Abstract
ABSTRACT Shannon’s entropy theory measures the average uncertainty in the outcomes of an event. Since drought monitoring is an important issue, it is imperative to develop more user-friendly, modern methods for it. The present study investigates the uncertainty of the difference between monthly mean precipitation and potential evapotranspiration utilizing Shannon’s entropy over short-, mid-, and long-term dynamic time scales in the Karkheh Basin of Iran. An entropy-based precipitation–evapotranspiration index (EPEI) is defined for drought classification. EPEI is compared with the standardized precipitation–evapotranspiration index (SPEI) in terms of spatiotemporal patterns. The results indicate a higher similarity between EPEI and SPEI under existing conditions with low average precipitation. Over short scales, both indices yield similar results in duration, frequency, and intensity. Over long scales, the consistency of the drought duration, frequency, and intensity results declines. The main difference between the two is the EPEI’s ability to determine the early onset of the drought event.
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