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A hyper-concentrated sediment yield prediction model using sediment delivery ratio for large watersheds
Abstract This paper presents a sediment prediction model using sediment delivery ratio approach for prediction of sediment yields from large watersheds (larger than 800 ha). The Sediment Delivery Ratio (SDR) approach is effective for predicting the sediment yield as it moves through the stream system to a concentration point (debris basin) in the watershed. A statistical model, the Multi-Sequence Debris Prediction Model (MSDPM), was developed for use in relatively small watersheds (50–800 ha) in the Los Angeles area. In this study, the MSDPM was extended to include a sediment delivery ratio for modeling of sediment transport through the stream network in the large watershed. The sediment delivery ratio approach was implemented to express the percent of sediment yield that is delivered through a stream system from the sub-watersheds to the debris basin. After adding the sediment delivery ratio to estimate the sediment yields from large watersheds, the revised MSDPM (MSDPM-R) was calibrated and validated based on precipitation, sediment yield and fire data collected from the William Fire (September 2002) and Grand Prix Fire (October and November 2003) events in southern California. Results from MSDPM-R were compared with the available field data obtained from several debris basins within Los Angeles and San Bernardino Counties. The MSDPM-R yields remarkably consistent results when compared with the measured field data.
A hyper-concentrated sediment yield prediction model using sediment delivery ratio for large watersheds
Abstract This paper presents a sediment prediction model using sediment delivery ratio approach for prediction of sediment yields from large watersheds (larger than 800 ha). The Sediment Delivery Ratio (SDR) approach is effective for predicting the sediment yield as it moves through the stream system to a concentration point (debris basin) in the watershed. A statistical model, the Multi-Sequence Debris Prediction Model (MSDPM), was developed for use in relatively small watersheds (50–800 ha) in the Los Angeles area. In this study, the MSDPM was extended to include a sediment delivery ratio for modeling of sediment transport through the stream network in the large watershed. The sediment delivery ratio approach was implemented to express the percent of sediment yield that is delivered through a stream system from the sub-watersheds to the debris basin. After adding the sediment delivery ratio to estimate the sediment yields from large watersheds, the revised MSDPM (MSDPM-R) was calibrated and validated based on precipitation, sediment yield and fire data collected from the William Fire (September 2002) and Grand Prix Fire (October and November 2003) events in southern California. Results from MSDPM-R were compared with the available field data obtained from several debris basins within Los Angeles and San Bernardino Counties. The MSDPM-R yields remarkably consistent results when compared with the measured field data.
A hyper-concentrated sediment yield prediction model using sediment delivery ratio for large watersheds
Pak, Jang Hyuk (Autor:in) / Lee, Joo Heon (Autor:in)
KSCE Journal of Civil Engineering ; 16 ; 883-891
29.06.2012
9 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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