Evaluating climate variability and future scenarios for agricultural planning in Pantnagar, Uttarakhand using statistical downscaling

Purpose The present research aims to evaluate climate variability at a micro-regional level to aid agricultural planning in Pantnagar, Uttarakhand. With 58 years (1961–2018) of observational data, rainfall variability, mean maximum and minimum temperatures and rainy days were evaluated at an annual and seasonal level. Design/methodology/approach Significant and drastic trends were evaluated using the Mann–Kendall test and Sen's slope estimator, respectively. Statistical downscaling was performed using multiple linear regression models calibrated with NCEP-NCAR reanalysis data and validated using historical station observations and calibrated with CanESM2 (CMIP5) GCM outputs under RCP4.5. Downscale projections from 2011 to 2100 were split into three-time intervals: 2020s, 2050s and 2080s. Findings The analysis revealed that rainfall trends were generally insignificant, whereas the mean minimum temperature exhibited a systematic and significant upward trend across the seasons. The anticipated temperature increase presents probable threats to agricultural productivity and water supply. Originality/value The present research emphasizes the significance of high-resolution projections of climate to ensure climate-resilient planning of agriculture in the Himalayan foothill area.

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Publication Details

Journal
Management of Environmental Quality An International Journal
Published
2026-04-27
DOI
https://doi.org/10.1108/meq-07-2025-0513
Primary Topic
Climate variability and models
Type
article
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article

Evaluating climate variability and future scenarios for agricultural planning in Pantnagar, Uttarakhand using statistical downscaling

Jyoti Singh Katariya, Mansi Nautiyal, Royal Madan, Basant Ballabh Dumka et al.
Management of Environmental Quality An International Journal
Climate variability and models
article

Evaluating climate variability and future scenarios for agricultural planning in Pantnagar, Uttarakhand using statistical downscaling

Jyoti Singh Katariya, Mansi Nautiyal, Royal Madan, Basant Ballabh Dumka, Pallavi Khobragade
article en

Abstract

Purpose The present research aims to evaluate climate variability at a micro-regional level to aid agricultural planning in Pantnagar, Uttarakhand. With 58 years (1961–2018) of observational data, rainfall variability, mean maximum and minimum temperatures and rainy days were evaluated at an annual and seasonal level. Design/methodology/approach Significant and drastic trends were evaluated using the Mann–Kendall test and Sen's slope estimator, respectively. Statistical downscaling was performed using multiple linear regression models calibrated with NCEP-NCAR reanalysis data and validated using historical station observations and calibrated with CanESM2 (CMIP5) GCM outputs under RCP4.5. Downscale projections from 2011 to 2100 were split into three-time intervals: 2020s, 2050s and 2080s. Findings The analysis revealed that rainfall trends were generally insignificant, whereas the mean minimum temperature exhibited a systematic and significant upward trend across the seasons. The anticipated temperature increase presents probable threats to agricultural productivity and water supply. Originality/value The present research emphasizes the significance of high-resolution projections of climate to ensure climate-resilient planning of agriculture in the Himalayan foothill area.

Management of Environmental Quality An International Journal
Uttarakhand Technical University (IN), Govind Ballabh Pant University of Agriculture and Technology (IN), Uttaranchal University (IN), Govind Ballabh Pant Hospital (IN), Graphic Era University (IN)
Climate action
Openalex Percentile: Top 5%
Climate variability and models
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Evaluating climate variability and future scenarios for agricultural planning in Pantnagar, Uttarakhand using statistical downscaling — Jyoti Singh Katariya, Mansi Nautiyal, et al. · Management of Environmental Quality An International Journal (2026) | TGRS Research Map | TGRS