Standardized Precipitation Evapotranspiration Index Drought Research Articles

Analysis of recent trends and spatiotemporal changes of droughts over Serbia using high-resolution gridded data

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.

Drought projection from CMIP6 Climate models over Morocco in the 21st century using the Standardized Precipitation Evapotranspiration Index (SPEI)

Quantifying how climate change drives drought in the 21st century is a priority to inform policy and adaptation planning in Morocco. SPEI drought index calculated from precipitation and temperature at 12 months’ time-scale covering the agricultural year September-August was carried out for each of the five models over the future period 2023-2099. The average changes across Morocco were obtained by comparing between the averages of SPEI values and the drought zone percentages (Light, Moderate, Severe and Extreme). Also, by comparing drought characteristics for the different 11-year time horizons 2023-2033, 2034-2044, 2045-2055, 2056-2066, 2067-2077, 2078-2088 and at the end 2089-2099. The study of future drought projections based on the SSP2-4.5 scenario of the CMIP6 models indicates a worsening of drought in Morocco during the second half of the century. Moderate drought is expected to predominate, with a sharp increase in the area affected by drought, even reaching 90% over six years. These results are essential for decision-makers in water resources management, highlighting the need to put in place strategies to mitigate the adverse effects of drought, including the efficient use of water resources.

Investigating the Effect of Climate Change on Drought Propagation in the Tarim River Basin Using Multi-Model Ensemble Projections

Recent studies on China’s arid and semi-arid regions, particularly the Tarim River Basin (TRB), have shown an increase in the intensity and frequency of extreme weather events. This research examines the link between meteorological droughts, as measured by the Standardized Precipitation Evapotranspiration Index (SPEI), and hydrological droughts, as indicated by the Standardized Runoff Index (SRI) and the Standardized Terrestrial Water Storage Index (STI), over various time scales. Historical data indicate that SPEI drought frequency (DF) was 14.3–21.9%, with prevalent events in the northern oases. SRI DF ranged from 9.0% to 35.8%, concentrated around the Taklamakan and Kumtag Deserts, while STI DF varied between 4.4% and 32.7%, averaging 15% basin-wide. Future projections show an increased DF of SPEI in deserts and a decrease in oases; SRI DF decreased in deserts but increased in oases. STI changes were more moderate. The study also found a higher risk of drought progression from SPEI to SRI in the southwestern and northeastern oases, exceeding 50% probability, while central and eastern TRB had lower risks. The western TRB and inner Taklamakan Desert faced higher risks of SPEI to STI progression, with probabilities over 45%, in contrast to the lower risks in the eastern and central oases. The concurrence of SRI/STI with moderate to extreme SPEI droughts led to a higher probability and area of SRI/STI droughts, whereas consistent SPEI types showed a reduced induced probability and extent of SRI/STI droughts. This study enhances the understanding of drought propagation from meteorological to hydrological droughts in the TRB and contributes to the prevention of hydrological drought to a certain extent.

Ensemble learning based on remote sensing data for monitoring agricultural drought in major winter wheat-producing areas of China

Drought is mainly triggered by the lack of precipitation, which can lead to insufficient water supply for crops thus affecting their growth and development. Reliable drought monitoring is crucial to understanding drought risk and avoiding drought-induced crop yield losses. Based on the Stacking regression method and multiple remotely-sensed drought factors from 2001 to 2017, this study developed an ensemble learning framework for monitoring agricultural drought in major winter wheat-producing areas in China. Stacking used five machine learning algorithms, namely, extreme gradient boosting, support vector regression, extra trees, and multi-layer perceptron, as the base learners to model the relationship between remote sensing drought factors and 1-, 3-, and 6-month standardized precipitation evapotranspiration index (SPEI). In this study, county-level winter wheat yield records and drought maps provided by the Global SPEI database (SPEIbase) were adopted to assess the suitability of Stacking-predicted SPEI drought maps in agricultural drought monitoring. The results show that Stacking outperformed other machine learning algorithms in terms of estimation accuracy, with the highest R2 value of 0.77 and the lowest root mean square error (RMSE) of 0.47. The longer the time scale of model-predicted SPEI, the higher its correlation with detrended winter wheat yields. The comparison with the drought maps of SPEIbase shows that the Stacking-predicted drought maps successfully captured the spatial pattern and intensity change of drought events. The approach presented in the study has good applicability for agricultural drought monitoring and could be extended to the rest of the areas.

Assessment of drought variability using SPEI under observed and projected climate scenarios over Uttar Pradesh, India

Drought is a widely occurring natural extreme that causes more severe negative impacts in the continuation of changing climate. This study presents the assessment of drought variability based on the standardized precipitation evapotranspiration index (SPEI) under historic and projected future climate scenarios. A probabilistic approach run theory is applied to define drought based on SPEI drought events, severity, intensity, and frequency according to the threshold of SPEI ≤ −1. The Statistical Downscaling Model (SDSM) was employed to downscale the meteorological variables. Drought variability under projected climate change is evaluated according to three scenarios: representative concentration pathways RCP 2.6, RCP 4.5, and RCP 8.5 using CanESM2 of the CMIP5 model for 32 years from 2019 to 2050. A drought event with maximum severity with a higher number of drought events associated with RCP 4.5 and RCP 8.5 among three scenarios, whereas synoptic stations Kanpur, Moradabad, Azamgarh, and Chitrakoot exhibit drought with higher maximum severity and frequency occurred under RCP 2.6. The Mann-Kendall (MK) test was used to assess the change in climatic variables and SPEI time series observed period. Results reveal a significant decrease in the trend of rainfall during monsoon season as well as annually observed at 16 locations except for Lucknow and Meerut and 83% of the stations exhibit a positive trend of SPEI at each timescale, which demonstrates most of the study regions exposed to the risk of drought, and locations namely Saharanpur, Meerut, and Aligarh, showed a positive trend, indicating a decrease in drying conditions over historic period.

Assessment of Meteorological and Agricultural Drought Analysis in Kırklareli province

The Global warming in the world cause to the climate change in this century. Agriculture is one of the sectors that can be most affected by climate change. Agricultural production is affected by precipitation and temperature variables. Due to the changes in these two parameters, the increase in the temperatures and the changes in the amount of precipitation in parallel with this disrupt the ecological balance and bring along the problems of desertification and drought. Agricultural production is highly dependent on meteorological factors in Thrace region. For this reason, it is expected that changes in climatic factors will affect the agriculture of the region positively or negatively. The aim of this study is to determine the frequency and severity of meteorological and agricultural drought with two indexes between 1963-2019 years in Kırklareli province. Standardized Precipitation Evapotranspiration Index (SPEI) was used to determine monthly, seasonal, six monthly and annual agricultural drought. According to annual agricultural drought results, it was calculated ten years mild arid (1969, 1985, 1986, 1990, 1991, 1992, 1993, 2011, 2016, and 2019), five years moderate arid (1983, 1989, 1996, 2008, and 2015), one year severe arid (1994), and two years extreme arid (2000 and 2001). Another drought index which is Standardized Precipitation Index (SPI) was used to determine meteorological drought. According to annual meteorological drought results, Eight years mild arid (1964, 1969, 1982, 1985, 1986, 1990, 1991, and 2011), seven years moderate arid (1983, 1989, 1992, 1993, 1994, 1996, and 2008), and two years extreme arid (2000, 2001) was figured out. According to linear correlation analysis, a good correlation was obtained for SPI and SPEI values, between annual, six monthly (Spring-Summer), and three monthly only winter and spring periods (R2=0.871, R2=0.901, R2=0.974, and R2=0.919), respectively. In the 57-year observation period; 18 years were determined as the arid year with SPEI index and 67% of these total arid years (12 arid years) occurred and 17 years were determined as the arid year with SPI index and 76% of these total arid years (13 arid years) occurred, between 1982 and 2002 years. The SPEI drought index which use precipitation, temperature and evapotranspiration data could give much good results to policy makers in drought mitigation policies in terms of giving results that are more accurate in agricultural production and drought assessments.

Drought index revisited to assess its response to vegetation in different agro-climatic zones

A combination of in-situ climatic variables and remote sensing data could provide dynamic information that facilitates to get effective dryness or wetness situations for planetary ecosystems. Thus, the traditional standardized precipitation evapotranspiration index (SPEI) was revisited by drought index (DI) using satellite soil moisture data and land surface evapotranspiration from Penman-Monteith-Leuning Version 2 (PML_V2) datasets to assess the dryness over 2417 station’s grid points in China. DI was compared with the self-calibrating Palmer drought severity index (scPDSI), SPEI and composite drought index (CDI) for three major land cover classes (croplands, grasslands, and forests) area. The independent evaluation was carried out using sun-induced chlorophyll fluorescence (vegetation photosynthesis), and normalized difference vegetation index datasets including crop yield. Results exhibited that DI performance was comparable with CDI than scPDSI and SPEI to capture the impact of drought on vegetation photosynthesis. Vegetation productivity assessed by NDVI was significantly affected by dryness in the northern and southern part of China using DI, CDI and scPDSI and compared to SPEI. DI displayed a positive correlation with wheat, maize, and rice yield. Revisited drought index showed significant results for vegetation productivity but still necessitate future work to improve DI for agricultural drought research.

Droughts Are Not the Likely Primary Cause for Abies sibirica and Pinus sibirica Forest Dieback in the South Siberian Mountains

Background. Since the mid-20th century, massive dieback of coniferous forests has been observed in the temperate and boreal zones across North America and Northern Eurasia. The first hypotheses explaining forest dieback were associated with industrial air pollution (acid rain). At the end of the century, new hypotheses emerged that supported critical climate-induced aridization to explain forest dieback. Many studies were based on the SPEI (Standardized Precipitation Evapotranspiration Index) drought index. Our goals were to investigate if the SPEI drought index was a suitable metric to reflect drought conditions in wet and moist dark-needled forests in the South Siberian Mountains (Mts) and if droughts trigger the dieback of those forests. Methods. We calculated the SPEI drought index, the annual moisture index AMI, potential evapotranspiration PET, and water balance dynamics for the period 1961–2019 for four transects in the South Siberian Mts. where decline/dieback of dark-needled Siberian pine and fir forests were identified in situ. Climate data from nine weather stations located at lower and upper elevations of each transect were used to calculate climatic index dynamics for the 1961–2019 period to identify dry and wet phases of the period. Results. Our findings showed that climatic moisture/dryness indices have rarely gone down to high risk levels during the last 60 years (1961–2019). AMI did not reach the critical limit, 2.25, characteristic of the lower border for the dark-needled taiga. SPEI values < −1.5 represent drought stress conditions for dark-needled conifers at the lower border, and these conditions occurred 3–4 times during the 60-year period. However, the annual water balance stayed positive in those years in wet and moist forests at mid-to-high elevations. Trees are known to survive occasional (1–2) dry years. We found that dark-needled conifer dieback often occurs in wet years with plentiful rain rather than in drought years. We found forest dieback was associated with the westerlies that bring atmospheric pollution from the west at 50–56 N latitudes, where the air masses cross populated regions that have widespread industrial complexes. Conclusions. We concluded that the observed decline of dark-needled conifers at middle-to-high elevations across the South Siberia’s Mts was conditioned by several plausible causes, among which air pollution seems to be more credible, rather than dry climatic conditions, as cited in recent literature. Results are essential for understanding these ecosystems and others as our planet changes. Other causes and mechanisms should be further investigated, which would necessitate creating infrastructure that supports multi-disciplinary, inter-agency teamwork of plant physiologists, foresters, chemists, etc.

Climatological Study of SPEI Drought Index Using Observed and CRU Gridded Dataset over Ethiopia

This study aims to investigate the standardized precipitation evapotranspiration index (SPEI) using the monthly observed and gridded Climate Research Unit (CRU) dataset across 13 stations in Ethiopia during the period 1970–2005. SPEI is computed at a 4-month timescale to represent drought during the Belg (February–May) and Kirmet (June–September) seasons separately, and at an 8-month timescale to represent the drought during these two seasons together (February–September). The results show that there are extremely strong correlations (R ≥ 0.8) between the estimated precipitation values from CRU and the observed values, with root mean square error (RMSE) of 4–99 mm and mean percentage error (MPE%) of −30 to 73% at most stations. For temperature and SPEI, the CRU shows almost strong correlations (0.6 ≤ R < 0.8), while the dominant values of RMSE and MPE are 0.7–5 °C and −22 to 26%, respectively, for temperature and 0.28–0.96 and −49 to 55%, respectively, for SPEI during the three seasons. It is also found that each of the SPEI clusters (dry, normal, and wet) estimated from CRU has a high success percentage (≥ 60%) at more than 50% of the stations, while the general accuracy exceeds 60% for the three SPEI clusters together at more than 75% of the stations. Finally, the correct hits for the estimated SPEI clusters from CRU are often within the corresponding observed cluster but may shift into another category (extreme, severe, and moderate) except for a few events.

A Drought Index: The Standardized Precipitation Evapotranspiration Irrigation Index

Drought has had an increasingly serious impact on humans with global climate change. The drought index is an important indicator used to understand and assess different types of droughts. At present, many drought indexes do not sufficiently consider human activity factors. This study presents a modified drought index and the standardized precipitation evapotranspiration irrigation index (SPEII), considering the human activity of irrigation that is based on the theory of the standardized precipitation evapotranspiration index (SPEI). This study aims to compare the modified drought index (SPEII) and ·SPEI and self-calibrating Palmer drought severity index (scPDSI) in the major crop-producing areas and use SPEII to evaluate the possible future drought characteristics based on CMIP5 Model. The Pearson correlation coefficient was used to assess the relevance between drought indexes (SPEII, SPEI, and scPDSI) and vegetation dynamics. The normalized difference vegetation index (NDVI) was used to represent the vegetation dynamics change. The results showed that SPEII had better performance than the SPEI and scPDSI in monitoring cropland vegetation drought, especially in cropland areas with high irrigation. The winter wheat growth period of the SPEII had better performance than that of summer maize in croplands with higher irrigation levels on the North China Plain (NCP) and Loess Plateau (LP). In general, future drought on the NCP and LP showed small changes compared with the base period (2001–2007). The drought intensity of the winter wheat growth period showed an increasing and steady trend in 2020–2080 under the representative concentration pathway (RCP) 4.5 scenario on the NCP and LP; additionally, the severe drought frequency in the central LP showed an increasing trend between 2020 and 2059. Therefore, the SPEII can be more suitable for analyzing and evaluating drought conditions in a large area of irrigated cropland and to assess the impacts of climate change on vegetation.

Is tree ring chronology of blue pine (Pinus wallichiana A. B. Jackson) prospective for summer drought reconstruction in the Western Himalaya?

• Tree ring chronology of blue pine is potential for long term SPEI (drought index) reconstruction. • Provides a reliable drought records (322-year’s) during monsoon season of the western Himalaya. • The spectral peaks (2–4 years) indicate drought fluctuations are linked mostly to ENSO events. • The reconstructed monsoon SPEI showed notable drying towards 1990 to 2017AD. A long record of drought beyond observable data is scarce in the Himalayan region, making it difficult to understand the region's long-term variability. Here we reconstructed the Standardized Precipitation Evapotranspiration Index (SPEI) a drought index using the tree-ring chronology of blue pine ( Pinus wallichiana ), to retrieve the past drought variations. The chronology is prepared from tree ring width series of well replicated samples of blue pine covering time span of 1660–2017 CE, from Darma Valley, Indian Western Himalaya. We observed that the combined expression of precipitation and temperature, conveyed as SPEI, is more effective in limiting tree growth during the monsoon season than either precipitation or temperature alone. The SPEI of June-September (monsoon season) exhibited a significant strong positive correlation (r = + 0.69, p < 0.001) with the tree ring chronology. Based on this relationship, we reconstructed monsoon SPEI covering 1696–2017 CE. The variance explained for the calibration period 47% of the actual SPEI variance of 1903–2017 CE. The extended SPEI time series indicates several high and low intensity droughts, which are consistent with the historical drought records of the Himalayan region. Furthermore, analyses of the spatial correlations reveal that the variation in the reconstructed monsoon SPEI is strongly associated with the regional summer drought variability in the Himalayan region. We recorded a strong teleconnection of SPEI data and sea surface temperature changes in the Indian and Pacific Oceans, indicating that Indian summer monsoon variability is prevalent for this region's summer monsoon SPEI. Furthermore, in the spectral analysis peaks between 2.0 and 4.0 years indicates that the summer drought fluctuation is linked to El Niño-Southern Oscillation (ENSO).

Spatial statistics techniques for SPEI and NDVI drought indices: a case study of Khuzestan Province.

Drought is a major water resources management issue in Iran. Khuzestan Province is in a drought state due to water shortage. Therefore, identifying areas at high risk of drought and when drought occurs is essential for drought management. For this purpose, this study used precipitation and temperature data of 12 selected stations and MODIS sensor images from the United States Geological Survey database in 2000–2017. The Standardized Precipitation Evapotranspiration Index (SPEI) and the Standardized Normalized Difference Vegetation Index (NDVI) were calculated using the Hargreaves–Samani method and ENVI software. Moreover, different spatial statistics techniques were used in the ArcGIS environment to analyze the results. Also, time series diagrams were drawn, and the trend was evaluated using the Mann–Kendall test. Finally, the distribution of NDVI values was investigated using EasyFit software, and the amount of drought damage was determined using NDVI. The investigation of the cluster maps of the Anselin Local Moran’s Index along with hot and cold spots formed for both SPEI and NDVI showed that drought severity was higher at the southern stations than at the semi-northern and northwestern ones in the province. Moreover, the survey results using the EasyFit software showed that the southern stations, including the Ahvaz, Mahshahr, and Omidiyeh-Aghajari stations, were more at risk of drought than the other stations due to the drought threshold. Furthermore, the total damage caused by drought for the Ahvaz and Abadan stations showed a damage rate of 50%.

Spatiotemporal variation of net primary productivity and its response to drought in Inner Mongolian desert steppe

The desert steppe in Inner Mongolia is an important part of the temperate grasslands in Central Asia and plays a key role in sustaining the regional pastoral livelihood and securing the ecological environment in northern China. Grassland net primary productivity (NPP) is an important indicator to ecosystem health, and is largely affected by the variation of precipitation, especially the frequent droughts in the desert steppe region. Monitoring the spatiotemporal changes of the NPP in relation with climate variation, especially with the drought events, is of great significance for assessing the total amount of grassland resources and predicting its future change trend, which is critically important for the development of grassland management regimes with the consideration of current and future climate changes. In the present study, we estimated the spatiotemporal variation of the NPP of the desert steppe in Inner Mongolia for the period from 2000 to 2019. We calculated the standardized precipitation evapotranspiration index (SPEI) of the study area, and analyzed its effects on vegetation NPP, especially for the drought effects. We found that the temporal trend line and Mann-Kendall statistical curve of vegetation NPP were basically consistent. Over the 20-year period, the NPP showed an overall downward trend during the plant growing season, or in summer and autumn period, but a slight upward trend in spring. Spatially, the plant growing season NPP slightly decreased on the 74.89% of the studied desert steppe area, the NPP in summer slightly decreased on the 72.25% of the area, while the NPP in spring slightly increased on the 61.8% of the area, and NPP in autumn significantly decreased on the 25.9% of the area. From the perspective of the persistence on different time scales, the proportion of moderate persistence-slight increase area covered 11.72% of the study area, and weak persistence-slight increase in spring covered 50.10% of the study area. The proportion of weak persistence-slight decrease in summer was 59.68%. The proportion of moderate persistence-slight decrease covered 18.83% in autumn. In the growing season, a positive correlation between NPP and SPEI accounted for 91.18% of the desert steppe area. Over 8% of the area showed a highly significant positive correlation, and 25.21% showed a significant positive correlation. Overall, 92.56% of the area showed a positive correlation in spring, and 87.26% showed a positive correlation in summer. A positive correlation was observed over 60.71% of the area in autumn. The research results show that the NPP results of CASA model simulating desert vegetation in Inner Mongolia are reliable. The SPEI drought index has good applicability in the study area. On the whole, the dynamic changes of NPP are closely related to drought. This research has important reference significance for regional ecosystem management and construction.

Potential impacts of stratospheric aerosol injection on drought risk managements over major river basins in Africa

Most socio-economic activities in Africa depend on the continent’s river basins, but effectively managing drought risks over the basins in response to climate change remains a big challenge. While studies have shown that the stratospheric aerosol injection (SAI) intervention could mitigate temperature-related climate change impacts over Africa, there is a dearth of information on how the SAI intervention could influence drought characteristics and drought risk managements over the river basins. The present study thus examines the potential impacts of climate change and the SAI intervention on droughts and drought management over the major river basins in Africa. Multi-ensemble climate simulation datasets from the Stratospheric Aerosol Geoengineering Large Ensemble (GLENS) Project were analysed for the study. The Standardized Precipitation Evapotranspiration Index (SPEI) and the Standardized Precipitation Index (SPI) were used to characterize the upper and lower limits of future drought severity, respectively, over the basins. The SPEI is a function of rainfall and potential evapotranspiration, whereas the SPI is only a function of rainfall, so the difference between the two indices is influenced by atmospheric evaporative demand. The results of the study show that, while the SAI intervention, as simulated in GLENS, may offset the impacts of climate change on temperature and atmospheric evaporative demand, the level of SAI that compensates for temperature change would overcompensate for the impacts on precipitation and therefore impose a climate water balance deficit in the tropics. SAI would narrow the gaps between SPEI and SPI projections over the basins by reducing SPEI drought frequency through reduced temperature and atmospheric evaporative demand while increasing SPI drought frequency through reduced rainfall. The narrowing of this gap lowers the level of uncertainty regarding future changes in drought frequency, but nonetheless has implications for future drought management in the basins, because while SAI lowers the upper limit of the future drought stress, it also raises the lower limit of the drought stress.

Zonal Patterns of Meteorological Drought on the Yunnan-Guizhou Plateau, China

Drought is a natural phenomenon caused by a shortage of water resources and has a great impact on agriculture, the economy, and the environment. To study the Spatio-temporal distribution and explore the zonal patterns of drought, this paper took the Yunnan-Guizhou Plateau (YGP) as the research region, selected the air temperature, relative humidity, sunshine duration, wind speed, and precipitation data from 47 meteorological stations on the YGP. First, the standardized precipitation evapotranspiration index (SPEI) was calculated, and then the Spatio-temporal distribution of YGP drought was analyzed with the SPEI, Mann–Kendall test, and principal component analysis (PCA). Finally, the correlations between the average SPEI, drought characteristics extracted from the SPEI, and longitude/elevation/latitude were analyzed with the linear regression method, and then the zonal patterns of the YGP drought were obtained. The results revealed that the annual and seasonal SPEI values mainly decreased. Because the first component of the SPEI (the largest eigenvalue makes it the most important component) in annual and winter had a poor relationship with longitude/elevation, its correlation was weak, while the average SPEI values in other seasons were significantly correlated with longitude/elevation (α = 0.001), and the absolute value of the correlation coefficient was between 0.6879–0.9453. Except for PC1 in annual and winter, PC1 and PC2 were significantly correlated with longitude/elevation (α = 0.001), and the absolute value of the correlation coefficient was between 0.5087–0.9501. The duration, severity, intensity, frequency of drought were significantly correlated with longitude/elevation (α = 0.001) in most situations. The average SPEI values and drought characteristics showed a good multivariate linear correlation with longitude, latitude, and elevation, indicating that drought exhibited strong zonal patterns. This study will provide new ideas for drought research and technical support for regional industrial layouts, planting structure adjustments, and drought and disaster reduction.

Application of meteorological drought for assessing watershed health using fuzzy-based reliability, resilience, and vulnerability

Extreme events, such as droughts, lead to considerable detrimental impacts on watersheds, especially in arid and semi-arid regions. To develop measures for mitigation of drought and formulate management plans, efficient methods are needed for assessing watershed health and risk. This study developed a Reliability, Resilience, and Vulnerability-based fuzzy framework (DRRV-Fuzzy) compared to the traditional method (DRRV-Fixed) for assessing watershed health and risk under drought. To this aim, the Standardized Precipitation-Evapotranspiration Index (SPEI) and Standardized Precipitation Index (SPI) of meteorological drought were employed to evaluating the proposed framework in the Zayandehrud River basin of Iran from 1983 to 2017. Also, to examine the role of both traditional and fuzzy methods for extreme droughts, the 2000 to 2017 period has been chosen to evaluate Rel, Res, and Vul indicators in the study area. The proposed framework yielded more efficient and different results from the traditional method. Results revealed that: (1) because of the evapotranspiration effects in SPEI drought index, vulnerability is expected to be larger than over SPI index, which fuzzy approach can clarify it better; (2) the fuzzy method can quantify the categories of failure types of drought in the watershed and detected drought failures relative to the threshold value; (3) the fuzzy framework was more efficient than the fixed approach for quantifying watershed health and drought risk, which was developed by DRRV metrics; (4) according to both fixed and fuzzy techniques, the health of Zayandehrud River basin was affected by drought, especially at a higher time scale (12-month time).

Assessment of Meteorological Drought with Application of Standardized Precipitation Evapotranspiration Index (SPEI) for Tripura, Northeast India

Drought is one of the major water-related natural hazards. Understanding the spatial and temporal variation of rainfall is of great importance in water resources planning and management as it is related with food security and management of scarce water resource, which becomes critical in case of drought events. The advent of GIS to produce spatially interpolated drought map helps the water managers to undertake appropriate measures in drought relief and prioritization of drought mitigation works. Limitation of literature on Tripura suggests that study of drought over Tripura could help in strengthening of mitigation planes and rationalization of disaster management policies. Hence, the present study is focused to investigate the drought persistence and severity in the Tripura state of India during the period 1980-2013, using Standardized Precipitation Evapotranspiration Index (SPEI). Three time scale i.e., 3, 6 and 12 month time scales were opted for the study. Gridded monthly precipitation data distributed over the four districts of Tripura was used for drought analysis. Significant drought events were detected over the study area during the selected period. Annual analysis of SPI time series showed that the study area received the intense drought during the year 1985. Geospatial technique was used to generate the SPEI drought map for the year 1985.

Accuracy Assessment of the SPEI, RDI and SPI Drought Indices in Regions of Iran with Different Climate Conditions

Considering the impact of drought on agricultural products and human food security, the selection of the appropriate drought index to assess drought conditions is very important. Therefore, in this research, based on the relationship between the percent annual yield loss (AYL) of winter wheat (Triticum sativum) and three commonly used drought indices, i.e. Standardized Precipitation Evapotranspiration Index (SPEI), Reconnaissance Drought Index (RDI) and Standardized Precipitation Index (SPI), the accuracy of these indices was evaluated at 1-, 3-, 6- and 12-month time scales. Results showed that the average AYL at Ahvaz, Babolsar, Esfahan, Gorgan, Kerman, Mashhad, Ramsar, Rasht, Shiraz and Zabol was 66.64, 5.42, 97.52, 10.20, 98.57, 84.99, 2.47, 3.84, 77.03 and 97.07%, respectively. At stations with hyper-arid, semi-arid, Mediterranean, humid and hyper-humid type A climate conditions such as Zabol, Esfahan, Mashhad, Shiraz, Gorgan, Babolsar, Ramsar and Rasht stations, the calculated values of SPEI demonstrated the highest CC with AYL in winter wheat. At Kerman and Ahvaz, with arid climate conditions, the calculated values of the RDI had the greatest CC with AYL in winter wheat. Thus, in general, among the SPI, RDI and SPEI, the use of the SPEI is recommended for the assessment of drought characteristics.

Spatiotemporal drought analysis by the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI) in Sichuan Province, China

Drought refers to a meteorological disaster that causes insufficient soil moisture and damage to crop water balance due to long-term lack of precipitation. With the increasing shortage of water resources, drought has become one of the hot issues of global concern. The standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI) can effectively reflect the changes in drought characteristics of different geomorphologies in Sichuan on time and space scales, to explore the difference in drought characteristics between different physiognomy types in Sichuan Province, We calculated the SPI and SPEI values based on the data of 44 meteorological stations in Sichuan Province from 1961 to 2019 and used Mann–Kendall trend test and multivariable linear regression method (MLR) to quantify the significance of the drought characteristic trends at different time and space scales. The results as follow: (1) The SPEI drought trend in plain and hilly regions was greater than that in plateau and mountain regions on all time scales (− 0.039 year−1 for 1-month in hilly, − 0.035 year−1 for 1-month in plain, − 0.14 year−1 for 1-month in plateau, − 0.026 year−1 for 1-month in mountain) and the magnitude of trend of eastern (− 4.4 to 0.1 year−1) was lager than western (− 2.1 to 2.7 year−1), means that the drought trends transfer from northwest to east. (2) The drought intensity in the western region gradually increased (0.54–1.05) and drought events mainly occurred in the southwest plateau and central mountainous regions (24–47 times), means that drought meteorological hotspots were mainly concentrated in the Sichuan basin. (3) The MLR indicated altitude (H) is not the main influencing factor that causes the spatial unevenness of precipitation in Sichuan Province, but altitude (H), temperature (T), longitude (Lo) and latitude (La) can co-determined the precipitation. The results of this study are instructive and practical for drought assessment, risk management and application decision-making in Sichuan Province, and have guiding significance for agricultural disaster prevention, mitigation and agricultural irrigation in Sichuan Province.

Assessment of agricultural drought in Morocco based on a composite of the Vegetation Health Index (VHI) and Standardized Precipitation Evapotranspiration Index (SPEI)

According to IPCC, Morocco is a highly vulnerable country to extreme climate events, especially droughts; this will affect different socioeconomic sectors, mainly the agriculture sector. Droughts are controlled by the variability of precipitation and evapotranspiration but also not neglecting the effect of land surface conditions such as land surface temperature. In this present study, the remote sense observations MODIS Normalized Difference Vegetation Index (NDVI) and CMSAF Land Surface Temperature (LST) were used for calculating the Vegetation Health Index (VHI). The main advantage of remote sensing products is that they are reasonably efficient in terms of temporal and spatial coverage, and they are useful for the monitoring and assessment of drought in the near real-time. Furthermore, ERA5 Reanalysis-based SPEI is calculated. The goal of this study is to assess the spatial and temporal patterns of drought, this study offers the composite of SPEI and VHI drought monitoring obtained by plotting maps and graphs to show the monthly and annual variability of drought for the period 2000–2015 over the whole of Morocco. This monitoring can be used as a near real-time warning system in a changing climate.