Preprint Article Version 1 This version is not peer-reviewed

Comparison of Meteorological and Agricultural Drought Indicators across Ethiopia

Version 1 : Received: 31 July 2019 / Approved: 2 August 2019 / Online: 2 August 2019 (08:54:40 CEST)

How to cite: Teweldebirhan Tsige, D.; Uddameri, V.; Forghanparast, F.; Hernandez, E.; Ekwaro-Osire, S. Comparison of Meteorological and Agricultural Drought Indicators across Ethiopia. Preprints 2019, 2019080020 (doi: 10.20944/preprints201908.0020.v1). Teweldebirhan Tsige, D.; Uddameri, V.; Forghanparast, F.; Hernandez, E.; Ekwaro-Osire, S. Comparison of Meteorological and Agricultural Drought Indicators across Ethiopia. Preprints 2019, 2019080020 (doi: 10.20944/preprints201908.0020.v1).

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.

Subject Areas

PDSI; Z-index; receiver operating characteristic (ROC); SPI; SPEI; GIS; food security; droughts

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.

Leave a public comment
Send a private comment to the author(s)
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.