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Evaluating the spatiotemporal dynamics of agrometeorological droughts in semi-arid Gwayi agroecosystems (1990-2020) using multiple indices
Evaluating the spatiotemporal dynamics of agrometeorological droughts in semi-arid Gwayi agroecosystems (1990-2020) using multiple indices
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Evaluating the spatiotemporal dynamics of agrometeorological droughts in semi-arid Gwayi agroecosystems (1990-2020) using multiple indices
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Evaluating the spatiotemporal dynamics of agrometeorological droughts in semi-arid Gwayi agroecosystems (1990-2020) using multiple indices
Evaluating the spatiotemporal dynamics of agrometeorological droughts in semi-arid Gwayi agroecosystems (1990-2020) using multiple indices

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Evaluating the spatiotemporal dynamics of agrometeorological droughts in semi-arid Gwayi agroecosystems (1990-2020) using multiple indices
Evaluating the spatiotemporal dynamics of agrometeorological droughts in semi-arid Gwayi agroecosystems (1990-2020) using multiple indices
Journal Article

Evaluating the spatiotemporal dynamics of agrometeorological droughts in semi-arid Gwayi agroecosystems (1990-2020) using multiple indices

2024
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Overview
Climate variability poses a significant threat to smallholder farmers in the Gwayi catchment, Zimbabwe. This study investigated the spatiotemporal dynamics of agrometeorological droughts from 1990 to 2020 using the Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), Vegetation Condition Index (VCI), and Vegetation Health Index (VHI). The triangulation of these indices provided a comprehensive understanding of drought dynamics. Severe to extreme drought events were identified in 1995, 1998, 2005, 2016, 2018, and 2020, while moderate droughts were consistently detected across all indices. Favourable conditions were observed in 2000 and 2006. A strong positive correlation (r = 0.88) between VHI and VCI suggests their similar effectiveness in reflecting vegetation health. In contrast, moderate correlations between VHI and SPI (r = 0.30), VHI and SPEI (r = 0.39), VCI and SPI (r = 0.28), and VCI and SPEI (r = 0.40) indicate that these indices capture complementary information, reflecting not only precipitation deficits but also the impacts of temperature, soil moisture, and land cover changes. The SPI and SPEI displayed a strong positive correlation (r = 0.78), aligning in their sensitivity to precipitation and evapotranspiration. Spatial analysis revealed a pronounced north-south drought gradient, with the southwestern region being particularly vulnerable, underscoring the need for targeted interventions.