Abstract

The need to cultivate effluent-irrigated rice is paramount and synonymous with treated wastewater reuse, recycling and water resources management. A trial in a peri-urban set-up with a low-cost decentralized wastewater treatment system (DEWATS) was carried out in the 2017 and 2018 cropping seasons to assess the effect of irrigation water reuse management techniques on the yield and water productivity of rice. It was hypothesized that anaerobic baffled reactor (ABR) irrigation water management does not have an effect on the yield of peri-urban grown rice. The impacts of irrigation water management techniques were very significant (P < 0.001) on the number of irrigation events, amount of irrigation and daily water balance. The impact was not significant (P > 0.05) on the tiller numbers per plant; it was however significant (P < 0.05) on the panicle numbers per plant. The effects were not significant (P > 0.05) on the plant height but significant (P < 0.05) on the yield rice for both trials. The effect was also significant (P < 0.05) on water productivity. The result proved that the hypothesis be rejected. It could be concluded that significant potential exists for applying wastewater reuse for non-drinking applications such as irrigation.

INTRODUCTION

Several communities in the Republic of South Africa struggle to get dependable and sufficient quantities of fresh water for various water requirements, hence, interest is increasing in the reuse of wastewater for non-drinking water requirements such as irrigation (Adewumi et al. 2010). The push to use less water in agriculture is because of increasing demand generated by the growing population. It is imperative to improve irrigation efficiency and access alternative sources such as water reuse in order to guarantee sustainable agriculture that will feed the increasing populace (Ram et al. 2016). One of the low-cost hygiene technologies which has been effectively used in developing countries is the decentralized wastewater treatment system (DEWATS) that includes an anaerobic baffled reactor (ABR) (Adhanom et al. 2018). Irrigating crops with effluent is important for water reuse and recycling nutrients and is better than direct discharge into rivers (Musazura et al. 2018). Irrigation with treated sewage effluents constitutes an environmentally sound way of disposing effluents into the environment (de Carvalho et al. 2012). When using domestic treated effluents, heavy metals are of less concern for irrigation because they are basically and effectively removed during common treatment processes. The majority of concentrations in raw sewage end up in the sludge settlement partition (Toze 2006). There is no significant effect of treated wastewater on some soil properties (Bedbabis et al. 2014). Musazura et al. (2015) also confirmed no significant changes of soil physico-chemical properties over three consecutive seasons after irrigation with ABR effluent. Irrigation water management techniques include alternate wetting and drying (AWD) (Bouman et al. 2007). According to Ruíz-Sánchez et al. (2011), well-watered soil conditions with 100% holding capacity are another techniques of irrigation water management. This situation is termed ‘wetting without flooding’ (WWF). Continuous flood irrigation (CFI) ensures ponded/flooded fields at any time (anaerobic conditions). Rice (Oriza stiva L.) is a main staple food for the majority of the world's populace. South Africa has one of the highest per capita rice consumptions at 14 kg/year (Africa Rice Center 2007). Basically, the international market is the source of rice in South Africa (Africa Rice Center 2007). This study therefore aimed at evaluating the performance, in terms of growth, yield and water productivity, of lowland rice grown under different irrigation water management techniques with treated wastewater reuse and recycling (ABR effluent) in a peri-urban environment. It was hypothesized that irrigation water management techniques do not have an effect on the yield of rice grown with treated wastewater reuse.

METHODS

Description of study site

The study area is situated at the eThekwini Agricultural hub research facility, Newlands East, Durban, South Africa, where the ABR effluent plant is located. The site is at 29° 46′ 26′′ S and 30° 58′ 25′′ E and characterized by 1,000 mm average annual rainfall and an average daily temperature of 20.5 °C. The site description is displayed in Figure 1. Eighty-three (83) households were contributing domestic wastewater to the DEWATS. The ABR effluent generated from the DEWATS was allowed to pass through another filter compartment called the anaerobic filter (AF). The continuous effluent was stored in a storage tank from which it was piped to the tunnel. The 30 m (L) × 8 m (W) × 4 m (H) tunnel (Figure 1) was meant to serve as a means of achieving zero effective rainfall in trials.

Figure 1

General overview of the research site showing tunnel house.

Figure 1

General overview of the research site showing tunnel house.

Trial design and layout

The pot trials were conducted from September 2017 to February 2018 for the first trial (Season 1) and January 2018 to June 2018 for trial 2 (Season 2). The trial was laid out in a randomized complete block design (RCBD) with three irrigation water management regime treatments and three replications each in both years. The three treatments were alternate wetting and drying (AWD), wetting without flooding (WWF) and conventional flooding irrigation (CFI). The controls for both seasons were CFI treatments. The pots were randomized periodically in the tunnel and blocked with respect to direction of sunlight. The pots used were 20-litre capacity plastic pots, each filled with 24.8 kg of clayey-loam soil from the adjacent field. Each of the pots served as an experimental unit (EU). A PVC observation tube 400 mm long, 50 mm diameter and perforated with the aid of a 5 mm drilling bit at intervals of 40 mm was embedded in each pot. Half of the tube length (200 mm) was inserted into the pot to observe the water table and dictate when to irrigate (Bouman et al. 2007; Ye et al. 2013; Lampayan et al. 2015). The water level in the tube was measured with the aid of a measuring tape.

Crop management

FARO 44 lowland adaptation rice species was used for the trials. It has an average yield ranging between 4.5 and 6.5 t/ha according to the specification from the supplier. Seedlings were washed and soaked in salty water for a day. They were then incubated at 30 °C for 24 hours in order to stimulate germination, according to Mulbah (2010). Seedlings were raised in a seedbed with sowing dates of September 21st in 2017 (Season 1) and January 19th in 2018 (Season 2). Transplanting was done on October 8, 2017 (Season 1) and February 4, 2018 (Season 2) at a hill spacing of 35.5 cm × 35.5 cm inter and intra plant spacing, respectively. Thinning was done between ages 7 to 14 days after planting in order to replace dead seedlings. Periodic weeding was done and no additional fertilizer was added. There were no plant diseases identified during the trials, hence, no insecticides were applied. Consideration was given to rice for irrigation with domestic ABR effluent since rice requires a lot of water and nutrients. Rice also needs to be cooked before eating, since that minimizes health hazards for consumers.

Water application

The pot trials were irrigated by the flood method with a 70 mm freeboard to control run-off. There were networks of PVC pipes and ball gates and a water tap at each pot. Splash erosion was prevented by placing a small bowl-shaped container at the point of discharge. The pots were lined with double-plastic black bags (25 μm) to keep water from seeping out of drainage holes at the bottom of the pots. The depth of irrigation was maintained at 50 mm for all CFI replications. AWD treatments adopted an irrigation depth of 50 mm as soon as the level of water in the tube dropped to 150 mm beneath the surface (Lampayan et al. 2015). The level of irrigation water inside the tube was the same as the level in the pots (WWF treatments). How much and when to irrigate were dictated by manual observation of an improvised light-weight foam (polystyrene).

Reference evapotranspiration (ETo in mm/day) according to the FAO Penman–Monteith equation was collected from an installed Campbell scientific automated weather station (AWS), installed 30 m away from the tunnel house. The actual crop evapotranspiration, ETc, was then calculated as a product of ETo and coefficient of crop factor, Kc. Kc for rice is 1.15 for the initial stage of 30 days, 1.23 for the second 30 days of development stage, 1.14 for the next mid stage of 60 days and 1.02 for the late stage of 30 days for a 150-day rice variety (Tyagi et al. 2000).

Pot experiment water balance, saving and productivity

The water balance was calculated according to Busari et al. (2019). The effect of the tunnel set-up (zero effective rainfall) and pots as medium for planting rice changed the equation to Equation (1): 
formula
(1)
where
  • = changes in soil water storage (mm) over time, t (days),

  • = applied irrigation water over time (mm),

  • = evapotranspiration over time (mm).

According to Yao et al. (2012) water productivity was defined as the yield per unit of total water input (irrigation and precipitation), and was calculated as in Equation (2): 
formula
(2)
where
  • Y = the actual harvestable yield (kg/ha),

  • TWU = the total seasonal water use (m3).

With reference to the conventional way of irrigating rice (the control treatment in this study), water saving was determined and calculated as in Equations (3) and (4): 
formula
 
formula
where
  • WSAWD = water saving for AWD,

  • WSWWF = water saving for WWF,

  • AWD(t) = total water applied in treatment AWD (mm),

  • CFI(t) = total water applied in treatment CFI (mm),

  • WWF(t) = total water applied in treatment WWF (mm).

Data collection and analysis

Data were collected weekly in all replications for all treatments on the growth parameters. Plant height was measured from the base to the shoot apex of the plant. The panicle and tiller numbers in each plant were obtained by direct counting. The LAI-2200C (LI-COR Environmental) Plant Canopy Analyzer was used to measure leaf area index (LAI). Yield components such as weight of 1,000 filled grains, number of filled grains per panicle and grain yield were measured. Three samples of harvested grains were randomly taken from each replicate and initial weights were recorded, and the final weights were also recorded after oven drying at 70 °C for 72 h; thereafter the grain yield was adjusted to 16% seed moisture content. Three samples of 1,000 grains were randomly selected from the harvested grains in each replicate for 1,000-grain weight determination. Data were subjected to analysis of variance (ANOVA) for a randomized complete block design using GenStat 18th edition (2016) and the Duncan multiple range test at 5% was used to determine differences between treatment means.

RESULTS AND DISCUSSION

Characterization of ABR effluent

The ABR effluent does not meet the minimum standards for the disposal of wastewater into the environment and water bodies in terms of the chemical oxygen demand (COD) (<400 mg/l), total N (5–30 mg/l), EC (0–3 dS/m) and the total coliforms. It does however meet the minimum standard such as in total suspended solids (TSS), pH. The chemical oxygen demand test procedure is based on the chemical decomposition of organic and inorganic contaminants, dissolved or suspended in water. This can indicate the ability of water to deplete oxygen and reduce other compounds such as nitrates. The ABR is capable of reducing COD by 86% (Foxon et al. 2004). Average pH in the ABR was 7.27 and this allows the activity of bacteria to act on the degradation of the organic waste. The minimum pH requirement for irrigation water is 6.5–8.4 (Bame et al. 2014). The pH in irrigation water is important as it affects the availability of nutrients, irrigation pipe corrosion and quality of crops, especially in sensitive species (Bame et al. 2014). TSS within a water sample is an indication of water that has been reduced in quality. It can be plant debris or soil particles. ABR can reduce about 50% of total solids in the first compartment of DEWATS, called the sedimentation chamber. TSS can affect soil physical properties, clogging and salinity problems and less than 100 mg/l is recommended.

Water application

The impacts of irrigation management techniques were very significant (P < 0.001) on the amount of irrigation, numbers of irrigation events and daily water balance for both 2017 and 2018 seasons, as shown in Table 1. Further analysis for both seasons showed that the means of each treatment were significantly different from one another in the amount of irrigation water and daily water balance. However, the difference between the means of AWD and CFI were not significant in the number of irrigations for both seasons (Table 1). The highest and lowest values in all the variables measured for both seasons were for CFI and AWD treatments, respectively. The amount of irrigation water applied for all the treatments was higher in the 2018 season than in the 2017 season. Water saved from AWD treatments was of the order of 27% and 22% for the 2017 and 2018 seasons, respectively, as compared with CFI without any significant yield penalty. The WWF treatments also saved water but this was accompanied by significant yield reduction.

Table 1

Treatments effects on number of irrigation events, amount and water balance

Treatments Number of irrigation events
 
Amount of irrigation (mm)
 
Water balance (mm/day)
 
2017 2018 2017 2018 2017 2018 
AWD 11.00a 12.00a 498.70a 548.00a 15.52a 15.34a 
CFI 28.00b 31.00b 680.00c 701.00b 21.91c 20.87c 
WWF 27.00b 30.00b 642.70b 660.30b 18.87b 18.04b 
p *** *** *** *** *** *** 
Treatments Number of irrigation events
 
Amount of irrigation (mm)
 
Water balance (mm/day)
 
2017 2018 2017 2018 2017 2018 
AWD 11.00a 12.00a 498.70a 548.00a 15.52a 15.34a 
CFI 28.00b 31.00b 680.00c 701.00b 21.91c 20.87c 
WWF 27.00b 30.00b 642.70b 660.30b 18.87b 18.04b 
p *** *** *** *** *** *** 

Note: Means with the same letters within a column in each season do not differ significantly at 5% level of probability; p= probability, *** = significant at 0.001 probability level.

Several studies have also reported water savings between intermittent flooding and drying as compared with continuous flooding. Bouman et al. (2007) reported savings of 200–900 mm, Yao et al. (2012) reported water savings of between 24% and 38%, 16% water saving was reported by Tan et al. (2013) and Pascual & Wang (2016) noted 50% to 72% savings. These savings were as a result of alternating flooding and drying of the rice field. The daily water balance showed that the amount of irrigation applied was higher than the crop evapotranspiration. The difference between irrigation applied in 2017 and 2018 was as a result of seasonal difference.

Growth parameters

The treatment effects (Table 2) did not affect the plant height significantly in 2017 (P = 0.24) and 2018 (P = 0.15). The plant heights for all the treatments were higher in 2018 than in 2017. The finding agreed with the study of Fonteh et al. (2013), who discovered that reduced depth of flooding and drying improves the emergence of weeds significantly, which eventually reduces the height of the rice plants. AWD treatments have the lowest plant height during both seasons. The effect of treatments was also not significant (P = 0.40) on the LAI in 2017 but was significant (P = 0.02) in 2018. This was deduced from the statistical analysis results in Table 2. The difference in LAI with reference to the three irrigation management techniques occurred at ages 14 and 8 weeks for the 2017 and 2018 seasons respectively. These weeks corresponded with the weeks of panicle initiation, respectively, for both seasons. This could be attributed to plant canopies and the atmosphere. Seasonal difference (2017 winter and 2018 summer) could also add to the effect. This translated to the consumption of more nutrient-rich effluent for irrigation in 2018 than 2017. The LAI was higher in AWD treatments than in CFI in both potted seasons and this was consistent with the study of Pascual & Wang (2016), who discovered that LAI under alternating irrigation is higher than under inundated conditions. The effect of treatments on the number of panicles per plant was significant (P = 0.004) in 2017 and (P = 0.02) in 2018. Panicle initiation commenced late (13 weeks after transplanting) in the 2017 winter season while early (8 weeks after transplanting) in the 2018 summer season. The initiations commenced first in AWD treatments in both seasons. The average panicle numbers per plant were higher in the 2018 than the 2017 potted season. The maximum number of tillers produced per plant was observed in AWD treatments in both seasons. However, the effects of treatment had no significant difference (P = 0.32 for 2017 and P = 0.09 for 2018) on the number of tillers per plant. The flood and dry cycles experienced under AWD improve air exchange between the soil and the atmosphere and may have contributed to more tiller and panicle numbers.

Table 2

Effects of treatment on growth parameters (height, LAI, panicle and tiller numbers)

Treatments Height (cm)
 
Leaf area index (LAI)
 
Number of panicles per plant
 
Number of tillers per plant
 
2017 2018 2017 2018 2017 2018 2017 2018 
AWD 70.17a 92.62a 1.40a 2.60b 22.79b 31.92b 36.12a 44.67a 
CFI 80.91a 102.22a 1.17a 1.91a 18.38a 27.22a,b 34.97a 43.09a 
WWF 75.10a 97.84a 1.35a 2.49b 15.75a 24.75a 29.92a 35.53a 
p ns ns ns ** * ns ns 
Treatments Height (cm)
 
Leaf area index (LAI)
 
Number of panicles per plant
 
Number of tillers per plant
 
2017 2018 2017 2018 2017 2018 2017 2018 
AWD 70.17a 92.62a 1.40a 2.60b 22.79b 31.92b 36.12a 44.67a 
CFI 80.91a 102.22a 1.17a 1.91a 18.38a 27.22a,b 34.97a 43.09a 
WWF 75.10a 97.84a 1.35a 2.49b 15.75a 24.75a 29.92a 35.53a 
p ns ns ns ** * ns ns 

Note: Means with the same letters within a column in a season do not differ significantly at 5% level of probability; p= probability, ns = not significant, * = significant at 0.05 probability level, ** = significant at 0.01 probability level.

Yield components

The effect was significant (P = 0.009 and 0.003) on the number of filled grains per m2 for both seasons (Table 3). The result showed that the means of CFI and AWD treatments were not different significantly from each other but significantly different from WWF. The effect of the treatments in potted rice was significant (P = 0.02) in 2017 and (P = 0.03) in 2018 on the number of filled grains per panicle. The effect was also significant (P = 0.002) in 2017 and (P = 0.001) in 2018 on the number of panicles per m2. The treatments, however, did not have significant effect (P = 0.65) in 2017 and (P = 0.57) in 2018 on the weight of 1,000 filled grains. The same trend was observed for both seasons.

Table 3

Effects of treatments on yield components, yield and water productivity of rice

 Treatments Number of filled grains per m2 Number of filled grains per panicle Number of panicles per m2 Weight of 1,000 filled grains (g) Grain yield (t/ha) Water productivity (kg/m3
2017 AWD 10,295b 48.00a 214.30c 22.55a 2.32b 0.47c 
 CFI 9,794b 55.67b 175.60b 23.32a 2.28b 0.34b 
 WWF 5,399a 41.67a 129.30a 24.25a 1.30a 0.20a 
 p ** ** ** ns ** ** 
2018 AWD 13,665b 62.67b 218.30b 23.54a 3.21b 0.59c 
 CFI 13,026b 63.67b 204.30b 24.78a 3.22b 0.46b 
 WWF 6,683a 49.67a 134.30a 24.84a 1.65a 0.25a 
 p ** * *** ns ** *** 
 Treatments Number of filled grains per m2 Number of filled grains per panicle Number of panicles per m2 Weight of 1,000 filled grains (g) Grain yield (t/ha) Water productivity (kg/m3
2017 AWD 10,295b 48.00a 214.30c 22.55a 2.32b 0.47c 
 CFI 9,794b 55.67b 175.60b 23.32a 2.28b 0.34b 
 WWF 5,399a 41.67a 129.30a 24.25a 1.30a 0.20a 
 p ** ** ** ns ** ** 
2018 AWD 13,665b 62.67b 218.30b 23.54a 3.21b 0.59c 
 CFI 13,026b 63.67b 204.30b 24.78a 3.22b 0.46b 
 WWF 6,683a 49.67a 134.30a 24.84a 1.65a 0.25a 
 p ** * *** ns ** *** 

Note: Means with the same letters within a column do not differ significantly at 5% level of probability; ns (not significant), * = significant at 0.05 probability level, ** = significant at 0.01 probability level, *** = significant at 0.001 probability level.

Grain yield and water productivity

The treatment effects (Table 3) were significant (P = 0.009) in the 2017 and (P = 0.002) in the 2018 seasons. Multiple comparison analysis revealed that CFI and AWD were not different significantly from each other but significantly different from the means of WWF in both seasons. Rice cultivated with AWD irrigation techniques showed higher yield than conventional flood irrigation (Yang & Zhang 2010; Zhang et al. 2010). The difference in yield obtained could be as a result of the higher amount of nutrient-rich effluent applied in 2018. The pond and alternate dry rotations practiced under AWD irrigation boosted the exchange of air between the soil and the atmosphere; sufficient oxygen is supplied to the root system to speed up soil organic matter, and that may be responsible for the higher numbers of tillers and panicles, LAI and ultimately grain yield experienced in this study. This was consistent with the results of Ye et al. (2013). The result of yield components such as number of filled grains per panicle and 1,000 grain weight agreed with the work of Pascual & Wang (2016) and Zhang et al. (2010). The grain yields obtained in both seasons were very low when compared with the yields obtained by other researchers (Oliver et al. 2008; Yang & Zhang 2010; Fonteh et al. 2013; Pascual & Wang 2016). This was largely attributed to the use of pots. The yield obtained also was justified with water productivity.

The effects of treatment on water productivity was significant (P = 0.005) in the 2017 and (P < 0.001) in the 2018 season. Water productivity is one of the most important justifications for AWD irrigation techniques. Each of the irrigation treatments was significantly different from the others. The features of water productivity came out clearly in the study with the highest water productivity in AWD treatments for both the 2017 and 2018 seasons as compared with CFI treatments. This concurred with the findings of Ye et al. (2013).

CONCLUSIONS

The effects of irrigation water management techniques on the growth and yield of rice crops using treated wastewater reuse and recycling have been shown in this study. The number of irrigation events and amounts were higher in WWF and CFI as compared with AWD treatments. AWD treatments saved water compared with CFI treatments. The yields obtained from CFI and AWD treatments in both seasons were not different from each other significantly. The yields obtained were as a result of ABR effluent, free of any additional inorganic fertilizer. The outcome of this study concluded that a submerged rice field is not necessarily the only answer to achieving optimum rice production. Rice can also be grown in a combination of anaerobic and aerobic conditions within a peri-urban environment where there is availability of treated wastewater for reuse. The AWD irrigation technique proved to be the most appropriate irrigation technology because of its highest water productivity in both seasons without significant yield loss penalty. The hypothesis was rejected. Finally, peri-urban farmers should be encouraged to contribute to treated wastewater reuse and recycling, especially on rice.

ACKNOWLEDGEMENTS

The study was funded by the University of KwaZulu-Natal and eThekwini Water and Sanitation (EWS), Durban, South Africa.

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