Abstract
Automated soil moisture sensors are widely used in agronomy and environmental sciences. However, to sense properly the amount of water retained in the soil matrix, a calibration with gravimetrically observed values is required. This is laborious and not appropriate when the soil physical properties change during the wetting and drying cycles due to swelling and shrinkage, respectively. The objective of this study was to analyze how gravimetric soil moisture, θ, series can be interpolated from a minimum number of field observations, using daily automated sensor output as secondary information. Weekly observed soil moisture data from three depth intervals, and daily data from four sets for FDR sensors in two adjacent plots subject to different tillage practices were used to validate the method. A variogram analysis showed that soil moisture was more persistent in time and with depth in no-tillage and that at least two scales of temporal variation could be distinguished. Kriging with an external drift produced the largest model efficiency when using calibrated sensor measurements as secondary information.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Reference
Baumhardt RL, Lascano RJ, Evett SR (2000) Soil material, temperature, and salinity effects on calibration of multisensor capacitance probes. Soil Sci Soc Am J 64:1940–1946
Deutsch CV, Journel AG (1998) GSLIB. Geostatistical software library and user’s guide, 2nd edition. Oxford University Press, New York
Evett SR, Parkin GW (2005) Advances in soil water content sensing: The continuing maturation of technology and theory. Vadose Zone J 4:986–991
Fares A, Buss P, Dalton M, El-Kadi AI, Parsons LR (2004) Dual field calibration of capacitance and neutron soil water sensors in a shrinking-swelling clay soil. Vadose Zone J 3:1390–1399
Goovaerts P (1997) Geostatistics for Natural Resources Evaluation. Oxford University Press, Nueva York, p 483
Jost G, Heuvelink GBM, Papritz A (2005) Analysing the space-time distribution of soil water storage of a forest ecosystem using spatio-temporal kriging. Geoderma, 128:258–273
Muñoz-Carpena R, Ritter A, Bosch D (2005) Field methods for monitoring soil water status. In: Benedí, Muńoz-Carpena (eds) Soil-Water-Solute process characterization. An integrated approach, CRC Press, Boca Raton, FL, p 778
Nash JE, Sutcliffe JV (1970) River flow forecasting through conceptual models. Part 1. A discussion of principles. J. Hydrol. 10:282–290
Paltineanu IC, Starr JL (1997) Real-time soil water dynamics using multisensor capacitance probes: laboratory calibration. Soil Sci Soc Am J 61:1576–1585
Panatier Y (1996) VARIOWIN: Software for spatial data analysis in 2D. Springer Verlag, New York
Polyakov V, Fares A, Ryder MH (2005) Calibration of a capacitance system for measuring water content of tropical soil. Vadose Zone J 4:1004–1010
Snepvangers JJJC, Heuvelink GBM, Huisman JA (2003) Soil water content interpolation using spatio-temporal kriging with external drift. Geoderma 112:253–271
Soil Survey Staff (1999) Soil Taxonomy. A basic system of soil classification for making and interpreting soil survey. 2a ed. USDA Agriculture Handbook n 436, Washington
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer Science+Business Media B.V.
About this chapter
Cite this chapter
Vanderlinden, K., Jiménez, J., Muriel, J., Perea, F., García, I., Martínez, G. (2008). Interpolation of Soil Moisture Content Aided by FDR Sensor Observations. In: Soares, A., Pereira, M.J., Dimitrakopoulos, R. (eds) geoENV VI – Geostatistics for Environmental Applications. Quantitative Geology and Geostatistics, vol 15. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-6448-7_33
Download citation
DOI: https://doi.org/10.1007/978-1-4020-6448-7_33
Publisher Name: Springer, Dordrecht
Print ISBN: 978-1-4020-6447-0
Online ISBN: 978-1-4020-6448-7
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)