Spatiotemporal characterization of meteorological drought and rainfall variation during El Niño/La Niña event over Bundelkhand region of India

Abstract This study analyzes the relationship between the El Niño-Southern Oscillation (ENSO) and rainfall variability in the Bundelkhand region using the Oceanic Niño Index (Niño 3.4 Index) for the period 1950–2022. Drought monitoring was conducted using the Standardized Precipitation Index (SPI) to assess the impact of ENSO on regional drought conditions. Results indicate that El Niño years correspond to a decline in rainfall, with weak and moderate El Niño events leading to deficits of − 38.62 mm and − 21.44 mm, respectively, while strong El Niño years experienced a significant reduction of − 128.8 mm. Conversely, the relationship between La Niña and rainfall is inconsistent, with moderate La Niña years showing a positive anomaly of 66.89 mm, while weak and strong La Niña years resulted in mixed effects, with anomalies of − 17.59 mm and − 56.72 mm, respectively. Spatiotemporal analysis further revealed that drought conditions persisted in Bundelkhand during the La Niña years of 1973 and 2020, highlighting the region’s unique response to ENSO events. These findings emphasize the need for localized climate assessments, as large-scale ENSO trends do not consistently predict rainfall patterns in Bundelkhand region. This study provides valuable insights for drought mitigation and early warning strategies in the region.

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Publication Details

Journal
Discover Applied Sciences
Published
2025-05-07
DOI
https://doi.org/10.1007/s42452-025-07035-9
Citations
2
Primary Topic
Hydrology and Drought Analysis
Type
article
Field-Weighted Citation Impact
2.21
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article

Spatiotemporal characterization of meteorological drought and rainfall variation during El Niño/La Niña event over Bundelkhand region of India

Anoop Kumar Shukla, Vaibhav Yadav, Satyavati Shukla, R. V. Galkate et al.
2 citations
Discover Applied Sciences
Hydrology and Drought Analysis
2.21
article

Spatiotemporal characterization of meteorological drought and rainfall variation during El Niño/La Niña event over Bundelkhand region of India

Anoop Kumar Shukla, Vaibhav Yadav, Satyavati Shukla, R. V. Galkate, Samikshya Panda, V.K. Chandola
article en
2 citations

Abstract

Abstract This study analyzes the relationship between the El Niño-Southern Oscillation (ENSO) and rainfall variability in the Bundelkhand region using the Oceanic Niño Index (Niño 3.4 Index) for the period 1950–2022. Drought monitoring was conducted using the Standardized Precipitation Index (SPI) to assess the impact of ENSO on regional drought conditions. Results indicate that El Niño years correspond to a decline in rainfall, with weak and moderate El Niño events leading to deficits of − 38.62 mm and − 21.44 mm, respectively, while strong El Niño years experienced a significant reduction of − 128.8 mm. Conversely, the relationship between La Niña and rainfall is inconsistent, with moderate La Niña years showing a positive anomaly of 66.89 mm, while weak and strong La Niña years resulted in mixed effects, with anomalies of − 17.59 mm and − 56.72 mm, respectively. Spatiotemporal analysis further revealed that drought conditions persisted in Bundelkhand during the La Niña years of 1973 and 2020, highlighting the region’s unique response to ENSO events. These findings emphasize the need for localized climate assessments, as large-scale ENSO trends do not consistently predict rainfall patterns in Bundelkhand region. This study provides valuable insights for drought mitigation and early warning strategies in the region.

Discover Applied SciencesVol. 7(5)
Manipal Academy of Higher Education (IN), Guilin University of Technology (CN), National Institute of Hydrology (IN), Banaras Hindu University (IN)
Openalex Percentile: Top 14%
Hydrology and Drought Analysis
2.21
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Spatiotemporal characterization of meteorological drought and rainfall variation during El Niño/La Niña event over Bundelkhand region of India — Anoop Kumar Shukla, Vaibhav Yadav, et al. · Discover Applied Sciences (2025) | TGRS Research Map | TGRS