Institute of Surface-Earth System Science, School of Earth System Science, Tianjin University, Weijin Road 92, Tianjin 300072, PR China.
Institute of Surface-Earth System Science, School of Earth System Science, Tianjin University, Weijin Road 92, Tianjin 300072, PR China; China Fire and Rescue institute, Nanyan Road 4, Beijing 102202, PR China.
Sci Total Environ. 2022 Jul 1;828:154538. doi: 10.1016/j.scitotenv.2022.154538. Epub 2022 Mar 14.
Spatiotemporal variations in soil water content (SWC) and soil water stable isotopic compositions (SWSIC; H/H (δD) and O/O (δO)) provide critical information on elucidating land surface processes across scales. Meanwhile, little is known about the spatiotemporal characteristics of SWSIC and its driving factors. Therefore, it's necessary to improve tracer techniques of SWSIC by interpreting their spatiotemporal variability patterns as well as the correlations with other factors such as texture, soil depth and vegetation. To this end, the spatiotemporal variations in SWC and SWSIC along with their controlling factors were jointly investigated based on seven field campaigns over roughly a two-year period at an agricultural field in North China Plain. Two transects, vegetated and bared, were considered. The results of vegetated transect showed that both SWC and SWSIC exhibited considerable spatiotemporal variabilities at the field scale of ~100 m, with SWSIC displaying more complex patterns. Overall, the spatial variations in SWSIC were larger in wet seasons than in dry seasons, which decreased with increasing soil depth, largely due to less impacts of precipitation inputs and soil evaporation on SWSIC dynamics at deeper depths. The temporal stability analysis (TSA) showed that there existed temporal persistence of the spatial structure of SWSIC, particularly at deeper soil depths. Moreover, the SWSIC data in our study showed that the effect of vegetation on the SWSIC dynamics was noticeable with shading effects, root distribution and water uptake, which caused much lesser degrees of soil evaporation at the vegetated transect. What's more, the representative sites for monitoring spatial average δD values were identified, demonstrating the viability of using the TSA method to estimate the spatial average SWSIC values at field scales. These findings can improve the interpretation of SWSIC data for practical applications.
土壤水分含量 (SWC) 和土壤水分稳定同位素组成 (SWSIC；H/H (δD) 和 O/O (δO)) 的时空变化为阐明跨尺度的陆地表面过程提供了关键信息。与此同时，人们对 SWSIC 的时空特征及其驱动因素知之甚少。因此，有必要通过解释 SWSIC 的时空变化模式及其与质地、土壤深度和植被等其他因素的相关性，改进 SWSIC 的示踪技术。为此，在中国华北平原的一个农业领域，进行了大约两年七次野外考察，联合研究了 SWC 和 SWSIC 的时空变化及其控制因素。考虑了两条样带，植被样带和裸地样带。植被样带的结果表明，SWC 和 SWSIC 在约 100 米的田间尺度上均表现出相当大的时空变异性，SWSIC 呈现出更复杂的模式。总体而言，SWSIC 的空间变化在湿润季节大于干燥季节，且随着土壤深度的增加而减小，这主要是由于降水输入和土壤蒸发对 SWSIC 动态的影响在较深的土壤深度上较小。时间稳定性分析（TSA）表明，SWSIC 的空间结构存在时间持续性，尤其是在较深的土壤深度。此外，我们研究中的 SWSIC 数据表明，植被对 SWSIC 动态的影响是显著的，具有遮荫效应、根系分布和水分吸收，这导致在植被样带的土壤蒸发程度较小。更重要的是，确定了监测空间平均 δD 值的代表性站点，证明了使用 TSA 方法估算田间尺度上的空间平均 SWSIC 值的可行性。这些发现可以提高对 SWSIC 数据的解释，以便在实际应用中使用。
