Statical Analysis of Rainfall Data: A Case Study of Hamirpur District, Himachal Pradesh

Author: Prithi Pal Singh and M.R. Sharma

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Abstract

Rainfall analysis is crucial for designing engineering projects and managing water resources. This paper focuses on the statistical study of rainfall in Hamirpur District, Himachal Pradesh, over a 30-year period, aiming to provide essential information for water resource planners, farmers and urban planners in the region. Mean, standard deviation, coefficient of variation, skewness, and kurtosis of monthly and annual rainfall were computed. Results revealed an unpredictable rainfall pattern, emphasizing the need for accurate input values in engineering design and crop planning. The study utilized various plotting position formulae and probability distribution functions to analyse the return period of yearly rainfall, identifying the Chegodayev technique as the most fitting distribution for this purpose. The projected rainfall for 5, 10, 50, 100, and 150 years return periods are 1279.57 mm, 1362.06 mm, 2021.97 mm, 2846.86 mm, and 3671.76 mm, respectively. This research contributes valuable insights into the specific rainfall dynamics of Hamirpur District, Himachal Pradesh, enhancing the relevance of the findings for local water management and infrastructure planning. The study faced challenges in dealing with the inherent unpredictability of rainfall patterns, particularly in months with lower variability. Additionally, ensuring the accuracy of input values for engineering structures and crop planning posed a significant challenge. This research makes significant contributions by providing in-depth statistical insights into the rainfall patterns of Hamirpur District. The identification of the Chegodayev technique as the optimal method for analysing return periods enhances the accuracy of rainfall projections for various planning horizons. The findings serve as a valuable resource for water resource planners, farmers and urban planners, facilitating informed decision-making in the development of engineering structures and crop planning strategies. The study underscores the importance of robust statistical analyses in understanding and managing the variability of rainfall, thereby contributing to the resilience and sustainability of water-related projects.

Keywords

Statistical Analysis, Hamirpur (H.P.), Return Period, Rainfall Data

Conclusion

Statistical analysis of rainfall data of Hamirpur District (H.P.) for (1994–2023) was done to understand the rainfall pattern of the Hamirpur District. The mean, standard deviation and coefficient of variation of yearly and monthly rainfall were determined to check the rainfall variability. From the calculated results, the rainfall pattern is found to be erratic. The greatest rainfall of 1728.20 mm occurred in 1997, followed by 1569.90 mm in 2006 while the minimum rainfall of 817.20 mm occurred in 2017, and average annual rainfall for the 30-year period is 1274.45 mm. The highest mean rainfall value is in August (374.19 mm) and the least is in November (15.31 mm). Generally, A high variability is noted in rainfall data for October, November and December (137.74%, 186.46% and 133.70%) respectively and lower variability in rainfall for July, August and September (36.04%, 30.61% and 39.58%) respectively. Agriculture engineers, farmers, and planners of water resources will all benefit from this analysis. It will provide assistance to them in determining the availability of water and design the appropriate storage. For instance, given the very unpredictable rainfall pattern, good drainage systems in areas where they do not already exist can be properly designed which will avoid flooding, in agricultural stabilization and also offer farmers security when making long-term investments. It will also aid in a better understanding of climate and rainfall patterns on a regional and global scale. Once adequate data becomes available, it is recommended that similar studies be performed for other districts of Himachal Pradesh. Short duration storms which higher intensities, as opposed to longer storms with higher constant loading, can have different effects on drainage systems. The findings of this study lay the groundwork for future research endeavors in the field of rainfall analysis and water resource management. Subsequent studies could explore the integration of advanced meteorological models and climate change projections to enhance the accuracy of long-term rainfall predictions. Additionally, investigations into the impact of unpredictable rainfall patterns on specific agricultural practices and urban infrastructure development could provide valuable insights for adaptive planning. The incorporation of emerging technologies, such as remote sensing and machine learning, could further refine our understanding of regional rainfall variations and contribute to the development of more robust engineering solutions and sustainable water management strategies. It is important to declare that there is no conflict of interest associated with the research presented in this paper. The authors have conducted this study with a commitment to scientific integrity and objectivity, free from any external influences that could compromise the validity or impartiality of the findings. The research is solely aimed at contributing to the scientific community's understanding of rainfall patterns in Hamirpur District, Himachal Pradesh, and providing practical insights for water resource planning and infrastructure development.

References

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How to cite this article

Prithi Pal Singh and M.R. Sharma (2023). Statical Analysis of Rainfall Data: A Case Study of Hamirpur District, Himachal Pradesh. Biological Forum – An International Journal, 15(1): 737-742.