Simulation performance and impact factors of soil surface roughness under different tillage practices based on the Monte Carlo algorithm

IF 6.1 1区 农林科学 Q1 SOIL SCIENCE
Xinyu Li , Mingxuan Lu , Xuelin You , Lei Wang , Shuang Zhou , Jianhua Ren
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引用次数: 0

Abstract

Soil surface roughness (SSR) is widely employed to quantify the spatial variability of soil surface height in farmland, which also plays a critical role in soil erosion. However, traditional methods for measuring SSR are often time-consuming and labor-intensive, with limitations in measurement scale and accuracy. In this study, simulation approach for random and oriented SSR under Gaussian and exponential distributions was developed using the Monte Carlo algorithm. The accuracy and effectiveness of simulation results were validated through field measurements during the soybean growth period under various tillage practices. Thereafter, variations in SSR and their influencing factors across different tillage practices were systematically analyzed. Results demonstrated that the simulation of soil surface height under ridge-based tillage outperformed no-tillage. Additionally, discrepancies were observed in the fitting performance of SSR parameters derived from measured and simulated soil surface heights. Specifically, root mean square height (RMSH) and mean deviation (Ra) exhibited the best fitting performance, followed by root mean square slope (σm), while correlation length (CL) showed the poorest agreement between measured and simulated values. Correlation analysis and analysis of variance further revealed that the correlation and stability between measured and simulated SSR parameters followed the order: no-tillage > reduced tillage > conventional tillage > rotary tillage > combined tillage. During the crop growth period, various factors such as field management, precipitation, wind erosion, and gravity influenced SSR under different tillage practices. The results of this study contribute to broadening the methodologies for obtaining SSR, and enhancing the understanding of farmland surface processes.
基于蒙特卡罗算法的不同耕作方式下土壤表面粗糙度模拟性能及影响因素
土壤表面粗糙度(SSR)被广泛用于量化农田土壤表面高度的空间变异性,土壤表面高度在土壤侵蚀中也起着至关重要的作用。然而,传统的SSR测量方法往往耗时费力,且测量规模和精度存在局限性。本文采用蒙特卡罗算法建立了高斯分布和指数分布下随机定向SSR的仿真方法。通过不同耕作方式下大豆生育期的田间实测,验证了模拟结果的准确性和有效性。在此基础上,系统分析了SSR在不同耕作方式下的变化及其影响因素。结果表明,垄作对土壤表面高度的模拟效果优于免耕。此外,实测和模拟土壤表面高度的SSR参数拟合性能也存在差异。其中,均方根高度(RMSH)和平均偏差(Ra)拟合效果最好,均方根斜率(σm)次之,相关长度(CL)拟合效果最差。相关分析和方差分析进一步表明,实测与模拟SSR参数的相关性和稳定性依次为:免耕>; 免耕>; 常规耕作>; 旋耕法>; 联合耕作。在作物生育期,不同耕作方式下,田间管理、降水、风蚀、重力等因素均对SSR产生影响。研究结果有助于拓宽SSR获取方法,提高对农田地表过程的认识。
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来源期刊
Soil & Tillage Research
Soil & Tillage Research 农林科学-土壤科学
CiteScore
13.00
自引率
6.20%
发文量
266
审稿时长
5 months
期刊介绍: Soil & Tillage Research examines the physical, chemical and biological changes in the soil caused by tillage and field traffic. Manuscripts will be considered on aspects of soil science, physics, technology, mechanization and applied engineering for a sustainable balance among productivity, environmental quality and profitability. The following are examples of suitable topics within the scope of the journal of Soil and Tillage Research: The agricultural and biosystems engineering associated with tillage (including no-tillage, reduced-tillage and direct drilling), irrigation and drainage, crops and crop rotations, fertilization, rehabilitation of mine spoils and processes used to modify soils. Soil change effects on establishment and yield of crops, growth of plants and roots, structure and erosion of soil, cycling of carbon and nutrients, greenhouse gas emissions, leaching, runoff and other processes that affect environmental quality. Characterization or modeling of tillage and field traffic responses, soil, climate, or topographic effects, soil deformation processes, tillage tools, traction devices, energy requirements, economics, surface and subsurface water quality effects, tillage effects on weed, pest and disease control, and their interactions.
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