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.     

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.     

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.

     

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.     

Toward Mapping Gridded Drought Indices to Evaluate Local Drought in a Rapidly Changing Global Environment

Uncertain future climate, recent persistent droughts, and subsequent water conflicts increasingly threaten the sustainability of regional water resources in the United States. Climate change and ongoing water disputes brought about by changes in water availability and timing emphasize the need for decision makers to develop proactive adaptive management strategies to mitigate losses. Developing a drought management system equipped with advanced visualization settings is critical to lay out drought evolvement at local scales, yet an effort has not been made to evaluate how different spatial discretization can represent local drought as opposed to conventional drought monitoring. Gridded drought indices, including the standardized precipitation index (SPI), Palmer drought severity index (PDSI), and Hydrologic drought index (HDI) at high-resolution spatial (12 km by 12 km) scales are demonstrated to provide useful insights to evaluate local drought possibly driven by a rapidly changing global environment. A new method for duration factors in PDSI is also discussed to better represent drought conditions over time and space.     

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.     

A Global Hydrological Drought Index Dataset Based on Gravity Recovery and Climate Experiment (GRACE) Data

The Gravity Recovery and Climate Experiment (GRACE) satellites have been used in drought/flood monitoring by observing terrestrial water storage (TWS) change. Meteorological drought indicators or other identified disaster information were usually adopted in association with GRACE-observed changes in TWS for the determination of the occurrence and severity of droughts/floods. Inter-comparisons of dry conditions based on TWS change on a global scale, however, were very difficult because TWS anomalies are not comparable for different hydro-climatic regions. In this paper, we established a global dataset of GRACE-based dimensionless drought index, the Total Storage Deficit Index (TSDI), which is spatially comparable and capable of independently examining the characteristics of dry/wet spells globally. The globally mapped GRACE-based TSDI was examined with some reported extreme hydrologic events, which suggested that the results were fairly consistent with documented drought/flood disaster information. Moreover, comparisons of the GRACE-based TSDI with other frequently used drought indicators, such as the Standardized Precipitation Index (SPI), the Palmer Drought Severity Index (PDSI), and the Palmer Hydrological Drought Index (PHDI), suggested that the TSDI was significantly correlated with the SPI at three different time scales, the PDSI, and the PHDI over most parts of the global surface. The longer the time scale of the selected SPI, the stronger the correlation tended to be with the TSDI. Moreover, the correlation of the TSDI with the PHDI was higher than that with the PDSI over almost the whole global surface. With regard to its performance, this study suggested that the TSDI derived from GRACE-based TWS could be a useful dimensionless index for global and regional hydrological drought monitoring, especially for areas where meteo-hydrological observations are insufficient or human activities are intensive.     

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...     

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.     

Comparison of Meteorological,Hydrological and Agricultural Drought Responses to Climate Change and Uncertainty Assessment

A comparison study of meteorological, hydrological and agricultural drought responses to climate change resulting from different General Circulation Models (GCMs), emission scenarios and hydrological models is presented. Drought variations from 1961–2000 to 2061–2100 in Huai River basin above Bengbu station in China are investigated. Meteorological drought is recognized by the Standardized Precipitation Index (SPI) while hydrological drought and agricultural drought are indexed with a similar standardized procedure by the Standardized Runoff Index (SRI) and Standardized Soil Water Index (SSWI). The results generally approve that hydrological and agricultural drought could still pose greater threats to local water resources management in the future, even with a more steady background to meteorological drought. However, the various drought responses to climate change indicate that uncertainty arises in the propagation of drought from meteorological to hydrological and agricultural systems with respect to alternative climates. The uncertainty in hydrological model structure, as well as the uncertainties in GCM and emission scenario, are aggregated to the results and lead to much wider variations in hydrological and agricultural drought characteristics. Our results also reveal that the selection of hydrological models can induce fundamental differences in drought simulations, and the role of hydrological model uncertainty may become dominating among the three uncertainty sources while recognizing frequency of extreme drought and maximum drought duration.     

Analysing Drought Severity and Areal Extent by 2D Archimedean Copulas

Droughts can be considered as multidimensional hazardous phenomena characterised by three attributes: severity, duration and areal extent. Conventionally, drought events are assessed for their severity, using drought indices such as SPI (Standardised Precipitation Index), RDI (Reconnaissance Drought Index), PDSI (Palmer Drought Severity Index) and many others. This approach may be extended to incorporate the modelling of an additional dimension, the duration or the areal extent. Since the marginal distributions describing these dimensions of drought are often different, no simple mixed probability distribution can be used for the bivariate frequency analysis. The copula approach seems to be sufficiently general and suitable for this type of analysis. It is the aim of this paper to analyse droughts as two-dimensional phenomena, including drought severity and areal extent. In this paper, the Gumbel-Hougaard copula from the Archimedean family is used for this two-dimensional frequency analysis. Annual data on historical droughts from Eastern Crete are analysed for their severity and areal extent, producing copula-based probability distributions, incorporating Gumbel marginal probability functions. Useful conclusions are derived for estimating the «OR» return period of drought events related to both severity and areal extent.     

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.     

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.     

Fifty Years of Precipitation: Some Spatially Remote Teleconnnections

In the present paper the authors analyse the drought occurrence over the European region by using the NCEP/NCAR reanalysis precipitation rates covering the period from 1948 to 2000. The drought assessment is based on the Standardized Precipitation Index (SPI), which has been proposed as an indicator of drought condition. At variance with other fields derived from precipitation, the SPI is, by construction, a Gaussian field. Thus, the understanding of its covariance structure exhausts the study of the associated density distribution. A method allowing a factorisation of a multivariate Gaussian distribution is the one known as Principal Component Analysis (PCA) or Kauman-Loeve decomposition. Therefore, a PCA is used to study the main spatial patterns and the time variability of drought first over Europe and then over the Northern Hemisphere. The analysis reveals a downward trend for the index over most of central Europe and the Mediterraneanbasin, implying an overall decrease of precipitation in the above mentioned regions. Moreover, the scores associated with the PCA covariance decomposition, besides the aforementioned trend, show few long-term periodicities.Similar drought analyses have been performed by considering the Palmer Drought Severity Index (PDSI).A preliminary comparison between the SPI and PDSI obtained by using the previously discussed data set is presented. It is shown that the indices compare favourably in assessing drought variability. Finally, when the SPI analysis is extended to the Northern Hemisphere some interesting spatially remote teleconnnections linking the Tropical Pacific with the European area are shown.     

Frequency and Spatial Characteristics of Droughts in the Conchos River Basin,Mexico

Abstract

The temporal and spatial characteristics of droughts are investigated to provide a framework for sustainable water resources management in a semi-arid region. Using the Palmer Drought Severity Index (PDSI) as an indicator of drought severity, the characteristics of droughts are examined in the Conchos River Basin in Mexico. This basin is important to both the United States and Mexico, because the Conchos River supplies approximately 80 percent of the flows of the Lower Bravo/Grande River above the binational reservoirs of Amistad and Falcon. The temporal and spatial characteristics of the PDSI are used to develop a drought intensity—areal extent—frequency curve that can assess the severity of a regional drought in the basin. The analysis of the PDSI suggests that the Conchos River Basin had a severe drought in the 1990s, which the basin has not experienced before. Based on this analysis, the recent drought that occurred in the 1990s has an associated return period of about 80 to 100 years over the basin.     

Analysis of Impacts of Climate Change and Human Activities on Hydrological Drought: a Case Study in the Wei River Basin,China

Climate change and human activity are the two major drivers that can alter hydrological cycle processes and influence the characteristics of hydrological drought in river basins. The present study selects the Wei River Basin (WRB) as a case study region in which to assess the impacts of climate change and human activity on hydrological drought based on the Standardized Runoff Index (SRI) on different time scales. The Generalized Additive Models in Location, Scale and Shape (GAMLSS) are used to construct a time-dependent SRI (SRI_var) considering the non-stationarity of runoff series under changing environmental conditions. The results indicate that the SRI_var is more robust and reliable than the traditional SRI. We also determine that different driving factors can influence the hydrological drought evolution on different time scales. On shorter time scales, the effects of human activity on hydrological drought are stronger than those of climate change; on longer time scales, climate change is considered to be the dominant factor. The results presented in this study are beneficial for providing a reference for hydrological drought analysis by considering non-stationarity as well as investigating how hydrological drought responds to climate change and human activity on various time scales, thereby providing scientific information for drought forecasting and water resources management over different time scales under non-stationary conditions.     

A New Non-stationary Hydrological Drought Index Encompassing Climate Indices and Modified Reservoir Index as Covariates

Due to accelerating climate variability and intensified anthropogenic activities, the hypothesis of stationarity of data series is no longer applicable, questioning the reliability of the traditional drought index. Thus, it is critical to develop a non-stationary hydrological drought index that takes into account the joint impacts of climate and anthropogenic changes in a drought assessment framework. In this study, using the Generalized Additive Model for Location, Scale and Shape (GAMLSS), a new Non-stationary Standardized Runoff Index (NSRI) was developed combining climate indices (CI) and modified reservoir index (MRI) as explanatory variables. This novel index was applied to the hydrological drought assessment of the Hanjiang River basin (HRB) in China, and its reliability was assessed by comparing with the traditional Standardized Runoff Index (SRI). Results indicated that the optimal non-stationary model with CI and MRI as covariates performed better than did other models. Furthermore, NSRI was more robust in identifying extreme drought events and was more effective in the study region than the conventional SRI. In addition, based on the method of Breaks for Additive Seasonal and Trend (BFAST), it was found that there were two change points in 1981 and 2003 for the NSRI series at four hydrological stations in the HRB, which indicated that hydrological drought in the basin had a prominent non-stationary behavior. Our findings may provide significant information for regional drought assessment and water resources management from a changing environment perspective.

     

Drought forecasting using the Standardized Precipitation Index

Unlike other natural disasters, drought events evolve slowly in time and their impacts generally span a long period of time. Such features do make possible a more effective drought mitigation of the most adverse effects, provided a timely monitoring of an incoming drought is available. Among the several proposed drought monitoring indices, the Standardized Precipitation Index (SPI) has found widespread application for describing and comparing droughts among different time periods and regions with different climatic conditions. However, limited efforts have been made to analyze the role of the SPI for drought forecasting. The aim of the paper is to provide two methodologies for the seasonal forecasting of SPI, under the hypothesis of uncorrelated and normally distributed monthly precipitation aggregated at various time scales k. In the first methodology, the auto-covariance matrix of SPI values is analytically derived, as a function of the statistics of the underlying monthly precipitation process, in order to compute the transition probabilities from a current drought condition to another in the future. The proposed analytical approach appears particularly valuable from a practical stand point in light of the difficulties of applying a frequency approach due to the limited number of transitions generally observed even on relatively long SPI records. Also, an analysis of the applicability of a Markov chain model has revealed the inadequacy of such an approach, since it leads to significant errors in the transition probability as shown in the paper. In the second methodology, SPI forecasts at a generic time horizon M are analytically determined, in terms of conditional expectation, as a function of past values of monthly precipitation. Forecasting accuracy is estimated through an expression of the Mean Square Error, which allows one to derive confidence intervals of prediction. Validation of the derived expressions is carried out by comparing theoretical forecasts and observed SPI values by means of a moving window technique. Results seem to confirm the reliability of the proposed methodologies, which therefore can find useful application within a drought monitoring system.     

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.     

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.