Spatial and Time Variability of Drought Based on SPI and RDI with Various Time Scales

The spatial and temporal variability of droughts were studied for the Northeast Algeria using SPI and RDI computed with monthly precipitation data from 123 rainfall stations and CFSR reanalysis monthly temperature data covering the period 1979–80 to 2013–14. The gridded temperature data was interpolated to all the locations having precipitation data, thus providing to compute SPI and RDI with the time scales of 3-, 6- and 12-month with the same observed rainfall data. Spatial and temporal patterns of droughts were obtained using Principal Component Analysis in S-Mode with Varimax rotation applied to both SPI and RDI. For all time scales of both indices, two principal components were retained identifying two sub-regions that are similar and coherent for all SPI and RDI time scales. Both components explained more than 70% and 74% of drought spatial variability of SPI and RDI, respectively. The identified sub-regions are similar and coherent for all SPI and RDI time scales. The Modified Mann-Kendall test was used to assess trends of the RPC scores, which have shown non-significant trends for decreasing drought occurrence and severity in both identified drought sub-regions and all time scales. Both indices have shown a coherent and similar behavior, however with RDI likely showing to identify more severe and moderate droughts in the southern and more arid sub-region which may be due to its ability to consider influences of global warming. Results for RDI are quite uniform relative to time scales and show smaller differences among the various climates when compared with SPI. Further assessments covering the NW and NE of Algeria using longer time series should be performed to better understand the behavior of both indices.     

Analysis of Drought from Humid,Semi-Arid and Arid Regions of India Using DrinC Model with Different Drought Indices

The study aims at evaluating the various drought indices for the humid, semi-arid and arid regions of India using conventional indices, such as rainfall anomaly index, departure analysis of rainfall and other indices such as Standard Precipitation Index (SPI) and Reconnaissance Drought Index (RDI) that were analyzed using the DrinC software. In SPI, arid region has seven drought years, whereas humid and semi-arid regions have four. In case of RDI, the humid and semi-arid regions have 11 drought years, whereas arid regions have 10 years. The difference in SPI and RDI was due to the fact that RDI considered potential evapotranspiration, and hence, correlation with plants would be better in case of RDI. Humid region showed a decreasing trend in initial value of RDI during the drought as compared to semiarid and arid regions and indicated possible climate change impact in these regions. Among all the indices, RDI was considered as an effective indicator because of implicit severity and high prediction matches with the actual drought years. SPI and RDI were found to be well correlated with respect to 3 months rainfall data and SPI values led to prediction of annual RDI. The results of our study established that this correlation could be used for developing disaster management plan well in advance to combat the drought consequences.

     

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.     

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.     

Effect of Air Temperature on Historical Trend of Long-Term Droughts in Different Climates of Iran

Effective monitoring of drought plays an important role in water resources planning and management, especially under global warming effect. The aim of this paper is to study the effect of air temperature on historical long-term droughts in regions with diverse climates in Iran. To this end, monthly air temperature (T) and precipitation (P) data were gathered from 15 longest record meteorological stations in Iran covering the period 1951–2014. Long-term meteorological droughts behavior was quantified using two different drought indices, i.e. the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI). Linear and non-linear trends in T, P, SPI and SPEI were evaluated using non-parametric and parametric statistical approaches such as non-modified and modified Mann-Kendall Test, Theil-Sen approach, and simple regression. The results indicated that the significant trends for temperature are approximately all increasing (0.2 °C to 0.5 °C per decade), and for precipitation are mostly decreasing (?7.2 mm to ?14.8 mm per decade). It was also indicated that long-term drought intensities monitored by the SPI and SPEI have had significant downward trend (drought intensification with time) at most stations of interest. The observed trends in the SPI series can be worsen if air temperature (in addition to precipitation) participates in drought monitoring as SPEI. In arid and extra arid climates, it was observed that temperature has strong effects on historical drought characteristics when comparing the SPI and SPEI series. Due to the determinative role of temperature in mostly dry regions like Iran, the study suggests using the SPEI rather than SPI for more effective monitoring of droughts.     

Regional Drought Assessment Based on the Reconnaissance Drought Index (RDI)

Regional drought assessment is conventionally based on drought indices for the identification of drought intensity, duration and areal extent. In this study, a new index, the Reconnaissance Drought Index (RDI) is proposed together with the well known Standardized Precipitation Index (SPI) and the method of deciles. The new index exhibits significant advantages over the other indices by including apart from precipitation, an additional meteorological parameter, the potential evapotranspiration. The drought assessment is achieved using the above indices in two river basins, namely Mornos and Nestos basins in Greece. It is concluded that although the RDI generally responds in a similar fashion to the SPI (and to a lesser extent to the deciles), it is more sensitive and suitable in cases of a changing environment.     

Influence of Precipitation Changes on the SPI and Related Drought Severity. An Analysis Using Long-Term Data Series

Drought indices, such as the Standardized Precipitation Index (SPI) are used to quantify drought severity. Due to the SPI probabilistic and standardized nature, a given value of SPI computed in distinct time periods or locations indicates the same relative drought severity but corresponds to different amounts of precipitation. Thus, the present study aims at contributing for a comprehensive analysis of the influence of long-term precipitation variability on drought assessment by the SPI. Long records of monthly precipitation, spanning from 1863 to 2007 in several locations across Portugal, were divided into 30 years sub-periods and the SPI with 12-month time scale (SPI-12) was computed for each sub-period and for the entire period of records. The probability distributions adjusted to precipitation in those different time periods were compared envisaging to detect the SPI sensitivity to the reference period and, therefore, to changes in precipitation. Precipitation thresholds relative to the upper limits of SPI-12 drought categories were obtained and the influence of the time period was investigated. Results have shown that when SPI values derived from the full data record for a recent time period are lower/higher than the SPI values derived from data of the considered time period a recent downward/upward shift of precipitation has occurred. Coherently, a common pattern of drought aggravation from the initial until the more recent period was not detected. However, in southern locations, lower precipitation thresholds of the SPI drought categories were generally found in the more recent period, particularly for more severe drought categories, whereas in the northern locations Porto and Montalegre, an increase was detected. The impacts of the reference period on the computed SPI drought severity and frequency are shown, bringing to discussion the need for updating ´normal´ conditions when long term precipitation records are available and precipitation changes are observed.     

Development of Drought Indices for Semi-Arid Region Using Drought Indices Calculator (DrinC) – A Case Study from Madurai District,a Semi-Arid Region in India

Drought is considered as a major natural hazard/ disaster, affecting several sectors of the economy and the environment worldwide. Drought, a complex phenomenon can be characterised by its severity, duration, and areal extent. Drought indices for the characterization and the monitoring of drought simplify the complex climatic functions and can quantify climatic anomalies for their severity, duration, and frequency. With this as background drought indices were worked out for Madurai district of Tamil Nadu using DrinC (Drought Indices Calculator) software. DrinC calculates the drought indices viz., deciles, Standard Precipitation Index (SPI), Reconnaissance Drought Index (RDI), Streamflow Drought Index (SDI) by providing a simple, though flexible interface by considering all the factors. The drought of 3, 6 and 9 months as time series can also be estimated. The results showed that drought index of Madurai region by decile method revealed that among the 100 years, 20 years were affected by drought and it is cyclic in nature and occurring almost every 3 to 7 years once repeatedly, except for some continuous period, i.e., 1923, 1924 and 1985, 1986, etc. During the last five decades, the incidence is higher with 13 events, whereas in the first five decades it was only 7. The SPI and RDI index also followed the similar trend of deciles. However, under SPI and RDI, the severely dry and extremely dry category was only seven years and all other drought years of deciles were moderately dry. Our study indicated that SPI is a better indicator than deciles since here severity can be understood. SDI did not follow the trend similar to SPI or RDI. Regression analysis showed that the SPI and RDI are significantly correlated and if 1st 3 months rainfall data is available one can predict yearly RDI drought index. The results demonstrated that these approaches could be useful for developing preparedness plan to combat the consequences of drought. Findings from such studies are useful tools for devising strategic preparedness plans to combat droughts and mitigate their effects on the activities in the various sectors of the economy.     

Drought Monitoring by Reconnaissance Drought Index (RDI) in Iran

Drought is one of the most important natural hazards in Iran and frequently affects a large number of people, causing tremendous economic losses, environmental damages and social hardships. Especially, drought has a strong impact on water resources in Iran. This situation has made more considerations toward the study and management of drought. The present study is focused on two important indices; SPI and RDI, for 3, 6, 9, 12, 18 and 24 months time scales in 40 meteorological synoptic stations in Iran. In the case of RDI computation, potential evapotranspiration was an important factor toward drought monitoring. So, evapotranspiration was calculated by Penman-Monteith equation. The correlation of RDI and SPI was also surveyed. Drought severity maps for SPI and RDI were also presented in the driest year (1999–2000). The present results have shown that the correlation of SPI and RDI was more considerable in the 3, 6 and 9 months than longer time scales. Furthermore, drought severity maps have shown that during 1999–2000, the central, eastern and south-eastern parts of Iran faced extremely dry conditions. While, according to SPI and RDI trends, other parts of the country suffered from severe drought. The SPI and RDI methods showed approximately similar results for the effect of drought on different regions of Iran. Since, RDI resolved more climatic parameters, such as evapotranspiration, into account which had an important role in water resource losses in the Iranian basins, it was worthwhile to consider RDI in drought monitoring in Iran, too.     

Application of a hybrid multiscalar indicator in drought identification in Beijing and Guangzhou,China

The Palmer drought severity index (PDSI) is physically based with multivariate concepts, but requires complicated calibration and cannot easily be used for multiscale comparison. Standardized drought indices (SDIs), such as the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI), are multiscalar and convenient for spatiotemporal comparison, but they are still challenged by their lack of physical basis. In this study, a hybrid multiscalar indicator, the standardized Palmer drought index (SPDI), was used to examine drought properties of two meteorological stations (the Beijing and Guangzhou stations) in China, which have completely different drought climatologies. The results of our case study show that the SPDI is correlated with the well-established drought indices (SPI, SPEI, and PDSI) and presents generally consistent drought/wetness conditions against multiple indicators and literature records. Relative to the PDSI, the SPDI demonstrates invariable statistical characteristics and better comparable drought/wetness frequencies over time and space. Moreover, characteristics of major drought events (drought class, and onset and end times) indicated by the SPDI are generally comparable to those detected by the PDSI. As a physically-based standardized multiscalar drought indicator, the SPDI can be regarded as an effective development of the Palmer drought indices, providing additional choices and tools for practical drought monitoring and assessment.     

标准化降水指数与有效干旱指数在新疆干旱监测中的应用

基于干旱监测理论,根据新疆测站1961—2010年逐日降水资料,对比分析了基于不同时间尺度(1、3、6、9、12、24个月)标准化降水指标(SPI)与有效干旱指数(EDI)对干旱监测的有效性与实用性。结果表明:不论针对短期干旱还是长期干旱,EDI监测能力均明显优于SPI。短时间尺度的SPI受短时间降水影响较大,能反映短时间新疆地区的干旱变化特征;随时间尺度的增加,SPI对短时间降水的响应能力较差,但仍可反映长时间序列下明显的干旱变化趋势。与SPI相比,EDI能够很好地反映出短期干旱和当时降水量的影响;同时能够随时间迁移,给每日降水量分配以不同权重,考虑前期降水量对当前干湿状况的影响。相关研究结果可为湿润区及其他气候区洪旱灾害监测提供重要理论依据。     

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.     

Spatial and Temporal Variability of Precipitation and Dryness/Wetness During 1961–2008 in Sichuan Province,West China

Changes in precipitation exerts a huge impact on human beings and it is of vital importance to study the regular pattern of meteorological and hydrological factors. In order to explore the changing patterns of precipitation in Sichuan province in west China during 1961–2008, several precipitation related indices were analysed by the Mann–Kendall test. For monthly precipitation, significant increasing trends are mainly found during January, March and June, while significant decreasing trends mostly are observed during July, September and October. Most of extreme precipitation indices are decreasing. Especially the annual total precipitation in wet days and maximum number of consecutive wet days show significant negative trends. Furthermore, the spatial and temporal variation of dryness/wetness has been assessed by Standardized Precipitation Index (SPI) and principal component analysis (PCA) on 24-month time scales. The results demonstrated noticeable spatial patterns with several sub-regions characterized by different trends: a remarkable dry tendency prevails in central and east Sichuan, while the other areas are dominated by a wet tendency.     

不同干旱指数在唐山地区旱情评价中的应用

基于唐山地区1957—2011年的气象资料,比较分析标准化降水指数（S SPI）、标准化降水蒸散发指数（S SPEI）和帕默尔水文干旱指数（P PHDI）3种不同干旱指数的相关性,并评价了各个指数在唐山地区连旱期间的适用性。结果表明：各时间尺度（年、季、月）的S SPI和S SPEI均显著相关;P PHDI与年尺度的S SPI和S SPEI均显著相关。P PHDI对长期干旱判断效果明显优于短期干旱。年尺度S SPEI和S SPI对干旱事件识别效果比较接近,二者对长期干旱判断偏涝,对短期干旱判断效果明显优于P PHDI。在气温偏低的年份,季尺度的S SPI能很好地反映旱情的严重程度,在气候变暖的背景下,季尺度S SPEI比S SPI更能准确地判断和评价旱情。     

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.

     

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.     

Drought Severity Assessment Based on Bivariate Probability Analysis

Conventionally drought severity is assessed based on drought indices. Recently the Reconnaissance Drought Index (RDI) was proposed to assess drought severity based on the precipitation to potential evapotranspiration ratio (P/PET). In this paper RDI is studied as a bivariate index under a set of assumptions and simplifications. The paper presents a simple computational procedure for estimating the P/PET ratio for selected reference periods varying from 3 to 12 months, for any return period of drought. Alternatively, based on this procedure, the severity of any drought episode is rationally assessed. A bivariate probability analysis is employed based on the assumption that P and PET values are normally distributed and often negatively correlated. Examples for the application of the proposed procedure are presented using data from several meteorological stations in Greece. It is shown that the assumption of normality of both P and PET holds for long periods at all examined stations.     

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.     

Multivariate Drought Assessment Considering the Antecedent Drought Conditions

Several drought indices have been developed based on a single variable or multiple variables using very complex calculations. Antecedent conditions are quite significant for analyzing physical processes involved in the conceptual rainfall-runoff modeling and for proper assessment of drought. However, not much attention has been paid to these conditions in the development of drought indices. Hence, we developed an alternative index for drought assessment, i.e., the antecedent condition-based multivariate drought index (AMDI), by taking into consideration all of the forms of drought, including meteorological, agricultural, and hydrological drought, in combination with the antecedent drought conditions. By comparing the AMDI with the standardized precipitation index (SPI) and reconnaissance drought index (RDI), it was revealed that in most cases, the drought trend was more or less the same. However, some discrepancies were also observed. Moreover, by considering additional factors, i.e., the antecedent soil moisture conditions and balance, an approximately 6 % difference in the drought frequency was observed compared to that of the SPI and RDI results, leading to a significant and proper drought assessment. The AMDI was also identified as a multi-scalar, multivariate index, which aggregates the effects of multiple drought forms by maintaining the continuity during month-to-month transitions. Hence, we concluded that the AMDI could be considered as an alternative tool for significant drought assessment.     

尼尔基水库上游格点降水数据适用性评估

以尼尔基水库上游流域为研究对象,评估了国家气象信息中心空间分辨率为0. 5°×0. 5°格点的逐日降水产品数据在该流域的适用性。基于格点降水产品提供的逐日降水量资料和该流域17个雨量站的相应资料,应用相关系数R、相对误差RE和均方根误差RMSE 3个指标分别对应用格点降雨产品数据的流域面雨量值及旬径流预报值进行精度分析。结果表明:基于格点数据的面雨量值与实测面雨量间相关系数R为0. 70,相对误差RE为16. 64%,均方根误差RMSE为4. 09 mm,精度满足检验标准,可以用于描述该流域的面雨量值;基于格点面雨量值预报旬径流量时,预报径流值与实测径流值间高度相关;拟合期、检验期径流预报值略微偏大,而外推期存在低估的现象,误差相对较大,但与应用实测面雨量得到的预报径流值误差相差仅3%,该格点降水数据可以替代实测站点的雨量数据用于研究流域。