to direct impacts such as floods or droughts, climate change also has a direct impact on rice yield through temperature and rainfall (Deb et al., 2016). High-intensity temperatures for short periods of time can lead to the sterility of sprouts in rice (Masutomi et al., 2009). Changes in temperature can alter the evaporation requirements of plants (Tao et al., 2003).
Table 1. Average population and rice growing area in Phu Thien district
Year 2016 2017 2018 2019 2020
Average population (person) 76,485 77,101 78,033 78,821 79,656 Planted area of paddy (ha) 12,720 12,522 12,585 12,678 12,935 Planted area of summer-autumn rice
(ha) 6,663 6,468 6,510 6,603 6,663
Planted area of spring rice (ha) 6,070 6,070 6,070 6,075 6,272
Source: Gia Lai Statistical Yearbook of 2020.
Therefore, measuring the performance of agricultural production in the context of climate change in the future is essential for building a sustainable agricultural production system in Phu Thien district and ensuring food security for the whole Gia Lai province in general. A weighted yield for each unit of provided irrigation water or a biomass buildup over water consumption is what is meant by the irrigation water use efficiency, which is one of the variables used to measure the performance of agricultural production systems (Abou-Baker, 2020). The decrease in irrigation water use efficiency will lead to a reduction in irrigated area and a decrease in rice production. This study aimed to evaluate irrigation water use efficiency (IWUE) for flood alternate wetting and drying paddy cultivation in different conditions of climate, soil types, and crop season in Phu Thien district, the “rice bowl” of Gia Lai province.
2. Materials and Methods
The study area was in the eastern region of Gia Lai province (13°31′48″N, 108°18′46″E, altitude 160 m above mean sea level). The site includes Ayun Hạ, Chrôh Pơnan, Chư A Thai, Ia Ake, Ia Hiao, Ia Piar, Ia Peng, Ia Sol, and Ia Yeng communes. The soil texture of the area is mostly sandy clay loam, followed by sandy loam, and clay (FAO, 2012).
2.2. Data collection 2.2.1. Climate
Meteorological data used in this study include solar radiation, precipitation, relative humidity, sunshine duration, mean air temperature, minimum air temperature, maximum air temperature, and wind speed from 1986 to 2005 at Ayun Pa meteorological station provided by Central Highlands Hydro-meteorological Regional Centre. This is baseline scenario for comparison with the three high greenhouse gas emission scenarios of normal, wet, and dry years according to Representative Concentration Pathway (RCP) 8.5 (2046 - 2065) from the 2020 version of the climate change scenario for Vietnam published by the Ministry of Natural Resources and Environment. The three main variables that change in future climate change scenarios are precipitation, maximum temperature, and minimum temperature. In which, the normal, dry, and wet scenarios used monthly meteorological data at Ayun Pa station (1986 - 2005) plus median, 20th/10th percentile, 80th/90th percentile of change according to RCP 8.5 (2046 - 2065), respectively.
2.2.2. Crop
In Phu Thien district, flood alternate wetting and drying paddy is grown in spring and summer- autumn crops. The growing period of flood alternate wetting and drying paddy is divided into (i) nursery/land preparation; (ii) initial stage (direct sowing to seedling establishment); (iii) development stage (branching to flowering); (iv) mid-stage (start of flowering to 100%
flowering, 40 days) and (v) late stage (flowering to maturity, 20 days) (The Vietnamese national standard TCVN 8641-2011 for hydraulic structures - Irrigation and drainage techniques for provisions crops, 2011).
In this study, it is assumed that December 25 and May 30 are suitable transplanting dates for spring and winter rice crops. The optimal height and maximum rooting depth of rice plants are 110 cm and 60 cm, respectively (IRRI, 1985).
Table 2. Physiological and Phenological parameters of flood alternate wetting and drying paddy
Parameter spring crop summer-autumn crop
Duration of initial stage [days] 20 10
Duration of development stage [days] 30 30
Duration of mid-season [days] 40 40
Duration of late season [days] 20 15
Rooting depth, initial stage [m] 0.1 0.1
Rooting depth, mid-season [m] 0.6 0.6
Crop height, mid-season [m] 1.1 1.1
Critical depletion fraction 0.2 0.2
Yield response factor 1.1 1.1
Source: The Vietnamese national standard TCVN 8641-2011 for hydraulic structures - Irrigation and drainage techniques for provisions crops.
2.2.3. Soil
The parameters of each soil texture class in the study area were calculated based on literature review as Table 3.
Table 3. The parameters of soil texture class
Soil texture class Clay Sandy Clay
Loam Sandy
Loam Reference Field capacity (m3/m-3) 0.494 0.352 0.325 (Hakojärvi, 2015) Permanent wilting point (m3/m-3) 0.364 0.176 0.072 (Hakojärvi, 2015) Maximum rain infiltration rate
(mm/day) 30 40 40 (JICA, 2018)
Drainable Porosity (%) 1-2 4-8 4-8 (Smedema &
Rycroft, 1983) 2.3. CropWat model
The FAO Penman-Monteith method is a standard method for the computation of ETo from meteorological data. The Penman-Monteith equation (Allen et al., 1998) integrated into the CropWat program is expressed by equation (1) as follows:
𝐸𝐸𝐸𝐸𝑇𝑇𝑇𝑇0 = 0.408𝛥𝛥𝛥𝛥(𝐸𝐸𝐸𝐸𝑡𝑡𝑡𝑡− 𝐺𝐺𝐺𝐺) + 𝛾𝛾𝛾𝛾 900
𝑇𝑇𝑇𝑇+ 273𝑁𝑁𝑁𝑁2(𝑡𝑡𝑡𝑡𝑠𝑠𝑠𝑠− 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡) 𝛥𝛥𝛥𝛥+ 𝛾𝛾𝛾𝛾(1 + 0.34 𝑁𝑁𝑁𝑁2)
(1)
Where, ETo is reference evapotranspiration [mm day-1], Rn is net radiation at the crop surface [MJ m-2 day-1], G is soil heat flux density [MJ m-2 day-1], T is air temperature at 2 m height [°C], u2 is wind speed at 2 m height [m s-1], es is saturation vapour pressure [kPa], ea is actual vapour pressure [kPa]. 𝛥𝛥𝛥𝛥 is slope vapour pressure curve [kPa °C-1], 𝛾𝛾𝛾𝛾 is psychrometric constant [kPa°C-1].
The FAO-CROPWAT 8.0 model (FAO, 2009) incorporates procedures for estimating ETo and crop water requirements and allows simulation of crop water use under various climate, crop, and soil conditions. The ETo was calculated for every 10 days (defined as “decade” by FAO) and then accumulated into monthly data.
A crucial problem that requires careful thought is the irrigation schedule. Crop irrigation water requirement (CWR) refers to the amount of water that needs to be supplied, while crop evapotranspiration (ETc) refers to the amount of water that is lost through evapotranspiration.
Information on the regional and temporal variability of CWR is essential not only for a better understanding of hydrological processes but also for applying more effective irrigation distribution criteria at both the farm and district levels (D’Urso, 2010). CWR (mm) was determined according to Jahn et al. (2006) as:
𝐶𝐶𝐶𝐶𝐺𝐺𝐺𝐺𝐸𝐸𝐸𝐸 = �(𝐾𝐾𝐾𝐾𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑∗ 𝐸𝐸𝐸𝐸𝑇𝑇𝑇𝑇0− 𝑃𝑃𝑃𝑃𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝)
𝑇𝑇𝑇𝑇
𝑡𝑡𝑡𝑡=0
(2)
Where Kci is the crop coefficient of the given crop i during the growth stage t, T is the final growth stage, Peff is effective rainfall and ETo is reference crop evapotranspiration (mm day-1).
In this study, we used the CropWat model to estimate irrigation water requirements for spring and summer-autumn rice crops grown on three soil types of sandy clay loams, sandy loams,
and clay in the baseline from 1986 to 2005, and three high greenhouse gas emission scenarios of normal, wet, and dry year by 2046 - 2065. The Kc of wet rice in CropWat was calibrated based on the Vietnamese national standard TCVN 8641-2011 for irrigation water. In the land preparation, development, and late stage, the Kc value of the model was 0.3, 1.1, and 0.7 for the dry state; 1.1, 1.27, and 1.02 for the wet state (JICA, 2018) respectively. Irrigation efficiency was assumed to be 70%. Because the water at this stage would prevent the crop from ripening, irrigation was not used during the last 10 days of its growing phase.
2.4. AquaCrop model
AquaCrop model is a windows-based program designed to simulate biomass and yield responses of field crops to different degrees of water availability under various soil conditions and climate change. According to Eq. 3, the model determines the aboveground biomass as a function of reference evapotranspiration, normalized water productivity, transpiration (a factor of canopy cover), and air temperature stress coefficient. The computed cumulative above- ground biomass is then transformed into yield using Eq. 4
𝐵𝐵𝐵𝐵 =𝐾𝐾𝐾𝐾𝑠𝑠𝑠𝑠𝑏𝑏𝑏𝑏×𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺∗×∑𝐸𝐸𝐸𝐸𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑝𝑝𝑝𝑝
𝑜𝑜𝑜𝑜 (3)
𝑌𝑌𝑌𝑌=𝑜𝑜𝑜𝑜𝐶𝐶𝐶𝐶𝐻𝐻𝐻𝐻×𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻0×𝐵𝐵𝐵𝐵 (4)
where B is the aboveground biomass in kg m-2; Ksb is the air temperature stress coefficient;
WP* is the normalized water productivity in kg m-2 mm-1 which is normalized for CO2, type of product synthesized (Raes et al. 2009); Tr is the transpiration in mm day-1; and ETo refers to the evapotranspiration in mm day-1. Y is referred as the yield in kg m-2, fHI is the adjustment factor for all the stress that affects the yield of crop, HIo is the reference harvest index.
Optimizing water is a main challenge for increasing crop productivity and maximizing water use efficiency. To quantify the impact of irrigation efficiency, several indicators have been developed and reviewed (Bastiaanssen & Steduto, 2017; Zwart et al., 2010; Corbari et al., 2021). Irrigation water use efficiency (IWUE) could be defined as the quantity of yield produced by one cubic meter of water supplied and was calculated using the following formula:
IWUE = yield (5) Im
where yield is the crop yield (ton ha−1), Im is the observed or modelled irrigation volume (m3 ha−1). This formula is also called irrigation water productivity (IWP) which is used to assess the performance of cultivation systems (El-Nady MA, Hadad WM, 2016).
In this study, the CropWat outputs including reference evapotranspiration and crop irrigation schedule were imported into the AquaCrop model to calculate rice yields under different climate, soil type, and crop season scenarios. The validation of AquaCrop was performed against observed rice productivity data in 2005 according to the statistical yearbook of Gia Lai province. Finally, IWUE was estimated as the ratio between rice yield simulated from AquaCrop, and the amount of irrigation water simulated from CropWat.
3. Results and Discussions