Spatial and Temporal Trend Analysis of Rainfall Distribution in Nambiyar Watershed, Tamil Nadu

nbsp         R S Libina; R Jegankumar; K Prakash; D Venkita Surya; S P Dhanabalan; M A Arya   nbsp

doi:10.53989/bu.ge.v10i2.4

Article

VIEWS 653
PDF 259

Geo-Eye

DOI: 10.53989/bu.ge.v10i2.4

Year: 2021, Volume: 10, Issue: 2, Pages: 18-25

Original Article

Spatial and Temporal Trend Analysis of Rainfall Distribution in Nambiyar Watershed, Tamil Nadu

R S Libina ¹, R Jegankumar ², K Prakash ³, D Venkita Surya ¹, S P Dhanabalan ³, M A Arya ¹

¹ Research Scholar, Department of Geography, Bharathidasan University, Tiruchirappalli, Tamil Nadu
² Professor and Head, Department of Geography, Bharathidasan University, Tiruchirappalli, Tamil Nadu
³ ICSSR Doctoral Research Fellow, Department of Geography, Bharathidasan University, Tiruchirappalli, Tamil Nadu

Received Date:12 June 2021, Accepted Date:27 September 2021

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

This study is an attempt to comprehend the spatial and temporal trend of rainfall distribution in the Nambiyar watershed. The daily rainfall data was processed for the period from 1988 to 2018 to map the spatial distribution and analyse the temporal trend of rainfall. The results reveals that mean annual rainfall received in the watershed is 1026.81 mm. Statistical techniques like Mann- Kendall test and Sen’s Slope estimator were used to analyse presence of trend and correlation of variables. Among four seasons northeast monsoon contributes around 47 per cent (482.57 mm) of the total rainfall. The results brought out the fact that annual rainfall of the watershed does not exhibit any significant trend at α=0.05 or 95% of confidence level. Agricultural and allied activities which requires adequate irrigation is determined by the rainfall received in this watershed. Hence this study brings out the spatial and temporal pattern of rainfall distribution in Nambiyar watershed.

Keywords: Rainfall trend, GIS, Sen's slope, Mann-Kendall test

References

Sridhar SI, Raviraj A. Statistical Trend Analysis of Rainfall in Amaravathi River Basin Using Mann-Kendall Test. Current World Environment. 2017;12(1):89–96. Available from: http://dx.doi.org/10.12944/CWE.12.1.11
ABP, Khare D, PKM, Singh L. Trend Analysis Of Rainfall, Temperature And Runoff Data: A Case Study Of Rangoon Watershed In Nepal. GIAP Journals. 2017;5(3). Available from: https://doi.org/10.18510/ijsrtm.2017.535
Praveen B, Talukdar S, Shahfahad. Analyzing trend and forecasting of rainfall changes in India using non-parametrical and machine learning approaches. Sci Rep. 2020;10(10342). Available from: https://doi.org/10.1038/s41598-020-67228-7
Júnior JBC, Lucena RL. Analysis of Precipitation Using Mann-Kendall and Kruskal-Wallis Non-Parametric Tests. Mercator. 2020;19:1–14. Available from: https://doi.org/10.4215/rm2020.e19001
John A, Brema J. Rainfall Trend Analysis By Mann-Kendall Test For Vamanapuram River Basin. International Journal of Civil Engineering and Technology. 2018;9(13):1549–1556.
Krishnaiah YV. Rainfall Analysis and Rainfall Recharge of the Papagni River Basin. National Georaphical Journal of India. 2014;60(1):83–96.
Singh V, Dev P. 50 year Rainfall Data Analysis and Future trend in Saharanpur Region. Mausam. 2012;63(1):55–64. Available from: https://doi.org/10.54302/mausam.v63i1.1455
Das J, Mandal T, Saha P, Bhattacharya SK. Varibility and Trends of Rainfall using Non-Paranmetric Approaches. A Case Study of Semi-Arid Area. Mausam. 2019;71(1):33–44.
Parthasarathy B, Dhar ON. Trend Analysis of Annual Indian Rainfall, Indian Institute of Tropical Meteorology. Hydrological Sciences-Bulletin. 1975;XX(26):257–260.
Sen P. Estimates of the Regression Coefficient Based on Kendall's Tau. Journal of the American Statistical Association. 1968;63(324):1379–1389. Available from: https://doi.org/https://doi:10.2307/2285891
Pal AB, Khare D, Mishra PK, Singh L. Trend analysis of rainfall, temperature and runoff data: a case study of Rangoon watershed in nepal. Technology & Management. 2017;5(3):21–38. Available from: https://doi.org/10.18510/ijsrtm.2017.535
Hinge G, Mazumdar M, Deb S. District-level assessment of changes in extreme rainfall indices in Barak and other basins in Indian Himalayan states: risks and opportunities. Model. Earth Syst. Environ. 2021;(8) 1145–1155. Available from: https://doi.org/10.1007/s40808-021-01152-1
Arumugam P, Karthik SM. Stochastic Modelling in Yearly Rainfall at Tirunelveli District. (pp. 1852-1858) 2018.
Jeremy MG, Taylor. Kendall's and Spearman's Correlation Coefficients in the Presence of a Blocking Variable. Biometrics. 1987;43(2):409–416. Available from: https://doi.org/https://doi:10.2307/2531822
Mann H. Nonparametric Tests Against Trend. Econometrica. 1945;13(3):245–259. Available from: https://doi.org/10.2307/1907187
Zavoianu I. Morphometry of Drainage Basins. (pp. 10-20) Elsevier. 1985.
Hassan SM, Adefolalu DO, Sani M. Recent Rainfall Trends in the FCT. Transactions Institute of Indian Geographers. 2009;31(1):51–55.
Mills TC. Modelling Precipitation trends in England and Wales. Meteorology Applications. 2005;12:169–176. Available from: https://doi.org/10.1017/S1350482705001611
Praveen B, Talukdar S, Shahfahad, SM, Mondal J, Sharma P, et al. Shahfahad et al. analysing trend and forecasting of rainfall changes in India using non-parametrical and machine learning approaches. Sci Rep. 2020;10(10342). Available from: https://doi.org/10.1038/s41598-020-67228-7
Gadedjisso-Tossou A, Adjegan KI, Kablan AK. Rainfall and Temperature Trend Analysis by Mann-Kendall Test and Significance for Rainfed Cereal Yields in Northern Togo. Sci. 2021;3(1):17. Available from: https://doi.org/10.3390/sci3010017

Copyright

© 2021 Libina et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Published By Bangalore University, Bengaluru, Karnataka