{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/114953"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/114953","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Trapping Efficiencies for the BLH-84, Helley-Smith, Elwha, and TR-2 Bedload Samplers","abstract":"Bedload-trapping efficiencies for four types of pressure-difference bedload samplers – a standard Helley-Smith (intake-nozzle width and height of 76.2 mm x 76.2 mm), BLH-84 (76.2 mm x 76.2 mm), Elwha (203 mm x 102 mm) and Toutle River-2 (305 mm x 152 mm) a standard Helley-Smith, US BLH-84 (both with intake nozzle dimensions of 76.2 mm × 76.2 mm), Elwha (203 mm × 102 mm) and Toutle River-2 (TR-2; 305 mm × 152 mm) – were calculated from data collected during the StreamLab06 experiments in the St. Anthony Falls Laboratory Main Flume during January-March 2006. Sampler nozzle-flare ratios –the area of the nozzle's outlet divided by its inlet area – equaled 1.4 for all but the Helley-Smith sampler's nozzle-flare ratio of 3.22. A sampler's trapping coefficient quantifies its bedload-trapping efficiency. Technically supportable trapping coefficients are divided into raw trapping rates measured by the sampler to produce "true" bedload-transport rates equivalent to that which was inferred to have occurred in the absence of the sampler. Six combinations of sampler and bed types were tested; the BLH-84, Elwha, and Helley-Smith samplers were deployed atop a sand bed (D50 = 1.0 mm) during five steady flows ranging from 2.0-3.6 m3/s. The BLH-84, Elwha, and TR-2 samplers were deployed atop a gravel bed (D50 = 11.2 mm) at four steady flows ranging from 4.0-5.5 m3/s. Thirty-seven trials – repeated manual at-a-point deployments of a given bedload sampler for a given steady flow and bed type – took place. Trapping coefficients were calculated for each sampler and bed type in which it was deployed. Ergo, two of the samplers – the BLH-84 and Elwha – were each assigned two trapping efficiencies for sampling on a sand versus a gravel bed. These data were evaluated using four analytical methods: Ratio of Averages: This relatively simple and straight-forward method required calculating averages of bedload-transport rates derived for each of the 37 trials for a given bedload sampler and for up to nine combinations of weigh pans and time intervals. The computations were performed using untransformed data. Average of Ratios: This more complex method using real-space trapping data involved developing average transport rates from selected pan data for each bedload sample. Pan transport-averages were calculated for each interval equal to the duration of a single at-a-point bedload measurement, ranging from 15-180 seconds. Ratios (coefficients) were calculated by dividing each interval average into the single-sample trap rate. Those ratios were then averaged to produce a single trapping coefficient for the trial and then combined into a single average for each bedload-sampler/bed type/flow combination. Modified Thomas and Lewis Model (1993): The Thomas-Lewis Model was revised to operate using untransformed data in addition to cube-root transformed data (thus, the third and fourth analytical methods used, respectively), and to use nine pan-window combinations to calculate trapping coefficients. The original 3-step model required first regressing cube root-transformed sampler data on time-window averaged pan transport rates. The second step squared the regression residuals from the first step on the variance of the cube root of the interval-mean transport rate for the time window. The predicted values from the second-step regression were inverted and used as weights to re-estimate the first-step regression. Generalized trapping-coefficient calculations based on results from the four analytical methods for the bed-types in which the samplers were deployed follow: • BLH-84 Sampler: A 0.83 sand-bed trapping coefficient and 0.87 gravel-bed coefficient, which could be averaged to a single coefficient of 0.85. • Elwha Sampler: A 1.67 sand-bed trapping coefficient and 1.54 gravel-bed coefficient, which could be averaged to a single coefficient of 1.6 • Helley-Smith Sampler: The 3.11 sand-bed trapping coefficient could be applied as such or reasonably simplified to a value of 3.0, and • TR-2: The gravel-bed trapping coefficient equaled 1.70. An unadjusted bedload-trapping rate calculated from a sample collected by a given sampler can be divided by its trapping coefficient(s) to obtain the most reliable transport-rate value.","abstract_html":"Bedload-trapping efficiencies for four types of pressure-difference bedload samplers – a standard Helley-Smith (intake-nozzle width and height of 76.2 mm x 76.2 mm), BLH-84 (76.2 mm x 76.2 mm), Elwha (203 mm x 102 mm) and Toutle River-2 (305 mm x 152 mm) a standard Helley-Smith, US BLH-84 (both with intake nozzle dimensions of 76.2 mm × 76.2 mm), Elwha (203 mm × 102 mm) and Toutle River-2 (TR-2; 305 mm × 152 mm) – were calculated from data collected during the StreamLab06 experiments in the St. Anthony Falls Laboratory Main Flume during January-March 2006. Sampler nozzle-flare ratios –the area of the nozzle's outlet divided by its inlet area – equaled 1.4 for all but the Helley-Smith sampler's nozzle-flare ratio of 3.22. A sampler's trapping coefficient quantifies its bedload-trapping efficiency. Technically supportable trapping coefficients are divided into raw trapping rates measured by the sampler to produce "true" bedload-transport rates equivalent to that which was inferred to have occurred in the absence of the sampler. Six combinations of sampler and bed types were tested; the BLH-84, Elwha, and Helley-Smith samplers were deployed atop a sand bed (D50 = 1.0 mm) during five steady flows ranging from 2.0-3.6 m3/s. The BLH-84, Elwha, and TR-2 samplers were deployed atop a gravel bed (D50 = 11.2 mm) at four steady flows ranging from 4.0-5.5 m3/s. Thirty-seven trials – repeated manual at-a-point deployments of a given bedload sampler for a given steady flow and bed type – took place. Trapping coefficients were calculated for each sampler and bed type in which it was deployed. Ergo, two of the samplers – the BLH-84 and Elwha – were each assigned two trapping efficiencies for sampling on a sand versus a gravel bed. These data were evaluated using four analytical methods: Ratio of Averages: This relatively simple and straight-forward method required calculating averages of bedload-transport rates derived for each of the 37 trials for a given bedload sampler and for up to nine combinations of weigh pans and time intervals. The computations were performed using untransformed data. Average of Ratios: This more complex method using real-space trapping data involved developing average transport rates from selected pan data for each bedload sample. Pan transport-averages were calculated for each interval equal to the duration of a single at-a-point bedload measurement, ranging from 15-180 seconds. Ratios (coefficients) were calculated by dividing each interval average into the single-sample trap rate. Those ratios were then averaged to produce a single trapping coefficient for the trial and then combined into a single average for each bedload-sampler/bed type/flow combination. Modified Thomas and Lewis Model (1993): The Thomas-Lewis Model was revised to operate using untransformed data in addition to cube-root transformed data (thus, the third and fourth analytical methods used, respectively), and to use nine pan-window combinations to calculate trapping coefficients. The original 3-step model required first regressing cube root-transformed sampler data on time-window averaged pan transport rates. The second step squared the regression residuals from the first step on the variance of the cube root of the interval-mean transport rate for the time window. The predicted values from the second-step regression were inverted and used as weights to re-estimate the first-step regression. Generalized trapping-coefficient calculations based on results from the four analytical methods for the bed-types in which the samplers were deployed follow: • BLH-84 Sampler: A 0.83 sand-bed trapping coefficient and 0.87 gravel-bed coefficient, which could be averaged to a single coefficient of 0.85. • Elwha Sampler: A 1.67 sand-bed trapping coefficient and 1.54 gravel-bed coefficient, which could be averaged to a single coefficient of 1.6 • Helley-Smith Sampler: The 3.11 sand-bed trapping coefficient could be applied as such or reasonably simplified to a value of 3.0, and • TR-2: The gravel-bed trapping coefficient equaled 1.70. An unadjusted bedload-trapping rate calculated from a sample collected by a given sampler can be divided by its trapping coefficient(s) to obtain the most reliable transport-rate value.","abstract_has_math":false,"creators":["Gray, John R."],"institution":"Virginia Tech","degree_name":"Ph.D.","degree_level":"doctoral","degree_discipline":"Civil and Environmental Engineering","degree_department":"Civil and Environmental Engineering","school":null,"contributors":[],"advisors":[],"committee_chairs":["Godrej, Adil N.","Diplas, Panayiotis"],"committee_members":["Czuba, Jonathan A.","Strom, Kyle Brent"],"year":2019,"date_issued":"2019-07-03","date_published":"2019-07-03","updated_at":"2026-07-22T22:19:32Z","subjects":["bedload","total load","sediment transport","bedload transport","bedload sampler","bedload sampler calibration","bedload-sampler trapping efficiency"],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/10919/114953","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Godrej, Adil N.","Diplas, Panayiotis"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Czuba, Jonathan A.","Strom, Kyle Brent"]},{"key":"dc:contributor.department","label":"Department","values":["Civil and Environmental Engineering"]},{"key":"dc:creator","label":"Author","values":["Gray, John R."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2023-05-08T11:50:19Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2023-05-08T11:50:19Z"]},{"key":"dc:date.issued","label":"Date","values":["2019-07-03"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Tech"]},{"key":"dc:type","label":"Dc Type","values":["Dissertation"]},{"key":"dc:type.dcmitype","label":"Dc Type Dcmitype","values":["Text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Civil and Environmental Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["doctoral"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Virginia Polytechnic Institute and State University"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["bedload","total load","sediment transport","bedload transport","bedload sampler","bedload sampler calibration","bedload-sampler trapping efficiency"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10919/114953"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Bedload-trapping efficiencies for four types of pressure-difference bedload samplers – a standard Helley-Smith (intake-nozzle width and height of 76.2 mm x 76.2 mm), BLH-84 (76.2 mm x 76.2 mm), Elwha (203 mm x 102 mm) and Toutle River-2 (305 mm x 152 mm) a standard Helley-Smith, US BLH-84 (both with intake nozzle dimensions of 76.2 mm × 76.2 mm), Elwha (203 mm × 102 mm) and Toutle River-2 (TR-2; 305 mm × 152 mm) – were calculated from data collected during the StreamLab06 experiments in the St. Anthony Falls Laboratory Main Flume during January-March 2006. Sampler nozzle-flare ratios –the area of the nozzle's outlet divided by its inlet area – equaled 1.4 for all but the Helley-Smith sampler's nozzle-flare ratio of 3.22. A sampler's trapping coefficient quantifies its bedload-trapping efficiency. Technically supportable trapping coefficients are divided into raw trapping rates measured by the sampler to produce "true" bedload-transport rates equivalent to that which was inferred to have occurred in the absence of the sampler. Six combinations of sampler and bed types were tested; the BLH-84, Elwha, and Helley-Smith samplers were deployed atop a sand bed (D50 = 1.0 mm) during five steady flows ranging from 2.0-3.6 m3/s. The BLH-84, Elwha, and TR-2 samplers were deployed atop a gravel bed (D50 = 11.2 mm) at four steady flows ranging from 4.0-5.5 m3/s. Thirty-seven trials – repeated manual at-a-point deployments of a given bedload sampler for a given steady flow and bed type – took place. Trapping coefficients were calculated for each sampler and bed type in which it was deployed. Ergo, two of the samplers – the BLH-84 and Elwha – were each assigned two trapping efficiencies for sampling on a sand versus a gravel bed. These data were evaluated using four analytical methods: Ratio of Averages: This relatively simple and straight-forward method required calculating averages of bedload-transport rates derived for each of the 37 trials for a given bedload sampler and for up to nine combinations of weigh pans and time intervals. The computations were performed using untransformed data. Average of Ratios: This more complex method using real-space trapping data involved developing average transport rates from selected pan data for each bedload sample. Pan transport-averages were calculated for each interval equal to the duration of a single at-a-point bedload measurement, ranging from 15-180 seconds. Ratios (coefficients) were calculated by dividing each interval average into the single-sample trap rate. Those ratios were then averaged to produce a single trapping coefficient for the trial and then combined into a single average for each bedload-sampler/bed type/flow combination. Modified Thomas and Lewis Model (1993): The Thomas-Lewis Model was revised to operate using untransformed data in addition to cube-root transformed data (thus, the third and fourth analytical methods used, respectively), and to use nine pan-window combinations to calculate trapping coefficients. The original 3-step model required first regressing cube root-transformed sampler data on time-window averaged pan transport rates. The second step squared the regression residuals from the first step on the variance of the cube root of the interval-mean transport rate for the time window. The predicted values from the second-step regression were inverted and used as weights to re-estimate the first-step regression. Generalized trapping-coefficient calculations based on results from the four analytical methods for the bed-types in which the samplers were deployed follow: • BLH-84 Sampler: A 0.83 sand-bed trapping coefficient and 0.87 gravel-bed coefficient, which could be averaged to a single coefficient of 0.85. • Elwha Sampler: A 1.67 sand-bed trapping coefficient and 1.54 gravel-bed coefficient, which could be averaged to a single coefficient of 1.6 • Helley-Smith Sampler: The 3.11 sand-bed trapping coefficient could be applied as such or reasonably simplified to a value of 3.0, and • TR-2: The gravel-bed trapping coefficient equaled 1.70. An unadjusted bedload-trapping rate calculated from a sample collected by a given sampler can be divided by its trapping coefficient(s) to obtain the most reliable transport-rate value."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Ph.D."]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["ETD"]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Trapping Efficiencies for the BLH-84, Helley-Smith, Elwha, and TR-2 Bedload Samplers"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Godrej, Adil N.","Diplas, Panayiotis"],"dc:contributor.committeemember":["Czuba, Jonathan A.","Strom, Kyle Brent"],"dc:contributor.department":["Civil and Environmental Engineering"],"dc:creator":["Gray, John R."],"dc:date.accessioned":["2023-05-08T11:50:19Z"],"dc:date.available":["2023-05-08T11:50:19Z"],"dc:date.issued":["2019-07-03"],"dc:description.abstract":["Bedload-trapping efficiencies for four types of pressure-difference bedload samplers – a standard Helley-Smith (intake-nozzle width and height of 76.2 mm x 76.2 mm), BLH-84 (76.2 mm x 76.2 mm), Elwha (203 mm x 102 mm) and Toutle River-2 (305 mm x 152 mm) a standard Helley-Smith, US BLH-84 (both with intake nozzle dimensions of 76.2 mm × 76.2 mm), Elwha (203 mm × 102 mm) and Toutle River-2 (TR-2; 305 mm × 152 mm) – were calculated from data collected during the StreamLab06 experiments in the St. Anthony Falls Laboratory Main Flume during January-March 2006. Sampler nozzle-flare ratios –the area of the nozzle's outlet divided by its inlet area – equaled 1.4 for all but the Helley-Smith sampler's nozzle-flare ratio of 3.22. A sampler's trapping coefficient quantifies its bedload-trapping efficiency. Technically supportable trapping coefficients are divided into raw trapping rates measured by the sampler to produce "true" bedload-transport rates equivalent to that which was inferred to have occurred in the absence of the sampler. Six combinations of sampler and bed types were tested; the BLH-84, Elwha, and Helley-Smith samplers were deployed atop a sand bed (D50 = 1.0 mm) during five steady flows ranging from 2.0-3.6 m3/s. The BLH-84, Elwha, and TR-2 samplers were deployed atop a gravel bed (D50 = 11.2 mm) at four steady flows ranging from 4.0-5.5 m3/s. Thirty-seven trials – repeated manual at-a-point deployments of a given bedload sampler for a given steady flow and bed type – took place. Trapping coefficients were calculated for each sampler and bed type in which it was deployed. Ergo, two of the samplers – the BLH-84 and Elwha – were each assigned two trapping efficiencies for sampling on a sand versus a gravel bed. These data were evaluated using four analytical methods: Ratio of Averages: This relatively simple and straight-forward method required calculating averages of bedload-transport rates derived for each of the 37 trials for a given bedload sampler and for up to nine combinations of weigh pans and time intervals. The computations were performed using untransformed data. Average of Ratios: This more complex method using real-space trapping data involved developing average transport rates from selected pan data for each bedload sample. Pan transport-averages were calculated for each interval equal to the duration of a single at-a-point bedload measurement, ranging from 15-180 seconds. Ratios (coefficients) were calculated by dividing each interval average into the single-sample trap rate. Those ratios were then averaged to produce a single trapping coefficient for the trial and then combined into a single average for each bedload-sampler/bed type/flow combination. Modified Thomas and Lewis Model (1993): The Thomas-Lewis Model was revised to operate using untransformed data in addition to cube-root transformed data (thus, the third and fourth analytical methods used, respectively), and to use nine pan-window combinations to calculate trapping coefficients. The original 3-step model required first regressing cube root-transformed sampler data on time-window averaged pan transport rates. The second step squared the regression residuals from the first step on the variance of the cube root of the interval-mean transport rate for the time window. The predicted values from the second-step regression were inverted and used as weights to re-estimate the first-step regression. Generalized trapping-coefficient calculations based on results from the four analytical methods for the bed-types in which the samplers were deployed follow: • BLH-84 Sampler: A 0.83 sand-bed trapping coefficient and 0.87 gravel-bed coefficient, which could be averaged to a single coefficient of 0.85. • Elwha Sampler: A 1.67 sand-bed trapping coefficient and 1.54 gravel-bed coefficient, which could be averaged to a single coefficient of 1.6 • Helley-Smith Sampler: The 3.11 sand-bed trapping coefficient could be applied as such or reasonably simplified to a value of 3.0, and • TR-2: The gravel-bed trapping coefficient equaled 1.70. An unadjusted bedload-trapping rate calculated from a sample collected by a given sampler can be divided by its trapping coefficient(s) to obtain the most reliable transport-rate value."],"dc:description.degree":["Ph.D."],"dc:format.medium":["ETD"],"dc:format.mimetype":["application/pdf"],"dc:identifier.uri":["http://hdl.handle.net/10919/114953"],"dc:language.iso":["en"],"dc:publisher":["Virginia Tech"],"dc:subject":["bedload","total load","sediment transport","bedload transport","bedload sampler","bedload sampler calibration","bedload-sampler trapping efficiency"],"dc:title":["Trapping Efficiencies for the BLH-84, Helley-Smith, Elwha, and TR-2 Bedload Samplers"],"dc:type":["Dissertation"],"dc:type.dcmitype":["Text"],"thesis:degree_discipline":["Civil and Environmental Engineering"],"thesis:degree_level":["doctoral"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["Virginia Polytechnic Institute and State University"]},"updated_at":"2026-07-22T22:19:32Z"}