Estimation of Evapotranspiration ETc and Crop Coefficient Kc of Wheat, in south Nile Delta of Egypt Using integrated FAO-56 approach and remote sensing data

Farg, Eslam; Arafat, S.M. Yasir; El-Wahed, M. S. A. A.; El-Gindy, A. M.

doi:10.1016/j.ejrs.2012.02.001

Cited by 58 publications

(48 citation statements)

References 15 publications

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“…Similar ET c maps at a field scale for agricultural crops including corn were reported by Farg et al [32], Zipper and Loheide [62], and Senay et al [63], they reported minimum and maximum ET c values at different crop growth stages, where the higher evapotranspiration rates were found at the mid-season growth stage and lowest evapotranspiration rates were found at early growth stage. that in those particular stages farmers can save irrigation water (grey wide column in the graph), because in those stages the crop needs small water requirements, due to the fact that the crop canopy is no yet fully developed.…”

Section: Et C Maps At a Field Scalesupporting

confidence: 64%

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Estimation of Crop Evapotranspiration Using Satellite Remote Sensing-Based Vegetation Index

Reyes-González

Kjaersgaard

Trooien

et al. 2018

Advances in Meteorology

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Irrigation water is limited and scarce in many areas of the world, including Comarca Lagunera, Mexico. Thus better estimations of irrigation water requirements are essential to conserve water. The general objective was to estimate crop water demands or crop evapotranspiration (ET c ) at different scales using satellite remote sensing-based vegetation index. The study was carried out in northern Mexico (Comarca Lagunera) during four growing seasons. Six, eleven, three, and seven clear Landsat images were acquired for 2013, 2014, 2015, and 2016, respectively, for the analysis. The results showed that ET c was low at initial and early development stages, while ET c was high during mid-season and harvest stages. These results are not new but give us confidence in the rest of our ET c results. Daily ET c maps helped to explain the variability of crop water use during the growing season. Based on the results we can conclude that ET c maps developed from remotely sensed multispectral vegetation indices are a useful tool for quantifying crop water consumption at regional and field scales. Using ET c maps at the field scale, farmers can supply appropriate amounts of irrigation water corresponding to each growth stage, leading to water conservation.

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Section: Et C Maps At a Field Scalesupporting

confidence: 64%

“…Crop coefficients derived from remotely sensed vegetation index also have used to generate local and regional ET c maps [2,[32][33][34]; however, in northern Mexico, ET c maps using satellite remote sensing-based vegetation index remain unexplored.…”

Section: Advances In Meteorologymentioning

confidence: 99%

Estimation of Crop Evapotranspiration Using Satellite Remote Sensing-Based Vegetation Index

Reyes-González

Kjaersgaard

Trooien

et al. 2018

Advances in Meteorology

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“…Singh et al [70] has demonstrated the use of the calculated reference ET and the remotely sensed NDVI in estimating the water use of cotton. A similar procedure has also been demonstrated by Farg et al [67] for estimating the daily water use of wheat.…”

Section: Weather-based Sensingmentioning

confidence: 83%

“…The K c curve defined for a crop over its growth stage is generalized for regions with similar climates. The K c is however dependent on the canopy dynamics including cover fraction, leaf area index and greenness which may vary across regions with similar climates [67]. This introduces errors into ET estimates derived using the standard FAO-PM crop coefficient approach.…”

Section: Weather-based Sensingmentioning

confidence: 99%

Advanced Monitoring and Management Systems for Improving Sustainability in Precision Irrigation

et al. 2017

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Globally, the irrigation of crops is the largest consumptive user of fresh water. Water scarcity is increasing worldwide, resulting in tighter regulation of its use for agriculture. This necessitates the development of irrigation practices that are more efficient in the use of water but do not compromise crop quality and yield. Precision irrigation already achieves this goal, in part. The goal of precision irrigation is to accurately supply the crop water need in a timely manner and as spatially uniformly as possible. However, to maximize the benefits of precision irrigation, additional technologies need to be enabled and incorporated into agriculture. This paper discusses how incorporating adaptive decision support systems into precision irrigation management will enable significant advances in increasing the efficiency of current irrigation approaches. From the literature review, it is found that precision irrigation can be applied in achieving the environmental goals related to sustainability. The demonstrated economic benefits of precision irrigation in field-scale crop production is however minimal. It is argued that a proper combination of soil, plant and weather sensors providing real-time data to an adaptive decision support system provides an innovative platform for improving sustainability in irrigated agriculture. The review also shows that adaptive decision support systems based on model predictive control are able to adequately account for the time-varying nature of the soil-plant-atmosphere system while considering operational limitations and agronomic objectives in arriving at optimal irrigation decisions. It is concluded that significant improvements in crop yield and water savings can be achieved by incorporating model predictive control into precision irrigation decision support tools. Further improvements in water savings can also be realized by including deficit irrigation as part of the overall irrigation management strategy. Nevertheless, future research is needed for identifying crop response to regulated water deficits, developing improved soil moisture and plant sensors, and developing self-learning crop simulation frameworks that can be applied to evaluate adaptive decision support strategies related to irrigation.

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“…The calculated Hargreaves potential evapotranspiration was modified using the cropcoefficient approach to estimate the potential evapotranspiration values for the model inputs (Farg et al 2012). …”

Section: [ Sin Sin + Cos Cos Sin ]mentioning

confidence: 99%

Precipitation Impacts on Groundwater Levels in the Ephemeral Holgate Lake: A MODFLOW Inquiry

Cervarich¹

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ii ACKNOWLEDGMENTS Dr. Johnson, for generously sharing her brain space and lab space. And for pulling me out of rabbit holes.Linley Mescher, for all the MODFLOW collaboration.PP and JMV, for the late night dinners and endless support.And to RC, for keeping the lights on.iii ABSTRACT Holgate Lake, an ephemeral lake located in southeast Portland, has a history of flooding and inundating residential areas. The appearance of the lake is hypothesized to be a function of precipitation-driven changes in groundwater levels. A model was developed using MODFLOW-NWT, a U.S. Geological Survey (USGS) modular hydrologic program, to analyze parameters contributing to the appearance of the lake. The model was most sensitive to changes in aquifer properties including hydraulic conductivity and storativity. The model displayed low sensitivity to changes in precipitation, evapotranspiration, and conductance of surface waters. Results from the analysis contribute to a better understanding of the surface-groundwater system, and could be used to assess flooding risks in the Holgate Lake area with additional model calibration.iv

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Estimation of Evapotranspiration ETc and Crop Coefficient Kc of Wheat, in south Nile Delta of Egypt Using integrated FAO-56 approach and remote sensing data

Cited by 58 publications

References 15 publications

Estimation of Crop Evapotranspiration Using Satellite Remote Sensing-Based Vegetation Index

Estimation of Crop Evapotranspiration Using Satellite Remote Sensing-Based Vegetation Index

Advanced Monitoring and Management Systems for Improving Sustainability in Precision Irrigation

Precipitation Impacts on Groundwater Levels in the Ephemeral Holgate Lake: A MODFLOW Inquiry

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