Adjustment of the Standardized Precipitation Index (SPI) for the Evaluation of Drought in the Arroyo Pechelín Basin, Colombia, under Zero Monthly Precipitation Conditions

Abstract

The evaluation of the meteorological drought is fundamental for the management of the water resource. One of the most used indices to evaluate the drought is the standardized precipitation index (SPI) due to its practicality and evaluation in a variety of time scales, however, this uses precipitation as the only variable, depending on the deviations in the precipitation values. This is important when evaluating the SPI, because in some ecosystems close to the equatorial zone, there are very warm periods with low rainfall, in which a large proportion of the data collected by the meteorological stations corresponds to zero. In this research, the SPI was calculated in the Pechelín basin located in Colombia, in which there is zero precipitation in a large proportion of the data, registering zero precipitation in the month of January and February in 67% and 70% respectively. As a result, the SPI values increased to “wet” ranges, only when the amount of data with zero precipitation exceeded half of the total data; this means that the SPI determines wrong values when it is calculated with zero-precipitation data in large proportions. Based on this finding, this study aims to modify the index by typing the distribution (using a correction factor K), finally correcting the SPI values, this correction was called SPI-C. The results indicate that the SPI-C improved the identification of drought, obtaining corresponding values that better represent the high frequency of zero precipitation existing in the study area.

Precipitation Anomalies and Trends Estimated via Satellite Rainfall Products in the Cananeia–Iguape Coastal System, Southeast Region of Brazil

“…CHIRPS data also measured the best metrics in relation to PERSIAN-CDR data for the Mearim river basin in the transition area of the Amazon and Caatinga in the state of Maranhão [65]. The authors also highlighted that in the rainiest period, between December and May, CHIRPS data performed better.…”

“…Although it is widely used to identify drought events [65][66][67], the SPI is also used to characterize rainfall anomalies in Brazil [68] and to understand the variability of rainfall [8,[69][70][71].…”

Modeling and indexing the drought severity by augmenting SPI metric system to incorporate multi-modal ground temperature data

“…Furthermore, the developed two-dimensional index system has been compared with the already existing, most widely used drought monitoring index SPI [14]. It's noteworthy that the SPI is built upon the analysis of precipitation data only [28]. The common approach of developing the SPI involves fitting a gamma distribution to the precipitation data [19].…”

“…Analyzing individual factors contributing to droughts falls short in offering a comprehensive understanding of the complex ramifications of drought events [11,35]. Consequently, relying solely on metrics like Standardized Precipitation Index (SPI) proves insufficient in gauging drought severity because it primarily assesses the influence of rainfall [14,28]. However, temperature is a crucial parameter in discerning droughts since certain temperature conditions can offset the effects of rainfall.…”

Assessing Drought Frequency and Predictive Climate Analysis in two Biosphere Reserves of Benin (West Africa)

“…Instead of the Standardized Precipitation Index (SPI) previously reported by the same research team while assessing the vegetation dynamics in the study area [9], SPEI is here used in order to overcome some limitations of the former. In fact, even when SPI remains widely [11][12][13], this index is thought to be an incomplete way to apprehend drought due to the fact that it relies only on precipitation but, drought as climatic phenomenon implies temperature and evapotranspiration considerations. Thus, many authors strongly suggested the use of multidimensional approaches to better characterize climatic events [14,15].…”