Assessment of spatial distribution of aridity indices in Raya valley, northern Ethiopia

M.A. Gebremedhin* (Corresponding Author), Gebrerufael Hailu Kahsay, Hailemariam Gebrewahed Fanta

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

20 Citations (Scopus)
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Aridity is a risk with the threat of desertification because of erratic precipitation and prolonged droughts. Aridity indices are often used for the climate-based land classification and monitoring droughts. Hence, this study aimed at analysis of the spatial distribution of aridity indices in Raya valley, northern Ethiopia. Meteorological data from eight meteorological stations located throughout the study area were used to compute the three aridity indices employed: the De Martonne aridity index (IDM), the Pinna combinative index (IP), and the Food and Agriculture Organization aridity index (IFAO). Each aridity index value was computed at each station. Then, once the statistical properties of each aridity index at each station were assessed, inverse distance-weighted geographic information system interpolation technique was used for the spatial estimation of the aridity indices. The three indices indicated a high coefficient of determination which in common revealed the area prone to dry and semi-dry risk. However, IDM was found more appropriate for the considered area since it defines more the climate of each location using seven classes, and it can be computed at specific season and month. The annual, seasonal, and monthly aridity indices of IDM showed high spatial variability of aridity index. The spatial distribution of the IDM underlined irrigation requirements in the northern east part of the study area. This analysis may be helpful for the utilization of water resources and irrigation systems of the study area.
Original languageEnglish
Article number217
Number of pages8
JournalApplied Water Science
Early online date8 Nov 2018
Publication statusPublished - 1 Dec 2018


  • Aridity indices
  • Raya valley
  • Spatial distribution


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