The North Shewa zone of Ethiopia is highly vulnerable to drought. The majority of the population of the zone is involved in agricultural activities for their livelihood. Agriculture is predominantly dependent on the timing, amount, duration, and distribution of natural rainfall. This makes the zone susceptible to the impacts of climatic extreme events such as drought. Yet, no drought assessment studies have been conducted on the spatial and temporal analysis of recent droughts over the zone. In view of that, this study examined the spatial and temporal characteristics of drought in the period 1990 to 2020 over the North Shewa zone of Oromia regional state, Ethiopia, using the Standardized Precipitation Index (SPI) drought index. The drought events at each of the stations had varying magnitudes and occurrences. During Kiremt (JJAS), seasonal drought was more frequent than Belg (FMAM). The years 2006, 1998, 2013, and 2016 are the top driest seasons in Belg (ordered from high to low spatial coverage); and 1992, 2009, 1990, 2012, and 2015 are the years when there was the highest spatially spread drought in the Kiremt (June-September) season. The comparison between the performance of Raw, Adjusted, and Merged datasets in terms of with relation to CORR, BR2, BIAS, and RMSE. The results show that merged data is stronger than row and adjusted data in reproducing the observed station data.
| Published in | American Journal of Remote Sensing (Volume 13, Issue 2) |
| DOI | 10.11648/j.ajrs.20251302.14 |
| Page(s) | 100-109 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2025. Published by Science Publishing Group |
Drought, SPI, CHRIPSv2, Oromia
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APA Style
Fana, T. B., Wakete, M. T. (2025). Meteorological Drought Analysis by Using CHRIPSv2 Satellite Remote Sensing and Station Data over North Shewa Zone, Oromia, Ethiopia. American Journal of Remote Sensing, 13(2), 100-109. https://doi.org/10.11648/j.ajrs.20251302.14
ACS Style
Fana, T. B.; Wakete, M. T. Meteorological Drought Analysis by Using CHRIPSv2 Satellite Remote Sensing and Station Data over North Shewa Zone, Oromia, Ethiopia. Am. J. Remote Sens. 2025, 13(2), 100-109. doi: 10.11648/j.ajrs.20251302.14
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Download@article{10.11648/j.ajrs.20251302.14,
author = {Tsige Berhanu Fana and Mesay Tolossa Wakete},
title = {Meteorological Drought Analysis by Using CHRIPSv2 Satellite Remote Sensing and Station Data over North Shewa Zone, Oromia, Ethiopia},
journal = {American Journal of Remote Sensing},
volume = {13},
number = {2},
pages = {100-109},
doi = {10.11648/j.ajrs.20251302.14},
url = {https://doi.org/10.11648/j.ajrs.20251302.14},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajrs.20251302.14},
abstract = {The North Shewa zone of Ethiopia is highly vulnerable to drought. The majority of the population of the zone is involved in agricultural activities for their livelihood. Agriculture is predominantly dependent on the timing, amount, duration, and distribution of natural rainfall. This makes the zone susceptible to the impacts of climatic extreme events such as drought. Yet, no drought assessment studies have been conducted on the spatial and temporal analysis of recent droughts over the zone. In view of that, this study examined the spatial and temporal characteristics of drought in the period 1990 to 2020 over the North Shewa zone of Oromia regional state, Ethiopia, using the Standardized Precipitation Index (SPI) drought index. The drought events at each of the stations had varying magnitudes and occurrences. During Kiremt (JJAS), seasonal drought was more frequent than Belg (FMAM). The years 2006, 1998, 2013, and 2016 are the top driest seasons in Belg (ordered from high to low spatial coverage); and 1992, 2009, 1990, 2012, and 2015 are the years when there was the highest spatially spread drought in the Kiremt (June-September) season. The comparison between the performance of Raw, Adjusted, and Merged datasets in terms of with relation to CORR, BR2, BIAS, and RMSE. The results show that merged data is stronger than row and adjusted data in reproducing the observed station data.},
year = {2025}
}
TY - JOUR T1 - Meteorological Drought Analysis by Using CHRIPSv2 Satellite Remote Sensing and Station Data over North Shewa Zone, Oromia, Ethiopia AU - Tsige Berhanu Fana AU - Mesay Tolossa Wakete Y1 - 2025/12/11 PY - 2025 N1 - https://doi.org/10.11648/j.ajrs.20251302.14 DO - 10.11648/j.ajrs.20251302.14 T2 - American Journal of Remote Sensing JF - American Journal of Remote Sensing JO - American Journal of Remote Sensing SP - 100 EP - 109 PB - Science Publishing Group SN - 2328-580X UR - https://doi.org/10.11648/j.ajrs.20251302.14 AB - The North Shewa zone of Ethiopia is highly vulnerable to drought. The majority of the population of the zone is involved in agricultural activities for their livelihood. Agriculture is predominantly dependent on the timing, amount, duration, and distribution of natural rainfall. This makes the zone susceptible to the impacts of climatic extreme events such as drought. Yet, no drought assessment studies have been conducted on the spatial and temporal analysis of recent droughts over the zone. In view of that, this study examined the spatial and temporal characteristics of drought in the period 1990 to 2020 over the North Shewa zone of Oromia regional state, Ethiopia, using the Standardized Precipitation Index (SPI) drought index. The drought events at each of the stations had varying magnitudes and occurrences. During Kiremt (JJAS), seasonal drought was more frequent than Belg (FMAM). The years 2006, 1998, 2013, and 2016 are the top driest seasons in Belg (ordered from high to low spatial coverage); and 1992, 2009, 1990, 2012, and 2015 are the years when there was the highest spatially spread drought in the Kiremt (June-September) season. The comparison between the performance of Raw, Adjusted, and Merged datasets in terms of with relation to CORR, BR2, BIAS, and RMSE. The results show that merged data is stronger than row and adjusted data in reproducing the observed station data. VL - 13 IS - 2 ER -
Ethiopia Meteorological Institute (EMI), Addis Ababa, Ethiopia
Ethiopia Meteorological Institute (EMI), Addis Ababa, Ethiopia
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