The AquaCrop model – Enhancing crop water productivity

SUMMARYWeed infestation is a major yield-reducing factor that also decreases crop water productivity. Yet weeds are often neglected in crop productivity simulation studies, because existing empirical equations and mechanistic models are not widely applicable or have a high demand for input data and calibration. For that reason, AquaCrop, a widely applicable crop water productivity model, was expanded with a weed management module which requires only two easily obtainable input variables: (i) relative leaf cover of weeds, and (ii) weed-induced increase of total canopy cover. Using these inputs, AquaCrop directly simulates soil water content, crop canopy development and production as it is observed in weed-infested fields. Despite this simple approach, AquaCrop performed well to simulate soil water content in the root zone (relative root-mean-square error (RRMSE) of 5–13%), canopy cover (RRMSE of 15–22%), dry above-ground crop biomass during the season (RRMSE of 21–39%) and at maturity (RRMSE of 5–6%) and yield (RRMSE of 11–25%) of barley and wheat grown under different weed infestation levels and environments. The current study illustrates that the AquaCrop model can be used to assess the effect of weed infestation on crop growth and production, using a simple approach that is applicable to diverse environmental and agronomic conditions, even in data-scarce regions.

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CROP WATER PRODUCTIVITY AND IRRIGATIONCROP WATER PRODUCTIVITY AS INFLUNCEDBYMAIZE(Zea mays L.) GENOTYPES AND IRRIGATION QUALITY USING AQUACROP MODEL

The Journal of The University of Duhok ◽

10.26682/avuod.2019.22.1.3 ◽

2019 ◽

Vol 22 (1) ◽

pp. 24-37

Author(s):

AKRAM ABBAS KHALAF ◽

Keyword(s):

Zea Mays ◽

Zea Mays L ◽

Water Productivity ◽

Crop Water ◽

Crop Water Productivity ◽

Aquacrop Model ◽

Irrigation Quality

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Validation of Aquacrop for Different Irrigation Regimes of Onion (Allium Cepa) in Bontanga Irrigation Scheme

International Journal of Irrigation and Agricultural Development (IJIRAD) ◽

10.47762/2017.964x.19 ◽

2018 ◽

Vol 1 (1) ◽

pp. 1-12

Author(s):

Y. K. Agbemabiese ◽

A-G Shaibu ◽

V. D. Gbedzi

Keyword(s):

Allium Cepa ◽

Crop Yield ◽

Water Productivity ◽

Leaf Biomass ◽

Crop Water ◽

Irrigation Scheme ◽

Crop Water Productivity ◽

Irrigation Regimes ◽

Aquacrop Model ◽

Mean Square Errors

Crop water productivity models are important tools in evaluating the effect of different irrigation regime on crop yield. AquaCrop model is a crop water productivity model adopted by the Land and Water Division of FAO in the year 2009. It simulates yield response to water for herbaceous crops, and it is particularly suitable in addressing conditions where water is a key limiting factor in crop production such as in northern Ghana. The objective of this study was to calibrate the AquaCrop model for different irrigation regimes for onion (Allium cepa), to determine its effect on crop growth and yield parameters of the crop at the Bontanga irrigation scheme. To achieve these, the Randomised Complete Block Design (RCBD) was used on Red Creole onion variety. RCBD was made up of four irrigation treatment regimes, 117%, 100%, 80% and 60% crop water requirements (CWR) of onion, with five replicates. Results indicated that there was no significant variation in yield, dry bulb biomass and total biomass, but there was difference for dry leaf biomass of onion at 0.05 significance level. The AquaCrop model simulated satisfactorily the crop yield, biomass and evapotranspiration water productivity of onion. There was a strong correlation and a significant linear relation between the simulated and measured crop yield, biomass and evapotranspiration water productivity. Validation of AquaCrop model using Nash-Sutcliffe efficiency (E), Root mean square errors (RMSE) and index of agreement (d) showed that, AquaCrop model can be used to simulate CWR of bulb crops, such as onion.

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Irrigation Management Effects on Crop Water Productivity for Maize Production in the Texas High Plains

Water Conservation Science and Engineering ◽

10.1007/s41101-020-00100-x ◽

2021 ◽

Vol 6 (1) ◽

pp. 37-43

Author(s):

Gary W. Marek ◽

Thomas H. Marek ◽

Steven R. Evett ◽

Yong Chen ◽

Kevin R. Heflin ◽

...

Keyword(s):

Water Productivity ◽

Irrigation Management ◽

High Plains ◽

Crop Water ◽

Maize Production ◽

Crop Water Productivity ◽

Texas High Plains ◽

Management Effects

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Simulated efficient growth-stage-based deficit irrigation strategies for maximizing cotton yield, crop water productivity and net returns

Agricultural Water Management ◽

10.1016/j.agwat.2021.106840 ◽

2021 ◽

Vol 250 ◽

pp. 106840

Author(s):

Sushil Kumar Himanshu ◽

Yubing Fan ◽

Srinivasulu Ale ◽

James Bordovsky

Keyword(s):

Deficit Irrigation ◽

Growth Stage ◽

Water Productivity ◽

Cotton Yield ◽

Crop Water ◽

Net Returns ◽

Crop Water Productivity

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Maize Seedling Establishment, Grain Yield and Crop Water Productivity Response to Seed Priming and Irrigation Management in a Mediterranean Arid Environment

Agronomy ◽

10.3390/agronomy11040756 ◽

2021 ◽

Vol 11 (4) ◽

pp. 756

Author(s):

AbdAllah M. El-Sanatawy ◽

Ahmed S. M. El-Kholy ◽

Mohamed M. A. Ali ◽

Mohamed F. Awad ◽

Elsayed Mansour

Keyword(s):

Grain Yield ◽

Deficit Irrigation ◽

Water Productivity ◽

Irrigation Management ◽

Seed Priming ◽

Severe Drought ◽

Arid Environments ◽

Crop Water ◽

Crop Water Productivity ◽

Irrigation Regimes

Water shortage is a major environmental stress that destructively impacts maize production, particularly in arid regions. Therefore, improving irrigation management and increasing productivity per unit of water applied are needed, especially under the rising temperature and precipitation fluctuations induced by climate change. Laboratory and field trials were carried out in the present study, which were aimed at assessing the possibility of promoting maize germination, growth, grain yield and crop water productivity (CWP) using seed priming under different irrigation regimes. Two seed priming treatments, i.e., hydro-priming and hardening versus unprimed seeds, were applied under four irrigation regimes, i.e., 120, 100, 80 and 60% of estimated crop evapotranspiration (ETc). The obtained results indicated that increasing irrigation water from 100% up to 120% ETc did not significantly increase grain yield or contributing traits, while it decreased CWP. Deficit irrigation of 80 and 60% ETc gradually decreased grain yield and all attributed traits. Seed priming significantly ameliorated seedlings’ vigor as indicated by earlier germination, higher germination percentage, longer roots and shoots, and heavier fresh and dry weight than unprimed seeds with the superiority of hardening treatment. Additionally, under field conditions, seed priming significantly increased grain yield, yield contributing traits and CWP compared with unprimed treatment. Interestingly, the results reflect the role of seed priming, particularly hardening, in mitigating negative impacts of drought stress and enhancing maize growth, grain yield and attributed traits as well as CWP under deficit irrigation conditions. This was demonstrated by a significant increase in grain yield and CWP under moderate drought and severe drought conditions compared with unprimed treatment. These results highlight that efficient irrigation management and seed priming can increase maize yield and water productivity in arid environments.

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Global Satellite-Based ET Products for the Local Level Irrigation Management: An Application of Irrigation Performance Assessment in the Sugarbelt of Swaziland

Remote Sensing ◽

10.3390/rs11060705 ◽

2019 ◽

Vol 11 (6) ◽

pp. 705 ◽

Cited By ~ 6

Author(s):

Poolad Karimi ◽

Bhembe Bongani ◽

Megan Blatchford ◽

Charlotte de Fraiture

Keyword(s):

Remote Sensing ◽

Performance Assessment ◽

Management Practices ◽

Local Level ◽

Water Productivity ◽

Irrigation Management ◽

Irrigation Performance ◽

Crop Water ◽

Management Regime ◽

Crop Water Productivity

Remote sensing techniques have been shown, in several studies, to be an extremely effective tool for assessing the performance of irrigated areas at various scales and diverse climatic regions across the world. Open access, ready-made, global ET products were utilized in this first-ever-countrywide irrigation performance assessment study. The study aimed at identifying ‘bright spots’, the highest performing sugarcane growers, and ‘hot spots’, or low performing sugarcane growers. Four remote sensing-derived irrigation performance indicators were applied to over 302 sugarcane growers; equity, adequacy, reliability and crop water productivity. The growers were segmented according to: (i) land holding size or grower scale (ii) management regime, (iii) location of the irrigation schemes and (iv) irrigation method. Five growing seasons, from June 2005 to October 2009, were investigated. The results show while the equity of water distribution is high across all management regimes and locations, adequacy and reliability of water needs improvement in several locations. Given the fact that, in general, water supply was not constrained during the study period, the observed issues with adequacy and reliability of irrigation in some of the schemes were mostly due to poor scheme and farm level water management practices. Sugarcane crop water productivity showed the highest variation among all the indicators, with Estate managed schemes having the highest CWP at 1.57 kg/m3 and the individual growers recording the lowest CWP at 1.14 kg/m3, nearly 30% less. Similarly center pivot systems showed to have the highest CWP at 1.63 kg/m3, which was 30% higher than the CWP in furrow systems. This study showcases the applicability of publicly available global remote sensing products for assessing performance of the irrigated crops at the local level in several aspects.

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