Optimizing sediment transport models by using the Monte Carlo simulation and deep neural network (DNN): A case study of the Riba-Roja reservoir

Dehghan-Souraki, Danial; López-Gómez, David; Bladé-Castellet, Ernest; Larese, Antonia; Sanz-Ramos, Marcos

doi:10.1016/j.envsoft.2024.105979

Environmental Modelling & Software

2024

DOI: 10.1016/j.envsoft.2024.105979

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Optimizing sediment transport models by using the Monte Carlo simulation and deep neural network (DNN): A case study of the Riba-Roja reservoir

Danial Dehghan-Souraki,

David López-Gómez,

Ernest Bladé-Castellet

et al.

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2024

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Cited by 3 publications

References 46 publications

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Utilizing InVEST ecosystem services model combined with deep learning and fallback bargaining for effective sediment retention in Northern Iran

Nasiri Khiavi,

Khodamoradi,

Sarouneh

2024

Environ Sci Pollut Res

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Utilizing InVEST ecosystem services model combined with deep learning and fallback bargaining for effective sediment retention in Northern Iran

Nasiri Khiavi,

Khodamoradi,

Sarouneh

2024

Environ Sci Pollut Res

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Applicability of sediment rating curves: analysis in the state of Rio Grande do Sul

Dorneles,

Wojahn,

Beskow

et al. 2024

Rev. Bras. Geog. Fis.

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The transport of sediments is present in all watercourses, occurring naturally, however, in different ways and characteristics. Its quantification in watersheds becomes extremely important for the planning and management of water resources. The sediment rating curve, which empirically describes the relationship between stream flow and suspended sediment concentration (Css), is an alternative tool to the lack of continuous monitoring of sediment transport. The aim of this research was to evaluate the use of rating curves in sedimentometric stations in Rio Grande do Sul, Brazil. Three Css data handling scenarios were tested for the analytical fitting of sediment rating curves considering a power function as follows: complete data sets, data sets subdivided into 10-year periods and subdivided into stream flow ranges. The approaches adopted in the present study were evaluated taking as reference 58 sedimentometric stations in the state. The goodness-of-fit tests used in this study - coefficient of determination, Relative Average Percentage Error and Nash Sutcliffe coefficient, indicated that the best results of the estimation of sediment transport were observed when the sediment rating curve was fitted to the 10-year period data set.

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Extension of Iber for Simulating Non–Newtonian Shallow Flows: Mine-Tailings Spill Propagation Modelling

Sanz-Ramos,

Bladé,

Sánchez-Juny

et al. 2024

Water

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Mine tailings are commonly stored in off-stream reservoirs and are usually composed of water with high concentrations of fine particles (microns). The rupture of a mine-tailings pond promotes, depending on the characteristics of the stored material, the fluidization and release of hyper-concentrated flows that typically behave as non–Newtonian fluids. The simulation of non–Newtonian fluid dynamics using numerical modelling tools is based on the solution of mass and momentum conservation equations, particularizing the shear stress terms by means of a rheological model that accounts for the properties of the fluid. This document presents the extension of Iber, a two-dimensional hydrodynamic numerical tool, for the simulation of non–Newtonian shallow flows, especially those related to mine tailings. The performance of the numerical tool was tested throughout benchmarks and real study cases. The results agreed with the analytical and theoretical solutions in the benchmark tests; additionally, the numerical tool also revealed itself to be adequate for simulating the dynamic and static phases under real conditions. The outputs of this numerical tool provide valuable information, allowing researchers to assess flood hazard and risk in mine-tailings spill propagation scenarios.

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Optimizing sediment transport models by using the Monte Carlo simulation and deep neural network (DNN): A case study of the Riba-Roja reservoir

Cited by 3 publications

References 46 publications

Utilizing InVEST ecosystem services model combined with deep learning and fallback bargaining for effective sediment retention in Northern Iran

Utilizing InVEST ecosystem services model combined with deep learning and fallback bargaining for effective sediment retention in Northern Iran

Applicability of sediment rating curves: analysis in the state of Rio Grande do Sul

Extension of Iber for Simulating Non–Newtonian Shallow Flows: Mine-Tailings Spill Propagation Modelling

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