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Improved gross primary productivity estimation using semi empirical (PRELES) model for moist Indian sal forest

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  • Krishna, Dyvavani K.
  • Watham, Taibanganba
  • Padalia, Hitendra
  • Srinet, Ritika
  • Nandy, Subrata

Abstract

The significant role that forests play in regulating the carbon and water exchange is critical to mitigate climate change. The remote sensing data and models provide good means for estimating gross primary productivity (GPP) and evapotranspiration (ET), although they seldom face issues when implemented without proper calibration. The study compares the performance of empirical (TG model) and semi-empirical (PRELES) model in estimation of GPP and ET of Indian moist sal forest. PRELES-PREdict Light use efficiency, Evapotranspiration and Soil water predicted the GPP and ET adequately; GPP ranged from 1.09 to 19.73 gC m−2 day−1 with RMSE of 1.64 gC m−2 day−1 and ET from 0.25 to 5.31 mm day−1 with RMSE of 0.65 mm day−1. It was found that PRELES estimated GPP with higher accuracy compared to TG model (a reduced RMSE of 0.68 gC m−2 day−1). The study reveals, with site-specific parametrization, semi empirical model can better predict GPP and ET than empirical model.

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  • Krishna, Dyvavani K. & Watham, Taibanganba & Padalia, Hitendra & Srinet, Ritika & Nandy, Subrata, 2023. "Improved gross primary productivity estimation using semi empirical (PRELES) model for moist Indian sal forest," Ecological Modelling, Elsevier, vol. 475(C).
    • Handle: RePEc:eee:ecomod:v:475:y:2023:i:c:s0304380022002769
    DOI: 10.1016/j.ecolmodel.2022.110175
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    1. Laibao Liu & Lukas Gudmundsson & Mathias Hauser & Dahe Qin & Shuangcheng Li & Sonia I. Seneviratne, 2020. "Soil moisture dominates dryness stress on ecosystem production globally," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
    2. Minunno, F. & Peltoniemi, M. & Launiainen, S. & Aurela, M. & Lindroth, A. & Lohila, A. & Mammarella, I. & Minkkinen, K. & Mäkelä, A., 2016. "Calibration and validation of a semi-empirical flux ecosystem model for coniferous forests in the Boreal region," Ecological Modelling, Elsevier, vol. 341(C), pages 37-52.
    3. Huntzinger, D.N. & Post, W.M. & Wei, Y. & Michalak, A.M. & West, T.O. & Jacobson, A.R. & Baker, I.T. & Chen, J.M. & Davis, K.J. & Hayes, D.J. & Hoffman, F.M. & Jain, A.K. & Liu, S. & McGuire, A.D. & N, 2012. "North American Carbon Program (NACP) regional interim synthesis: Terrestrial biospheric model intercomparison," Ecological Modelling, Elsevier, vol. 232(C), pages 144-157.
    4. Hanqin Tian & Guangsheng Chen & Chaoqun Lu & Xiaofeng Xu & Daniel Hayes & Wei Ren & Shufen Pan & Deborah Huntzinger & Steven Wofsy, 2015. "North American terrestrial CO 2 uptake largely offset by CH 4 and N 2 O emissions: toward a full accounting of the greenhouse gas budget," Climatic Change, Springer, vol. 129(3), pages 413-426, April.
    5. Shvidenko, Anatoly & Schepaschenko, Dmitry & Nilsson, Sten & Bouloui, Yuri, 2007. "Semi-empirical models for assessing biological productivity of Northern Eurasian forests," Ecological Modelling, Elsevier, vol. 204(1), pages 163-179.
    6. Brendan Choat & Steven Jansen & Tim J. Brodribb & Hervé Cochard & Sylvain Delzon & Radika Bhaskar & Sandra J. Bucci & Taylor S. Feild & Sean M. Gleason & Uwe G. Hacke & Anna L. Jacobsen & Frederic Len, 2012. "Global convergence in the vulnerability of forests to drought," Nature, Nature, vol. 491(7426), pages 752-755, November.
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