Regional applicability of seven meteorological drought indices in China

The definition of a drought index is the foundation of drought research. However, because of the complexity of drought, there is no a unified drought index appropriate for different drought types and objects at the same time. Therefore, it is crucial to determine the regional applicability of various drought indices. Using terrestrial water storage obtained from the Gravity Recovery And Climate Experiment, and the observed soil moisture and streamflow in China, we evaluated the regional applicability of seven meteorological drought indices: the Palmer Drought Severity Index (PDSI), modified PDSI (PDSI_CN) based on observations in China, self-calibrating PDSI (scPDSI), Surface Wetness Index (SWI), Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), and soil moisture simulations conducted using the community land model driven by observed atmospheric forcing (CLM3.5/ObsFC). The results showed that the scPDSI is most appropriate for China. However, it should be noted that the scPDSI reduces the value range slightly compared with the PDSI and PDSI_CN; thus, the classification of dry and wet conditions should be adjusted accordingly. Some problems might exist when using the PDSI and PDSI_CN in humid and arid areas because of the unsuitability of empiricalparameters. The SPI and SPEI are more appropriate for humid areas than arid and semiarid areas. This is because contributions of temperature variation to drought are neglected in the SPI, but overestimated in the SPEI, when potential evapotranspiration is estimated by the Thornthwaite method in these areas. Consequently, the SPI and SPEI tend to induce wetter and drier results, respectively. The CLM3.5/ObsFC is suitable for China before 2000, but not for arid and semiarid areas after 2000. Consistent with other drought indices, the SWI shows similar interannual and decadal change characteristics in detecting annual dry/wet variations. Although the long-term trends of drought areas in China detected by these seven drought indices during 1961–2013 are consistent, obvious differences exist among the values of drought areas, which might be attributable to the definitions of the drought indices in addition to climatic change.     

On the Impact of Insufficient Atmospheric Moistening on the Low Annual Discharge of Large Rivers in European Russia

Water Resources - The regional peculiarities of annual atmospheric moistening in European Russia are investigated using Standardized Precipitation and Evapotranspiration Index (SPEI). It was found...     

Power spectral characteristics of drought indices in the Ebro river basin at different temporal scales

A deep spectral investigation of the monthly time series of Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) in 45 meteorological stations in the Ebro basin (Spain) from 1950 to 2006 for timescales ranging from 1 to 48 months was performed. In order to summarize the results for the whole basin, the spectral analysis was also carried out on the four principal components of SPI and SPEI. Results confirm that SPI and SPEI presents very similar spectral characteristics. At the shorter time scales, the signal of SPI and SPEI is characterized by purely random temporal fluctuations. The longer time scales tend to feature the signal as a smoothly varying time series or persistent, mostly due to the aggregated nature of the indices calculation. The comparative analysis of the spectral properties of the drought indices for all the 45 sites in the Ebro basin lead to the identification of global or regional effects discriminated by local effects. It was found that some periodical signals are common to almost all the sites, while others where only identified in specific meteorological stations.     

Observed trends and relationships between ENSO and standardized hydrometeorological drought indices in central Chile

Droughts are natural phenomena that severely affect socio economic and ecological systems. In Chile, population and economic activities are highly concentrated in its central region (i.e. between latitudes 29°S and 40°S), which periodically suffers from severe droughts affecting agriculture, hydropower, and mining. Understanding the dynamics of droughts and large-scale atmospheric processes that influence the occurrence of dry spells is essential for forecasting and efficient early detection of drought events. Central Chile's climate is marked by a significant El Niño Southern Oscillation (ENSO) influence that might help to better characterize droughts as well as to identify the effects of ENSO on the spatial and temporal characteristics of meteorological and hydrological droughts in the region. We analysed the behaviour of the Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Streamflow Index (SSI) time series for 6-month accumulation periods over the austral winter and summer seasons. Multiple linear regression (MLR) and Generalized Linear Models (GLM) showed a significant ENSO influence on dry events for SPEI-6 and SSI-6 during winter and summer. We found that the magnitude of correlation between ENSO and SPEI-6 has changed over the last decades becoming weaker in winter periods and increasing in spring summer periods. Increasing trends in meteorological and hydrological drought events were also identified, along all latitudes, with significant trends during winter in the southern latitudes, and during summer in the semi-arid and Mediterranean zones. These results indicate that drought mitigation actions and policies are necessary to overcome their adverse effects. Given the monthly persistence of ENSO and its relationship to drought indices, there are opportunities for drought monitoring and seasonal forecasting that could become part of national drought management systems.     

Impact of climate indicators on continental‐scale potential groundwater recharge in Africa

In the last decades, human activity has been contributing to climate change that is closely associated with an increase in temperatures, increase in evaporation, intensification of extreme dry and wet rainfall events, and widespread melting of snow and ice. Understanding the intricate linkage between climate warming and the hydrological cycle is crucial for sustainable management of groundwater resources, especially in a vulnerable continent like Africa. This study investigates the relationship between climate‐change drivers and potential groundwater recharge (PGR) patterns across Africa for a long‐term record (1960–2010). Water‐balance components were simulated by using the PCR‐GLOBWB model and were reproduced in both gridded maps and latitudinal trends that vary in space with minima on the Tropics and maxima around the Equator. Statistical correlations between temperature, storm occurrences, drought, and PGR were examined in six climatic regions of Africa. Surprisingly, different effects of climate‐change controls on PGR were detected as a function of latitude in the last three decades (1980–2010). Temporal trends observed in the Northern Hemisphere of Africa reveal that the increase in temperature is significantly correlated to the decline of PGR, especially in the Northern Equatorial Africa. The climate indicators considered in this study were unable to explain the alarming negative trend of PGR observed in the Sahelian region, even though the Standardized Precipitation‐Evapotranspiration Index (SPEI) values report a 15% drought stress. On the other hand, increases in temperature have not been detected in the Southern Hemisphere of Africa, where increasing frequency of storm occurrences determine a rise of PGR, particularly in southern Africa. Time analysis highlights a strong seasonality effect, while PGR is in‐phase with rainfall patterns in the summer (Northern Hemisphere) and winter (Southern Hemisphere) and out‐of‐phase during the fall season. This study helps to elucidate the mechanism of the processes influencing groundwater resources in six climatic zones of Africa, even though modelling results need to be validated more extensively with direct measurements in future studies. Copyright © 2016 John Wiley & Sons, Ltd.     

Temporal trends and spatial characteristics of drought and rainfall in arid and semiarid regions of Iran

Drought, a normal recurrent event in arid and semiarid lands such as Iran, is typically of a temporary nature usually leaving little permanent aftermath. In the current study, the rainfall and drought severity time series were analyzed at 10 stations in the eastern half of Iran for the period 1966–2005. The drought severity was computed using the Standardized Precipitation Index (SPI) for a 12‐month timescale. The trend analyses of the data were also performed using the Kendall and Spearman tests. The results of this study showed that the rainfall and drought severity data had high variations to average values in the study period, and these variations increased with increasing aridity towards the south of the study area. The negative serial correlations found in the seasonal and annual rainfall time series were mostly insignificant. The trend tests detected a significant decreasing trend in the spring rainfall series of Birjand station at the rate of 8.56 mm per season per decade and a significant increasing trend in the summer rainfall series of Torbateheydarieh station at the rate of 0.14 mm per season per decade, whereas the rest of the trends were insignificant. Furthermore, the 12‐month values of the standardized precipitation index decreased at all the stations except Zabol during the past four decades. During the study period, all of the stations experienced at least one extreme drought which mainly occurred in the winter season. Copyright © 2011 John Wiley & Sons, Ltd.     

Study of the temporal and spatial patterns of drought in the Yellow River basin based on SPEI

Drought is one of the severe natural disasters to impact human society and occurs widely and frequently in China,causing considerable damage to the living environment of humans.The Yellow River basin(YRB)of China shows great vulnerability to drought in the major basins;thus,drought monitoring in the YRB is particularly important.Based on monthly data of 124 meteorological stations from 1961 to 2015,the Standardized Precipitation Evapotranspiration Index(SPEI)was used to explore the temporal and spatial patterns of drought in the YRB.The periods and trends of drought were identified by Extreme-point Symmetric Mode Decomposition(ESMD),and the research stages were determined by Bernaola-Galvan Segmentation Algorithm(BGSA).The annual and seasonal variation,frequency and intensity of drought were studied in the YRB.The results indicated that(1)for the past 55 years,the drought in the YRB has increased significantly with a tendency rate of-0.148(10 a)~(-1),in which the area Lanzhou to Hekou was the most vulnerable affected(-0.214(10 a)~(-1));(2)the drought periods(2.9,5,10.2 and 18.3 years)and stages(1961–1996,1997–2002 and 2003–2015)were characterized and detected by ESMD and BGSA;(3)the sequence of drought frequency was summer,spring,autumn and winter with mean values of 71.0%,47.2%,10.2%and 6.9%,respectively;and(4)the sequence of drought intensity was summer,spring,winter and autumn with mean values of 0.93,0.40,0.05 and 0.04,respectively.     

Tropical drought patterns and their linkages to large-scale climate variability over Peninsular Malaysia

Ocean–atmosphere modes of climate variability in the Pacific and Indian oceans, as well as monsoons, regulate the regional wet and dry episodes in tropical regions. However, how those modes of climate variability, and their interactions, lead to spatial differences in drought patterns over tropical Asia at seasonal to interannual time scales remains unclear. This study aims to analyse the hydroclimate processes for both short- and long-term spatial drought patterns (3-, 6, 12- and 24-months) over Peninsular Malaysia using the Standardized Precipitation Index, Standardized Precipitation Evapotranspiration Index, and Palmer Drought Severity Index. Besides that, a generalized least squares regression is used to explore underlying circulation mechanisms of these spatio-temporal drought patterns. The tested drought indices indicate a tendency towards wetter conditions over Peninsular Malaysia. Based on principal component analysis, distinct spatio-temporal drought patterns are revealed, suggesting North–South and East–West gradients in drought distribution. The Pacific El Nino Southern Oscillation (ENSO), the South Western Indian Ocean (SWIO) variability, and the quasi-biennial oscillation (QBO) are significant contributors to the observed spatio-temporal variability in drought. Both the ENSO and the SWIO modulate the North–South gradient in drought conditions over Peninsular Malaysia, while the QBO contributes more to the East–West gradient. Through modulating regional moisture fluxes, the warm phases of the ENSO and the SWIO, and the western phases of the QBO weaken the southwest and northeast monsoon, leading to precipitation deficits and droughts over Peninsular Malaysia. The East–West or North–South gradients in droughts are related to the middle mountains blocking southwest and northeast moisture fluxes towards Peninsular Malaysia. In addition, the ENSO and QBO variations are significantly leading to short-term droughts (less than a year), while the SWIO is significantly associated with longer-duration droughts (2 years or more). Overall, this work demonstrates how spatio-temporal drought patterns in tropical regions are related to monsoons and moisture transports affected by the oscillations over the Pacific and Indian oceans, which is important for national water risk management.     

Multivariate Standardized Drought Index: A parametric multi-index model

Defining droughts based on a single variable/index (e.g., precipitation, soil moisture, or runoff) may not be sufficient for reliable risk assessment and decision-making. In this paper, a multivariate, multi-index drought-modeling approach is proposed using the concept of copulas. The proposed model, named Multivariate Standardized Drought Index (MSDI), probabilistically combines the Standardized Precipitation Index (SPI) and the Standardized Soil Moisture Index (SSI) for drought characterization. In other words, MSDI incorporates the meteorological and agricultural drought conditions for overall characterization of drought. In this study, the proposed MSDI is utilized to characterize the drought conditions over several Climate Divisions in California and North Carolina. The MSDI-based drought analyses are then compared with SPI and SSI. The results reveal that MSDI indicates the drought onset and termination based on the combination of SPI and SSI, with onset being dominated by SPI and drought persistence being more similar to SSI behavior. Overall, the proposed MSDI is shown to be a reasonable model for combining multiple indices probabilistically.     

Vegetation response to rainfall seasonality and interannual variability in tropical dry forests

Projected changes in rainfall seasonality and interannual variability are expected to have severe impacts on arid and semi‐arid tropical vegetation, which is characterized by a fine‐tuned adaptation to extreme rainfall seasonality. To study the response of these ecosystems and the related changes in hydrological processes to changes in the amount and seasonality of rainfall, we focused on the caatinga biome, the typical seasonally dry forest in semi‐arid Northeast Brazil. We selected four sites across a gradient of rainfall amount and seasonality and analysed daily rainfall and biweekly Normalized Difference Vegetation Index (NDVI) data for hydrological years 2000 to 2014. Rainfall seasonal and interannual statistics were characterized by recently proposed metrics describing duration, timing and intensity of the wet season and compared to similar metrics of NDVI time series. The results show that the caatinga tends to have a more stable response with longer and less variable growing seasons (3.1 ± 0.1 months) compared to the duration wet seasons (2.0 ± 0.5 months). The ecosystem ability to buffer the interannual variability of rainfall is also evidenced by the stability in the timing of the growing season compared to the wet season, which results in variable delays (ranging from 0 to 2 months) between the peak of the rainfall season and the production of leaves by the ecosystem. The analyses show that the shape and size of the related hysteresis loops in the rainfall–NDVI relations are linked to the buffering effects of soil moisture and plant growth dynamics. Finally, model projections of vegetation response to different rainfall scenarios reveal the existence of a maximum in ecosystem productivity at intermediate levels of rainfall seasonality, suggesting a possible trade‐off in the effects of intensity (i.e. amount) and duration of the wet season on vegetation growth and related soil moisture dynamics and transpiration rates. Copyright © 2016 John Wiley & Sons, Ltd.     

Ensemble prediction of regional droughts using climate inputs and the SVM–copula approach

In this study, the climate teleconnections with meteorological droughts are analysed and used to develop ensemble drought prediction models using a support vector machine (SVM)–copula approach over Western Rajasthan (India). The meteorological droughts are identified using the Standardized Precipitation Index (SPI). In the analysis of large‐scale climate forcing represented by climate indices such as El Niño Southern Oscillation, Indian Ocean Dipole Mode and Atlantic Multidecadal Oscillation on regional droughts, it is found that regional droughts exhibits interannual as well as interdecadal variability. On the basis of potential teleconnections between regional droughts and climate indices, SPI‐based drought forecasting models are developed with up to 3 months' lead time. As traditional statistical forecast models are unable to capture nonlinearity and nonstationarity associated with drought forecasts, a machine learning technique, namely, support vector regression (SVR), is adopted to forecast the drought index, and the copula method is used to model the joint distribution of observed and predicted drought index. The copula‐based conditional distribution of an observed drought index conditioned on predicted drought index is utilized to simulate ensembles of drought forecasts. Two variants of drought forecast models are developed, namely a single model for all the periods in a year and separate models for each of the four seasons in a year. The performance of developed models is validated for predicting drought time series for 10 years' data. Improvement in ensemble prediction of drought indices is observed for combined seasonal model over the single model without seasonal partitions. The results show that the proposed SVM–copula approach improves the drought prediction capability and provides estimation of uncertainty associated with drought predictions. Copyright © 2013 John Wiley & Sons, Ltd.     

Long-term periodic drought modeling

Drought modeling is essential to water resources management and planning. In this study, Fourier spectral analysis is used to examine the cyclic structure for drought patterns and develop a long-term periodic model. A case study for historical precipitation data, obtained from the arid region of Kuwait for the period spanning from January 1967 to December 2009, are converted to drought measurements following the Standardized Precipitation Index (SPI) criterion. The SPI calculations are performed for two time scales of 12 and 24 months. The periodogram technique used for both time scales reveals periodicities of 12, 14, 19, 26, 31, 43, 64, 103 and 258 months. It is advocated here that the 26- and 258-month periods present in the data are attributed, respectively, to a Quasi-Biennial Oscillation pattern and a solar cycle over which the magnetic polarity of the sun first reverses then reverts to its former state. The detected periods are manipulated in the SPI model to produce drought forecasts, which suggest that until the end of year 2024 the climate is considered normal to very wet. This finding may be implemented to assess policy requirements related to water resources management.     

Hydro-meteorological drought assessment under climate change impact over the Vu Gia–Thu Bon river basin,Vietnam

Hydro-meteorological drought was assessed with respect to climate change over an estuary catchment Vu Gia-Thu Bon in Central Vietnam, which economy is dependent on agriculture. The fully-distributed hydrological model MIKE SHE was used to simulate river flow over the study region for the period 1991–2010. Drought were assessed using the Standardized Precipitation Index and the Standardized Runoff Index. The future climate was studied using the regional climate model Weather Research and Forecasting by downscaling an ensemble of three global climate models – CCSM3.0, ECHAM5 and MIROC-medium resolution over current (1961–1990) and future climates (2011–2040), under the A2 emissions scenario. The results suggest that, despite hotter and wetter future climate, the area is likely to suffer more from severe and extreme droughts, increasing about 100% in the median range for drought characteristics. Thus, there is a need for proper adaptation and planning for water resources management in this region.     

A multimodel assessment of the climate change effect on the drought severity–duration–frequency relationship

In this study, the patterns of past and future drought occurrences in the Seoul region were analysed using observed historical data from the Seoul weather station located in the Korean Peninsula and four different types of general circulation models (GCMs), namely, GFDL:CM2_1, CONS:ECHO‐G, MRI:CGCM2_3_2 and UKMO:HADGEM1. To analyse statistical properties such as drought frequency duration and return period, the Standardized Precipitation Index was used to derive the severity–duration–frequency (SDF) curve from the drought frequency analysis. In addition, a drought spell analysis was conducted to estimate the frequency and change of drought duration for each drought classification. The results of the analysis suggested a decrease in the frequency of mild droughts and an increase in the frequency of severe and extreme droughts in the future. Furthermore, the average duration of droughts is expected to increase. A comparison of the SDF relationship derived from the observed data with that derived via the GCMs indicated that the drought severity for each return period was reduced as drought duration increased and that the drought severity derived from the GCMs was severer than the severity obtained using the observed data for the same duration and return period. Furthermore, among the four types of GCMs used in this study, the MRI model predicted the most severe future drought for the Seoul region, and the SDF curve derived using the MRI model also resulted in the highest degree of drought severity compared with the other GCMs. Copyright © 2012 John Wiley & Sons, Ltd.     

Cotton canopy reflectance under variable solar zenith angles: Implications of use in evapotranspiration models

Evapotranspiration (ET) is an important parameter in hydrologic processes and modelling. In agricultural watersheds with competing uses of fresh water including irrigated agriculture, estimating crop evapotranspiration (ET_c) accurately is critical for improving irrigation system and basin water management. The use of remote sensing-based basal crop coefficients is becoming a common method for estimating crop evapotranspiration for multiple crops over large areas. The Normalized Difference Vegetation Index (NDVI) and the Soil Adjusted Vegetation Index (SAVI), based on reflectance in the red and near-infrared bands, are commonly used for this purpose. In this paper, we examine the effects of row crop orientation and soil background darkening due to shading and soil surface wetness on these two vegetation indices through modelling, coupled with a field experiment where canopy reflectance of a cotton crop at different solar zenith angles, was measured with a portable radiometer. The results show that the NDVI is significantly more affected than the SAVI by background shading and soil surface wetness, especially in north–south oriented rows at higher latitudes and could lead to a potential overestimation of crop evapotranspiration and irrigation water demand if used for basal crop coefficient estimation. Relationships between the analysed vegetation indices and canopy biophysical parameters such as crop height, fraction of cover and leaf area index also were developed for both indices.     

Spatiotemporal analysis of climate variability (1971–2010) in spring and summer on the Loess Plateau,China

By using the Variable Infiltration Capacity model with Palmer Drought Severity Index (VIC‐PDSI) model and Standardized Precipitation Index (SPI), spatiotemporal trends of climate variation during the main growing seasons for plants of Loess Plateau between 1971 and 2010 were detected and characterized. The VIC‐PDSI model is established by combining the VIC model with PDSI. The simulation results and the grids system of VIC were applied to substitute for the two‐layer bucket‐type model to do the hydrological accounting, which could improve the physical mechanism of PDSI and expand its application range. Our results suggest that the climate of the study area has experienced a drying and warming trend during the past four decades. Apart from some individual years and regions, there was a perpetuation of water deficit over the Plateau both in spring and summer. The drought frequency increased from southeast to northwest in spring, while the drought frequency decreased from southeast to northwest in summer. The climate in the southern part of the Loess Plateau, accounting for 23.3% of the study region, showed a significant drying and warming trend in spring over the past four decades. The climate variability detected by VIC‐PDSI model shows good agreement with that monitored by SPI. Since a large part of the study region frequently suffered from water shortage during the main growing seasons for plants, people living in such drought‐prone areas should take measures to prevent the negative effects on agricultural production, reforestation, and regional food security caused by drought. Copyright © 2013 John Wiley & Sons, Ltd.     

Spatiotemporal variability of drought and the potential climatological driving factors in the Liao River basin

Spatiotemporal characteristics of drought based on the Standardized Precipitation Index (SPI) in the Liao River basin (LRB) are investigated in this study. High autocorrelation in SPI seems to lend itself to drought prediction. Drought is becoming more frequent, widespread, and severe in the LRB during the past several decades. Major factors affecting drought in this basin are analysed by investigating relationship between SPI and several circulations including western Pacific Subtropical High (WPSH), East Asian Summer Monsoon (EASM) and El Niño‐Southern Oscillation (ENSO) indices. Different correlation patterns between WPSH indices and SPI are obtained. Several significant positive correlations between the area, intensity of WPSH and SPI are observed in the west and the centre of the study area, while negative correlations are observed in the east. Reverse patterns are observed in the correlation between the ridge of westward longitude of WPSH and SPI. Corresponding lag‐correlation is dominated by positive correlations between the area, intensity of WPSH and SPI, and by negative correlation between the ridge of westward longitude of WPSH and SPI. EASM is mainly negative related with drought in the east of the LRB. Significant positive correlation between ENSO and SPI is mainly located in the east while negative correlation is located in west of the basin. Lag‐correlation (with lags of 1 to 12 months) between them is also investigated and results show that significant negative correlation is located in a broad area extending from the west to the centre of the basin, while less positive correlation is observed with the increase of lags. The possibility of employing general circulation models (GCMs) for drought prediction is discussed based on the above analyses. Copyright © 2011 John Wiley & Sons, Ltd.     

Analysis of agricultural drought in Iiuni,Eastern Kenya: application of a Markov model

In semi‐arid Kenya, episodes of agricultural droughts of varying severity and duration occur. The occurrence of these agricultural droughts is associated with seasonal rainfall variability and can be reflected by seasonal soil moisture deficits that significantly affect crop performance and yield. The objective of this study was to stochastically simulate the behaviour of dry and wet spells and rainfall amounts in Iiuni watershed, Kenya. The stochastic behaviour of the longest dry and wet spells (runs) and largest rainfall amounts were simulated using a Markov (order 1) model. There were eight raingauge stations within the watershed. The entire analysis was carried out using probability parameters, i.e. mean, variance, simple and conditional probabilities of dry and rain days. An analysis of variance test (ANOVA ) was used to establish significant differences in rainfall characteristics between the eight stations. An analysis of the number of rain days and rainfall amount per rain day was done on a monthly basis to establish the distribution and reliability of seasonal rainfall. The graphic comparison of simulated cumulative distribution functions (Cdfs) of the longest spells and largest rainfall amounts showed Markovian dependence or persistence. The longest dry spells could extend to 24 days in the long rainy season and 12 in the short rainy season. At 50% (median) probability level, the largest rainfall amounts were 91 mm for the long rainy season and 136 mm for the short rainy season. The short rains were more reliable for crop production than the long rains. The Markov model performed well and gave adequate simulations of the spells and rainfall amounts under semi‐arid conditions. Copyright © 2004 John Wiley & Sons, Ltd.     

A new standardized Palmer drought index for hydro‐meteorological use

Accepting the concept of standardization introduced by the standardized precipitation index, similar methodologies have been developed to construct some other standardized drought indices such as the standardized precipitation evapotranspiration index (SPEI). In this study, the authors provided deep insight into the SPEI and recognized potential deficiencies/limitations in relating to the climatic water balance it used. By coupling another well‐known Palmer drought severity index (PDSI), we proposed a new standardized Palmer drought index (SPDI) through a moisture departure probabilistic approach, which allows multi‐scalar calculation for accurate temporal and spatial comparison of the hydro‐meteorological conditions of different locations. Using datasets of monthly precipitation, temperature and soil available water capacity, the moisture deficit/surplus was calculated at multiple temporal scales, and a couple of techniques were adopted to adjust corresponding time series to a generalized extreme value distribution out of several candidates. Results of the historical records (1900–2012) for diverse climates by multiple indices showed that the SPDI was highly consistent and correlated with the SPEI and self‐calibrated PDSI at most analysed time scales. Furthermore, a simple experiment of hypothetical temperature and/or precipitation change scenarios also verified the effectiveness of this newly derived SPDI in response to climate change impacts. Being more robust and preferable in spatial consistency and comparability as well as combining the simplicity of calculation with sufficient accounting of the physical nature of water supply and demand relating to droughts, the SPDI is promising to serve as a competent reference and an alternative for drought assessment and monitoring. Copyright © 2013 John Wiley & Sons, Ltd.