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<p>Effective agricultural drought monitoring is vital for achieving the Sustainable Development Goals (SDGs), particularly SDG 13 (Climate Action). This study evaluated the performance of various drought indices, Standardized Precipitation-Evapotranspiration Index (SPEI), Standardized Soil Moisture Index (SSMI), soil moisture (SM), and evapotranspiration (ET) against the Modified Soil-Adjusted Vegetation Index (MSAVI) in detecting agricultural drought along the southern route of the China–Pakistan Economic Corridor (CPEC). Remote sensing and climate datasets spanning 1990–2023 were acquired from different remote sensing sources, which also served as the primary data preparation and analysis tool. Complementary statistical analyses included Cross-Correlation, Modified Mann–Kendall (MMK) trend test, Principal Component Analysis (PCA), Moran’s I, Geographically Weighted Regression (GWR), and exponential growth modeling. Results indicated that MSAVI exhibited stronger correlations (<i>r</i> = 0.50–0.84) with SPEI than SSMI. PCA confirmed a close relationship between MSAVI and SPEI, while SSMI followed a divergent pattern. Time-lag correlations further reinforced the stronger MSAVI-SPEI link. MMK analysis showed a declining trend in MSAVI, an increasing trend in SPEI, and a neutral trend for SSMI. Moran’s I revealed High–High clusters for SPEI and MSAVI in northern and southern zones and High–Low clusters for SSMI and MSAVI. Moreover, MSAVI displayed a robust correlation with ET (<i>R</i><sup>2</sup> = 0.818) in the southern region, while the SM-ET correlation was comparatively weaker (<i>R</i><sup>2</sup> = 0.424). These findings demonstrate that SPEI and ET are reliable indicators of agricultural drought and offer valuable insights for drought mitigation and sustainable agriculture in the CPEC region.</p> Graphical abstract <p></p>

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Comparative assessment of drought indicators for agricultural drought monitoring to support sustainable development goal 13 in China–Pakistan economic corridor’s southern route

  • 期刊论文

  • 发表日期：

    2025年7月8日

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  • Tehseen Javed,
  • Zhenhua Wang,
  • Jian Liu,
  • Wenhao Li,
  • Haixia Lin,
  • Pengpeng Chen,
  • Jihong Zhang

摘要

Effective agricultural drought monitoring is vital for achieving the Sustainable Development Goals (SDGs), particularly SDG 13 (Climate Action). This study evaluated the performance of various drought indices, Standardized Precipitation-Evapotranspiration Index (SPEI), Standardized Soil Moisture Index (SSMI), soil moisture (SM), and evapotranspiration (ET) against the Modified Soil-Adjusted Vegetation Index (MSAVI) in detecting agricultural drought along the southern route of the China–Pakistan Economic Corridor (CPEC). Remote sensing and climate datasets spanning 1990–2023 were acquired from different remote sensing sources, which also served as the primary data preparation and analysis tool. Complementary statistical analyses included Cross-Correlation, Modified Mann–Kendall (MMK) trend test, Principal Component Analysis (PCA), Moran’s I, Geographically Weighted Regression (GWR), and exponential growth modeling. Results indicated that MSAVI exhibited stronger correlations (r = 0.50–0.84) with SPEI than SSMI. PCA confirmed a close relationship between MSAVI and SPEI, while SSMI followed a divergent pattern. Time-lag correlations further reinforced the stronger MSAVI-SPEI link. MMK analysis showed a declining trend in MSAVI, an increasing trend in SPEI, and a neutral trend for SSMI. Moran’s I revealed High–High clusters for SPEI and MSAVI in northern and southern zones and High–Low clusters for SSMI and MSAVI. Moreover, MSAVI displayed a robust correlation with ET (R2 = 0.818) in the southern region, while the SM-ET correlation was comparatively weaker (R2 = 0.424). These findings demonstrate that SPEI and ET are reliable indicators of agricultural drought and offer valuable insights for drought mitigation and sustainable agriculture in the CPEC region.

Graphical abstract