Fitting and comparing water retention curves for soils under contrasting experimental treatment: Examples from conservation agriculture trials in southern Africa

IF 6.6 1区 农林科学 Q1 SOIL SCIENCE
I. Sandram , W. Namaona , N. Magwero , V. Mbanyele , C. Miti , M. Moombe , T. Mtangadura , P. Lubinga , C.B. Chisanga , I. Nyagumbo , K. Njira , I.S. Ligowe , J. Banda , W.R. Whalley , G. Sakala , E. Phiri , P.C. Nalivata , H. Nezomba , P. Mapfumo , F. Mtambanengwe , J.G. Chimungu
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引用次数: 0

Abstract

Conservation Agriculture (CA) is proposed as a ‘climate-smart’ intervention for resilient crop production in dryland areas affected by climate change. Evidence is needed for how these practices affect fundamental properties of the soil. The soil water retention curve (SWRC) is a physical attribute of the soil which provides information on its porous structure and physical quality. It is also critical for modelling processes in the soil such as water movement, water availability for plants and infiltration into the soil during rainfall events. In this paper we estimate parameters of the van Genuchten model of the SWRC from experiments on CA interventions in southern Africa, using a linear mixed modelling framework. The method we use, stochastic approximation maximization, allows for maximum likelihood estimation of the parameters without use of linearizing approximation. We show how sequential fitting of model parameters, with marginal false discovery rate control, allows us to make robust inferences about differences in the SWRC between soils under contrasting experimental management. We also show how the method allows us to draw samples from distribution of SWRC parameters, reflecting the uncertainty which arises from variation within the management treatments. Indices of soil physical quality may be computed from the parameter estimates to compare treatments, and by computing them from the samples, the uncertainty in these indices can also be assessed. We use the estimated model parameters to simulate infiltration of water into the soils under different management during a rainfall event. Again, by using the samples from the joint distributions of the parameters the effects of uncertainty in these parameters as propagated through the model can be computed. We applied these methods to soils collected from experimental plots under CA and conventional tillage (CV) at sites in Zimbabwe, Zambia and Malawi. We observed differences in the SWRC for the CA and CV plots at the Zambian site where a physically vulnerable soil showed greater macroporosity under CA than CV. In contrast, a sandy and organic-poor soil at the site in Zimbabwe showed somewhat greater macroporosity under cultivation rather than CA management. There was no detectable treatment effect of the management system on the SWRC for the soils at the site in Malawi.
不同试验处理下土壤保水曲线的拟合和比较:来自南部非洲保护性农业试验的例子
保护性农业(CA)被提议作为一种“气候智能型”干预措施,用于受气候变化影响的旱地地区的弹性作物生产。需要证据来证明这些做法如何影响土壤的基本特性。土壤保水曲线(SWRC)是土壤的一种物理属性,它提供了土壤孔隙结构和物理质量的信息。它对于模拟土壤中的过程也至关重要,例如水的运动、植物的水分有效性和降雨期间渗入土壤的情况。在本文中,我们使用线性混合建模框架,从南部非洲的CA干预实验中估计SWRC的van Genuchten模型的参数。我们使用的方法,随机近似最大化,允许参数的最大似然估计,而不使用线性化近似。我们展示了在边际错误发现率控制下,模型参数的顺序拟合如何使我们能够在对比实验管理下对土壤之间SWRC的差异做出稳健的推断。我们还展示了该方法如何允许我们从SWRC参数的分布中提取样本,反映了管理处理中变化引起的不确定性。根据参数估计值可以计算出土壤物理质量指数,以比较不同处理的土壤物理质量,并通过从样品中计算这些指数来评估这些指数的不确定性。我们使用估计的模型参数来模拟在降雨事件中不同管理下的土壤入渗。同样,通过使用参数联合分布的样本,可以计算这些参数在模型中传播的不确定性的影响。我们将这些方法应用于在津巴布韦、赞比亚和马拉维的试验田采用CA和常规耕作法(CV)收集的土壤。我们观察到在赞比亚样地,物理脆弱土壤在CA下比CV下表现出更大的宏观孔隙度,在CA和CV样地的SWRC存在差异。相比之下,津巴布韦的沙质和有机贫瘠土壤在耕作而不是CA管理下显示出更大的宏观孔隙度。管理系统对马拉维场地土壤的SWRC没有可检测到的处理效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Geoderma
Geoderma 农林科学-土壤科学
CiteScore
11.80
自引率
6.60%
发文量
597
审稿时长
58 days
期刊介绍: Geoderma - the global journal of soil science - welcomes authors, readers and soil research from all parts of the world, encourages worldwide soil studies, and embraces all aspects of soil science and its associated pedagogy. The journal particularly welcomes interdisciplinary work focusing on dynamic soil processes and functions across space and time.
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