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.     

Hydrologic model-based Palmer indices for drought characterization in the Yellow River basin,China

The Palmer indices (PIs) that have been most widely used for drought monitoring and assessment are criticized for two main drawbacks: coarse hydrological accounting processes with a simplified two-stage bucket soil water balance model and arbitrary rules for defining drought properties and standardizing index values through limited calibration and comparison. In this study, we introduce a new proposal of the VIC hydrologic model-based Palmer drought scheme, where traditional PIs (e.g. PDSI) can readily be calculated on the basis of distributed finescale hydrologic simulations. Moreover, recent variants of PI (i.e., SPDI and SPDI-JDI) also provide a preferable standardization strategy that allows probabilistic invariability and better spatio-temporal comparability of computed drought indices. Using gridded meteorological forcing, soil and vegetation data to drive the three-layer VIC model, both non-VIC and VIC-based PIs are investigated to examine their performances for drought characterization and detection. Results indicate that VIC hydrologic model would allow for adjustments in statistical properties of computed PDSI and VIC-based SPDI is also preferable to PDSI for better statistical robustness and spatio-temporal consistency/comparability. Moreover, the joint SPDI-JDI has the strength of integrating multi-scale probabilistic properties and drought information released by individual SPDI, providing overall drought conditions that take into account the onset, persistence and termination of droughts. At proposed 0.25° grid scale, the VIC-based SPDI-JDI indicates high frequency and long total time of drought condition in the Yellow River basin (YRB), China. Although no significant temporal trends are found in identified drought duration and severity, both the seasonal and annual drought index values demonstrate a downward trend (higher drought intensity) for considerable proportions of the YRB. These findings imply high drought risk and potential drying stress for this region. The new framework of hydrologic model-based PIs can help to strengthen our knowledge and/or practices in regional drought monitoring and assessment.     

Exploring spatiotemporal relationships among meteorological,agricultural, and hydrological droughts in Southwest China

Each type of drought has different characteristics in different regions. It is important to distinguish different types of droughts and their correlations. Based on gauged precipitation, temperature, simulated soil moisture, and runoff data during the period 1951–2012, the relationships among meteorological, agricultural, and hydrological droughts were analyzed at different time scales in Southwest China. The standardized precipitation evapotranspiration index (SPEI), soil moisture anomaly percentage index (SMAPI), and standardized runoff index (SRI) were used to describe meteorological, agricultural, and hydrological droughts, respectively. The results show that there was a good correlation among the three indices. SMAPI had the best correlation with the 3 month SPEI and SRI values. It indicates that agricultural drought was characterized by a 3-month scale. The three drought indices displayed the similar special features such as drought scope, drought level, and drought center during the extreme drought of 2009–2010. However, the scope and level of SPEI were bigger than those of SMAPI and SRI. The propagation characteristics of the three types of droughts were significantly different. The temporal drought process in typical grids reflect that the meteorological drought occurred ahead of agricultural and hydrological droughts by about 1 and 3 months, respectively. Agricultural drought showed a stable drought process and reasonable time periods for the drought beginning and end. These results showed the quantitative relationships among three types of drought and thus provided an important supporting evidence for regional drought monitoring and strategic decisions.     

Drought monitoring

Drought detection, monitoring and indices are closely related to its definition. The specific definition chosen for a particular drought analysis will affect the procedures one uses in drought detection and monitoring. The traditional Palmer Drought Severity Index (PDSI) has been proven to be ineffective in regions of predominantly irrigated agriculture.The recently developed ALERT (Automated Local Evaluation in Real Time) system is proposed for use in monitoring the spatial and temporal variations of drought in real time. The ALERT system uses standardized instruments, radio frequencies, software and hardware. It was originally developed as a flash flood waming system by local flood control districts and the National Weather Service. However, now it has expanded to over 100 other uses in the areas of natural and man-made disaster detection and warning. The successful ALERT system indicates the need for the continued development of a national drought monitoring index that is applicable to a wide range of climate, hydrologic and water resource environments.     

Drought monitoring

Drought detection, monitoring and indices are closely related to its definition. The specific definition chosen for a particular drought analysis will affect the procedures one uses in drought detection and monitoring. The traditional Palmer Drought Severity Index (PDSI) has been proven to be ineffective in regions of predominantly irrigated agriculture.The recently developed ALERT (Automated Local Evaluation in Real Time) system is proposed for use in monitoring the spatial and temporal variations of drought in real time. The ALERT system uses standardized instruments, radio frequencies, software and hardware. It was originally developed as a flash flood waming system by local flood control districts and the National Weather Service. However, now it has expanded to over 100 other uses in the areas of natural and man-made disaster detection and warning. The successful ALERT system indicates the need for the continued development of a national drought monitoring index that is applicable to a wide range of climate, hydrologic and water resource environments.     

An insight into the Palmer drought mechanism based indices: comprehensive comparison of their strengths and limitations

Considering the drawbacks of the original Palmer drought severity index (PDSI) in terms of its simplified hydrologic algorithm and spatio-temporal inconsistency, we compare six variants of PDSI derived from different combinations of two hydrologic algorithms and three standard processes so as to provide deep insights into the individual impacts of hydrological processing and standardization on final PDSI values as well as their combined effects. Investigations are conducted in whole Yellow River basin. On basis of 52 years’ (1961–2012) hydro-meteorological data, comprehensive analysis on multiple drought characteristics are carried out for each PDSI variant, combined with comparison of three crucial intermediate variables of PDSI. Results show that variable infiltration capacity (VIC) model based modification in the hydrologic accounting section significantly improve drought trends with more reasonable spatial distributions presented. For the statistical characteristics of drought areas and frequency, comparable performance is found between VIC-based modification and self-calibrating standard procedure-based modification, though they are derived from different mechanisms. However, in case of the coupling of these two modifications, indices derived from combined modifications perform poorly than single modification-based indices with unexpected high frequency of extreme events detected in certain regions. This reflects the complicated mechanism of PDSI and it is essential to propose an appropriate standardization to match the hydrological algorithm and further improve the performance of relevant drought index. With the crucial findings mentioned above, this study is promising to provide some theoretical supports and serve as a competent reference for future PDSI based researches.     

Scenarios of global municipal water-use demand projections over the 21st century

Abstract

A comparison study is presented of three methods for evaluating trends in drought frequency: the standardized precipitation index (SPI), the Palmer drought severity index (PDSI), and a new method for estimation of dry spells (DS), which is based on average daily temperature and precipitation, and takes into account the length of a spell. The methods were applied to climate data from 450 stations in the Elbe River basin for the period 1951–2003, as well as data from several stations with longer observed time series. Statistical methods were used to calculate trend lines and evaluate the significance of detected trends. The dry spells estimated with the new method show significant trends in the whole lowland part of the Elbe basin during the last 53 years, and at the 10% level almost everywhere in the German part of the basin excluding mountains and the area around the river mouth. The SPI and PDSI methods also revealed significant trends, but for smaller areas in the lowland. The new DS method provides a useful supplement to other drought indices for the detection of trends in drought frequency. Furthermore, the DS method was able to detect statistically significant trends in areas where the other two methods failed to find significant trends, e.g. in the loess region in the southwest of the German part of the basin, where small insignificant changes in climate can lead to significant changes in water fluxes. This is important, because the loess region is the area within the basin having the highest crop yields. Therefore, additional research has to be done to investigate possible impacts of detected trends on water resources availability, and possible future trends in drought frequency under climate change.     

Spatiotemporal variability of drought in the northern part of northeast China

The thermal and moisture balance of permafrost regions has been altered by global warming, profoundly influencing vegetation dynamics and forest carbon cycling. To understand the spatial and temporal characteristics and driving forces responsible for changes in moisture conditions in the permafrost region of the Greater and Lesser Hinggan Mountains, northeastern China, we assessed long‐term trends for temperature, precipitation, and the standardized precipitation‐evapotranspiration index. From 1951 to 2014, annual mean temperature had a significant increase trend and the annual precipitation was not with significant trend. Since 1951, the annual standardized precipitation‐evapotranspiration index has decreased significantly at the boundary between regions with seasonal soil freezing and permafrost, suggesting that conspicuous permafrost degradation and moisture loss has occurred. The study area can be divided into 4 parts with a different balance between thermal and moisture conditions: the northern Songnen Plains, the Hulun Buir Sand Land, the middle reaches of the Heilongjiang River, and the Mohe region. However, only the middle reaches of the Heilongjiang River showed an obvious long‐term drying trend. The 4 areas showed quasi‐periodic oscillation and sea surface temperature during the winter half‐year affected drought intensity in the northern of Songnen Plains. When El Niño strengthened, moisture conditions increased in the northern of Songnen Plains, whereas stronger La Niña events decreased water availability. The result of this study will be beneficial for regional water resource management and prepare for potential drought hazards in the northeastern China.     

Drought assessment using a multivariate drought index in the Luanhe River basin of Northern China

With climate change and the rapid increase in water demand, droughts, whose intensity, duration and frequency have shown an increasing trend in China over the past decades, are increasingly becoming a critical constraint to China’s sustainable socio-economic development, especially in Northern China, even more so. Therefore, it is essential to develop an appropriate drought assessment approach in China. To propose a suitable drought index for drought assessment, the Luanhe river basin in the northern China was selected as a case study site. Based on the Principal Component Analysis of precipitation, evapotranspiration, soil moisture and runoff, the three latter variables of which were obtained by using the Variable Infiltration Capacity land surface macro-scale hydrology model, a new multivariate drought index (MDI) was formulated, and its thresholds were determined by use of cumulative distribution function. To test the applicability of the newly developed index, the MDI, the standardized precipitation index (SPI) and the palmer drought severity index (PDSI) time series on a monthly scale were computed and compared during 1962–1963, 1968 and 1972 drought events. The results show that the MDI exhibited certain advantages over the PDSI and the SPI, i.e. better assessing drought severity and better reflecting drought evolution. The MDI formulated by this paper could provide a scientific basis for drought mitigation and management, and references for drought assessment elsewhere in China.     

Improving drought predictability in Arkansas using the ensemble PDSI forecast technique

Drought prediction is important for improved water resources management and agriculture planning. Although Arkansas has suffered severe droughts and economic loss in recent years, no significant study has been done. This study proposes a local nonparametric autoregressive model with designed stochastic residual-resampling approach to produce ensemble drought forecasts with associated confidence. The proposed model utilizes historical climate records, including drought indices, temperature, and precipitation to improve the quality of the short-term forecast of drought indices. Monthly forecasts of Palmer Drought Severity Index (PDSI) in Arkansas climate divisions show remarkable skills with 2–3 month lead-time based on selected performance measure such as, Normalized Root Mean Square Error (NRMSE) and the Kuiper Skill Score (KSS). Rank histograms also show that the model captures the natural variability very well in the produced drought forecasts. The incorporation of categorical long-term precipitation prediction significantly enhances the performance of the monthly drought forecasts.     

Identification of extreme events using drought indices and their impact on the Danube lower basin discharge

In this study extreme droughts and extremely wet periods in the Danube upper and middle basin (DUMB) have been highlighted with specific indices. The most widely used indices have been considered to estimate both the dry and wet phenomena severity and the frequency or spatio‐temporal extension. The climatic condition of 15 meteorological stations situated in the Danube basin has been evaluated using four indices: Palmer Drought Severity Index (PDSI), Palmer Hydrological Drought Index (PHDI), Weighted PDSI (WPLM) and Palmer Z‐index (ZIND). The four indices have been analysed separately for each of the four seasons between 1901 and 2000. First the internal structure of the time series of the four indices has been analysed separately. Then the overall temporal characteristic has been analysed by means of the principal component of the Multivariate Empirical Orthogonal Functions decomposition of the four indices (PC1‐MEOF). For the discharge in the Danube lower basin, station Orsova has been chosen, representing an integrator of the discharges from the DUMB. A very close connection has been found between Palmer indices and Danube discharge in all seasons (with correlation coefficients greater then 0.80) excepting the spring season. A classification in five classes of both the four indices separately and the PC1‐MEOF has been achieved in order to highlight extreme events. The impact of phenomena quantified by Palmer indices in DUMB upon discharges in Danube lower basin is evident. It was demonstrated in this study that the Greenland‐Balkan Oscillation (GBO) influences the south‐east European hydro‐climatic regime more than the North Atlantic Oscillation (NAO) Index. Copyright © 2016 John Wiley & Sons, Ltd.     

A drought index for Rainfed agriculture: The Standardized Precipitation Crop Evapotranspiration Index (SPCEI)

A drought index is one of the main methods used for measuring drought and represents the basis of drought monitoring, early warning, and classification. On the basis of an analysis of the advantages and limitations of the Standardized Precipitation Evapotranspiration Index (SPEI), the Standardized Precipitation Crop Evapotranspiration Index (SPCEI), which is a drought index of rainfed agriculture, was constructed in this study. The applicable conditions of the SPCEI were then investigated, and the results showed that the SPCEI was suitable for dryland crops under non‐irrigated conditions in arid and semi‐arid areas. The difference between the SPEI and SPCEI is analysed. Compared with the SPEI, the SPCEI considers crop evapotranspiration and the crop growth stage and was found to be more suitable for monitoring agricultural drought. Qigihar, which is located in a semi‐arid area in western Heilongjiang Province, China, was then analysed as an example. The characteristics of the spatial and temporal variability of regional agricultural drought were analysed based on maize and soybean in dryland areas. The results for the different growth stages of maize and soybean showed that drought intensity is more serious in the initial stage in the middle part. In crop development, mid‐season and late season stage, the drought conditions gradually increased from north to south. The drought degree of the two crops at the initial stage gradually increased, and the drought degree at the crop development stage gradually decreased. The main reason is that precipitation gradually increases during the crop development stage.     

Drought hotspot analysis and risk assessment using probabilistic drought monitoring and severity–duration–frequency analysis

Drought hotspot identification requires continuous drought monitoring and spatial risk assessment. The present study analysed drought events in the agriculture‐dominated mid‐Mahanadi River Basin in Odisha, India, using crop water stress as a drought indicator. This drought index incorporated different factors that affect crop water deficit such as the cropping pattern, soil characteristics, and surface soil moisture. The drought monitoring framework utilized a relevance vector machine model‐based classification that provided the uncertainty associated with drought categorization. Using the proposed framework, drought hotspots are identified in the study region and compared with indices based on precipitation and soil moisture. Further, a bivariate copula is employed to model the agricultural drought characteristics and develop the drought severity–duration–frequency (S–D–F) relationships. The drought hotspot maps and S–D–F curves are developed for different locations in the region. These provided useful information on the site‐specific drought patterns and the characteristics of the devastating droughts of 2002 and 2012, characterized by an average drought duration of 7 months at several locations. The site‐specific risk of short‐ and long‐term agricultural droughts are then investigated using the conditional copula. The results suggest that the conditional return periods and the S–D–F curves are valuable tools to assess the spatial variability of drought risk in the region.     

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.     

Retrieving Groundwater Depletion and Drought in the Tigris‐Euphrates Basin Between 2003 and 2015

Quantitative estimates of the groundwater depletion and droughts in the Tigris‐Euphrates Basin (TEB) can be useful for sustainably managing its water resources. Here, data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission are used to infer the monthly changes in the total water storage of the TEB from January 2003 to December 2015. Additionally, the data of altimetry and output from land surface models are used to remove the contributions from lake water changes and other hydrological factors to obtain the total groundwater depletion (TGWD), human‐driven groundwater depletion (HGWD), and climate‐driven groundwater depletion. We conclude that an alarming rate of decrease in the total water storage and the loss of TGWD have an “accelerating” trend, as the trend during 2007 to 2015 was 3.6 times that during 2003 to 2006. Moreover, the HGWD is 116.09 Gt, which accounts for 98% of the TGWD. Finally, the total storage deficit index (TSDI) is derived from the GRACE data to characterize the drought of the TEB. The results show that TSDI agrees well with the actual drought rather than the Palmer drought severity index (PDSI) and that the TEB has been undergoing a severe drought since September 2007 according to both the TSDI and PDSI. The research in this study provides an effective and unique method for understanding the hydrological processes and sustainable use of water resources in regions or countries with little data, which is essential for more efficient, sustainable, and cross‐boundary cooperative water resource management.     

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.     

A theoretical drought classification method for the multivariate drought index based on distribution properties of standardized drought indices

Drought indices have been commonly used to characterize different properties of drought and the need to combine multiple drought indices for accurate drought monitoring has been well recognized. Based on linear combinations of multiple drought indices, a variety of multivariate drought indices have recently been developed for comprehensive drought monitoring to integrate drought information from various sources. For operational drought management, it is generally required to determine thresholds of drought severity for drought classification to trigger a mitigation response during a drought event to aid stakeholders and policy makers in decision making. Though the classification of drought categories based on the univariate drought indices has been well studied, drought classification method for the multivariate drought index has been less explored mainly due to the lack of information about its distribution property. In this study, a theoretical drought classification method is proposed for the multivariate drought index, based on a linear combination of multiple indices. Based on the distribution property of the standardized drought index, a theoretical distribution of the linear combined index (LDI) is derived, which can be used for classifying drought with the percentile approach. Application of the proposed method for drought classification of LDI, based on standardized precipitation index (SPI), standardized soil moisture index (SSI), and standardized runoff index (SRI) is illustrated with climate division data from California, United States. Results from comparison with the empirical methods show a satisfactory performance of the proposed method for drought classification.     

Study of indices for drought characterization in KBK districts in Orissa (India)

Drought is a temporary, random and regional climatic phenomenon, originating due to lack of precipitation leading to water deficit and causing economic loss. Success in drought alleviation depends on how well droughts are defined and their severity quantified. A quantitative definition identifies the beginning, end, spatial extent and the severity of drought. Among the available indices, no single index is capable of fully describing all the physical characteristics of drought. Therefore, in most cases it is useful and necessary to consider several indices, examine their sensitivity and accuracy, and investigate for correlation among them. In this study, the geographical information system‐based Spatial and Time Series Information Modeling (SPATSIM) and Daily Water Resources Assessment Modeling (DWRAM) software were used for drought analysis on monthly and daily bases respectively and its spatial distribution in both dry and wet years. SPATSIM utilizes standardized precipitation index (SPI), effective drought index (EDI), deciles index and departure from long‐term mean and median; and DWRAM employs only EDI. The analysis of data from the Kalahandi and Nuapada districts of Orissa (India) revealed that (a) droughts in this region occurred with a frequency of once in every 3 to 4 years, (b) droughts occurred in the year when the ratio of annual rainfall to potential evapotranspiration (Pae/PET) was less than 0·6, (c) EDI better represented the droughts in the area than any other index; (d) all SPI, EDI and annual deviation from the mean showed a similar trend of drought severity. The comparison of all indices and results of analysis led to several useful and pragmatic inferences in understanding the drought attributes of the study area. Copyright © 2007 John Wiley & Sons, Ltd.     

Summer drought index using SPEI based on 10-day temperature and precipitation data and its application in Zhejiang Province (Southeast China)

Summer drought is one of the main natural disasters in Zhejiang Province, China. To explore the characteristics of summer drought in Zhejiang Province during 1973–2013, the standardized precipitation evapotranspiration index (SPEI) is calculated based on 10-day precipitation and temperature data, and the summer drought index (DI) is defined. The Mann–Kendall test and Sen’s trend test are used to analyze changes of DI and drought area. Temperature is the main effect on changes of summer drought intensity and drought area. Significant increasing trends are observed for drought intensity, drought area, and extreme drought area, and their linear trend rates in northeast Zhejiang Province are larger than that in the southwest Zhejiang Province. DI and drought area time series have significant mutations in 2003. County-average DI and drought area during 2003–2013 are significantly larger than that during 1973–2002. The aforementioned SPEI could quantify, monitor and analyze summer drought onset, extent, and end.