Depth distributions of soil temperature: Seasonal sensitivity and simulation across dryness/wetness conditions

IF 5.9 1区 农林科学 Q1 AGRONOMY
Yining Wang , Jiefeng Wu , Jian-yun Zhang , Tiesheng Guan , Guoqing Wang , Junliang Jin , Zhenlong Wang
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Abstract

Exploring the response patterns of soil temperature to dryness/wetness at various depths enhances our understanding of the complex interactions between surface water dynamics and thermal transfer. Previous studies have focused primarily on analyzing the thermal evolution and response mechanisms of soil temperature with respect to various meteorological factors, neglecting its response across different timescales for dry/wet conditions. This research examines response patterns from four perspectives: trends, seasonal sensitivity, propagation, and response relationships. Based on these patterns, the random forest model was employed to simulate the cumulative soil temperature (CST) during dry and wet periods, using the duration and severity of these periods at different soil depths as input variables. Using long-term monthly observations (1966–2022) from the Wudaogou National Comprehensive Hydrological Observation Station in Anhui Province, China, we analyzed the soil temperature at depths of 0–320 cm paired with meteorological data. The standardized precipitation evapotranspiration index (SPEI) was employed to characterize dryness/wetness across various timescales (from 1-month to 12-months). The results indicate the following: (1) A distinct shift in soil thermal dynamics was observed, with a cooling trend prior to 1992 transitioning into a pronounced warming phase thereafter. The post-1992 warming rate was 3–4 times faster than the overall rate for 1966–2022, revealing critical temporal shifts in soil temperature responses. (2) Shallower soil layers (0–40 cm) exhibited heightened seasonal sensitivity to dryness/wetness, responding more rapidly and intensely than deeper layers (>80 cm), especially at short timescales (≤3 months). This underscores the critical role of surface soil interactions in thermal dynamics. (3) A ‘compression’ phenomenon in temperature transmission was identified, where the influence of dryness and wetness on soil temperature diminishes with increasing depth. Dry periods consistently elevated soil temperatures, whereas wet periods reduced them, providing insights into vertical thermal propagation mechanisms. (4) The random forest model showcased a strong capability to simulate CST achieving R² and Ens values above 0.91 and absolute PBIAS values below 5 %. These findings are essential for managing ecosystems and agricultural practices, as well as informing water management strategies in regions facing extreme climate events.
土壤温度的深度分布:干/湿条件下的季节敏感性和模拟
探索不同深度土壤温度对干湿的响应模式,有助于我们了解地表水动力学与热传递之间的复杂相互作用。以往的研究主要集中在分析土壤温度在各种气象因子下的热演化及其响应机制,而忽略了干湿条件下土壤温度在不同时间尺度上的响应。本研究从趋势、季节敏感性、传播和反应关系四个方面考察了反应模式。基于这些模式,采用随机森林模型,以不同土壤深度的干湿期持续时间和严重程度为输入变量,模拟了干湿期累积土壤温度。利用安徽省五道沟国家综合水文观测站1966-2022年的长期逐月观测资料,结合气象资料分析了0 ~ 320 cm深度的土壤温度。采用标准化降水蒸散指数(SPEI)表征不同时间尺度(1 ~ 12个月)的干湿特征。结果表明:(1)土壤热动态变化趋势明显,1992年以前为降温趋势,1992年以后转为明显升温。1992年后的升温速率是1966-2022年总体升温速率的3-4倍,揭示了土壤温度响应的关键时间变化。(2)浅层土壤(0 ~ 40 cm)对干湿的季节敏感性明显高于深层土壤(>80 cm),尤其是在短时间尺度(≤3个月)。这强调了地表土壤相互作用在热动力学中的关键作用。(3)发现了温度传递中的“压缩”现象,其中干湿对土壤温度的影响随着深度的增加而减小。干旱期持续提高土壤温度,而潮湿期则降低土壤温度,这为垂直热传播机制提供了洞见。(4)随机森林模型对CST的模拟能力较强,R²和Ens值均大于0.91,绝对PBIAS值小于5 %。这些发现对于管理生态系统和农业实践,以及为面临极端气候事件的地区的水管理战略提供信息至关重要。
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
Agricultural Water Management
Agricultural Water Management 农林科学-农艺学
CiteScore
12.10
自引率
14.90%
发文量
648
审稿时长
4.9 months
期刊介绍: Agricultural Water Management publishes papers of international significance relating to the science, economics, and policy of agricultural water management. In all cases, manuscripts must address implications and provide insight regarding agricultural water management.
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