Teweldebirhan Tsige, D.; Uddameri, V.; Forghanparast, F.; Hernandez, E.A.; Ekwaro-Osire, S. Comparison of Meteorological- and Agriculture-Related Drought Indicators across Ethiopia. Water2019, 11, 2218.
Teweldebirhan Tsige, D.; Uddameri, V.; Forghanparast, F.; Hernandez, E.A.; Ekwaro-Osire, S. Comparison of Meteorological- and Agriculture-Related Drought Indicators across Ethiopia. Water 2019, 11, 2218.
Teweldebirhan Tsige, D.; Uddameri, V.; Forghanparast, F.; Hernandez, E.A.; Ekwaro-Osire, S. Comparison of Meteorological- and Agriculture-Related Drought Indicators across Ethiopia. Water2019, 11, 2218.
Teweldebirhan Tsige, D.; Uddameri, V.; Forghanparast, F.; Hernandez, E.A.; Ekwaro-Osire, S. Comparison of Meteorological- and Agriculture-Related Drought Indicators across Ethiopia. Water 2019, 11, 2218.
Abstract
Meteorological drought indicators are commonly used for agricultural drought contingency planning in Ethiopia. Agricultural droughts arise due to soil moisture deficits. While these deficits may be caused by meteorological droughts, the timing and duration of agricultural droughts need not coincide with the onset of meteorological droughts due to soil moisture buffering. Similarly, agricultural droughts can persist even after the cessation of meteorological droughts due to delayed hydrologic processes. Understanding the relationship between meteorological and agricultural droughts is therefore crucial. An evaluation framework was developed to compare meteorological and agricultural droughts using a suite of exploratory and confirmatory tools. Receiver operator characteristics (ROC) was used to understand the covariation of meteorological and agricultural droughts. Comparisons were carried out between SPI-2, SPEI-2 and Palmer Z-index to assess intra-seasonal droughts and between SPI-6, SPEI-6 and PDSI for full-season evaluations. SPI was seen to correlate well with selected agricultural drought indicators but did not explain all the variability noted in agricultural droughts. The relationships between meteorological and agricultural droughts exhibited spatial variability which varied across indicators. SPI is better suited to predict non-agricultural drought states more so than agricultural drought states. Differences between agricultural and meteorological droughts must be accounted for better drought-preparedness planning.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
,
*
