Estimating the Evaporative Cooling Effect of Irrigation within and above Soybean Canopy

Ghafarian, Fatemeh; Wieland, Ralf; Nendel, Claas

doi:10.3390/w14030319

Cited by 6 publications

(5 citation statements)

References 30 publications

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“…To quantify impacts on crop growth, ESS, and biodiversity, the DAKIS models agro-ecological systems via the SIMPLACE (Scientific Impact assessment and Modelling Platform for Advanced Crop and Ecosystem management) modelling framework [ 43 ]; www.simplace.net ) and two newly-developed stand-alone models on microclimate [ 44 , 45 ] and biodiversity (see SM Section 2.3.2 for details on the agro-ecological modelling components). The SIMPLACE framework captures numerous processes affecting biomass production, crop yield and nutrient content of a large range of crops, selected ESS like groundwater recharge, nitrate leaching, soil carbon sequestration, and GHG emissions in cropland and grassland systems.…”

Section: Resultsmentioning

confidence: 99%

The Digital Agricultural Knowledge and Information System (DAKIS): Employing digitalisation to encourage diversified and multifunctional agricultural systems

Mouratiadou¹,

Lemke²,

Chen³

et al. 2023

Environmental Science and Ecotechnology

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Section: Resultsmentioning

confidence: 99%

The Digital Agricultural Knowledge and Information System (DAKIS): Employing digitalisation to encourage diversified and multifunctional agricultural systems

Mouratiadou¹,

Lemke²,

Chen³

et al. 2023

Environmental Science and Ecotechnology

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“…Fig. 3 -Canto et al 2007;Madakarah et al 2019;Ghafarian et al 2022). By August 3, 2021, LST values continued to decline across the field, except for patches displaying elevated temperatures, potentially due to the absence of plants in those areas.…”

Section: Land Surface Temperature Spatial Variabilitymentioning

confidence: 94%

Evapotranspiration estimation using high-resolution aerial imagery and pySEBAL for processing tomatoes

Peddinti,

Nicolas,

Raij-Hoffman

et al. 2024

Preprint

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The utilization of high-resolution aerial imagery for assessing actual crop evapotranspiration (ETa) holds the potential to optimize the use of limited water resources in agriculture. Despite this potential, there is a shortage of information regarding the effectiveness of energy balance algorithms, initially designed for satellite remote sensing, in estimating ETa using aerial imagery. This study addresses this gap by employing the remote sensing model pySEBAL (Surface Energy Balance Algorithm for Land) in conjunction with high-resolution aerial imagery to estimate ETa for processing tomatoes. Throughout the 2021 growing season, an aircraft captured multispectral and thermal imagery over a processing tomato field near Esparto, California. Simultaneously, an eddy covariance flux tower within the field measured high-frequency turbulent fluxes and low-frequency biometeorology variables essential for evaluating the energy balance. The comprehensive assessment of energy balance components, including ETa, yielded compelling evidence that pySEBAL accurately estimated ETa at high spatial resolution. The root mean square error (RMSE) for various energy balance components were as follows: 33 Wm− 2 for latent heat flux, 29 Wm− 2 for sensible heat flux, 24 Wm− 2 for net radiation, and 10 Wm− 2 for soil heat flux. Additionally, ETa exhibited an RMSE of 0.26 mmd− 1. Notably, all components demonstrated an R2 exceeding 0.92. Moreover, the spatial mapping of ETa across the processing tomato field visually depicted the spatial variability associated with irrigation scheduling, crop development, areas affected by disease, and soil heterogeneity. This research underscores the value of high resolution spatial aerial imagery and pySEBAL algorithm for estimating ETa variability in the field, a crucial aspect for guiding precision irrigation management and ensuring the optimal use of limited water resources in agriculture.

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“…We also find that LAI and NDVI exert controls over land surface temperature. (Tan et al, 2018;Ghafarian et al, 2022). On both basin-wide and sub-basin scales of the Amazon, vegetation cooling effects have been shown to be much stronger during daytime than nighttime (Huang et al, 2022).…”

Section: Plant Traits and Regulation Of Land Surface Temperaturementioning

confidence: 99%

Influence of plant traits on water cycle processes in the Amazon Basin

Nguyen,

Santos

2024

Preprint

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Abstract. Plants play a key role in the soil-plant-atmosphere-climate hydrological continuum. Plants depend on the water cycle and, in return, several hydrological processes could be impacted via vegetation-induced mechanisms. Changes in plant composition are known to affect this relationship, however, detailed understanding on how plant characteristics, i.e., their traits, are seldom included in observational and modeling studies. Here we examine the effect of plant traits on water cycle processes in the Amazon Basin. We used remotely-sensed estimates of four plant traits, namely Specific Leaf Area (SLA), Leaf Dry Matter Content (LDMC), Leaf Phosphorus Content (LPC), Leaf Nitrogen Content (LNC), and two vegetation indices, the Normalised Difference Vegetation Index (NDVI), and Leaf Area Index (LAI), for 10 years between 2001 and 2010. We examined the relationship between plant traits and six parameters relevant for water cycle processes, namely Evapotranspiration (ET), Potential Evapotranspiration (PET), Vapour Pressure Deficit (VPD), Land Surface Temperature (LST) Day/Night and Soil Moisture (SM). We used multivariate and quantile regressions to analyse how plant traits explain the average and standard deviation in water cycle process parameters. We find that SLA, NDVI, and LAI exert the strongest effects across the whole of Amazon basin and the sub-basins, most important for the regulation of atmospheric water content and of land surface temperature, but little effect on the regulation of soil moisture content. These effects are exacerbated at extreme values of water process parameters, where plant traits exert an even stronger effect at low values of ET and PET and high values of VPD and LST. Leaf gas exchange traits are most important in comparison to the other traits, and these results also highlight that if water cycle process parameters achieve extreme values, plant traits are key to the persistence of hydrological processes fundamental to the resilience of the Amazon.

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Estimating the Evaporative Cooling Effect of Irrigation within and above Soybean Canopy

Cited by 6 publications

References 30 publications

The Digital Agricultural Knowledge and Information System (DAKIS): Employing digitalisation to encourage diversified and multifunctional agricultural systems

The Digital Agricultural Knowledge and Information System (DAKIS): Employing digitalisation to encourage diversified and multifunctional agricultural systems

Evapotranspiration estimation using high-resolution aerial imagery and pySEBAL for processing tomatoes

Influence of plant traits on water cycle processes in the Amazon Basin

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