A refined method for rapidly determining the relationship between canopy NDVI and the pasture evapotranspiration coefficient

Alam, Muhammad Shahinur; Lamb, David; Rahman, Muhammad Moshiur

doi:10.1016/j.compag.2018.02.008

Cited by 23 publications

(17 citation statements)

References 20 publications

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“…Whether calculated by the "big-leaf" or "dual-leaf" method, LAI remains the most significant determinant of canopy conductance [8,20], and it therefore plays an important role in the estimation of transpiration. It is evident from previous studies that transpiration is linked to the canopy LAI [24][25][26][27].…”

Section: Introductionmentioning

confidence: 99%

A Canopy Transpiration Model Based on Scaling Up Stomatal Conductance and Radiation Interception as Affected by Leaf Area Index

Alam

Lamb

Warwick

2021

Water

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Estimating transpiration as an individual component of canopy evapotranspiration using a theoretical approach is extremely useful as it eliminates the complexity involved in partitioning evapotranspiration. A model to predict transpiration based on radiation intercepted at various levels of canopy leaf area index (LAI) was developed in a controlled environment using a pasture species, tall fescue (Festuca arundinacea var. Demeter). The canopy was assumed to be a composite of two indistinct layers defined as sunlit and shaded; the proportion of which was calculated by utilizing a weighted model (W model). The radiation energy utilized by each layer was calculated from the PAR at the top of the canopy and the fraction of absorbed photosynthetically active radiation (fAPAR) corresponding to the LAI of the sunlit and shaded layers. A relationship between LAI and fAPAR was also established for this specific canopy to aid the calculation of energy interception. Canopy conductance was estimated from scaling up of stomatal conductance measured at the individual leaf level. Other environmental factors that drive transpiration were monitored accordingly for each individual layer. The Penman–Monteith and Jarvis evapotranspiration models were used as the basis to construct a modified transpiration model suitable for controlled environment conditions. Specially, constructed self-watering tubs were used to measure actual transpiration to validate the model output. The model provided good agreement of measured transpiration (actual transpiration = 0.96 × calculated transpiration, R2 = 0.98; p < 0.001) with the predicted values. This was particularly so at lower LAIs. Probable reasons for the discrepancy at higher LAI are explained. Both the predicted and experimental transpiration varied from 0.21 to 0.56 mm h−1 for the range of available LAIs. The physical proportion of the shaded layer exceeded that of the sunlit layer near LAI of 3.0, however, the contribution of the sunlit layer to the total transpiration remains higher throughout the entire growing season.

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Section: Introductionmentioning

confidence: 99%

A Canopy Transpiration Model Based on Scaling Up Stomatal Conductance and Radiation Interception as Affected by Leaf Area Index

Alam

Lamb

Warwick

2021

Water

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“…The d-index is 0.91, which means there is very good agreement between the datasets. An interest in estimating the K c with the vegetation index, mainly to generate information for irrigation scheduling, appears with the availability of high spatial and temporal resolution multispectral satellite systems and the emergence of ultrahigh spatial resolution aerial platforms such as RPAS [64]. This fact would help precision irrigation practices, especially at a regional scale.…”

Section: Ndvi-k C Relationshipmentioning

confidence: 99%

“…The isolated group with three NDVI values of approximately 0.8 and K c of 0.4 is related to the image corresponding to 074 DAS ( Figs 3B and 5B), where NDVI (depending only on vegetation) is high (� 0.8), while ETrF, which depends on more factors (e.g., soil moisture and climatic conditions), remained at approximately 0.4. One of the first works developed with this objective was performed by Bausch and Neale [65], and since then, numerous studies have found good results in estimating vegetation index-based K c using linear regression models in different agricultural areas around the world [63,64,66,67]. https://doi.org/10.1371/journal.pone.0235620.g008 Table 6 shows the soybean water productivity (WP) on two bases, calculated from the ETa estimated by MFAO methodology, and harvest machine-measured yield data.…”

Section: Ndvi-k C Relationshipmentioning

confidence: 99%

Mapping within‑field variability of soybean evapotranspiration and crop coefficient using the Earth Engine Evaporation Flux (EEFlux) application

et al. 2020

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Accurate information about the spatiotemporal variability of actual crop evapotranspiration (ETa), crop coefficient (K c) and water productivity (WP) is crucial for water efficient management in the agriculture. The Earth Engine Evapotranspiration Flux (EEFlux) application has become a popular approach for providing spatiotemporal information on ETa and Kc worldwide. The aim of this study was to quantify the variability of water consumption (ETa) and the K c for an irrigated commercial planting of soybeans based on the EEFlux application in the western region of the state of Bahia, Brazil. The water productivity (WP) for the fields was also obtained. Six cloud-free images from Landsat 7 and 8 satellites, acquired during the 2016/17 soybean growing season were used and processed on the EEFlux platform. The ETa from EEFlux was compared to that of the modified FAO (MFAO) approach using the following statistical metrics: Willmot's index of agreement (d-index), root mean square error (RMSE), mean absolute error (MAE) and mean bias error (MBE). The K c from EEFlux was compared to the K c used in the soybean field (K c FAO-based) and to the K c values obtained in different scientific studies using the d-index. A similar procedure was performed for WP. Our results reveal that EEFlux is able to provide accurate information about the variability of ETa and the K c of soybean fields. The comparison between ETa EEFlux and ETa MFAO showed good agreement based on the d-index, with values of 0.85, 0.83 and 0.89 for central pivots 1, 2 and 3, respectively. However, EEFlux tends to slightly underestimate ETa. The K c EEFlux showed good accordance with the K c values considered in this study, except in phase II, where a larger difference was observed; the average WP of the three fields (1.14 kg m-3) was higher than that in the majority of the previous studies, which is a strong indicator of the efficient use of water in the studied soybean fields. The study showed that EEFlux, an innovative and free tool for access spatiotemporal variability of ETa and Kc at global scale is very efficient to estimate the ETa and Kc on different growth stages of soybean crop.

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“…The geographical location of the study area with banana plots the crops or vegetation. An example of this is the Normalized Difference Vegetation Index (NDVI), which has demonstrated its usefulness as a bioindicator of aerial biomass production in vegetation (Jedermann et al, 2014;Machovina et al, 2016;Ye et al, 2020), also allows estimating the atmospheric demand of water in terms of the potential evapotranspiration (PE) (Alam et al, 2018;Zhou et al, 2021). Despite these important features, the Venezuelan banana sector does not usually contemplate the operational use of VIs in its management plans.…”

Section: Introductionmentioning

confidence: 99%

The relationship between the normalized difference vegetation index, rainfall, and potential evapotranspiration in a banana plantation of Venezuela

Olivares¹,

Paredes

Rey

et al. 2021

Sains Tanah J. Soil Sci. Agroclimatology

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<p>The water supply for rainfed crops such as bananas in the Aragua state of Venezuela is often uncertain, particularly towards the beginning of the rainy season (April-May). Where climatic conditions are seasonal, the temporal evolution of the NDVI (Normalized Difference Vegetation Index) closely accompanies the interannual variation of vegetation growth in response to thermal and hydric factors. The aim of the study is to assess the relationship between NDVI, rainfall and potential evapotranspiration during the period of January/2016 to December/2017 in a Venezuelan banana plantation. In this study, the NDVI derived from the GIMMS MODIS Terra product, the daily accumulated precipitation data (mm) and the daily mean air temperature (°C) were used as the only way to estimate the potential evapotranspiration. The results showed that the GMOD09Q1-based NDVI reflects reasonably well the spatiotemporal variation in biomass accumulation. Besides, this provides information on the water stress conditions in banana plants at the plot level. The influence of Precipitation and potential evapotranspiration on the NDVI was more evident when a lag of 1 month was considered in terms of the Spearman r, implying that there is a delay in the banana phonological response to rainfall changes and dryness conditions. However, due to its low spatial resolution (i.e. 250 m), it is not adequate for the identiﬁcation of banana wilt disease. Therefore, future studies are needed to assess other satellite-derived spectral indices for monitoring the health of banana plants over different sites in Venezuela.</p>

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A refined method for rapidly determining the relationship between canopy NDVI and the pasture evapotranspiration coefficient

Cited by 23 publications

References 20 publications

A Canopy Transpiration Model Based on Scaling Up Stomatal Conductance and Radiation Interception as Affected by Leaf Area Index

A Canopy Transpiration Model Based on Scaling Up Stomatal Conductance and Radiation Interception as Affected by Leaf Area Index

Mapping within‑field variability of soybean evapotranspiration and crop coefficient using the Earth Engine Evaporation Flux (EEFlux) application

The relationship between the normalized difference vegetation index, rainfall, and potential evapotranspiration in a banana plantation of Venezuela

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