Scholarlink

<p>Marathwada, a semi-arid region in Maharashtra, India, frequently experiences droughts that severely impact agriculture and water resources. This study developed a drought susceptibility map using a spatial multicriteria decision-making framework based on the Analytic Hierarchy Process (AHP). Six key parameters: rainfall anomaly, Soil Moisture Anomaly Percentage Index (SMAPI), Normalized Difference Vegetation Index (NDVI), Vegetation Condition Index (VCI), Vegetation Health Index (VHI), and Temperature Condition Index (TCI), were integrated due to their proven relevance in assessing meteorological and agricultural droughts in semi-arid climates. Assigned weights were: VHI (28.42%), rainfall anomaly (27.44%), SMAPI (25.59%), VCI (8.97%), NDVI (6.47%), and TCI (3.11%). The resulting drought susceptibility map categorized the region into five classes: very low, low, moderate, severe, and extreme. Districts such as Beed, Osmanabad, and Latur were identified as high-risk zones, marked by rainfall anomalies below − 230&#xa0;mm, soil moisture below 36%, and vegetation stress. In contrast, districts like Hingoli and eastern Nanded exhibited high NDVI (&gt; 0.35), VHI (&gt; 63%), and SMAPI (&gt; 68%), placing them in low-susceptibility zones. This spatial assessment highlights the utility of combining climatic, thermal, and vegetation indices for drought risk evaluation and provides a valuable tool for targeted mitigation, agricultural planning, and adaptive water resource management by local and regional authorities.</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

Geospatial analysis of drought susceptibility in Marathwada region, Maharashtra, India

  • 期刊论文

  • 发表日期：

    2026年2月27日

查看全文
  • Kiran Jalem,
  • Suresh Ghosh,
  • Sagar Kumar Swain

摘要

Marathwada, a semi-arid region in Maharashtra, India, frequently experiences droughts that severely impact agriculture and water resources. This study developed a drought susceptibility map using a spatial multicriteria decision-making framework based on the Analytic Hierarchy Process (AHP). Six key parameters: rainfall anomaly, Soil Moisture Anomaly Percentage Index (SMAPI), Normalized Difference Vegetation Index (NDVI), Vegetation Condition Index (VCI), Vegetation Health Index (VHI), and Temperature Condition Index (TCI), were integrated due to their proven relevance in assessing meteorological and agricultural droughts in semi-arid climates. Assigned weights were: VHI (28.42%), rainfall anomaly (27.44%), SMAPI (25.59%), VCI (8.97%), NDVI (6.47%), and TCI (3.11%). The resulting drought susceptibility map categorized the region into five classes: very low, low, moderate, severe, and extreme. Districts such as Beed, Osmanabad, and Latur were identified as high-risk zones, marked by rainfall anomalies below − 230 mm, soil moisture below 36%, and vegetation stress. In contrast, districts like Hingoli and eastern Nanded exhibited high NDVI (> 0.35), VHI (> 63%), and SMAPI (> 68%), placing them in low-susceptibility zones. This spatial assessment highlights the utility of combining climatic, thermal, and vegetation indices for drought risk evaluation and provides a valuable tool for targeted mitigation, agricultural planning, and adaptive water resource management by local and regional authorities.