Establishment of rainfall partitioning parameters for tea plantations

ABSTRACTTea is a popular crop in Asia and Africa, yet only limited information on tea watershed hydrology is available. This study attempts to experimentally establish the rainfall partitioning parameters (RPPs), namely throughfall (TF), stemflow (SF), and rainfall interception (IC), for a plantation of 27-year-old tea plants grown in West Bengal, India. The relative proportions of TF, SF and IC were 59–89%, 0.12%, and 10–40% with coefficients of variation of 10%, 29%, and 27%, respectively. The SF proportion, being insignificant (≤2%), can be omitted. RPP responses were also analysed against rainfall depth, intensity, and duration. All RPPs except SF showed an exponential decay with rainfall depth. The fitted/validated models were evaluated for goodness of fit using coefficient of determination, mean absolute error, root mean square error, and Nash-Sutcliffe efficiency as error metrics. These results have pragmatic significance in tea watershed hydrology.KEYWORDS: rainfall eventsrainfall partitioningrainfall interceptionstemflowtea watershed hydrologythroughfall Editor A. Fiori Associate Editor D. PennaEditor A. Fiori Associate Editor D. PennaAcknowledgementsThe authors are thankful to Digital India Corporation (formerly Media Lab Asia), Information Technology Research Academy (ITRA) under the 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 the administration of IIT Kharagpur for providing the necessary facilities and administrative support.Disclosure statementNo potential conflict of interest was reported by the author(s).Data availabilityThe data supporting this study’s findings was experimentally obtained and is available from the corresponding author upon reasonable request.Supplementary materialSupplemental data for this article can be accessed online at https://doi.org/10.1080/02626667.2023.2182211Additional informationFundingThis work was supported by the Digital India Corporation (formerly Media Lab Asia), Information Technology Research Academy (ITRA), under the Ministry of Electronics and Information Technology (MeitY), Government of India. [ITRA/15(67)/ WATER/IGLQ/01].