Environ. Sci. Technol. 2001, 35, 753-760
Fluorescence Imaging of Tracer Distributions in Soil Profiles P H I L I P P A E B Y , † U T E S C H U L T Z E , * ,† DANIEL BRAICHOTTE,‡ MAYA BUNDT,§ FARNAZ MOSER-BOROUMAND,‡ HANNES WYDLER,† AND HANNES FLU ¨ HLER† Institute of Terrestrial Ecology, Swiss Federal Institute of Technology Zu ¨ rich (ETHZ), Grabenstrasse 11a, CH-8952 Schlieren, Switzerland, Department of Rural Engineering, Air and Soil Pollution Laboratory, Swiss Federal Institute of Technology Lausanne (EPFL), GR Ecublens, CH-1015 Lausanne, Switzerland, and Swiss Federal Institute of Forest, Snow, and Landscape Research (WSL), Zu ¨ rcherstrasse 111, CH-8903 Birmensdorf, Switzerland
To evaluate and parametrize transport models for the vadose (partially water-unsaturated) zone, information about the spatial distributions of solutes is needed. We describe a technique for the simultaneous imaging of several fluorescent tracers in structured field soils. With this technique, we obtain information on local mixing under field conditions. Local dispersion is a decisive process that discriminates different flow regimes. The imaging device consists of a high-power xenon lamp and a sensitive charge coupled device (CCD) camera. The three fluorescent dyes Brilliant sulfaflavine (BF), Sulforhodamine B (SB), and Oxazine 170 (OX) were chosen as solute tracers for their spectroscopic properties and different sorption coefficients. We conducted a field experiment using these tracers and took images of their distribution in a vertical soil profile. The fluorescence images (1242 by 1152 pixels) were corrected for nonuniform lighting, changing surface roughness, and varying optical properties of the soil profile. The resulting two-dimensional relative concentration distributions were similar for BF and SB. The reason might be the fast transport regime, which prevents the establishment of sorption equilibria. According to its higher sorption coefficient, OX was more strongly retarded. In this paper, we show that the fluorescence imaging technique is a powerful tool for the in-situ investigation of transport processes of fluorescent solute tracers in soil profiles. Due to the high spatial resolution of the tracer concentration maps and the ability to detect the flow field characteristics of differently reactive tracers simultaneously under field conditions, this technique provides valuable experimental data for the test and development of theoretical models for heterogeneous solute transport in soils.
Introduction In field soils and laboratory columns, solute transport is often studied using salts, radioactive isotopes, or dyes as tracers. * Corresponding author phone: ++41-1-6336075; fax: ++41-16331123; e-mail:
[email protected]. † Swiss Federal Institute of Technology Zu ¨ rich. ‡ Swiss Federal Institute of Technology Lausanne. § Swiss Federal Institute of Forest, Snow, and Landscape Research. 10.1021/es000096x CCC: $20.00 Published on Web 01/11/2001
2001 American Chemical Society
Conventional techniques for measuring tracer concentrations in soil, such as sampling soil cores or soil solution with suction cups, have a rather poor spatial resolution and, in the latter case, average over an unknown measuring volume. A good spatial resolution however is necessary to detect and quantify dominant features of the flow field. Local dispersion, which is the small-scale mixing process, has in recent years been recognized to be a or even the clue for explaining why fundamentally different flow regimes occur in soils, especially under water-unsaturated conditions. Local dispersion affects the spreading and dilution of solutes (1, 2). Local dispersion in soils and subsoils is in many cases a highly anisotropic phenomenon. The problem is that none of the available tracer detection techniques captures such features of the flow field heterogeneity. In addition, solute transport studies are usually carried out with fairly mobile tracers, but the ultimate goal is often to describe the fate of reactive (sorbing) compounds such as pesticides, heavy metals, radionuclides, etc. In this paper, we present a method that makes the smallscale mixing processes detectable and allows us to compare the local distribution of differently mobile compounds and all this not only under laboratory conditions in columns but also under real-world conditions in the field. In several studies, nonfluorescent dyes have been used to visualize flow paths in soils. From photographs taken from vertical or horizontal soil profile cuts, the dye coverage can be assessed and analyzed using digital image analysis. With the exception of a few studies (3, 4), this method usually yields only qualitative information on the dye distribution (5, 6). Moreover, due to insufficient detection selectivity, it is limited to the application of only one dye tracer at a time. With respect to the evaluation of models for solute transport in soils and to the determination of the corresponding parameters, it is interesting to compare the transport patterns of differently reactive tracers. Using fluorescent instead of nonfluorescent dyes as tracers, their spatial distribution on a soil profile cannot only be detected simultaneously but also quantitatively by fluorescence spectroscopy. Fluorescence spectroscopy is well-established in environmental analysis. Mostly techniques that utilize laser excitation (laser-induced fluorescence) in combination with fiber optics are applied for the in-situ detection of environmental pollutants in air, water, and soil (7-10). Moreover, fiber optic spectroscopy was used in the context of soil science, e.g., to study the flow of fluorescent dyes in porous media such as glass beads (11). The spectroscopic techniques mentioned allow highly sensitive and selective on-site detection of fluorescent compounds but are restricted to the performance of point measurements. In contrast, we are interested in a high spatial resolution for the determination of the distribution of different fluorescent tracers in a soil profile. We therefore developed a fluorescence imaging technique based on a device that consists of a high-power xenon lamp and various optical filters for selective fluorescence excitation and a highly sensitive CCD camera for fluorescence detection. With this setup, a spatial resolution of ca. 1 mm2 per pixel (image size of 1242 × 1152 pixels) can be achieved. Three fluorescent dyes were chosen as solute tracers according to their different transport characteristics and to minimize difficulties that may impair fluorescence measurements in soils. These difficulties are primarily (i) the quenching of fluorescence by humic substances (12) or by the interaction with dissolved molecules and mineral surfaces; (ii) photodecomposition of the dyes; (iii) dependence of the fluorescence intensity on VOL. 35, NO. 4, 2001 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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powered by a gasoline-driven generator. All the equipment fit into a medium-sized van. We selected the three fluorescent dyes Brilliant sulfaflavine (BF; C20H15N2NaO5S, no CAS No. available, Sigma Chemical Co., St. Louis, MO), Sulforhodamine B monosodium salt (SB; C27H29N2NaO7S2, CAS No. 3520-42-1, Fluka Chemie AG, Buchs, Switzerland), and Oxazine 170 perchlorate (OX; C21H22ClN3O5, CAS No. 62669-60-7, Fluka Chemie AG, Buchs, Switzerland) as tracers because of their favorable fluorescence properties and their sufficient water solubility. The UV/Vis absorption as well as the fluorescence spectra of the different dyes are separated well from each other allowing selective excitation and detection of their fluorescence. The fluorescence intensity of the dyes does not change when illuminated for a few hours and is pH independent in the range from 4 to 9. The background fluorescence of the soil itself does not interfere significantly with the dye emission. Except for OX, fluorescence is not quenched by soil organic matter. The dyes have different sorption coefficients for soil (BF < SB < OX).
FIGURE 1. Experimental setup used for imaging of fluorescent tracers in soil profiles. A xenon lamp provides the fluorescence excitation light, which is guided through a liquid lightguide to the soil profile after appropriate optical filtering. A slow-scan CCD camera system is used for the detection of the light re-emitted from the soil profile. Detailed information on the different components of the optical setup are given in the text. ionic strength and pH (13); and (iv) interfering fluorescence of the soil background. The acquired fluorescence images of the two-dimensional distributions of the different dyes in the soil profile must be processed to gain concentration maps. In the present study, we propose a correction procedure that copes with the influence of changing roughness and varying optical properties of the soil on the measured fluorescence intensities. The suitability of the fluorescence imaging technique to visualize transport phenomena of solutes in soils is demonstrated with a field experiment.
Experimental Methods and Equipment Instrumentation for Fluorescence Imaging and Fluorescent Tracer Selection. The device used for fluorescence imaging consists of an excitation and a detection module (Figure 1). The excitation light is generated by a water-cooled 1-kW xenon lamp (KiloArc, Photon Technology International, South Brunswick, NJ), optically filtered and guided through a liquid lightguide (series 380, Lumatec, Munich, Germany) to the soil profile. Re-emitted light (fluorescence as well as reflected light) from the soil profile is, after appropriate optical filtering, detected by a slow-scan CCD camera system (Antares TE4 EEV CCD05-30 MPP, AstroCam Ltd., Cambridge, U.K.) equipped with a high-speed normal lens (Noct-Nikkor 58 mm f/1.2, Nikon Corporation, Tokyo, Japan). The camera system consists of a Peltier/air-cooled CCD with a lightsensitive area of 1242 × 1152 pixels and a readout electronic that permits 16-bit digitization and up to 83 kHz readout rates. The spatial resolution depends on the particular experimental conditions; for the measurements presented here, 1 pixel in the image corresponded to ca. 1 mm2 in the soil profile. Images are captured with the software PixCel (Version 2.1, LSR AstroCam Ltd., Cambridge, U.K.) that is supplied with the camera and runs under Windows 95 (Microsoft Corporation, Redmond, WA). For field use, the whole equipment can be placed on a rugged rack and is 754
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Spectral windows, appropriate for selective excitation and detection of the different fluorescent dyes, were designed by choosing a suitable series of optical filters. The excitation filters 1 (long pass; Reynard Corporation, San Clemente, CA), 2 (short pass; Reynard Corporation), and 3 (band-pass; Omega Optical Inc., Brattleboro, VT) as well as the emission filters 1 (long pass; Schott, Mainz, Germany) and 2 (short pass; Reynard Corporation) were specifically selected for each dye and must be exchanged when measuring another dye. The ranges of high optical transmission of the filter combinations as well as the UV/Vis absorption and fluorescence spectra of the fluorescent dyes are shown in Figure 2. Fixed elements of the optical path are a hot mirror (Tempax 113, Schott, Mainz, Germany) that removes most of the NIR/IR part of the excitation light before it enters the liquid lightguide and various lenses (Melles Griot, Irvine, CA). Three images of the soil profile (recording the light intensity at the coordinates x and y) are taken for the detection of each of the three fluorescent dyes: (i) Fluorescence image F(x,y): The dye-specific combination of excitation and emission filters is used for the fluorescence excitation and detection of a given dye. Typical exposure times are in the range of 100-400 s. (ii) Reflection image R(x,y): To obtain an image of the reflected excitation light intensities, the emission filters in front of the CCD camera are removed. For pure reflection measurements, the same optical filters would have to be used at the output of the xenon lamp and in front of the CCD camera; otherwise, not only reflected excitation light but also fluorescence can reach the detector. However, since the fluorescence intensities are some orders of magnitude lower than the intensities of the reflected light, we omitted the optical filters in front of the CCD camera. Typical exposure times for reflection images are in the range of 100 ms. (iii) Flat-field image I(x,y): The spatial intensity distribution of the incident light is recorded by taking an image of a smooth gray cardboard covering the entire soil profile. The gray cardboard was used as a cost-effective alternative to professional diffuse reflectance panels (made of Spectralon, for example). Although it may not provide a real “lambertian surface”, its suitability for our application was tested in preliminary experiments. The same optical filters are used as for the acquisition of the reflection image. The procedure developed for the determination of the two-dimensional distribution of the dye concentration from the raw fluorescence image is discussed later. The images were processed on a personal computer using IDL software (Version 5.0, Research Systems Inc., Boulder, CO).
FIGURE 2. UV/Vis absorption (left) and fluorescence spectra (right) of the three fluorescent dyes Brilliant sulfaflavine (BF; - - -, light gray), Sulforhodamine B (SB; s, gray) and Oxazine 170 (OX; -‚-, deep gray) in aqueous solution (excitation wavelength λex ) 418 nm for BF, 564 nm for SB, and 621 nm for OX). At the bottom of the figure, the ranges of high optical transmission of the optical filter combinations used for fluorescence excitation (left) and detection (right) with the fluorescence imaging device are indicated by shaded regions. UV/Vis Absorption, Fluorescence, and Diffuse Reflectance Spectroscopy. UV/Vis absorption spectra of dye solutions were measured with a Varian Cary 1E UV/Visible spectrophotometer (Varian, Palo Alto, CA), while fluorescence spectra were recorded with a Perkin-Elmer LS 50 fluorescence spectrometer (Perkin-Elmer, Offenbach, Germany). The diffuse reflectance spectrum of a soil sample, representative for the soil profile under investigation, was measured with a Varian Cary 1E spectrophotometer equipped with a diffuse reflection accessory similar to the Praying Mantis of Harrick Scientific (Ossining, NY). The diffuse reflectance R∞ of the sample was determined relative to a white reflectance standard (BaSO4, Eastman Kodak, Rochester, NY). For the determination of the absorption and scattering coefficient of the soil, 5.7 g of soil was mixed with 2.3 mL of SB solution of varying concentration. The diffuse reflectances of these mixtures were determined at the wavelength of maximum absorption of SB (λ ) 564 nm) as described above.
Image Processing To assess the two-dimensional concentration distribution of a fluorescent dye in a soil profile, the fluorescence signal measured at a certain location has to be related to the corresponding dye concentration. For a fluorescent dye dissolved in a nonabsorbing and nonscattering medium, the fluorescence intensity F is related to the molar dye concentration c by
F ) κΦFI[1 - e(-2.303cd)]
(1)
with ΦF denoting the dye’s fluorescence quantum yield, I is the intensity of the incident light, is the molar absorption coefficient of the dye, and d is the thickness of the absorbing layer (14). The proportionality constant κ depends on the particular instrumental settings such as the detector sensitivity, the aperture, the exposure time, etc. For dye solutions
with 2.303cd < 0.05, eq 1 can be approximated by
F ) 2.303κΦFIcd
(2)
A comprehensive overview concerning fluorescence spectroscopy of solutions is given in refs 14 and 15. If the fluorescent dye is embedded in a scattering as well as absorbing matrix such as a soil, F also depends on the optical properties σ, i.e., the absorption and scattering characteristics, of the matrix:
F ) f(κ, ΦF, I, , c, d, σ)
(3)
For a given instrumental setting, a given dye, and a given matrix, the dye concentration of a sample can easily be determined by a F/c calibration procedure performed with samples of known dye concentration. If the dye concentration does not exceed the value where the approximation made for eq 2 no longer holds, the relation between F and c is linear:
F ) mc + b
(4)
Explicit knowledge of the parameters in eq 3 is not required since the parameters are lumped into the slope m and the intercept b of the empirical calibration function (eq 4). In case of fluorescence imaging measurements of a soil profile, it has to be considered that some of the parameters given in eq 3 are a function of space: (i) the illumination of the soil profile is not uniform, i.e., I ) f(x,y); (ii) the soil surface is rough and the incidence of light varies therefore with space; and (iii) the optical properties of the matrix differ for different locations in the soil profile, i.e., σ ) f(x,y). Since it is not feasible to measure calibration functions for each location in the soil profile, we propose an image correction procedure. After image processing, the corrected fluorescence intensities correspond to intensities that would have been measured from a uniformly illuminated, flat, and homogeVOL. 35, NO. 4, 2001 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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FIGURE 4. Schematic illustration of the theoretical model used for the correction of fluorescence intensities measured from a soil profile. Dye molecules are assumed to be located directly on the soil surface or in a thin water film covering soil particles, respectively. The total light intensity available for excitation of dye fluorescence consists of the intensity of the light coming directly from the light source (Idir) and the intensity of the part of the direct light that is reflected from the soil surface (Iref).
FIGURE 3. Flowchart outlining the major steps of the image processing procedure to calculate an image of relative or absolute dye concentrations from a raw fluorescence image taken from a soil profile (rectangles denote images, rhomboids denote operations). Only images of relative dye concentration have been calculated. neous soil surface. Absolute dye concentrations can then be determined for the whole image using a single calibration function. In the following, the different image processing steps are discussed into detail. A flowchart of the correction procedure (Figure 3) outlines the major steps graphically. Step 1: Correction for Nonuniform Lighting. As shown in eq 2, the fluorescence intensity is proportional to the intensity of the incident light. The recorded flat-field image I(x,y) is a map of the spatial distribution of the incident light. The raw fluorescence image F(x,y) is corrected for nonuniform illumination of the soil profile by dividing it by I(x,y). Moreover, it is normalized with the median value, hI, of the flat-field image:
F1(x,y) )
F(x,y)Ih I(x,y)
(5a)
The same is done for the reflection image R(x,y):
R1(x,y) )
R(x,y)Ih I(x,y)
(5b)
The corrected images are subscripted according to the number of the correction step as F1(x,y) and R1(x,y). Step 2a and b: Correction for Surface Roughness and for Varying Soil Optical Properties. For a rough soil surface with heterogeneous optical properties, the light actually 756
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available for excitation of dye fluorescence, E(x,y), has not necessarily the same intensity as the incident light I(x,y): (a) surface roughness (shadowing of certain regions within the soil profile) or (b) absorption of a part of the incident light by the soil matrix may cause discrepancy. The reflection image, R(x,y), is a map of the backscattered part of the incident light and therefore contains the information on the surface roughness and the optical characteristics of the soil profile. To correct the fluorescence image, we use information from the reflection image and consider the two effects a and b independently from each other. For the correction for surface roughness, we assume that the optical properties of the soil matrix are constant over the whole soil profile. Under this assumption, R1(x,y) is an image of the illuminated and shaded regions in the soil profile and therefore of the light available for fluorescence excitation, E(x,y). Since the intensity of the excitation light is proportional to the fluorescence intensity, F1(x,y) can be corrected for surface roughness according to
F2a(x,y) )
h1 F1(x,y)R R1(x,y)
(6)
with R h 1 denoting the average light intensity of the reflection image. For the correction of varying soil optical properties, we assume that the soil surface is macroscopically flat. If incident light penetrates an absorbing powdery material like soil, one part of the incident light is absorbed, and the other part is scattered back (Figure 4). Because of the random orientation of the soil particles, the light reflection is mainly diffuse. The extent of light absorption and reflection depends on the optical properties of the material at the wavelength of the incident light. According to the phenomenological theory given by Kubelka and Munk (16) the optical properties of a material can be described by a wavelength-dependent absorption coefficient K (cm-1) and a wavelength-dependent scattering coefficient S (cm-1). K and S are related to the so-called diffuse reflectance R∞ by
K (1 - R∞) ) S 2R∞
2
(7)
This relationship is called Kubelka-Munk function. The diffuse reflectance R∞ is the ratio of the radiant flux in the negative z-direction (induced by scattering) to that in the positive z-direction (incident light) in case of an infinitely thick sample and can be measured by diffuse reflectance spectroscopy (see Experimental Methods and Equipment). It corresponds to the fraction of the incident light that is reflected and not absorbed by the material. The diffuse reflectance spectrum of a soil sample representative for the soil profile investigated in this work is shown in Figure 5. The spectral shape is typical for soils (17, 18) with diffuse reflectance values ranging from ca. 0.07 (λ ) 400 nm) to 0.30 (λ ) 800 nm). The fluorescence intensity detected from a dye contained in a soil sample depends on the optical properties of the soil. Because incident light is attenuated due to the absorption and scattering of radiation when penetrating a soil sample, less light is available for the excitation of dye molecules. The light attenuation can be described by:
I(z) ) I exp[-(K + S)z]
(8)
with I(z) denoting the light intensity at sample depth z and I denoting the intensity of the incident light on the sample surface (z ) 0). Thus, the fluorescence intensity decreases with increasing distance from the sample surface depending on the values of K and S. Assuming that the fluorescence excitation becomes negligible when I(z) drops below 5% of the incident light intensity (i.e., ln[I(z0.05)/I] ) -3), the thickness z0.05 of the layer from which most of the fluorescence originates can be calculated from eq 8, provided K and S are known. We therefore measured K and S of a representative soil sample adapting an approach suggested in ref 16. Homogenized soil samples were spiked with increasing amounts of a dye that absorbs at the wavelength for which K and S should be determined. The overall absorption coefficient Ktot of a spiked sample is the sum of a constant term, Ksoil, corresponding to the absorption coefficient of the soil, and a term, Kdye, that depends on the concentration of the dye, i.e.
Ktot ) Ksoil + Kdye
(9)
where Kdye is related to the dye concentration and the molar absorption coefficient of the dye at the selected wavelength:
Kdye ) 2 ln(10)c
(10)
Hence, a plot of (1 - R∞)2/2R∞ against Kdye results in a straight line with slope 1/S and intercept Ksoil/S. In the inset of Figure 5, this plot is shown for a representative soil sample spiked with the fluorescent dye SB. By this method, we estimated an absorption coefficient of Ksoil ) 145 cm-1 and a scattering coefficient of S ) 62 cm-1 at a wavelength of λ ) 564 nm. From these estimates, we calculated z0.05 to be 145 µm. K and S values recently measured for soils by Schober and Lo¨hmannsro¨ben (19) compare well with these values and result in similar estimates of the thickness of the layer mainly contributing to fluorescence. Because of the small value of z0.05, it is reasonable to assume that the observed fluorescence originates from dye molecules located at or close to the soil surface. This assumption is in accordance with results of Apitz et al. (20), who showed that fluorescence originates only from molecules located on the surface of clay or sand particles or in the interstices between the first particle layer.
FIGURE 5. Diffuse reflectance spectrum of a soil sample representative for the examined soil profile. Inset: Plot of the KubelkaMunk function (eq 7) measured for soil samples of varying SB concentration against the absorption coefficient Kdye of SB at a wavelength of 564 nm. The given standard deviations are based on three replicate measurements. From the slope and intercept of the linear regression (solid line), a scattering coefficient of S ) 62 cm-1 and an absorption coefficient of K ) 145 cm-1 of the soil were determined. Under natural conditions, soil particles are covered by a water film. The dye molecules in this film contribute to fluorescence. If we assume that the attenuation of the incident light in the water film is negligible, then the intensity E(x,y) of the excitation light at location (x,y) is the sum of (i) the intensity of the incident light, Idir, and (ii) the intensity of the fraction of the incident light, Iref(x,y), that traversed the film and is being reflected at the soil surface (Figure 4):
E(x,y) ) Idir + Iref(x,y) ) Idir + Rex ∞ (x,y)Idir ) Idir(1 + Rex ∞ (x,y)) (11) Idir is supposed to be constant for each location (x,y), i.e., the illumination of the soil profile is supposed to be uniform. Iref(x,y) depends on the local diffuse reflectance of the soil at ex the excitation wavelength, Rex ∞ (x,y). The values of R∞ (x,y) are not known, but they are related to the measured intensities of the reflection image R1(x,y) by
Rex ∞ (x,y) R h ex ∞
)
R1(x,y) R h1
(12)
Here, R h ex ∞ denotes the average diffuse reflectance of the soil profile at the excitation wavelength. It is determined from a homogenized soil sample that is representative for the soil profile using diffuse reflectance spectroscopy. The value of R h ex ∞ for a given fluorescent dye can be taken from the diffuse reflectance spectrum shown in Figure 5 (BF, 0.07 at 418 nm; SB, 0.13 at 565 nm; OX, 0.18 at 618 nm). The intensity of the excitation light, E2b, corrected for the local variations of the optical properties of the soil should be constant over the whole soil profile and is given by
E2b ) Idir + R h ex ∞ Idir
(13)
The fluorescence intensity is directly proportional to the intensity of the excitation light. The corrected fluorescence image Fex 2b(x,y) is then obtained from F1(x,y) by VOL. 35, NO. 4, 2001 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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E2b 1+R h ex ∞ Fex ) F1(x,y) ) 2b(x,y) ) F1(x,y) ex E(x,y) 1 + R∞ (x,y) 1+R h ex ∞ (14) F1(x,y) ex 1+R h ∞ R1(x,y)/R h1 Since not only a part of the incident light but also a part of the emitted fluorescence light can be absorbed by the soil matrix, we must adjust the recorded fluorescence by a similar correction:
F(x,y) ) Fdir(x,y) + Fref(x,y) ) Fdir + Rem ∞ (x,y)Fdir
(15)
Fdir(x,y) is the intensity of the fluorescence that is emitted in direction of the detector, and Fref(x,y) is the intensity of the fluorescence that is emitted in direction of the soil surface but reflected back to the detector. Rem ∞ (x,y) denotes the local diffuse reflectance of the soil at the emission wavelength. Since a strong correlation was found between the reflection images measured at different wavelengths, we substitute R h em h 1 for Rem h em ∞ R1(x,y)/R ∞ (x,y) in eq 15. The value of R ∞ for a given fluorescent dye is taken from the diffuse reflectance spectrum of the soil shown in Figure 5 (BF, 0.09 at 514 nm; SB, 0.15 at 580 nm; OX, 0.19 at 650 nm). Combining both corrections we finally obtain the result:
Fex,em (x,y) ) 2b F1(x,y)
(
1+R h ex ∞
1+R h ex h1 ∞ R1(x,y)/R
)(
1+R h em ∞
1+R h em h1 ∞ R1(x,y)/R
)
(16)
Lo¨hmannsro¨ben and Schober (17) proposed a simpler empirical approach for the correction of fluorescence calibration functions measured for mineral oils on soils with varying optical properties. These authors divided the fluorescence signals by the diffuse reflectances of the soil at the excitation wavelength and found a significant reduction of the variations in the slopes of the calibration curves. Combination of Correction Steps 2a and b. Both surface roughness and the optical properties of the soil vary in space (x,y). Thus, a change in reflection cannot be assigned exclusively to a change in surface roughness or in surface absorption. If we assume that the surface roughness and the optical properties of the soil vary over the soil profile independently from each other and have the same importance, then the following correction function seems appropriate:
[( ) ( )(
F2a+b(x,y) ) F1(x,y)
h1 1 R + 2 R1(x,y)
1+R h ex 1 ∞ 2 1+R h ex R (x,y)/R h1 ∞ 1
1+R h em ∞
1+R h em h1 ∞ R1(x,y)/R
)]
(17)
Here, we assume that the effects of surface roughness and surface absorption are equally important. This is supported by the measurement of reflection images from a soil profile at six different wavelengths (400, 450, 500, 550, 600, 650 nm), which revealed that ca. 50% of the image pixels showed increasing reflectance values with increasing wavelength according to the diffuse reflectance spectrum of the soil, whereas for the other 50% of the image pixels no wavelength dependence of the reflectance values was found. If the first effect is attributed to soil absorbance and the second to shadowing of soil regions by surface roughness, it is reasonable to assume that the impact of these effects on the fluorescence signal measured from a soil profile is more or less equally important. 758
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Image Smoothing. Small image areas of extremely high or low reflection intensities, such as strongly reflecting soil components, specular reflections, little holes, etc., introduce large errors. For this reason, smoothing is applied before application of eq 17. However, smoothing impairs the spatial resolution and should therefore be employed only in critical regions. Critical regions are detected by a large local variance of reflection that exceeds the variance of a reference region without spots of very high or very low reflection. Both the detection of the critical regions and the smoothing is performed by a locally adapting digital filter:
(
SS(x,y) ) 1 -
νn
)
νw(x,y)
Sh w(x,y) +
(
νn
νw(x,y)
S(x,y)
)
(18)
where SS is the filter output at a certain location (x,y), i.e., the smoothed signal, SS(x,y) is the original signal at the same location, Sh w(x,y) the local mean of the signal in a region around (x,y), νw(x,y) the local variance of the reflection in this region, and νn, the variance of the reflection in a reference region. The region to calculate the local mean and variance is a quadratic area of 7 × 7 pixels surrounding the central location. Such a region is called filter window. To calculate the filter output in the whole image, the filter window moves over the whole image and applies the filtering eq 18 to the central locations. This filter is applied to both signal images, the reflection, and the fluorescence image. However, standard and local variances are determined from the reflection image only. The filter output in the fluorescence image depends therefore on the corresponding values in the reflection image. If the variance of reflection values in the reference region, i.e., the standard reflection variance νn, is larger than the reflection variance νw(x,y) in a 7 × 7 pixels neighborhood of a location (x,y), the value at this location is left unchanged in the reflection and the fluorescence image. By contrast, if νw(x,y) is larger than νn, the value at (x,y) is replaced by the mean of the surrounding pixels in the reflection and the fluorescence image. Since different regions are smoothed to different extents no universally valid value for the loss in spatial resolution can be given. The filtering eq 18 is motivated by the Local Minimum Mean Square Error (LMMSE) filter (21, 22). However, the underlying assumptions are completely different. Calibration. After the image processing procedure, the corrected fluorescence image corresponds to a map of the relative tracer concentrations. If absolute concentrations are needed, there are several ways to relate relative to absolute values: (i) Calibration by Extraction: Small samples are scraped off from exactly positioned areas of the soil surface, and their dye concentration is determined by extraction. Then, the dye concentrations are plotted against the fluorescence intensities read from the image for the sampled spot. (ii) Calibration with Standard Samples: Soil calibration samples of known dye concentration are prepared and placed onto the soil profile. Their fluorescence is directly measured in the field with the described imaging technique. The second calibration method should be preferred to the calibration by extraction because large uncertainties are associated with the extraction method. Mass recoveries of the dyes used in our study depend on soil composition, sample treatment, water content, and dye concentration.
Field Application The objective of the field experiment was to demonstrate that the fluorescence imaging technique is suitable for the simultaneous measurements of several fluorescent dyes in a soil profile under field conditions. The experiment was conducted in a forest stand in Unterehrendingen, Switzer-
of measurements. The influence of excavation, profile preparation, and redistribution of the tracer due to evaporation at the profile face was thoroughly tested and found to be negligible using Brilliant Blue FCF as dye tracer (4). A comparison of X-ray tomography and dye tracer images showed an almost identical spatial pattern of subtle structures (very fine fissures and pores) and major flow paths (25). The corrected fluorescence images and the vertical distribution of the relative concentrations of the three chosen tracers BF, SB and OX, are shown in Figure 6. We were able to detect concentrations as low as 0.05 mmol kg-1 for BF and 0.02 mmol kg-1 for SB (estimated from calibration curves measured with soil samples of known dye concentration under identical experimental conditions). Below these concentrations, the signal-to-noise ratio became to small to yield reliable data. The dye patterns of SB and BF are quite similar. Sorption studies showed higher linear sorption coefficients for SB than for BF (24). Therefore, BF should be less retarded in the soil and reach a deeper depth. The reason for the similar pattern and depth functions might be due to the prevalence of transport through preferential pathways, where the rather strongly sorbing SB travels as fast and far as the more mobile BF without reaching a sorption equilibrium. Oxazine 170 sorbs stronger to organic matter and mineral soil particles than BF and SB (data not shown). Therefore, almost all the fluorescence was restricted to the uppermost 5 cm. However, the small amounts of OX that reached deeper soil depths marked the same areas of the soil profile as BF and SB. Soil column studies showed breakthrough curves for OX that are typical for strongly sorbing compounds (data not shown). Therefore, we consider OX to be a probe for hydrophobic organic chemicals and a good tracer for rather extreme preferential flow events. In conclusion, the fluorescence imaging technique proposed is suitable to determine two-dimensional concentration distributions of several fluorescent dyes in soil profiles. By selecting appropriate optical filters, a powerful xenon lamp, and a sensitive CCD camera, we achieved a high signalto-noise ratio. Correction procedures cope with the variable lighting and background. Hence, this tool allows us to quantify the small-scale heterogeneity of flow patterns under realistic field conditions and for compounds of different reactivity. FIGURE 6. Left: Corrected fluorescence images of the fluorescent dyes Brilliant sulfaflavine, Sulforhodamine B, and Oxazine 170 measured from a soil profile of 1 × 1 m after a multitracing infiltration experiment. Right: Relative dye concentration as function of profile depth. land, on June 24/25, 1998. The soil is a Typic Haplumbrept (23). Using a field sprinkler (6), we irrigated a plot of 0.5 by 1.5 m during 6 h with 40 L of a solution containing the fluorescent dyes BF (2.39 mmol L-1), SB (1.72 mmol L-1), and OX (0.035 mmol L-1). One day after irrigation, we opened a 1.3 m deep, 1.5 m wide, and 3 m long trench and prepared a vertical soil profile that was centered in the irrigated plot. The CCD camera and the liquid lightguide of the fluorescence imaging device (Figure 1) were placed into the far end of the pit. The light source and the computer for data acquisition were placed in a van close to the trench. The trench was covered with a black blanket to prevent any stray light from entering. The black blanket is specially manufactured for high opacity (type “foroscur”, col. 6899 black, Ph. Schuler S. A., Lausanne, Switzerland). To further minimize stray light, we conducted all measurements at night. That had the additional advantage of rather low temperatures and high air humidity in the covered soil pit, so that the soil profile did not dry out noticeably during the approximately 4-5 h
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Received for review May 15, 2000. Revised manuscript received October 6, 2000. Accepted October 23, 2000. ES000096X
