Location: Location not imported yet.Title: Mapping soil moisture across an irrigated field using electromagnetic conductivity imaging
|HUANG, JINGY - University Of New South Wales|
|SCUDIERO, ELIA - University Of California|
|CHOO, HOSEA - University Of New South Wales|
|TRIANTAFILIS, JOHN - University Of New South Wales|
Submitted to: Agricultural Water Management
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/3/2015
Publication Date: 9/4/2015
Citation: Huang, J., Scudiero, E., Choo, H., Corwin, D.L., Triantafilis, J. 2015. Mapping soil moisture across an irrigated field using electromagnetic conductivity imaging. Agricultural Water Management. 163:285-294. doi: 10.1016/j.agwat.2015.09.003.
Interpretive Summary: Field-scale knowledge of spatial variations in water content within the root zone is crucial for precision irrigation practices and for the delineation of stream-tubes used in modeling the movement of water and solutes (e.g., salts, fetilizers, etc.) in soil. Measurements of apparent soil electrical conductivity (ECa) with electromagnetic induction sensors can help map changes in water content over time across a field. Indeed, ECa is a function of water content, soil type (e.g., texture), and salinity. Recently developed inversion techniques enable the estimation of water content, texture, or salinity from ECa values at discrete points through the soil profile. In this study eleven 350m-long saline soil transects were monitored on the day following irrigation (soil close to field capacity), using ECa measurements and soil sampling for calibration and validation of the water content estimates. The inversion of the ECa data allows for estimations of soil water content over the 11 profiles. Water content mapping provided 2-D images that reveal the efficacy of the employed irrigation practices (e.g., depth of penetration of the wetting front). Water content mapping is very accurate with a leave-one-out validation RMSE of 0.04 m3 m-3. This can improve irrigation practices, potentially allowing for much more sustainable and profitable agricultural water use, and provides a means of characterizing the moisture regime to define stream-tubes. The approach has applications for water use and management given it can identify inefficiencies in water application rates and use. Farmers, agriculture consultants, extension specialists could benefit greatly from the application of this methodology.
Technical Abstract: The ability to measure and map volumetric soil water theta quickly and accurately is important in irrigated agriculture. However, the traditional approach of using thermogravimetric moisture (w) and converting this to theta using measurements of bulk density (theta – cm3/cm3) is laborious and time consuming. To speed up the process electromagnetic (EM) instruments have been used to assist in mapping average theta along a transect or across a field. This is because ECa has been shown to be a function of theta, when other soil properties are uniform. However, mapping depth-specific soil theta has been little explored. One possible approach is to invert the ECa data to calculate estimates of true electrical conductivity theta at specific depths (i.e. 0.15, 0.45, 0.75, 1.05 and 1.35 m) and couple this to measured theta. This research explores this possibility by using a single frequency multi-coil DUALEM-421 across a centre-pivot irrigated Lucerne field (Medicago sativa L.) in San Jacinto, CA, USA. The first aim is to determine an optimal set of inversion parameters (i.e. forward modelling, inversion algorithm and damping factor – lambda) which are appropriate to establish a calibration between lambda and theta. In this regard the largest coefficient of determination (R2 = 0.56) is achieved when we used the FS model, S2 algorithm and a theta = 0.3. The second aim is to see if all the coil arrays of the DUALEM-421 are necessary. We conclude that while the DUALEM-1 produces a larger R2 (0.59), the use of the DUALEM-421 data is better (R2 = 0.56), because the total model misfit (4.70 mS m-1) is smaller and because it better accounts for the spatial variation of theta in the subsoil. In terms of predicting theta, the calibration equation (theta = 2.751 + 0.190 x lambda) was examined using a leave-one-out cross validation. The Lin’s concordance (0.73) between measured and predicted theta was good. The resulting 2-d depth slices and cross-sections gave insights into the spatial distribution of theta which allowed the inference of depth of saturated soil and location of the wetting front and identified areas where deep drainage may be problematic. The approach has applications for water use and management given it can identify inefficiencies in water application rates and use.