Uncertainty analysis of SPI and SRI calculation using bootstrap in the Mediterranean regions of Algeria

Mohammad Achite (), Ommolbanin Bazrafshan (), Zohreh Pakdaman (), Andrzej Wałęga (), Fateme Pourhaghverdi () and Tommaso Caloiero ()
Additional contact information
Mohammad Achite: Hassiba Benbouali University of Chlef
Ommolbanin Bazrafshan: University of Hormozgan
Zohreh Pakdaman: University of Hormozgan
Andrzej Wałęga: University of Agriculture in Krakow
Fateme Pourhaghverdi: University of Hormozgan
Tommaso Caloiero: Research Institute for Geo-Hydrological Protection (CNR˗IRPI)

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2024, vol. 120, issue 12, No 24, 11061 pages

Abstract: Abstract The standardized precipitation index (SPI) and the standardized runoff index (SRI) are widely used in drought monitoring. In the calculation of these indices, the time scale and distribution functions are especially significant. In the current study, the uncertainty in the estimation of the two indices, in terms of time scale and distribution functions, was investigated in the wadi Mina basin (Algeria) using monthly precipitation and runoff values based on the gamma-II (GAM-II), extreme value-III (EVD-III), Pierson-III (PEI-III) and Weibull-II (WEI-II) distribution functions. With this aim, precipitation and runoff amounts were calculated considering 12- and a 24-month time scales; then, using the bootstrap method, 1000 random sample were generated for each precipitation and runoff event and for each time scale, and the confidence interval of the two indices was calculated at around 95%. The size of the confidence interval was considered as uncertainty and the error rate between the estimated and observed data was calculated. The results showed that all the considered distributions fit the time series acceptably, and that the time scale of the data is not significantly correlated with the goodness of fit. Moreover, there is no apparent relationship between the rejection cases and the scale and position of the regional stations or the investigated variables. The lack of significant differences between the observed and estimated time series for a specific distribution caused the averages estimated in SPI to fall within the same descriptive class. Based on the results, WEI-II and EVD-III showed the lowest estimation error and uncertainty in meteorological and hydrological drought, respectively, at both 12- and 24-month time scales, thus suggesting the use of these two functions for drought monitoring at medium-term and long-term time scales.

Keywords: Drought monitoring; Uncertainty; Bootstrap; Sampling; Precipitation index; Standardized runoff (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11069-024-06642-w Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:nathaz:v:120:y:2024:i:12:d:10.1007_s11069-024-06642-w

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11069

DOI: 10.1007/s11069-024-06642-w

Access Statistics for this article

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards is currently edited by Thomas Glade, Tad S. Murty and Vladimír Schenk

More articles in Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards from Springer, International Society for the Prevention and Mitigation of Natural Hazards
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().