Scholarlink

<p>‘Climate change’, common term used for answering the questions of impacts of weather parameters on production sectors, needs to be assessed using genuine techniques. Representative Temperature and Precipitation GCM Subsetting Approach was used to subset 29 General Circulation Models from a pool of CMIP5 climatic projections for eleven districts of South Interior Karnataka comprising three dry zones (Eastern Dry Zone-EDZ, Central Dry Zone-CDZ and Southern Dry Zone-SDZ). Among 29 models, 5 models each representing normal, hot/wet, hot/dry, cool/wet, and cool/dry situations of RCP 4.5 and 8.5 scenarios were selected. The rainfall and temperature datasets from each model were divided into near-century (2010–2039), mid-century (2040-69) and end-century (2070-99) and subjected to calculation of Standardized Precipitation-Evapotranspiration Index (SPEI) adopting five-time lags viz., 1-month, 3-month, 4-month, 6-month and 12-month accounting short, medium (<i>Kharif</i> and <i>Rabi</i>) and long duration drought, estimation of its trend during <i>Kharif</i> (JJAS) and <i>Rabi</i> (OND) seasons using Innovative Trend Analysis (ITA). Results revealed the decreasing trends of <i>Kharif</i> and <i>Rabi</i> SPEI over drier districts of the region like Chikkaballapura (EDZ), Chitradurga and Davangere (CDZ), and Chamarajanagara (SDZ) indicating increased tendency of drought susceptibility of these districts. characterization of monthly SPEI using ‘runs theory’, revealed the susceptibility of Davangere district for longer and more severe droughts compared to other regions, Chitradurga and Bangalore Urban districts for higher drought intensity in the region. Driver Partitioning Analysis further indicated that precipitation dominated temperature-driven evapotranspiration in determining drought variability, explaining over 80–90% of SPEI variance across districts. The study highlights ITA’s usefulness in analyzing future drought trends and developing climate risk tools to enhance regional food security under climate change.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Innovative trend analysis for assessing projected impacts of climate change on droughts over South Interior Karnataka, India

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年1月13日

查看全文
  • M. H. Manjunatha,
  • M. N. Thimmegowda,
  • Lingaraj Huggi,
  • R. S. Pooja,
  • Santanu Kumar Bal,
  • M. A. Sarath Chandran,
  • D. V. Soumya

摘要

‘Climate change’, common term used for answering the questions of impacts of weather parameters on production sectors, needs to be assessed using genuine techniques. Representative Temperature and Precipitation GCM Subsetting Approach was used to subset 29 General Circulation Models from a pool of CMIP5 climatic projections for eleven districts of South Interior Karnataka comprising three dry zones (Eastern Dry Zone-EDZ, Central Dry Zone-CDZ and Southern Dry Zone-SDZ). Among 29 models, 5 models each representing normal, hot/wet, hot/dry, cool/wet, and cool/dry situations of RCP 4.5 and 8.5 scenarios were selected. The rainfall and temperature datasets from each model were divided into near-century (2010–2039), mid-century (2040-69) and end-century (2070-99) and subjected to calculation of Standardized Precipitation-Evapotranspiration Index (SPEI) adopting five-time lags viz., 1-month, 3-month, 4-month, 6-month and 12-month accounting short, medium (Kharif and Rabi) and long duration drought, estimation of its trend during Kharif (JJAS) and Rabi (OND) seasons using Innovative Trend Analysis (ITA). Results revealed the decreasing trends of Kharif and Rabi SPEI over drier districts of the region like Chikkaballapura (EDZ), Chitradurga and Davangere (CDZ), and Chamarajanagara (SDZ) indicating increased tendency of drought susceptibility of these districts. characterization of monthly SPEI using ‘runs theory’, revealed the susceptibility of Davangere district for longer and more severe droughts compared to other regions, Chitradurga and Bangalore Urban districts for higher drought intensity in the region. Driver Partitioning Analysis further indicated that precipitation dominated temperature-driven evapotranspiration in determining drought variability, explaining over 80–90% of SPEI variance across districts. The study highlights ITA’s usefulness in analyzing future drought trends and developing climate risk tools to enhance regional food security under climate change.