摘要:为揭示黄土高寒区人工林土壤水分的时空变化特征，基于2018年植被生长期一处典型人工植被恢复坡面0-200cm剖面土壤含水率连续动态数据，运用经典统计和时间稳定性分析，研究不同深度土壤含水率的时空变异性和时间稳定性。结果表明：在测定时段内，剖面各土层深度土壤含水率无显著差别，在空间上均表现为中等变异性，呈现随土层深度的增加而增大的趋势，在时间上表层表现为中等变异性，其余各层均表现为弱变异性，深层土壤水分的时间变异性小于浅层；随着测定时间变化，试验地0-200cm土壤含水率Spearman秩相关系数均达到0.8以上，且呈极显著相关，表现出一定的时间稳定性特征；土壤含水率的时间稳定性随土层深度的增加而增强，具有深度依赖性；基于相对差分分析可以选择代表性测点监测区域平均土壤含水率（决定系数R²为0.7138-0.8605），以期为合理布设土壤水分监测点提供理论依据，对于植被恢复与生态重建模式的选择具有指导意义。



Abstract:Studying the temporal and spatial variability of soil moisture in artificial ecosystems is of great significance for guiding the restoration of vegetation patterns and the efficient management and utilization of regional water resources. We selected an artificial vegetation restoration slope with a depth of 0-200cm in the loess alpine region for research, in order to reveal the spatio-temporal variation characteristics of its soil moisture. During the vegetation growth peak season in 2018 (June-August), continuous dynamic data of soil moisture content in different soil layers were measured by neutron meter. Based on this, the spatio-temporal variability and temporal stability of soil moisture at different depths were studied by using classical statistics and temporal stability analysis. The results showed that there was no significant difference in the soil moisture content of each soil layer profile during the period of measurement. At the spatial scale, the result indicated that all the soil layers showd a moder variance which increased with the increase in soil depth. At the time scale, the topsoil layer showed a moderate variance while the other layers exhibited weak variance, which suggested that time variability of soil moisture in deep layer was smaller than that in shallow layer. The spearman rank correlation coefficient of soil moisture content of 0-200cm in the experimental site reached 0.8 or more at different measuring periods, and the correlation with moisture was extremely significant. As the depth of the soil increased, the temporal stability of soil moisture also increased between different soil layers. Based on relative difference analysis, the representative measuring points can be applied to predict the average soil moisture content of the corresponding soil layers in a region (determination coefficient R² is 0.7138-0.8605). In conclusion, with this paper we aim to provide a theoretical basis for the deployment of soil moisture monitoring sites, and suitable guidance for the selection of vegetation restoration and ecological reconstruction models.





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