Impact of Methodological Variations on the Standard Precipitation Index: A Focus on Rainfall-Deficient Scenarios

Petrit Zorba – Institute of Geoscience, Polytechnic University of Tirana, Albania

Elsuida Hoxha – Grove School of Engineering, The City College of New York, United States of America

Abstract: This study delves into the nuances of Standard Precipitation Index (SPI) calculations, especially under conditions where precipitation records for certain months within the dataset are absent. It’s crucial to highlight that these gaps in data are not attributed to observational omissions but are instances where no rainfall was actually documented. In such cases, the absent values are substituted with nominal figures, such as 0.1 mm or 0.01 mm, to maintain the continuity of the dataset. Utilizing well-established methodologies for SPI estimation and referencing various models employed in similar analyses, including “RDIT,” “SPI Generator,” “DrinC,” and one developed by our team named “SPI – Alb PZ,” we aim to explore the implications and errors arising from the replacement of missing values with 0.1 or 0.01. At first glance, these small values may seem insignificant and may not appear to alter climate assessments for the study area. However, contrary to suggestions from some authors advocating for such replacements in SPI calculation methodologies, our study results demonstrate that this type of modification cannot be recommended. Unfortunately, it leads to higher SPI values and, at times, significantly inflates drought estimations for those specific months when rain values are modified.

Keywords: Standard Precipitation Index; drought; data monitoring; meteorology, data modification, SPI error.

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Publication Date: 26.03.2024

How to Cite: Zorba, P., & Hoxha, E. Impact of Methodological Variations on the Standard Precipitation Index: A Focus on Rainfall-Deficient Scenarios. Journal of Integrated Engineering and Applied Sciences, 2024; 2(1); 48–57.


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