scholarly journals Inadequacy of the gamma distribution to calculate the Standardized Precipitation Index

2015 ◽  
Vol 19 (12) ◽  
pp. 1129-1135 ◽  
Author(s):  
Gabriel C. Blain ◽  
Monica C. Meschiatti
Keyword(s):  
Normal Distribution ◽  
Gamma Distribution ◽  
Goodness Of Fit ◽  
Drought Index ◽  
Standardized Precipitation Index ◽  
Early Warning Systems ◽  
Precipitation Index ◽  
Calculation Algorithm ◽  
The Standardized Precipitation Index ◽  
Generalized Normal Distribution

ABSTRACT The Standardized Precipitation Index was developed as a probability-based index able to monitor rainfall deficit in a standardized or normalized way. Thus, the performance of this drought index is affected by the use of a distribution that does not provide an appropriate fit for the rainfall data. The goal of this study was to evaluate the adjustment of the gamma distribution for the rainfall amounts summed over several time scales (Pelotas, Rio Grande do Sul, Brazil), to assess the goodness-of-fit of alternative distributions to these rainfall series and to evaluate the normality assumption of the Standardized Precipitation Index series calculated from several distributions. Based on the Lilliefors test and on a normality test, it is verified that the gamma distribution is not suitable for calculating this Index in several timescales. The generalized normal distribution presented the best performance among all analysed distributions. It was also concluded that the drought early warning systems and the academic studies should re-evaluate the use of the gamma distribution in the Standardized Precipitation Index calculation algorithm. A computational code that allows calculating this drought index based on the generalized normal distribution has also been provided.

scholarly journals Computation of the Standardized Precipitation Index (SPI) and Its Use to Assess Drought Occurrences in Cameroon over Recent Decades

2014 ◽  
Vol 53 (10) ◽  
pp. 2310-2324 ◽  
Author(s):  
Guy Merlin Guenang ◽  
F. Mkankam Kamga
Keyword(s):  
Time Scales ◽  
Goodness Of Fit ◽  
Standardized Precipitation Index ◽  
Research Unit ◽  
Distribution Functions ◽  
Precipitation Index ◽  
Severe Drought ◽  
East Anglia ◽  
The Standardized Precipitation Index ◽  
Short Time

AbstractThe standardized precipitation index (SPI) is computed and analyzed using 55 years of precipitation data recorded in 24 observation stations in Cameroon along with University of East Anglia Climate Research Unit (CRU) spatialized data. Four statistical distribution functions (gamma, exponential, Weibull, and lognormal) are first fitted to data accumulated for various time scales, and the appropriate functions are selected on the basis of the Anderson–Darling goodness-of-fit statistic. For short time scales (up to 6 months) and for stations above 10°N, the gamma distribution is the most frequent choice; below this belt, the Weibull distribution predominates. For longer than 6-month time scales, there are no consistent patterns of fitted distributions. After calculating the SPI in the usual way, operational drought thresholds that are based on an objective method are determined at each station. These thresholds are useful in drought-response decision making. From SPI time series, episodes of severe and extreme droughts are identified at many stations during the study period. Moderate/severe drought occurrences are intra-annual in short time scales and interannual for long time scales (greater than 9 months), usually spanning many years. The SPI calculated from CRU gridded precipitation shows similar results, with some discrepancies at longer scales. Thus, the spatialized dataset can be used to extend such studies to a larger region—especially data-scarce areas.

scholarly journals Flash Drought Response to Precipitation and Atmospheric Evaporative Demand in Spain

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 165
Author(s):  
Iván Noguera ◽  
Fernando Domínguez-Castro ◽  
Sergio M. Vicente-Serrano
Keyword(s):  
Drought Index ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Rapid Decline ◽  
Spatial And Temporal Patterns ◽  
Evaporative Demand ◽  
Main Driver ◽  
The Standardized Precipitation Index ◽  
High Degree

Flash drought is the result of strong precipitation deficits and/or anomalous increases in atmospheric evaporative demand (AED), which triggers a rapid decline in soil moisture and stresses vegetation over short periods of time. However, little is known about the role of precipitation and AED in the development of flash droughts. For this paper, we compared the standardized precipitation index (SPI) based on precipitation, the evaporative demand drought index (EDDI) based on AED, and the standardized evaporation precipitation index (SPEI) based on the differences between precipitation and AED as flash drought indicators for mainland Spain and the Balearic Islands for 1961–2018. The results show large differences in the spatial and temporal patterns of flash droughts between indices. In general, there was a high degree of consistency between the flash drought patterns identified by the SPI and SPEI, with the exception of southern Spain in the summer. The EDDI showed notable spatial and temporal differences from the SPI in winter and summer, while it exhibited great coherence with the SPEI in summer. We also examined the sensitivity of the SPEI to AED in each month of the year to explain its contribution to the possible development of flash droughts. Our findings showed that precipitation is the main driver of flash droughts in Spain, although AED can play a key role in the development of these during periods of low precipitation, especially in the driest areas and in summer.

scholarly journals The Assessment of Climate Change Impact on Meteorological Draught Susceptability on Sampean Watershed

2021 ◽  
Vol 9 (4) ◽  
pp. 146
Author(s):  
Masita Ratih ◽  
Gusfan Halik ◽  
Retno Utami Agung Wiyono
Keyword(s):  
Climate Change ◽  
Atmospheric Circulation ◽  
Drought Index ◽  
Standardized Precipitation Index ◽  
Assessment Method ◽  
Precipitation Index ◽  
Climate Change Scenarios ◽  
Change Impact ◽  
The Standardized Precipitation Index ◽  
The Impact

Drought disasters that occur in the Sampean watershed from time to time have increased, both the intensity of events and the area affected by drought. The general objective of this research is to develop an assessment method for the impact of climate chan ge on vulnerability to drought disasters based on atmospheric circulation data. The specific objectives of this study are to model rainfall predictions based on atmospheric circulation data, predict rainfall in various climate change scenarios (Intergovernm ental Panel on Climate Change, IPCC – AR5), and assess vulnerability to drought disasters using a meteorological approach. The Standardized Precipitation Index (SPI) is one way to analyze the drought index in an area which was developed previous researcher. The Standardized Precipitation Index (SPI) is designed to quantitatively determine the rainfall deficit with various time scales. The advantage of the Standardized Precipitation Index (SPI) is that it is enough to use monthly rainfall data to compare drou ght levels between regions even with different climate types. To facilitate the presentation of the data base on the identification of d rought susceptibility, we need a system that can assist in building, storing, managing and displaying geographically ref erenced information in the form of spatial mapping. This research facilitates monitoring of the area of drought-prone areas, predicts drought levels, prevents future drought disasters, and prepares plans for rebuilding drought-prone areas in the Sampean watershed.

scholarly journals Meteorological Drought Index Mapping in Bangladesh Using Standardized Precipitation Index during 1981–2010

2017 ◽  
Vol 2017 ◽  
pp. 1-17 ◽  
Author(s):  
Md. Anarul Haque Mondol ◽  
Iffat Ara ◽  
Subash Chandra Das
Keyword(s):  
Drought Index ◽  
Management Strategies ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Precipitation Index ◽  
Spatiotemporal Variations ◽  
Distance Weighted ◽  
Index Mapping ◽  
The Standardized Precipitation Index ◽  
Inverse Distance

Natural disasters are a major concern in Bangladesh, particularly drought which is one of the most common disaster in Bangladesh. Drought needs to be explained spatially to understand its spatiotemporal variations in different areas. In this paper, the meteorological drought has been shown by using the Standardized Precipitation Index (SPI) method and illustrated through the Inverse Distance Weighted (IDW) method across Bangladesh. We used rainfall data of 30 meteorological stations in Bangladesh during the study period of 1981–2010. The results indicate that drought has been fluctuating and it has become a recurrent phenomenon during the study period. The SPI depicted the drought conditions that plunged dramatically in 1981, 1982, 1985, 1987, 1989, 1992, 1994, and 1996 and then gradually improved in 2004, 2006, and 2009 in the country. The present study demonstrated that drought occurred in Bangladesh on an average of 2.5 years. Drought was more prominent in the northern, south-western, and eastern regions in Bangladesh compared to the rest of the areas of the country. The outcomes of the present study will help in during disaster management strategies, particularly drought, by initiating effective plans and adaptation remedies in different areas of Bangladesh.

scholarly journals Modeling a Drought Index Using a Nonparametric Approach

2017 ◽  
Vol 19 (1) ◽  
pp. 58-68 ◽  
Keyword(s):  
Time Scales ◽  
Gamma Distribution ◽  
Drought Index ◽  
Standardized Precipitation Index ◽  
Kernel Density ◽  
Density Estimator ◽  
Monthly Precipitation ◽  
Nonparametric Approach ◽  
The Standardized Precipitation Index ◽  
Drought Classes

<p>Alternatively, to other studies that used parametric distributions (e.g. Gamma) in the estimation of the Standardized Precipitation Index (SPI), this study aims to apply a nonparametric method based on Kernel Density Estimator (KDE) for calculating the SPI. Results of the proposed method were compared with the ones from the most widely used parametric distribution, using a long dataset of monthly precipitation of four meteorological stations in Iran (including Bushehr, Mashhad, Tehran and Esfahan) over a period of 107 water years (1895-2002). The capability of KDE-based SPI was compared with the Gamma-based SPI at four-time scales of 3, 6, 9 and 12 months. The frequencies of the drought classes of SPI were calculated and compared with corresponding expected frequencies. The results revealed that the KDE is more consistent with the expected values of the SPI drought/wet classes frequencies (especially in the extreme classes) at all stations as well as at the four-time scales, compared to the Gamma distribution. The greatest deviation from the expected frequencies for KDE and Gamma distribution were about 10% and 150%, respectively. This study proposes a new analytical approach in modeling SPI that provides more accurate results pertaining frequency of occurrences of extreme drought events. The output of the study can be used in many fields (e.g. tourism, agriculture, insurance, etc.) that are influenced by severe droughts.</p>

scholarly journals Temporal and Spatial Interpolation of the Standardized Precipitation Index for Computational Efficiency in the Dynamic Drought Index Tool

2015 ◽  
Vol 54 (4) ◽  
pp. 795-810 ◽  
Author(s):  
Arthur T. DeGaetano ◽  
Brian N. Belcher ◽  
William Noon
Keyword(s):  
Gamma Distribution ◽  
Computational Efficiency ◽  
Spatial Interpolation ◽  
Large Scale ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Spi Index ◽  
Fixed Base ◽  
Distribution Parameters ◽  
The Standardized Precipitation Index

AbstractThe feasibility of interpolating gamma-distribution parameters between different precipitation accumulation intervals (durations) is statistically evaluated. The interpolation of these parameters for a specific accumulation interval, but ending on different dates, is similarly assessed. Such interpolation increases the computational efficiency of drought-monitoring tools that require calculation of the standardized precipitation index (SPI) for any user-specified accumulation period on any given day. Spatial interpolation of the distribution parameters is also assessed. Given a 60-yr period of record, few statistically significant differences were found between gamma-distribution percentiles interpolated between fixed base durations and those computed directly. Shorter interpolation intervals (generally 30 days) were required for the shortest (e.g., 30 days) durations, whereas interpolation over periods of as long as 180 days could be used for the longest (between 360 and 720 days) durations. Interpolating the distribution parameters to different ending dates on the basis of those computed for the end of each month was also appropriate. The spatial interpolation of gamma-distribution parameters, although viable in practice for monitoring large-scale drought conditions, was associated with larger SPI differences than was the spatial interpolation of the SPI index itself or the interpolation of historical precipitation and the subsequent calculation of gamma-distribution parameters on the basis of these values.

scholarly journals Hydrological response to different time scales of climatological drought: an evaluation of the Standardized Precipitation Index in a mountainous Mediterranean basin

2005 ◽  
Vol 9 (5) ◽  
pp. 523-533 ◽  
Author(s):  
S. M. Vicente-Serrano ◽  
J. I. López-Moreno
Keyword(s):  
Time Scales ◽  
Hydrological Cycle ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Drought Indices ◽  
Long Time ◽  
The Standardized Precipitation Index ◽  
Hydrological Droughts ◽  
Different Time Scales

Abstract. At present, the Standardized Precipitation Index (SPI) is the most widely used drought index to provide good estimations about the intensity, magnitude and spatial extent of droughts. The main advantage of the SPI in comparison with other indices is the fact that the SPI enables both determination of drought conditions at different time scales and monitoring of different drought types. It is widely accepted that SPI time scales affect different sub-systems in the hydrological cycle due to the fact that the response of the different water usable sources to precipitation shortages can be very different. The long time scales of SPI are related to hydrological droughts (river flows and reservoir storages). Nevertheless, few analyses empirically verify these statements or the usefulness of the SPI time scales to monitor drought. In this paper, the SPI at different time scales is compared with surface hydrological variables in a big closed basin located in the central Spanish Pyrenees. We provide evidence about the way in which the longer (>12 months) SPI time scales may not be useful for drought quantification in this area. In general, the surface flows respond to short SPI time scales whereas the reservoir storages respond to longer time scales (7–10 months). Nevertheless, important seasonal differences can be identified in the SPI-usable water sources relationships. This suggests that it is necessary to test the drought indices and time scales in relation to their usefulness for monitoring different drought types under different environmental conditions and water demand situations.

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