Sediment transport and evaluation of sediment surrogate ratings in the Kootenai River near Bonners Ferry, Idaho, Water Years 2011–14

Wood, Molly S.; Fosness, Ryan L.; Etheridge, Alexandra B.

doi:10.3133/sir20155169

Cited by 2 publications

(2 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Peak streamflow generally occurs during spring snowmelt runoff in mid-to late-spring. Low, base flow conditions generally begin in mid-to late summer [33]. Libby Dam regulates streamflow except for small tributary contributions between the dam and Bonners Ferry.…”

Section: Study Areamentioning

confidence: 99%

Defining the Limits of Spectrally Based Bathymetric Mapping on a Large River

Legleiter

Fosness

2019

Remote Sensing

View full text Add to dashboard Cite

Remote sensing has emerged as a powerful method of characterizing river systems but is subject to several important limitations. This study focused on defining the limits of spectrally based mapping in a large river. We used multibeam echosounder (MBES) surveys and hyperspectral images from a deep, clear-flowing channel to develop techniques for inferring the maximum detectable depth, d m a x , directly from an image and identifying optically deep areas that exceed d m a x . Optimal Band Ratio Analysis (OBRA) of progressively truncated subsets of the calibration data provided an estimate of d m a x by indicating when depth retrieval performance began to deteriorate due to the presence of depths greater than the sensor could detect. We then partitioned the calibration data into shallow and optically deep ( d > d m a x ) classes and fit a logistic regression model to estimate the probability of optically deep water, P r ( O D ) . Applying a P r ( O D ) threshold value allowed us to delineate optically deep areas and thus only attempt depth retrieval in relatively shallow locations. For the Kootenai River, d m a x reached as high as 9.5 m at one site, with accurate depth retrieval ( R 2 = 0.94 ) in areas with d < d m a x . As a first step toward scaling up from short reaches to long river segments, we evaluated the portability of depth-reflectance relations calibrated at one site to other sites along the river. This analysis highlighted the importance of calibration data spanning a broad range of depths. Due to the inherent limitations of passive optical depth retrieval in large rivers, a hybrid field- and remote sensing-based approach would be required to obtain complete bathymetric coverage.

show abstract

Section: Study Areamentioning

confidence: 99%

Defining the Limits of Spectrally Based Bathymetric Mapping on a Large River

Legleiter

Fosness

2019

Remote Sensing

View full text Add to dashboard Cite

show abstract

“…Storm centering can also increase sediment eroded from portions of the watershed with distinct geology or land use giving sediment loads different gradation signatures (Bogen, ). Tributaries with distinct suspended sediment gradations (Costigan et al, ; Davis et al, ; Rubin & Topping, ; Wood et al, ) or the relative contributions of watershed, bank, catchment slope, and bed sources (Grangeon et al, ; Lenzi & Marchi, ; Slattery & Burt, ; Wood et al, ) for different flows can also affect suspended sediment gradations. Walling and Moorhead () suggested that supply factors are built into flow‐gradation trends, since larger flows draw sediment from larger areas, introducing a “sediment latency” effect.…”

Section: Introductionmentioning

confidence: 99%

Flow Dependence of Suspended Sediment Gradations

Gibson

Cai

2017

Water Resources Research

View full text Add to dashboard Cite

Suspended sediment loads can coarsen or fine as a function of flow. The flow‐load gradation relationships can also vary nonmonotonically. This complex relationship between flow and load gradation complicates sediment model boundary condition selection and sediment rating curve analysis. This study analyzed flow‐gradation data from 78 gages in the continental United States, exploring trends and tendencies in the flow‐gradation relationships. Results were then compared to the flow‐gradation trends generated by sediment capacity equations and a meta‐analysis of sediment model data. Several systems, with abundant sediment supply fined with flow. However, most gage data and calibrated model inputs coarsened with flow. When nonmonotonic models were considered, one‐third to one‐half of the gages fit a second‐order curve, coarsening over low‐to‐moderate flows (up to an average annual exceedance probability of ∼30%) and fining over higher flows. The low‐flow‐coarsening trend was generally stronger than high‐flow‐fining trends. Many of these second‐order trends demonstrated behavior more like “asymptotic coarsening.” They coarsened until they reached a maximum physical grain size limit and gradation fined slightly or remained constant beyond the threshold flow. The dominance of flow‐coarsening suggests most of the rivers surveyed (which included a bias toward large, regulated rivers) are supply limited. Supply limited (bed regulated) rivers tend to coarsen with flow, while capacity limited, high supply systems tend to fine with flow. Sediment capacity equations computed a variety of flow‐gradation trends. Using transport functions to compute load‐gradation model boundary conditions will often diverge from (or even invert) observed trends, especially in supply limited systems.

show abstract

Sediment transport and evaluation of sediment surrogate ratings in the Kootenai River near Bonners Ferry, Idaho, Water Years 2011–14

Cited by 2 publications

References 17 publications

Defining the Limits of Spectrally Based Bathymetric Mapping on a Large River

Defining the Limits of Spectrally Based Bathymetric Mapping on a Large River

Flow Dependence of Suspended Sediment Gradations

Contact Info

Product

Resources

About