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<p>Drought is influenced by various factors, but existing indices overlook the role of terrain slope, which impacts water retention, drainage, and drought severity. To address this gap, this study proposes a novel Slope-Integrated Drought Index (SIDI) that incorporates Topographic Wetness Index (TWI) alongside Standardized Precipitation Index (SPI), Vegetation Health Index (VHI), and Evaporative Stress Index (ESI), representing terrain slope, precipitation deficit, vegetation health, and evapotranspiration, respectively. Principal Component Analysis (PCA) was used to derive and cross-validate the weights: SPI (0.42), ESI (0.21), TWI (0.20), and VHI (0.17). SIDI was evaluated using water scarcity records of the Vavuniya district, Sri Lanka. Sensitivity and uncertainty analyses were performed to assess the influence of each input index. SIDI outperformed both SPI alone and a combined index excluding TWI, achieving 89% accuracy, 85% recall, 62% precision, an 11% false positive rate, and an F1-score of 72%. The Area Under the Curve (AUC) of 0.74 and Youden’s Index (optimal threshold = 0.85) confirmed its robustness. Given its accuracy and reliance on freely available data, SIDI presents a practical solution for drought monitoring. However, limitations include the short-term performance evaluation and the use of institutional water scarcity data instead of long-term hydro-meteorological records. Future research will focus on long-term validation and broader applicability across diverse topographical regions.</p>

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Development of a novel Slope-Integrated Drought Index (SIDI) for comprehensive drought assessment

  • 期刊论文

  • 发表日期：

    2025年5月21日

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  • M. L. P. Anuruddhika,
  • K. K. K. R. Perera,
  • L. P. N. D. Premarathna,
  • T. H. W. Pathiranage,
  • V. P. A. Weerasinghe

摘要

Drought is influenced by various factors, but existing indices overlook the role of terrain slope, which impacts water retention, drainage, and drought severity. To address this gap, this study proposes a novel Slope-Integrated Drought Index (SIDI) that incorporates Topographic Wetness Index (TWI) alongside Standardized Precipitation Index (SPI), Vegetation Health Index (VHI), and Evaporative Stress Index (ESI), representing terrain slope, precipitation deficit, vegetation health, and evapotranspiration, respectively. Principal Component Analysis (PCA) was used to derive and cross-validate the weights: SPI (0.42), ESI (0.21), TWI (0.20), and VHI (0.17). SIDI was evaluated using water scarcity records of the Vavuniya district, Sri Lanka. Sensitivity and uncertainty analyses were performed to assess the influence of each input index. SIDI outperformed both SPI alone and a combined index excluding TWI, achieving 89% accuracy, 85% recall, 62% precision, an 11% false positive rate, and an F1-score of 72%. The Area Under the Curve (AUC) of 0.74 and Youden’s Index (optimal threshold = 0.85) confirmed its robustness. Given its accuracy and reliance on freely available data, SIDI presents a practical solution for drought monitoring. However, limitations include the short-term performance evaluation and the use of institutional water scarcity data instead of long-term hydro-meteorological records. Future research will focus on long-term validation and broader applicability across diverse topographical regions.