Potential of Wireless Sensor Networks for Measuring Soil Water Content Variability
Potential of Wireless Sensor Networks for Measuring Soil Water Content Variability
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DOI：
10.2136/vzj2009.0173
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发表时间：
2010-11-01
影响因子：
2.8
通讯作者：
Vereecken, H.
中科院分区：
文献类型：
--
作者：
Bogena, H. R.;Herbst, M.;Vereecken, H.
土壤含水量在分配地表水通量和能量通量以及控制地下水补给等水文通量方面起着关键作用。尽管SWC的重要性，它还没有在更大的规模上以可操作的方式进行测量。本研究的目的是调查潜在的无线传感器网络技术的近实时监测SWC在现场和源头流域尺度使用最近开发的无线传感器网络SoilNet。森林集水区Wustebach（类似于27公顷）配备了Decagon Devices的ECH 2 O系列的150个终端设备和600个EC-5 SWC传感器。在2009年8月至11月期间，获得了超过600万个SWC测量结果。观察到的空间变异性与以前的研究结果一致。平均SWC对SWC方差的曲线图中的非常低的散射表明，传感器网络数据提供了比来自测量活动的不连续数据更准确的SWC方差估计。例如，在一个实施例中，固定的采样位置和永久安装的传感器。SWC在50厘米深度的空间变异性显着低于5厘米，这表明，较长的旅行时间，这个深度降低了SWC的空间变异性。干旱期地形特征与土壤含水量的相关性最强，表明地形对土壤含水量格局的控制依赖于土壤水分状况。插值结果表明，高采样密度允许捕获的关键模式的SWC变化。
Soil water content (SWC) plays a key role in partitioning water and energy fluxes at the land surface and in controlling hydrologic fluxes such as groundwater recharge. Despite the importance of SWC, it is not yet measured in an operational way at larger scales. The aim of this study was to investigate the potential of wireless sensor network technology for the near-real-time monitoring of SWC at the field and headwater catchment scales using the recently developed wireless sensor network SoilNet. The forest catchment Wustebach (similar to 27 ha) was instrumented with 150 end devices and 600 EC-5 SWC sensors from the ECH2O series by Decagon Devices. In the period between August and November 2009, more than six million SWC measurements were obtained. The observed spatial variability corresponded well with results from previous studies. The very low scattering in the plots of mean SWC against SWC variance indicates that the sensor network data provide a more accurate estimate of SWC variance than discontinuous data from measurement campaigns, due, e. g., to fixed sampling locations and permanently installed sensors. The spatial variability in SWC at the 50-cm depth was significantly lower than at 5 cm, indicating that the longer travel time to this depth reduced the spatial variability of SWC. Topographic features showed the strongest correlation with SWC during dry periods, indicating that the control of topography on the SWC pattern depended on the soil water status. Interpolation results indicated that the high sampling density allowed capture of the key patterns of SWC variation.