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Representative locations from time series of soil water content using time stability and wavelet analysis

机译:使用时间稳定性和小波分析的土壤水分时间序列中的代表性位置

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摘要

The concept of time stability has been widely used in the design and assessment of monitoring networks of soil moisture, as well as in hydrological studies, because it is as a technique that allows identifying of particular locations having the property of representing mean values of soil moisture in the field. In this work, we assess the effect of time stability calculations as new information is added and how time stability calculations are affected at shorter periods, subsampled from the original time series, containing different amounts of precipitation. In doing so, we defined two experiments to explore the time stability behavior. The first experiment sequentially adds new data to the previous time series to investigate the long-term influence of new data in the results. The second experiment applies a windowing approach, taking sequential subsamples from the entire time series to investigate the influence of short-term changes associated with the precipitation in each window. Our results from an operating network (seven monitoring points equipped with four sensors each in a 2-ha blueberry field) show that as information is added to the time series, there are changes in the location of the most stable point (MSP), and that taking the moving 21-day windows, it is clear that most of the variability of soil water content changes is associated with both the amount and intensity of rainfall. The changes of the MSP over each window depend on the amount of water entering the soil and the previous state of the soil water content. For our case study, the upper strata are proxies for hourly to daily changes in soil water content, while the deeper strata are proxies for medium-range stored water. Thus, different locations and depths are representative of processes at different time scales. This situation must be taken into account when water management depends on soil water content values from fixed locations.
机译:时间稳定性的概念已被广泛用于土壤水分监测网络的设计和评估以及水文研究中,因为它是一种允许识别具有代表土壤水分平均值特性的特定位置的技术。在该领域。在这项工作中,我们评估了添加新信息后时间稳定性计算的效果,以及从包含不同数量降水量的原始时间序列中对子时间采样的较短时间对时间稳定性计算的影响。为此,我们定义了两个实验来探索时间稳定性行为。第一个实验将新数据顺序添加到先前的时间序列中,以研究新数据对结果的长期影响。第二个实验采用窗口化方法,从整个时间序列中获取连续的子样本,以调查与每个窗口中的降水相关的短期变化的影响。我们从一个运行网络(在2公顷的蓝莓田中七个监测点分别配备四个传感器)得出的结果表明,随着时间序列中信息的添加,最稳定点(MSP)的位置也会发生变化,并且通过移动21天的窗口可以清楚地看出,土壤含水量变化的大部分变化都与降雨的数量和强度有关。每个窗口上MSP的变化取决于进入土壤的水量和土壤含水量的先前状态。对于我们的案例研究,较高的地层是土壤水含量从每小时到每天的变化的代理,而较深的地层是中等范围储水的代理。因此,不同的位置和深度代表了不同时间尺度的过程。当水管理取决于固定位置的土壤含水量值时,必须考虑这种情况。

著录项

  • 来源
    《Environmental Monitoring and Assessment》 |2014年第12期|9075-9087|共13页
  • 作者单位

    Department of Water Resources, Laboratory of Comparative Policies in Water Resources CONICYT/FONDAP-15130015, University of Concepcion, Chilian, Chile;

    Department of Mechanization and Energy, University of Concepcion, Chilian, Chile;

    Departamento de Ciencias de la Vida, Universidad de las Fuerzas Armadas-ESPE, Sangolqui, Ecuador;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Time stability; Soil water content; Time series analysis; Wavelet filtering;

    机译:时间稳定性;土壤含水量;时间序列分析;小波滤波;
  • 入库时间 2022-08-17 13:26:55

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