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000011423 0247_ $$2DOI$$a10.2136/vzj2009.0173
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000011423 041__ $$aeng
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000011423 084__ $$2WoS$$aEnvironmental Sciences
000011423 084__ $$2WoS$$aSoil Science
000011423 084__ $$2WoS$$aWater Resources
000011423 1001_ $$0P:(DE-Juel1)129440$$aBogena, H. R.$$b0$$uFZJ
000011423 245__ $$aPotential of wireless sensor networks for measuring soil water content variability
000011423 260__ $$aMadison, Wis.$$bSSSA$$c2010
000011423 300__ $$a1002 - 1013
000011423 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article
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000011423 440_0 $$010301$$aVadose Zone Journal$$v9$$x1539-1663$$y4
000011423 500__ $$aWe gratefully acknowledge financial support by the SFB/TR32 "Pattern in Soil-Vegetation-Atmosphere Systems: Monitoring, Modelling, and Data Assimilation" funded by the Deutsche Forschungsgemeinschaft (DFG) and by TERENO "Terrestrial Environmental Observatories" funded by the Federal Ministry of Education and Research (BMBF).
000011423 520__ $$aSoil 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.
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000011423 7001_ $$0P:(DE-Juel1)129469$$aHerbst, M.$$b1$$uFZJ
000011423 7001_ $$0P:(DE-Juel1)129472$$aHuisman, J. A.$$b2$$uFZJ
000011423 7001_ $$0P:(DE-Juel1)VDB72369$$aRosenbaum, U.$$b3$$uFZJ
000011423 7001_ $$0P:(DE-Juel1)VDB72368$$aWeuthen, A.$$b4$$uFZJ
000011423 7001_ $$0P:(DE-Juel1)129549$$aVereecken, H.$$b5$$uFZJ
000011423 773__ $$0PERI:(DE-600)2088189-7$$a10.2136/vzj2009.0173$$gVol. 9, p. 1002 - 1013$$p1002 - 1013$$q9<1002 - 1013$$tVadose zone journal$$v9$$x1539-1663$$y2010
000011423 8567_ $$uhttp://dx.doi.org/10.2136/vzj2009.0173
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