# Biofilm growth dynamics in a micro-irrigation with reclaimed wastewater in the field scale

Vincent Moulia, Marc Heran, Geoffroy Lesage, Jérôme Hamelin, Jérôme Pinta, Aurélie Gazon, Moeana Penlae, Valérie Bru-Adan, Nathalie Wéry, Nassim Ait-Mouheb

► To cite this version:

Vincent Moulia, Marc Heran, Geoffroy Lesage, Jérôme Hamelin, Jérôme Pinta, et al. Biofilm growth dynamics in a micro-irrigation with reclaimed wastewater in the field scale. Journal of Environmental Management, 2024, 370, pp.122976. 10.1016/j.jenvman.2024.122976. hal-04748831

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Research article

# Biofilm growth dynamics in a micro-irrigation with reclaimed wastewater in the field scale

Vincent Moulia<sup>a,b,c</sup>, Marc Heran<sup>b</sup>, Geoffroy Lesage<sup>b</sup>, Jérôme Hamelin<sup>c</sup>, Jérôme Pinta<sup>a</sup>, Aurélie Gazon<sup>a</sup>, Moeana Penlae<sup>b</sup>, Valérie Bru-Adan<sup>c</sup>, Nathalie Wéry<sup>c</sup>, Nassim Ait-Mouheb<sup>a,*</sup>

<figure><img src="image_3.png" /></figure>

## ARTICLE INFO

**Keywords:**

Drip irrigation

Optical coherence tomography

Biofouling

Irrigation hydrodynamics

Water reuse

3DEEM fluorescence

## ABSTRACT

The dripper clogging due to the development of biofilm can reduce the benefits of micro-irrigation technology implementation using reclaimed wastewater. The narrow cross-section and labyrinth geometry of the dripper channel enhance the fouling mechanisms. The aim of this study was to evaluate the water distribution and biofouling of drip irrigation systems at the field scale during irrigation with treated wastewater. Six 100 m lines of commercial pipes with two pressure-compensating dripper types (flow rate, Q, of 0.65 L h⁻¹ and 1.5 L h⁻¹, respectively) were monitored for four months. Different zones along the pipes were selected to evaluate the influence of hydrodynamical conditions (Reynolds number = 5400 to 0) on biofouling. Destructive methods involving the biofilm extraction by mechanical means, showed little biofilm development without significant differences in dry and organic matter content in function of the sampling location along the pipe or dripper flow rate (Q₀.₆₅ and Q₁.₅). These results were confirmed by non-destructive methods, such as optical coherence tomography, that nevertheless showed that biofouling concerned 15–20% of the total dripper labyrinth volume. Total organic carbon monitoring and its composition (by three-dimensional excitation and emission matrix fluorescence microscopy) showed that the biofilm did not significantly influence the organic matter nature. Our results indicated that the biological activity and biofilm development in irrigation systems were more affected by the environmental conditions, particularly water temperature, rather than flow conditions. This confirmed that treated wastewater with low organic content can be used in micro-irrigation systems without significant loss of efficiency, even in conditions requiring intensive irrigation, such as the Mediterranean climate.

## 1. Introduction

The development of water-saving irrigation techniques is more crucial than ever due to the rapid global climate change and the need of water resource conservation. Using treated wastewater emerges as a sustainable option to meet the expanding irrigation demands (Ait-Mouheb et al., 2018). Moreover, micro-irrigation techniques (e.g. drip irrigation) might allow saving up to 90% of water (versus ~50% with surface irrigation techniques) (Darouich et al., 2014). In micro-irrigation systems, drippers are composed of a flow path with a labyrinth conformation and an outlet chamber. The dripper geometry will determine the water delivery flow rate (Lequette et al., 2020). However, drippers are sensitive to clogging due to the labyrinth conformation, slow flow rate and small flow section (close to 1 mm³).

Clogging problems can affect the water delivery uniformity along the pipe and increase maintenance costs (Dosoretz et al., 2010). Clogging is worse when treated wastewater is used because of the increased concentration in microorganisms (Moulia et al., 2023) that tend to attach to surfaces (Flemming and Wingender, 2010). In addition, treated wastewater might promote the development of biofilms due to the higher concentration of nutrients (e.g. organic matter, nitrogen, phosphorus) present in the effluent (Moulia et al., 2023; Qian et al., 2017). The combination of nutrients, organic matter and microorganisms and of favorable hydrodynamic conditions (laminar flow) increases the risk of biofilm development and of dripper clogging. Moreover, temperatures up to 37 °C increase the cell hydrophobicity and favor cell attachment to the surface (Di Bonaventura et al., 2008). This could suggest favorable conditions in the pipe for biofilm development when using irrigation

<footnote><sup>a</sup> INRAE, UMR G-EAU, University of Montpellier, Montpellier, France</footnote>

<footnote><sup>b</sup> IEM, University of Montpellier, Montpellier, France</footnote>

<footnote><sup>c</sup> INRAE, Univ Montpellier, LBE, 102 Avenue des Étangs, 11100, Narbonne, France</footnote>

<footnote>* Corresponding author.</footnote>

<footnote>E-mail address: nassim.ait-mouheb@inrae.fr (N. Ait-Mouheb).</footnote>
<figure><img src="image_4.png" /><figcaption>**Fig. 1.** Schematic description of the irrigation lines and sampling locations. Red circles: biofilm and water sampling locations (upstream, middle and downstream); blue rectangles: volume meter; green rectangles: water temperature probes.</figcaption></figure>

systems with treated wastewater in the field where temperature cannot be controlled. However, most studies have been carried out in the laboratory in controlled conditions where the temperatures observed in field conditions are difficult to mimic.

Several methods are currently available to assess biological clogging in irrigation systems (Petit et al., 2022). First, mass measurement allows the quantitative and qualitative (physical, chemical and biological) characterization of the matter contained in pipes and drippers. However, this technique is inevitably destructive. Previous studies using mass measurements showed the development of biofilms in pipes, although not at very high concentrations (up to 1 g of dried mass) (Gamri et al., 2015). Second, dripper flow rate measurement is an efficient and non-destructive method to monitor biofouling in the dripper part of the irrigation system. Some authors characterized biological clogging in drippers using optical coherence tomography (OCT), a technique that can be non-destructive (Lequette et al., 2020; Wagner et al., 2010; Ma et al., 2024; Yao et al., 2024) if an optical access is available.

In addition, several techniques are used to quantify organic matter concentration in the effluent, such as the chemical oxygen demand (COD) and total organic carbon (TOC) quantification. Fluorescence spectroscopy can be used in combination with these techniques to quantify organic matter present at low concentrations and also to monitor its composition changes due to microbial activity (Li et al., 2020). This technique was previously used to predict the organic matter behavior in a membrane bioreactor system (Jacquin et al., 2018a, 2018b). Moreover, Xue et al. (2021) investigated the effect of pipe length on biological clogging in drip irrigation networks. These previous studies brought new insights, but not on drip irrigation using wastewater in field conditions. They focused on the organic matter concentration in water supply pipes under hundred kilometers and not in surface irrigation pipes. The removal of organic matter in the pipe could reach a value between 0.17 and 0.42 mg.L⁻¹. Nevertheless, in the case of irrigation using treated wastewater this could be an efficient method to

determine microbial activity/development in irrigation pipe systems and to potentially detect biofouling. Biofilm development in pipes is driven by different factors, including hydrodynamic conditions, temperature and concentration of microorganisms and nutrients (Katz et al., 2014; Li et al., 2019; Oliveira et al., 2017). In field conditions, drip irrigation lines can be hundreds of meters long, thus creating different hydrodynamic conditions. Moreover, they are exposed to environmental conditions, such as changes in temperature and water quality. Few studies assessed the effect of reclaimed wastewater on biofouling development in irrigation pipes in field experiments. Also, to our knowledge, little is known about the pipe biofilm influence on the water microbial quality deterioration. Study on pipe irrigation systems using surface water already showed higher concentration of some bacterial groups (such as *Escherichia coli*) in water sampled at the outlet than at the inlet (Pachepsky et al., 2012).

Therefore, the main objective of this study was to better understand biofouling development along the whole drip irrigation system in field conditions during summer irrigation in the Mediterranean climate context. Secondary objectives were: i) to determine whether biofilm formation is influenced by the location along the pipe; and ii) to correlate the dripper flow rate with biofilm formation. We hypothesized that biofilm would be thicker downstream in the pipe and that lower flow rate would facilitate biofilm formation. To this aim, we used conservative methods, such as OCT, to evaluate biofilm volume in drippers, and a destructive method (dry mass measurement) to monitor biofouling. We investigated biofilm formation by measuring total bacteria, organic matter using three-dimensional excitation and emission matrix (3DEEM) fluorescence (for indirect measurement of biofilm formation and activity), and TOC measurement and nutrient concentration quantification by ion chromatography to follow microbial biofilm activities.

<caption>**Table 1**</caption>

Hydrodynamic and operational conditions in the irrigation pipes at each sampling location (upstream, middle and downstream) and for both irrigation pipe types (Q₀.₆₅ and Q₁.₅).

<table><thead><tr><th>Sampling location</th><th>Distance from the beginning of the pipe (m)</th><th>Flow rate type</th><th>Water velocity (m.s<sup>-1</sup>)</th><th>Reynolds number (Re)</th><th>Hydraulic residence time (s)</th><th>Distance between drippers (m)</th></tr></thead><tbody><tr><td>Upstream</td><td>1</td><td>Q<sub>1.5</sub></td><td>0.21</td><td>4174</td><td>646</td><td>1</td></tr><tr><td>Upstream</td><td>1</td><td>Q<sub>0.65</sub></td><td>0.30</td><td>5366</td><td>448</td><td>0.3</td></tr><tr><td>Middle</td><td>50</td><td>Q<sub>1.5</sub></td><td>0.10</td><td>2059</td><td>646</td><td>1</td></tr><tr><td>Middle</td><td>50</td><td>Q<sub>0.65</sub></td><td>0.15</td><td>2972</td><td>448</td><td>0.3</td></tr><tr><td>Downstream</td><td>99</td><td>Q<sub>1.5</sub></td><td>&lt;0.01</td><td>41</td><td>646</td><td>1</td></tr><tr><td>Downstream</td><td>99</td><td>Q<sub>0.65</sub></td><td>&lt;0.01</td><td>59</td><td>448</td><td>0.3</td></tr></tbody></table>
## 2. Materials and methods

### 2.1. Experimental procedure and irrigation procedure

Experiments were done at the Murviel-Lès-Montpellier wastewater reuse facility (43.605034° N, 3.757292° E) in the south of France, in the Mediterranean basin. This wastewater treatment plant has a nominal capacity of 3000 inhabitant equivalents. It includes the usual pretreatment steps (screening and grit removal), followed by an organic constructed wetland treatment step (forced aeration planted filters), supplemented by phosphorus removal using ferric chloride. One 400 µm mesh disk filter and one 100 µm mesh disk filter are installed at the exit from the inlet chamber and before the irrigation system to avoid clogging due to suspended particles. Six 100 m commercial drip lines (model D5000, Rivulis Irrigation SAS, Lespinasse, France) (Fig. 1) were used with integrated pressure-compensating drippers with flow rates of 0.65 L h⁻¹ (Q₀.65) and 1.5 L h⁻¹ (Q₁.5) (three lines for each dripper type). Pipes were made of polyethylene compounds and the internal diameter (d) equals to 13.8 mm for both. Drippers with different flow rates were used to vary the flow regime (from turbulent to laminar) in the pipe. The pressure setpoint was between 80 and 150 kPa to respect the manufacturer's recommendations. Drippers included a non-return valve to avoid external contamination and root intrusion. The between-dripper distances were 0.3 m (Q₀.65) and 1 m (Q₁.5) (Table 1). In the field, low-flow drippers Q₀.65 are generally used for vegetable crops with short 'dripper spacing', whereas Q₁.5 are generally used for vines or trees with 1m spacing. However, as these commercial pipes do not allow visually monitoring biofouling, non-pressure compensating (NPC) drippers (OADR), which provided a flow rate of 1 L h⁻¹, were also used (model D2000, Rivulis Irrigation SAS, Lespinasse). These drippers were set in transparent pipes that allowed visual access and that were used for the first time in a field experiment (internal diameter 15 mm, TubClair, Vitry-le-François, France) for microscopic observations according to (Lequette et al., 2020). The optical drippers (OADR) were positioned on each pipe in upstream, middle and downstream section (three in total for each dripper line).

The system was operated for a total duration of 129 days (from June 28 to November 2, 2022). Irrigation was activated six times per day (30 min on and 90 min off) from 10 a.m. to 8 p.m. to avoid long periods without irrigation during the high summer temperatures. The total volumes of water delivered during the study period were 46.8 m³ (Q₁.5) and 67.4 m³ (Q₀.65) for all irrigation experiments. These are the volumes needed for olive and apricot trees during one irrigation season and for vines during two irrigation seasons.

### 2.2. Hydrodynamic and operational conditions in pipe and drippers

The hydrodynamic and operational conditions were measured in both pipe types (Q₀.65 and Q₁.5) and are summarized in Table 1.

Theoretically, the water velocity was calculated using the formula:

$$V_i = \frac{Q}{\pi \cdot \frac{d^2}{4}} \qquad (1)$$

where Q is the flow rate (m³.s⁻¹) and d is the pipe diameter (m).

Theoretical water velocities ranged from 0 to 0.3 for the Q₀.65 and from 0 to 0.2 m s⁻¹ for the Q₁.5 pipe type. Water velocities decreased along the pipe length due to the water released from the drippers, leading to Reynolds numbers (Re) from 4174 to 0 at the end of dripper Q₁.5 pipe type and from 5366 to 0 at the end of dripper Q₀.65 pipe type. At the inlet of the dripper, the Re numbers were 520 for the Q₁.5 and 225 for the Q₀.65 pipe type. For optical access drippers (OADR), the Reynolds number at the dripper inlet was 347 for all drippers. Reynolds numbers were calculated using the formula:

<table><caption>**Table 2**

Chemical and microbiological characteristics of the treated wastewater used for irrigation.</caption><thead><tr><th>Parameters</th><th>Sampling events</th><th>Units</th><th>Mean</th><th>Standard deviation</th></tr></thead><tbody><tr><td>COD</td><td>n = 9</td><td>mg(O₂).L⁻¹</td><td>20.4</td><td>5.7</td></tr><tr><td>TSS</td><td>n = 3</td><td>mg.L⁻¹</td><td>8.3</td><td>11.3</td></tr><tr><td>N-NH₄⁺</td><td>n = 5</td><td>mg.L⁻¹</td><td>1.2</td><td>3.3</td></tr><tr><td>N-NO₃⁻</td><td>n = 5</td><td>mg.L⁻¹</td><td>15</td><td>8.5</td></tr><tr><td>N-NO₂</td><td>n = 5</td><td>mg.L⁻¹</td><td>0.9</td><td>2.5</td></tr><tr><td>P-PO₄³⁻</td><td>n = 5</td><td>mg.L⁻¹</td><td>1.4</td><td>2.2</td></tr><tr><td>Cl⁻</td><td>n = 5</td><td>mg.L⁻¹</td><td>188</td><td>40</td></tr><tr><td>Na⁺</td><td>n = 5</td><td>mg.L⁻¹</td><td>96</td><td>23</td></tr><tr><td>K⁺</td><td>n = 5</td><td>mg.L⁻¹</td><td>21</td><td>5</td></tr><tr><td>Mg²⁺</td><td>n = 5</td><td>mg.L⁻¹</td><td>20</td><td>3</td></tr><tr><td>Ca²⁺</td><td>n = 5</td><td>mg.L⁻¹</td><td>187</td><td>130</td></tr><tr><td>Total coliforms</td><td>n = 6</td><td>MPN.100 mL⁻¹</td><td>4.6</td><td>0.4</td></tr><tr><td>E. coli</td><td>n = 6</td><td>MPN.100 mL⁻¹</td><td>3.7</td><td>0.6</td></tr><tr><td>Enterococci</td><td>n = 6</td><td>MPN.100 mL⁻¹</td><td>2.8</td><td>1.3</td></tr></tbody></table>

COD, chemical oxygen demand; TSS, total suspended solids.

$$Re = \frac{\rho V D}{\mu} \qquad (2)$$

where ρ is the fluid density (kg.m⁻³), V is the fluid velocity (m.s⁻¹), D is the pipe diameter (m), and μ is the fluid dynamic viscosity (kg.m.s⁻¹).

The hydraulic retention time (HRT) (i.e. the water storage time in the pipe and the contact between nutrients and microorganisms during the irrigation procedure) was calculated with the formula:

$$HRT = \frac{Q}{V} \qquad (3)$$

where Q is the flow rate in the pipe (L.h⁻¹) and V is the total pipe volume (L).

The water temperature in the pipe was measured using a PT100 sensor (SICK AG, Waldkirch, Germany) at the beginning (0 m) and the end (100 m) of the irrigation system. The mean temperatures in the water at the beginning of the pipe were 32 °C, 30.3 °C, 24.3 °C and 10.8 °C for month 1 (July), 2 (August), 3 (September) and 4 (October), respectively (Fig. S1). The mean temperature in the water at the end of the pipe were 37 °C, 34.8 °C, 26 °C and 9.5 °C for month 1, 2, 3 and 4, respectively. However, the peak temperature in the pipe reached 49 °C, 50 °C, 42 °C and 33 °C at month 1, 2, 3 and 4, respectively. In this range of water temperatures measured in the pipe, it should be noted that the variation of water density and kinetic viscosity is negligible.

### 2.3. Flow rate changes

Dripper flow was measured every 2 weeks to monitor dripper clogging during the irrigation period. The flow rate was measured at the beginning (0 m), in the middle (50 m) and at the end of the pipe (100 m). Two drippers were selected for flow rate monitoring at each location and for each flow rate pipe type (Karmeli, 1977). Flow rate was also measured at all OADR (n = 18) every 2 weeks.

### 2.4. Treated wastewater quality

#### 2.4.1. Nutrient and microbial composition analyses

The treated wastewater used for irrigation was sampled at the beginning of each pipe at different time points during the irrigation period to monitor its physicochemical and microbiological qualities and the parameters that could influence clogging formation in the micro-irrigation system. The COD was monitored with a spectrophotometer (DR1900, Hach Company, Loveland, CO, USA). Anions [chloride (Cl⁻),
<figure><img src="image_5.png" /><figcaption>Fig. 2. Dry matter concentration (in µg.cm⁻²) (a), organic matter concentration (in µg.cm⁻²) (b), and bacterial concentration (in log 16S rRNA gene copies.cm⁻²) (c) in commercial pipes at the different sampling locations and with different dripper flow rates. Green = upstream, orange = middle, and red = downstream.</figcaption></figure>

nitrate (NO₃⁻), nitrite (NO₂⁻), phosphate (PO₄³⁻)] and cations [ammonia (NH₄⁺), sodium (Na⁺), magnesium (Mg²⁺), calcium (Ca²⁺)] were analyzed by ion chromatography (Dionex Thermo Fisher ICS 1000, Waltham, MA USA). Total coliforms, E. coli and Enterococci were measured with Colilert18 and Enterolert-E (IDEXX Laboratories, Westbrook, ME) according to the manufacturers' protocols. These parameters are summarized in Table 2.

### 2.4.2. Tracking organic matter fate during irrigation

Water collected at different locations along the pipes was analyzed by 3DEEM fluorescence microscopy to detect the dissolved and colloidal organic matter in the effluents and the potential microbial activity in the matrix (Jacquin et al., 2017). This analysis was performed every two weeks and to our knowledge it was the first time that this technique was used to characterize organic matter in the effluent of a micro-irrigation system. First, samples were filtered with 0.45 µm filters (AIT, France). The resulting matrix was divided in three different areas according to Jacquin et al. (2017): Zone I (protein regions), Zone II (soluble microbial product regions), Zone III (humic acid and fulvic acid regions). The volumes of each zone were integrated to perform a semi-quantitative analysis of each fluorophore type. Inlet and outlet (i.e. downstream, middle or upstream zone) water changes were compared using the following equation:

$$ \text{Change} = \frac{\text{Concentration (or peak area) in outlet water}}{\text{Concentration (or peak area) in inlet water}} \quad (4) $$

If the change value was >1, the outlet water was more concentrated in fluorophores than the inlet water. If the change value was <1, the outlet water was less concentrated in fluorophores than the inlet water. Four indicators were followed: Zones I to III and the biological index (BIX) that assesses the water biodegradability (Xiao et al., 2016).

## 2.5. Biofilm analysis

### 2.5.1. Pipe clogging and biofilm analysis

Biofilm samples were collected at each sampling location (upstream, middle and downstream zones) and for both flow rate irrigation pipe types (Q₀.₆₅ and Q₁.₅) at day 87 and at the study end (day 129). Biofilms were extracted along a 2 m length of pipe using a clean device (piston-like). Total dry matter, organic matter and inorganic matter were measured using standard methods. Drippers were extracted along the same 2 m pipe section and stored in sterile tubes at -20 °C for DNA extraction. Moreover, three 10 cm pipe sections were randomly selected to make composite samples at each location zones. Genomic DNA from biofilm (pipes and drippers) was extracted using the PowerWater DNA Isolation Kit (Qiagen, Hilden, Germany) following the manufacturer's instructions.

Bacteria in the DNA samples were quantified by qPCR analysis of the 16S ribosomal RNA (rRNA) gene (V3 region). Two sample dilutions were used to check the absence of PCR reaction inhibitors. Reaction mixtures (12 µL) contained 6 µL of Super Mix qPCR (Invitrogen), 1 µL of 200 nM forward primer W31 (5'-ACGGTCCAGACTCCTACGGG -3'), 1 µL of 200 nM reverse primer W49 (5'-TTACCGCGGCTGCTGGCAC-3'), and 2 µL of water. The cycling parameters were: 2 min at 95 °C for denaturation, and then 40 cycles at 95 °C for 10 s for denaturation and 61 °C for 20 s for annealing and amplification (Yu et al., 2005).

### 2.5.2. Biovolume quantification by optical coherence tomography (OCT)

OCT was used to monitor biofilm formation in OADR in a non-destructive manner every 2 weeks. Each dripper was temporarily removed from the irrigation system by isolating the valves that allowed keeping the dripper labyrinth filled with water. Three-dimensional OCT images were acquired at the laboratory using a Ganymede II OCT system (LSM03 lens, lateral resolution: 8 µm; Thorlabs GmbH, Lübeck, Germany). After each measurement, each dripper was put back in the same
place. The axial voxel size in water (n = 1.333) of the Ganymede II OCT system is 2.1 µm. The dripper labyrinth was divided into three parts for image acquisition (inlet, return, and outlet part) (Lequette et al., 2020) (Fig. S2).

Then, OCT images were processed with Fiji (ImageJ version 1.50b, Schindelin et al., 2012) and converted into 8-bit grayscales. The dataset was divided into several images from top to bottom and throughout the labyrinth depending on the studied area. The other part of the image was assigned to background. Then, images were processed using an optical-access code in Python (Python 3.9). The pixels associated with the transparent tube were removed from the analysis and a threshold was set to binarize the dataset. Only the regions above the threshold were quantified. The quantifications associated with the biofilm were summed to evaluate the biofilm thickness over the study area. Then, the dripper labyrinth total volume was measured. To quantify the percentage of volume occupied by the biofilm, the following formula was used:

$$ \text{Biofouling percentage (\%)} = \frac{V_{\text{biofilm}}}{V_{\text{labyrinth}}} \times 100 \quad (5) $$

where V biofilm is the sum of the pixels associated with the biofilm, V labyrinth is the total volume of the labyrinth.

## 2.6. Statistical analyses

All graphical representations and statistical analyses were performed with R (R Core Team, 2022; version 4.2.2), using the package ggplot2 (Wickham, 2016). Data were compared with the Kruskal-Wallis test followed by the Dunn post-hoc test to compare differences between sampling locations and between flow rate irrigation pipe types. The Student's t-test was used to compare changes in TOC concentration and organic matter characterization at each sampling location. The Kendall rank correlation test was used to test the links between dripper flow rate and biovolume, between dry matter and bacterial concentration in the pipe, and between bacterial concentration in the drippers and bacterial concentration changes in the irrigation water.

# 3. Results and discussion

## 3.1. Biofouling in the irrigation pipes

### 3.1.1. Biofilm amount along the pipes

Dry matter quantity was monitored in the irrigation pipes to quantify biofouling in function of the sampling location and hydrodynamical conditions (turbulent flow in the upstream zones: Re from 5366 to 4174, and laminar flow in the downstream zones: Re < 59). The high variability among replicates (n = 3/sampling zone) did not allow establishing any significant difference (Kruskal-Wallis, p > 0.05) (Fig. 2a). Nevertheless, for both pipe types (Q1.5 and Q0.65), dry matter content tended to be 94.1 and 82% (for Q1.5 pipes) and 86.7 and 59.5% higher (for Q0.65 pipes) in the downstream zone where water flow speed was minimal (Re = 41 and Re = 59) than in the upstream (Re = 4174 and Re = 5366) and middle (Re = 2059 and Re = 2972) sampling locations, respectively, at both sampling times (day 87 and day 129). Similarly, dry matter quantities tended to be higher in the middle than upstream sampling locations for both flow rate pipe types and at both sampling times.

In the Q1.5 pipe type, organic matter percentage was significantly higher at the downstream (Re = 41) than upstream (Re = 4171) sampling zones at day 87 (Kruskal-Wallis, p < 0.05) (Fig. 2b). The organic matter percentage in dry matter was higher in the upstream and middle than downstream sampling locations at both sampling times: 44–88% (day 87-day 129) and 70–74% vs 29–33% in Q1.5 pipes, respectively, and 73–64% and 62–54% vs 38–38% in Q0.65 pipes, respectively. These results showed higher deposition of inorganic material in downstream zones for both flow rate irrigation pipe types. This indicates that laminar

flow conditions enhanced the accumulation of inorganic materials.

Biofouling in the pipes was expected to be influenced by the location and hydrodynamic conditions (from turbulent to laminar conditions). The results showed 5-10-fold less dry matter compared with previous laboratory studies that reported >1 mg cm⁻² of deposit (Japhet et al., 2022; Tarchitzky et al., 2013). The total irrigation period in these previous studies ranged from 70 days to 16 years (from 2 to 16 years). The percentages of organic matter in the pipes in laboratory conditions were similar to what found in the present study. The average temperature in the pipes over the irrigation period were between 20 °C and 40 °C in our study, which could have favored biofilm formation. However, temperature was above 45 °C several times during the day and for several consecutive days during no operation time. This high temperature over long periods could explain the slower biofilm formation compared with what observed in temperate laboratory conditions.

Furthermore, our results suggested higher potential for dry matter accumulation in the downstream zone that together with its more favorable flow conditions (laminar conditions with Re between 41 and 59) might promote biofilm formation (Cowle et al., 2020; Liu et al., 2016).

### 3.1.2. Bacterial concentration in the biofilm from the pipe

Bacterial concentrations were measured in irrigation pipes at all sampling locations (upstream, middle and downstream) and for both flow rate irrigation pipe types (Q1.5 and Q0.65) (Fig. 2c). In the Q0.65 pipe type, the mean bacterial concentrations ranged from 7.7 ± 0.4 to 9.4 ± 0.0 16S rRNA gene copies (log.cm⁻²) at both sampling times. At day 87, the concentration was lower in the upstream than in the middle and downstream samples. Conversely, at the study end, bacterial concentration was lower in downstream than in the upstream and middle samples.

In the Q1.5 pipe type, the mean bacterial concentration ranged from 8.5 ± 0.1 to 9.5 ± 0.1 16S rRNA gene copies (log.cm⁻²). The concentration was higher in the downstream samples compared with the upstream and middle samples at day 87, but only compared with the upstream samples at the study end. Indeed, at day 129, bacterial concentrations in the middle and downstream samples were similar (9.3 ± 0.1 and 9.4 ± 0.2 16S rRNA gene copies; log.cm⁻²). Moreover, in the Q1.5 pipe type, bacterial concentration was significantly different in the upstream samples collected at the two sampling times (Kruskal-Wallis test, p < 0.05), but not in the middle and downstream samples (Kruskal-Wallis test, p > 0.05). Conversely, in the Q0.65 pipe type, bacterial concentrations were significantly different in the middle and downstream samples between sampling times (Kruskal-Wallis test, p < 0.05).

Bacterial density indicates the concentration of bacteria present in the biofilm formed inside irrigation pipes. This density is measured by counting the number of 16S rRNA gene copies per unit mass of biofilm dry matter, providing an estimate of the number of bacteria present in the biofilm. At both sampling times, bacterial density in the pipe biofilm was significantly higher in the upstream and middle than in the downstream samples in both pipe types (Fig. S3). However, at the study end, bacterial density in the Q1.5 pipe type was highest in middle samples. At day 87, the mean bacterial densities were 7.8 ± 0.4 and 8.2 ± 0.4 log 16S rRNA gene copy.µg⁻¹ for Q0.65 and Q1.5 pipes. Bacterial density was highly correlated with the Reynolds number (ρ between 0.65 and 0.8, Kendall correlation test, p < 0.05).

Overall, bacterial concentrations in the biofilm were higher in the downstream than in the middle and upstream zones of the pipes. This suggested that bacterial development was promoted by lower shear stress forces (laminar conditions in the downstream zone and turbulent conditions in the upstream and middle zones). Moreover, bacterial concentrations in the middle and downstream zones were higher in the Q1.5 than in the Q0.65 pipe type. This confirmed that bacterial concentrations were higher when shear stress forces were lower (see Table 1). Several studies that modeled the influence of hydrodynamic conditions on bacterial concentration showed similar results (Cowle et al., 2020;
<figure><img src="image_6.png" /><figcaption>**Fig. 4.** Mean biovolume percentage in the OADr labyrinth from the two pipe types: Q₀.₆₅ (a) and Q₁.₅ (b). Smoothing line and confidence interval were represented (95% of the associated variance). The orange line shows the 25% of labyrinth volume occupied by the biovolume. Biovolumes in the drippers were not measured at the beginning of the experiment and a 0 value was attributed to all drippers.</figcaption></figure>

correct distribution of water (data not shown). Specifically, in two drippers in the downstream zone of the Q₀.₆₅ pipe and Q₁.₅ pipe, the flow rate decreased by 28% and 24% and by 39% and 24%, respectively (Erreur! Source du renvoi introuvable.a-b). Only drippers in the Q₀.₆₅ pipe type showed a significant decrease (>25%) of the flow rate in the upstream zone after 115 days of experiment (Kruskal-Wallis test, *p* < 0.05) (Fig. 3c-d). Overall (both pipe types), the mean flow rate values were lower in the downstream zone than in the upstream and middle zones, but the difference was not significant due to the high variabilities among replicates (*p* > 0.05). Commercial drippers had a non-return valve to remove water from the labyrinth to avoid root intrusion (antiphon drippers). This dripper conformation can limit biofilm development probably due to air flushing at the start of the irrigation. Previous studies found decreased flow rate using different commercial microirrigation system set-ups (pipe length, water quality, dripper flow rate). Katz et al. (2014) reported a flow rate reduction by > 30% (pipe length of 30 m and 76 days of experiment) and Green et al. (2018) between 11 and 15%. Our results are more similar to those found by Szekut et al. (2015) and Lequette et al. (2019) (<7% of flow rate reduction), but with a much shorter pipe (~10 m) and not in field conditions. Similarly, in OADr, no significant flow rate decrease was observed (Lequette et al., 2020).

### 3.2.2. Biovolume in drippers

The percentage of dripper volume covered by biofouling was measured in three different zones of the OADr labyrinth (Fig. S2) using OCT measurements at different time points. Biofilm development was homogeneous inside the drippers as indicated by the absence of significant variations in the different zones (Kruskal-Wallis test, *p* > 0.05). Therefore, the results from the three zones were merged and the mean biovolume values were reported for the analyses (Fig. 4). Biofilm volume homogeneity within drippers was unexpected based on previous studies showing differences in the volume covered by the biofilm in the different zones (Lequette et al., 2020).

At day 36, the mean biovolume percentage was higher in OADr from the downstream zone in both pipe types, but in this zone it was higher in the Q₀.₆₅ than in the Q₁.₅ pipe type (13.2 ± 2.5% vs 7.5 ± 1.5%). At day

50, the mean biovolume percentages were 1.3-, 1.7- and 1.6-fold higher in the OADr from the upstream, middle, and downstream zones of the Q₀.₆₅ than Q₁.₅ pipe type. Specifically, the mean values for drippers placed in upstream, middle, and downstream zones were between 14 and 16.6%, 10.8–18.1% and 9.4–14% for the Q₀.₆₅ pipe and 12–17.1%, 10.5–14.7% and 8.1–15.8% for the Q₁.₅ pipes, respectively. These results suggested a higher biovolume percentage in upstream zone drippers. The increase in biovolume percentage from the beginning of the experiment to day 50 indicated biofilm formation in the drippers. This was followed by a stable phase that could correspond to similar rates of biofilm development and detachment. Overall, all biovolume percentages did not exceed 20% of the total labyrinth volume. This indicated the absence of critical biofouling in drippers due to biofilm repartition (and no significant decrease in flow rate). Flow rate changes were negatively and weakly correlated with biovolume percentage in OADr ($\tau$ = -0.19, Kendall rank correlation test). This suggests no relationship between flow rate variation and biovolume percentage in OADr where the increase in biofouling did not decrease the dripper flow rate. The concentration of total suspended solids was not very high (mean value: 8.3 ± 11.3 mg.L⁻¹) (Table 2) in this study. However, the low decrease in the OADr flow rate could be explained by momentary clogging by physical particles or organic material (Muniz et al., 2022; Oliveira et al., 2017). These temporarily phenomena can be caused by spontaneous detachment of particles from the pipes, or by particle accumulation on the filters. Biofouling increase in the drippers was not influenced by their location along the pipes (Fig. 4). The high temperature of pipe materials could explain the limited biofouling in the drippers.

In commercial drippers, the labyrinth was not optically visible for OCT visualization and a destructive method was needed for visualization. Moreover, in this study, the biomaterial in the pipes was not sufficient for OCT visualization at day 87 and 129. The dripper labyrinth was evaluated using a digital microscope (Leica DVM6) at day 87 and day 129 (images not shown). Only planktonic particles were found and they did not obstruct the labyrinth. The absence of biofouling in commercial drippers could be explained by the combination of different factors, such as their conformation that limits clogging and the high temperature that reduces microbial development.
<figure><img src="image_7.png" /><figcaption>**Fig. 5.** Bacterial concentration (16S rRNA gene copies, log, per dripper) in commercial (a) and optical-access (b) drippers at the different sampling areas and in drippers with different flow rate. Green = upstream, orange = middle, and red = downstream.</figcaption></figure>

### 3.2.3. Bacterial concentration in drippers

Bacterial colonization in drippers was monitored using the 16s rRNA copy number obtained for the whole dripper in each sampling zone (upstream, middle and downstream) along the pipes ($Q_{0.65}$ and $Q_{1.5}$) (Fig. 5). This is the first time this technique was used to study the bacterial biomass in drip irrigation pipes at the field scale.

Copies numbers were ~7.5 log in commercial drippers (Figs. 5a) and 10 log in OADr (Fig. 5b). Copy number variations were observed in the three zones (Kruskal-Wallis test, *p* < 0.05). Specifically, for drippers on the $Q_{1.5}$ pipe type, at day 87, copy number was significantly higher in the middle zone than in the upstream zone. For drippers along the $Q_{0.65}$ pipe, at day 129, copy number was higher in the upstream zone than in the middle ($7.2 \pm 0.1$ log) and downstream ($7.1 \pm 0.2$ log) zones (Kruskal-Wallis test, *p* < 0.05). Comparison of the values between time points showed that copy number in the middle zone of the $Q_{1.5}$ pipe was higher at day 87 than at day 129 ($7.7 \pm 0.1$ versus $7.3 \pm 0.1$ log 16S rRNA gene copy) (Kruskal-Wallis test, *p* < 0.05).

For OADr, no significant difference was found between irrigation pipe types (Fig. 5b). For both $Q_{1.5}$ and $Q_{0.65}$ pipe types, copy numbers were higher in the upstream and downstream zones than in the middle zone (Kruskal-Wallis test, *p* < 0.05). Overall, bacterial densities in OADr at day 129 ranged between $9.9 \pm 0.2$ and $10.8 \pm 0.1$ log 16S rRNA gene copies.mm$^{-3}$ (Fig. S5). Bacterial densities in OADr at day 129 were higher in the upstream and downstream zones than in middle zones for both irrigation pipe types.

Bacterial concentration in the drippers did not increase significantly during the irrigation period. A previous study on irrigation with treated wastewater (lagoon wastewater treatment systems) showed an increase in bacterial concentration with time, but no impact of the dripper flow rate on bacterial concentrations (Lequette et al., 2020). Here, similar results were obtained concerning the bacterial concentration in drippers. The lack of differences between pipe location zones and flow rate pipe types could be explained by the use of pressure-compensating drippers. This results in the draining of the water from the dripper after irrigation, thus decreasing the favorable conditions for biofilm development. In addition, the high summer temperature during the experiment and the low organic matter concentration in the irrigation water contributed to limiting biofilm formation. In this experiment, at day 87, bacterial counts in the drippers had already reached the plateau phase, as indicated by the absence of difference with the final values.

<figure><img src="image_8.png" /><figcaption>**Fig. 6.** Bacterial concentration (in log 16S rRNA gene copies per dripper) in treated wastewater used for irrigation according to the different sampling areas and dripper flow rates. Black = inlet water, green = upstream, orange = middle, and red = downstream.</figcaption></figure>
<figure><img src="image_9.png" /><figcaption>**Fig. 7.** TOC concentration (mg.L⁻¹) changes in outlet water samples (upstream, middle, and downstream zones) in function of the mean water temperature in the 5 days before sampling (a) and Reynolds number (b). Blue lines, trend lines over the existing plot.</figcaption></figure>

### 3.3. Changes in the concentration and composition of bacteria and organic matter in treated wastewater

#### 3.3.1. Bacterial concentration in the treated wastewater

Bacterial concentrations in the irrigation water sampled at different locations was compared to determine whether the biofilms in the pipe influenced the in-transit effluent in the pipe (Fig. 6). At day 1 of the study (first day of irrigation), bacterial concentration decreased significantly (Kruskal-Wallis test, *p* < 0.05) between the inlet (8.3 ± 0.0 log 16S rRNA gene copies.mL⁻¹) and the middle zone (7.3 ± 0.3 log 16S rRNA gene copies.mL⁻¹) in the Q₁.₅ flow rate pipe type and between the inlet water and the upstream (7.9 ± 0.2 log 16S rRNA gene copies. mL⁻¹) and middle (7.9 ± 0.1 log 16S rRNA gene copies.mL⁻¹) zones in the Q₀.₆₅ flow rate pipe type. At day 85, bacterial concentrations were significantly increased in the three pipe zones for the Q₁.₅ pipe type (from 6.8 ± 0.0 in the inlet to 7.9 ± 0.3, 8.2 ± 0.2, 8.3 ± 0.2 log 16S rRNA gene copies.mL⁻¹ in the upstream, middle and downstream zones, respectively) and in the middle and downstream zones in the Q₀.₆₅ flow rate pipe type (8.04 ± 0.72 and 7.97 ± 0.20 log 16S rRNA gene copies. mL⁻¹, respectively). At the study end, the most striking result was the decrease in bacterial concentration in the upstream zone compared with the inlet in the Q₁.₅ pipe (from 8.5 ± 0.1 to 8.1 ± 0.2 log 16S rRNA gene copies.mL⁻¹).

At day 85, bacterial concentrations in the outlet water (Q₁.₅ pipe) and in the downstream and middle zones (Q₀.₆₅ pipe) were systematically higher than in the inlet water. No correlation was found between bacterial concentrations in the drippers and bacterial concentration differences between inlet and outlet water, due to the weak differences in bacterial concentrations in the drippers (τ = 0.02, Kendall rank correlation test). Overall, the downstream zones showed higher concentrations of bacteria in water (both pipe types) at both day 85 and day 128. This could be explained by biofilm detachment from the upstream and middle zones of the pipes. The differences in bacterial concentrations between inlet and outlet water samples have been poorly studied in irrigation water distribution systems. Pachepsky et al. (2012) reported the increase in E. coli concentration in outlet water compared with inlet water due to biofilm formation in the pipe and suggested that it could be used as a marker of microbial community enrichment in outlet water.

#### 3.3.2. TOC changes are driven by temperature

TOC concentrations were measured to follow the organic matter concentration in the effluent. TOC ratios between the outlet (downstream, middle, or upstream zone) and inlet waters were similar at the different dripper positions and between flow rate pipe types. Measurements uncertainties in TOC (1 mg L⁻¹) for outlet and inlet water samples did not allow measuring differences in TOC ratio (Student's t-test, *p* < 0.05). The TOC ratios between outlet and inlet waters were close to 1 and showed very low organic matter consumptions in the irrigation pipes. This can be explained by the low quantities of biofilm formed in the pipes, but also by the low water retention times (8 min 2s and 6 min 11 s for Q₀.₆₅ and Q₁.₅, respectively) during irrigation. Moreover, only in larger and longer (hundreds kilometers) pipes, low organic matter differences between inlet and outlet water were found, with values between 0.17 and 0.42 mg.L⁻¹ (Xue et al., 2021). These observations confirmed that the low retention time in the pipe even in field conditions does not promote organic matter consumption. Moreover, TOC concentration changes in outlet waters were highly correlated with the temperature (Kendall correlation test, r = 0.56) (Fig. 7a), but not with the Reynolds number (Kendall correlation test, r = -0.12) (Fig. 7b). This showed that temperature rather than location along the pipe (hydrodynamical conditions) influenced the release of organic matter in the water.

#### 3.3.3. Organic matter quality composition changes

Organic matter quality composition in irrigation wastewater was followed by 3DEEM fluorescence for the first time. No significant BIX change was observed between inlet and outlet (upstream, middle and downstream zones) water throughout the irrigation period (t-test, *p* < 0.05) (Fig. S6). Similar results were found for Zone I (protein region) and Zone III (humic and fulvic acid regions) over time. Zone II (soluble microbial products) seemed to change in the downstream zone compared with the upstream and middle zones (Fig. S6). This suggests a higher concentration of soluble microbial products in downstream zone water compared with inlet water. The fluorescence results confirmed the absence of significant differences in TOC. However, the soluble microbial product zone (Zone II) seemed to be higher in the downstream zone water, suggesting a small microbial activity in this final part of the pipe (100 m from the pipe initiation). This result is correlated with the higher dry mass (between 10 and 65 µg cm⁻¹) found in the downstream part of
<figure><img src="image_10.png" /><figcaption>**Fig. 8.** 3DEEM fluorescence index (soluble microbial product) in outlet (downstream, middle, upstream zones) water samples in function of the mean water temperature in the 5 days before sampling (a) and Reynolds number (b). Blue lines show the trend line.</figcaption></figure>

the irrigation pipes. A previous study on a potable water distribution system found an active microbial community on the pipe wall by ATP measurement (Van Der Wielen and Lut, 2016).

As observed for TOC, soluble microbial product changes were more strongly correlated with water temperature (Kendall correlation test, r = 0.65) (Fig. 8a) than hydrodynamical conditions (Kendall correlation test, r = -0.06) (Fig. 8b). This could explain the low differences in biofouling among pipe locations.

## 4. Conclusions

Here, for the first time, several techniques were used to study and predict biofouling in a micro-irrigation system with treated wastewater at the field scale. Due to the low organic matter input (low COD) in the effluent, no significant decrease in the flow rate and efficiency of all tested pipes (from turbulent to laminar flow) was observed during the 129 days of study. Low concentrations of dry matter were found at the pipe surface. However, its concentration was slightly higher in the downstream zone of both flow rate irrigation pipe types. The bacterial densities in the biofilm developed along the internal pipe surface were strongly correlated with the hydrodynamic (Reynolds' number) conditions (i.e. higher in upstream areas of the pipe with turbulent flow), due to the formation of a highly resistant biofilm.

Biofilm in commercial drippers and in OADr occupied ~15-20% of the total labyrinth volume, without significant differences among sampling zones and flow rate pipe types. Compared with inlet water, bacterial concentrations in water from the sampling zones in the pipes showed <1 log increase, and was higher in the downstream zones. Also, for the first time, 3DEEM fluorescence was used to quantify and qualify organic matter patterns in treated wastewater. The results showed the potential of this technique to predict biofilm formation and activities in the irrigation pipe system. More studies are needed to assess the microbiological quality of the effluent and biofilm along the irrigation system to target microbial community structures and to identify indicators of undesirable microorganisms.

## Funding

This work was funded by ANR (the French National Research Agency) under the "Investissements d'avenir" program with the reference ANR-16-IDEX-0006.

## CRediT authorship contribution statement

Vincent Moulia: Writing – original draft, Validation, Methodology,

Investigation, Formal analysis, Conceptualization. **Marc Heran:** Writing – review & editing, Project administration, Funding acquisition. **Geoffroy Lesage:** Writing – review & editing, Validation, Methodology. **Jérôme Hamelin:** Writing – review & editing, Validation. **Jérôme Pinta:** Methodology, Investigation. **Aurélie Gazon:** Investigation. **Moeana Penlae:** Methodology. **Valérie Bru-Adan:** Methodology. **Nathalie Wéry:** Writing – review & editing, Validation, Methodology, Investigation, Conceptualization. **Nassim Ait-Mouheb:** Writing – review & editing, Validation, Methodology, Investigation, Formal analysis, Conceptualization.

## Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Acknowledgments

The authors gratefully acknowledge the technical support of Valérie Bonniol for sample processing and analyses.

## Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.jenvman.2024.122976.

## Data availability

Data will be made available on request.

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