GNGTS 2017 SeSSione 3.2

673

APPLICATION OF ELECTRICAL RESISTIvITy TOMOgRAPhy TO MONITORThE SOIL-ROOT INTERACTIONS uNDER DEFICIT IRRIgATIOND. Vanella1, G. Cassiani2, L. Busato2, J. Boaga2, S. Consoli11 Dipartimento di Agricoltura, Alimentazione, Ambiente, Università degli Studi di Catania, Italy2 Dipartimento di Geoscienze, Università degli Studi di Padova, Italy

Introduction. �eoph�sical methods can provide indirect high-resolution information on soil water content (�WC) distri�ution, which is fundamental during irrigation to avoid excessive water depletion conditions, especiall� when water deficit treatments are imposed [e.g. using partial root-zone dr�ing technique -PRD- as descri�ed �� Romero-Conde et al. (2014)]. Recent studies (Cassiani et al., 2015� Consoli et al., 2017� �atriani et al., 2015) have shown that near-surface o�serving technologies (e.g. geoph�sical methods) can support and improve the irrigation operations in terms of �oth applied water amounts and irrigation timing. Furthermore, results have demonstrated the match �etween �WC variations and temporal changes in electrical resistivit� (ER). However, the effects of other governing factors (e.g. pore water electrical conductivit� and soil temperature) must also �e considered. In this stud�, we present and discuss the results of a 3-D ER� time-lapse monitoring applied in an orange orchard with the following main goals: i) verif�, with different time resolutions, the relia�ilit� of a small scale ER� setup to qualitativel� monitor the soil-root interactions, in the context of two irrigation treatments (i.e. full drip irrigation and PRD)� ii) identif�, for each treatment, the active root water uptake (RWU) patterns and their time evolution, �� integrating time-lapse ER� with ancillar� measurements.

Materials and methods. Experimental site and irrigation scheduling. We conducted small scale 3-D ER� monitoring in an orange orchard located in Eastern �icil� (Ital�) and �elonging to the Italian Council for Agricultural Research and Agricultural Economics Anal�ses (CREA). Here, 8-�ear old orange trees spaced are 4 m within the tree rows and 6 m �etween rows. �he soil is fairl� uniform with a sand�-loam texture, while the mean �WC at field capacit� (pF = 2.5) and wilting point (pF = 4.2) are 28% and 14%, respectivel�. Irrigation rates were fixed on the �asis of crop evapotranspiration (E�c). �wo different irrigation regimes were tested: (i) a control treatment (called �1), with trees irrigated with enough water to replace 100% of the E�c, and (ii) a partial root-zone dr�ing (PRD) treatment (called �2), with trees irrigated at 50% of the E�c level. In �oth cases, the drip irrigation took place using two surface lateral pipes per tree row. More in detail, in �1 the pipes were located on the same side, while in �2 the� were placed on opposite sides with respect to the tree trunk and irrigation was applied onl� to one lateral pipe. Moreover, ancillar� measurements were performed during the stud� period and comprised �WC at �oth treatments, soil temperature and electrical conductivit� of soil pore water (in order to evaluate their effect on the soil ER varia�ilit� and add the necessar� correction if needed), and tree transpiration rate, �� means of heat pulse velocit� sap flow technique.

3-D ERT time-lapse monitoring. ER� acquisition scheme. �mall scale 3-D ER� monitoring was conducted around two selected orange trees irrigated at full level (�1) and �� PRD (�2), respectivel�. �he ER� set-up (Fig. 1) comprised �oth superficial and �uried electrodes (204 in total) and consisted of 9 �oreholes (1.2 m deep) each housing 12 electrodes (verticall� spaced 0.1 m), plus 96 surface electrodes (spaced 0.26 m on a regular square grid). In �oth treatments, the �oreholes are spaced 1.3 m on a square grid, thus delimiting 4 quarters (named q1, q2, q3, q4), onl� one of which is centred around the tree (q4). Each quarter represents the minimal unit of ER� acquisition, with 72 electrodes, surrounding a soil volume of a�out 1.3 m×1.3 m, and 1.2 m thickness.

�he ER� monitoring was performed in an attempt to capture long-term variations (along the irrigation season) as well as short-term changes (during a da�), within the monitored irrigation season.

�he 3-D ER� long-term monitoring was conducted at the following time steps: i) when no irrigation was supplied (June)� ii) 1 month after the irrigation start (Jul�)� iii) at the end

674

GNGTS 2017 SeSSione 3.2

of irrigation (�eptem�er). At the �eginning of each ER� monitoring time steps a�ove, one ER� acquisition was conducted on the full 204 electrode setup (�ackground). During Jul� and �eptem�er, when the irrigation took place, we also acquired a full acquisition on all 4 quarters at the end of the dail� irrigation, on �oth �1 and �2 treatments. More frequent time-lapse acquisitions were performed on a hourl� �asis on the quarter surrounding the tree (q4 in �oth treatments).

3-D ER� data processing and inversion. All the ER� acquisitions took place with a ten-channel resistivit� meter (��scal Pro 72 �witch, IRI� Instruments) using the same acquisition scheme (skip-0 dipole-dipole). Direct and reciprocal resistance data were measured, to have an estimate of the data errors (Binle� et al., 1995) for each quarter (i.e. 72 electrodes). �he ER� data processing consisted of data error identification and inversion of the resistance values using an �ccam’s approach (R3t code, Binle�, 2013), where the target mismatch �etween measured and computed resistance data is set according to the data error� more specificall�, different inversion strategies were adopted: i) inversions aimed at producing 3-D ER “�ackground” images in all quarters for �oth treatments� ii) inversions aimed at producing images of 3-D ER changes �efore and after irrigation (at a dail� temporal scale), simultaneousl� for all quarters for �oth treatments� iii) time-lapse ER inversions of the individual quarters containing the trees (q4).

Results and discussion. Ancillary data observed during the 3-D ERT monitoring. �he results of the �WC monitoring for the PRD treatment show the expected alternating dr�ing and wetting c�cles on either side of the tree (i.e., east and west) after each switching event. In the �1 treatment, the �WC remained close to field capacit�. �oil temperature variations were, on average, approximatel� 2°C during each ER� acquisition. Considering that the ER changes 2% per °C (Friedman, 2005), we conclude that in our case the temperature effect is negligi�le with respect to the effect of inferred �WC changes (Nijland et al., 2010). �he anal�sis of soil pore water indicates a moderate salinit�, with EC25°C values in the range of 2-3 d� m

-1. �uch values should not affect the sensitivit� of our ER� measurements to �WC. During the ER�

Fig. 1 - �mall scale 3-D ER� monitoring scheme at (a) �1 and (�) �2 treatments.

GNGTS 2017 SeSSione 3.2

675

Fig. 2 - Background inversions of the datasets collected during the long-term ER� monitoring in 2015 (June, Jul�, �eptem�er) at (a) �1 and (�) in �2 treatments� (c, d) average ER (Ωm) values are reported in function of the depth.

676

GNGTS 2017 SeSSione 3.2

monitoring surve�s, the dail� average tree transpiration reached 1.9 mm d-1 in �1, and 0.9 mm d-1 in the �2.

�easonal changes shown by ERT data. Fig. 2 shows the 3-D-ER (Ω m) images derived from the �ackground acquisitions of June, Jul� and �eptem�er 2015 in �1 (Fig. 2a) and �2 (Fig. 2�), along with the ER profiles averaged within selected soil la�ers of the investigated soil volume (Fig. 2c for �1 and Fig. 2d for �2).

At the end of the irrigation season (�eptem�er), the mean reduction of ER, in the investigated soil profile, was of 69% in �1 and 38% in �2. �his is consequence of the adopted irrigation regimes (i.e. full irrigation versus PRD). �verall, the most nota�le features emerging from the �ackground inversions in Fig. 2 are the high ER (a�ove 100 ٠m) areas located especiall� at depths �etween 0.4 and 1.0 m at the �eginning of the irrigation phase. �ne of the most interesting aspects concerning the patterns of high ER in Fig. 2 is that the� seem all to evolve su�stantiall� over time. �his is a strong evidence against the widel� spread �elief that most of the electrical signal from roots comes from their large lignified structures (Amato et al., 2008� Rossi et al., 2011). In fact, the effect of large roots can �e mistaken for the associated effects of strong soil dr�ing (due to RWU) that roots ma� exert on the near�� soil. Results from our work seem to point towards the latter explanation.

Fig. 3 - a) �ime-lapse ER ratio volume at a selected time step (after the end of the irrigation, time 03) with respect to the �ackground condition (�efore irrigation, time 00)� �) tree transpiration rate (mm h-1), irrigation and ER� surve�s timing are displa�ed in the graph in function of time. Data refers to the full-irrigated treatment (�1) on 15 Jul 2015.

GNGTS 2017 SeSSione 3.2

677

Evidence of RWU patterns from ERT data. �he dail� time-lapse images reproduce fairl� complex patterns of ER (increasing and decreasing ER in % with respect to the �ackground), caused �� the effects of irrigation and �WC depletion �� RWU processes (Cassiani et al., 2015, 2016). Considering the results of the more frequent time-lapse measurements collected during the Jul� and �eptem�er irrigation experiments, Fig. 3a shows an example of time-lapse ER ratio images for q4 in �1, while Fig. 3� shows the hourl� transpiration fluxes (mm h-1) of the irrigated tree in �1.

B� comparing the ER changes in �1 and �2, some ke� features are noted: i) the decrease in ER occurs in the soil volume while the irrigation front progresses� ii) the increase in ER corresponds in time with the higher rate of transpiration fluxes� iii) in �2, the higher ER increase occurs at the dried side of the plot� iv) the soil depth showing ER changes is 50% larger in �1 than in �2� v) in general, the finer time resolution of the single quarter acquisitions is ver� helpful at detecting processes linked to RWU that modif� �WC on a hourl� scale, while a comparison of patterns �efore and after irrigation alone is definitel� more difficult to interpret.

Conclusion. �he stud� has proved the effectiveness of the 3-D ER� technique at a small scale of application in reproducing ER changes associated with soil water d�namics. Clear patterns of wetting and dr�ing were evident in the investigated soil profiles at different experimental time resolutions (season and dail�/hourl� time steps). �hese patterns were clearl� driven �� the irrigation operations and plant transpiration due to RWU processes. �he 3-D ER� results also identified the scale of the quarter plot (a�out 1.7 m2) as the minimum for capturing the main processes at the soil-root interface in the experimental orange orchard. �he complexit� of the RWU processes �� using soil electrical properties also emerges clearl� from this stud�, together with the need of controlling several ancillar� ground-�ased data. Due to the complexit� and heterogeneit� of the studied soil-root s�stem, the integration of h�drological and geoph�sical modelling might �e effective for improving the anal�sis of the recorded ER anomalies. Finall�, ER� ma� �e considered as a useful tool in precision irrigation strategies, in particular for identif�ing in which areas of the su�soil RWU occurs, thus allowing an optimisation of the irrigation procedure.

Acknowledgements �he authors acknowledge support in the frame of the colla�orative international consortium IRIDA “Innovative remote and ground sensors, data and tools into a decision support s�stem for agriculture water management” financed under the ERA-NE� Cofund WaterWorks2014 Call and from the ERANE�-MED project WA�A “Water �aving in Agriculture: �echnological developments for the sustaina�le management of limited water resources in the Mediterranean area”.

References Amato M., Basso B., Celano �., Bitella �., Morelli �.,Rossi R. (2008). In situ detection of tree root distri�ution and

�iomass �� multielectrode resistivit� imaging. �ree Ph�siolog�, 28, 10:1441-1448Binle�, A., Ramirez, A., Dail�, W., (1995). Regularised image reconstruction of nois� electrical resistance tomograph�

data. In: Beck, M.�., Ho�le, B.�., Morris, M.A., Waterfall, R.C., Williams, R.A. (Eds.), Process �omograph� - 1995. Proceedings of the 4th Workshop of the European Concerted Action on Process �omograph�, Bergen, 6–8 April 1995, pp. 401–410

Binle�, A., (2013). http://www.es.lancs.ac.uk/people/am�/Freeware/R3t/R3t.htm, R3t software version 1.8 March 2013

Cassiani, �., Boaga, J., Vanella, D., Perri, M.�., Consoli, �., (2015). Monitoring and modelling of soil-plant root zone interaction: the joint use of ER�, sap flow and Edd� Covariance data to define the volume of an orange tree root zone. H�drolog� and Earth ��stem �ciences, 19, 2213-2225, doi:10.5194/hess-19-2213-2015

Consoli, �., �tagno, F., Vanella, D., Boaga, J., Cassiani, �., & Roccuzzo, �. (2017). Partial root-zone dr�ing irrigation in orange orchards: Effects on water use and crop production characteristics. European Journal of Agronom�, 82, 190-202.

Friedman, �.P. (2005). �oil properties influencing apparent electrical conductivit�: a review. Computers and Electronics in Agriculture 46, 45–70

Nijland, W., Van der Meijde, M., Addink, E. A., & De Jong, �. M. (2010). Detection of soil moisture and vegetation water a�straction in a Mediterranean natural area using electrical resistivit� tomograph�. Catena, 81(3), 209-216

678

GNGTS 2017 SeSSione 3.2

Romero-Conde, A., Kusaka�e, A., & Melgar, J. C. (2014). Ph�siological responses of citrus to partial rootzone dr�ing irrigation. �cientia Horticulturae, 169, 234-238

Rossi, R. Amato, M., Bitella, �., Bochicchio, R., Ferreira �omes, J., J., Lovelli, �., Martorella, E., Favale, P., (2011). Electrical resistivit� tomograph� as a non-destructive method for mapping root �iomass in an orchard. European Journal of �oil �cience, 62 (2), 206–215

�atriani, A., Loperte, A., �oldovieri, F., (2015). Integrated geoph�sical techniques for sustaina�le management of water resource. A case stud� of local dr� �ean versus commercial common �ean cultivars, Agricultural Water Management, 162, 57-66