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2021 | OriginalPaper | Chapter

Ground-Level Water Predication Using Time Series Statistical Model

Authors : Sandeep Kumar Mittal, Mamta Mittal, Muhammad Sajjad Ali Khan

Published in: Advances in Information Communication Technology and Computing

Publisher: Springer Singapore

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Abstract

With exponential increase in population, scarcity of water in Nation Capital of India, Delhi, has become the most critical issue over last few years. The change in climatic conditions, usage of lands and immense abstraction of water are plausible reasons for depletion of groundwater at a rapid rate. To deal with this issue, authors predict the groundwater level using time series model in various regions of Delhi. To understand the reasons of decline in groundwater level and its quality is necessary for the development and livelihood in all regions of Delhi. The results depict that decline in number of wells from 125 in year 2012 to 82 in the current year. Over the period of six years, lower rain falls and high population growth is the major reasons for depletion of groundwater level in Delhi. Along with this, the quality of ground water has been deteriorated which has also become a prime issue of concern.

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Metadata
Title
Ground-Level Water Predication Using Time Series Statistical Model
Authors
Sandeep Kumar Mittal
Mamta Mittal
Muhammad Sajjad Ali Khan
Copyright Year
2021
Publisher
Springer Singapore
Book
Advances in Information Communication Technology and Computing

Print ISBN: 978-981-15-5420-9

Electronic ISBN: 978-981-15-5421-6

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-981-15-5421-6_43