Total views : 199
Trend Analysis of Precipitation by MK Test in Kumaon Region of Uttarakhand (1901–2010)
Objective: To identify trend in annual precipitation time series using the M-K and Sen’s T-tests. Methods/Analysis: Climate change has disrupted the major climatic parameters at a global level. However, there is no equal change for all regions and have localized intensity especially in India. These changes should be identified nearby to manage the natural water resources. One of the most important climatic parameters is precipitation. As a starting point towards the apprehension of global climate change precipitation has been widely measured. The main objective of this study is to analyze the temporal variability of precipitation for the period 110 years, to enhance the hydrological status of the Uttarakhand districts of Kumaon region. The aim is to identify trend in annual precipitation time series using the M-K and Sen’s T tests. Sen’s estimator method has been used to estimate the extent of trend in precipitation. Before applying the M-K test for the trend in precipitation auto correlation effect is reduced. Finding: The analysis of M-K test shows non-significance increasing (positive) trend on annual basis. These areas experience a heavier rainfall for duration of shorter splash, which leads to very less scope for groundwater recharge and more runoff in these areas. Thus, these findings give a broad overview of the regional rainfall behavior in the study area. Applications/Improvements: The similar study can be carried out for other places as well with more locations for more diversity in the results attributing to the surroundings etc. to get a more clear and precise view about the trend in annual precipitation.
Mann-Kendall Tests, Non-Parametric Tests and Auto Correlation, Precipitation, Sen’s Estimator Tests.
- Kothawale DR, Rupakumar K. On the recent changes in surface temperature trends over India. Geophysical Research Letters. 2005 Sep; 32(18):1-4.
- Hingane LS. Is a signature of socio-economic impact written on the climate? Climatic Change. 2005; 32:91-101.
- Pant GB, Kumar KR. Chichester: John Wiley & Sons Ltd: Climates of South Asia. 1997 May.
- Arora M, Goel NK, Singh P. Evaluation of temperature trends over India. Hydrological Sciences Journal. 2005 Feb; 50(1):81-93.
- Dash SK, Jenamani RK, Kalsia SR. Panda SK. Some evidence of climate change in twentieth-century India. Climatic change. 2007 Dec; 85(3):299-321.
- Mishra N, Khare D, Shukla R, Singh L. A study of temperature Variation in Upper Ganga Canal Command India. Advances in Water Resource and Protection (AWRP). 2013 Jul; 1(3):1-7.
- Kumar Kalyani, Mishra N, Gupta S. Trend Analysis of Temperature by Mann-Kendall Test in the High Altitude Regions of Uttarakhand, India: AARJMD. 2014 Feb; 1(18):387-99.
- Kulkarni A, Von Storch H. Monte Carlo experiments on the effect of serial correlation on the Mann-Kendall test of trend. Meteorologische Zeitschrift. 1995 Jan; 4(2):82-5.
- Von Storch H, Navarra A. New York: Springer-Verlag: Analysis of Climate Variability-Applications of Statistical Techniques. 1995.
- Hirsch RM, Slack JR. Non-parametric trend test for seasonal data with serial dependence. Water Resources Research. 1984 Jun; 20(6):727-32.
- Mann HB. Non-parametric tests against trend. Econometrica. 1994; 13:163-71.
- Kendall MG. London: Charles Griffin: Rank Correlation Methods, 4th edition. 1975.
- Gilbert RO. NY: Wiley: Statistical Methods for Environmental Pollution Monitoring. 1987 Feb.
- Turgay Partal, Ercan Kahy. Trend analysis in Turkish precipitation data. Hydrological Processes. 2006 Jun; 20(9):2011-26.
- Sen PK. Estimates of the regression coefficient based on Kendall’s tau. Journal of the American Statistical Association. 1968; 63(4):1379-89.
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.