Studies focusing on the impact of levelling on the management of available water for rice growth and on soil hydro‐physical quality indicators cultivated in lowland soils under aerobic conditions are still scarce. The objective of this study was to evaluate the levelling impact on soil water retention and soil quality indicators by multivariate and geostatistical analyses. A 10 × 10 m grid was used to sample the 0‐ to 20‐cm layer in a 1.0‐ha experimental field, before and after levelling. Sand and clay contents, macroporosity, bulk density (Bd), organic matter (OM), weighted average diameter of aggregates, and the water retention curve were measured. Available water capacity, structural stability, and S indexes and relative field capacity were calculated. Descriptive statistics, Kolmogorov–Smirnov test, and geostatistical analysis were used. Maps of all data sets significantly correlated with Bd and OM after levelling were constructed using ordinary and indicator kriging. Kaiser–Meyer–Olkin and Bartlett tests were performed for factorial and principal component analyses which were used to reduce the dimensionality of data and of main principal component maps. Levelling negatively affected the majority of soil quality indicators, caused an increase of their spatial range, and an improved the goodness of fit of the semivariogram models used. The majority of variables were best fitted by the Gaussian model after levelling. Bd and OM probability maps were found to be useful tools for farmers wanting to utilize different strategies for topsoil management, with the goal of improving soil quality of levelled areas for future land recuperation operations.

中文翻译：

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通过多变量和地统计分析评估土地平整对低地土壤质量指标和保水率的影响

仍然缺乏集中研究水准对水稻生长可用水的管理以及有氧条件下在低地土壤中耕作的土壤水文物理质量指标的影响的研究。这项研究的目的是通过多元和地统计分析来评估整平对土壤保水率和土壤质量指标的影响。在校平前后，在1.0公顷的实验场地中，使用10×10 m的网格对0至20 cm的层进行采样。测量了沙子和粘土的含量，大孔隙率，堆积密度（Bd），有机质（OM），骨料的加权平均直径和保水率曲线。计算了可用水容量，结构稳定性，S指数和相对田间容量。使用描述性统计，Kolmogorov–Smirnov检验和地统计分析。使用普通克里金法和指标克里金法，绘制出在归类后与Bd和OM显着相关的所有数据集的地图。进行了Kaiser–Meyer–Olkin和Bartlett测试，以进行阶乘和主成分分析，以减少数据和主要主成分图的维数。整平对大多数土壤质量指标产生负面影响，导致其空间范围增加，并改善了所用半变异函数模型的拟合优度。平整后，高斯模型最适合大多数变量。发现Bd和OM概率图对于希望采用不同策略进行表土管理的农民来说是有用的工具，其目的是改善平整地区的土壤质量，以进行未来的土地复垦作业。