Detecting changes in sediment sources in drought periods: The Latrobe River case study

Vigiak, Olga; Beverly, Craig; Roberts, Anna; Thayalakumaran, Thabo; Dickson, Michelle; McInnes, J.; Borselli, L.

doi:10.1016/j.envsoft.2016.08.011

Cited by 13 publications

(6 citation statements)

References 47 publications

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“…Wu et al [ 24 ] applied FME to simulate the spatial pattern of grain yield production for crops and net primary production (NPP) in their studies. Vigiak et al [ 28 ] used FME in simulating sediment and changes in sediment sources during drought periods. To date, FME-based modeling has not been used for wetland modeling.…”

Section: Introductionmentioning

confidence: 99%

Modeling Nitrogen Dynamics in a Waste Stabilization Pond System Using Flexible Modeling Environment with MCMC

Mukhtar

Lin

Shipin

et al. 2017

IJERPH

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This study presents an approach for obtaining realization sets of parameters for nitrogen removal in a pilot-scale waste stabilization pond (WSP) system. The proposed approach was designed for optimal parameterization, local sensitivity analysis, and global uncertainty analysis of a dynamic simulation model for the WSP by using the R software package Flexible Modeling Environment (R-FME) with the Markov chain Monte Carlo (MCMC) method. Additionally, generalized likelihood uncertainty estimation (GLUE) was integrated into the FME to evaluate the major parameters that affect the simulation outputs in the study WSP. Comprehensive modeling analysis was used to simulate and assess nine parameters and concentrations of ON-N, NH3-N and NO3-N. Results indicate that the integrated FME-GLUE-based model, with good Nash–Sutcliffe coefficients (0.53–0.69) and correlation coefficients (0.76–0.83), successfully simulates the concentrations of ON-N, NH3-N and NO3-N. Moreover, the Arrhenius constant was the only parameter sensitive to model performances of ON-N and NH3-N simulations. However, Nitrosomonas growth rate, the denitrification constant, and the maximum growth rate at 20 °C were sensitive to ON-N and NO3-N simulation, which was measured using global sensitivity.

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Section: Introductionmentioning

confidence: 99%

Modeling Nitrogen Dynamics in a Waste Stabilization Pond System Using Flexible Modeling Environment with MCMC

Mukhtar

Lin

Shipin

et al. 2017

IJERPH

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“…The type, intensity and spatiotemporal distribution of erosion also affect sediment connectivity (Millares‐Valenzuela et al, 2022). The strong development of gullies and gravity erosion can cause landslides and collapses that interrupt sediment pathways, resulting in large changes in connectivity (Vigiak et al, 2016). Human‐made buffers and engineering measures can also lead to disconnections and reduce sediment delivery capacity (Zou et al, 2022).…”

Section: Discussionmentioning

confidence: 99%

An integrated watershed modelling framework to explore the covariation between sediment connectivity and soil erosion

Guo,

Wu,

Liu

et al. 2023

European J Soil Science

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Quantitative identification of the covariation between sediment connectivity and soil erosion can contribute to provide the key information for watershed sediment management. However, this covariation and its spatiotemporal response mechanisms are still unclear, especially whether this covariation can be used as a basis for identifying critical source areas of sediment in large‐scale ecological restored watersheds. In this study, an integrated methodology framework by the RUSLE, index of connectivity (IC), and sediment delivery ratio (SDR) was proposed to visually assess the spatiotemporal characteristics of erosion and sediment yield processes in the Yanhe Watershed with large‐scale ecological restoration from 1985 to 2020, and to identify the covariation between sediment connectivity and erosion in subbasins. The soil erosion estimated by RUSLE has decreased by over 80% since 1985 owing to increased vegetation cover and the effective implementation of soil conservation measures, but the upper reaches still have high erosion intensity due to differences in specific controlling factors such as topographic conditions and land cover, requiring focused soil conservation practice. The IC results showed that as the vegetation restoration and soil conservation measures in the Yanhe Watershed varied from year to year, their spatial and temporal patterns had a strong influence on the distribution of sediment connectivity, some local areas in the middle reaches showed local minima of IC in 1995, 1998 and 2010 mainly due to the implementation of long‐term ecological restoration project. The developed IC‐Erosion maps indicated that areas with high‐connectivity but low‐erosion accounted for over 60% of the total watershed area from 1985 to 1999, demonstrating a reverse correlation between sediment connectivity and erosion. Meanwhile, over 40% of the erosion occurred in a few areas (approximately 20%) with high‐connectivity and high‐erosion from 2000 to 2004, which can be characterized as the critical areas of erosion. The methods and results of this study provide ideas for separately defining both erosion and connectivity, and quantifying bi‐variable erosion‐connectivity classification that can be easily viewed on a scatterplot.This article is protected by copyright. All rights reserved.

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“…Borselli et al (2008) proposed an index of connectivity (IC) describing the hydrological linkage between sediment sources and sinks. The IC consists of the following two components: an upslope component (D up ) that represents the potential for down-routing at a given location and a downslope component (D dn ) that accounts for potential flow sinks between that location and the stream network (Vigiak et al, 2016). The calculation formula is as follows:…”

Section: Structural Sdr (Hsdr)mentioning

confidence: 99%

“…For example, Zhao et al (2020) used this type of model to explore the effects of land-use change and soil and water conservation measures on the sediment yield. However, the SDR based on the IC has been considered a stationary property assessed for average landscape conditions, which ignores the dynamic mechanism of sediment transport (Vigiak et al, 2016;Najafi et al, 2021;Zhang, 2021). Zhang Y. et al (2019) pointed out that the SDR algorithm based on the IC characterizes the potential sediment transport capacity on a hillslope but does not reflect the actual variation in sediment transport over time.…”

Section: Introductionmentioning

confidence: 99%

Construction of a monthly dynamic sediment delivery ratio model at the hillslope scale: a case study from a hilly loess region

Xu,

Zhang,

et al. 2024

Front. Environ. Sci.

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Introduction: Soil loss is a worldwide environmental problem, and sediment transport is one of its important components. In recent years, a hillslope sediment delivery ratio (SDR) model based on an index of connectivity has been widely used to describe the variation in sediment transport characteristics. However, the hillslope SDR model only considers the structural characteristics of the watershed and ignores the dynamic mechanism of sediment transport, which leads to poor dynamic applicability over short timescales and makes it difficult to reflect changes of sediment yield.Methods: Therefore, we here propose a monthly dynamic SDR model that integrates the hillslope structural connectivity and sediment transport threshold of rainfall event based on the main influencing factors of sediment delivery. We then combine the dynamic SDR model with an empirical erosion model to simulate the hillslope sediment yield in the Mahuyu watershed, and verify the applicability of the coupled model using the Heimutouchuan watershed.Results: The results show that the coupled model can effectively simulate the hillslope sediment yields of the Mahuyu and Heimutouchuan watersheds. The contribution of the rainfall transport threshold factor to sediment delivery and yield is essentially in dynamic stability at the multi-year timescale, but increases the heterogeneity of both inter-month distributions and the spatial distribution of hillslope sediment yield.Discussion: The dynamic SDR model, which considers the rainfall thresholds of transport and re-transport, can effectively improve the simulation accuracy of low and high sediment yield values on hillslopes. Our results can provide a reference for understanding sediment transport processes on hillslopes and optimizing soil and water conservation measures in watersheds.

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Detecting changes in sediment sources in drought periods: The Latrobe River case study

Cited by 13 publications

References 47 publications

Modeling Nitrogen Dynamics in a Waste Stabilization Pond System Using Flexible Modeling Environment with MCMC

Modeling Nitrogen Dynamics in a Waste Stabilization Pond System Using Flexible Modeling Environment with MCMC

An integrated watershed modelling framework to explore the covariation between sediment connectivity and soil erosion

Construction of a monthly dynamic sediment delivery ratio model at the hillslope scale: a case study from a hilly loess region

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