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Yield response to water.

About: The article was published on 1979-01-01 and is currently open access. It has received 2318 citations till now. The article focuses on the topics: Yield (engineering) & Water use.
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Journal ArticleDOI
TL;DR: In this article, the authors used a grid-based dynamic water balance model to estimate the green, blue and grey water footprint of global crop production in a spatially-explicit way for the period 1996-2005.
Abstract: This study quantifies the green, blue and grey water footprint of global crop production in a spatially-explicit way for the period 1996–2005. The assessment improves upon earlier research by taking a high-resolution approach, estimating the water footprint of 126 crops at a 5 by 5 arc minute grid. We have used a grid-based dynamic water balance model to calculate crop water use over time, with a time step of one day. The model takes into account the daily soil water balance and climatic conditions for each grid cell. In addition, the water pollution associated with the use of nitrogen fertilizer in crop production is estimated for each grid cell. The crop evapotranspiration of additional 20 minor crops is calculated with the CROPWAT model. In addition, we have calculated the water footprint of more than two hundred derived crop products, including various flours, beverages, fibres and biofuels. We have used the water footprint assessment framework as in the guideline of the Water Footprint Network. Considering the water footprints of primary crops, we see that the global average water footprint per ton of crop increases from sugar crops (roughly 200 m3 ton−1), vegetables (300 m3 ton−1), roots and tubers (400 m3 ton−1), fruits (1000 m3 ton−1), cereals (1600 m3 ton−1), oil crops (2400 m3 ton−1) to pulses (4000 m3 ton−1). The water footprint varies, however, across different crops per crop category and per production region as well. Besides, if one considers the water footprint per kcal, the picture changes as well. When considered per ton of product, commodities with relatively large water footprints are: coffee, tea, cocoa, tobacco, spices, nuts, rubber and fibres. The analysis of water footprints of different biofuels shows that bio-ethanol has a lower water footprint (in m3 GJ−1) than biodiesel, which supports earlier analyses. The crop used matters significantly as well: the global average water footprint of bio-ethanol based on sugar beet amounts to 51 m3 GJ−1, while this is 121 m3 GJ−1 for maize. The global water footprint related to crop production in the period 1996–2005 was 7404 billion cubic meters per year (78 % green, 12 % blue, 10 % grey). A large total water footprint was calculated for wheat (1087 Gm3 yr−1), rice (992 Gm3 yr−1) and maize (770 Gm3 yr−1). Wheat and rice have the largest blue water footprints, together accounting for 45 % of the global blue water footprint. At country level, the total water footprint was largest for India (1047 Gm3 yr−1), China (967 Gm3 yr−1) and the USA (826 Gm3 yr−1). A relatively large total blue water footprint as a result of crop production is observed in the Indus river basin (117 Gm3 yr−1) and the Ganges river basin (108 Gm3 yr−1). The two basins together account for 25 % of the blue water footprint related to global crop production. Globally, rain-fed agriculture has a water footprint of 5173 Gm3 yr−1 (91 % green, 9 % grey); irrigated agriculture has a water footprint of 2230 Gm3 yr−1 (48 % green, 40 % blue, 12 % grey).

1,664 citations

Journal ArticleDOI
TL;DR: Several cases on the successful use of regulated deficit irrigation (RDI) in fruit trees and vines are reviewed, showing that RDI not only increases water productivity, but also farmers' profits.
Abstract: At present and more so in the future, irrigated agriculture will take place under water scarcity. Insufficient water supply for irrigation will be the norm rather than the exception, and irrigation management will shift from emphasizing production per unit area towards maximizing the production per unit of water consumed, the water productivity. To cope with scarce supplies, deficit irrigation, defined as the application of water below full crop-water requirements (evapotranspiration), is an important tool to achieve the goal of reducing irrigation water use. While deficit irrigation is widely practised over millions of hectares for a number of reasons—from inadequate network design to excessive irrigation expansion relative to catchment supplies—it has not received sufficient attention in research. Its use in reducing water consumption for biomass production, and for irrigation of annual and perennial crops is reviewed here. There is potential for improving water productivity in many field crops and there is sufficient information for defining the best deficit irrigation strategy for many situations. One conclusion is that the level of irrigation supply under deficit irrigation should be relatively high in most cases, one that permits achieving 60–100% of full evapotranspiration. Several cases on the successful use of regulated deficit irrigation (RDI) in fruit trees and vines are reviewed, showing that RDI not only increases water productivity, but also farmers’ profits. Research linking the physiological basis of these responses to the design of RDI strategies is likely to have a significant impact in increasing its adoption in water-limited areas.

1,540 citations

Journal ArticleDOI
TL;DR: The FAO crop model AquaCrop as mentioned in this paper is a water-driven growth engine, in which transpiration is calculated first and translated into biomass using a conservative, crop-specific parameter: the biomass water productivity, normalized for atmospheric evaporative demand and air CO 2 concentration.
Abstract: This article introduces the FAO crop model AquaCrop. It simulates attainable yields of major herbaceous crops as a function of water consumption under rainfed, supplemental, deficit, and full irrigation conditions. The growth engine of AquaCrop is water-driven, in that transpiration is calculated first and translated into biomass using a conservative, crop-specific parameter: the biomass water productivity, normalized for atmospheric evaporative demand and air CO 2 concentration. The normalization is to make AquaCrop applicable to diverse locations and seasons. Simulations are performed on thermal time, but can be on calendar time, in daily time-steps. The model uses canopy ground cover instead of leaf area index (LAI) as the basis to calculate transpiration and to separate out soil evaporation from transpiration. Crop yield is calculated as the product of biomass and harvest index (HI). At the start of yield formation period, HI increases linearly with time after a lag phase, until near physiological maturity. Other than for the yield, there is no biomass partitioning into the various organs. Crop responses to water deficits are simulated with four modifiers that are functions of fractional available soil water modulated by evaporative demand, based on the differential sensitivity to water stress of four key plant processes: canopy expansion, stomatal control of transpiration, canopy senescence, and HI. The HI can be modified negatively or positively, depending on stress level, timing, and canopy duration. AquaCrop uses a relatively small number of parameters (explicit and mostly intuitive) and attempts to balance simplicity, accuracy, and robustness. The model is aimed mainly at practitioner-type end-users such as those working for extension services, consulting engineers, governmental agencies, nongovernmental organizations, and various kinds of farmers associations. It is also designed to fit the need of economists and policy specialists who use simple models for planning and scenario analysis.

1,329 citations


Cites methods from "Yield response to water."

  • ...AquaCrop evolves from the previous Doorenbos and Kassam (1979) approach (Eq....

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Journal ArticleDOI
TL;DR: In this paper, a review of 84 literature sources with results of experiments not older than 25 years, it was found that the ranges of CWP of wheat, rice, cotton and maize exceed in all cases those reported by FAO earlier.

908 citations

Journal ArticleDOI
TL;DR: In this paper, the authors summarize the advantages and disadvantages of deficit irrigation and compare them with field research and crop water productivity modeling, concluding that a certain minimum amount of seasonal moisture must be guaranteed.

850 citations


Cites background or result from "Yield response to water."

  • ...Section d can be quite large, for crops such as alfalfa, sugar beets (Doorenbos and Kassam, 1979), wheat (Kang et al., 2002; Zhang et al., 2008; Sun et al., 2006) or cotton (Henggeler et al., 2002; Kanber et al., 2006; DeTar, 2008), while it may be almost absent for other crops, such as maize…...

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  • ...Doorenbos and Kassam (1979) point out that the relationship between Yrel and ETrel remains linear for ETrel up to a lower limit of 0.5 (point B in Fig....

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  • ...2a, linear approximation of upper sub-section of d) or a convex quadratic CPWs function was found for sugarbeet (Bazza (1999) and Doorenbos and Kassam (1979), respectively)....

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  • ...In line with the reference works of Hanks et al. (1969), Hanks (1974), Stewart et al. (1977), Doorenbos and Kassam (1979) and Taylor et al. (1983), the relation between crop evapotranspiration and yield is proposed as a framework for evaluating the drought sensitivity of a particular crop during…...

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  • ...The crop water production function (CWP function) expresses the relation between obtained marketable yield (Ya) and the total amount of water evapotranspired (ETa) (Stewart et al., 1977; Hexem and Heady, 1978; Doorenbos and Kassam, 1979; Taylor et al., 1983)....

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