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.     

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.     

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.     

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.

     

Assessment of Hydrological Drought Revisited

A variety of indices for characterising hydrological drought have been devised which, in general, are data demanding and computationally intensive. On the contrary, for meteorological droughts very simple and effective indices such as the Standardised Precipitation Index (SPI) have been used. A methodology for characterising the severity of hydrological droughts is proposed which uses an index analogous to SPI, the Streamflow Drought Index (SDI). Cumulative streamflow is used for overlapping periods of 3, 6, 9 and 12 months within each hydrological year. Drought states are defined which form a non-stationary Markov chain. Prediction of hydrological drought based on precipitation is also investigated. The methodology is validated using reliable data from the Evinos river basin (Greece). It can be easily applied within a Drought Watch System in river basins with significant storage works and can cope with the lack of streamflow data.     

Drought Risk Assessment and Management

The paper presents an overview of issues related to the estimation of drought severity, the vulnerability of affected systems towards the drought hazards, the assessment of system drought risk and the required preparedness planning against droughts. To face these recurrent and temporary phenomena, a proactive approach is promoted based on technocratic support, systematic organisational and institutional structure and active public participation. Special emphasis is given to the simple and practical approaches, though scientifically sound, for the characterisation of drought episodes and the assessment of drought risk affected systems.     

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)...     

南水北调受水区干旱灾害风险评估方法探讨

南水北调工程的受水区为黄淮海流域,干旱问题已经成为该区域经济和社会发展的瓶颈,因此有必要对受水区内的干旱风险做出准确评估.区域干旱风险可以理解为区域内暴露于干旱下的承灾体,在外部致灾因子扰动下,由于自身的脆弱性,所遭受损失的可能性及可能的损失程度的大小.区域干旱风险评估的任务是明晰发生干旱时暴露于干旱下各个部门和社会生活的各个方面,确定引发干旱的自然致灾因子,分析承灾体的脆弱性,预测干旱造成的影响和损失,并通过数学方法合理量化风险的大小,同时确定造成各部门、地区和人口风险的主要原因,即干旱风险的主要影响因素,从而寻求降低风险的有效途径.现以南水北调某一特定受水区域为研究对象,分析了干旱灾害的成灾机理,对干旱致灾因子的危险性及承灾体的脆弱性进行了讨论,提出相应的计算公式,建立了针对特定区域的干旱灾害风险评估模式,对干旱灾害风险提出了量化的方法.并结合南水北调受水区济南市的实际情况对本文提出的方法进行了应用和验证,实践证明该风险评估模式有一定的科学性和应用价值.     

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.     

Future Hydrological Drought Analysis Considering Agricultural Water Withdrawal Under SSP Scenarios

Hydrological drought is assessed through river flow, which depends on river runoff and water withdrawal. This study proposed a framework to project future hydrological droughts considering agricultural water withdrawal (AWW) for shared socioeconomic pathway (SSP) scenarios. The relationship between AWW and potential evapotranspiration (PET) was determined using a deep belief network (DBN) model and then applied to estimate future AWW using projections of the twelve global climate models (GCMs). 12 GCMs were bias-corrected using the quantile mapping method, climate variables were generated, and river flow was estimated using the soil and water assessment tool (SWAT) model. The standardized runoff index (SRI) was used to project the changes in hydrological drought characteristics. The results revealed a higher occurrence of severe droughts in the future. Droughts would be more frequent in the near future (2021–2060) than in the far future (2061–2100) and more severe when AWW is considered. Droughts would also be more severe for SSP5-8.5 than for SSP2-4.5. The study revealed that the increased PET due to rising temperatures is the primary cause of the increased drought frequency and severity. The AWW will accelerate the drought severities in the future in the Yeongsan River basin.

     

Multivariate Drought Frequency Analysis using Four-Variate Symmetric and Asymmetric Archimedean Copula Functions

In drought frequency analysis, as the number of drought variables increases, the joint behavior between these variables needs to be studied. Therefore, this study aims to develop a flexible four-variate joint distribution function of the regional stochastic nature of drought. Using run theory, drought duration, severity, peak, and inter-arrival time were abstracted from the Standardized Precipitation Evapotranspiration Index (SPEI) aggregated at six months, observed in mainland China between 1961 and 2013. As these drought variables showed significant dependence properties and followed different marginal distributions, we employed and compared six four-variate symmetric and asymmetric Archimedean copulas (i.e., Frank, Clayton, Gumbel–Hougaard). The best-fitting model for each region was carefully selected using RMSE, AIC, and BIAS goodness-of-fit tests. Results revealed that the empirical and theoretical probabilities of the symmetric Clayton in regions NE (Northeast), CS (Central and Southern China), EMC (Entire China), and symmetric Frank in regions NC (North China), SC (South China), IM (Inner Mongolia), NW (Northwest), TP (Tibet Plateau) agreed well. Symmetric Frank copula was considered the best-fit for station-based drought analysis in EMC. Based on these copulas, the drought probabilities and return periods for the occurrence of drought events over the next 5, 10, 20, 50, and 100 years in each region were hereby comprehensively explained, and the results shown here could be helpful in the appraisal of the adequacies of water supply systems under drought conditions in all regions. This study showed that a four-variate copula approach is a vital tool for probabilistic interpretation of hydrological and meteorological data in the different climatic region of mainland China.

     

呼伦湖流域水文干旱评价

以呼伦湖流域2个水文站阿拉坦额莫勒站和坤都冷站1971—2010年的月径流量资料为基础,计算了流域的径流干旱指数,同时运用游程理论对径流干旱指数进行了分析,进而得到呼伦湖流域的干旱历时和干旱烈度。结果表明:呼伦湖流域干旱主要发生在秋季和冬季;随着年代的变化,阿拉坦额莫勒站和坤都冷站平均干旱历时和平均干旱烈度均呈增长状态;进入21世纪以后,呼伦湖流域干旱频发,且持续时间长、干旱烈度大。     

Assessing a Multivariate Approach Based on Scalogram Analysis for Agricultural Drought Monitoring

Due to the complexity of agricultural drought, univariate indices may not be suitable for assessing its impacts comprehensively. The main objective of this study was to develop a new multivariate drought index using the Scalogram concepts, in which the input data weights and their cluster separation were performed based on the entropy theory and fuzzy k-means algorithm, respectively. The newly developed index, named as SCI index, integrates the four weighted individual quantitative indicators such as the difference between precipitation and potential evapotranspiration (D_i), the moisture departure (d_i), the Soil Moisture index (SMI), and the Vegetation Condition Index (VCI) to quantify agricultural drought in monthly and annual timescales in the various climate conditions of Golestan province, Iran. Next, the Composite Drought Index (CDI) was calculated for the selected stations by the same variables in the SCI index as an input. According to the results a good agreement and a high behavioral similarity for the identifying moisture conditions was found between SCI index and CDI index and even other well-known drought indices such as SPEI and SPDI. But the intensity with extremes of wet and dry conditions in the CDI significantly were more than the SCI index and other ones. Comparing results obtained by the Standardized Yield Index (SYI) for rainfed wheat with the SCI index showed that at most stations when a severe drought as happened in 2000–2001 and 2007–2008, severe crops losses also occurred. The flexible structure of SCI index provides a comprehensive approach to quantify agricultural drought and can be adapted to characterize other types of drought on a practical basis.     

考虑IHA指标周期性的水文情势评估方法

结合小波分析方法,考虑IHA指标的周期性变化,建立了一种合理的水文情势评估方法。研究表明:①泾河流域径流量在1986年前后发生显著突变,30个IHA指标的周期发生变化;②考虑周期性变化后,计算得到的河流水文情势改变度增大,9个IHA指标的改变度等级由低度改变转为中度改变,1个IHA指标的改变度由中度改变转为重度改变;③泾河流域水文情势的整体改变度为中度改变,原RVA法和该方法计算的改变度分别为0.363和0.493。     

Assessment of Sustainability in Water Supply-Demand Considering Uncertainties

Water is a vital resource for life on earth; hence its maintenance is very important. Different regions especially in arid and semi-arid areas are facing population growth and subsequent increase in the domestic, industrial and agricultural activities. Planning of water systems in order to be ready for future development conditions needs further studies on the estimation of the sustainable levels of demands based on the sustainable levels of supplies. In this study a threefold approach for estimating sustainability level of supply and demand in Ahachay river basin in northwestern part of Iran as a case study is taken. In the first method, the internal flows and the origins and final uses of the total resources for each subsystem are estimated and planning for sustainability use index is determined by calculating the available water. Second method introduced a simulation model which is utilized to estimate reliability, resiliency, vulnerability and maximum deficit for a river basin to determine a group sustainability index. In the third method, for evaluating the movement toward sustainability, an index is developed. This index includes parameters that are the difference between supply and demand, percentage of the satisfied demand, productivity of water resources and an indicator for evaluating the reduction of aquifer storage. Finally these methods are compared and a hybrid index combining the indices is developed. An uncertainty analysis is also performed to investigate the random nature of variables in estimating water balance and quantifying the water sustainability. This hybrid index can be used for evaluating the planning scenarios and for maintaining and improving the sustainable state of supply-demand for the region.     

A Novel Method for Agricultural Drought Risk Assessment

Climate change, increased temperatures and imbalanced precipitation distributions will potentially increase the local drought risk in certain areas. Drought assessment can identify the hidden dangers of drought and provide a theoretical basis for disaster prevention and mitigation. In this paper, a new agricultural drought risk assessment method proposed from the perspective of grain yield. The first principal components of precipitation, temperature, humidity and soil moisture represent hazard factors. The sensitive yield, which represents the sensitivity, was separated from the grain yield using a regression method. Additionally, the trend component of the grain yield represents the adaptive capacity, and the crop planting area represents exposure. Based on these definitions, the concepts of unit drought risk and regional drought risk are proposed. Four cities in Heilongjiang Province, which has the highest grain yield of any province in China, were used as application examples, and the spatial and temporal variation in the agricultural drought risk were analyzed. Application example show that the method for evaluating agricultural drought presented in this paper is reasonable in a statistical sense. The process for calculating sensitivity and adaptability shows that this method is suitable for arid and semi-arid areas, where grain yield is sensitive to hazard factors, and areas where grain yield has a certain trend.

     

干旱评估和灌溉效益计算方法研究

以徐州市为研究区域,对自然干旱的评估问题进行了研究,包括单指标评估、多指标综合评估,以县为基本计算单元的点干旱评估、由点到整个研究区域的干旱综合评估;同时,对采取灌溉措施后的综合旱情评估问题也进行了研究,并对灌溉效益的评价方法进行了探讨。     

关于农业旱情延时评价指标问题的讨论

论述了三种农业旱情延时评价指标的概念及计算方法,包括:降雨型指标、腾发型指标和产量型指标,通过实例分析,说明了产量型指数是一种科学合理的指标,其他两种指标存在问题,不宜采用.     

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.     

Hydrological Drought Assessment in Northwestern Iran Based on Streamflow Drought Index (SDI)

Drought is a natural and worldwide phenomenon that occurs when water availability is significantly below normal levels during a significant period of time and cannot meet demand. This work focused on the hydrologic drought defined by the streamflow drought index (SDI) for overlapping periods of 3, 6, 9 and 12 months at 14 hydrometric stations in the northwest of Iran over the period 1975–2009. It was found that some of the streamflow volume series did not follow the normal distribution. The ability of the log-normal, exponential and uniform probability distributions was examined in order to choose the most suitable distribution, and the log-normal distribution was used to fit the long-term streamflow data. The results of the hydrological drought analysis based on the SDI showed that almost all the stations suffered from extreme droughts during the study period. Additionally, extreme droughts occurred most frequently in the last 12 years from 1997–1998 to 2008–2009.