Nutrient dynamics in water and soil under conventional rice cultivation in the Vietnamese Mekong Delta

Study area

This study was conducted at a local farmer's field in Long Tuyen district, Can Tho city, Vietnam (9°59’19”N, 105°36’14”E), from 2018 to 2019. The field experiment was located in a lowland soil, which applied triple-cropping rice, an intensive rice production system. According to Dong et al. (2012), the soil area was classified as Thionic Glycesol (International Union of Soil Sciences (IUSS) working group World Reference Base (WRB), 2015). The average weather data was annually recorded from 2015 to 2019 as follows: rainfall, 2,088.4 mm; humidity, 70.0–86.0%; sunshine, 2,467.4–2,695.4 hours (DONRE, 2020). The initial soil physicochemical properties were as follows: bulk density, 0.98 g cm⁻³; soil texture (sand, 1.9%, silt, 31.7%, and clay, 66.4%); soil organic matter (SOM), 35.4 g kg⁻¹.

Experimental design

The size of the field experiment was 200 m² (20 m × 10 m). The field was enclosed by a soil bank with plastic sheet coverage. The plastic sheet was buried 20 cm under the ground’s surface to secure against leaks or intrusion into the nearby fields. We conducted the field experiment in two seasons, including summer–autumn 2018 (wet season) and winter–spring 2019 (dry season). In summer–autumn 2018, the field experiment incorporated rice straw into the soil using a hand tractor. The straw was residue from the previous rice-growing season (spring–summer season 2018). The field witnessed a 10-day fallow period before sowing. In the winter–spring 2019 season, the field underwent a three-month natural flooding season. Before sowing, the field was drained and harrowed by a hand tractor. The rice crop calendar of the two field experiments is shown in Table 1. Table 1 shows the rice farming practices during the wet season 2018 (summer–autumn) and the dry season (winter–spring). The main practices comprise the schedule of soil preparation (ploughing), sowing, irrigation, fertilization, drainage, and harvest.

Rice cultivation and water management

Short-duration rice varieties of OM4900 and OM6976 cultivars for the WS and the DS were used, respectively. The varieties were obtained from Cuu Long Delta Rice Research Institution (CLRRI), Vietnam. The maturity of the two rice varieties varied from 95 to 100 days. The selection of varieties was based on common use and edaphological adaptation in this region. Pre-germinated seeds were sown at 150 kg ha⁻¹ under saturated soil by direct seeding. Water was supplied from a watershed near the field. Water management followed the locally typical water use practices. Water irrigation was started on the seventh day after seeding (DAS), re-irrigated 5–7 cm before fertilizing, always retaining a water level of 1–3 cm during heading and flowering, and openly drained ten days before harvesting. Multiple drainages, which are a simplified form of alternative wetting and drying (AWD) typically conducted in the VMD (Uno et al., 2021), were performed whenever water level naturally decreased 10 cm below the soil surface for the remaining cultivation period.

Fertilizer application

We applied synthetic fertilizers according to locally conventional rice cultivation. In the WS, 129.5 kg N ha⁻¹ and 75 kg P₂O₅ ha⁻¹ were used in total. These topdressings were applied at intervals of 10, 20, and 47 DAS. The fertilizers were applied as follows: 55/42.5/32 kg N ha⁻¹, 25/25/25 kg P₂O₅ ha⁻¹. In the DS, chemical fertilizers were used with a total amount of 90 kg N ha⁻¹, 94 kg P₂O₅ ha⁻¹, and 70.5 kg K₂O ha⁻¹. Fertilization was split into four intervals on days 10, 16, 26, and 47 DAS. The quantity of fertilizer was as follows: 30/15/30/34 kg N ha⁻¹, 30/0/30/34 kg P₂O₅ ha⁻¹, and 22.5/0/22.5/22.5 kg K₂O ha⁻¹. Nitrogen (N), phosphorous (P), and potassium (K) were applied based on the application of urea, superphosphate, and potassium chloride fertilizer. Applied fertilizer quantities for field experiments are shown in the Table 2.

Measurements

Topsoil samples (10 cm) were collected by an auger with a 3.5 cm diameter. In the WS of 2018, we collected a soil sample before sowing to determine the soil's initial physicochemical properties. During the growth period, soil samples were taken on days 9, 13, 19, 27, 39, 53, 65, and 72 DAS. In the dry season of 2019, soil samples were collected on days 7, 14, 21, 29, 44, 52, 61, and 72 DAS. Samples were collected at five cross-sectional sites (four corners and one midpoint) and mixed to a similar weight to achieve a compromised sample. Fresh soil samples were removed of visible biomass, and air-dried and sieved at 2 mm. Soil texture was measured by sieving particle sizes to separate out coarse sand from the finer particles and the silt and clay contents were then determined by measuring the rate of settling of these two separates from the suspension in water according to the Robinson pipette method (Carter and Gregorich, 2008). Bulk density samples were collected by core samplers and the cores were dried in an oven at 110^oC until the weight was constant in accordance with the Core method (Blake and Hartge, 1986). Soil organic matter (SOM) was oxidized by a K₂Cr₂O₇-H₂SO₄ oxidation procedure and titrated using (NH₄)₂Fe(SO₄)₂(H₂O)₆ solution (Walkley and Black, 1934). NH₄⁺ was extracted by KCl 1M (1:10 soil/extract (wt:vol)) and measured according to the indophenol blue colorimetric method (Lu, 2000). Total N (TKN) was digested in the digestion tablets (K₂SO₄, CuSO₄, and Se) and H₂SO₄ solution at 375^oC, then the digest was analyzed for NH₄⁺ by the automated phenate method according to the Kjeldahl method (Bremner, 1996). Total P (TP) was digested in sulphuric acid-hydrogen peroxide-hydrofluoric acid (H₂SO₄-H₂O₂-HF) and detected by the molybdenum blue method (Bowman, 1988).

We also established a similar sampling program among SW, SbW, and soil. Likewise, SW samples were collected at soil sampling points and then mixed to obtain a joint representative sample. For SbW sampling, we installed five PVC pipes (120 cm in length and 9 cm in diameter) around the selected sampling points. The pipe was perforated by 2 mm holes and covered underneath by a lid. The perforated pipes were 15 cm in length. A plastic net of 2 mm was wrapped around the perforated pipe to avoid sediment intrusion. At each selected site, the pipe was anchored under the soil surface at 0.45 m depth. A lid was used to cover the pipe during non-sampling periods. NH₄⁺, NO₃⁻, PO₄³⁻ and TP were analysed according to Standard Methods for the examination of Water and Wastewater (SMEWW) (APHA, 1998): NH₄⁺ was detected by the phenate method (SMEWW 4500-NH₃ F), NO₃⁻ was analysed by the automated hydrazine reduction method (SMEWW 4500-NO₃⁻ G), PO₄³⁻ was determined by the ascorbic acid method (SMEWW 4500-P E), TP was measured by the persulfate method for simultaneous determination of total phosphorus (SMEWW 4500-P J).

Analysis

We assessed the nutrient variation in SW, SbW, and soil between the WS and DS and compared the concentration of water environmental parameters between SW and SbW. The differences between levels of each factor were analysed assuming equal variances (Student’s t-test) at a significant level of P = 0.05 after passing the normality test (Shapiro-Wilk) (P > 0.05). A P-value less than 0.05 was statistically significant, while a P-value greater than 0.05 indicated no effect. Significantly different comparison was considered at ***P < 0.001, **P < 0.01, *P < 0.05 and †P > 0.05. All computations were performed using R stats Version 4.2.0 (R Project for Statistical Computing, RRID:SCR_001905).

N-NH₄⁺, N-NO₃⁻, P-PO₄³⁻ and total phosphorus in the surface water and sub-surface water

Nutrient variations in SW and SbW are shown in Figure 1. The concentrations of N-NH₄⁺, N-NO₃⁻_, P-PO₄³⁻ and TP varied largely in the SW while remained relatively stable in the SbW. In particular, the nutrient values of the SW varied as follows: N-NH₄⁺ (WS, 1.14–4.25 mg L⁻¹; DS, 1.03–4.09 mg L⁻¹), N-NO₃⁻ (WS, 0.46–1.03 mg L⁻¹; DS, 0.27–0.97 mg L⁻¹)_, P-PO₄³⁻ (WS, 0.23–0.96 mg L⁻¹; DS, 0.23–0.81 mg L⁻¹)_, and TP (WS, 1.06–4.89 mg L⁻¹; DS, 0.81–4.24 mg L⁻¹), while the concentration of nutrients in the SbW varied as follows: N-NH₄⁺ (WS, 0.34–0.73 mg L⁻¹; DS, 0.24–0.71 mg L⁻¹), N-NO₃⁻ (WS, 0.22–0.86 mg L⁻¹; DS, 0.23–0.81 mg L⁻¹)_, P-PO₄³⁻ (WS, 0.03–0.08 mg L⁻¹; DS, 0.02–0.07 mg L⁻¹)_, and TP (WS, 0.51–1.19 mg L⁻1; DS, 0.41–1.08 mg L⁻¹). The ratio of N-NH₄⁺/N-NO₃⁻ in the SW was consistently higher than in the SbW. Particularly, the rate of N-NH₄⁺/N-NO₃⁻ in the WS and DS varied by (SW, 1.4–6.9; SbW, 0.57–1.63) and (SW, 1.27–11.7; SbW, 0.72–2.0). It is noted that the concentration of N-NH₄⁺, P-PO₄³⁻ and TP in the SW was consistently higher than that in the SbW (P < 0.05), while the value of N-NO₃⁻ was insignificant between the SW and SbW (P > 0.05). As observed, the highest peaks of these parameters were reached after fertilizing. It is likely that the higher concentration of N-NH₄⁺, P-PO₄³⁻ and TP in the SW were observed during the fertilizing period. NO₃⁻ increased in the SbW during the fertilizing period, while the SW only rose in the WS and was more complex in the DS (Figure 1). Although the temporal-spatial dynamics of the SW and SbW parameters were complex over the rice-growing period, statistical analysis indicates that for N-NH₄⁺, N-NO₃⁻, P-PO₄³⁻ and TP; no significant differences between the WS and DS were seen (Table 3).

Figure 1. The variation of N-NH₄⁺, N-NO₃⁻, P-PO₄³⁻ and total phosphorus in the surface water and sub-surface water during the wet season and dry season rice growing seasons.

Vertical dotted lines indicate the times of the synthetic fertilizer application. F₁, F₂, F₃ and F₄ depict topdressing of fertilizer 1, 2, 3, and 4, respectively.

N-NH₄⁺, total nitrogen, soil organic matter, and total phosphorus in the soil

Figure 2 shows the N-NH₄⁺, TN, SOM, and TP variation in the soil paddy field over the WS and DS. In the WS, the concentration of soil chemical properties varied as follows: N-NH₄⁺ (21.5–38.0 mg kg⁻¹), TN (2.37–2.90 g kg⁻¹), SOM (37.6–48.5 g kg⁻¹), and TP (0.65–1.69 g kg⁻¹), while the DS fluctuated as follows: N-NH₄⁺ (18.4–29.6 mg kg⁻¹), TN (1.53–4.48 g kg⁻¹), SOM (38.7–44.9 g kg⁻¹), and TP (0.35–0.89 g kg⁻¹). The concentration of N-NH₄⁺ increased relatively after fertilizer application in both the WS and DS. Likely, a similar trend was seen in the TN during the DS. However, the effects of synthetic fertilizer topdressing on the TN (in the WS), SOM, and TP were neglectable. Statistically, N-NH₄⁺, TN, and SOM slightly increased in the WS (P > 0.05), while TP significantly increased (P < 0.001) (Table 4).

Figure 2. The variation of N-NH₄⁺, total nitrogen, soil organic matter and total phosphorus in the soil during the rice growing wet season and dry season.

Vertical dotted lines indicate the times of the synthetic fertilizer application. F₁, F₂, F₃ and F₄ depict topdressing of fertilizer 1, 2, 3, and 4, respectively.

TP = total phosphorus; TN = total nitrogen.

Variation of nutrient contents in the SW and SbW

Our study assessed nutrient variability in the SW and SbW through the WS and DS under typical water management and conventional rice practices in the Vietnamese MD. The study found that the concentration of N-NH₄⁺, N-NO₃⁻_, P-PO₄³⁻, and total P in the SW exhibited a relatively large variation in the WS and DS (Figure 1). This could be partly attributed to shifting water levels (rainfall and irrigation) and fertilizer application (Qiao et al., 2012). The alteration of SW levels could likely increase/decrease the denseness of constituents regarding the concentration/dilution in the rice field. In this study, we did not record the water levels as the farmer let water flow free on the paddy field. Thus, the interdependence between water levels and nutrient dynamics remains uncertain. However, fertilizer topdressings could also potentially stimulate the dynamic mineralization processes within the rice paddy field. Here, we found that higher N fertilizer applications (39.5 kg N ha⁻¹) in the WS slightly increased the average N-NH₄⁺ and N-NO₃⁻ concentration by 5.83% and 13.8%. In contrast, higher P fertilizer utilization (15 kg P₂O₅ ha⁻¹) in the DS was indistinguishable in cases of P-PO₄³⁻, and TP (Table 2). Thus, we suggest that an interaction between water levels and fertilizer application rates on the dynamics of N-NH₄⁺, N-NO₃⁻, P-PO₄³⁻, and TP in the Vietnamese MD’s paddy fields should be considered for further work.

Our study showed that the N-NH₄⁺, N-NO₃⁻, P-PO₄³⁻, and TP contents in the SW were consistently higher than that of the SbW simultaneously (P < 0.001), irrespective of factors including fertilizer application rate and seasonal variation (Ngan et al., 2021). This means that nutrient losses could occur through the SW runoff, evaporation (nitrogen gases) and rice plant absorption rather than leaching to SbW. The lower nutrient concentrations in the SbW may also be partly explained by various transformation processes or plant uptake during percolation regression. For instance, the N-NH₄⁺ could be reduced during leachate due to volatilization, nitrification (N-NH₄⁺ to N-NO₃⁻), and rice roots uptake (Hou et al., 2007). Furthermore, P-PO₄³⁻ reduction could also be explained by rice plant uptake, binding onto soil minerals and being more prone to removal through surface runoff (McDowell et al., 2001). In line with our findings, Cho et al. (2011) found that leaching downward subsurface waters were responsible for 6.4–9.8% and 0.2–0.3% of N and P losses, respectively, while N and P losses via surface runoff accounted for 34.3–42.6% and 3.8–5.3%. It has been reported that nutrient loss during the rice-growing period is more relevant to the fertilizer application rate. Cui et al. (2020) confirmed that fertilizer applications significantly impacted N and P losses from surface runoff, with increased fertilizer application rates significantly increasing N loss through surface runoff. Besides, Qiao et al. (2012) showed that N loss via surface runoff and percolation positively correlated with fertilizer application rate. Also, the rate and timing of fertilizer application in the field influenced the N loss over surface runoff (Li et al., 2018). These studies strongly supported our findings.

Our study found that N-NO₃⁻ concentrations showed no significant difference between the SW and SbW, while N-NH₄⁺ in the SbW was consistently lower than in the SW (Ngan et al., 2021). This could be partly explained by rice plants preferring uptake of N-NH₄⁺ rather than N-NO₃⁻, resulting in higher N-NO₃⁻ concentration disclosed in the SbW. Moreover, nitrification progression also occurs very fast in the rhizosphere (Li et al., 2015; Li et al., 2018). In the rice paddy field, N-NH₄⁺ was simulated by both passive and active uptake, while N-NO₃⁻ was solely simulated by a passive uptake (Šimůnek and Hopmans, 2009). This meant that rice uptakes more N-NH₄⁺ than N-NO₃⁻. In line with these findings, Kirk and Kronzucker (2005) depicted that rice could absorb N-NH₄⁺ from 60% to 85%, while 85% of N leaching loss exists in the N-NO₃⁻ form; a higher concentration of N-NO₃⁻ found below the soil surface (mostly in the rhizosphere) resulted in it being quickly transported to the subsoil (Mo’allim et al., 2018). As such, it is evident that N-NO₃⁻ tends to be high in SbW, which is consistent with our findings. However, it is noted that the change between N-NH₄⁺ and N-NO₃⁻ pertains to rainfall, surface runoff, and irrigation (Li et al., 2015). Thus, we propose that the underlying nutrient dynamics in rice paddy fields under different water management regimes and differences of rice farming practices in the lowland soils of the Vietnamese MD should be further studied in future work.

Variation of soil nutrients in rice paddy fields

This study described the soil chemical properties during the rice-growing period under conventional rice practices in the Vietnamese MD. Variability of N-NH₄⁺, TN, SOM, and TP during rice growth was comparable to the previous studies undertaken in the lowland soils of the MD (Minamikawa et al., 2021; Vo et al., 2018; Uno et al., 2021). According to Hung et al. (2016) and Tanaka et al. (2014), soil properties in our study were characterized by medium-high TN, high N-NH₄⁺, low-to-medium SOM, and high-to-very high TP. Thus, with respect to ensuring soil responsiveness to rice nutrient demand, reducing the N and P fertilizer application rate, and increasing SOM to a feasible degree should be considered in conventional rice practices in the Vietnamese MD.

We found that soil N-NH₄⁺ and TN concentration slightly increased after fertilizing. Higher N-fertilizer application (39.5 kg N ha⁻¹) in the WS insignificantly increased the N-NH₄⁺ and TN in the soil in comparison to that of the DS (P > 0.05). However, higher fertilizer application of 15 kg P₂O₅ ha⁻¹ significantly increased TP in the soil paddy field (P < 0.001). It is indicated that the fertilizer application moderately boosted the dynamic of N availability in soil. In agreement with our study, Dong et al. (2012) confirmed that available N slightly increased with chemical fertilizer application but significantly increased with organic matter additions. It is noted that the significant difference in TP could be likely due to the excessive P fertilizer application rates in the WS, while utilization efficacy and loss of P are usually low (Irfan et al., 2020; Schröder et al., 2011; Cho et al., 2011).

SOM plays an inevitable role in promoting nutrient availability and improving soil fertility. Our study found that SOM change was minor during rice growth. This could be partly explained by no organic matter sources being incorporated into the soil. Thus, organic matter ineffectively contributed to nutrient availability in the soil. In the soil, the change of SOM depends on temperature, pH, microbial growth, soil management, organic matter amendment, and C/N ratio (Tanaka et al., 2014).

Underlying data

Figshare: Underlying data for ‘Nutrient dynamics in water and soil under conventional rice cultivation in the Vietnamese Mekong Delta’. ‘Paddy field in the Vietnamese Mekong Delta 2021’, https://doi.org/10.6084/m9.figshare.16499508.v1 (Ngan et al., 2021).

This project contains the following underlying data:

Data are available under the terms of the Creative Commons Zero “No rights reserved” data waiver (CC0 1.0 Public domain dedication).