article · Journal of Hydrology Regional Studies
Agricultural drought poses a severe environmental and socioeconomic challenge in Sub-Saharan Africa. Remote sensing multivariate indices were utilised alongside ground-based data to assess agricultural drought occurrence and severity in North Wollo within the Northern Ethiopian highlands. Satellite datasets from Landsat images at a thirty-metre spatial resolution were processed to compute vegetation and temperature indices, deriving spatial and temporal drought variability that was validated against in-situ data. The assessment revealed that the territory experienced extreme drought in 1984, 2009, and 2014, whilst extreme drought conditions did not dominate in 1989, 1994, 1999, and 2004. Linear regression analysis identified strong, statistically significant relationships between the normalised difference vegetation index and land surface temperature, the vegetation condition index and temperature condition index, and the vegetation health index and standardised precipitation index.
Drought severely threatens food security and rural livelihoods across Sub-Saharan Africa. Combining high-resolution satellite imagery with ground measurements provides dependable, real-time spatial and temporal tracking of drought conditions. This capability allows agricultural decision-makers, environmental planners, and regional authorities to accurately evaluate drought severity, identify vulnerable highland areas, and base resource management decisions on empirically validated historical patterns.
This work demonstrates an applied and tested methodology that could enable the creation of digital drought monitoring and early warning services. The primary prospective users are regional agricultural planners, environmental agencies, and resource managers needing validated spatio-temporal data. While the underlying remote sensing indices and ground validations are established at a regional scale, operational deployment would require translating these models into automated software platforms for ongoing agricultural risk assessment.
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Northern Ethiopian highland, North Wollo, Ethiopia Drought is one of the most serious environmental and socioeconomic problems of Sub-Sahara Africa's countries. The study aims to assess and evaluate the agricultural drought occurrence and its severity by using remote sensing-based multivariate indices to provide real-time spatial-temporal information for drought monitoring. Satellite datasets from Landsat images with a spatial resolution of 30 m were processed and rescaled to compute vegetation and temperature indices and derive drought status indices. The temporal and spatial variability of drought were detected and mapped by using satellite-based drought indices and validated by available in-situ data. The study revealed that the area was exposed to extreme drought in 1984, 2009, and 2014. On the contrary, no longer extreme drought dominated in 1989, 1994, 1999, and 2004. Moreover, the relationships between various indices have been examined by using a linear regression model. It has been detected that there is a significant strong relationship between NDVI and LST (R2 /p = 0.93/0.00), VCI and TCI (R2 /p = 0.71/0.00), VHI and SPI (R2/p = 0.85/0.00). Therefore, the spatial extent and temporal assessment of drought-related information are important for decision-making in the field of agriculture.
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DOI: 10.1016/j.ejrh.2024.101700
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