Revisiting the drivers of at-a-station hydraulic geometry in stream reaches

Morel, Maxime; Tamisier, Vincent; Pella, Hervé; Booker, D. J.; Navrátil, Oldřich; Piégay, Hervé; Gob, Frédéric; Lamouroux, Nicolas

doi:10.1016/j.geomorph.2018.12.007

Cited by 12 publications

(25 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Morel et al (2019) used hydraulic descriptions at Q 50 to compare hydraulic conditions across many reaches at a comparable discharge rate. However, field measurements were made at another discharge rate ( Q m ) than Q 50 .…”

Section: Methodsmentioning

confidence: 99%

“…However, field measurements were made at another discharge rate ( Q m ) than Q 50 . Therefore, Morel et al (2019) proposed to predict the reach characteristics at Q 50 from those at Q m using the following correction common to all reaches:

W_{50} = W_{m} \cdot {(Q_{50} / Q_{m})}^{\tilde{b}},

H_{50} = H_{m} \cdot {(Q_{50} / Q_{m})}^{\tilde{f}},

where W 50 and H 50 are, respectively, reach‐average wetted width and water depth at Q 50 . W m and H m are wetted width and water depth at measurement discharge Q m .…”

Section: Methodsmentioning

confidence: 99%

“…This ratio was judged sufficient given that reach-scale AHG fits well to power laws below bankfull (Lamouroux et al, 1992;Navratil & Albert, 2010). OBS_2Qs data came from applications of the habitat model ESTIMHAB (n = 378; Lamouroux, 2002), from applications of the French national tool of river hydromorphology characterization CARHYCE (n = 88; Gob et al, 2014) and from unpublished surveys borrowing from the two previous methods (ESTIMHAB+; n = 14; see also Morel et al, 2019, for further information about ESTIMHAB and CARHYCE). Other AHG exponents were estimated from applications of hydrodynamic numerical models calibrated in reaches (hereafter, OBS_NUM data).…”

Section: Observed Ahg Exponentsmentioning

confidence: 99%

“…Despite these difficulties to relate AHG to geomorphic features, a recent empirical analysis of data from 492 reaches in France suggested that AHG exponents could be partly predicted from hydraulic characteristics measured at a single discharge: the Froude number of the reach and the ratio of wetted width to bankfull width (Morel et al, 2019). In the same vein, environmental descriptors available in GIS databases (e.g., reach slope and catchment area) partly (although weakly) explained AHG exponents in both France and New Zealand data sets (Morel et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Consistent Theoretical and Empirical Predictions of at‐a‐Station Hydraulic Geometry Exponents in Stream Reaches

Morel

Booker

Gob

et al. 2020

Water Resources Research

Self Cite

View full text Add to dashboard Cite

Reach-scale at-a-station hydraulic geometry (AHG) relationships are power laws that describe variations of reach-averaged water depth, wetted width, and current velocity in stream reaches when discharge varies. Modeling AHG exponents is important, because the variations of hydraulics with discharge in stream networks influence physical habitats of aquatic species, biodiversity, water temperature, nutrient fluxes, and sediment transport. Theoretical approaches indicated that AHG exponents should depend on topographic descriptors of cross sections and roughness elements. Empirical approaches suggested that AHG exponents partly depend on hydraulic characteristics measured at a single discharge. We used a unique data set of AHG observed in 812 stream reaches (obtained from measurements at several discharge rates or from hydrodynamic models) to (1) test the consistency of theoretical and empirical predictions of AHG exponents and (2) test the generality of AHG predictions across rivers of different countries with variable landscape settings. We found that observed AHG depended on topographic predictors (describing cross-section shape and substrate size) as expected from theory. However, AHG exponents were better predicted by empirical hydraulic characteristics of reaches: the ratio of wetted width to bankfull width and the reach Froude number. The effects of hydraulic variables were consistent with those of topographic predictors. In addition, relations between AHG and hydraulic predictors were significant and with similar direction in different data sets. Despite limited explanatory power, our results help identifying general drivers of AHG exponents. Their application still requires measurements at a single discharge rate but open perspectives of generalized AHG prediction by remote sensing.

show abstract

Section: Methodsmentioning

confidence: 99%

W_{50} = W_{m} \cdot {(Q_{50} / Q_{m})}^{\tilde{b}},

H_{50} = H_{m} \cdot {(Q_{50} / Q_{m})}^{\tilde{f}},

where W 50 and H 50 are, respectively, reach‐average wetted width and water depth at Q 50 . W m and H m are wetted width and water depth at measurement discharge Q m .…”

Section: Methodsmentioning

confidence: 99%

Section: Observed Ahg Exponentsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Consistent Theoretical and Empirical Predictions of at‐a‐Station Hydraulic Geometry Exponents in Stream Reaches

Morel

Booker

Gob

et al. 2020

Water Resources Research

Self Cite

View full text Add to dashboard Cite

show abstract

“…Williams [27] compiled 16 methods for determining this flow while Navratil [28] compared several methods of determination of bankfull discharge magnitude and frequency in gravel-bed rivers. The most common of them are: field observation at a hydrometric station equipped with a stable rating curve, hydraulic geometry of the section [29,30], flood frequency analysis, or a determination through Manning equation. Other authors analyze water level time-series in order to detect the overbank flow [31].…”

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

View full text Add to dashboard Cite

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.

show abstract

Combining hillslope erosion and river connectivity models to assess large scale fine sediment transfers: Application over the Rhône River (France)

Fabre,

Fressard,

Bizzi

et al. 2024

Earth Surf Processes Landf

View full text Add to dashboard Cite

Sediment connectivity at the catchment scale includes the processes linking sediment sources, sinks and the river outlet. Soil erosion models usually estimate yields without considering riverine processes or human infrastructure that may affect sediment connectivity. Quantifying these processes at a large scale is a determinant of understanding sediment transfers from continental lands to marine ecosystems. This study tries to fill this gap by coupling the soil erosion model WaTEM/SEDEM (WS) with the riverine connectivity tool CASCADE to quantify sediment fluxes in the Rhône watershed. The coupling returned a good fit, with deviations of −51.7%. WS alone predicts the exported fluxes better with a deviation of −34.9%. Nevertheless, this paper shows the importance of considering connectivity and transport capacity to develop a more realistic representation of fine sediment dynamics at a large scale. However, connectivity tools depend on the quality of the models (soil erosion and hydrology) and the geomorphological data on which they depend, which is a limiting factor in large‐scale studies.

show abstract

Revisiting the drivers of at-a-station hydraulic geometry in stream reaches

Cited by 12 publications

References 46 publications

Consistent Theoretical and Empirical Predictions of at‐a‐Station Hydraulic Geometry Exponents in Stream Reaches

Consistent Theoretical and Empirical Predictions of at‐a‐Station Hydraulic Geometry Exponents in Stream Reaches

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

Combining hillslope erosion and river connectivity models to assess large scale fine sediment transfers: Application over the Rhône River (France)

Contact Info

Product

Resources

About