EGU21-15857, updated on 04 Mar 2021
https://doi.org/10.5194/egusphere-egu21-15857
EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

 Spatio-temporal characterization of rainfall using an innovative trend and discrete wavelet transformation approaches in Bhakra catchment, India

Neha Gupta and Sagar Chavan
Neha Gupta and Sagar Chavan
  • INDIAN INSTITUTE OF TECHNOLOGY, ROPAR, CIVIL ENGINEERING, India (2017cez0006@iitrpr.ac.in)

Using a high-resolution daily gridded rainfall data of 0.25° from the Indian Meteorological Department (IMD), the present study investigates the detailed characteristics of rainfall in the Bhakra Catchment from 1901 to 2019. The long term spatial and temporal rainfall variations in Bhakra Catchment are not well explored. The spatial pattern of rainfall regimes in this catchment is identified by estimating index like the precipitation concentration index (PCI) and seasonality index (SI). Extreme rainfall trends on annual and seasonal basis are examined using the innovative trend analysis (ITA) method. Reliability of ITA was assessed by comparing them with widely applied Mann–Kendall (MK) or modified Mann–Kendall (mMK) test results. Furthermore, the change in two halves of rainfall series is estimated using percent bias technique for estimating changes in rainfall. Changes in slopes are estimated by using Sen’s slope estimator (Q). Discrete wavelet transform (DWT) in conjunction with Sequential Mann–Kendall test (SQMK) is employed to find out the dominant periodicity in rainfall patterns. The effectiveness of the graphical method in qualitative analysis can be seen, while DWT is found efficient in identifying periodicity. Both positive and negative trends are detected in annual and seasonal time series over the study area. The outcomes of this study may be helpful in the planning and management of water resources projects in the catchment along with the planning of mitigation measures to alleviate the effects of climate change under extreme rainfall conditions.

How to cite: Gupta, N. and Chavan, S.:  Spatio-temporal characterization of rainfall using an innovative trend and discrete wavelet transformation approaches in Bhakra catchment, India, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15857, https://doi.org/10.5194/egusphere-egu21-15857, 2021.

This abstract will not be presented.