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Crop coefficient

About: Crop coefficient is a research topic. Over the lifetime, 2371 publications have been published within this topic receiving 78703 citations.


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01 Jan 1998
TL;DR: In this paper, an updated procedure for calculating reference and crop evapotranspiration from meteorological data and crop coefficients is presented, based on the FAO Penman-Monteith method.
Abstract: (First edition: 1998, this reprint: 2004). This publication presents an updated procedure for calculating reference and crop evapotranspiration from meteorological data and crop coefficients. The procedure, first presented in FAO Irrigation and Drainage Paper No. 24, Crop water requirements, in 1977, allows estimation of the amount of water used by a crop, taking into account the effect of the climate and the crop characteristics. The publication incorporates advances in research and more accurate procedures for determining crop water use as recommended by a panel of high-level experts organised by FAO in May 1990. The first part of the guidelines includes procedures for determining reference crop evapotranspiration according to the FAO Penman-Monteith method. These are followed by updated procedures for estimating the evapotranspiration of different crops for different growth stages and ecological conditions.

21,958 citations

Journal ArticleDOI
TL;DR: In this paper, an equation is presented that estimates ETo from measured values of daily or mean values of maximum and minimum temperature. But this equation is compared with various other methods for estimating ETo.
Abstract: MEASURED lysimeter evapotranspiration of Alta fescue grass (a cool season grass) is taken as an index of reference crop evapotranspiration (ETo). An equation is presented that estimates ETo from measured values of daily or mean values of maximum and minimum temperature. This equation is compared with various other methods for estimating ETo. The equation was developed using eight years of daily lysimeter data from Davis, California and used to estimate values of ETo for other locations. Comparisons with other methods with measured cool season grass evapotranspiration at Aspendale, Australia; Lompoc, California; and Seabrook, New Jersey; with lysimeter data from Damin, Haiti; and with the modified Penman for various locations in Bangladesh indicated that the method usually does not require local calibration and that the estimated values are probably as reliable and useable as those from the other estimating methods used for comparison. Considering the scarcity of complete and reliable climatic data for estimating crop water requirements in developing countries, this proposed method can do much to improve irrigation planning design and scheduling in the developing countries.

3,252 citations

01 Jan 1982
TL;DR: SWATR calculates the actual transpiration and growth rate of a crop as mentioned in this paper, and CROPR calculates transpiration of a given crop and crop growth rate, respectively, based on its transpiration, growth rate and transpiration.
Abstract: SWATR calculates the actual transpiration of a crop and CROPR calculates the actual growth rate of a crop

1,274 citations

Journal ArticleDOI
TL;DR: In this article, the authors present a two-part series of recommendations for documentation to be associated with published evapotranspiration (ET) data and provide guidelines for reducing error in ET retrievals.

743 citations

Journal ArticleDOI
TL;DR: The first crop chosen to parameterize and test the new FAO AquaCrop model is maize (Zea mays L.). Working mainly with data sets from 6 yr of maize field experiments at Davis, CA, plus another 4 yr of Davis maize canopy data, a set of conservative (nearly constant) parameters, presumably applicable to widely different conditions and not specific to a given crop cultivar, was evaluated by test simulations, and used to simulate the 6 yr Davis data as discussed by the authors.
Abstract: The first crop chosen to parameterize and test the new FAO AquaCrop model is maize (Zea mays L.). Working mainly with data sets from 6 yr of maize field experiments at Davis, CA, plus another 4 yr of Davis maize canopy data, a set of conservative (nearly constant) parameters of AquaCrop, presumably applicable to widely different conditions and not specific to a given crop cultivar, was evaluated by test simulations, and used to simulate the 6 yr of Davis data. The treatment variable was irrigation―withholding water after planting continuously, only up to tasseling, from tasseling onward, or intermittently, and with full irrigation (FI) as the control. From year to year, plant density (7―11.9 plants m ―2 ), planting date (14 May―15 June), cultivar (a total of four), and atmospheric evaporative demand varied. The conservative parameters included: canopy growth and canopy decline coefficient (CDC); crop coefficient for transpiration (Tr) at full canopy; normalized water productivity for biomass (WP * ); soil water depletion thresholds for the inhibition leaf growth and of stomatal conductance, and for the acceleration of canopy senescence; reference harvest index (HI o ); and coefficients for adjusting harvest index (HI) in relation to inhibition of leaf growth and of stomatal conductance. With all 19 parameters held constant, AquaCrop simulated the final aboveground biomass within 10% of the measured value for at least 8 of the 13 treatments (6 yr of experiments) and also the grain yield for at least five of the cases. In at least four of the cases, the simulated results were within 5% of the measured for biomass as well as for grain yield. The largest deviation between the simulated and measured values was 22% for biomass, and 24% for grain yield. Importantly, the simulated pattern of canopy progression and biomass accumulation over time were close to those measured, with Willmott's index of agreement (d) for 11 of the 13 cases being ≥0.98 for canopy cover (CC), and ≥0.97 for biomass. Accelerated senescence of canopy due to water stress, however, proved to be dif- ficult to simulate accurately; of the six cases, the index of agreement for the worst one was 0.957 for canopy and 0.915 for biomass. Possible reasons for the discrepancies between the simulated and measured results include simplifications in the model and inaccuracies in measurements. The usefulness of AquaCrop with well-calibrated conservative parameters in assessing water use efficiency (WUE) of a crops under different conditions and in devising strategies to improve WUE is discussed.

718 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202390
2022146
2021114
2020122
2019113
2018114