A Novel Multi-Scalar Drought Index for Monitoring Drought: the Standardized Precipitation Temperature Index

Nowadays human beings are facing many environmental challenges because of frequently occurring drought hazards. Several adverse impacts of drought hazard are continued in many parts of the world. Drought has a substantial influence on water resources and irrigation. It may effect on the country’s environment, communities, and industries. Therefore, it is important to improve drought monitoring system. In this paper, we proposed a novel method – Standardized Precipitation Temperature Index (SPTI) for drought monitoring that utilize the regional tempreature. We compared the performance of our proposed drought index – SPTI with commonly used drought indices (i.e., Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI)) for 17 meteorological stations of Khyber Pakhtunkhwa (KPK) province (Pakistan) that have both extreme (arid and humid) climatic environment. We found that SPTI is strongly correlated with SPI and performed better than SPEI in low temperature regions for drought monitoring. In summary, SPTI is recommended for detecting and monitoring the drought conditions over different time scales.     

Projected Changes of Future Extreme Drought Events under Numerous Drought Indices in the Heilongjiang Province of China

Effective drought prediction methods are essential for the mitigation of adverse effects of severe drought events. This study utilizes the Reconnaissance Drought Index, Standardized Precipitation Index and Standardized Precipitation Evapotranspiration Index to assess the occurrence of future drought events in the study area of the Heilongjiang province of China over a period of 2016–2099. The drought indices were computed from the meteorological data (temperature, precipitation) generated by the global climate model (HadCM3A2). Moreover, Mann-Kendall trend test was applied for the assessment of future climatic trends and detecting probable differences in the behaviour of various drought indices. Drought forecasting periods has been divided into three categories: the early phase (1916–2030), middle phase (2031–2060) and late phase (2061–2099). The occurrence of future droughts is also ranked according to their intensity (mild, moderate, severe and extreme drought). Based on the drought results, more number of drought events are expected to occur during 12-month drought analysis are, RDI during 2084–2098 (DD = 14, DS = ?1.38), SPEI during 2084–2098 (DD = 14, DS = ?1.33) and SPI during 2084–2095 (DD = 12, DS = ?1.19). The 1st and 2nd months of the years studied predicted a warming trend, while the 7th, 8th, and 9th months predicted a wetter trend. Finally, it was observed that RDI is more sensitive to drought and indicated a high percentage of years under severe and extreme drought conditions during the drought frequency analysis. Conclusively, this study provides a strategies for water resources management and monitoring of droughts, in which drought indices like RDI can play a central role.     

干旱指数在四川省的适用性分析

干旱灾害频发严重制约着四川省的农业发展,为合理分析四川省干旱情况,干旱指数的选择尤为重要。本文基于四川省39个气象站点1960年-2013年的气象资料,分别计算1961年、1994年、2006年和2009年-2010年各站点相对湿润指数M、气象干旱综合指数CI、标准化降水指数SPI和标准化降水蒸散指数SPEI,利用Arcgis反距离插值法进行空间插值,并与中国气象灾害大典记录的四川省典型年干旱情况进行对比分析,进而评价四种干旱指数在四川省的适用性。结果表明:对于1961年夏旱,M指数和CI指数均表现出无旱或轻旱,SPI指数结果较实际情况偏小,SPEI指数监测出了干旱的重灾区,效果在四个干旱指标中最好;1994年夏伏旱,M指数监测结果偏小;CI指数出现了空报,对川东地区和川西高原的监测结果偏小,SPEI指数在达县、巴中一带结果偏小,而SPI指数在成都、绵阳一带的结果偏小。2006年伏旱,M指数监测结果偏小;CI指数比M指数效果稍好,但结果仍然偏小;SPI指数和SPEI指数监测出的干旱特征与实际一致;2009年-2010年的冬春连旱,SPEI指数效果最好,M指数次之,SPI指数效果最差。SPEI指数最能反映四川省典型干旱年干旱的空间分布特征。     

鄱阳湖干旱多尺度特征及其与月均水位的相关性

以鄱阳湖13个气象站1957~2013年的逐月降水量、平均气温、各站点纬度和同期水位站逐月平均水位为实验数据,分别计算1、3、6、12、24、48个月尺度下标准降水指数(SPI)和标准降水蒸散指数(SPEI)时间序列,并利用Morlet小波分析理论,分析了该序列多时间尺度变化特征。基于Mann-Kendall检验,分析了鄱阳湖气象干旱趋势特征;利用Spearman秩相关系数,研究了不同时间尺度SPI和SPEI序列与月平均水位的相关关系。研究表明,鄱阳湖流域SPI和SPEI序列存在约68个月变化的主周期,两个主要特征时间尺度变化的强分布;气象干旱与湖水位的相关关系随时间尺度的增大而减弱。     

Drought Monitoring Using the Multivariate Standardized Precipitation Index (MSPI)

One major characteristic of the Standardized Precipitation Index (SPI) is its flexibility to be calculated in a variety of time scales and hence being aware of different types of droughts. However, various time scales may result in confusion of the water resources’ researchers, decision makers and users in identifying and specifying drought periods in a certain region. To solve this problem in this article, a multivariate approach has been utilized having the ability to aggregate a variety of the SPI time series into a new time series called the Multivariate Standardized Precipitation Index (MSPI). The MSPI is based on the principal components analysis (PCA) of the SPI time series in a certain location. Having specified the first principal component’s (PC₁’s) scores, the MSPI would be simply attained by dividing PC₁’s values by the monthly standard deviation. In this article, MSPI’s capability in depicting the variability of the SPI time series (in five ranges of time scales, including 3–6, 6–12, 3–12, 12–24, and 24–48 months) was studied at four weather stations representing the four different climates in Iran from the driest to the wettest climates. The results showed that the PC₁ is able to justify more than 74 % of the variability for the selected sets of the SPI time scales in the studied climates. Also, it became clear that the drought and wet severity classes monitored by MSPIs matched very satisfyingly to those of the five sets of the SPI time scales. Therefore, in cases where the aggregation time scales for calculating the SPI are not previously known, this study recommends the researchers use the MSPI.     

基于SPEI干旱指数的东北地区干旱时空分布特征

基于东北地区86个国家基本气象站1960年-2014年逐月降水量和平均气温数据,计算不同时间尺度下的标准化降水蒸散指数(SPEI),分析不同时间尺度下东北地区季节、年际以及年代际干旱时空分布特征,并与实际干旱成灾面积进行对比分析,验证SPEI在东北地区干旱评估中的适用性。结果表明:春季、夏季和冬季重旱发生频率随时间尺度增大而升高;中旱发生频率随时间尺度增大而降低。近55年东北地区旱涝情势交替出现,干旱频率随年代际变化逐渐升高,干旱程度逐渐加重。整体来看,随时间尺度增加,极旱发生范围逐渐扩大。东北三省在春季、夏季和秋季均有不同频率的干旱事件发生;冬季吉林和辽宁无极旱发生;黑龙江中部无重旱发生。     

基于多模式情景的长江中下游未来气象干旱时空演变特征分析

为了分析未来时期(2020-2099年)长江中下游区域气象干旱演变特征,选取跨行业影响模式比较计划(ISI-MIP)的4个全球气候模式,基于不同代表性浓度路径(RCP)的排放情景(RCP-2.6、RCP-6.0和RCP-8.5),分别计算了标准化降水指数(SPI)和标准化蒸散发指数(SPEI),探讨了两种指数对研究区气...     

Spatio-temporal Changes and Frequency Analysis of Drought in the Wei River Basin,China

This study has investigated the spatio-temporal changes of droughts from 1961 to 2005 in the Wei River Basin. The Standardized Precipitation Index (SPI) was employed to describe the droughts. The trends of SPI value at all the meteorological stations were calculated by using the modified Mann-Kendall (MMK) trend test method, indicating that the western basin has a significantly wet trend, whilst the eastern basin including the Guanzhong Plain has a trend towards drought . Since the historical droughts records were too short to fully investigate drought properties in this basin, a practical nonparametric method was proposed to calculate the joint probability distribution of drought properties, which overcomes the shortcomings of the univariate and parametric frequency analysis. The frequency analysis of drought in the Wei River Basin indicates that the Guanzhong Plain and the surrounding areas of Huanxian meteorological station have a high drought risks, whilst the western and northern basin except the surrounding areas of Huanxian station has a relatively low drought risk.     

Drought Occurrence Probability Analysis Using Multivariate Standardized Drought Index and Copula Function Under Climate Change

This study aims to investigate the effect of climate change on the probability of drought occurrence in central Iran. To this end, a new drought index called Multivariate Standardized Drought Index (MSDI) was developed, which is composed of the Standardized Precipitation Evapotranspiration Index (SPEI) and the Standardized Soil Moisture Index (SSI). The required data included precipitation, temperature (from CRU TS), and soil moisture (from the ESA CCA SM product) on a monthly time scale for the 1980–2016 period. Moreover, future climate data were downloaded from CMIP6 models under the latest SSPs-RCPs emission scenarios (SSP1-2.6 and SSP5-8.5) for the 2020–2056 period. Based on the normalized root mean square error (NRMSE), Cramer-von mises statistic (S_n), and Nash Sutcliffe (NS) evaluation criteria, the Galambos and Clayton functions were selected to derive copula-based joint distribution functions in both periods. The results showed that more severe and longer droughts will occur in the future compared to the historical period and in particular under the SSP5-8.5 scenario. From the derived joint return period, a drought event with defined severity or duration will happen in a shorter return period as compared with the historical period. In other words, the joint return period indicated a higher probability of drought occurrence in the future period. Moreover, the joint return period analysis revealed that the return period of mild droughts will remain the same, while it will decrease for extreme droughts in the future.

     

Drought Concepts and Characterization

Abstract

A better knowledge of droughts is required to improve water management in water scarce areas. To appropriately cope with droughts, there is the need to adopt adequate concepts relative to droughts and water scarcity, to properly use drought indices that help characterize them, including ones relative to their severity, and to develop prediction tools that may be useful for early warning and that may reduce the respective lead time needed for appropriate response. In this paper, concepts relative to drought and other water scarcity regimes are discussed aiming both to distinguish droughts from other water scarcity regimes and to base a common understanding of the general characteristics of droughts as hazards and disasters. Three main drought indices are described aiming at appropriate characterization of droughts: the theory of runs, the Palmer Drought Severity Index (PDSI), and the Standardized Precipitation Index (SPI). Their application to local and regional droughts in the region of Alentejo, Portugal is presented focusing on the respective comparison and possible adequateness for drought monitoring. Results indicate some difficulties in using the theory of runs, particularly because it requires a subjective definition of thresholds in precipitation and does not provide a standardized classification of severity. Results show that draught characterization with the PDSI and the SPI produce coherent information, but the PDSI is limited relative to the SPI because it requires more data to perform a soil water balance while the SPI needs only precipitation data, which are more easily available in numerous locations. It is concluded that adopting the SPI is appropriate, but there is advantage in combining different indices to characterize droughts.     

Recent Climate Trends and Drought Behavioral Assessment Based on Precipitation and Temperature Data Series in the Songhua River Basin of China

Precise analysis of spatiotemporal trends of temperature, precipitation and meteorological droughts plays a key role in the sustainable management of water resources in the given region. This study first aims to detect the long-term climate (monthly/seasonally and annually) trends from the historical temperature and precipitation data series by applying Spearmen’s Rho and Mann-Kendall test at 5 % significant level. The measurements of both climate variables for a total period of 49 years (1965–2013) were collected from the 11 different meteorological stations located in the Songhua River basin of China. Secondly, the two well-known meteorological drought indices including the Standardized Precipitation Index (SPI) and Reconnaissance Drought Index (RDI) were applied on normalize data to detect the drought hazards at 3, 6, 9 and 12 month time scale in the study area. The analysis of monthly precipitation showed significant (p < 0.05) increasing trends during the winter (November and December months) season. Similarly, the results of seasonal and annual air temperature showed a significant increase from 1 °C to 1.5 °C for the past 49 years in the basin. According to the Sen’s slope estimator, the rate of increment in seasonal temperature slope (0.26 °C/season) and precipitation (9.02 mm/season) were greater than annual air temperature (0.04 °C/year) and precipitation (1.36 mm/year). By comparing the results of SPI and RDI indices showed good performance at 9 (r = 0.96, p < 0.01) and 12 (r = 0.99, p < 0.01) month drought analysis. However, the yearly drought analysis at over all stations indicated that a 20 years were under dry conditions in entire study area during 49 years. We found the extreme dry and wet conditions in the study region were prevailing during the years of 2001 and 2007, and 1994 and 2013, respectively. Overall, the analysis and quantifications of this study provides a mechanism for the policy makers to mitigate the impact of extreme climate and drought conditions in order to improve local water resources management in the region.

     

Analysis of spatio-temporal evolution of droughts in Luanhe River Basin using different drought indices

Based on the monthly precipitation and air temperature from 1960 to 1989 in the Luanhe River Basin, the standardized precipitation evapotranspiration index(SPEI) and standardized precipitation index(SPI) at three- and six-month time scales and the self-calibrating Palmer drought severity index(sc-PDSI) were calculated to evaluate droughts in the study area. Temporal variations of the drought severity from 1960 to1989 were analyzed and compared based on the results of different drought indices, and some typical drought events were identified. Spatial distributions of the drought severity according to the indices were also plotted and investigated. The results reveal the following: the performances of different drought indices are closely associated with the drought duration and the dominant factors of droughts; the SPEI is more accurate than the SPI when both evaporation and precipitation play important roles in drought events; the drought severity shown by the sc-PDSI is generally milder than the actual drought severity from 1960 to 1989; and the evolution of the droughts is usually delayed according to the scPDSI. This study provides valuable references for building drought early warning and mitigation systems in the Luanhe River Basin.     

适宜表征农业干旱的气象干旱指标——以湖南省为例

以最新的全国土壤水再分析产品为参考,通过最大相关性分析确定最适宜表征湖南省农业干旱的标准化降水蒸散发指数(SPEI)时间尺度,进而分析湖南省1960-2014年农业干旱的时空演变特征。结果表明:全省尺度最适宜表征农业干旱的SPEI时间尺度为SPEI-6;基于SPEI-6表征的全省农业干旱在1960-2014年呈不显著减小趋势,中度及以上干旱的发生频率为14.4%,重度及以上干旱的发生频率为4.9%;在季节分布上,中度及以上农业干旱在冬季发生频率最高,其次为秋季;重度及以上农业干旱亦在冬季发生频率最高,其次为春季;在年代际变化上,农业干旱的发生频率在20世纪60年代最高,而后持续降低,90年代达到最低值,21世纪初又快速升高。     

Comparative evaluation of impacts of climate change and droughts on river flow vulnerability in Iran

Rivers in arid and semi-arid regions are threatened by droughts and climate change. This study focused on a comparative evaluation of the impacts of climate change and droughts on the vulnerability of river flows in three basins with diverse climates in Iran. The standardized precipitation-evapotranspiration index (SPEI) and precipitation effectiveness variables (PEVs) extracted from the conjunctive precipitation effectiveness index (CPEI) were used to analyze the drought severity. To investigate hydrological droughts in the basins, the normalized difference water index (NDWI) and the streamflow drought index (SDI) were calculated and compared. The effects of droughts were assessed under various representative concentration pathway (RCP) scenarios. Changes in the number of wet days and precipitation depth restricted hydrological droughts, whereas an increasing number of dry days amplified their severity. The projected increases in dry days and precipitation over short durations throughout a year under future climate scenarios would produce changes in drought and flood periods and ultimately impact the frequency and severity of hydrological droughts. Under RCP 4.5, an increase in the frequencies of moderate and severe meteorological/hydrological droughts would further affect the Central Desert Basin. Under RCPs 2.6 and 8.5, the frequencies of severe and extreme droughts would increase, but the drought area would be smaller than that under RCP 4.5, demonstrating less severe drought conditions. Due to the shallow depths of most rivers, SDI was found to be more feasible than NDWI in detecting hydrological droughts.     

Multivariate Frequency Analysis of Meteorological Drought Using Copula

The multivariate frequency analysis of droughts for Agartala (India) was carried out in the present study. The meteorological drought was modelled using Standardised Precipitation Index(SPI) at the time scale of 1, 3, 6 and 12 months. Three droughts variables i.e., duration, severity, interval were determined for SPI at the time scale of 1, 3, 6 and 12 months. For the construction of bivariate and trivariate joint distributions Archimedean and metaelliptical copulas were used. Upper tail dependence test was also carried out. The best copula was selected based on minimum value Akaike’s information criteria (AIC)) and Schwarz information criterion(SIC). The drought risk was estimated using joint probabilities and return period for the study area.     

Regional Drought Modes in Iran Using the SPI: The Effect of Time Scale and Spatial Resolution

In the present paper, regional drought modes in Iran are identified applying the Principal Component Analysis (PCA) and Varimax rotation to the Standardized Precipitation Index (SPI) computed on different time scales. Data used include gridded monthly precipitation covering the period 1951–2007 retrieved from the Global Precipitation Climatology Centre (GPCC) archive with different spatial resolutions (2.5, 1 and 0.5° resolution). The objective of the study is twofold: (i) Investigate the stability of drought spatial modes as a function of the SPI time scales used for monitoring the different kinds of drought, (ii) Evaluate the impact of the spatial resolution of gridded data on drought regionalization. For the coarse spatial resolution of 2.5°, results show four drought modes of distinct variability, which remain quite stable when the SPI time scale is varied from 1- to 24-month. Differently, for higher spatial resolutions drought modes appear more sensitive to the index time scale and become less spatially homogeneous as the time scale is increased. Moreover, the number of identified modes (sub-regions) may reduce to three or two, but in all cases the most well defined sub-region appears to be the southern one. This suggests that both the spatial resolution of precipitation data and the time scale may affect drought regionalization, i.e. the number of drought modes and their spatial homogeneity.     

Spatiotemporal Analysis of Droughts Over Different Climate Regions Using Hybrid Clustering Method

Assessment of spatiotemporal variations of drought is an efficient method for implementing drought mitigation strategies and reducing its negative impacts. This study aimed to assess the spatiotemporal pattern of short- to long-term droughts for an area with different climates. Therefore, 31 stations located in Iran were selected and the Standardized Precipitation Index (SPI) series with timescales of 3, 6, and 12 months were computed during the 1951-2016 period. A hybrid methodology including Maximal Overlap Discrete Wavelet Transform (MODWT) and K-means methods was used for obtaining the SPIs time-frequency properties and multiscale zoning of the area. The energy amounts of the decomposed subseries via the MODWT were applied as inputs for K-means. Also, the statistics in drought features (i.e. drought duration, severity, and peak) were assessed and the results showed that shorter term droughts (i.e. SPI-3 and -6) were more frequent and severe in the northern parts where the lowest values were obtained for drought duration. It was observed that the regions with more droughts frequency had the highest energy values. For shorter term droughts a direct relationship was obtained between the energy values and the mean SPIs, drought severity, and drought peak, whereas an inverse relationship was obtained for longer term drought. It was found that increasing the degree of SPI led to more similarity between the stations of each cluster. Also, the homogeneity of stations for the SPI-12 was slightly higher than the SPI-3 and -6.

     

Drought Characterisation Based on Water Surplus Variability Index

Drought assessment, characterisation and monitoring increasingly requires considering not only precipitation but also the other meteorological parameters such as an evapotranspiration. Thus, some new drought indices based on precipitation and evapotranspiration have been developed. This study introduces a new drought index named the water surplus variability index (WSVI). The procedure to estimate the index involves accumulation water surplus at different time scales. To approve the proposed procedure, the WSVI is compared with the standardized precipitation index (SPI), the reconnaissance drought index (RDI) and the standardized precipitation evapotranspiration index (SPEI) based on 1-, 3-, 6- and 12-month timescales using data from several weather stations located in regions with different aridity index. Near perfect agreement (d?~?1) between WSVI and SPI, RDI and SPEI was indicated in humid and sub-humid locations. The results also showed that the correlation coefficients between WSVI and SPI, RDI and SPEI were higher for semi-arid stations than for arid ones.     

Hydro-Climatological Drought Analyses and Projections Using Meteorological and Hydrological Drought Indices: A Case Study in Blue River Basin, Oklahoma

Understanding the characteristics of historical droughts will benefit water resource managers because it will reveal the possible impacts that future changes in climate may have on drought, and subsequently, the availability of water resources. The goal of this study was to reconstruct historical drought occurrences and assess future drought risk for the drought-prone Blue River Basin in Oklahoma, under a likely changing climate using three types of drought indices, i.e., Standardized Precipitation Index (SPI), Palmer Drought Severity Index (PDSI) and Standardized Runoff Index (SRI). No similar research has been conducted in this region previously. Monthly precipitation and temperature data from the observational period 1950?C1999 and over the projection period 2010?C2099 from 16 statistically downscaled Global Climate Models (GCM) were used to compute the duration, severity, and extent of meteorological droughts. Additionally, soil moisture, evapotranspiration (ET), and runoff data from the well-calibrated Thornthwaite Monthly Water Balance Model were used to examine drought from a hydrological perspective. The results show that the three indices captured the historical droughts for the past 50?years and suggest that more severe droughts of wider extent are very likely to occur over the next 90?years in the Blue River Basin, especially in the later part of the 21st century. In fact, all three indices display lower minimum values than those ever recorded in the past 50?years. This study also found that SRI and SPI (PDSI) had a correlation coefficient of 0.81 (0.78) with a 2-month (no appreciable) lag time over the 1950?C2099 time period across the basin. There was relatively lower correlation between SPI and PDSI over the same period. Although this study recommends that PDSI and SRI are the most suitable indices for assessing future drought risks under an increasingly warmer climate, more drought indices from ecological and socioeconomic perspectives should be investigated and compared to provide a complete picture of drought and its potential impacts on the dynamically coupled nature-human system.     

Evaluation and Assessment of Meteorological Drought by Different Methods in Trarza Region,Mauritania

Drought Indexes (DIs) are commonly used for assessing the effect of drought such as the duration and severity. In this study, long term precipitation records (monthly recorded for 44 years) in three stations (Boutilimit (station 1), Nouakchott (station 2), and Rosso (station 3)) are employed to investigate the drought characteristics in Trarza region in Mauritania. Six DI methods, namely normal Standardized Precipitation Index (normal-SPI), log normal Standardized Precipitation Index (log-SPI), Standardized Precipitation Index using Gamma distribution (Gamma-SPI), Percent of Normal (PN), the China-Z index (CZI), and Deciles are used for this purpose. The DI methods are based on 1-, 3-, 6-, and 12 month time periods. The results showed that DIs produce almost the same results for the Trarza region. The droughts are detected in the seventies and eighties more than the 1990s. Twelve drought years might be experienced in station 2 and six in stations 1 and 3 in every 44 years, according to reoccurrence probability of the gamma-SPI and log-SPI results. Stations 1 and 3 might experience fewer drought years than station 2, which is located right on the coast. In station 1, which is located inland, when the annual rainfall is less than 123 mm, it is likely that severe drought would occur. This is 63 mm/year for station 2 and 205 mm/year for station 3 which is located in the south west on the Senegal River. DI results indicate that the CZI and the gamma-SPI methods make similar predictions and the log-SPI makes extreme drought predictions for the monthly period for all the stations. For longer periods (3-, 6-, and 12 month period), for all the stations, the log-SPI and the gamma-SPI produce similar results, making severe drought predictions while the normal-SPI and the CZI methods predict more wet and fewer drought cases. The log-SPI, the gamma-SPI, PN and Deciles were able to capture the historical extreme and severe droughts observed in early 1970s and early 1980s.