Articles | Volume 21, issue 2
https://doi.org/10.5194/hess-21-1263-2017
https://doi.org/10.5194/hess-21-1263-2017
Research article
 | 
02 Mar 2017
Research article |  | 02 Mar 2017

Feasibility analysis of using inverse modeling for estimating field-scale evapotranspiration in maize and soybean fields from soil water content monitoring networks

Foad Foolad, Trenton E. Franz, Tiejun Wang, Justin Gibson, Ayse Kilic, Richard G. Allen, and Andrew Suyker

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Revised manuscript accepted for HESS
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Cited articles

Allen, R. G., Pereira, L. S., Raes, D., and Smith, M.: Crop evapotranspiration-guidelines for computing crop water requirements-FAO irrigation and drainage paper 56, FAO, Rome, 300, D05109, 1998.
Allen, R. G., Tasumi, M., and Trezza, R.: Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC)-Model, J. Irrig. Drain. E.-ASCE, 133, 380–394, 2007.
Anayah, F. M. and Kaluarachchi, J. J.: Improving the complementary methods to estimate evapotranspiration under diverse climatic and physical conditions, Hydrol. Earth Syst. Sci., 18, 2049–2064, https://doi.org/10.5194/hess-18-2049-2014, 2014.
Andreasen, M., Andreasen, L. A., Jensen, K. H., Sonnenborg, T. O., and Bircher, S.: Estimation of regional groundwater recharge using data from a distributed soil moisture network, Vadose Zone J., 12, https://doi.org/10.2136/vzj2013.01.0035, 2013.
ASCE-EWRI: The ASCE Standardized reference evapotranspiration equation. ASCE-EWRI Standardization of Reference Evapotranspiration Task Comm. Report, ASCE Bookstore, ISBN 078440805, Stock Number 40805, 216 pp., 2005.
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Short summary
Estimates of evapotranspiration are vital for validation of models. However, those datasets are often limited to research applications. Here, we explore using vadose zone modeling with widespread and readily available soil water content monitoring networks. While this work focused on one agricultural site, the framework can be used everywhere there is basic data. The resulting evapotranspiration and soil water content measurements are valuable benchmarks for evaluation of land surface models.