EVALUATION OF DROUGHT IN IRAQ USING DSI. BY REMOTE SENSING

Authors

  • Jawad &et al.

DOI:

https://doi.org/10.36103/ijas.v49i6.152

Keywords:

percentage of precipitation anomaly, evapotranspiration, potential evapotranspiration, NTSG, GIS, MODIS, standard deviation, drought events.

Abstract

Evaluation of drought patterns in Iraq and determining the most susceptible areas of this phenomenon were analyzed, using the remotely-sensed Drought Severity Index (DSI) through analysis the daily and annual DSI for three zones over Iraq, also have been analyzed DSI time series using run theory to evaluate the characteristics of drought in Iraq. The efficiency of DSI for drought monitoring was examined from compared with Percentage of Precipitation Anomaly (PPA) for three zones (Arid and Semi-Arid, Steppes and Desert), and compared with drought indicators (Evapotranspiration (ET), Potential evapotranspiration (PET) and total annual precipitation (PRE)) for the period 2000-2011, were derived from the Numerical Terradynamic Simulation Group (NTSG). The spatial interpolation techniques in Geographic Information System (GIS) package has been used, to cover the whole extent of country and extracting the zones. Statistical methods were applied to compute the probability of drought events at every zone. The results showed the drier year is 2008, the wetter years are 2001 in Desert zone and 2003 in steppes and Arid and Semi-Arid Zone zones. The results also showed a significant fluctuation in precipitation from the average, especially at Arid and Semi-Arid Zone when compared with other zones. The values of standard deviation of precipitation were compared with precipitation anomalies for each zone, Arid and Semi-Arid is the drier zone in 2007-2008, the wetter zone is also Arid and Semi-Arid in 2002-2003. Using run theory, the drier Zone is Arid and Semi-Arid and the wetter Zone is steppes during study period.

Published

2018-12-06

Issue

Section

Articles

How to Cite

&et al., J. (2018). EVALUATION OF DROUGHT IN IRAQ USING DSI. BY REMOTE SENSING. IRAQI JOURNAL OF AGRICULTURAL SCIENCES, 49(6). https://doi.org/10.36103/ijas.v49i6.152

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