Abstract

Quantifying the spatiotemporal variability of rainfall is the principal component for the assessment of the impact of climate change on the hydrological cycle. A better understanding of the quantification of variability and its trend is vital for water resources planning and management. Therefore, a multitude of studies has been dedicated to quantifying the rainfall variability over the years. Despite their importance for modelling rainfall variability, the studies mainly focused on the amount of rainfall and its spatial patterns. The studies investigating the spatial and temporal variability of rainfall across Central India, in general, and at multiscale, in particular, are limited. In this study, we used a Standardized Variability Index (SVI), based on information theory to investigate the spatiotemporal variability of rainfall. SVI is independent of the temporal scale, length of the data and can compare the rainfall variability at multiple timescales. Distinct spatial patterns were observed for information entropies at the monthly and seasonal scale. Grid points with statistically significant trends were observed and vary from monthly to seasonal scale. There is an increase in the variability of rainfall amount from South to North, indicating that spread of the rainfall is high in the South when compared to North of Central India. Trend analysis revealed there is changing behavior in the rainfall amount as well as rainy days, showing an increase in variability of rainfall over Central India, hence the high probability of occurrence of extreme events in the near future.

Highlights

  • MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.Licensee MDPI, Basel, Switzerland

  • The annual rainfall variability is more for the points corresponding to the South-west region

  • The Marginal Entropy (ME) of annual time series is more than the seasonal time series, i.e., the variability of annual rainfall is less than the seasonal rainfall

Read more

Summary

Introduction

MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Rainfall is a reliable feature for the Indian subcontinent and highly uncertain in space and time. Rain is the primary component of the hydrological cycle, describes the transfer of energy between earth and atmosphere. In the cyclic process of atmospheric circulation, there is a high impact of global warming-induced climate change on the components of the hydrological cycle and its variability [1]. There is a significant variation in the average rainfall, temperature, evaporation and change of rate, timing and distribution of rainfall [2]. The spatiotemporal variability of rainfall has a significant impact on agricultural productivity, and the Indian economy depends on the monsoon rains and accounts for 22% of Indian gross domestic product

Methods
Results
Discussion
Conclusion

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.