Surface Energy Partitioning and Evaporative Fraction in a Water-Saving Irrigated Rice Field Article Swipe
Xiaoyin Liu
,
Junzeng Xu
,
Shihong Yang
,
Yuping Lv
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.3390/atmos10020051
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.3390/atmos10020051
Surface energy distribution in paddy fields and the ratio of latent heat flux (LE) to available energy, termed as the evaporative fraction (EF), are essential for an understanding of water and energy processes. They are expected to vary in different ways in response to changes in the soil moisture condition under water-saving irrigation practice. In this study, the diurnal and seasonal variations in energy distribution were examined based on the data measured by the eddy covariance system and corrected with enforcing energy balance closure by the EF method in water-saving irrigated rice paddies in 2015 and 2016. Soil heat flux (G) values were similar in magnitude to sensible heat flux (Hs) values, with both accounting for approximately 5% of the energy input. Both magnitudes of G and Hs were significantly lower than that of LE. Generally, EF in water-saving irrigated rice paddies was larger than that of other ecosystems, and varied within a narrow range from 0.7 to 1.0. Diurnally, EF decreased till noon and then increased slowly in the afternoon till sunset. It was found be less varied between 10:00 and 14:00. Seasonally, the alternative drying-wetting soil water conditions in water-saving irrigated rice paddies resulted in a change in the variation of the EF. The LE flux is the largest component of available energy, with EF being mostly higher than 0.9. EF, increasing consistently till the tillering stage, remaining high from the late tillering to milk stage, and then following a declining trend. The maximum EF (approaching 1.0) was found in the milk stage. The results of EF in water-saving irrigated rice paddies will be helpful for estimating daily or long temporal scale evapotranspiration (ET) by the EF method based on satellite-derived ET.
Related Topics
Concepts
Eddy covariance
Bowen ratio
Environmental science
Latent heat
Sensible heat
Evapotranspiration
Paddy field
Energy balance
Irrigation
Hydrology (agriculture)
Noon
Flux (metallurgy)
Water content
Available energy
Energy flux
Atmospheric sciences
Water balance
Agronomy
Ecosystem
Ecology
Meteorology
Energy (signal processing)
Chemistry
Mathematics
Geography
Physics
Geology
Statistics
Astronomy
Biology
Organic chemistry
Geotechnical engineering
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/atmos10020051
- https://www.mdpi.com/2073-4433/10/2/51/pdf?version=1548662172
- OA Status
- gold
- Cited By
- 18
- References
- 68
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2914895430
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2914895430Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/atmos10020051Digital Object Identifier
- Title
-
Surface Energy Partitioning and Evaporative Fraction in a Water-Saving Irrigated Rice FieldWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2019Year of publication
- Publication date
-
2019-01-28Full publication date if available
- Authors
-
Xiaoyin Liu, Junzeng Xu, Shihong Yang, Yuping LvList of authors in order
- Landing page
-
https://doi.org/10.3390/atmos10020051Publisher landing page
- PDF URL
-
https://www.mdpi.com/2073-4433/10/2/51/pdf?version=1548662172Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/2073-4433/10/2/51/pdf?version=1548662172Direct OA link when available
- Concepts
-
Eddy covariance, Bowen ratio, Environmental science, Latent heat, Sensible heat, Evapotranspiration, Paddy field, Energy balance, Irrigation, Hydrology (agriculture), Noon, Flux (metallurgy), Water content, Available energy, Energy flux, Atmospheric sciences, Water balance, Agronomy, Ecosystem, Ecology, Meteorology, Energy (signal processing), Chemistry, Mathematics, Geography, Physics, Geology, Statistics, Astronomy, Biology, Organic chemistry, Geotechnical engineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
18Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 3, 2024: 1, 2023: 3, 2022: 4, 2021: 3Per-year citation counts (last 5 years)
- References (count)
-
68Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.available | 15, 213 |
| abstract_inverted_index.component | 211 |
| abstract_inverted_index.condition | 49 |
| abstract_inverted_index.corrected | 78 |
| abstract_inverted_index.declining | 242 |
| abstract_inverted_index.decreased | 161 |
| abstract_inverted_index.different | 39 |
| abstract_inverted_index.enforcing | 80 |
| abstract_inverted_index.essential | 24 |
| abstract_inverted_index.following | 240 |
| abstract_inverted_index.increased | 166 |
| abstract_inverted_index.irrigated | 90, 139, 192, 261 |
| abstract_inverted_index.magnitude | 105 |
| abstract_inverted_index.practice. | 53 |
| abstract_inverted_index.remaining | 229 |
| abstract_inverted_index.tillering | 227, 234 |
| abstract_inverted_index.variation | 201 |
| abstract_inverted_index.Diurnally, | 159 |
| abstract_inverted_index.Generally, | 135 |
| abstract_inverted_index.accounting | 114 |
| abstract_inverted_index.conditions | 189 |
| abstract_inverted_index.covariance | 75 |
| abstract_inverted_index.estimating | 268 |
| abstract_inverted_index.increasing | 223 |
| abstract_inverted_index.irrigation | 52 |
| abstract_inverted_index.magnitudes | 123 |
| abstract_inverted_index.processes. | 32 |
| abstract_inverted_index.variations | 61 |
| abstract_inverted_index.Seasonally, | 183 |
| abstract_inverted_index.alternative | 185 |
| abstract_inverted_index.ecosystems, | 148 |
| abstract_inverted_index.evaporative | 20 |
| abstract_inverted_index.(approaching | 247 |
| abstract_inverted_index.consistently | 224 |
| abstract_inverted_index.distribution | 2, 64 |
| abstract_inverted_index.water-saving | 51, 89, 138, 191, 260 |
| abstract_inverted_index.approximately | 116 |
| abstract_inverted_index.significantly | 129 |
| abstract_inverted_index.understanding | 27 |
| abstract_inverted_index.drying-wetting | 186 |
| abstract_inverted_index.satellite-derived | 282 |
| abstract_inverted_index.evapotranspiration | 274 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 90 |
| corresponding_author_ids | https://openalex.org/A5101542078, https://openalex.org/A5108782197 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| corresponding_institution_ids | https://openalex.org/I163340411, https://openalex.org/I4210099662 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/6 |
| sustainable_development_goals[0].score | 0.49000000953674316 |
| sustainable_development_goals[0].display_name | Clean water and sanitation |
| citation_normalized_percentile.value | 0.80405288 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |