Deficit Irrigation Optimization of Cotton with AquaCrop

García-Vila, Margarita; Fereres, E.; Mateos, Luciano; Orgaz, F.; Steduto, Pasquale

doi:10.2134/agronj2008.0179s

Cited by 142 publications

(66 citation statements)

References 42 publications

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“…The results of the economic model demonstrated that maximum profit from quinoa production can be achieved with less irrigation water than required for maximum quinoa yield in all type of climate scenarios, and that prof it differences between rainfed and irrigated quinoa are greater in dry and very dry years. Also, as it was found by other studies García-Vila et al, 2009;Pérez-Pérez et al, 2010), the study showed that product price is one of the main forces to drive the use of irrigation for improving crop productivity.…”

Section: Discussionsupporting

confidence: 56%

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Economic assessment at farm level of the implementation of deficit irrigation for quinoa production in the Southern Bolivian Altiplano

Cusicanqui

Dillen

Garcia

et al. 2013

Span. j. agric. res.

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In the Southern Bolivian Altiplano recent research has suggested to introduce deficit irrigation as a strategy to boost quinoa yields and to stabilize it at 2.0 ton ha-1. In this study we carried out an economic assessment of the implementation of deficit irrigation at farm level using a hydro-economic model for simulating profit for quinoa production. As input of the model we worked with previously developed farms typology (livestock, quinoa and subsistence farms), simulated quinoa production with and without irrigation using AquaCrop model, and calculated yield response functions for four different climate scenarios (wet, normal, dry and very dry years). Results from the hydro-economic model demonstrate that maximum profit is achieved with less applied irrigated water than for maximum yield, and irrigated quinoa earned more profit than rainfed production for all farms types and climate scenarios. As expected, the benefits of irrigation under dry and very dry climate conditions were higher than those under normal and wet years, and benefits among farms types were higher for quinoa farms. In fact, profit of irrigated quinoa might be stabilized at around BOB 6500 ha-1 (about USD 920) compared with the huge differences found for rainfed conditions for all climate scenarios. Interestingly, the economic water productivity, expressed in terms of economic return for amount of applied irrigated water (BOB mm-1), reached the highest values with intermediate and low level of water availability schemes of deficit irrigation for all climate scenarios.

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Section: Discussionsupporting

confidence: 56%

“…Economic water productivity can be expressed on the basis of the economic value of the product and water use (Rodrigues & Pereira, 2009), or as in this paper, on the economic value of the product and irrigated water (Playán & Mateos, 2006;García-Vila et al, 2009 …”

Section: Economic Water Productivitymentioning

confidence: 99%

Economic assessment at farm level of the implementation of deficit irrigation for quinoa production in the Southern Bolivian Altiplano

Cusicanqui

Dillen

Garcia

et al. 2013

Span. j. agric. res.

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“…The model performance on simulating crop growth and water use has been well tested for a variety of crop types under diverse environmental conditions (e.g. Kumar et al, 2014;Jin et al, 2014;Abedinpour et al, 2012;Mkhabela and Bullock, 2012;Andarzian et al, 2011;Stricevic et al, 2011;Heng et al, 2009;Farahani et al, 2009;García-vila et al, 2009). AquaCrop has been applied in WF accounting at field (Chukalla et al, 2015), river basin (Zhuo et al, 2016a), and national level (Zhuo et al, 2016b) at high spatial resolution.…”

Section: Estimating Consumptive Wf Of Growing a Cropmentioning

confidence: 99%

Benchmark levels for the consumptive water footprint of crop production for different environmental conditions: a case study for winter wheat in China

Zhuo

Mekonnen

Hoekstra

2016

Hydrol. Earth Syst. Sci.

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Abstract. Meeting growing food demands while simultaneously shrinking the water footprint (WF) of agricultural production is one of the greatest societal challenges. Benchmarks for the WF of crop production can serve as a reference and be helpful in setting WF reduction targets. The consumptive WF of crops, the consumption of rainwater stored in the soil (green WF), and the consumption of irrigation water (blue WF) over the crop growing period varies spatially and temporally depending on environmental factors like climate and soil. The study explores which environmental factors should be distinguished when determining benchmark levels for the consumptive WF of crops. Hereto we determine benchmark levels for the consumptive WF of winter wheat production in China for all separate years in the period 1961-2008, for rain-fed vs. irrigated croplands, for wet vs. dry years, for warm vs. cold years, for four different soil classes, and for two different climate zones. We simulate consumptive WFs of winter wheat production with the crop water productivity model AquaCrop at a 5 by 5 arcmin resolution, accounting for water stress only. The results show that (i) benchmark levels determined for individual years for the country as a whole remain within a range of ±20 % around long-term mean levels over 1961-2008, (ii) the WF benchmarks for irrigated winter wheat are 8-10 % larger than those for rain-fed winter wheat, (iii) WF benchmarks for wet years are 1-3 % smaller than for dry years, (iv) WF benchmarks for warm years are 7-8 % smaller than for cold years, (v) WF benchmarks differ by about 10-12 % across different soil texture classes, and (vi) WF benchmarks for the humid zone are 26-31 % smaller than for the arid zone, which has relatively higher reference evapotranspiration in general and lower yields in rain-fed fields. We conclude that when determining benchmark levels for the consumptive WF of a crop, it is useful to primarily distinguish between different climate zones. If actual consumptive WFs of winter wheat throughout China were reduced to the benchmark levels set by the best 25 % of Chinese winter wheat production (1224 m 3 t −1 for arid areas and 841 m 3 t −1 for humid areas), the water saving in an average year would be 53 % of the current water consumption at winter wheat fields in China. The majority of the yield increase and associated improvement in water productivity can be achieved in southern China.

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“…Still, some studies report that model performance declines in estimating some variables in severe water stress environments [1,13]. Although a highlighted feature of the model is the applicability of conservative parameters used in crop simulations (these parameters are reported by Heng et al [8] and Hsiao et al [12] for maize), several researchers observed that model parameterization is essentially site-specific and that important calibrated parameters necessary for accurate simulation must be tested under different climate, soil, cultivars, irrigation methods, and field management to improve the reliability of the simulated results [3,14,15].…”

Section: Introductionmentioning

confidence: 99%

Assessment of FAO AquaCrop Model for Simulating Maize Growth and Productivity under Deficit Irrigation in a Tropical Environment

Greaves

Wang

2016

Water

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Abstract:Crop simulation models have a pivotal role to play in evaluating irrigation management strategies for improving agricultural water use. The objective of this study was to test and validate the AquaCrop model for maize under deficit irrigation management. Field observations from three experiments consisting of four treatments were used to evaluate model performance in simulating canopy cover (CC), biomass (B), yield (Y), crop evapotranspiration (ET c ), and water use efficiency (WUE). Statistics for root mean square error, model efficiency (E), and index of agreement for B and CC suggest that the model prediction is good under non-stressed and moderate stress environments. Prediction of final B and Y under these conditions was acceptable, as indicated by the high coefficient of determination and deviations <10%. In severely stressed conditions, low E and deviations >11% for B and 9% for Y indicate a reduction in the model reliability. Simulated ET c and WUE deviation from observed values were within the range of 9.5% to 22.2% and 6.0% to 32.2%, respectively, suggesting that AquaCrop prediction of these variables is fair, becoming unsatisfactory as plant water stress intensifies. AquaCrop can be reliably used for evaluating the effectiveness of proposed irrigation management strategies for maize; however, the limitations should be kept in mind when interpreting the results in severely stressed conditions.

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Deficit Irrigation Optimization of Cotton with AquaCrop

Cited by 142 publications

References 42 publications

Economic assessment at farm level of the implementation of deficit irrigation for quinoa production in the Southern Bolivian Altiplano

Economic assessment at farm level of the implementation of deficit irrigation for quinoa production in the Southern Bolivian Altiplano

Benchmark levels for the consumptive water footprint of crop production for different environmental conditions: a case study for winter wheat in China

Assessment of FAO AquaCrop Model for Simulating Maize Growth and Productivity under Deficit Irrigation in a Tropical Environment

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