English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Due to climate change, the rainfall pattern has changed, which ultimately either cause flood or drought in any region of the world. Hence, a rainfall variability analysis helps to manage the water resources better. Rainfall variability analysis of a long term at particular area reveals vital information about past and future climate. The study's objective was to analyse the rainfall variability and intensity of long term monthly rainfall data (1982–2018) using the Precipitation Concentration Index (PCI). Data was collected from Punjab Agricultural University, Regional Research Station, located at Bathinda, India. The PCI was calculated for the annual, winter, pre-monsoon, monsoon, post-monsoon season, and decadal scale. Results have outlined that PCIAnnual ranges from the lowest of 14.96 in 2006 to the highest of 43.82 in 2000, and the average of 37 years is 23.22. About ≈59.5% of the year PCIAnnual was characterised by Strong Irregularity of Precipitation Distribution (SIPD, PCIAnnual&gt; 20), an indication of SIPD within the 37 years. While ≈2.7% of the year recorded annual value within the moderate irregular range (10&lt;PCIAnuual&lt;15), which indicates an irregular rainfall distribution (MIPD) and concentration across the months. Similarly, the precipitation concentration in China was also found strongly irregular in the western and northern parts of the northwest and the northern region of the Tibetan Plateau. The study recommends that the Bathinda Development Authority (BDA) may use and adopt these results and redevelop the existing groundwater recharge structures (pond) and artificial recharge structures.

Rainfall variability analysis using Precipitation Concentration Index: a case study of the western agro-climatic zone of Punjab, India