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.     

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.     

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.     

Comparing SPI and RDI Applied at Local Scale as Influenced by Climate

Drought and wetness events were studied in the Northeast Algeria with SPI and RDI. The study area includes a variety of climatic conditions, ranging from humid in the North, close to the Mediterranean Sea, to arid in the South, near the Sahara Desert. SPI only uses precipitation data while RDI uses a ratio between precipitation and potential evapotranspiration (PET). The latter was computed with the Thornthwaite equation, thus using temperature data only. Monthly precipitation data were obtained from 123 rainfall stations and monthly temperature data were obtained from CFSR reanalysis gridded temperature data. Both data sets cover the period 1979–80 to 2013–14. Using ordinary kriging, the gridded temperature data was interpolated to all the locations having precipitation data, thus providing to compute SPI and RDI with the same observed rainfall data for the 3-, 6- and 12-month time scales. SPI and RDI were therefore compared at station level and results and have shown that both indices revealed more sensitive to drought when applied in the semi-arid and arid zones. Differently, more wetness events were detected by RDI in the more humid locations. Comparing both indices, they show a coherent and similar behavior, however RDI shows smaller differences among climate zones and time-scales, which is an advantage relative to the SPI and is likely due to including PET in RDI.     

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.     

A Non-Stationary Reconnaissance Drought Index (NRDI) for Drought Monitoring in a Changing Climate

Traditionally, drought indices are calculated under stationary condition, the assumption that is not true in a changing environment. Under non-stationary conditions, it is assumed the probability distribution parameters vary linearly/non-linearly with time or other covariates. In this study, using the GAMLSS algorithm, a time-varying location parameter of lognormal distribution fitted to the initial values (α₀) of the traditional Reconnaissance Drought Index (RDI) was developed to establish a new index called the Non-Stationary RDI (NRDI), simplifying drought monitoring under non-stationarity. The fifteen meteorological stations having the longest records (1951–2014) in Iran were chose to evaluate the NRDI performances for drought monitoring. Trend analysis of the α₀ series at multiple time windows was tested by using the Mann-Kendall statistics. Although all stations detected decreasing trend in the α₀ series, eight of them were significant at the 5% probability level. The results showed that the time-dependent relationship is adequate to model the location parameter at the stations with the significant temporal trend. There were remarkable differences between the NRDI and the RDI, especially for the time windows larger than 6 months, implying monitoring droughts using the NRDI under non-stationarity. The study suggests using the NRDI where the significant time trend appears in the initial values of RDI due to changing climate.     

Analysis of Changes in Spatial Pattern of Drought Using RDI Index in south of Iran

Drought is one of the main natural hazards affecting the economy and the environment of large areas. Droughts cause crop losses, urban water supply shortages, social alarm, degradation and desertification. In this study, the spatial characteristics of annual and seasonal drought were evaluated based on climate data from 16 synoptic stations during the period of 1980–2010 in south of Iran. To estimate the drought severity used modified Reconnaissance Drought Index (RDI) and to prepare maps, ArcGis10.2 software was used. Results showed in annual drought, percent of areas with normal condition, severe dry and extreme dry condition have had significant increasing trend (0.95 level). In winter drought, the percentage of areas with severe dry and extreme dry condition have had significant increasing trend (0.95 level). In spring drought, percent of areas with moderate dry has had significant increasing trend (0.95 level), in summer drought, percent of areas with moderate dry has had increasing trend (insignificant) and in autumn drought, percent of areas with severe dry has had significant increasing trend (0.95 level). Other classes of drought in different time scales had not significant trend. Result showed that the percentage of area with dry condition is increasing, this can be effective on the agricultural activities, agricultural productions, water resource management and other activities.     

Impacts of Multi-year Droughts and Upstream Human-Induced Activities on the Development of a Semi-arid Transboundary Basin

This paper aims at investigating the combined impacts of basin-wide multi-year droughts and upstream human-induced activities on current and future potential development of a semi-arid transboundary basin. The approach is based on the drought analysis through three widely used drought indices (Standardised Drought Index- SPI, Reconnaissance Drought Index - RDI and Streamflow Drought Index- SDI), coupled with the current and future conceivable man-made changes upstream, taking also into account the effects of climate change. As a representative case, the Diyala river basin, shared between Iraq and Iran, is selected. A close examination of the climate trends in the study area exhibits that the basin points to be drier, with a decreasein precipitation and rise in the rates of temperature and potential evapotranspiration. The comparison between RDI and SDI indicates the cumulative drought effects on runoff during recent multi-year droughts episodes (1999–2001 and 2008–2009), which crippled the socio-economic activities and influenced the environmental system. Further, the results reveal that the combined impacts of multi-year droughts at basin scale and the river damming, water abstraction and water diversion works upstream have significant effects on water availability, especially at the middle and lower parts of the basin, with impacts on the security of the irrigated agriculture and public water supply, contributing to displacement and tribal conflicts. The projected climate change conditions along with the water withdrawal schemes upstream, which will put into operation in the foreseeable future, are expected to increase the vulnerability of water security in the portion of the basin that lies in the downstream country.     

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.

     

Evaluation of Drought Condition in Arid and Semi- Arid Regions,Using RDI Index

Investigation of drought event has a great importance in the natural resources management and planning water resources management. One strategy to manage drought is to predict drought conditions by probabilistic tools. In this study climate data of 11 synoptic stations in south of Iran during 1980–2014 were used to estimate of seasonal drought based on RDI index. To prediction of drought (from 2015 to 2020) and analysis of changes trend of it, time series model, first-order Markov Chain model and parametric and non- parametric statistical methods were used. Results showed that MA (5), MA (10), AR (12) and AR (15) were the best time series models that fitted in data of all stations. According to results of prediction of drought classes, classes with normal and moderate dry condition had allocated the most frequency of seasonal drought classes from 2015 to 2020 based on time series model and Markov Chain method. Analysis of changes trend of drought classes showed that based on observed data (1980–2014) and predicted data (1980–2020) changes trend of drought classes in all stations had increasing trend based on parametric and non- parametric statistical methods but increasing trend in about 27% of stations include: Bandar Abbas, Bandar Lengeh, Jask and Shiraz had significant level of 5%. Finally result showed that the study area in 2020 compared to 2014 will be drier.     

Past and Future Global Drought Assessment

Water Resources Management - Understanding the climate change impacts on drought occurrence is of great importance for comprehensive water resources management. Reconnaissance drought index (RDI)...     

Geoinformatic Intelligence Methodologies for Drought Spatiotemporal Variability in Greece

One of the most important hazards in terms of cost, frequency of occurrence and impact on humans is drought. Drought indices are estimations of precipitation shortage and water supply deficit. Satellite drought indices are normally radiometric recordings of vegetation condition and dynamics, exploiting the unique spectral signatures of canopy elements, particularly in the red and near-infrared bands. However, the identification of drought based on the Reconnaissance Drought Index (RDI) enables the assessment of hydro-meteorological drought, since it uses hydro-meteorological parameters. RDI is a fairly comprehensive index as it combines the simplicity of use and the successfully assessment and monitoring of the phenomenon. However, the study and understanding of the spatiotemporal variability of drought is not an easy process. In this study the main goal is to use the PCA + clustering method to transform the RDI temporal data (1982–2001) and cluster the different regions of Greece based on that temporal variations. Firstly, Principal Component Analysis (PCA) applied onto 19 annual RDI indices followed by Clustering that was based on certain eigenchannels resulted from the previous PCA analysis. Both methods are linear transformations capable to decorrelate the spatiotemporal information provided in the estimated RDI. The time series presented approach proved to be advantageous in relation to other statistical methods used to describe variability and provide excellent and fast results for stakeholders and environmental organizations. The results are quite satisfactory in classifying the drought-induced climatic regions of Greece.     

Assessment of Trend in Global Drought Propensity in the Twenty-First Century Using Drought Management Index

This study attempts to perform a global analysis of the trend in drought propensity in the twenty-first century using bias corrected soil moisture simulations from two General Circulation Model (GCMs) outputs based on the Representative Concentration Pathway-8.5 (RCP8.5) scenario. Drought propensity is characterized in terms of the probabilistic index – Drought Management Index (DMI), which is suitable for the assessment of slowly varying changes in soil moisture drought on a multi-year time scale. A global gridded analysis is performed to assess the future trend in drought propensity at each location on the globe over the twenty-first century. Regional analysis is also carried out to investigate the trends, if any, at the continental scale. A significant increasing trend in drought propensity is observed in large parts of Africa, South America and Asia, whereas a significant decreasing trend is observed in the northern parts of Europe and North America. This study helps to assess the spatio-temporal propagation of global drought propensity in future and aids in identifying the regions that would be relatively more/less prone to droughts towards the end of the century.     

Drought variability and its connection with large-scale atmospheric circulations in Haihe River Basin

Drought is one of the most widespread and devastating extreme climate events when water availability is significantly below normal levels for a long period. In recent years, the Haihe River Basin has been threatened by intensified droughts. Therefore, characterization of droughts in the basin is of great importance for sustainable water resources management. In this study, two multi-scalar drought indices, the standardized precipitation evapotranspiration index(SPEI) with potential evapotranspiration calculated by the Penmane Monteith equation and the standardized precipitation index(SPI), were used to evaluate the spatiotemporal variations of drought characteristics from 1961 to 2017 in the Haihe River Basin. In addition, the large-scale atmospheric circulation patterns were used to further explore the potential links between drought trends and climatic anomalies. An increasing tendency in drought duration was detected over the Haihe River Basin with frequent drought events occurring in the period from 1997 to 2003. The results derived from both SPEI and SPI demonstrated that summer droughts were significantly intensified. The analysis of large-scale atmospheric circulation patterns indicated that the intensified summer droughts could be attributed to the positive geopotential height anomalies in Asian mid-high latitudes and the insufficient water vapor fluxes transported from the south.     

基于双源蒸散与混合产流的Palmer 旱度模式构建及应用

选取半干旱地区老哈河流域为研究对象,基于双源蒸散发能力计算模型和混合产流模块,依据palmer旱度模式的思路,构建适用于我国北方半干旱地区的机理性旱度模式。利用该模式计算15个代表站点1957—2008年的旱度值,并与实际旱情记载以及降水距平百分率进行了对照检验。结果表明,该旱度模式计算的各地区的Palmer干旱指标与文献描述的干湿情况较为一致,能够反映所研究区域干旱程度的变化情况;与降水距平百分率相比,该模式综合考虑了水分亏缺量和持续时间因子对干旱强度的影响,可以反映流域下垫面特性及植被生理物候特性对干旱的影响机制,能够更好地表现干旱过程的持续性。此外,该模式还能合理给出旱情在空间上的发生和发展的变化情况。     

防患严重干旱引发危机建设南水北调西线工程

西北地区深处内陆，属干旱、半干旱气候。由于人类活动的不断增强，已出现严重的缺水局面，据预测未来缺水形势更趋严峻。历史上重大旱灾事件表明，防患严重干旱引发水资源危机于未然，及早实施南水北调西线工程，以抗御可能出现的重大旱灾。     

Development and Testing of Drought Indicators

Numerous definitions of droughts which are based on different climatological time series have been in use. In this paper, the development of drought indicators by using different time series is described. These drought indicators were developed for use by the Department of Natural Resources in the State of Indiana, U.S.A. The second part of the study deals with an analysis of the consistency of results obtained by using different time series, in order to select two or three of the commonly available series for drought analysis. Past drought data are used to test the performance of the drought indicators. As a result of this study, three month precipitation, monthly river flow and the Palmer Hydrologic Drought Index series are recommended for operational use.     

贵州省旱灾成因及其减灾对策

贵州省地处高原山区，各种自然灾害频繁，旱灾是主要的灾害之一。旱灾受灾范围广、发生频次高，已成为制约社会经济发展的重要因素。本文在充分分析旱灾成因、水资源开发利用及其存在问题的基础上，提出推广雨洪水利用、加快水利工程除险加固及灌溉配套工程建设、大力发展提水工程、加强水资源的统一管理、重视抗旱预案编制工作和推行水资源危机管理制度等减轻旱灾的一些对策。     

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.