Hybrid - 2YOU501 and 2YOU725 (China)

Experimental treatment and design

Table 1 summarizes some key characteristics of each experiment. More details of the experiments are presented by Belder et al (2004, 2005) and Cabangon et al (2001) for Tuanlin.

Table 1. Experimental details of the field experiments. GD is the growth duration from transplanting to physiological maturity. E-Date is the emergence date and T-date is the transplanting date. CS is continuously submerged; SNS is alternately submerged-nonsubmerged; RF is partially rainfed; FI is flush irrigation; FI-30 is flush irrigation with a threshold in soil water tension of 30 kPa; and FI-50 is flush irrigation with a threshold in soil water tension of 50 kPa.

 At Tuanlin, experiments were done during summer seasons on a silty clay loam of the experiment station of the Zhanghe Irrigation System. Two hybrid cultivars were used: 2You501 in 1999 and 2You725 in 2000-02. The experiments were laid out in a split-plot design with four replicates, with water regimes in the main plot and N levels in the subplot.  The water regimes were continuously submerged (CS), alternately submerged-nonsubmerged (SNS), rainfed (RF), and flush irrigation (FI). The N treatments were 0 and 180 kg N ha–1 (locally recommended to obtain no N-limited yields). The 180 kg N was applied as 30% as basal, 30% at 10 days after transplanting (DAT), 30% at panicle initiation, and 10% at flowering.

 The CS, SNS, and RF plots were puddled, whereas the FI plots were dry-plowed and harrowed. In SNS plots, the periods without submergence usually lasted 4–5 days, depending on rainfall conditions, with a special “mid-season drainage” period of 7–12 days just before panicle initiation. The RF plots were kept submerged during the first 2 weeks after transplanting and were irrigated only when fertilizer N was applied. FI plots were irrigated when the soil water tension surpassed 30 and 50 kPa, except in 2001, when no tensiometers were installed. In that year, irrigation application was based on the occurrence of cracks in the soil.

In 2001, plastic sheets were installed in the bunds between plots with different water regimes to 0.3 m deep to prevent seepage flows. In 2002, a deep drain of 1.0-m depth was excavated around the main plots to increase internal drainage and lower the groundwater table.

 The amount of irrigation water applied was monitored in each irrigation from transplanting till maturity by using flow meters (installed in the flexible hoses used for irrigation). In FI plots, gauged tensiometers were installed at 15–20-cm depth except in 2001 and readings were recorded daily. In all except the FI plots, field-water levels were measured daily using 30-cm-high perforated PVC pipes installed in each plot.

The groundwater table depth was determined only in 2001 and 2002 in bunds separating replicates using 5-cm-diameter PVC pipes.

Cultural practice

For all treatments, 20–24-day-old seedlings from wet-bed nurseries were transplanted at 3 seedlings per hill at a spacing of 25 X 10 cm.

Data collection

Daily weather data, including rainfall, maximum and minimum air temperature, sunshine hours, wind speed, and relative humidity, were measured at on-site meteorological stations.

Crop samples were taken at key growth stages (transplanting, mid-tillering, panicle initiation, flowering, mid-grain filling, and physiological maturity) to determine total crop biomass and leaf area index. In total, plant samples from 12 hills were used, representing 0.50 m2. Biomass was determined after oven-drying at 70°C to constant weight. LAI was determined using a Licor LI 3100 area meter. At maturity, yield was determined from one central 4.8-m2 area, and expressed at 14% moisture content. Soil water retention characteristics were determined in several soil layers.

Simulation design and parameterization

ORYZA2000 was parameterized for the rice cultivars used in our experiments, starting with the standard crop parameters for cultivar IR72. The development rates, specific leaf area, and partitioning table were derived from our experimental data. Leaf stress parameters were parameterized by Wopereis et al (1996a), so the values of minimum and maximum soil water tension allowed nonlimited and complete inhibition of leaf expansion. For each experiment in submerged conditions (CS, SNS), the average percolation rate was first estimated from a water balance calculation and from daily measurements of field-water level, and then fine-tuned by model fitting (fine-tuning the parameter value until simulated field-water levels agreed best with measured field-water levels). For nonsubmerged conditions, the Van Genuchten equations were used to describe soil water retention and conductivity characteristics in the PADDY water balance model. The Van Genuchten parameters were calculated with the pedotransfer functions developed by Wösten et al (2001), using the measured soil texture and soil organic matter content data at the sites (Table 2). The value for the saturated conductivity (Ksat) of the least permeable layer (plow pan) was further fine-tuned by matching simulated and measured field-water levels and soil water tensions. The indigenous soil N supply was first estimated from crop N uptake in zero-N treatments, and subsequently fine-tuned by model fitting.

 For each experimental year, the daily groundwater depth and weather data were directly taken from the measurements. For 1999 and 2000, a fixed groundwater table depth of 40 cm was assumed based on groundwater observations in the other years, although recorded field-water levels indicated perched water tables of less than 15 cm during a large part of the growing season.

 The same numbers of simulations as field experiments were designed to validate the performance of ORYZA2000 on simulating soil water tension, field-water level, LAI, biomass, and yield.

 Table 2. Soil water retention characteristics, saturated hydraulic conductivity, and parameterized Van Genuchten parameters per soil layer at Tuanlin.

Model evaluation

Following the methodology introduced in Section 2.5, the performance of ORYZA2000 in simulating soil water tension, field-water level, LAI, biomass, and yield was evaluated.

Parameter values

The parameterized soil hydraulic properties are given in Table 3. The average percolation rate of the soil varied between 1.6 and 15.1 mm d-1. The highest values were found in 2002, when the deep drain promoted rapid downward water movement through the soil. All percolation rates of individual replicates were within the 0–26 mm d-1 range of values reported in the literature for puddled rice fields (Wickham and Singh 1978, Tabbal et al 2002). For 1999 and 2000, the percolation rates of SNS fields (only during periods of ponded water when continuous percolation occurred) were about twice as high as those of the CS fields.

The value of Ksat of the plow pan varied between 0.4 and 50 mm d-1, and was well in the range of values presented by Wopereis et al (1996b). High percolation rates were matched by high values of Ksat.

Table 3. Calibrated parameter values in ORYZA2000: percolation rate and saturated hydraulic conductivity of the most impermeable layer.

Soil water tension

The simulated and observed values of soil water tension are given in Figure 1 for the FI treatment in 2002. The graph shows a good agreement between simulated and observed values. The agreement between simulated and observed soil water tension was a little weak: the R2 was lower, the slope was not close to 1, and the intercept deviated from 0. The RMSEn of soil water tension was even 77% (Table 4).

Fig. 1. Simulated and observed soil water tension at 15-cm depth in time for the FI regime in 2002.

Field water level

A comparison between the course of simulated and measured field-water levels is presented in Figure 2 for CS and SNS in 2000. Especially, CS regimes showed a good match in all seasons. For SNS, small deviations occurred, especially at moments of re-irrigation after a period of nonsubmergence. Given the daily percolation rates of 2–15 mm, the RMSE for field-water level of 9–17 mm showed good simulation results over a range of observed field-water levels of 0 to 125 mm. The agreement between simulated and observed field-water depth was also weak like that for soil water tension: the R2 was lower, the slope was not close to 1, and the intercept deviated from 0. However, the RMSEn of field-water level was low (less than 43%, Table 4).

Fig. 2. Simulated and observed field-water levels in time for (A) the CS regime at Tuanlin in 2000 and (B) the SNS regime in 2000.

LAI

The simulated LAI deviated relatively more from observed values than did total biomass. This was due to an overestimation of LAI in the control treatment. For LAI, and values deviated more from 1 and 0, respectively, R2 was only 0.80, and RMSEn was relatively high at 45% (Tables 4 and 5).

Biomass

In Figure 3, simulated versus measured biomass data are presented for all experiments and treatments combined with a 1:1 line.  The RMSEn for biomass was higher than the measured CV, whereas the coefficient of determination was high (R2  0.96) (Tables 4 and 5).

Yields

Tables 4 and 5 present the goodness-of-fit parameters between simulated and measured crop grain yield. Simulated grain yield was not significantly different from observed values with Student’s t-test, and R2values of the linear regression between observed and simulated values were at least 0.71; RMSEn was only 13%.

Fig. 3. Evaluation of simulated and observed biomass with a 1:1 line for all experiments at Tuanlin, China.

Table 4. Results of statistical comparison between observed and simulated biomass, leaf area index, grain yield, field-water level, and soil water potential.

Table 5. Standard deviation (same unit as variable) and coefficient of variation (CV, %) of crop variables.

References

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Belder P, Spiertz JHJ, Bouman BAM, Lu G, Tuong TP. 2005. Nitrogen economy and water productivity of lowland rice under water-saving irrigation. Field Crops Res. 93:169-185.

Cabangon RJ, Castillo EG, Bao LX, Lu G, Wang G, Cui Y, Tuong TP, Bouman BAM, Li YH, Chen C, Wang J. 2001. Impact of alternate wetting and drying irrigation on rice growth and resource-use efficiency. In: Barker R, Loeve R, Li Y, Tuong TP, editors. Water-saving irrigation for rice. Proceedings of an International Workshop. 23-25 March 2001, Wuhan, China. p 55-79.

Tabbal DF, Bouman BAM, Bhuiyan SI, Sibayan EB, Sattar MA. 2002. On-farm strategies for reducing water input in irrigated rice: case studies in the Philippines. Agric. Water Manage. 56:93-112.

Wopereis MCS, Kropff MJ, Maligaya AR, Tuong TP. 1996a. Drought-stress responses of two lowland rice cultivars to soil water status. Field Crops Res. 46:21-39.

Wopereis MCS, Bouman BAM, Tuong TP, ten Berge HFM, Kropff MJ. 1996b. ORYZA_W: rice growth model for irrigated and rainfed environments. SARP Research Proceedings, IRRI/ABDLO, Wageningen, Netherlands. 159 p. 

Wösten JHM, Veerman GJ, de Groot WJM, Stolte J. 2001. Waterretentie- en doorlatendheidskarakteristieken van boven- en ondergronden in Nederland: de Staringreeks. (Water retention and conductivity characteristics of top and subsoils in The Netherlands: the Staring series). Alterra rapport 153, Wageningen Universityand Research Center. 31 p.

Wickham TH, Singh VP. 1978. Water movement through wet soils. In: Soils and rice. Los Baños (Philippines): International Rice Research Institute. p 337-358.