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Validation of Aquacrop Model Under Awd Water Management and Effect of Usg in Rice Production -2014

Dr. Md. Maniruzzaman
PSO
Irrigation and Water Management Division, BRRI, Gazipur-1701, Bangladesh.

Dr. Md. Mahbubul Alam
SSO
Irrigation and Water Management Division, BRRI, Gazipur-1701, Bangladesh.

Priya Lal Chandra Paul
SSO
Irrigation and Water Management Division, BRRI, Gazipur-1701, Bangladesh.

Abstract/ Executive Summary:

A field experiment was conducted to determine crop yield and water requirement under AWD method, to determine the effect of USG under AWD method, to validate yield and water requirement with AquaCrop model and to estimate the probabilistic yield under AWD method for similar climatic condition. Water Treatments were: I₁= continuous standing water, I₂= Irrigation when water level reached 15 cm below soil surface and I₃= Irrigation when water level reached 20 cm below soil surface and nitrogen treatments were: N₀= No nitrogen, N₁= Pilled urea applied @220 kg ha^-1 and N₂= USG applied @70 gm between four rows.The field experiment was conducted at BRRI farm, Gazipur, during the dry season of 2013-14. The AquaCrop model was calibrated using experimental data of dry season (Boro) rice during 2013-14 for BRRI dhan28 in transplanted conditions to predict canopy cover (CC), biomass and crop grain yield under three irrigation water regimes. Based on indicators of evaluation for CC and biomass and the required irrigation amounts, the AWD-15 irrigation regime appears to be the best water-saving option for rice production during the dry season in Bangladesh. It is noted, however, that the often extremely good correlation metrics presented in the study are somewhat influenced/assisted by the small number of observation points available over the season for which the comparison of observed and simulated values could be compared. Regardless, the obtained season-end metrics in terms of simulated biomass and crop yield are suggesting high potential for the AquaCrop model to be reliably used in e.g. irrigation scheduling, yield prediction or potentially in climate related scenario studies in Bangladesh. After validation of the model the probabilistic yield will be estimated under AWD method for similar climatic condition.

Keywords: Aqua crop model, AWD, Irrigation scheduling

Location: BRRI farm, Gazipur

Start Date: 00-00-2013

End Date: 00-00-2014

Program Area: Crop-Soil-Water Management

Commodity: Rice

Objectives:

To determine crop yield and water requirement under AWD method
To determine the effect of USG under AWD method
To validate yield and water requirement with AquaCrop model
To estimate the probabilistic yield under AWD method for similar climatic condition.

Methodology:

Water Treatments were: I₁= continuous standing water, I₂= Irrigation when water level reached 15 cm below soil surface and I₃= Irrigation when water level reached 20 cm below soil surface and nitrogen treatments were: N₀= No nitrogen, N₁= Pilled urea applied @220 kg ha^-1 and N₂= USG applied @70 gm between four rows.The field experiment was conducted at BRRI farm, Gazipur, during the dry season of 2013-14. The experimental field irrigated from a deep tubewell. The experiment was laid out in a split-split-plot design with three replications. The water treatments were in main plot and variety in sub plot and fertilizer management in sub-sub-plot. BRRI dhan28 and BRRI dhan29 were used as test variety. Forty-two days-old seedlings were transplanted with a population of 500,000 plants per hectare (i.e. with 2-3 seedlings hill^-1 density, and 20 ´ 20 cm hill spacing – following BRRI recommendation) on 2nd January in 2014 and harvested in late April for BRRI dhan28 and first week of May for BRRI dhan29. Measured quantities of irrigation water were applied directly to the experimental plots. Field water depths for different water regimes were monitored by installing a partly perforated PVC pipe of 25 and 30 cm length and 10 cm diameter. In order to simulate crop growth and yield, the AquaCrop model accounts for soil physical and hydraulic processes, atmospheric conditions (rainfall, temperature, evapo-transpiration, ET and carbon dioxide concentration), crop physiological and productivity parameters (phenology, crop cover, root depth, biomass production and harvestable yield) and field management components (irrigation, fertilizer and field agronomic practices) (Raes et al., 2009a; Steduto et al., 2009). AquaCrop calculates a daily water balance and separates its ET into evaporation and transpiration, where transpiration is proportional to the area of soil covered by the crop canopy, and evaporation is proportional to the area of uncovered soil. The crop responds to water stress through four stress coefficients (leaf expansion, stomata closure, canopy senescence, and change in harvest index).

Source of Information: Proceedings of the BRRI Annual Review for 2014, BRRI, Gazipur-1701, Bangladesh

Article Link (Online Journal):

Funding Source:

1. Government

Budget:

Total Budget (Tk.) :

Achievement/Findings:

Crop canopy cover (CC) estimation statistics showed good to excellent fit of the model to the observed data, with a noticeably better fit for the AWD-15 treatment than for the other two treatments. Apart from the imperfection of the simulation model and its parameterization, the systematic nature of those deviations, can possibly also be related to unaccounted losses that occurred at harvest or the recurring destructive sampling for CC and biomass assessment during the experiment.Biomass and yield estimates were slightly under and over the observed values, yielding -6.04% underestimation to 5.95% overestimation of biomass, and -5.31 underestimation to 8.28% overestimation in yield estimates, depending on the irrigation regime and fertilizer doses. These differences are rather small, and they also support the good statistical metrics. The differences in biomass vs. yield in the observations and the simulations indicate that the final HI value that the model used differed slightly from the observations, but the difference in HI remained at 1%.

Knowledge Management: Report/Proceedings