rivers of New South Wales (NSW), Australia.https://doi.org/10.1371/journal.pone.0315796
spellingShingle Amir Mohammad Arash
Kirstie Fryirs
Timothy J Ralph
Protocol for extracting flow hydrograph shape metrics for use in time-series flood hydrology analysis.
PLoS ONE
title Protocol for extracting flow hydrograph shape metrics for use in time-series flood hydrology analysis.
title_full Protocol for extracting flow hydrograph shape metrics for use in time-series flood hydrology analysis.
title_fullStr Protocol for extracting flow hydrograph shape metrics for use in time-series flood hydrology analysis.
title_full_unstemmed Protocol for extracting flow hydrograph shape metrics for use in time-series flood hydrology analysis.
title_short Protocol for extracting flow hydrograph shape metrics for use in time-series flood hydrology analysis.
title_sort protocol for extracting flow hydrograph shape metrics for use in time series flood hydrology analysis
url https://doi.org/10.1371/journal.pone.0315796
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AT timothyjralph protocolforextractingflowhydrographshapemetricsforuseintimeseriesfloodhydrologyanalysis