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<p>In recent decades, India has witnessed notable spatiotemporal shifts in its rainfall patterns, characterized by a decrease in rainy days and an increase in extreme events. These extremes have significantly impacted various aspects of life and property across the country, leading to flash floods, drought, landslides, and infrastructure damage, posing risks to human lives, water bodies, ecosystems, and other aspects of life. This study analyzed daily gridded rainfall data for Himachal Pradesh, India, from 1951 to 2020 using information theory and advanced statistical techniques to assess trends. The results demonstrated that intra-variation in rainfall amounts and rainy days increases with increasing time scale. Most districts showed a significant increasing trend in daily SVI<sub>AE</sub> at the 5% significance level. The classification based on the relationship between daily SVI<sub>AE</sub> and mean annual rainfall reveals that nearly 47% of the state falls under the extreme category (Class-A &amp; D), characterized by either sustained high rainfall or intense variability, while reaming 53% lies in the moderate classes (Class-B &amp; C). This spatial heterogeneity highlights the significant disparities in water resource availability across districts, indicating that several regions are prone to limited water availability and require targeted water management and storage interventions.</p>

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Quantifying Complexities in Hydrological Indicators and Classification of Water Resources through Information Theory

  • 期刊论文

  • 发表日期：

    2026年5月9日

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  • Shekhar Singh,
  • Anil Kumar

摘要

In recent decades, India has witnessed notable spatiotemporal shifts in its rainfall patterns, characterized by a decrease in rainy days and an increase in extreme events. These extremes have significantly impacted various aspects of life and property across the country, leading to flash floods, drought, landslides, and infrastructure damage, posing risks to human lives, water bodies, ecosystems, and other aspects of life. This study analyzed daily gridded rainfall data for Himachal Pradesh, India, from 1951 to 2020 using information theory and advanced statistical techniques to assess trends. The results demonstrated that intra-variation in rainfall amounts and rainy days increases with increasing time scale. Most districts showed a significant increasing trend in daily SVIAE at the 5% significance level. The classification based on the relationship between daily SVIAE and mean annual rainfall reveals that nearly 47% of the state falls under the extreme category (Class-A & D), characterized by either sustained high rainfall or intense variability, while reaming 53% lies in the moderate classes (Class-B & C). This spatial heterogeneity highlights the significant disparities in water resource availability across districts, indicating that several regions are prone to limited water availability and require targeted water management and storage interventions.