Generation of Synthetic Sedimentgraphs

Gracia-Sánchez, Jesús

doi:10.1002/(sici)1099-1085(199609)10:9<1181::aid-hyp369>3.0.co;2-x

Cited by 4 publications

(3 citation statements)

References 10 publications

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“…Inspired by the extensive linear systems theory approach to the hydrologic response [ Sherman , ; Nash , ; Dooge, ; Kirkby , ; Rodriguez‐Iturbe and Valdes , ; Gupta et al ., ; Troutman and Karlinger , ; Gupta et al ., ; Mesa and Mifflin , ; Gupta and Mesa , ; Maidment et al ., ; Muzik , ; Rinaldo et al ., ; Botter et al ., ] and its extension to the sedimentological response for mud at the storm‐event time scale [ Johnson , ; Williams , ; Kumar and Rastogi , ; Sharma et al ., ; Raghuwanshi et al ., ; Gracia‐Sanchez , ; Lee and Singh , ; Kalin et al ., ; Singh et al ., ; Bhunya et al ., ; Lee and Yang , ], we propose here a conceptual framework for computing the “sedimentological response function” of a basin focusing specifically on the transport of mud, sand, and gravel. The sedimentological response function is defined as the time distribution of the sediment quantity delivered to the outlet of a basin in response to an instantaneous unit input of sediment uniformly distributed over the basin.…”

Section: Introductionmentioning

confidence: 99%

A network-based framework for identifying potential synchronizations and amplifications of sediment delivery in river basins

2014

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Long-term prediction of environmental response to natural and anthropogenic disturbances in a basin becomes highly uncertain using physically based distributed models, particularly when transport time scales range from tens to thousands of years, such as for sediment. Yet, such predictions are needed as changes in one part of a basin now might adversely affect other parts of the basin in years to come. In this paper, we propose a simplified network-based predictive framework of sedimentological response in a basin, which incorporates network topology, channel characteristics, and transport-process dynamics to perform a nonlinear process-based scaling of the river-network width function to a time-response function. We develop the process-scaling formulation for transport of mud, sand, and gravel, using simplifying assumptions including neglecting long-term storage, and apply the methodology to the Minnesota River Basin. We identify a robust bimodal distribution of the sedimentological response for sand of the basin which we attribute to specific source areas, and identify a resonant frequency of sediment supply where the disturbance of one area followed by the disturbance of another area after a certain period of time, may result in amplification of the effects of sediment inputs which would be otherwise difficult to predict. We perform a sensitivity analysis to test the robustness of the proposed formulation to model parameter uncertainty and use observations of suspended sediment at several stations in the basin to diagnose the model. The proposed framework has identified an important vulnerability of the Minnesota River Basin to spatial and temporal structuring of sediment delivery.

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Section: Introductionmentioning

confidence: 99%

A network-based framework for identifying potential synchronizations and amplifications of sediment delivery in river basins

2014

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“…A watershed is represented by storage systems that include the catchment processes, without including the specific details of process interactions that may require detailed catchment information. Examples of some existing conceptual models include the Unit Sediment Graph (USG; Rendon-Herrero 1978) and Instantaneous Unit Sediment Graph (IUSG; Williams 1978;Singh et al 1982Singh et al , 2008Kumar and Rastogi 1987;Raghuwanshi et al 1994;Gracia-Sanchez 1996;Lee and Singh 2005). If a model is constructed by using mass conservation equation of sediment, it is called a processbased model.…”

Section: Introductionmentioning

confidence: 99%

“…Secondly, the method cannot be used on ungauged watersheds (Gracia-Sanchez 1996). On the other hand, to derive sediment graphs directly from rainfall of a storm, the regression type relations (between the effective rainfall and mobilized sediment) are in frequent use (Chen and Kuo 1986;Kumar and Rastogi 1987;Raghuwanshi et al 1994Raghuwanshi et al , 1996Sharma et al 1992;Sharma and Murthy 1996).…”

Section: Introductionmentioning

confidence: 99%

A Simple Conceptual Model of Sediment Yield

Bhunya

Jain

Singh

et al. 2009

Water Resour Manage

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The sediment graphs (time distribution of sediment yield) are very essential if the sediment transports the pollutants that are toxic at high concentrations, requiring determination of peak, rather than average sediment flow rate. In this paper, an effort has been made to develop a simple conceptual model of sediment yield based on Soil Conservation Service Curve Number (SCS-CN) method, instantaneous unit sediment graph (IUSG) method, and Power law and the performance is tested using real field data of Chaukhutia watershed of Ramganga river catchment (area = 452.25 km 2 ). The proposed model is found to provide realistic estimates of temporal variation of sediment yield as well as total sediment yield during a storm event. The model is found to be most sensitive to parameter β followed by k, α, A, and n s . A comparison is made with the existing IUSG based models of Kumar and Rastogi (J Hydrol 95:155-163, 1987) and Raghuwanshi et al. (J Hydraul Eng ASCE 120(4): 495-503, 1994) for developing sediment graphs.

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