Spatiotemporal Analysis of Drought Characteristics in Nineveh, Iraq using the Standardized Precipitation Evapotranspiration Index (SPEI)

] Dai [2011] (henceforth D11) reported that the PalmerDrought Severity Index (PDSI) is superior to other statisti-cally based drought indices including the StandardizedPrecipitation Index (SPI) and the Standardized PrecipitationEvapotranspiration Index (SPEI). D11 argued that given thephysical character of the PDSI water balance model, theindex provides robust estimates of drought severity becauseit takes the preceding conditions into account, in contrast toother drought indices that are based purely on past statisticsof particular climate variable(s). However, D11 has over-estimated the ability of the PDSI to realistically simulate thedistributed soil water balance at large spatial scales, andignored the inherent complexity and multiscalar character ofdrought phenomena, which are related to more than themoisture conditions of the soil. In this comment we discussthe complex characteristics of droughts and the limitationsof the PDSI to quantify drought conditions in a variety ofhydrological systems. We describe the advantages of statis-tically based drought indices including the SPI and the SPEI.ThefactthattheSPIandtheSPEIarenot(anddonotintendtobe) physically based indices is more liberating than con-straining, especially when the physical basis of PDSI can beseriously questioned.[

The purpose of this study is to analyze the spatiotemporal variations in drought in Serbia over recent decades using the standardized precipitation evapotranspiration index (SPEI). The analysis is performed for time series of 1-, 3-, 6-, and 12-month SPEI indices (SPEI-01, SPEI-03, SPEI-06 and SPEI-12, respectively) calculated using the E-OBS gridded dataset with a horizontal resolution of 0.1° for the period of 1950–2022. In general, it was found that negative SPEI trends prevailed in Serbia for all months and all analyzed SPEI timescales, indicating a more frequent appearance of droughts in recent decades. Moreover, for a large majority of month-timescale combinations, the area with a negative trend was larger than the area with a positive trend. For several reasons, we focused on the SPEI for August. First, the SPEI for this month shows one of the most pronounced negative trends, which is rather consistent over different timescales and consistent in terms of the area over which the trend was found to be significant. Statistically significant negative trends of SPEI-03, −06 and − 12 for August were found over 11, 17 and 38% of the country area, respectively. To better understand the trends and changes in the SPEI for August, focusing on extreme and severe drought events, an innovative trend analysis (ITA) was applied. It was found that the occurrence of both extreme and severe SPEI drought categories has doubled over the last thirty years in comparison with the previous thirty-year period. Additionally, more frequent transitions from neutral and wet categories to dry categories were observed through an application of the Markov chain. Second, the special focus on SPEI-03, −06 and − 12 for August was motivated by the fact that we found a significant correlation between these index values and the annual maize production in Serbia, indicating that the SPEI for August can be useful for the assessment of drought impact on agriculture. To better understand interannual variability and long-term trends, this paper also explores the relations between the SPEI over Serbia and large-scale circulation patterns, together with general global and continental warming trends. Our findings indicate that drought changes over recent decades may be driven by the interplay of long-term warming and large-scale circulation patterns. In the context of climate change, especially climate projections, Serbia is situated in a region for which climate projections of mean precipitation change demonstrate weak signals and often with conflicting signs of change within multimodel ensembles. From this point of view, our results can be seen as a contribution to a better understanding of changes in extremes, in our case droughts, that can be hidden by inconclusive changes in the mean values. Finally, due to the similar situation in terms of precipitation and drought trends and changes, our results may be relevant for a wider region, and not only for Serbia.

The Arabian Peninsula (AP) has been reported to experience increasing drought in recent decades. With this background, this study evaluates best performing Climate Model Intercomparison Project 6 (CMIP6) Global Climate Models (GCMs) for historical (1985–2014) simulations and future drought projections across the AP until 2100, using the standardized precipitation index (SPI) and standardized precipitation–evapotranspiration index (SPEI). We assess uncertainties from model differences, scenarios, timescales, and methods. Our findings reveal the limitations of most models in reproducing precipitation, leading to uncertainties in SPI projections. Nonetheless, CMIP6-GCMs better capture the increase in the current-day potential evapotranspiration (PET) and therefore the SPEI, which is dominated by PET. The Hargreaves based PET is identified as the most suitable method for SPEI projections. The rate of increase in PET surpasses that of precipitation in all scenarios by fivefold. Consequently, SPEI indicates projected increase in future droughts with greater changes in SSP585 and SSP370 scenario compared to SSP245 and SSP126. In general, drought will exacerbate in the AP despite uncertainties from indices selection, scenarios, and inter-model variability, followed by methods and timescales which predominantly impacts drought magnitude. Over findings emphasize the need for more reliable representation of the AP precipitation in climate models for improved drought projection over the AP to enhance planning and adaptation strategies.

Projecting drought characteristics over East African basins at specific global warming levels

Global warming has resulted in unevenly distributed changes in precipitation and evapotranspiration, which has some influence on dry/wet conditions, thus exerting a tremendous impact on national life and the social economy, especially agricultural production. In order to characterize the dry/wet variations in the Poyang Lake basin during 1958–2013, based on the potential evapotranspiration (PET) estimated by the Thornthwaite (TH) and Penman–Monteith (PM) formulas, two types of Standardized Precipitation Evapotranspiration Index (SPEI), namely SPEI_th and SPEI_pm, were calculated in this study. The characteristic of dry/wet variations in the Poyang Lake basin was analyzed and a comparative analysis of two SPEIs was conducted. The results indicate that both SPEI series showed a wet trend in the Poyang Lake basin on an annual scale as well as seasonal scales during 1958–2013, except for spring and autumn. A drying trend was observed in spring, while in autumn, the dry and wet conditions in two SPEIs had opposite trends. However, all trends from two SPEIs were not significant, except for summer SPEI_pm. Meanwhile, significant positive correlations were detected between precipitation and two SPEIs, with the correlation coefficients above 0.95, whereas negative correlations were detected between PET and two SPEIs, with the correlation coefficients ranging from −0.17 to −0.85. This indicates that precipitation was the main climatic factor to determine change in dry/wet conditions in the Poyang Lake basin. Although there were obvious differences between the accumulated values of the Penman–Monteith-based PET (ET_pm) and Thornthwaite-based PET (ET_th), trends in the SPEI_pm series were generally consistent with those in the SPEI_th series, revealing that the method for PET calculation was not critical to the change in dry/wet conditions. Moreover, the results of the conditional probability of SPEI_pm and SPEI_th show that both SPEI_pm and SPEI_th could detect wet or dry events that were identified by SPEI_pm or SPEI_th.

Anthropogenic climate change has significantly exacerbated the frequency and severity of Compound Drought and Heatwave (CDHW) events, increasing risks such as water shortages, wildfires, and heat-related mortality. Previous studies often use a single drought index, such as the Standardized Precipitation Index (SPI) or the Standardized Precipitation Evapotranspiration Index (SPEI), while our study uses both SPI and SPEI to elucidate the effect of different drought indices on the quantification of population exposure to CDHW events. Six General Circulation Models under four future Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5) are considered. Exposure is defined as the product of CDHW Magnitude (°C) and the population in each region (million people), providing a quantitative measure of how CDHW events affect populations. The role of potential evapotranspiration (PET) in CDHW population exposure projections is examined by comparing SPI, which considers only precipitation, with SPEI, which accounts for both precipitation and PET in drought measurements. Results show that after 2050, CDHW Magnitude population exposure diverges significantly across scenarios, with SSP3-7.0 exhibiting the largest increase, reaching 0.72 (SPI) and 1.78 (SPEI) million person-°C by the end of the century. Regions such as Western Africa (WAF), Southeastern Africa, and South Asia (SAS) experience the largest increases in population exposure under SSP3-7.0 with SPEI, reaching 6.93, 6.77, and 5.56 million person-°C, respectively. Additionally, regions like Western & Central Europe, the Mediterranean, WAF, Western Central Africa, Eastern Asia, and SAS display heightened sensitivity to PET, with discrepancies between SPEI and SPI projections exceeding 1 million person-°C. Attribution analysis reveals that climate change, particularly when drought is calculated using PET by SPEI, is the primary factor, followed by interaction change and population change. These findings emphasize the critical role of PET in CDHW projections and the need for region-specific adaptation strategies to manage escalating risks in highly vulnerable areas.

In this study, we investigate the spatiotemporal characteristics of drought in India and its impact on agriculture during the summer season (April–September). In the analysis, we use Standardized Precipitation Evapotranspiration Index (SPEI) datasets between 1982 and 2012 at the six-monthly timescale. Based on the criterion SPEI < −1, we obtain a map of the number of occurrences of drought and find that the humid subtropical Upper Middle Gangetic Plain (UMGP) region is highly drought-prone, with an occurrence frequency of 40%–45%. This UMGP region contributes at least 18%–20% of India’s annual cereal production. Not only the probability of drought, but the UMGP region has become increasingly drought-prone in recent decades. Moreover, cereal production in the UMGP region has experienced a gradual declining trend from 2000 onwards, which is consistent with the increase in drought-affected areas from 20%–25% to 50%–60%, before and after 2000, respectively. A higher correlation coefficient (−0.69) between the cereal production changes and drought-affected areas confirms that at least 50% of the agricultural (cereal) losses are associated with drought. While analyzing the individual impact of precipitation and surface temperature on SPEI at 6 month timescale [SPEI (6)] we find that, in the UMGP region, surface temperature plays the primary role in the lowering of the SPEI. The linkage is further confirmed by correlation analysis between SPEI (6) and surface temperature, which exhibits strong negative values in the UMGP region. Higher temperatures may have caused more evaporation and drying, which therefore increased the area affected by drought in recent decades.

As one of the extreme climatic events, the frequency and intensity of drought have great impacts on regional water resource. Water is a main limiting factor for plant growth in arid and semi-arid regions. Therefore, it is of great scientific significance to explore the spatiotemporal variations and future tendency of drought for the ecological environment in the Loess Plateau. Based on grid data of monthly precipitation and temperature from 1986 to 2019, we calculated standardized precipitation evapotranspiration index (SPEI) and drought frequency. The spatiotemporal patterns and its variations were analyzed at the seasonal and annual scales in the Loess Plateau using the Mann-Kendall test and Sen's slope estimation method. Finally, the future trend of drought was analyzed in the Loess Plateau by the NAR neural network combined with Hurst index. Results showed that the trend of aridification became more significant in the Loess Plateau, and that the frequency of droughts events exhibited great spatial variations at the interannual and seasonal scales during the study period. Specifically, the highest frequency of drought in the interannual, spring and winter was found in the southeast and west of the Loess Plateau, whereas the frequency of drought in summer and autumn was higher in the northwest. The frequency of moderate drought was the highest in summer compared with other seasons while the frequency of slight drought was the highest in interannual and other seasons. The Loess Plateau showed a trend of aridification in spring and summer, but this trend in autumn and winter became weaker in most areas of the study area. The SPEI value in the interannual, spring, and summer exhibited a decline trend in a future period in the Loess Plateau. The aridification would be enhanced. The Hurst index value was the largest and the persis-tence of its change remained stronger in summer. The possibility of continuous drought in summer would be higher than that in other seasons in the future.

This study was conducted to assess drought trend, frequency and extremity during 1966–2012 over widely different climatic regimes in Iran. Two drought indicators, i.e. the standardized precipitation index (SPI) and the standardized precipitation evapotranspiration index (SPEI), were employed to characterize the droughts at 3, 6, 12 and 24 month time scales. In addition, the Mann–Kendall test was used for trend analysis. There was a declining (drying) trend in the SPI and SPEI at 76% and 85% or more, respectively, of the investigated sites. The SPIs were not well correlated with the SPEIs over the hyper‐arid/arid regions, demonstrating the significance of reference evapotranspiration (ET0) inclusion for drought identification over these water‐limited areas. Furthermore, the SPEI appears not to be calculated reliably using temperature‐based ET0 equations and also when wind speed data are missing at hyper‐arid/arid sites. More frequent droughts were detected during 1998–2012, which can be attributed to more recurrent La Niña events in this period. Seasonally, a greater increment in drought frequency at 3 and 6 month time scales was found in the March–April–May period. The most extended droughts and the most intensive dry months were also captured over 1998–2012 for most locations. In the majority of cases, it seems that the 1998–2001, 2007–2009 and 2010–2012 La Niña events caused long and severe droughts. The drought frequency increment and the most extreme drought incidences seem to have adversely impacted the agricultural sector over the studied areas. Consequently, there is a need for adaptation to negate the influences of frequent intensive dry episodes in Iran.

Ethiopia is highly vulnerable to the impact of climate change due to its low adaptive capacity and a higher dependence on rain-fed agriculture for livelihood. The aim of this paper was to identify the long-term climatic trends and the magnitude of those trends and to analyse drought duration, frequency, and severity in southern and south-eastern Ethiopia based on climatic data (1980-2017). This research is a quantitative research method. The southern and south-eastern of Ethiopia were purposely selected based on a frequent occurrence of drought in the country. Monthly data were obtained from National Meteorological Agency (NMA) of Ethiopia. Mann-Kendall (MK) Test coupled with Sen’s Slope Estimator was used to analyse the trend of climatic data and its magnitude, and Standardized Precipitation Evapotranspiration Index (SPEI) was used to analysis drought characteristics. SPEI of 1-, 3- and 6-month timescales were calculated to understand drought characteristics. The result of the MK test showed that annual rainfall trend had non-significant decrease at all station except at Gode. The trend of annual maximum and minimum temperature is insignificantly increasing. The calculated SPEI revealed drought is more frequent and severe from time to time in the study area. Results showed that the most frequent, severe and prolonged droughts occurred during1999-2017 compared to 1980-1999. Climate change mitigation and proactive drought management approach is highly recommended in order to minimize the risk of drought.

This study was conducted to assess the impacts of climate change on drought over the Lake Urmia basin, Iran. Drought events for 2011–2040, 2041–2070, and 2071–2100 were analyzed based on the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) and were compared with the adopted baseline period (1976–2005). The SPI and SPEI were calculated using the precipitation and temperatures obtained from the second-generation Canadian Earth System Model (CanESM2) under Representative Concentration Pathway (RCP) 2.6 and RCP 8.5 as optimistic and pessimistic scenarios respectively. The results of SPI analyses revealed that under RCP 2.6 the frequency of droughts is almost constant while under RCP 8.5 drought frequency increased especially in the period 2071–2100. The calculated SEPI under both scenarios and during all future periods predict that the frequency and duration of droughts will increase. Generally, the difference between the SPI and SPEI is related to the input to each index. SPI is solely based on precipitation while the SPEI accounts for both precipitation and potential evapotranspiration (PET). Under global warming and changing climate, the significant role of PET was highlighted. It was concluded that the SPEI outperformed the SPI for drought studies under a changing climate.

Climate change impacts on water security in global drylands

Spatiotemporal analysis of multiscalar drought characteristics across the Loess Plateau of China

This study elucidates drought characteristics in China during 1980–2015 using two commonly used meteorological drought indices: standardized precipitation index (SPI) and standardized precipitation–evapotranspiration index (SPEI). The results show that SPEI characterizes an overall increase in drought severity, area, and frequency during 1998–2015 compared with those during 1980–97, mainly due to the increasing potential evapotranspiration. By contrast, SPI does not reveal this phenomenon since precipitation does not exhibit a significant change overall. We further identify individual drought events using the three-dimensional (i.e., longitude, latitude, and time) clustering algorithm and apply the severity–area–duration (SAD) method to examine the drought spatiotemporal dynamics. Compared to SPI, SPEI identifies a lower drought frequency but with larger total drought areas overall. Additionally, SPEI identifies a greater number of severe drought events but a smaller number of slight drought events than the SPI. Approximately 30% of SPI-detected drought grids are not identified as drought by SPEI, and 40% of SPEI-detected drought grids are not recognized as drought by SPI. Both indices can roughly capture the major drought events, but SPEI-detected drought events are overall more severe than SPI. From the SAD analysis, SPI tends to identify drought as more severe over small areas within 1 million km2 and short durations less than 2 months, whereas SPEI tends to delineate drought as more severe across expansive areas larger than 3 million km2 and periods longer than 3 months. Given the fact that potential evapotranspiration increases in a warming climate, this study suggests SPEI may be more suitable than SPI in monitoring droughts under climate change.

干旱是北京地区发生最频繁、波及面积最大、持续时间最长的一种自然灾害。基于1868—2010 年每月的降水和平均气温数据，应用综合了降水和气温变化共同效应的新的干旱指标标准化降水蒸散指数（SPEI）定量描述北京地区的干湿状况，并利用历史旱灾记录对其进行验证；采用连续小波转换(CWT)分析近150 a来的干旱振荡特征，并利用交叉小波变换(XWT)探论了干旱与大尺度气候因子之间的关系。结果表明：1）SPEI揭示的干旱与历史记录比较吻合，证明该指数可以在多时间尺度上有效地反映北京地区旱涝程度及其持续时间；2）北京地区干旱具有80—120个月年际尺度和250个月、480个月年代际尺度的周期振荡，呈现了同大尺度气候因子相似的变化特征；3）北京干旱变化与四大气候因子存在着多时间尺度的显著相关性，SPEI和北大西洋涛动（NAO）、北极涛动(AO)、太平洋涛动（PDO）都具有100—120个月和250个月的年代际主共振周期，而SPEI和厄尔尼诺-南方涛动（ENSO）在整个研究期内都表现出极显著的32—64个月年际主共振周期，同时SPEI与4个气候因子在共振周期上均体现出比较明确的时滞特征（2—6月不等）。因此，可以基于大尺度气象因子结合SPEI预测北京地区未来的干旱变化。;Drought occurs in nature when precipitation is significantly lower than normal. When lasting many months or even years in a large area, drought will develop into a natural hazard that permanently damages the environment and causes great economic losses. Thus, improving our knowledge about the variability and impacts of drought is fundamental to quantify the drought hazard and improve the prediction and drought mitigation. Beijing is located in the middle and lower reaches of Haihe River Basin, which belong to a temperate continental monsoon climate zone. The precipitation distribution is very uneven, and often accompanied by high temperature. So drought is one of the most frequently and enduring natural hazard that influences most area in Beijing, north China. In this paper, we analyzed the variability and possible teleconnections between drought occurrences and large-scale climate indices between 1868—2010 in Beijng, such as El Niño-Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Arctic Oscillation (AO), and Pacific Decadal Oscillation (PDO). The drought occurrences were quantified by a new drought index, Standardized Precipitation Evapotranspiration Index (SPEI) based on the data of monthly mean temperature and precipitation. The SPEI considers not only precipitation but also temperature data by means of evapotranspiration in calculation, allowing for a more complete approach to explore the effects of climate changes on drought occurrences under global warming. The SPEI can also be calculated at several time scales to adapt to the critical times of responses to drought in target natural and economic systems and to determine their resistance to drought. Local historical drought hazard records in Beijing since 1868 were used to improve the validation of SPEI. We then used the method of continuous wavelet transform (CWT) to analyze inter-decadal and decadal oscillation in the time and frequency of drought. Finally, we analyzed the correlations between SPEI and four large scale climate indices through the cross wavelet transform (XWT). The good agreement between SPEI and historical drought records proves that SPEI can effectively reflect the intensity and duration of drought in multi-temporal dimension in this region. SPEI of Beijing had 80—120 month, 250 month, and 480 month oscillation circles, which was similar to the pattern of the four large-scale climate indices. The significant coherence was found between SPEI and the four large-scale climate indices. There were the common patterns of 100—120 month decadal and 250 month inter-decadal oscillation circles between SPEI and NAO, AO, PDO, as well as a common pattern of 32—64 month inter-decadal oscillation circle between SPEI and ENSO during the whole period. There was a clear lag time (2—6 months) during the coherence circle. Therefore, we can forecast the future drought variations in Beijing based on the data of large scale climate indices and SPEI, which is useful for water resources management and agriculture. This article is an initial step to application of the new multi-scalar SPEI drought index in studying the drought variability and impacts in China.