Sediment is one of the most common causes of stream impairment. Great progress has been made in understanding the processes of soil erosion due to surface runoff and incorporating these in prediction technologies. In many landscapes, however, the dominant source of sediment is derived from mass wasting of hillslopes and stream banks, potentially driven by subsurface flow. We highlight the mechanisms and importance of subsurface flow processes in erosion associated with hillslopes and stream banks. Subsurface flow affects erosion directly by seepage and pipe flow processes and indirectly by the relationship of soil properties with soil water pressure. Seepage contributes to erosion through interrelated mechanisms: hydraulic gradient forces that reduce the resistance of the particle to dislodging from the soil matrix and particle mobilization when soil particles become entrained in exfiltrating water. Preferential flow through soil pipes results in internal erosion of the pipe, which may produce gullies by tunnel collapse. The eroded material can clog soil pipes, causing pore water pressure buildup inside the pipes that can result in landslides, debris flows, embankment failures, or reestablishment of ephemeral gullies. Research in the past decades has advanced our understanding of these processes, leading to mathematical relationships that can be incorporated into mechanistic, process-based models. Further research advances are necessary, however, especially on the complexity of the interactive effects of surface flow, seepage, pipe flow, and vegetation on soil erosion properties. More information is needed on the extent that subsurface flow contributes to hillslope and stream bank erosion. We believe that multidisciplinary efforts between soil scientists, geotechnical engineers, hydraulic engineers, and hydrologists are necessary to fully understand and integrate subsurface flow and soil erosion processes in simulation tools.

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The Role of Subsurface Flow in Hillslope and Stream Bank Erosion: A Review

Evaluating nutrient impacts in urban watersheds: Challenges and research opportunities

https://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=1314&context=biosysengfacpub

Evaluation of the bank stability and toe erosion model (BSTEM) for predicting lateral retreat on composite streambanks

[1] In this study, the natural process of river meandering is captured in a computational model that considers the effects of bank erosion, the process of land accretion along the inner banks of meander bends, and the formation of channel cutoffs. The methodology for predicting bank erosion explicitly includes a submodel treating the formation and eventual removal of slump blocks. The accretion of bank material on the inner bank is modeled by defining the time scale over which areas that are originally channel become land. Channel cutoff formation is treated relatively simply by recomputing the channel alignment at a single model time step when migrating banks meet. The model is used to compute meandering processes in both steady and unsteady flows. The key features of this new model are the ability (a) to describe bank depositional and bank erosional responses separately, (b) to couple them to bed morphodynamics, and thus (c) to describe coevolving river width and sinuosity. Two cases of steady flow are considered, one with a larger discharge (i.e., “bankfull”) and one with a smaller discharge (i.e., “low flow”). In the former case, the shear stress is well above the critical shear stress, but in the latter case, it is initially below it. In at least one case of constant discharge, the planform pattern can develop some sinuosity, but the pattern appears to deviate somewhat from that observed in natural meandering channels. For the case of unsteady flow, discharge variation is modeled in the simplest possible manner by cyclically alternating the two discharges used in the steady flow computations. This model produces a rich pattern of meander planform evolution that is consistent with that observed in natural rivers. Also, the relationship between the meandering evolution and the return time scale of floods is investigated by the model under the several unsteady flow patterns. The results indicate that meandering planforms have different shapes depending on the values of these two scales. In predicting meander evolution, it is important to consider the ratio of these two time scales in addition to such factors as bank erosion, slump block formation and decay, bar accretion, and cutoff formation, which are also included in the model.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/jgrf.20150

Numerical simulation of river meandering with self‐evolving banks

Water utilities face a challenge in maintaining a good quality of service under a wide range of operational management and failure conditions. Tools for assessing the resilience of water distribution networks are therefore essential for both operational and maintenance optimization. In this paper, a novel graph-theoretic approach for the assessment of resilience for large scale water distribution networks is presented. This is of great importance for the management of large scale water distribution systems, most models containing up to hundreds of thousands of pipes and nodes. The proposed framework is mainly based on quantifying the redundancy and capacity of all possible routes from demand nodes to their supply sources. This approach works well with large network sizes since it does not rely on precise hydraulic simulations, which require complex calibration processes and computation, while remaining meaningful from a physical and a topological point of view. The proposal is also tailored for the analysis of sectorised networks through a novel multiscale method for analysing connectivity, which is successfully tested in operational utility network models made of more than 100,000 nodes and 110,000 pipes.

/pdf/a-graph-theoretic-framework-for-assessing-the-resilience-of-4l5v4ai54l.pdf

A Graph-Theoretic Framework for Assessing the Resilience of Sectorised Water Distribution Networks

We present an integrated analysis of bank erosion in a high-curvature bend of the gravel bed Cecina River (central Italy). Our analysis combines a model of fluvial bank erosion with groundwater flow and bank stability analyses to account for the influence of hydraulic erosion on mass failure processes, the key novel aspect being that the fluvial erosion model is parameterized using outputs from detailed hydrodynamic simulations. The results identify two mechanisms that explain how most bank retreat usually occurs after, rather than during, flood peaks. First, in the high curvature bend investigated here the maximum flow velocity core migrates away from the outer bank as flow discharge increases, reducing sidewall boundary shear stress and fluvial erosion at peak flow stages. Second, bank failure episodes are triggered by combinations of pore water and hydrostatic confining pressures induced in the period between the drawdown and rising phases of multipeaked flow events.

/pdf/numerical-simulation-of-hydrodynamics-and-bank-erosion-in-a-54xz41fjia.pdf

Numerical simulation of hydrodynamics and bank erosion in a river bend

Microglial cells polarized towards a proinflammatory phenotype are considered the main cellular players of neuroinflammation, underlying several neurodegenerative diseases. Many studies have suggested that imbalance of the gut microbial composition is associated with an increase in the pro-inflammatory cytokines and oxidative stress that underlie chronic neuroinflammatory diseases, and perturbations to the gut microbiota were detected in neurodegenerative conditions such as Parkinson’s disease and Alzheimer’s disease. The importance of gut-brain axis has been uncovered and the relevance of an appropriate microbiota balance has been highlighted. Probiotic treatment, rebalancing the gut microbioma, may reduce inflammation. We show that Milmed yeast, obtained from S. cerevisiae after exposure to electromagnetic millimeter wavelengths, induces a reversal of LPS-M1 polarized microglia towards an anti-inflammatory phenotype, as demonstrated morphologically by the recovery of resting phenotype by microglia, by the decrease in the mRNAs of IL-1β, IL-6, TNF-α and in the expression of iNOS. Moreover, Milmed stimulated the secretion of IL-10 and the expression of Arginase-1, cell markers of M2 anti-inflammatory polarized cells. The present findings data suggest that Milmed may be considered to be a probiotic with diversified anti-inflammatory activity, capable of directing the polarization of microglial cells.

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Beatrice Mengoni

Papers

Numerical simulation of hydrodynamics and bank erosion in a river bend

Milmed Yeast Alters the LPS-Induced M1 Microglia Cells to Form M2 Anti-Inflammatory Phenotype