A new standardized Palmer drought index for hydro‐meteorological use

Accepting the concept of standardization introduced by the standardized precipitation index, similar methodologies have been developed to construct some other standardized drought indices such as the standardized precipitation evapotranspiration index (SPEI). In this study, the authors provided deep insight into the SPEI and recognized potential deficiencies/limitations in relating to the climatic water balance it used. By coupling another well‐known Palmer drought severity index (PDSI), we proposed a new standardized Palmer drought index (SPDI) through a moisture departure probabilistic approach, which allows multi‐scalar calculation for accurate temporal and spatial comparison of the hydro‐meteorological conditions of different locations. Using datasets of monthly precipitation, temperature and soil available water capacity, the moisture deficit/surplus was calculated at multiple temporal scales, and a couple of techniques were adopted to adjust corresponding time series to a generalized extreme value distribution out of several candidates. Results of the historical records (1900–2012) for diverse climates by multiple indices showed that the SPDI was highly consistent and correlated with the SPEI and self‐calibrated PDSI at most analysed time scales. Furthermore, a simple experiment of hypothetical temperature and/or precipitation change scenarios also verified the effectiveness of this newly derived SPDI in response to climate change impacts. Being more robust and preferable in spatial consistency and comparability as well as combining the simplicity of calculation with sufficient accounting of the physical nature of water supply and demand relating to droughts, the SPDI is promising to serve as a competent reference and an alternative for drought assessment and monitoring. Copyright © 2013 John Wiley & Sons, Ltd.     

Impacts of climate variability and change on drought characteristics in the Niger River Basin,West Africa

West Africa has been afflicted by droughts since the declining rains of the 1970s. Therefore, this study examines the characteristics of drought over the Niger River Basin (NRB), investigates the influence of the drought on the river flow, and projects the impacts of future climate change on drought. A combination of observation data and regional climate simulations of past (1986–2005) and future climates (2046–2065 and 2081–2100) were analyzed. The standardized precipitation index (SPI) and standardized precipitation and evapotranspiration index (SPEI) were used to characterize drought while the standardized runoff index (SRI) was used to quantify river flow. Results of the study show that the historical pattern of drought is consistent with previous studies over the Basin and most part of West Africa. RCA4 ensemble gives realistic simulations of the climatology of the Basin in the past climate. Generally, an increase in drought intensity and frequency are projected over NRB. The coupling between SRI and drought indices was very strong (P < 0.05). The dominant peaks can be classified into three distinct drought cycles with periods 1–2, 2–4, 4–8 years. These cycles may be associated with Quasi-Biennial Oscillation (QBO) and El-Nino Southern Oscillation (ENSO). River flow was highly sensitive to precipitation in the NRB and a 1–3 month lead time was found between drought indices and SRI. Under RCP4.5, changes in the SPEI drought frequency range from 1.8 (2046–2065) to 2.4 (2081–2100) month year^?1 while under RCP8.5, the change ranges from 2.2 (2046–2065) to 3.0 month year^?1 (2081–2100). Niger Middle sub-basin is likely to be mostly impacted in the future while the Upper Niger was projected to be least impacted. Results of this study may guide policymakers to evolve strategies to facilitate vulnerability assessment and adaptive capacity of the basin in order to minimize the negative impacts of climate change.     

Meteorological drought analysis using data-driven models for the Lakes District,Turkey

Abstract

Droughts may be classified as meteorological, hydrological or agricultural. When meteorological drought appears in a region, agricultural and hydrological droughts follow. In this study, the standardized precipitation index (SPI) was applied for meteorological drought analysis at nine stations located around the Lakes District, Turkey. Analyses were performed on 3-, 6-, 9- and 12-month-long data sets. The SPI drought classifications were modelled by Adaptive Neural-Based Fuzzy Inference System (ANFIS) and Fuzzy Logic, which has the advantage that, in contrast to most of the time series modelling techniques, it does not require the model structure to be known a priori. Comparison of the observed values and the modelling results shows a better agreement with SPI-12 and ANFIS models than with fuzzy logic models.     

A theoretical drought classification method for the multivariate drought index based on distribution properties of standardized drought indices

Drought indices have been commonly used to characterize different properties of drought and the need to combine multiple drought indices for accurate drought monitoring has been well recognized. Based on linear combinations of multiple drought indices, a variety of multivariate drought indices have recently been developed for comprehensive drought monitoring to integrate drought information from various sources. For operational drought management, it is generally required to determine thresholds of drought severity for drought classification to trigger a mitigation response during a drought event to aid stakeholders and policy makers in decision making. Though the classification of drought categories based on the univariate drought indices has been well studied, drought classification method for the multivariate drought index has been less explored mainly due to the lack of information about its distribution property. In this study, a theoretical drought classification method is proposed for the multivariate drought index, based on a linear combination of multiple indices. Based on the distribution property of the standardized drought index, a theoretical distribution of the linear combined index (LDI) is derived, which can be used for classifying drought with the percentile approach. Application of the proposed method for drought classification of LDI, based on standardized precipitation index (SPI), standardized soil moisture index (SSI), and standardized runoff index (SRI) is illustrated with climate division data from California, United States. Results from comparison with the empirical methods show a satisfactory performance of the proposed method for drought classification.     

Evaluation of multi-sensor satellite data for monitoring different drought impacts

Drought is a natural disaster that significantly affects human life; therefore, precise monitoring and prediction is necessary to minimize drought damage. Conventional drought monitoring is based predominantly on ground observation stations; however, satellite imagery can be used to overcome the disadvantages of existing monitoring methods and has the advantage of monitoring wide areas. In this research, we assess the applicability of drought monitoring based on satellite imagery, focusing on historic droughts in 2001 and 2014, which caused major agricultural and hydrological issues in South Korea. To assess the applicability and accuracy of the drought index, drought impact areas in the study years were investigated, and spatiotemporal comparative analyses between the calculated drought index and previously affected areas were conducted. For drought monitoring based on satellite imagery, we used hydro-meteorological factors such as precipitation, land surface temperature, vegetation, and evapotranspiration, and applied remote sensing data from various sensors. We verified the effectiveness of using precipitation data for meteorological drought monitoring, vegetation and land surface temperature data for agricultural drought monitoring, and evapotranspiration data for hydrological drought monitoring. Moreover, we confirmed that the Standard Precipitation Index (SPI) can be indirectly applied to agricultural or hydrological drought monitoring by determining the temporal correlation between SPI, calculated for various time scales, and satellite-based drought indices.     

Combined analysis of precipitation and water deficit for drought hazard assessment

Abstract

The combined analysis of precipitation and water scarcity was done with the use of the Standardized Precipitation Index (SPI) and the Standardized Runoff Index (SRI), developed as a monthly, two-variable SPI-SRI indicator to identify different classes of hydrometeorological conditions. Stochastic analysis of a long-term time series (1966–2005) of monthly SPI-SRI indicator values was performed using a first-order Markov chain model. This provided characteristics of regional features of drought formation, evolution and persistence, as well as tools for statistical long-term drought hazard prediction. The study was carried out on two subbasins of the Odra River (Poland) of different orography and land use: the mountainous Nysa K?odzka basin and the lowland, agricultural Prosna basin. Classification obtained with the SPI-SRI indicator was compared with the output from the NIZOWKA model that provided identification of hydrological drought events including drought duration and deficit volume. Severe and long-duration droughts corresponded to SPI-SRI Class 3 (dry meteorological and dry hydrological), while severe but short-term droughts (lasting less than 30 days) corresponded to SPI-SRI Class 4 (wet meteorological and dry hydrological). The results confirm that, in Poland, meteorologically dry conditions often shift to hydrologically dry conditions within the same month, droughts rarely last longer than 2 months and two separate drought events can be observed within the same year.     

基于马尔科夫链模型的鄱阳湖流域水文气象干旱研究

基于气象和水文干旱的二维变量干旱状态基础上,通过一阶马尔科夫链模型对二维变量干旱状态进行频率、重现期和历时分析,建立水文气象干旱指数,从干旱灾害形成、演变和持续3方面对干旱灾害进行研究,同时预测未来6个月非水文干旱到水文干旱的概率.结果表明:(1)修河流域在干旱形成中危害大,抚河流域和修河流域在干旱演变中危害大,赣江流域和饶河流域在干旱持续中危害大;(2)鄱阳湖流域状态4(气象、水文干旱)发生的频率最高,为0.30,连续湿润或者干旱的概率最大,湿润状态(状态2)与水文干旱(状态4、状态5(气象湿润、水文干旱))的相互转移概率最低;(3)在长期干旱预测中,鄱阳湖流域从状态2转到状态4和状态5的平均概率为0.11,属最低,而状态1(气象、水文无旱)和状态3(气象干旱、水文湿润)到达状态4的概率为0.23,发生概率最大.修河流域在非水文干旱状态下未来发生气象、水文干旱状态的平均概率为0.28,是"五河"中最高的,而赣江流域在正常或者湿润状态下未来发生气象、水文干旱的概率最低,为0.18,该研究对于鄱阳湖流域水文气象干旱的抗旱减灾具有重要理论与现实意义.     

Multivariate Standardized Drought Index: A parametric multi-index model

Defining droughts based on a single variable/index (e.g., precipitation, soil moisture, or runoff) may not be sufficient for reliable risk assessment and decision-making. In this paper, a multivariate, multi-index drought-modeling approach is proposed using the concept of copulas. The proposed model, named Multivariate Standardized Drought Index (MSDI), probabilistically combines the Standardized Precipitation Index (SPI) and the Standardized Soil Moisture Index (SSI) for drought characterization. In other words, MSDI incorporates the meteorological and agricultural drought conditions for overall characterization of drought. In this study, the proposed MSDI is utilized to characterize the drought conditions over several Climate Divisions in California and North Carolina. The MSDI-based drought analyses are then compared with SPI and SSI. The results reveal that MSDI indicates the drought onset and termination based on the combination of SPI and SSI, with onset being dominated by SPI and drought persistence being more similar to SSI behavior. Overall, the proposed MSDI is shown to be a reasonable model for combining multiple indices probabilistically.     

Drought projection based on a hybrid drought index using Artificial Neural Networks

The Tarim River Basin is a special endorheic arid drainage basin in Central Asia, characterized by limited rainfall and high evaporation as common in deserts, while water is supplied mainly by glacier and snow melt from the surrounding mountains. The existing drought indices can hardly capture the drought features in this region as droughts are caused by two dominant factors (meteorological and hydrological conditions). To overcome the problem, a new hybrid drought index (HDI), integrating the meteorological and hydrological drought regimes, was developed and tested in the basin in the work. The index succeeded in revealing the drought characteristics and the ensemble influence better than the single standardized precipitation index or the hydrological index. The Artificial Neural Network approach based on temperature and precipitation observations was set up to simulate the HDI change. The method enabled constructing scenarios of future droughts in the region using climate simulation of the GCMs under four RCP scenarios from the latest CMIP5 project. The simulations in the study have shown that the water budget patterns in the Tarim River Basin are more sensitive to temperature than to precipitation. Dominated by temperature rise causing an accelerating snow/glacier melt, the frequency of drought months is projected to decrease by about 14% in the next decades (until 2035). The drought duration is expected to be shortened to 3 months on average, with the severity alleviated. However, the region would still suffer more severe droughts with a high intensity in some years. The general decrease in drought frequency and intensity over the region in the future would be beneficial for water resources management and agriculture development in the oases. Copyright © 2014 John Wiley & Sons, Ltd.     

Regional applicability of seven meteorological drought indices in China

The definition of a drought index is the foundation of drought research. However, because of the complexity of drought, there is no a unified drought index appropriate for different drought types and objects at the same time. Therefore, it is crucial to determine the regional applicability of various drought indices. Using terrestrial water storage obtained from the Gravity Recovery And Climate Experiment, and the observed soil moisture and streamflow in China, we evaluated the regional applicability of seven meteorological drought indices: the Palmer Drought Severity Index (PDSI), modified PDSI (PDSI_CN) based on observations in China, self-calibrating PDSI (scPDSI), Surface Wetness Index (SWI), Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), and soil moisture simulations conducted using the community land model driven by observed atmospheric forcing (CLM3.5/ObsFC). The results showed that the scPDSI is most appropriate for China. However, it should be noted that the scPDSI reduces the value range slightly compared with the PDSI and PDSI_CN; thus, the classification of dry and wet conditions should be adjusted accordingly. Some problems might exist when using the PDSI and PDSI_CN in humid and arid areas because of the unsuitability of empiricalparameters. The SPI and SPEI are more appropriate for humid areas than arid and semiarid areas. This is because contributions of temperature variation to drought are neglected in the SPI, but overestimated in the SPEI, when potential evapotranspiration is estimated by the Thornthwaite method in these areas. Consequently, the SPI and SPEI tend to induce wetter and drier results, respectively. The CLM3.5/ObsFC is suitable for China before 2000, but not for arid and semiarid areas after 2000. Consistent with other drought indices, the SWI shows similar interannual and decadal change characteristics in detecting annual dry/wet variations. Although the long-term trends of drought areas in China detected by these seven drought indices during 1961–2013 are consistent, obvious differences exist among the values of drought areas, which might be attributable to the definitions of the drought indices in addition to climatic change.     

Drought hotspot analysis and risk assessment using probabilistic drought monitoring and severity–duration–frequency analysis

Drought hotspot identification requires continuous drought monitoring and spatial risk assessment. The present study analysed drought events in the agriculture‐dominated mid‐Mahanadi River Basin in Odisha, India, using crop water stress as a drought indicator. This drought index incorporated different factors that affect crop water deficit such as the cropping pattern, soil characteristics, and surface soil moisture. The drought monitoring framework utilized a relevance vector machine model‐based classification that provided the uncertainty associated with drought categorization. Using the proposed framework, drought hotspots are identified in the study region and compared with indices based on precipitation and soil moisture. Further, a bivariate copula is employed to model the agricultural drought characteristics and develop the drought severity–duration–frequency (S–D–F) relationships. The drought hotspot maps and S–D–F curves are developed for different locations in the region. These provided useful information on the site‐specific drought patterns and the characteristics of the devastating droughts of 2002 and 2012, characterized by an average drought duration of 7 months at several locations. The site‐specific risk of short‐ and long‐term agricultural droughts are then investigated using the conditional copula. The results suggest that the conditional return periods and the S–D–F curves are valuable tools to assess the spatial variability of drought risk in the region.     

Climate change impacts on meteorological drought using SPI and SPEI: case study of Ankara,Turkey

ABSTRACT

Using regionally downscaled and adjusted outputs of three global climate models (GCMs), meteorological drought analysis was accomplished across Ankara, the capital city of Turkey. To this end, standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI) were projected under (representative concentration pathway) RCP4.5 and RCP8.5 greenhouse gas scenarios. In general, our results show that Ankara experienced six severe and two extreme drought events during the reference period, 1971–2000. However, the projections indicate fewer drought events for the near-future period of 2016–2040, with no potential extreme drought events. While the RCP4.5 scenario showed that dry spells will be dominant in the second half of the near-future period, the RCP8.5 scenario projected that dry spells will be evenly distributed during the entire near-future period.     

Spatio-temporal drought analysis in the Trakya region,Turkey

Abstract

Since droughts are natural phenomena, their occurrence cannot be predicted with certainty and thus it must be treated as a random variable. Once drought duration and magnitude have been found objectively, it is possible to plan for the transport of water in known quantities to drought-stricken areas either from alternative water resources or from water stored during wet periods. The summation of deficits over a particular period is referred to as the drought magnitude. Drought intensity is the ratio of drought magnitude to its duration. These drought properties at different truncation levels provide significant hydrological and hydrometeorological design quantities. In this study, the run analysis and z-score are used for determining drought properties of given hydrological series. In addition, kriging is used as a spatial drought analysis for mapping. This study is applied to precipitation records for Istanbul, Edirne, Tekirdag and Kirklareli in the Trakya region, Turkey and then the drought period, magnitude and standardized precipitation index (SPI) values are presented to depict the relationships between drought duration and magnitude.     

Meteorological drought in the Beijiang River basin,South China: current observations and future projections

It is expected that climate warming will be experienced through increases in the magnitude and frequency of extreme events, including droughts. This paper presents an analysis of observed changes and future projections for meteorological drought for four different time scales (1 month, and 3, 6 and 12 months) in the Beijiang River basin, South China, on the basis of the standardized precipitation evapotranspiration index (SPEI). Observed changes in meteorological drought were analysed at 24 meteorological stations from 1969 to 2011. Future meteorological drought was projected based on the representative concentration pathway (RCP) scenarios RCP4.5 and RCP8.5, as projected by the regional climate model RegCM4.0. The statistical significance of the meteorological drought trends was checked with the Mann–Kendall method. The results show that drought has become more intense and more frequent in most parts of the study region during the past 43 years, mainly owing to a decrease in precipitation. Furthermore, long-term dryness is expected to be more pronounced than short-term dryness. Validation of the model simulation indicates that RegCM4.0 provides a good simulation of the characteristic values of SPEIs. During the twenty first century, significant drying trends are projected for most parts of the study region, especially in the southern part of the basin. Furthermore, the drying trends for RCP8.5 (or for long time scales) are more pronounced than for RCP4.5 (or for short time scales). Compared to the baseline period 1971–2000, the frequency of drought for RCP4.5 (RCP8.5) tends to increase (decrease) in 2021–2050 and decrease (increase) in 2051–2080. The results of this paper will be helpful for efficient water resources management in the Beijiang River basin under climate warming.     

The mirage water concept and an index-based approach to quantify causes of hydrological changes in semi-arid regions

ABSTRACT

In semi-arid regions, reduced river flows present is a major challenge in water resources management. We present a new standardized contribution of rainfall to runoff index (SCRI) for evaluating changes in rainfall contribution to river flow. We employ the standardized precipitation index (SPI), standardized discharge index (SDI) and SCRI to characterize meteorological drought, hydrological drought and land-use change impacts on river flow, respectively. These indices are applied to the Mond River Basin (Iran), which is regulated by the Salman Farsi and Tangab dams since 2006. A new concept called “mirage water” is proposed that represents the reduced water delivery to downstream areas due to new developments and water withdrawals in headwater tributaries. In particular, mirage water accounts for changes in upstream water consumption between the planning phase and construction/operation life of dams. We recommend that this concept be used for communication with decision-makers and managers to clarify the need for revising dimensions of planned dams.     

A framework for quantifying the impacts of climate change and human activities on hydrological drought in a semiarid basin of Northern China

Climate change and human activities are two major driving forces affecting the hydrologic cycle, which further influence the stationarity of the hydrologic regime. Hydrological drought is a substantial negative deviation from the normal hydrologic conditions affected by these two phenomena. In this study, we propose a framework for quantifying the effects of climate change and human activities on hydrological drought. First, trend analysis and change‐point test are performed to determine variations of hydrological variables. After that, the fixed runoff threshold level method (TLM) and the standardized runoff index (SRI) are used to verify whether the traditional assessment methods for hydrological drought are applicable in a changing environment. Finally, two improved drought assessment methods, the variable TLM and the SRI based on parameter transplantation are employed to quantify the impacts of climate change and human activities on hydrological drought based on the reconstructed natural runoff series obtained using the variable infiltration capacity hydrologic model. The results of a case study on the typical semiarid Laohahe basin in North China show that the stationarity of the hydrological processes in the basin is destroyed by human activities (an obvious change‐point for runoff series is identified in 1979). The traditional hydrological drought assessment methods can no longer be applied to the period of 1980–2015. In contrast, the proposed separation framework is able to quantify the contributions of climate change and human activities to hydrological drought during the above period. Their ranges of contributions to hydrological drought calculated by the variable TLM method are 20.6–41.2% and 58.8–79.4%, and the results determined by the SRI based on parameter transplantation method are 15.3–45.3% and 54.7–84.7%, respectively. It is concluded that human activities have a dominant effect on hydrological drought in the study region. The novelty of the study is twofold. First, the proposed method is demonstrated to be efficient in quantifying the effects of climate change and human activities on hydrological drought. Second, the findings of this study can be used for hydrological drought assessment and water resource management in water‐stressed regions under nonstationary conditions.     

Using standardized indicators to analyse dry/wet conditions and their application for monitoring drought/floods: a study in the Logone catchment,Lake Chad basin

The standardized precipitation index (SPI) and standardized streamflow index (SSI) were used to analyse dry/wet conditions in the Logone catchment over a 50-year period (1951–2000). The SPI analysis at different time scales showed several meteorological drought events ranging from moderate to extreme; and SSI analysis showed that wetter conditions prevailed in the catchment from 1950 to 1970 interspersed with a few hydrological drought events. Overall, the results indicate that both the Sudano and Sahelian zones are equally prone to droughts and floods. However, the Sudano zone is more sensitive to drier conditions, while the Sahelian zone is sensitive to wetter conditions. Correlation analysis between SPI and SSI at multiple time scales revealed that the catchment has a low response to rainfall at short time scales, though this progressively changed as the time scale increased, with strong correlations (≥0.70) observed after 12 months. Analysis using individual monthly series showed that the response time reduced to 3 months in October.     

Observed trends and relationships between ENSO and standardized hydrometeorological drought indices in central Chile

Droughts are natural phenomena that severely affect socio economic and ecological systems. In Chile, population and economic activities are highly concentrated in its central region (i.e. between latitudes 29°S and 40°S), which periodically suffers from severe droughts affecting agriculture, hydropower, and mining. Understanding the dynamics of droughts and large-scale atmospheric processes that influence the occurrence of dry spells is essential for forecasting and efficient early detection of drought events. Central Chile's climate is marked by a significant El Niño Southern Oscillation (ENSO) influence that might help to better characterize droughts as well as to identify the effects of ENSO on the spatial and temporal characteristics of meteorological and hydrological droughts in the region. We analysed the behaviour of the Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Streamflow Index (SSI) time series for 6-month accumulation periods over the austral winter and summer seasons. Multiple linear regression (MLR) and Generalized Linear Models (GLM) showed a significant ENSO influence on dry events for SPEI-6 and SSI-6 during winter and summer. We found that the magnitude of correlation between ENSO and SPEI-6 has changed over the last decades becoming weaker in winter periods and increasing in spring summer periods. Increasing trends in meteorological and hydrological drought events were also identified, along all latitudes, with significant trends during winter in the southern latitudes, and during summer in the semi-arid and Mediterranean zones. These results indicate that drought mitigation actions and policies are necessary to overcome their adverse effects. Given the monthly persistence of ENSO and its relationship to drought indices, there are opportunities for drought monitoring and seasonal forecasting that could become part of national drought management systems.     

Effects of the Three Gorges Reservoir on the hydrological droughts at the downstream Yichang station during 2003–2011

Since the Three Gorges Reservoir (TGR) was put into operation in June 2003, the effects of the TGR on downstream hydrology and water resources have become the focus of public attention. This article examines the effects of the TGR on the hydrological droughts at the downstream Yichang hydrological station during 2003–2011. The two‐parameter monthly water balance model was used to generate the monthly discharges at the Yichang station for the period of 2003–2011 to represent the unregulated flow regime and thus to provide a comparison benchmark for the observed flow series at the Yichang station after the operation of the TGR. To provide a reference series for the observed monthly discharge series of the entire study period of 1951–2011, we constructed the naturalized monthly discharge series at the Yichang station by joining the observed monthly discharge at the Yichang station for the period of 1951–2002 and the two‐parameter monthly water balance simulated monthly runoff at the Yichang station for the period of 2003–2011. For both the observed and naturalized monthly discharge series of 1951–2011, the hydrological drought index series were calculated using the standardized streamflow index method. By comparing the drought indices of these two monthly discharge series, we investigated the effects of the TGR on the hydrological droughts at the downstream Yichang station during 2003–2011. The results show that the hydrological droughts at the downstream Yichang station are slightly aggravated by the TGR's initial operation from 2003 to 2011. The river flow reduction at the Yichang station after impoundment of the TGR might account for the downstream drought aggravation. Copyright © 2012 John Wiley & Sons, Ltd.     

Letters to the Editor

Abstract

This work investigates historical trends of meteorological drought in Taiwan by means of long-term precipitation records. Information on local climate change over the last century is also presented. Monthly and daily precipitation data for roughly 100 years, collected by 22 weather stations, were used as the study database. Meteorological droughts of different levels of severity are represented by the standardized precipitation index (SPI) at a three-monthly time scale. Additionally, change-point detection is used to identify meteorological drought trends in the SPI series. Results of the analysis indicate that the incidence of meteorological drought has decreased in northeastern Taiwan since around 1960, and increased in central and southern Taiwan. Long-term daily precipitation series show an increasing trend for dry days all over Taiwan. Finally, frequency analysis was performed to obtain further information on trends of return periods of drought characteristics.