Time Lapse 3D Electrical tomography for soil-plant dynamics

Transcription

1 Time Lapse 3D Electrical tomography for soil-plant dynamics Jacopo Boaga 1, Giorgio Cassiani 1, Matteo Rossi 1 Andrea D Alpaos 1, Giuseppe Fadda 2, Mario Putti 2, Marco Marani 3 1. Department of Geosciences, Università di Padova, Italy 2. Department of Matemathics, Università di Padova, Italy 3. Department of Civil and Environmental Engineering, Duke University, Dhuram, USA

2 SUMMARY Non-invasive (geophysical) soil monitoring: methods, strengths and limitations 3D time-lapse ERT monitoring of an apple tree 2D time-lapse ERT in salt marshes Conclusions and outlook

3 What geophysical methods can help define structure / texture water table aquifer impermeable bedrock large scale small scale

4 What geophysical methods can help define structure / texture fluid-dynamics spring evapo-transpiration water table aquifer impermeable bedrock large scale water table small scale

5 GOAL Integrate measurements and physical models that explain the spacetime evolution of state variables (e.g. moisture content, solute concentration and temperature) that affect the space-time changes of geophysical response. Physical model (e.g hydrologic) Geophysical measurements physical parameters (e.g. hydraulic conductivity) structure (geometry, geology) dynamics (fluids, temperature)

6 SUMMARY Non-invasive (geophysical) soil monitoring: methods, strengths and limitations 3D time-lapse ERT monitoring of an apple tree 2D time-lapse ERT in salt marshes Conclusions and outlook

7 Case 1 CLES, val di Non, Trentino Noce catchment apple orchard EU FP7 Project

8 sandy-silty soil with no clay EU FP7 Project

9 Construction of the micro ERT cross-borehole system 4 PVC tubes Length =120 cm; Ø= 1 inch Totally internal wiring Built with 10 cm water-tight segments to allow internal link operability Stainless steel circular electrodes with height of 3 cm

10 Field deployment - Installation without pre dig for the max electrode-soil coupling - Selected an apple tree already monitored - by other means - (dielectric probes) Resistivimeter SYSCAL pro 72 channels (48 in boreholes, 24 on surface)

11 Acquisition scheme A complete skip-0 dipole-dipole scheme with reciprocal was used for all acquisitions.

12 Repeated (seasonal) measurements Irrigation tests Date Note 15/10/10 Installation and Measurement 1 14/01/11 Measurement 2 04/04/11 Measurement 3 28/04/11 Measurement 4 18/05/11 Measurement 5 06/07/11 Measurement 6 04/08/11 Measurement 7 + Irrigation TEST 07/09/11 Measurement 8 05/10/11 Measurement 9 03/05/12 Measurement 10 + Irrigation TEST 04/11/12 Measurement 11 + Irrigation TEST

13 Three irrigation tests: August 2011, May 2012, November 2012 EU FP7 Project August 2011: irrigation performed via two drippers on the ground surface: total flow rate =2.4 l/h for six hours, following a long dry period. May 2012: widespread irrigation performed with a sprinkler ; total water volume = 500 l over 2.5 hours, at the top of growing season. November 2012: widespread irrigation performed via a sprinkler ; total water volume = 500 l over 5 hours, wet period following apple harvest (low ET).

14 ERT inversion Using the ERT code R3T (A.Binley, Lancaster University)

15 August 2011 experiment: resistivity ratio with respect to background at four time steps. The iso-surface equal to 60 % of the background resistivity does not penetrate any deeper than cm below ground surface.

16 May 2012 experiment: resistivity ratio with respect to background at four time steps shown on the horizontal slice at 30 cm depth. Moisture content measured by TDR in the top 32 cm. The moisture content was already high at the start of the experiment.

17 May 2012 experiment: resistivity ratio with respect to background at 30 cm depth and at 8.5 hours after start of irrigation 30 cm depth root suction zone? % Resistivity ratio w.r.t. background

18 November 2012 experiment: resistivity ratio with respect to background at four time steps. Moisture content measured by TDR in the top 32 cm. The initial moisture content is higher than other experiments, low ET

19 May 2012 experiment: resistivity ratio with respect to background averaged over horizontal slices root suction Zone? 0.5 h after irrigation start irrigation end at 2.5 h

20 Rho EU FP7 Project May 2012 experiment: resistivity changes converted into saturation changes and averaged along horizontal planes. Archie from lab Sw root suction Zone? 0.5 h after irrigation start irrigation end at 2.5 h

21 November 2012 experiment: resistivity ratio with respect to background averaged over horizontal slices? 0.5 h after irrigation start 2.5 h after irrigation start

22 May 2012 experiment: mass balance issue from 3D ERT Note that the total irrigated water amounts to 500 liters

23 Sw EU FP7 Project We applied the CATHY (CATchment HYdrology) model [Bixio et al, 2000; Camporese et al., 2010], a physicallybased 3D distributed model which uses Richards equation to describe variably saturated flow in porous media. We used the following parameters: K s = 6x10-5 m/s Van Genuchten n = 1.35 Porosity = 0.5 r = 8x10-2 a = -0.7

24 Depth m EU FP7 Project May 2012 experiment Time = 2 hours Volume of interest tracking of particle motion starting from the surface Pseudo-color Var-saturation m

25 Depth m EU FP7 Project May 2012 experiment Time = 3 hours Volume of interest tracking of particle motion starting from the surface Pseudo-color Var-saturation m

26 Depth m EU FP7 Project May 2012 experiment Time = 5 hours Volume of interest tracking of particle motion starting from the surface Pseudo-color Var-saturation m

27 Depth m EU FP7 Project May 2012 experiment Time = 3 hours Volume of interest Pseudo-color Var-saturation m

28 Depth m EU FP7 Project Piston effect? Time = 3 hours (240 μs/cm) November and May irrigation experiment Pseudo-color Var-saturation m

29 SUMMARY Non-invasive (geophysical) soil monitoring: methods, strengths and limitations 3D time-lapse ERT monitoring of an apple tree 2D time-lapse ERT in salt marshes Conclusions and outlook

30 Case2 TIME LAPSE MICRO-ERT in Venice Lagoon

31 2D TIME LAPSE MICRO-ERT in Venice Lagoon Aim: are marsh plants able to induced a permanent aerated layer when flooded? Marani et al. 2006, Water Resource - 24 buried electrodes + 24 surface elect m spacing - Time-lapse skip0 dip-dip (pre, during and after flooding) - 6 Tensiometers in depth

32 TIME LAPSE MICRO-ERT in Venice Lagoon July 2012 experiment: resistivity ratio with respect to background at 3 time steps during marsh flooding Boaga et al. 2013, submitted to GRL Dryer zone at roots depth

33 Confirmed by tensiometers TIME LAPSE MICRO-ERT in Venice Lagoon Water level Dryer zone at cm depth Boaga et al submitted to GRL

34 TIME LAPSE MICRO-ERT in Venice Lagoon Boaga et al submitted to GRL Dryer zone at roots depth

35 Conclusions Near surface geophysics is strongly affected by both static and dynamic soil/subsoil characteristics. This fact, if properly recognized, is potentially full of information on the soil/subsoil structure and dynamic behaviour. ERT is a technique that can provide a lot of information on small scale, vegetation related processes. Integration with physical modelling is essential to capture the meaning of space-time signal changes However, it must be recalled that ERT response depends on both soil moisture AND pore water salinity. This can also be a further source of information, if properly analyzed.

36 Transpiratio n (mm h -1 ) EU FP7 Project Outlook Sap flow and Eddy Correlation tower for ET meas. ERT + suction cup for soil water monitoring (ongoing experiment in Sicily, Italy, orange tree) 0,3 0,2 0,1 0, hours

37 Outlook COUPLED HYDRO-GEOPHYSICAL INVERSION OF ELECTRICAL RESISTIVITY TOMOGRAPHY USING SEQUENTIAL DATA ASSIMILATION Conceptual plant model indicating mesh nodes of Richards equation solver and the distribution of the plant water flux paths. The model is based on an optimality criterion maximizing plant transpiration.

38 Thanks for your attention EU FP7 Project Acknowledgements ALBERTO BELLIN, BRUNO MAJONE, Università di Trento, Italy SIMONA CONSOLI Università di Catania, Italy FUNDING FROM: - EU FP7 CLIMB - CARIPARO FOUNDATION EXCELLENCE PROJECT - MIUR PRIN 2011 Innovative methods for water resources management under hydro-climatic uncertainty scenarios