scholarly journals Drought Analysis for Kuwait Using Standardized Precipitation Index

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Jaber Almedeij

Implementation of adequate measures to assess and monitor droughts is recognized as a major matter challenging researchers involved in water resources management. The objective of this study is to assess the hydrologic drought characteristics from the historical rainfall records of Kuwait with arid environment by employing the criterion of Standardized Precipitation Index (SPI). A wide range of monthly total precipitation data from January 1967 to December 2009 is used for the assessment. The computation of the SPI series is performed for intermediate- and long-time scales of 3, 6, 12, and 24 months. The drought severity and duration are also estimated. The bivariate probability distribution for these two drought characteristics is constructed by using Clayton copula. It has been shown that the drought SPI series for the time scales examined have no systematic trend component but a seasonal pattern related to rainfall data. The results are used to perform univariate and bivariate frequency analyses for the drought events. The study will help evaluating the risk of future droughts in the region, assessing their consequences on economy, environment, and society, and adopting measures for mitigating the effect of droughts.

2005 ◽  
Vol 9 (5) ◽  
pp. 523-533 ◽  
Author(s):  
S. M. Vicente-Serrano ◽  
J. I. López-Moreno

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.


2005 ◽  
Vol 2 (4) ◽  
pp. 1221-1246 ◽  
Author(s):  
S. M. Vicente-Serrano ◽  
J. I. López-Moreno

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 higher (>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 higher 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.


2021 ◽  
Vol 893 (1) ◽  
pp. 012022
Author(s):  
Misnawati ◽  
R Boer ◽  
F Ramdhani

Abstract Drought is a natural hazard that results from a deficiency of precipitation, leading to low soil moisture and river flows, reduced storage in reservoirs, and less groundwater recharge. This study investigates the spatial variations of drought characteristics (drought event frequency, duration, severity, and intensity). This study using the Standardized Precipitation Index (SPI) to analyse the drought characteristics in Central Java during 1990-2010. The rain gauge station data and CHIRPS rainfall data over Central Java is used to calculate the SPI index. The SPI was calculated at multiple timescales (1-, 3-, 6-, 12-, 24- and 48-month), the run theory was used for identification and characterization of drought events. Analysis of drought characteristics by SPI from 1990 to 2010 shows the longest drought event is four months, the maximum drought severity is 6.06, and the maximum drought intensity is 2.02. El Nino year probability drought occurrence reached 100% in August for moderate drought, severe drought, and extreme drought category, whereas the probability drought occurrences in the Normal and La Nina year range 0-70% for moderate drought, 0-50% for severe drought category and 0-40% for extreme drought category. The results of this study may help inform researchers and local policymakers to develop strategies for managing drought.


2008 ◽  
Vol 17 ◽  
pp. 23-29 ◽  
Author(s):  
A. Loukas ◽  
L. Vasiliades ◽  
J. Tzabiras

Abstract. This paper evaluates climate change effects on drought severity in the region of Thessaly, Greece. The Standardized Precipitation Index (SPI) has been used for estimation of drought severity. A geographical information system is applied for the division of Thessaly region to twelve hydrological homogeneous areas based on their geomorphology. Mean monthly precipitation values from 50 precipitation stations of Thessaly for the hydrological period October 1960–September 1990 were used for the estimation of mean areal precipitation. These precipitation timeseries have been used for the estimation of Standardized Precipitation Index (SPI) for multiple time scales (1-, 3-, 6-, 9-, and 12-months) for each sub-basin or area. The outputs of Global Circulation Model CGCM2 were applied for two socioeconomic scenarios, namely, SRES A2 and SRES B2 for the assessment of climate change impact on droughts. The GCM outputs were downscaled to the region of Thessaly using a statistical methodology to estimate precipitation time series for two future periods 2020–2050 and 2070–2100. A method has been proposed for the estimation of annual cumulative drought severity-time scale-frequency curves. These curves integrate the drought severity and frequency for various types of drought. The SPI timeseries and annual weighted cumulative drought severity were estimated and compared with the respective timeseries and values of the historical period 1960–1990. The results showed that the annual drought severity is increased for all hydrological areas and SPI time scales, with the socioeconomic scenario SRES A2 being the most extreme.


2011 ◽  
Vol 12 (2) ◽  
pp. 206-226 ◽  
Author(s):  
Aristeidis G. Koutroulis ◽  
Aggeliki-Eleni K. Vrohidou ◽  
Ioannis K. Tsanis

Abstract A modified drought index, named the spatially normalized–standardized precipitation index (SN-SPI), has been developed for assessing meteorological droughts. The SN–SPI is a variant index to the standardized precipitation index and is based on the probability of precipitation at different time scales, but it is spatially normalized for improved assessment of drought severity. Results of this index incorporate the spatial distribution of precipitation and produce improved drought warnings. This index is applied in the island of Crete, Greece, and the drought results are compared to the ones of SPI. A 30-year-long average monthly precipitation dataset from 130 watersheds of the island is used by the above indices for drought classification in terms of its duration and intensity. Bias-adjusted monthly precipitation estimates from an ensemble of 10 regional climate models were used to quantify the influence of global warming to drought conditions over the period 2010–2100. Results based on both indices (calculated for three time scales of 12, 24, and 48 months) from 3 basins in west, central, and east parts of the island show that 1) the extreme drought periods are the same (reaching 7% of time) but the intensities based on SN–SPI are lower; 2) the area covered by extreme droughts is 3% (first time scale), 16% (second time scale), and 25% (third time scale), and 96% (first time scale), 95% (second time scale), and 80% (third time scale) based on the SN–SPI and SPI, respectively; 3) concerning the longest time scale (48 months), more than half of the area of Crete is about to experience drought conditions during 28%, 69%, and 97% for 2010–40, 2040–70, and 2070–2100, respectively; and 4) extremely dry conditions will cover 52%, 33%, and 25% of the island for the future 90-year period using 12-, 24-, and 48-month SN–SPI, respectively.


2018 ◽  
Vol 10 (1) ◽  
pp. 181-196 ◽  
Author(s):  
Mehdi Bahrami ◽  
Samira Bazrkar ◽  
Abdol Rassoul Zarei

Abstract Drought as an exigent natural phenomenon, with high frequency in arid and semi-arid regions, leads to enormous damage to agriculture, economy, and environment. In this study, the seasonal Standardized Precipitation Index (SPI) drought index and time series models were employed to model and predict seasonal drought using climate data of 38 Iranian synoptic stations during 1967–2014. In order to model and predict seasonal drought ITSM (Interactive Time Series Modeling) statistical software was used. According to the calculated seasonal SPI, within the study area, drought severity classes 4 and 3 had the greatest occurrence frequency, while classes 6 and 7 had the least occurrence frequency. Results indicated that the best fitted models were Moving-Average or MA (5) Innovations and MA (5) Hannan-Rissenen, with 60.53 and 15.79 percentage, respectively. On the other hand, results of the prediction as well, indicated that drought class 4 with the highest percentages, was the most abundant class over the study area and drought class 7 was the least frequent class. According to results of trend analysis, without attention to significance of them, observed seasonal SPI data series (1967–2014), in 84.21% of synoptic stations had a negative trend, but this percentage changes to 86.84% when studying the combination of observed and predicted simultaneously (1967–2019).


2021 ◽  
Author(s):  
Tianliang Jiang ◽  
Xiaoling Su

<p>Although the concept of ecological drought was first defined by the Science for Nature and People Partnership (SNAPP) in 2016, there remains no widely accepted drought index for monitoring ecological drought. Therefore, this study constructed a new ecological drought monitoring index, the standardized ecological water deficit index (SEWDI). The SEWDI is based on the difference between ecological water requirements and consumption, referred to as the standardized precipitation index (SPI) method, which was used to monitor ecological drought in Northwestern China (NWRC). The performances of the SEWDI and four widely-used drought indices [standardized root soil moisture index (SSI), self-calibrated Palmer drought index (scPDSI), standardized precipitation-evaporation drought index (SPEI), and SPI) in monitoring ecological drought were evaluated through comparing the Pearson correlations between these indices and the standardized normalized difference vegetation index (SNDVI) under different time scales, wetness, and water use efficiencies (WUEs) of vegetation. Finally, the rotational empirical orthogonal function (REOF) was used to decompose the SEWDI at a 12-month scale in the NWRC during 1982–2015 to obtain five ecological drought regions. The characteristics of ecological drought in the NWRC, including intensity, duration, and frequency, were extracted using run theory. The results showed that the performance of the SEWDI in monitoring ecological drought was highest among the commonly-used drought indices evaluated under different time scales [average correlation coefficient values (r) between SNDVI and drought indices: SEWDI<sub></sub>= 0.34, SSI<sub></sub>= 0.24, scPDSI<sub></sub>= 0.23, SPI<sub></sub>= 0.20, SPEI<sub></sub>= 0.18), and the 12-month-scale SEWDI was largely unaffected by wetness and WUE. In addition, the results of the monitoring indicated that serious ecological droughts in the NWRC mainly occurred in 1982–1986, 1990–1996, and 2005–2010, primarily in regions I, II, and V, regions II, and IV, and in region III, IV, and V, respectively. This study provides a robust approach for quantifying ecological drought severity across natural vegetation areas and scientific evidence for governmental decision makers.</p>


Data ◽  
2020 ◽  
Vol 5 (4) ◽  
pp. 109
Author(s):  
Matthew P. Lucas ◽  
Clay Trauernicht ◽  
Abby G. Frazier ◽  
Tomoaki Miura

Spatially explicit, wall-to-wall rainfall data provide foundational climatic information but alone are inadequate for characterizing meteorological, hydrological, agricultural, or ecological drought. The Standardized Precipitation Index (SPI) is one of the most widely used indicators of drought and defines localized conditions of both drought and excess rainfall based on period-specific (e.g., 1-month, 6-month, 12-month) accumulated precipitation relative to multi-year averages. A 93-year (1920–2012), high-resolution (250 m) gridded dataset of monthly rainfall available for the State of Hawai‘i was used to derive gridded, monthly SPI values for 1-, 3-, 6-, 9-, 12-, 24-, 36-, 48-, and 60-month intervals. Gridded SPI data were validated against independent, station-based calculations of SPI provided by the National Weather Service. The gridded SPI product was also compared with the U.S. Drought Monitor during the overlapping period. This SPI product provides several advantages over currently available drought indices for Hawai‘i in that it has statewide coverage over a long historical period at high spatial resolution to capture fine-scale climatic gradients and monitor changes in local drought severity.


Sign in / Sign up

Export Citation Format

Share Document