Bankfull Frequency in Rivers

Agouridis, Carmen T.

doi:10.1201/b16683-4

Cited by 3 publications

(1 citation statement)

References 32 publications

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“…In most stable alluvial channels, it is generally accepted that the recurrence of Q b ranges between 1 and 2 years, expressed in annual series [27,[32][33][34][35][36]. Dury [37] considered that the return period of Q b was equal to 1.58 years, the value corresponding to the most probable value of the annual maximum in the Gumbel distribution.…”

Section: Bankfull Discharges Of a Selection Of Rivers In The Meuse Anmentioning

confidence: 99%

Return Period of Characteristic Discharges from the Comparison between Partial Duration and Annual Series, Application to the Walloon Rivers (Belgium)

Campenhout

Houbrechts

Peeters

et al. 2020

Water

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The determination of the return period of frequent discharges requires the definition of flood peak thresholds. Unlike daily data, the volume of data to be processed with the generalization of hourly data loggers or even with an even finer temporal resolution quickly becomes too large to be managed by hand. We therefore propose an algorithm that automatically extracts flood characteristics to compute partial series return periods based on hourly series of flow rates. Thresholds are defined through robust analysis of field observation-independent data to obtain five independent flood peaks per year in order to bypass the 1-year limit of annual series. Peak over thresholds were analyzed using both Gumbel’s graphical method and his ordinary moments method. Hydrological analyses exhibit the value in the convergence point revealed by this dual method for floods with a recurrence interval around 5 years. Pebble-bedded rivers on impervious substratum (Ardenne rivers) presented an average bankfull discharge return period of around 0.6 years. In the absence of field observation, the authors have defined the bankfull discharge as the Q0.625 computed with partial series. Annual series computations allow Q100 discharge determination and extreme floods recurrence interval estimation. A comparison of data from the literature allowed for the confirmation of the value of Myer’s rating at 18, and this value was used to predict extreme floods based on the area of the watershed.

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Section: Bankfull Discharges Of a Selection Of Rivers In The Meuse Anmentioning

confidence: 99%

Return Period of Characteristic Discharges from the Comparison between Partial Duration and Annual Series, Application to the Walloon Rivers (Belgium)

Campenhout

Houbrechts

Peeters

et al. 2020

Water

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Conversion Options for Mining-Affected Lands and Waters in Appalachia

Zipper

Agouridis

Barton

et al. 2020

Appalachia's Coal-Mined Landscapes

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River Extraction under Bankfull Discharge Conditions Based on Sentinel-2 Imagery and DEM Data

Wang

Qin

et al. 2021

Remote Sensing

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River discharge and width, as essential hydraulic variables and hydrological data, play a vital role in influencing the water cycle, driving the resulting river topography and supporting ecological functioning. Insights into bankfull river discharge and bankfull width at fine spatial resolutions are essential. In this study, 10-m Sentinel-2 multispectral instrument (MSI) imagery and digital elevation model (DEM) data, as well as in situ discharge and sediment data, are fused to extract bankfull river widths on the upper Yellow River. Using in situ cross-section morphology data and flood frequency estimations to calculate the bankfull discharge of 22 hydrological stations, the one-to-one correspondence relationship between the bankfull discharge data and the image cover data was determined. The machine learning (ML) method is used to extract water bodies from the Sentinel-2 images in the Google Earth Engine (GEE). The mean overall accuracy was above 0.87, and the mean kappa value was above 0.75. The research results show that (1) for rivers with high suspended sediment concentrations, the water quality index (SRMIR-Red) constitutes a higher contribution; the infrared band performs better in areas with greater amounts of vegetation coverage; and for rivers in general, the water indices perform best. (2) The effective river width of the extracted connected rivers is 30 m, which is 3 times the image resolution. The R2, root mean square error (RMSE), and mean bias error (MBE) of the estimated river width values are 0.991, 7.455 m, and −0.232 m, respectively. (3) The average river widths of the single-thread sections show linear increases along the main stream, and the R2 value is 0.801. The river width has a power function relationship with bankfull discharge and the contributing area, i.e., the downstream hydraulic geometry, with R2 values of 0.782 and 0.630, respectively. More importantly, the extracted river widths provide basic data to analyze the spatial distribution of bankfull widths along river networks and other applications in hydrology, fluvial geomorphology, and stream ecology.

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Bankfull Frequency in Rivers

Cited by 3 publications

References 32 publications

Return Period of Characteristic Discharges from the Comparison between Partial Duration and Annual Series, Application to the Walloon Rivers (Belgium)

Return Period of Characteristic Discharges from the Comparison between Partial Duration and Annual Series, Application to the Walloon Rivers (Belgium)

Conversion Options for Mining-Affected Lands and Waters in Appalachia

River Extraction under Bankfull Discharge Conditions Based on Sentinel-2 Imagery and DEM Data

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