基于GIS和遥感的摩洛哥马拉喀什-萨菲地区不同时间尺度干旱变率评估

Chaima Elair, Khalid Rkha Chaham, Abdessamad Hadri
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摘要

在摩洛哥西南部半干旱的马拉喀什-萨菲(MS)地区,气候变化加剧了干旱的发生,对水资源和农业构成了重大威胁。全面了解干旱模式对于管理这些风险和有效提高抗旱能力至关重要。采用标准化降水指数(SPI)对1980 - 2018年18个雨量站的降水进行了气象干旱分析。此外,利用植被条件指数(VCI)、温度条件指数(TCI)和植被健康指数(VHI) 3个遥感驱动指数对2000 - 2018年农业干旱进行了量化。将这些指标与SPI进行关联,评价其性能,并衡量植被对气象干旱的敏感性。曼-肯德尔测试评估了干旱事件的趋势及其严重程度。结果表明,SPI、VCI、TCI和VHI经历了干湿交替期,总体呈上升趋势,特别是在MS地区的山区、高原区和豪兹平原。相关分析表明,遥感指数与SPI-6呈显著相关,平均相关系数超过0.6。这些发现强调了考虑多个时间尺度来全面评估气候对植被影响的重要性。季节干旱趋势分析表明,冬春季无显著的负趋势,秋季有显著的正趋势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assessment of drought variability in the Marrakech-Safi region (Morocco) at different time scales using GIS and remote sensing
Abstract In the semi-arid Marrakech-Safi (MS) region of southwest Morocco, climate change has amplified drought occurrences, posing significant threats to water resources and agriculture. A comprehensive understanding of drought patterns is imperative to manage these risks and enhance resilience effectively. Precipitation from 18 pluviometer stations was employed to analyze meteorological drought using the standardized precipitation index (SPI) from 1980 to 2018. Additionally, agricultural drought is quantified using three remote sensing-driven indices: vegetation condition index (VCI), temperature conditions index (TCI), and vegetation health index (VHI) from 2000 to 2018. These indices are correlated with SPI to evaluate their performance and gauge vegetation sensitivity to meteorological drought. The Mann–Kendall test assesses trends in drought events and their severity. The results demonstrated that SPI, VCI, TCI, and VHI experienced alternating dry and wet periods with an overall upward trend, especially in mountainous areas, plateau zones, and Haouz plain of the MS region. The correlation analysis establishes a significant relationship between remote sensing-based indices and SPI-6, with mean correlation coefficients exceeding 0.6. The findings underscore the importance of considering multiple time scales to comprehensively assess climate's impact on vegetation. Seasonal drought trends analysis indicates no significant negative trends in winter and spring but positive trends in autumn.
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