An improved cellular automata model for soil erosion in coastal areas based on discrete physical variables

Tang, Shengqiang; She, Dongli; Wang, Hongde; Lü, Haishen

doi:10.1111/ejss.13261

Cited by 5 publications

(4 citation statements)

References 45 publications

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“…In contrast, the measured results may be affected by the complexity of the surface runoff on the slope, resulting in the collection of rainwater on the front edge of the slope only at a later time after ponding. This phenomenon is basically consistent with the E1-3 runoff experimental simulation results conducted by Tang et al 25 .…”

Section: Discussionsupporting

confidence: 92%

GIS and cellular automata based slope rainwater movement process model and its application

Liu,

Chen,

Zhang

et al. 2024

Sci Rep

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Rainfall serves as a significant factor contributing to slope stability challenges in mountainous areas, and simulating the process of slope rainwater movement is a crucial approach for analyzing the stability of slopes triggered by rainfall. By combining computer numerical simulation technology with traditional hydraulic and hydrological calculation theories, it is possible to create an efficient and precise rainwater movement model that can simulate and analyze the process of rainwater movement on slopes. Utilizing natural slopes as the focal point of our research, the cellular automaton method was applied to simulate rainfall runoff on slopes, and a Cellular Automata (CA) based model for rainwater movement process was developed. This model modified the Green-Ampt (G-A) infiltration model by adopting an elliptical water content curve and introducing a coefficient that quantifies the ratio of saturated to unsaturated depth. Additionally, we refined the rules governing runoff generation and convergence within the slope and on its surface, enabling a comprehensive simulation of the entire rainwater movement process on the slope. Furthermore, the effectiveness of the model was validated through analytical solutions derived from simplified assumptions, laboratory experiments on infiltration and runoff in the flume, and a case study of a natural slope. The results show that the infiltration calculation results of the rainwater movement model are closer to the experimental values, and their overall values are slightly higher than the measured values, which are basically consistent with the model test results; The runoff calculation results show a phenomenon of initially increasing and gradually approaching the measured values compared to the measured values. When applying the model to an actual slope, it was found that the model comprehensively accounts for the influence of slope seepage, infiltration and runoff process, has better performance compared to G-A modified model. The model can be used to describe the spatial distribution and temporal variation of infiltration and runoff processes.

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Section: Discussionsupporting

confidence: 92%

GIS and cellular automata based slope rainwater movement process model and its application

Liu,

Chen,

Zhang

et al. 2024

Sci Rep

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“…Soil erosion is a major and costly environmental hazard worldwide, while a thorough understanding of the soil erosion process essential for erosion control is still missing. Tang et al (2022) developed an optimized cellular automata model, based on discrete physical variables (CADV), capable for improved predictions of the soil erosion dynamics in coastal areas. The CADV model provides a promising approach for soil erosion modelling towards improved mechanistic understanding of soil erosion processes.…”

Section: Figurementioning

confidence: 99%

Soil physics matters for the land–water–food–climate nexus and sustainability

Wang,

Liu,

Yan

et al. 2023

European J Soil Science

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Soil is a complex ecosystem within which many species interact and where physicochemical and geological processes occur at different spatiotemporal scales, with strong interactions taking place between ecological and management processes. Soil processes affect the qualities of the food and water that we eat and drink, the regulation of greenhouse gases, and are the foundation of our habitation and transportation infrastructures. However, it is estimated that over 2 billion hectares of lands are degraded, with a further 12 million hectares degraded each year causing the annual loss of 24 billion tons of fertile soil. Soil degradation negatively affects the well‐being of over 3 billion people, costing more than 10% of the annual global GDP via the loss of ecosystem services, and reducing the productivity of 23% of the global terrestrial area. The sustainable management of soil ecosystems is, therefore, fundamental to global food, water, and energy security, especially under increasingly unpredictable weather patterns caused by climate change. The land–water–food–energy nexus is central to sustainable development and soil inextricably links these critical domains. Stakeholders and decision‐makers in all four domains are necessarily focusing on the effects of soil degradation on climate change, water resource management, and food production as key to the development of sustainable agricultural practices and policies. A properly integrated approach to managing rural soils is thus required to ensure global water, food, and energy security, whilst increasing and protecting biodiversity. This special issue collects 15 papers on recent advances on soil physical‐, hydrological‐, and biological processes, and linkages with agroecosystem sustainability across experiments, field observations, and methodological breakthroughs.

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“…Soil erosion is one of the most serious environmental problems for soil health, regional ecological, environmental, social and economic developments (FAO, 2019; FAO, ITPS, 2015). The occurrence of soil erosion is closely related to human activities and climatic extremes (Montgomery, 2007; Tang et al, 2022). Currently, about 84% of the world's land is subject to various degrees of erosion, resulting in 33% of the world's land suffering from soil degradation (Borrelli et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Responses of soil microbial metabolic limitations to erosion under contrasting soil types and management practices

Rong,

Zhu,

Jiao

et al. 2024

European J Soil Science

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Soil microbial metabolism plays important role in supporting soil services and functionalities, but is usually restricted by the availability of soil nutrients. Although soil microbial metabolism limitation (SMML) has been widely addressed regarding to various driving factors, its response to erosion was not examined, but is urgently needed given the important influence of erosion on global environments. To understand how erosion affects SMML and whether erosion's effect varies with tillage practices and soil types, we conducted a simulated erosion experiment to compare the eroded and non‐eroded plots with contrast soils (Mollisol vs. loess soils) and managements (conventional tillage vs. no‐tillage in plots with vs. without crops). We measured soil extracellular enzymatic activities and quantified SMML with extracellular enzymatic stoichiometry models. In both soils, the microbes were limited by carbon (C) and phosphorous (P), but not by nitrogen, and that the microbial C and P limitations were greater in Mollisol than loess soils. For the Mollisol, erosion significantly increased the relative C limitation, whereas the presence of crops eliminated this increase. For the loess soils, erosion enhanced the relative C limitation regardless of crop presence and tillage management. Erosion consistently increased microbial P limitation in plots with crops, with greater effect under no‐tillage (+2.9%) than conventional tillage (+0.7%) conditions regardless of soil types (P < 0.05). In plots without crops, microbial P limitation was increased by erosion under no‐tillage (+2.1%) but was decreased under conventional tillage (‐5.6%) (P < 0.05). Additionally, conventional tillage exacerbated microbial C limitation but alleviated microbial P limitation. These results indicated that erosion shifted microbial C and P limitations depending on soil types, tillage practices and the presence of plant, highlighting the importance of considering all these factors when assessing soil microbial metabolic limitation at various spatial scales.This article is protected by copyright. All rights reserved.

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An improved cellular automata model for soil erosion in coastal areas based on discrete physical variables

Cited by 5 publications

References 45 publications

GIS and cellular automata based slope rainwater movement process model and its application

GIS and cellular automata based slope rainwater movement process model and its application

Soil physics matters for the land–water–food–climate nexus and sustainability

Responses of soil microbial metabolic limitations to erosion under contrasting soil types and management practices

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