# The State of the Art of Clogging in Vertical Flow Wetlands

^{*}

## Abstract

**:**

## 1. Introduction

## 2. Clogging Processes in VF Wetlands

_{i}) at the surface, the hydraulic conductivity (k

_{f}) within the filter body, as well as the local porosity. Due to the heterogeneity of the clogging development within the media, the effects can range from minor changes of the local flow velocities to the development of preferential flow paths and the exclusion of main parts of the filter. The built up of a clogging mat on the surface of VF wetlands leads to an uneven distribution of the wastewater, followed by exclusion of filter parts, surface ponding and overflow. Consequences thereof can be the risk of human contact with wastewater and the development of bad odour [12].

^{−2}day

^{−1}) and SS concentration (mg L

^{−1}). Other influential parameters include the grain size distribution of the filter media, the feeding intervals and resting periods. Outer blockage occurs due to the accumulation of SS, namely particulate organic and inorganic matter, at the surface, while inner blockage happens within the filter media [13,14,15]. Two main types of clogging are identified, namely bioclogging and clogging due to SS. Bioclogging describes the blockage of the pore space due to surplus sludge production based on biofilm (BF) growth and microbial uptake. A BF is composed of extracellular polymeric substances (EPS) and cells which undergo replication producing biopolymers when sufficient nutrients are present [16]. Clogging due to SS describes the accumulation of SS on and its deposition within the filter. Caselles-Osorio et al. [17] differentiate two types of accumulated solids, namely interstitial solids entrapped in the empty space between the media and adhered solids which are tightly adsorbed by the media. Interstitial solids are easily released by washing and filtering while adhered solids need ultrasonic treatment to be released by the media.

## 3. Design and Operational Suggestions to Avoid Clogging

#### 3.1. Design

^{2}per person equivalent (PE) and is operated in unsaturated free flow conditions.

^{2}per PE. The first stage has a coarser filter media with a grain size of 1–4 mm and an impounded drainage layer (15 cm). In this faster flowing media, OM and nitrogen (after nitrification) is available in the impounded layer leading to denitrification. In the second stage (0–4 mm), the remaining COD and NH

_{4}-N is treated.

^{2}per PE. One of the biggest VF wetlands implemented is a French system in Moldova treating the wastewater of up to 20,000 PE [23].

#### 3.1.1. Filter Media

_{10}and the uniformity coefficient U = d

_{60}/d

_{10}. d

_{10}and d

_{60}describe the grain size under which 10% and 60% of the grains pass during sieve analysis (by weight), respectively. The German design guideline DWA-A262 [24] requests a grain size of 0–2 mm d

_{10}= 0.2 to 0.4 mm and U < 5, for a size of 0–4 mm d

_{10}= 0.25 to 0.4 mm and U < 5.

#### 3.1.2. Loading

^{−2}day

^{−1}[9,13,25,26], 80 g COD m

^{−2}day

^{−1}for a two stage system [9,27] and 100–350 g COD m

^{−2}day

^{−1}for French VF wetlands [8,9]. It is important to note that the OLR is also a temperature dependent parameter, as the prevailing biological processes decrease with decreasing temperatures [28]. In order to avoid clogging, it is recommended to not only choose the appropriate OLR but also the related dosing strategy, which will be discussed in the next section.

#### 3.1.3. Dosing Strategy

_{2}m

^{−1}h

^{−1}. The availability of O

_{2}supports degradation processes during the resting period as accumulated SS are hydrolysed with its products adding another source of COD which has to be further degraded by bacteria [1,30].

#### 3.2. Pre-Treatment

^{−1}[13,31,32]. Regular maintenance of the pre-treatment facility is of the upmost importance to avoid solids carryover which will lead to clogging [1,33].

#### 3.3. Effects of Macrophytes

## 4. Remediation Strategies

_{2}O

_{2}), an aggressive oxidation agent [40,41,42]. Based on their findings, good results are achieved within a short time period, but the method of application is crucial. The injection of 1600 L of H

_{2}O

_{2}directly into the media of a 670 m

^{2}horizontal (HF) wetland was effective immediately. The use on the surface of a VF wetland (75 m

^{2}, 100 L of 35% H

_{2}O

_{2}) was reported as insufficient, as the peroxide reacted with the clog matter on top of the filter but not within the subsurface media [42].

^{−2}of earthworms after 10 days, as well as their positive effect during ongoing operation.

^{−1}and a TSS loading rate of 48 g TSS m

^{−2}day

^{−1}. Based on a VF column experiment using artificial wastewater without SS, the recovery time of the filter was achieved after one to three weeks [50,51], while others suggest 10 days in summer and 20 days in winter conditions [52].

## 5. Experimental Studies on Clogging

#### 5.1. Methods to Evaluate Clogging Behavior

#### 5.2. Experimental Studies

^{−2}day

^{−1}after two months and in the coarse media at a HLR of 250 L m

^{−2}day

^{−1}after one month. Measured NH

_{4}-N effluent concentrations were low also for high HLRs with removal rates of 99% for the fine and 90% for the coarse media. For early detection of clogging monitoring the water content within the substrate showed good results. For the 0–4 mm substrate, a linear increase in the residual water content before a dose was observed two weeks before clogging occurred. Based on soil physical and structural investigations, the main cause for clogging was found to be the SS load and not BM growth.

^{−2}day

^{−1}and an SS loading rate of 300 g SS m

^{−2}day

^{−1}and filled with different grain sizes of gravel, namely 3, 10 and 20 mm. Based on monitoring the infiltration rate and the effective porosity at different depths, the study concludes that firstly a blanket-like deposition layer is formed on top of the filter, followed by particles accumulating within the pore space in the first 0–4 cm. In a follow-up study, Hua et al. [66] investigate the time until clogging occurs, which was observed as 75, 120 and 240 days.

^{−2}day

^{−1}. The effluent quality, as well as the k

_{f}and the SS distribution within the filter, were monitored. A change in porosity/k

_{f}was measured but no clogging leading to malfunction of the columns occurred during the measurement campaign of one year.

^{−2}day

^{−1}and a BOD concentration of 600 mg L

^{−1}. The influence a resting time was determined after 3, 7 and 10 days in different filter depths. Main BF accumulation was found in the top 20 cm of the filter. The recovery ratio for k

_{f}was high after 7 and 10 days but started decreasing, while for the porosity it stayed constant. One explanation, therefore, was the remaining inert BF within the pore space. To evaluate the reduction of BF, polysaccharides and proteins were measured as a good correlation is stated. The anthrone–sulfuric acid method is used to measure polysaccharides and Coomassie Brilliant Blue G-250 colorimetry for the measurement of proteins. The quantity of EPS is calculated as the sum of both, and a significant decrease over the resting period is observed.

^{−1}was supplied within the recirculation process. Every week, the column was drained and filled with new synthetic wastewater. Thereby the porosity was evaluated. BF development caused preferential flow and local porosity reduction in dead zones within the column after one year.

_{4}-N removal rates of 39%–46% and 28%–39% respectively for the high load regime. The coarse to fine layering (from top to bottom) showed the least reduction in the water storage volume.

_{3}-N while measured NH

_{4}-N increased only nine days after clogging occurred. Measuring the oxygen concentration within the media using a portable gas analyser (Dräger X am 7000) is easy to do, but the as the oxygen content varies quickly, the time of observation is critical and therefore not practical. Observation of the NO

_{3}-N effluent concentration combined with an observation of surface ponding can be a valid method to identify if clogging is occurring.

_{f}were monitored. The main conclusions were as follows: bioclogging is a main driver while SS accelerates clogging. Undegraded starch particles are compacted by EPS and reduce the porosity. Bioclogging, Op-clogging and C-clogging can be relieved by a resting period, especially when the water level is reduced.

## 6. Model Concepts

#### 6.1. Clogging Due to SS

_{ss}, M) within the pore space based on the flow rate Q

_{in}(L

^{3}T

^{−1}) and the SS influent and effluent concentration (C

_{in}, C

_{out}, M L

^{−3}). The SS mass in the outflow (${M}_{out}$, M) is assumed to relate to a certain particle size (d

_{0}), hence a fraction of the total mass (Equation (2)). The certain sized SS accumulated in the pores would be washed off when the flow rate is higher than that of the maximum tolerated impact speed. Therefore, ${M}_{\le d0\%}$ is a function of the infiltration rate $K$ (L T

^{−1}) (Equation (3)). The calculation of $K$ (Equation (4)) is based on the Hagen–Poiseuille equation in combination with Darcy’s law and the porosity $\epsilon $ (-),

^{−2}), ${\mu}_{w}$ is the viscosity of the fluid (M T

^{−1}L

^{−1}) and ${\rho}_{w}$ is the fluid density (M L

^{−3}). The authors further assume that $K$ is a function of the operational time $\varphi \left(t\right)$.

_{ss},

_{n}) is calculated as follows (Equation (5)): clogging is described as pore volume reduction, hence when a certain mass is reached the pore space is used up and a fully clogged state is reached. This threshold condition is described in Equation (6),

^{2}) is the filter area, ${h}_{c}$ is the height of the clogging layer (L) and $\rho $ and $\omega $ are the density (M L

^{−3}) and moisture content (%) of SS, respectively. Values for the last named parameters are not provided by the authors.

^{−1}), $D$ is the dispersion coefficient (L

^{2}T

^{−1}), $z$ is the depth (L), $u$ is the vertically flowing water velocity (L T

^{−1}), v

_{i}is the fall velocity or settling velocity of SS of particle size i (L T

^{−1}), ${\psi}_{i}$ is the source or sink term of the SS of particle size i (M L

^{−3}) and is used to take account of the effect of the aggregation or break-up of particles, q(z) is the lateral inflow to the wetland (L

^{3}T

^{−1}), $A$ is the wetland area (L

^{−2}) and ${\phi}_{i,in}$ is the concentration of the SS of size i in the lateral flow (M L

^{−3}). For the described continuous flow system, Darcy’s law (Equation (8)) is used to model the water flow where $u$ is calculated as,

^{−1}), $H$ is the water head (L) and z is the depth (L). Within Equation (7), lateral flow is neglected and effects of aggregation and breakup of SS are reflected by the dispersion coefficient and the settling velocity. A modified mass conservation model is given in Equation (9), where R is the source or sink term of SS,

^{2}T

^{−1}), $\alpha $ is the dispersivity (L) and $u$ is the velocity based on Equation (8). The settling velocity for SS is represented using Equations (11) and (12) [72].

^{−3}) and n is an empirical parameter given the value of 5.1 [72] as this represents the physical properties of the presented work [15]. The parameter ${w}_{0}^{i}$ is an adjustable parameter representing the average effect of the sedimentation velocity of varied particle sizes. The last equation to solve Equation (9) is the description of the source or sink term R (Equation (13)). As attached BF supports SS accumulation, a form of the Monod equation [73] is used to describe particle adsorption.

^{−1}) and $\phi $ is the total SS concentration and ${\phi}_{S}$ represents the half-saturation-coefficient (M L

^{−3}) of the Monod equation. The reduction of the hydraulic conductivity based on the decreasing pore space is taken into account using the Kozeny–Carman Equation (14) [74],

^{3}L

^{−3}), K

_{0}is the hydraulic conductivity (M T

^{−1}) and ${\epsilon}_{0}$ the porosity (-) of the clean filter respectively and p, x and y describe empirical parameters (-).

#### 6.2. Bioclogging

^{−1}), m and n are van Genuchten model parameters [76]. The radii of the capillary tube can be determined by (Equation (16)),

^{−2}) and $\beta $ is the contact angle, which is generally set to 0. The bundle of capillary tubes representing the porous media is divided into a user specific number N. The thickness of the BF ${t}_{h}$ (L) is calculated using Equation (17) where the microbial volume ${V}_{m}$ (L

^{3}) is an input parameter. Equation (18) defines the relationship between the clean filter media and the impact of the BF thickness on the media. In a last step, the hydraulic conductivity (L T

^{−1}) is updated based on the BF thickness in Equation (19). Growth and decay of BF is described using the Monod [73] equation similar to Equation (20).

^{−1}), X is the BF concentration (M L

^{−3}), ${\mu}_{max}$ is the maximum growth rate (T

^{−1}), C is the concentration of the substrate (M L

^{−3}) and K is the half saturation constant (M L

^{−3}). The subscripts ea and s stand for electron acceptor and substrate respectively. ${d}_{r}$ represents the lysis rate with ${k}_{d}$ as the first-order decay constant (T

^{−1}). As within a porous media, the space for growth of BF is limited. Brovelli et al. [79] introduced a self-limiting function (Equation (22)) [80,81],

^{−1}) (Equation (23)) is described as [82,83],

^{−1}), ${d}_{g}$ is the characteristic grain diameter (L) and $\eta $ is the collector efficiency representing the frequency of collisions between mobile BF and grain surface (-). The collector efficiency is used by the authors as fitting parameter during model calibration as its general determination is difficult to assess [83]. Detachment due to shear forces is well discussed within the literature providing different approaches from dismissal [84] to simplified laws independent from the flow velocity. Here, a semi-empirical equation proposed by Rittmann [85] (Equation (24)) is used,

^{−1}), $\gamma $ is the viscosity of water (M L

^{−1}T

^{−1}), $M$ is the specific surface area (L

^{2}) and ${c}_{d}$ is an empirical parameter which is dependent on the experimental setup and calibrated for the work of Brovelli et al. [79]. Rittmann [85] proposes a value of 2.29 × 10

^{−6}. When combining Equations (20) to (24) one gets the variation of BF over time,

^{−3}) and ${\rho}_{S}^{i}$ is the density of the ith component of the immobile BF (M L

^{−3}). The change of the hydraulic conductivity based on the reduction of the pore space has been investigated based on experiments providing an exponential relationship (Equation (29)) [86,87],

^{−1}) and porosity (-), respectively, the subscript 0 represents the value of the clean media and, based on fitted data, $p=19/6$. The model based on Equation (29) assumes that BF clogs bigger pores first [86]. Another model describing the reduction of the hydraulic conductivity is based on pore network simulations where the assumption is in contrast with the description above stating that BF growth occurs first in the smaller pores [88]. This so called colonies model (Equation (30)) is described as

^{−3}–6 × 10

^{−2}for ${K}_{min}$. Within the model, the update of the hydraulic conductivity is carried out using the presented Equations (29)–(31) but no detail on which is actually used, nor a comparison of modelling results, is given.

^{−1}T

^{−1}), u is the velocity vector (L T

^{−1}), $\rho $ is the density of the fluid (M L

^{−3}), $p$ is the pressure (Pa), ${\epsilon}_{p}$ is the porosity (-), $K$ is the permeability (L

^{2}) and ${Q}_{br}$ is defined a mass source/sink (M L

^{−3}T

^{−1}). The influence of volume forces such as gravity is respected by the force term $F$ (M L

^{−2}T

^{−2}). As the column experiment was carried out in saturated conditions, a single phase flow model was used. The solute transport is described by a simple advection-diffusion Equation (34), incorporating the biokinetic model within the source/sink term $R$,

^{−3}), D is the molecular diffusivity (L

^{2}T

^{−1}) and R is the reaction rate for the solute (M L

^{−3}T

^{−1}) derived from a biokinetic model. The biokinetic model used in cooperates the processes of mineralization, hydrolysis, growth and lysis of heterotrophic bacteria (XH), respectively and is based on the work of Langergraber and Simunek [90]. For OM, three fractions are respected, namely, readily, slowly and inter OM. Hydrolysis of slowly to readily available OM is described in Equation (35), while the growth and decay of XH on readily OM is described by Equation (18),

^{−1}) and saturation/inhibition of hydrolysis (M M

^{−1}), ${S}_{S}$ is the readily available OM concentration (M L

^{−3}) and ${C}_{S}$ is slowly available OM (M L

^{−3}).

^{−1}), ${b}_{ina,H}$ is the lysis rate (T

^{−1}) and ${K}_{S}$ is the half saturation coefficient (M L

^{−3}). The removal of ${S}_{S}$ is further described by Equation (37),

^{−1}). The next sub-model describes the BF detachment rate [85] implement in this model (Equation (38)). BF detachment is caused by fluid shear stress and is based on the flow rate, and therefore increases the local porosity.

^{−1}) is the BF detachment rate, $dp$ is the average spherical gravel diameter (L) and $M$ is the specific surface area of the filter media (L

^{−1}). The parameter M is determined by using a uniform gravel size with a spherical shape.

^{−3}). With this information, the relative change in local porosity and its effect on the permeability is calculated using the Kozeney–Carman Equation (40) [91] and is used to update the velocity and pressure profile (Equations (32) and (33),

^{−3}) and u is the pore-water velocity (L T

^{−1}) described as

^{−1}) and $n$ is the porosity (-). The subscripts i and j represent the time index and the space grid index, respectively. The reaction term r is represented by the following equation,

^{−1}). The BF growth is described by

^{−1}). Here the authors claim using the Monod equation, but BF growth is only related to consumption of substrate as well as lysis. The substrate concentration within the micro region for the time step $\Delta t$ is described as

^{−1}) of BF and is determined empirically by Kretzschmar et al. [94] as,

^{−1}), L is the column length (L) and ${C}_{0}$ and $C$ represent the influent and effluent BOD concentration (M.L

^{−3}), respectively. The total amount of BF deposition ${\sigma}_{i,j}$ (M L

^{−3}) is calculated as

^{−3}) and ${n}_{0}$ is the initial porosity. The update of the hydraulic conductivity ${K}_{i,j+1}$ is finally carried out using the Kozeny–Carman equation

#### 6.3. Bioclogging and SS Clogging

^{3}L

^{−3}), $t$ is the time (T), $z$ is the spatial coordinate (L), $K$ is the unsaturated hydraulic conductivity (L T

^{−1}) and $h$ is the matrix potential (L). The relationship between the pressure head, hydraulic conductivity and water content are described by the van Genuchten–Mualem model (Equations (51)),

^{3}L

^{−3}) as well as ${K}_{S}$ are the saturated hydraulic conductivity (L T

^{−1}). The empirical parameters $\alpha $ (L

^{−1}) $m$ and n influence the shape of the functions $\theta $(h) and K(h), and l is defined as the pore-connectivity parameter. Se equals the effective water content as shown in Equation (51a). Transport of dissolved components is described using Bresler’s equation (Equations (54)) [97],

^{−3)}, d is the dispersion coefficient (L

^{2}T

^{−1}), q is the specific flow rate (L T

^{−1}) and R is the reaction term. The dispersion coefficient accounts for diffusion and mechanical dispersion, but the authors assume that in the liquid phase the effect of diffusion compared to dispersion can be neglected. Under saturated conditions and constant flow, the mechanical dispersion is considered to be proportional to the average flow velocity and dependent on the dispersivity $\lambda $ (L),

^{−3}) and $f$ is the filter coefficient (L

^{−1}). The reduction of the porosity is related to the total volumetric specific deposit ${D}_{vtot}$ (L

^{3}L

^{−3}), which is continuously updated. How this parameter is determined is not further described. The effect of the change in porosity on the hydraulic conductivity is described using the Kozeny–Carman Equation (57) [100],

_{0}is the hydraulic conductivity (L T

^{−1}), ${\epsilon}_{0}$ is the porosity (-) of the clean filter respectively and p, x and y describe empirical parameters (-).

^{−1}) and S the source/sink term (M T

^{−1}) representing reaction and conversation rates. This is used as analogues for the influent parameters SS (${M}_{IS}$) and BF solids (${M}_{BS}$), contributing to SS clogging and bioclogging, respectively. The accumulation of total solid mass is represented by Equation (59). Two source terms represent the contributing loads from either BF development based on BOD (${S}_{BS}$, (Equations (60)) and from inert matter production (${S}_{IS}$, (Equations (61)),

^{3}T

^{−1}), t is the time (T), ${C}_{BOD}$ the BOD influent concentration (M L

^{−3}), ${Y}_{H}$ is the observed yield for heterotrophic BF (-),${K}_{d}$ is the heterotrophic microbial endogenous decay coefficient (T

^{−1}), $\theta $ is the mean residence time of biosolids within the system (T) and ${f}_{p}$ is the fraction of microbial BM converted to inert matter (-).

^{−3}), ${f}_{v}$ is the proportion of organic matter in SS (-), ${f}_{nv}$ is the proportion of the inert matter in the organic SS (-) and $\lambda $ is a proportional factor with a value between 0 and 1. The authors are aware of the simplification representing BF detachment and SS retention. In addition, Hua et al. [101] introduce a model predicting the effect of plant roots on clogging depending on two seasons, namely the growing season (Equations (64)) and the non-growing season (Equations (65)). During the growing season plant BM is increasing while during the non-growing season plant decay is prevailing,

^{−1}) is the plant decay coefficient for living plant material, ${f}_{NH}$ is the plant growth rate depending on ammonia and ${f}_{NO}$ is the plant growth rate depending on nitrate (T

^{−1}). Those growth rates are calculated as follows,

^{−1}), ${K}_{pNH}$ and ${K}_{pNO}$ (M L

^{−3}) are the half saturation coefficients for ammonia and nitrogen respectively and ${C}_{NH}$ and ${C}_{NO}$ are the influent concentrations (g m

^{−3}) for ammonia and nitrogen respectively. Due to plant decay, dead plant BM is produced. The change of this mass over time is calculated using Equation (68),

^{−1}) representing the loss of BM due to physical degradation processes such as physical degradation and invertebrate consumption. The total plant BM for the growth season (Equations (69)) and non-growth season (Equations (70)) is calculated by combining Equations (64) and (65) with Equation (68).

^{−3}) and the moisture content (-) of the total solids and ${\rho}_{root}$ is the density of the plant roots (M L

^{−3}). The time after full clogging is reached is determined over the operational time of the model run and the following criteria,

^{2}).

## 7. Summary and Conclusions

#### 7.1. Experimental Studies

^{−2}day

^{−1}) used compared to other studies (Table 4). Generally, it can be concluded that

- A general definition of clogging in various states is missing.
- The majority of the experimental studies in the literature used continuous loading to fast track clogging of the system.
- Besides analyses of occurring processes, the impact of resting on the recovery is observed and its importance pointed out. This strongly supports the importance of the intermittent loading operation used in the design guidelines [9].
- For future studies on clogging processes, using real life operation is highly recommended to close the gap between experimental studies and implemented systems.

#### 7.2. Modelling

- A variety of modelling concepts are available to describe clogging processes in VF wetlands, ranging from simple black box models to deterministic process based models describing the actual processes.
- Thereby different contributing factors, alone or in combination, are included, namely clogging due to SS, bioclogging and plant detritus.
- Interactions between those contributors are, up to now, not implemented in existing models.
- The main sub-models used [69] follow the same concepts over all modelling studies despite different details in the implemented versions.
- Only a small fraction of the sub-models describe water flow in unsaturated conditions.
- Detailed information on model parameters is often missing.

## Author Contributions

## Funding

## Conflicts of Interest

## Abbreviations

BF | Biofilm | PE | Person equivalent |

BM | Biomass | RH | Relative humidity |

CFD | Computational fluid dynamics | SHP | Soil hydraulic parameters |

COD | Chemical oxygen demand | SS | Suspended solids |

EPS | Extracellular polymeric substances | TDR | Time domain reflectometry |

ET | Evapotranspiration | TSS | Total suspended solids |

HF | Horizontal flow | TW | Treatment wetland |

HLR | Hydraulic loading rate | VF | Vertical flow |

OLR | Organic loading rate | VSS | Volatile suspended solids |

OM | Organic matter | XH | Heterotrophic bacteria |

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**Table 1.**Comparison of design parameters of VF wetland types to prevent clogging (adapted from [1]).

Type | Surface Area Per PE | Pre-Treatment | Media | OLR | Dosing | |
---|---|---|---|---|---|---|

Single stage VF | 4 m^{2} | Yes | Sand | 0–2 mm | 20 | >6 h |

4 m^{2} | Yes | Sand | 0–4 mm | 20–27 | >6 h | |

Two stage VF | 2 m^{2} | Yes | Sand | 1–4 mm/0–4 mm | 80 | >3 h |

French VF | 2–2.5 m^{2} | No | Fine gravel | 2–8 mm/0–4 mm | 100–350 | 3.5 day 7 day rest |

Category | Method | Time Until Recovery |
---|---|---|

Destructive methods | Excavation and replacement using new media | Within one day Several days |

Excavation, washing and reuse of media | ||

Active treatment | Application of oxidising agent | Immediate up to several hours |

Addition of solubilisation agent | One week | |

Enzyme treatment | - | |

Addition of earthworms | Around 10 days | |

Passive treatment | Resting of the whole treatment wetland (TW) | 10–20 days |

Study | Bioclogging | SS Clogging | Nutrients Added | |
---|---|---|---|---|

Zhao et al. | [59] | Glucose | Starch | KNO_{3}, K_{2}HPO_{4} |

Hua et al. | [60] | - | Lake sediment | - |

Hua et al. | [61] | Glucose | - | (NH_{4})_{2}SO_{4}, CO(NH_{2})_{2}, K_{2}HPO_{4}, |

Rajabzadeh et al. | [62] | Molasses, urea | - | NH_{4}H_{2}PO_{4} |

Song et al. | [63] | not mentioned | ||

Yang et al. | [31] | - | Zeolite powder | - |

Zhou et al. | [64] | Glucose | Starch | NaCl, (NH_{4})_{2}SO_{4}, CO(NH_{2})_{2}, K_{2}HPO_{4}, NaH_{2}PO_{4}·12H_{2}O, MgSO_{4}·7H_{2}0, CaCl_{2} |

Authors | Feeding | Wastewater | $\frac{{O}{L}{R}}{{g}{C}{O}{D}\text{}{{m}}^{-2}\text{}{d}{a}{{y}}^{-1}}$ | $\frac{{T}{S}{S}}{{g}{T}{S}{S}\text{}{{m}}^{-2}\text{}{d}{a}{{y}}^{-1}}$ | $\frac{{H}{L}{R}}{{L}\text{}{{m}}^{-2}\text{}{d}{a}{{y}}^{-1}}$ | $\frac{\mathbf{COD}}{{\mathbf{mg}\text{}{L}}^{-1}}$ | $\frac{\mathbf{TSS}}{{\mathbf{mg}\text{}{L}}^{-1}}$ | ||
---|---|---|---|---|---|---|---|---|---|

Langergraber et al. | [14] | intermittent | every 6 h | real | 5–100 * | 8–29 | 40–150 | 100–700 * | 50–300 * |

5–120 * | 8–48 | 40–250 | 100–700 * | 50–300 * | |||||

Zhao et al. | [59] | continuously | synthetic | 40–343 | 40 | 850 | 47–404 | ||

Hua et al. | [60] | continuously | Lake sediments | 300 | 500 | ||||

300 | 500 | ||||||||

300 | 500 | ||||||||

Sani et al. | [15] | continuously | 72 h/36 h feeding | real | 22 | 23 | 73 | 301 | |

48 h rest | real diluted | 11 | 8 | 151 | |||||

Hua et al. | [50] | continuously | synthetic | 300 (as BOD) | 500 | ||||

Rajabzadeh et al. | [62] | continuously | synthetic | 500 | |||||

Song et al. | [63] | fill and drain 10 h HRT 2 h draining | synthetic | 112 | |||||

236 | |||||||||

113 | |||||||||

Ren et al. | [68] | continuously | real | 66 | 28 | 800 | 82 | 35 | |

Petijean et al. | [11] | intermittent | every 6 or 8 h | real | 35 | 9 | 73 | 483 | 119 |

Yang et al. | [31] | continuously | synthetic | 18.5 | 37 | 500 | |||

Zhou et al. | [64] | continuously | synthetic | 163 | 137 | 815 | 200 | 168 | |

68 | 84 |

Authors | Media | $\frac{{S}{i}{z}{e}}{{m}{m}}$ | Porosity | $\frac{{k}{f}}{{c}{m}\text{}{{s}}^{-1}}$ | $\frac{{d}10}{{m}{m}}$ | $\frac{{d}60}{{m}{m}}$ | Cu | |
---|---|---|---|---|---|---|---|---|

Langergraber et al. | [14] | Sand | 0.063–4 | 0.13 | 1 | 7.69 | ||

1–4 | 1.1 | 3 | 2.73 | |||||

Zhao et al. | [59] | Coarse sand | 0.36 | 4.85 × 10^{−2} | 1 | 4.4 | 4.4 | |

Hua et al. | [60] | Gravel | 3 | 0.34 | 2.5 | 5.8 | 2.32 | |

10 | 0.44 | 6 | 11.4 | 1.9 | ||||

20 | 0.47 | 15 | 25 | 1.67 | ||||

Sani et al. | [15] | Pea gravel | 10 | |||||

20 | ||||||||

Hua et al. | [50] | Coarse sand | 0.12 | 0.2784 | 2.32 | |||

Rajabzadeh et al. | [62] | Pea gravel | 10 | |||||

Song et al. | [63] | Sand, 4 layers | 3–8 | |||||

Sand, 4 layers | 8–3 | |||||||

Uniform | 5–6 | |||||||

Ren et al. | [68] | Sand | ||||||

Petitjean et al. | [11] | Sand | 0–4 | 0.16 | 0.048 | 0.3 | ||

Yang et al. | [31] | Gravel | 3–4 | 0.37 | 0.458 | |||

Zhou et al. | [64] | Sand | 1–2 |

Reference | Description | Clogging | Model Type | SHP Update | Sub-Model | |
---|---|---|---|---|---|---|

Hua et al. | [66] | Estimate clogging time based on SS influent and effluent data | SS | BB | Non | Based on mass balance |

Sani et al. | [15] | Describe the impact of SS on clogging | SS | GB | Kozeny-Carman | Water flow Mechanical dispersion Settling Adsorption |

Mostafa and van Geel | [75] | Conceptual model describing the impact of BF growth on the SHP | BC | WB | Change of porosity | Water flow Change of SHP based on reduction of pore space |

Brovelli et al. | [79] | Simulate effect of biomass on SHP in saturated conditions | BC | WB | Change of porosity | Biokinetic model BF attachment and detachment |

Rajabzadeh et al. | [62] | Effect of BF on permeability in saturated conditions, including BF detachment due to shear stress | BC | GB | Kozeny-Carman | Fluid transport Solute transport Biokinetic model BF detachment Clogging |

Hua et al. | [92] | Parameter efficient model to describe bioclogging based on colloid transport models | BC | BB | Kozeny-Carman | Water flow Solute transport (advection) Linear growth of BF Clogging model |

Giraldi et al. | [95] | Forecast behaviour and treatment properties due to clogging | SS, BC | GB | Kozeny-Carman | Water flow Solute transport Biokinetic model Transport and filtration of SS |

Hua et al. | [101] | Clogging time based on influent of SS, BF, development on BOD and Plant detritus | SS, BC, P | BB | Non | BF, SS based on mass balance Plant clogging model |

**Table 7.**Identification and classification of clogging (adapted from [13]).

Degree of Clogging | Description |
---|---|

Clogging | >80% of the surface is permanently ponded between two loadings |

Partly clogged | 30%–70% of the surface is ponded between two loadings |

No clogging | <30% of the surface is ponded between two loadings |

Geometry of Plot/Column | Filter Media | Loading Rates | Quality Parameters |
---|---|---|---|

Diameter or length width | Material used | OLR | COD |

Area | General grain size distribution | HLR | SS |

Total height | d_{10}, d_{60} | SS LR | VSS |

Height of main layer | Porosity | Loading interval | NH_{4}-N |

Height of other layer | Hydraulic conductivity | Duration of a single dosing | NO_{3}-N |

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**MDPI and ACS Style**

Pucher, B.; Langergraber, G.
The State of the Art of Clogging in Vertical Flow Wetlands. *Water* **2019**, *11*, 2400.
https://doi.org/10.3390/w11112400

**AMA Style**

Pucher B, Langergraber G.
The State of the Art of Clogging in Vertical Flow Wetlands. *Water*. 2019; 11(11):2400.
https://doi.org/10.3390/w11112400

**Chicago/Turabian Style**

Pucher, Bernhard, and Guenter Langergraber.
2019. "The State of the Art of Clogging in Vertical Flow Wetlands" *Water* 11, no. 11: 2400.
https://doi.org/10.3390/w11112400