Analyzing spatial patterns of meteorological drought using Standardized Precipitation Index

Meteorological Applications (Impact Factor: 1.34). 12/2007; 14(4):329 - 336. DOI: 10.1002/met.33


Drought is a slow-onset, creeping natural hazard and a recurrent phenomenon in the arid and semi-arid regions of Gujarat (India). In Asia, the standardized precipitation index (SPI) has gained wider acceptance in the detection and the estimation of the intensity, magnitude and spatial extent of droughts. The main advantage of the SPI, in comparison with other indices, is that the SPI enables both determination of drought conditions at different time scales and monitoring of different drought types. This index captures the accumulated deficit (SPI < 0) or surplus (SPI > 0) of precipitation over a specified period, and provides a normalized measure (i.e. spatially invariant Z score) of relative precipitation anomalies at multiple time scales. In the present study, monthly time series of rainfall data (1981–2003) from 160 stations were used to derive SPI, particularly at 3-month time scales. This 3-month SPI was interpolated to depict spatial patterns of meteorological drought and its severity during typical drought and wet years. Correlation analysis was also done to evaluate usefulness of SPI to quantify effects of drought on food grain productivity. Further, time series of SPI were exploited to assess the drought risk in Gujarat. Copyright © 2007 Royal Meteorological Society

Download full-text


Available from: Patel N. R., Oct 03, 2014
  • Source
    • "The importance of climate for crop production is well recognized, and an increasing number of studies have also examined this relationship in South Asia (Parthasarathy et al., 1988; Kumar and Panu, 1997; Zubair, 2002; Selvaraju , 2003; Krishna Kumar et al., 2004; Patel et al., 2007; Welch et al., 2010; Subash and Ram Mohan, 2011; Sarker et al., 2012; Osborne and Wheeler, 2013). Many of the studies have however been limited to the national scale (Parthasarathy et al., 1988; Selvaraju, 2003; Krishna Kumar et al., 2004; Sarker et al., 2012; Osborne and Wheeler, 2013) or to specific provinces or states (Kumar and Panu, 1997; Patel et al., 2007) and focused only on monsoon season precipitation. In this article, we aim to contribute to the discussion on the use of drought indices in assessing climate impacts on rice yield variation by conducting a spatially explicit analysis for the GBM region. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Climate variability has major impacts on crop yields and food production in South Asia. The spatial differences of the impact are not, however, well understood. In this study, we thus aim to analyse the spatio-temporal relationship between precipitation and rice yields in the Ganges–Brahmaputra–Meghna region. The effects of rainfall variation on yields were analysed with regression models using the Standardized Precipitation Index (SPI) as an explanatory variable. Our results indicate that in large part of the study region, a strong relationship between precipitation and rice yields exists and the SPI at various lags chosen as the predictor variable performed well in describing the inter-annual yield variability. However, the study demonstrated large spatial variations in the strength of this relationship or optionally in the suitability of the chosen methodology for investigating it. In the mid-plains of the Ganges, which represent very important agricultural areas, precipitation variability has a strong impact on rice yields, while in downstream Ganges as well as in Brahmaputra, where precipitation is more abundant, the relationship was less pronounced. Where the performance of the regression models was weaker, it is likely that yield variation depended on other factors such as management practices or on other climate factors such as temperature. The results further showed that the SPI at 1, 3, 6 and 12 month lags calculated for the monsoon time (June–October) are most commonly the best at explaining the rice yield variability. The SPI can thus be considered a very useful predictor of rice yield variability in some parts of the study region, demonstrating that they could be used for agricultural applications and policy decisions to improve the region's food security.
    International Journal of Climatology 09/2015; DOI:10.1002/joc.4489 · 3.16 Impact Factor
    • "The SPI is a simple way for defining and monitoring drought events which was developed by McKee et al. (1993) and has become a popular measure of drought across the globe (Do-Woo et al. 2009; Duggins et al. 2010). Positive SPI values indicate greater than mean precipitation (or rainfall surplus), negative values represent less than mean precipitation (or deficit rainfall) (Patel et al. 2007), and the magnitude of SPI values represent the intensity of drought and wet events. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Abstract In recent years, droughts have become more intense and frequent in arid and semi-arid regions like Iran on the one hand, and water demand has been rising on the other hand and, as a result, their impacts are being aggravated. Therefore, the meteorological and hydrological droughts are receiving much more attention. This paper focused on the meteorological and hydrological drought characteristics for the overlapping periods of 3, 6, 9, and 12 months in northwestern Iran over the period of 1981–1982 to 2010–2011. The results showed that the majority of drought events over the reference periods were in the last 15 years from 1995–1996 to 2010–2011. Furthermore, the driest year based on the meteorological drought index was 2007–2008, while it was detected to be 2010–2011 based on the hydrological drought index. The Spearman’s rho and Kendall’s tau tests were used for the temporal trends analysis of the meteorological and hydrological droughts. The decreasing time series trends were more evident for the streamflow droughts index than for the standardized precipitation index series. In general, the results of the meteorological and hydrological drought trends showed that the study area suffered from the hydrological drought more than meteorological droughts. Moreover, the results revealed that the study area has become drier during the last three decades. Finally, the Spearman correlation analysis was applied to explore the relationships between meteorological and hydrological droughts which indicated a strong correlation between May–Jul-SPI series and the Jun– Aug-SDI series with a value of 0.65.
    Natural Hazards 07/2015; 79(20):1-22. · 1.72 Impact Factor
  • Source
    • "On the other hand, the Standardized Precipitation Index (SPI) is a very useful tool as well as an index to monitor meteorological drought which is exclusively based on precipitation data. According to McKee et al. (1993, 1995), SPI gives an easy and flexible way to monitor drought at a different scale (Table 2) ranging from near normal (À0.99) to extreme drought condition (<À2.0) and it has been recommended by various studies for its suitability to estimate meteorological drought at different time lag (Guttman, 1998; Patel et al., 2007; Kumar et al., 2009, 2012; Quiring and Ganesh, 2010; Poonia and Rao, 2012; Dutta et al., 2013; Zhang and Jia, 2013; Belayneh et al., 2014). "
    [Show abstract] [Hide abstract]
    ABSTRACT: Owing to its severe effect on productivity of rain-fed crops and indirect effect on employment as well as per capita income, agricultural drought has become a prime concern worldwide. The occurrence of drought is mainly a climatic phenomenon which cannot be eliminated. However, its effects can be reduced if actual spatio-temporal information related to crop status is available to the decision makers. The present study attempts to assess the efficiency of remote sensing and GIS techniques for monitoring the spatio-temporal extent of agricultural drought. In the present study, NOAA-AVHRR NDVI data were used for monitoring agricultural drought through NDVI based Vegetation Condition Index. VCI was calculated for whole Rajasthan using the long term NDVI images which reveals the occurrence of drought related crop stress during the year 2002. The VCI values of normal (2003) and drought (2002) year were compared with meteorological based Standardized Precipitation Index (SPI), Rainfall Anomaly Index and Yield Anomaly Index and a good agreement was found among them. The correlation coefficient between VCI and yield of major rain-fed crops (r > 0.75) also supports the efficiency of this remote sensing derived index for assessing agricultural drought.
    Egyptian Journal of Remote Sensing and Space Science 04/2015; 18(1):53-63. DOI:10.1016/j.ejrs.2015.03.006
Show more