Water vapor flux in tropical lowland rice
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A field experiment was conducted at Indian Council of Agricultural Research-National Rice Research Institute, Cuttack, Odisha, India in the dry seasons of 2015 and 2016 to assess the water vapor flux (FH2O) and its relationship with other climatic variables. The FH2O and climatic variables were measured by an eddy covariance system and a micrometeorological observatory. Daily mean FH2O during the dry seasons of 2015 and 2016 were 0.009–0.092 g m−2 s−1 and 0.014–0.101 g m−2 s−1, respectively. Seasonal average FH2O was 14.6% higher in 2016 than that in 2015. Diurnal variation for FH2O showed a bell-shaped curve with its peak at 13:30–14:00 Indian Standard Time (IST) in both the years. Carbon dioxide flux was found higher with rise in FH2O. This relationship was stronger at higher vapor pressure deficit (VPD) (20 ≤ VPD ≤ 40 and VPD > 40 hPa). The FH2O showed significant positive correlation with latent heat flux, net radiation flux, photosynthatically active radiation, air, water and soil temperatures, shortwave down and upwell radiations, maximum and minimum temperatures, evaporation, and relative humidity in both the years. Principal component analysis showed that FH2O was very close to latent heat flux in both the years (Pearson correlation coefficient close to 1). The two-dimensional observation map of the principal component F1 and F2 showed the observations taken during the vegetative stage and panicle initiation stage, and flowering stage and maturity stage were closer to each other. It can be concluded that the most important climatic variables controlling the FH2O were latent heat of vaporization, net radiation, air temperature, soil temperatures, and water temperature.
KeywordsNet ecosystem exchange of carbon dioxide Eddy covariance Water vapor flux Principal component analysis
The authors sincerely acknowledge the scientists, students, and technical staffs who have maintained the eddy covariance site since its establishment.
The work has been supported by the grant of National Innovations on Climate Resilient Agriculture (NICRA), Indian Council of Agricultural Research, New Delhi.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
- Anonymous (2018) https://www.statista.com/statistics/271969/world-rice-acreage-since-2008/ visited on 6th July 2018.
- Attarod, P., Komori, D., Hayashi, K., Aoki, M., Ishida, T., Fukumura, K., Boonyawat, S., Polsan, P., Tongdeenok, P., Somboon, P., & Punkngum, S. (2005). Comparison of the evapotranspirations among a paddy field, cassava plantation and teak plantation in Thailand. Journal of Agricultural Meteorology, 60(5), 789–792.CrossRefGoogle Scholar
- Aubinet, M., Grelle, A., Ibrom, A., Rannik, Ü., Moncrieff, J., Foken, T., Kowalski, A. S., Martin, P. H., Berbigier, P., Bernhofer, C., Clement, R., Elbers, J., Granier, A., Grünwald, T., Morgenstern, K., Pilegaard, K., Rebmann, C., Snijders, W., Valentini, R., & Vesala, T. (2000). Estimates of the annual net carbon and water exchange of forests: the EUROFLUX methodology. Advances in Ecological Research, 30, 113–175.Google Scholar
- Burba, G. (2013). Eddy covariance method. Lincoln: Li-COR Biogeosciences.Google Scholar
- Chatterjee, D., Tripathi, R., Chatterjee, S., Debnath, M., Shahid, M., Bhattacharyya, P., Swain, C. K., Tripathy, R., Bhattacharya, B. K., & Nayak, A. K. (2019). Characterization of land surface energy fluxes in a tropical lowland rice paddy. Theoretical and Applied Climatology, 136(1-2), 157–168. https://doi.org/10.1007/s00704-018-2472-y.CrossRefGoogle Scholar
- Huang, Z., Dong, X., Jiang, G., & Yuan, W. (2002). Primary studies on the daily dynamic changes of photosynthesis and transpiration of Salix psammophila. Acta Botanica Boreali-Occidentalia Sinica, 22(4), 817–823.Google Scholar
- Klosterhalfen, A., Graf, A., Brüggemann, N., Drüe, C., Esser, O., González-Dugo, M. P., Heinemann, G., Jacobs, C. M., Mauder, M., Moene, A. F., & Ney, P. (2019). Source partitioning of H2O and CO2 fluxes based on high-frequency eddy covariance data: a comparison between study sites. Biogeosciences, 16(6), 1111–1132.CrossRefGoogle Scholar
- Kumagai, T. O., Saitoh, T. M., Sato, Y., Takahashi, H., Manfroi, O. J., Morooka, T., Kuraji, K., Suzuki, M., Yasunari, T., & Komatsu, H. (2005). Annual water balance and seasonality of evapotranspiration in a Bornean tropical rainforest. Agricultural and Forest Meteorology, 128(1-2), 81–92.CrossRefGoogle Scholar
- Law, B. E., Falge, E., Gu, L. V., Baldocchi, D. D., Bakwin, P., Berbigier, P., Davis, K., Dolman, A. J., Falk, M., Fuentes, J. D., & Goldstein, A. (2002). Environmental controls over carbon dioxide and water vapor exchange of terrestrial vegetation. Agricultural and Forest Meteorology, 113(1), 97–120.CrossRefGoogle Scholar
- Massmann, A., Gentine, P., Lin, C.. (2018). When does vapor pressure deficit drive or reduce evapotranspiration?. arXiv preprint arXiv:1805.05444.Google Scholar
- Mauder, M., Foken, T. (2011). Documentation and instruction manual of the eddy covariance software package TK3, Work Report University of Bayreuth, Dept. of Micrometeorology, ISSN: 1614-8916, pp. 46, 58.Google Scholar
- Nay-Htoon, B., Xue, W., Lindner, S., Cuntz, M., Ko, J., Tenhunen, J., Werner, C., & Dubbert, M. (2018). Quantifying differences in water and carbon cycling between paddy and rainfed rice (Oryza sativa L.) by flux partitioning. Plos One, 13(4), e0195238. https://doi.org/10.1371/journal.pone.0195238.CrossRefGoogle Scholar
- Pathak H, Nayak AK, Jena M, Singh ON, Samal P and Sharma SG (Eds.) (2018) Rice Research for Enhancing Productivity, Profitability and Climate Resilience, ICAR-National Rice Research Institute, Cuttack, Odisha, p 527.Google Scholar
- Perez-Priego, O., Katul, G., Reichstein, M., El-Madany, T. S., Ahrens, B., Carrara, A., Scanlon, T. M., & Migliavacca, M. (2018). Partitioning eddy covariance water flux components using physiological and micrometeorological approaches. Journal of Geophysical Research: Biogeosciences, 123(10), 3353–3370.Google Scholar
- Reichstein, M., Falge, E., Baldocchi, D., Papale, D., Aubinet, M., Berbigier, P., Bernhofer, C., Buchmann, N., Gilmanov, T., Granier, A., & Grünwald, T. (2005). On the separation of net ecosystem exchange into assimilation and ecosystem respiration: review and improved algorithm. Global Change Biology, 11(9), 1424–1439. https://doi.org/10.1111/j.1365-2486.2005.001002.x.CrossRefGoogle Scholar
- Schneider, T., O’Gorman, P. A., & Levine, X. J. (2010). Water vapor and the dynamics of climate changes. Reviews of Geophysics, 48(3), 1–22. https://doi.org/10.1029/2009RG000302.
- Shekhar DC (2013) Greenhouse gas emissions CH4, CO2 and N2O from a newly flooded hydroelectric reservoir in subtropical South Asia: the case of Nam Theun 2 Reservoir, Lao PDR. Doctoral dissertation, Université Paul Sabatier-Toulouse III.Google Scholar
- Swain CK, Bhattacharyya P, Singh NR, Neogi S, Sahoo RK, Nayak AK, Zhang G, Leclerc MY (2016). Net ecosystem methane and carbon dioxide exchange in relation to heat and carbon balance in lowland tropical rice. Ecological Engineering, 95, 364–374. https://doi.org/10.1016/j.ecoleng.2016.06.053.CrossRefGoogle Scholar
- Swain, C. K., Bhattacharyya, P., Nayak, A. K., Singh, N. R., Chatterjee, D., Dash, P. K., Neogi, S., & Pathak, H. (2018a). Temporal variation of energy fluxes during dry season in tropical lowland rice. MAPAN-Journal of Metrology society of India, 33, 241–251. https://doi.org/10.1007/s12647-018-0260-x.CrossRefGoogle Scholar
- Swain, C. K., Nayak, A. K., Bhattacharyya, P., Chatterjee, D., Chatterjee, S., Tripathi, R., Singh, N. R., & Dhal, B. (2018b). Greenhouse gas emissions and energy exchange in wet and dry season rice: eddy covariance-based approach. Environmental Monitoring Assessment, 190, 423. https://doi.org/10.1007/s10661-018-6805-1.CrossRefGoogle Scholar
- Tseng, K. H., Tsai, J. L., Alagesan, A., Tsuang, B. J., Yao, M. H., & Kuo, P. H. (2010). Determination of methane and carbon dioxide fluxes during the rice maturity period in Taiwan by combining profile and eddy covariance measurements. Agricultural and Forest Meteorology, 150(6), 852–859.CrossRefGoogle Scholar