Spatio-Temporal Mechanisms of Rainfall in Kalaburagi District: An Analysis of Trends and Variability

The study used data from 11 taluks to analyse the changes and variability in annual and seasonal rainfall in the Kalaburagi district between 2016 and 2022. Sen Slope and Mann-Kendall analyses were used to evaluate trends, while the coefficient of variation was used to measure rainfall variability. The mean rainfall was calculated using simple mathematical formulas. The findings showed minimal seasonal and yearly variability, with the exception of the southwest monsoon season. The district as a whole as well as all 11 taluks consistently saw a rise in rainfall, according to annual Sen slope research. However, during the northeast monsoon season, negative trends were observed in Aland and Sedam Taluks. In the Mann-Kendall test, the district did not exhibit any general pattern; nevertheless, several taluks, such as Yadrami and Kamalapur, demonstrated remarkable trends in the southwest and northeast seasons, respectively. Due to geographical and climatic fluctuations, the district of Kalaburagi experienced an annual mean precipitation of 797 mm. Higher mean rainfall was recorded in Sedam, Kalagi, Chincholi, and Kamalapur, while lower mean rainfall was recorded in Jevaragi and Yadrami Taluks. In the water-scarce Kalaburagi district, this work is important for policymakers addressing climate change and water resource management.

Authors

Institutions

Publication Details

Journal
Journal of Climate Change
Published
2024-09-05
DOI
https://doi.org/10.3233/jcc240024
Primary Topic
Agricultural risk and resilience
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Spatio-Temporal Mechanisms of Rainfall in Kalaburagi District: An Analysis of Trends and Variability

B.C. Vishwanath, Mahalingam Bose, Anveer, K.R. Prasanna Kumar
Journal of Climate Change
Agricultural risk and resilience
article

Spatio-Temporal Mechanisms of Rainfall in Kalaburagi District: An Analysis of Trends and Variability

B.C. Vishwanath, Mahalingam Bose, Anveer, K.R. Prasanna Kumar
article en

Abstract

The study used data from 11 taluks to analyse the changes and variability in annual and seasonal rainfall in the Kalaburagi district between 2016 and 2022. Sen Slope and Mann-Kendall analyses were used to evaluate trends, while the coefficient of variation was used to measure rainfall variability. The mean rainfall was calculated using simple mathematical formulas. The findings showed minimal seasonal and yearly variability, with the exception of the southwest monsoon season. The district as a whole as well as all 11 taluks consistently saw a rise in rainfall, according to annual Sen slope research. However, during the northeast monsoon season, negative trends were observed in Aland and Sedam Taluks. In the Mann-Kendall test, the district did not exhibit any general pattern; nevertheless, several taluks, such as Yadrami and Kamalapur, demonstrated remarkable trends in the southwest and northeast seasons, respectively. Due to geographical and climatic fluctuations, the district of Kalaburagi experienced an annual mean precipitation of 797 mm. Higher mean rainfall was recorded in Sedam, Kalagi, Chincholi, and Kamalapur, while lower mean rainfall was recorded in Jevaragi and Yadrami Taluks. In the water-scarce Kalaburagi district, this work is important for policymakers addressing climate change and water resource management.

Journal of Climate ChangeVol. 10(3)
Central University of Karnataka (IN)
Openalex Percentile: Top 80%
Agricultural risk and resilience
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.