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A Field‐Scale Sensor Network Data Set for Monitoring and Modeling the Spatial and Temporal Variation of Soil Water Content in a Dryland Agricultural Field
Author(s) -
Gasch C. K.,
Brown D. J.,
Campbell C. S.,
Cobos D. R.,
Brooks E. S.,
Chahal M.,
Poggio M.
Publication year - 2017
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1002/2017wr021307
Subject(s) - environmental science , water content , soil water , soil texture , hydrology (agriculture) , spatial variability , agriculture , data set , mediterranean climate , soil science , remote sensing , geography , geology , mathematics , statistics , geotechnical engineering , archaeology
We describe a soil water content monitoring data set and auxiliary data collected at a 37 ha experimental no‐till farm in the Northwestern United States. Water content measurements have been compiled hourly since 2007 by ECH2O‐TE and 5TE sensors installed at 42 locations and five depths (0.3, 0.6, 0.9, 1.2, and 1.5 m, 210 sensors total) across the R.J. Cook Agronomy Farm, a Long‐Term Agro‐Ecosystem Research Site stationed on complex terrain in a Mediterranean climate. In addition to soil water content readings, the data set includes hourly and daily soil temperature readings, annual crop histories, a digital elevation model, Bt horizon maps, seasonal apparent electrical conductivity, soil texture, and soil bulk density. Meteorological records are also available for this location. We discuss the unique challenges of maintaining the network on an operating farm and demonstrate the nature and complexity of the soil water content data. This data set is accessible online through the National Agriculture Library, has been assigned a DOI, and will be maintained for the long term.