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Multi-point sampling for improved throughfall measurement from tree plantations

Abstract

Key message

Based on a large set of experimental data, this research shows a significant spatial-variation of throughfall (\(\mathrm{TF}\)) underneath canopies and proposes multi-point sampling approach for precise TF measurements.

Abstract

Throughfall (\(\mathrm{TF}\)) exhibits excessive spatial variability in its measurements under a tree canopy. This study proposes multiple sampling for more accurate \(\mathrm{TF}\) estimation, suggesting positioning configuration of receptacles under trees. Total 106 rainfall (R) events of cumulative rainfall depth 1741.5 mm that occurred during monsoon seasons of 2017–18 were considered. Single-factor ANOVA analysis showed significant variation in TF under nine different plantations. Relative \(\mathrm{TF}\) (\({\mathrm{TF}}^{{\prime}}\)) varied from 56.4 to 84.2% with a mean of 71.7% of R. For three event classes for R (2.8–20 mm), (20–40 mm), and > 40 mm, mean \({\mathrm{TF}}^{{\prime}}\) values were 71%, 73%, and 74%, respectively. As expected, the spatial variability of \(\mathrm{TF}\) decreased with increasing rainfall depths; the rainfall events smaller than 2.8 mm were completely retained by the tree canopy, implying that the interception is high during small magnitude rains. The lowest mean relative difference and root mean square error of relative difference (RMSE_RD) values were obtained for the receptacles placed at a distance of 100 cm, 150 cm, and 200 cm from the tree stem, exhibiting \(\mathrm{TF}\) sampling at the middle of the canopy radius to be more stable (in time) than towards canopy edge or very near to the tree stem. \(\mathrm{TF}\) inconsistency on either side of the tree canopy represents the variability of \(\mathrm{TF}\) with the direction from tree stem. Thus, \(\mathrm{TF}\) varied with both location and direction under a tree canopy. \(\mathrm{TF}\) obtained using the proposed multi-sampling procedure showed significantly lower variability than that measured conventionally at a random point under a tree canopy, and thus, underscores its importance in formulation of a throughfall sampling strategy.

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Data availability statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Abbreviations

\(\mathrm{TF}\) :

Throughfall

SF:

Stem flow

I c :

Interception loss

LAI:

Leaf area index

R :

Rainfall

\(\mathrm{TF }{^{\prime}}:\) :

Relative throughfall

r :

Correlation coefficient

r 2 :

Regression coefficient or coefficient of determination

SD:

Standard deviation

CV:

Coefficient of variation

l:

Liter

ml:

Milli-liter

mm:

Milli-meter

a.m.:

Ante meridiem

MRD:

Mean relative difference (symbol: \({\overline{\delta }}_{i,p}\))

VRD:

Variance of the relative difference (symbol: \(\sigma {(\delta )}_{i,p}^{2})\))

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Acknowledgements

The authors are thankful to Digital India Corporation (formerly Media Lab Asia), Information Technology Research Academy (ITRA) under Ministry of Electronics and Information Technology (MeitY), Government of India (Grant no: ITRA/15(67)/WATER/IGLQ/01), for providing the financial support to conduct this experiment. The authors thank to IIT Kharagpur administration for providing the necessary facilities and administrative support. We also thank Mr. Harsh Beria, a Ph.D. research scholar at the University of Lausanne, Lausanne, Switzerland for his keen interest in this study and offering his valuable suggestions. We would like to acknowledge anonymous reviewers and editor of this Journal for their constructive comments and suggestions to improve the quality of the manuscript.

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Correspondence to Chitra Shukla.

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Shukla, C., Tiwari, K.N. & Mishra, S.K. Multi-point sampling for improved throughfall measurement from tree plantations. Trees (2021). https://doi.org/10.1007/s00468-021-02202-y

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Keywords

  • Throughfall
  • Leaf area index
  • Tree plantations
  • Rainfall events
  • Receptacles