Abstract

We studied water loss performance in a model plant, the Tufted sedge (Carex elata All.), which is an active water balance component of subsurface flow constructed wetlands. Due to active regulation of transpiration, the volume and dynamics of water loss in these constructed wetlands are difficult to plan without preliminary and targeted measurements and calculations with regard to the specific plant component. We estimated transpiration values in the laboratory based on daytime transpiration ranges for spring, summer and autumn, and examined the transpiration effect of the hydraulic load. During spring, water loss via transpiration can reach 83% of the hydraulic load on certain days. During summer, this value can increase to 100% of the hydraulic load, which means that the daytime transpiration can significantly affect effluent concentration. Air humidity proved to be the most critical environmental factor for water loss resulting from transpiration, therefore a water discharge plan designed in such a way as to be able to also adjust soil moisture is the key to optimal water circulation at the system level.

INTRODUCTION

Constructed wetlands (CWs), also known as treatment wetlands, are engineered systems designed and constructed to treat wastewater. The two main types of constructed wetlands are free-surface flow systems (FSF-CWs), and sub-surface flow systems (SSF-CWs). The latter can be constructed with the wastewater flowing either horizontally (HSSF-CWs) or vertically (VSSF-CW) through the substrate that supports the growth of plants.

The two components of evapotranspiration that negatively affect the water balance of CWs by causing loss of water are evaporation from the water surface and soil, and plants' transpiration (Allen et al. 1998; Kadlec & Wallace 2009). Water loss to the atmosphere via evapotranspiration can be high (Borin et al. 2011), especially under warm and windy environmental conditions (Białowiec & Wojnowska-Baryla 2007; Albuquerque et al. 2009; Headley et al. 2012).

The rate of evapotranspiration primarily depends on climatic factors, such as precipitation, temperature and wind (Kumar et al. 2012), as well as on the growth (Borin et al. 2011) and the height of the plants in the system and the density of the leaves (Pauliukonis & Schneider 2001; Bialowiec et al. 2014). Plants also play a key role in determining water loss in a CW (Leto et al. 2013).

Pedescoll et al. (2013) showed that the evapotranspiration in SSF-CWs was 20–22 mm/day, generally accounting for 44% of the hydraulic load, but reaching 100% on some days. Beebe et al. (2014) measured similar values of 20 mm/day but reaching 40 mm/day during certain times of the day. In another study, values of evapotranspiration in SSF-CWs fluctuated between 19.5 and 40 mm/day (Freedman et al. 2014).

Tuttolomondo et al. (2015) measured evapotranspiration in a CW in Italy and observed that on some summer days evapotranspiration reached 25–35 mm/day, accounting for 20–30% of the hydraulic load. Tanner (1995) measured evapotranspiration in a CW during a hot (30–33 °C) summer in New Zealand, measuring rates of 7.1–11.7 mm/day, which means that transpiration was accounting for 20% of the hydraulic load.

Chazarenc et al. (2003) estimated evapotranspiration using a 1 m2 pilot-scale CW, planted with Common reed (Phragmites australis L.). Monthly evapotranspiration rates were 165.0, 378.2, 127.5 and 281.5 mm/month in May to August, respectively. The evapotranspiration water loss accounted for 13–40% of the hydraulic load. The study concluded that in CWs, evapotranspiration increased hydraulic retention time and decreased dispersion (Chazarenc et al. 2003). As a result of evapotranspiration, concentration of solutes increases in CWs (Kadlec et al. 2000). The highest evapotranspiration rates in a HSSF-CW were found to occur at midday, at 12:00 to 13:00 (Jacobs et al. 2002; Galvão et al. 2010). Bialowiec et al. (2014) studied the pollutant removal efficiency of CWs under different evapotranspiration rates and concluded that higher evapotranspiration caused higher effluent concentrations. In another study of the relationship between evapotranspiration and removal efficiency, increased rate of evapotrans­piration positively affected outflow biochemical oxygen demand (BOD5) and chemical oxygen demand (COD) concentrations (Tuttolomondo et al. 2016). As evapotranspiration indirectly affects effluent water quality, it is imperative to obtain detailed knowledge about evapotranspiration in SSF-CWs.

Among the many studies on water management processes of surface flow constructed wetlands (Konyha et al. 1995; Kadlec 1999, 2006; Kadlec et al. 2000), only a few contain detailed water balance analysis of SSF-CWs (Chazarenc et al. 2003).

In this study, we aim to estimate daytime transpiration rates and determine the range of transpiration for a CW under local climatic conditions near Hódmezővásárhely, Hungary. In order to obtain more detailed and precise results, we used estimations. In this study, we only calculated seasonal rates of transpiration. According to Jasechko et al. (2013), the ratio of transpiration and evaporation of vegetation-covered surfaces can reach 80:20 at a global scale.

MATERIALS AND METHODS

Study site

Our study site was a SSF-CW treatment plant near Hódmezővásárhely (Hungary). This artificial wetland treats 1–1.5 m3 of wastewater per day from a dairy farm. The treatment establishment consists of a septic tank, a pump system, VSSF-CW, HSSF-CW, a polishing pond and a trickling system planted with poplar trees (Populus spp.), and Tufted sedge (Carex elata All.). In this study we focus on the HSSF-CW.

Species description

Tufted sedge is a widespread species found all over Europe, except for the Mediterranean. This species is native to Hungary and is generally abundant throughout much of its central European range (http://www.iucnredlist.org). It is mostly found in shallow water, preferring oligotrophic to eutrophic and often calcareous freshwater habitats, and in seasonally flooded areas. The primary life form of the species is perennial and aquatic. Tufted sedge grows as a tussock-forming graminoid, often forming extensive stands. Being a Eurasian temperate flora element, it presents broad ecological tolerance to light as well as the moisture, nitrogen and salt content of soil. Its stem grows up to 40–120 cm tall, has a triangular shape and is very rough at the top (https://www.brc.ac.uk/plantatlas). The cross section of the leaf is M-shaped, the blade is 2–5 mm wide, greyish-green, and the underside of the leaf is dull. It is a hypostomatic plant; that is, stomatal openings for gas exchange are on the underside of the leaf (Dean & Ashton 2008). Stomatal openings are also generally found on the leafy floral shoots (personal observation). Drained soil conditions, especially during the hottest period of the summer, can strongly decrease the stomatal conductance-induced transpiration rate (Busch & Lösch 1998).

Sampling units

Four tussock-forming units were collected by the authors at the study site in a SSF-CW area in May 2012. Specimens were planted in four large (40 × 40 cm) containers and they were grown in the Botanical garden of the University of Pécs under natural field conditions (Figure 1). Throughout the growing season (May to October 2013), including the data collection periods (May, July and October 2013), plants were irrigated daily using recycled water. These four containers were the sampling units used for gas exchange measurements in the laboratory. The SSF-CW with Tufted sedge as a whole was the unit for transpiration estimation at a stand level. To measure the total surface area of the plants for the system level water loss estimation we used a portable leaf area meter (AM-100-002, ADC Ltd, UK).

Figure 1

Ombrothermic diagram for the Botanical garden of the University of Pécs based on local meteorological data during the study period (2013). AMT, annual mean temperature; ASP, annual sum of precipitation; MMT, monthly mean temperature; MSP, monthly sum of precipitation (http://joido.ttk.pte.hu/en/).

Figure 1

Ombrothermic diagram for the Botanical garden of the University of Pécs based on local meteorological data during the study period (2013). AMT, annual mean temperature; ASP, annual sum of precipitation; MMT, monthly mean temperature; MSP, monthly sum of precipitation (http://joido.ttk.pte.hu/en/).

Gas exchange measurements

We used a portable infrared gas exchange analyser (LCA-Pro + , ADC Ltd, UK) to measure and calculate the transpiration rate of model plant individuals. In this equipment, the microclimate can be controlled by four abiotic environmental parameters, temperature (T), air humidity (RH), light intensity (PPFD), and CO2 concentration (vpm). The air flowed around both sides of the sample leaf, and CO2 and H2O content were measured simultaneously. Measurements were carried out in an ‘open system’ configuration, where fresh air was continuously passing through the plant leaf chamber. A small fan in the chamber ensured thorough mixing of the air around the leaf. Gas exchange functions of the plant caused CO2 concentration to decrease and air humidity to increase. We detected water vapour by the two laser-trimmed humidity sensors incorporated in the analyser, measuring both incoming (‘reference’) and outgoing (‘analysis’) gas concentrations. Transpiration rate (E) was calculated approximately every 20 seconds by the analyser, using two parameters and a correction factor (Equation (1)). 
formula
(1)
where Δe = dilution-corrected differential water vapour concentration (mBar); us = air mass flow into the leaf chamber per square metre of leaf area (mol s−1 m−2); p = current atmospheric air pressure (mBar).

Undamaged, mature (not too young or old) leaves rich in photosynthetic pigments were selected for the analysis. They were marked with a sampling strip before the measurements. After setting up the instrument and the measuring system, two leaves from two test units were placed parallel to each other in the leaf chamber. We selected the part of the leaf plate that had a sufficiently wide assimilating tissue and thin central vessel, in order to increase measurement accuracy, and ensured that the available leaf chamber area (5.8 cm2) was filled. Using the selected leaf-pairs, we measured three parameters of gas exchange (light, temperature and air humidity) using standard scales and also a constant level of CO2. In general, during the measurements three of the four abiotic variables were kept constant at a time, and the fourth was increased or decreased. Light responses were recorded between 0 and 1,566 μmol m−2 s−1 under constant level of CO2 (370 vpm), temperature (20 °C, 25 °C, 30 °C), and air humidity (1–19 mBar equal to 3.6–62.5% relative air humidity). Temperature responses were recorded at 17.5–39.0 °C, under constant level of irradiation (1,218 μmol m−2 s−1), CO2 (370 vpm), and water vapour pressure (1–19 mBar equal to 3.6–62.5% relative air humidity). Humidity responses were recorded at 1–19 mBar, under constant level of light (1,218 μmol m−2 s−1), CO2 (370 vpm), and temperature (20 °C, 25 °C and 30 °C). The sampling size was the four tussock-forming units with duplicated pairs of leaves in the plant chamber (N = 4), and there were five replications per measurement.

Data processing and calculations

Light responses were recorded under representative mean temperatures during the seasons; that is, 20 ± 0.5 °C in spring, 30 ± 0.5 °C in summer, and 25 ± 0.5 °C in autumn. First order exponential curves were computed for a wide range of irradiation (0–1,566 μmol m−2 s−1), representing lower and higher levels of light intensity. Considering temperature responses, we recorded data in the measurement range of the instrument and considering environmental conditions. With regard to humidity responses, the measurement range extended from extreme low to medium values, representing very dry to moderately dry environments for transpiration, respectively. In both of the previous cases, to match the scales and make water loss calculations consistent, third-order polynomials were fitted for standardized temperature (17.5–42.0 °C) and humidity (3.2–60.2%) ranges, corresponding to representative levels of environmental parameters during the particular seasons. The evaporation values at total darkness have been omitted from the calculations, because this is not typical during the daytime. We applied polynomial equations in the matched function using the program Origin 6.0 (Originlab, Northampton, USA) for curve fitting and data interpretation.

We used a leaf area meter to measure the leaf area of the experimental unit. The total leaf area of the 0.25 m2 test field (total of four sampling units) area was 2.65 m2. The leaf area of the CW was estimated based on this value. The surface of the system was 25.2 m2 and therefore the estimated leaf surface was 267 m2. To determine water loss we used Equation (2): 
formula
(2)
where V is the water loss due to transpiration (m3), E is the transpiration rate of the given period (mol m−2 s−1), A is the leaf surface (m2), t is the duration of the transpiration of the given period (s), MH2O is the molar mass of water (g mol−1), and ρ is the density of water (g m−3).

Considering the lack of detailed information about the measured light intensity per unit per day during the period of the test, extreme minimum and maximum transpiration values were calculated in the SSF-CW based on the measured data. Information about sunrise and sunset was obtained from the Hungarian Meteorological Service website (http://www.met.hu/), based on which the number of daytime hours were averaged for a given season.

RESULTS AND DISCUSSION

Transpiration responses of the model plant

In this section, we describe characteristics of the environmental response curves of model plant individuals derived from three studied parameters (Figure 2). Considering light responses, as expected, saturation curves are more or less progressively increasing in all seasons. The lowest minimum and maximum transpiration rates were observed in the autumn at medium leaf temperature conditions. The most intense transpiration occurred at the highest temperatures, during summer.

Figure 2

Transpiration rates (E) of Tufted sedge (Carex elata All.) to (a) light (PPFD: Photosynthetic Photon Flux Density); (b) leaf temperature (T), and (c) relative air humidity (RH). Light responses refer to seasonal mean temperatures (Spring: 20 ± 2.5 °C; Summer: 30 ± 2.5 °C; Autumn: 25 ± 2.5 °C); first order exponential curves are fitted to a wide range of irradiation (0–1,566 μmol m−2 s−1). Third order polynomials are calculated for standardized temperature (17.5–42.0 °C) and humidity (3.2 = 60.2%), with ranges corresponding to the representative levels of environmental parameters of the three seasons.

Figure 2

Transpiration rates (E) of Tufted sedge (Carex elata All.) to (a) light (PPFD: Photosynthetic Photon Flux Density); (b) leaf temperature (T), and (c) relative air humidity (RH). Light responses refer to seasonal mean temperatures (Spring: 20 ± 2.5 °C; Summer: 30 ± 2.5 °C; Autumn: 25 ± 2.5 °C); first order exponential curves are fitted to a wide range of irradiation (0–1,566 μmol m−2 s−1). Third order polynomials are calculated for standardized temperature (17.5–42.0 °C) and humidity (3.2 = 60.2%), with ranges corresponding to the representative levels of environmental parameters of the three seasons.

Transpiration was the lowest in spring and increased as time progressed. During spring and summer, the maximum rate of transpiration was observed at a relatively low level of irradiation (198.5 and 197.7 μmol m−2 s−1, respectively). During autumn, maximum water loss (302.5 μmol m−2 s−1) required a more intense irradiation. Transpiration did not increase in close correlation with the mean temperature increase of the seasons, as water loss during spring exceeded transpiration during autumn. Temperature responses steadily increased throughout the seasons, and third-order polynomial curves fitted best to the changes of transpiration. The most dynamic transpiration increase was detected during summer, at temperatures above 40 °C (outside the measuring range). During autumn and spring, water loss was highest at lower temperatures (35.5 and 32.5 °C, respectively). This phenomenon shows that the water loss process in the model plant during spring and autumn can be controlled by temperature conditions, representing a seasonal abiotic constraint. The third environmental response in the experiment was humidity. Increasing water content of the air caused a monotonous decrease in transpiration. In general, there is a higher water loss at a lower level of humidity that can dramatically decrease with increasing air humidity. During summer, extreme low humidity can decrease transpiration, suggesting that under elevated temperature transpiration can be controlled by water conditions. Accordingly, low atmospheric humidity coupled with high temperatures may be an environmental barrier to the full development of transpiration maxima.

Water loss calculations

During spring, the daytime water losses via transpiration were 0.46–0.83 m3 and under typical climatic conditions water loss was 0.50 m3 (Tables 1–4). The daily influent wastewater was around 1 m3, which means in spring this value is half of the amount of daily influent wastewater.

Table 1

Transpiration rates of Tufted sedge (Carex elata All.), calculated for representative seasonal ranges of the studied environmental factors (mean ± SD)

 Spring Summer Autumn 
E (PPFD) 12.18 ± 0.47 24.43 ± 0.05 11.63 ± 0.39 
E (T) 31.07 ± 0.63 43.80 ± 0.24 52.76 ± 0.50 
E (RH) 63.02 ± 0.41 73.32 ± 0.27 82.52 ± 0.64 
Mean ± SD 2.09 ± 0.98 3.85 ± 0.56 2.31 ± 0.60 
 Spring Summer Autumn 
E (PPFD) 12.18 ± 0.47 24.43 ± 0.05 11.63 ± 0.39 
E (T) 31.07 ± 0.63 43.80 ± 0.24 52.76 ± 0.50 
E (RH) 63.02 ± 0.41 73.32 ± 0.27 82.52 ± 0.64 
Mean ± SD 2.09 ± 0.98 3.85 ± 0.56 2.31 ± 0.60 

E is transpiration (mmol m−2 s−1), PPFD is Photosynthetic Photon Flux Density – i.e. irradiation (μmol m−2 s−1), T is temperature (°C) and RH is relative air humidity (%).

1PPFD: 44–870 μmol m−2 s−1; 2PPFD: 870–1,566 μmol m−2 s−1; 3T: 20 ± 2.5 °C; 4T: 30 ± 2.5 °C; 5T: 25 ± 2.5 °C; 6RH: 38–60.2%; 7RH: 15.8–38%; 8RH: 25.3–50.7%.

Table 2

Transpiration rates of Tufted sedge (Carex elata All.) calculated for minimum seasonal ranges of the studied environmental factors (mean ± SD)

 Spring Summer Autumn 
E (PPFD) 11.89 ± 0.33 12.99 ± 0.44 11.23 ± 0.21 
E (T) 21.07 ± 0.63 21.95 ± 0.37 21.44 ± 0.35 
E (RH) 32.78 ± 0.29 31.01 ± 0.73 31.22 ± 0.47 
Mean ± SD 1.91 ± 0.86 1.98 ± 0.99 1.29 ± 0.12 
 Spring Summer Autumn 
E (PPFD) 11.89 ± 0.33 12.99 ± 0.44 11.23 ± 0.21 
E (T) 21.07 ± 0.63 21.95 ± 0.37 21.44 ± 0.35 
E (RH) 32.78 ± 0.29 31.01 ± 0.73 31.22 ± 0.47 
Mean ± SD 1.91 ± 0.86 1.98 ± 0.99 1.29 ± 0.12 

E is transpiration (mmol m−2 s−1), PPFD is Photosynthetic Photon Flux Density i.e. irradiation (μmol m−2 s−1), T is temperature (°C) and RH is relative air humidity (%).

1PPFD: 44–218 μmol m−2 s−1; 2T: 20 ± 2.5 °C; 3RH: 47.5–62.5%.

Table 3

Transpiration rates of Tufted sedge (Carex elata All.) calculated for maximum seasonal ranges of the studied environmental factors (mean ± SD)

 Spring Summer Autumn 
E (PPFD) 12.69 ± 0.02 14.44 ± 0.05 12.17 ± 0.03 
E (T) 23.16 ± 0.45 24.65 ± 0.13 24.64 ± 0.27 
E (RH) 34.59 ± 0.11 33.32 ± 0.16 33.91 ± 0.04 
Mean ± SD 3.48 ± 0.99 4.14 ± 0.71 3.57 ± 1.27 
 Spring Summer Autumn 
E (PPFD) 12.69 ± 0.02 14.44 ± 0.05 12.17 ± 0.03 
E (T) 23.16 ± 0.45 24.65 ± 0.13 24.64 ± 0.27 
E (RH) 34.59 ± 0.11 33.32 ± 0.16 33.91 ± 0.04 
Mean ± SD 3.48 ± 0.99 4.14 ± 0.71 3.57 ± 1.27 

E is transpiration (mmol m−2 s−1), PPFD is Photosynthetic Photon Flux Density, i.e. irradiation (μmol m−2 s−1), T is temperature (°C) and RH is relative air humidity (%).

1PPFD: 1,044–1,566 μmol m−2 s−1; 2T: 37 ± 2.5 °C; 3RH: 3.2–15.7%.

Table 4

Seasonal daytime water loss via transpiration in the HSSF-CW system

 Spring Summer Autumn 
WLTmin 0.46 0.52 0.17 
WLTmean 0.50 0.97 0.31 
WLTmax 0.83 1.08 0.48 
WLTmeana 0.02 0.04 0.01 
 Spring Summer Autumn 
WLTmin 0.46 0.52 0.17 
WLTmean 0.50 0.97 0.31 
WLTmax 0.83 1.08 0.48 
WLTmeana 0.02 0.04 0.01 

WLT, Water loss via transpiration (m3).

aWLT: Mean water loss via transpiration expressed in m3/m2 (of CW surface area); min: minimum; max: maximum.

During summer, the daytime water loss via transpiration was 0.52–1.08 m3 and under typical climatic conditions water loss was 0.97 m3. According to this value, the water loss can be almost 100% of the daily hydraulic load.

During autumn, the daytime water loss via transpiration was 0.17–0.48 m3 and under typical climatic conditions water loss was 0.31 m3, which is lower than the spring values.

In summary, at extreme daytime weather conditions the water loss caused by transpiration can exceed the rate of hydraulic loading. This conclusion is very important for effluent concentration and emission limit values.

CONCLUSIONS

In spring, the daytime water loss via transpiration was 0.46–0.83 m3. In the CW studied, the current influent wastewater was around 1 m3. Under low irradiance and temperature and high humidity, plants transpire only half of the influent water. On the other hand, under high irradiance and temperature and low humidity, plants can transpire 83% of the hydraulic load. There may be days during spring when the transpiration performance of the plant significantly alters the water balance.

During summer, the daytime water loss via transpiration was 0.52–1.08 m3. Under low environmental irradiance and temperature, and high air humidity, plants can only transpire half of the influent water. Under high irradiance and temperature, and low air humidity, the plants can transpire more than the daily hydraulic load, which can affect effluent concentration to a large degree. If the water balance of an SSF-CW is significantly reduced, it may increase the residence time in the system, which could decrease removal efficiency. Plants can provide the largest contribution to the water balance function in the subsurface flow constructed wetland during an average summer. In spring and autumn this impact is lower, because climatic conditions, including high precipitation, are rarely optimal.

In autumn, daytime water loss via transpiration was 0.17–0.48 m3. Under low irradiation and temperature, and high air humidity, plants can transpire only 17% of the influent water. Under increased levels of light and temperature and decreased air humidity, the plants can transpire only half of the daily hydraulic load.

In summary, similar to results reported in the literature (Chazarenc et al. 2003; Pedescoll et al. 2013), we found that transpiration affected the water balance of the constructed wetlands to a large degree.

In the future, we plan to conduct 24-hour on-site measurements at the same field site, in order to clarify the ratio of evaporation and transpiration as a function of local climatic conditions. From these measurements, we expect to develop an environment-calibrated engineering model to better estimate system-level evapotranspiration processes and mechanisms.

ACKNOWLEDGEMENTS

We would like to thank the water and sewage management research team at the University of Pécs, Faculty of Engineering and Information Technology for their cooperation. This scientific contribution is dedicated to the 650th anniversary of the foundation of the University of Pécs, Hungary. The project has been supported by the European Union, co-financed by the European Social Fund under grant agreement No. EFOP-3.6.1.-16-2016-00004.

REFERENCES

REFERENCES
Albuquerque
A.
,
Arendacz
M.
,
Gajewska
M.
,
Obarska-Pempkowiak
H.
,
Randerson
P. F.
&
Kowalik
P.
2009
Removal of organic matter and nitrogen in an horizontal subsurface flow (HSSF) constructed wetland under transient loads
.
Water Science and Technology
60
,
1677
1682
.
doi:10.2166/wst.2009.548
.
Allen
R. G.
,
Pereira
L. S.
,
Raes
D.
&
Smith
M.
1998
Crop Evapotranspiration Guidelines For Computing Crop Water Requirements
.
FAO Irrigation and Drainage Paper 56
.
United Nations Food and Agriculture Organization
,
Rome
,
Italy
.
Beebe
D. A.
,
Castle
J. W.
,
Molz
F. J.
&
Rodgers
J.
2014
Effects of evapotranspiration on treatment performance in constructed wetlands: experimental studies and modelling
.
Ecological Engineering
71
,
394
400
.
doi:10.1016/j.ecoleng.2014.07.052
.
Białowiec
A.
&
Wojnowska-Baryla
I.
2007
The efficiency of landfill leachate evapotranspiration in soil-plant system with reed Phragmites australis
.
Ecohydrologic Hydrobiologic
7
(
3–4
),
331
337
.
doi.org/10.1016/S1642-3593(07)70116-7
.
Bialowiec
A.
,
Albuquerque
A.
&
Randerson
P. F.
2014
The influence of evapotranspiration on vertical flow subsurface constructed wetland performance
.
Ecological Engineering
67
,
89
94
.
doi: 10.1016/j.ecoleng.2014.03.032
.
Borin
M.
,
Milani
M.
,
Salvato
M.
&
Toscano
A.
2011
Evaluation Phragmites australis (Cav.) Trin. evapotranspiration in Northern and Southern Italy
.
Ecological Engineering
37
(
5
),
721
728
.
doi: 10.1016/j.ecoleng.2010.05.003
.
Busch
J.
&
Lösch
R.
1998
Stomatal behaviour and gas exchange of sedges (Carex spp.) under different soil moisture regimes
.
Physics and Chemistry of the Earth
23
,
443
448
.
doi: 10.1016/S0079-1946(98)00051-2
.
Chazarenc
C.
,
Merlin
G.
&
Yves
G.
2003
Hydrodynamics of horizontal subsurface flow constructed wetlands
.
Ecological Engineering
21
,
165
173
.
doi:10.1016/j.ecoleng.2003.12.001
.
Dean
M.
&
Ashton
P. A.
2008
Leaf surfaces as a taxonomic tool: the case of Carex section Phacocystis (Cyperaceae) in the British Isles
.
Plant Systematics Evolution
273
,
97
105
.
doi: 10.1007/s00606-008-0029-8
.
Freedman
A.
,
Gross
A.
,
Shelef
O.
,
Rachmilevitch
S.
&
Arnon
S.
2014
Salt uptake and evapotranspiration under arid conditions in horizontal subsurface flow constructed wetland planted with halophytes
.
Ecological Engineering
70
,
282
286
.
doi:10.1016/j.ecoleng.2014.06.012
.
Galvão
A.
,
Matos
J.
,
Ferreira
F.
&
Correia
F.
2010
Simulating flows in horizontal subsurface flow constructed wetlands operating in Portugal
.
Ecological Engineering
36
,
596
600
.
doi: 10.1016/j.ecoleng.2009.11.014
.
Headley
T. R.
,
Davison
L.
,
Huett
D. O.
&
Müller
R.
2012
Evapotranspiration from subsurface horizontal flow wetlands planted with Phragmites australis in sub-tropical Australia
.
Water Research
46
(
2
),
345
354
.
doi: 10.1016/j.watres.2011.10.042
.
Jacobs
J. M.
,
Myers
D. A.
,
Anderson
M. C.
&
Diak
G. R.
2002
GOES surface insolation to estimate wetlands evapotranspiration
.
Journal of Hydrology
266
,
53
65
.
doi:10.1016/S0022-1694(02)00117-8
.
Jasechko
S.
,
Sharp
Z. D.
,
Gibson
J. J.
,
Birks
S. J.
,
Yi
Y.
&
Fawcett
P. J.
2013
Terrestrial water fluxes dominated by transpiration
.
Nature
496
(
7445
),
347
350
.
doi: 10.1038/nature11983
.
Kadlec
R. H.
1999
Chemical, physical and biological cycles in treatment wetlands
.
Water Science and Technology
40
,
37
44
.
doi:10.1016/S0273-1223(99)00417-5
.
Kadlec
R. H.
2006
Water temperature and evapotranspiration on surface flow wetlands in hot arid climate
.
Ecological Engineering
26
,
328
340
.
doi:10.1016/j.ecoleng.2005.12.010
.
Kadlec
R. H.
&
Wallace
S. D.
2009
Treatment Wetlands
,
2nd edn
.
Taylor and Francis Group LLC
,
Boca Raton
, pp.
107
113
.
Kadlec
R. H.
,
Knight
R. L.
,
Vymazal
J.
,
Brix
H.
,
Cooper
P.
&
Haberl
R.
2000
Constructed Wetlands for Pollution Control: Processes. Performances. Design and Operation. IWA Specialist Group on Use of Macrophytes in Water Pollution Control
.
IWA Publishing
,
London. UK
.
Konyha
D. K.
,
Shaw
D. T.
&
Weiler
K. W.
1995
Hydrologic design of a wetland: advantages of continuous modelling
.
Ecological Engineering
4
,
99
116
.
doi: 10.1016/0925-8574(93)E0052-R
.
Kumar
R.
,
Jat
M. K.
&
Shankar
V.
2012
Methods to estimate irrigated reference crop evapotranspiration – a review
.
Water Science and Technology
66
(
3
),
525
535
.
doi: 10.2166/wst.2012.191
.
Pedescoll
A.
,
Sidrach-Cardona
R.
,
Sánchez
J. C.
&
Bécares
E.
2013
Evapotranspiration affecting redox conditions in horizontal constructed wetlands under Mediterranean climate: influence of plant species
.
Ecological Engineering
58
,
335
343
.
doi: 10.1016/j.ecoleng.2013.07.007
.
Tanner
C. C.
1995
Accumulation of organic solids in gravel-bed constructed wetlands
.
Water Science and Technology
32
(
3
),
229
239
.
doi: 10.1016/0273-1223(95)00624-9
.
Tuttolomondo
T.
,
Leto
C.
,
La Bella
S.
,
Leone
R.
,
Virga
G.
&
Licata
M.
2016
Water balance and pollutant removal efficiency when considering evapotranspiration in a pilot-scale horizontal subsurface flow constructed wetland in Western Sicily (Italy)
.
Ecological Engineering
87
,
295
304
.
doi: 10.1016/j.ecoleng.2015.11.036
.