Dynamics of the superficial fluxes over a flooded rice paddy in southern Brazil

Diaz, Marcelo Bortoluzzi; Roberti, Débora Regina; Carneiro, Janaína Viário; Souza, Vanessa de Arruda; Moraes, Osvaldo L. L.

doi:10.1016/j.agrformet.2019.107650

Cited by 21 publications

(23 citation statements)

References 59 publications

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“…Diaz et al [39], showed the transpiration in CAS in fallow season (April to November) almost vanish, while evaporation dominates the ET. This behavior was also represented by MOD16 algorithm (Figure 7c,d).…”

Section: Sensitivity Of Mod16 Algorithm On the Accuracy Of Meteorologmentioning

confidence: 99%

“…The soil type at PRS is silt loam and in CAS is sandy clay loam, both typical flooded soil where rice is grown in Rio Grande do Sul state. More details about physical properties of the soil at the experimental sites are described in Timm et al [37] for PRS and in Diaz et al [39] for CAS.…”

Section: Site Descriptionmentioning

confidence: 99%

“…The PRS and CAS flux towers were equipped the sensors described in Table 1. Further details are described in References [37,[39][40][41].…”

Section: Meteorological and Flux Tower Measurementsmentioning

confidence: 99%

“…The EddyPro Advanced software (version 5.1, LI-COR) was used to process the flux data over half-hourly time scales. Further details of the configurations used are described in References [39,42].…”

Section: Et Experimental Data Processingmentioning

confidence: 99%

“…In general, PRS and CAS present similar behavior on the energy balance components. A detailed discussion about the energy partitioning over rice paddy, using the PRS dataset, is described in Timm et al [37] and using the CAS dataset, is described in Diaz et al [39].…”

Section: Energy Balance Analysismentioning

confidence: 99%

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Evaluation of MOD16 Algorithm over Irrigated Rice Paddy Using Flux Tower Measurements in Southern Brazil

Souza

Roberti

Ruhoff

et al. 2019

Water

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Evapotranspiration (ET) is an important component of the hydrological cycle. Understanding the ET process has become of fundamental importance given the scenario of global change and increasing water use, especially in the agricultural sector. Determining ET over large agricultural areas is a limiting factor due to observational data availability. In this regard, remote sensing data has been used to estimate ET. In this study, we evaluated the Moderate-Resolution Imaging Spectroradiometer (MODIS) land surface ET product estimates (hereafter MOD16 ET -MODIS Global Terrestrial Evapotranspiration Product) over two rice paddy areas in Southern Brazil, through the ET measured using the eddy covariance technique (hereafter EC). The energy balance components were evaluated during fallow and flooded seasons showing latent heat flux dominates in both seasons. The results showed that MOD16 ET underestimated EC measurements. Overall, the RMSE (root mean square error) ranged between 13.40 and 16.35 mm 8-day −1 and percent bias (PBIAS) ranged between −33.7% and −38.7%. We also assessed the ET (measured and estimated) main drivers, with EC yielding higher correlation against observed net radiation (R n ) and global radiation (R g ), followed by air temperature (Temp) and vapor pressure deficit (VPD), whilst MOD16 ET estimates yielded higher correlation against leaf area index (LAI) and fraction of photosynthetically active radiation (f PAR). The MOD16 algorithm was forced with meteorological measurements but the results did not improve as expected, suggesting a low sensitivity to meteorological inputs. Our results indicated when a water layer was present over the soil surface without vegetation (LAI around zero), the largest differences between EC measurements and MOD16 ET were found. In this period, the expected domain of soil evaporation was not observed in MOD16 ET physical processes partition, indicating the algorithm was not able to detect areas with high soil moisture. In general, the MOD16 ET product presented low accuracy when compared against experimental measurements over flooded rice paddy, suggesting more studies are necessary, in order to reduce uncertainties associated to the land cover conditions.

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Section: Sensitivity Of Mod16 Algorithm On the Accuracy Of Meteorologmentioning

confidence: 99%

Section: Site Descriptionmentioning

confidence: 99%

“…The PRS and CAS flux towers were equipped the sensors described in Table 1. Further details are described in References [37,[39][40][41].…”

Section: Meteorological and Flux Tower Measurementsmentioning

confidence: 99%

Section: Et Experimental Data Processingmentioning

confidence: 99%

Section: Energy Balance Analysismentioning

confidence: 99%

See 3 more Smart Citations

Evaluation of MOD16 Algorithm over Irrigated Rice Paddy Using Flux Tower Measurements in Southern Brazil

Souza

Roberti

Ruhoff

et al. 2019

Water

Self Cite

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Methane flux measurements in rice by static flux chamber and eddy covariance

Reba

Fong

Rijal

et al. 2020

Agrosystems Geosci & Env

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Understanding methane (CH4) fluxes from rice (Oryza sativa L.) at the field scale is paramount to reducing environmental impacts while ensuring global food security. Greenhouse gas (GHG) measurements at the plot scale using static flux chambers (SFC) have long informed the understanding of flux dynamics and have largely been the basis of global flux estimates. However, in many parts of the world, the landscapes where agricultural fluxes are generated come from larger fields. Eddy covariance (EC) can measure trace gases on larger fields, but there are few studies available quantifying CH4 emissions under typical practices at a field scale. Furthermore, few of these studies are from the U.S. Midsouth, the largest producer of U.S. rice. This study compares and quantifies field‐scale SFC and EC flux measurements on a large commercial system in northeastern Arkansas during the 2015 and 2016 growing seasons, following typical producer practices. Daily measured SFC CH4 fluxes did not differ from EC‐daily CH4 fluxes (p = .108). Total season CH4 emissions, calculated as the sum of daily fluxes ranged from 50 to 156 kg CH4 ha−1 season−1, with SFC reporting greater emissions than EC. Although SFC and EC‐daily flux measurements were similar early (p = .382) and late (p = .543) in the season, they differed mid‐season (p < .001) with SFC consistently reporting greater fluxes than EC. The findings of this study help unify season long plot‐scale and field‐scale flux measurements and signify an advancement of our understanding of GHG fluxes from rice systems.

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