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1.
Regional applicability of seven meteorological drought indices in China   总被引：2，自引：0，他引：2  
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.  相似文献   

2.
Abstract

A comparison study is presented of three methods for evaluating trends in drought frequency: the standardized precipitation index (SPI), the Palmer drought severity index (PDSI), and a new method for estimation of dry spells (DS), which is based on average daily temperature and precipitation, and takes into account the length of a spell. The methods were applied to climate data from 450 stations in the Elbe River basin for the period 1951–2003, as well as data from several stations with longer observed time series. Statistical methods were used to calculate trend lines and evaluate the significance of detected trends. The dry spells estimated with the new method show significant trends in the whole lowland part of the Elbe basin during the last 53 years, and at the 10% level almost everywhere in the German part of the basin excluding mountains and the area around the river mouth. The SPI and PDSI methods also revealed significant trends, but for smaller areas in the lowland. The new DS method provides a useful supplement to other drought indices for the detection of trends in drought frequency. Furthermore, the DS method was able to detect statistically significant trends in areas where the other two methods failed to find significant trends, e.g. in the loess region in the southwest of the German part of the basin, where small insignificant changes in climate can lead to significant changes in water fluxes. This is important, because the loess region is the area within the basin having the highest crop yields. Therefore, additional research has to be done to investigate possible impacts of detected trends on water resources availability, and possible future trends in drought frequency under climate change.  相似文献   

3.
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.  相似文献   

4.
The Palmer indices (PIs) that have been most widely used for drought monitoring and assessment are criticized for two main drawbacks: coarse hydrological accounting processes with a simplified two-stage bucket soil water balance model and arbitrary rules for defining drought properties and standardizing index values through limited calibration and comparison. In this study, we introduce a new proposal of the VIC hydrologic model-based Palmer drought scheme, where traditional PIs (e.g. PDSI) can readily be calculated on the basis of distributed finescale hydrologic simulations. Moreover, recent variants of PI (i.e., SPDI and SPDI-JDI) also provide a preferable standardization strategy that allows probabilistic invariability and better spatio-temporal comparability of computed drought indices. Using gridded meteorological forcing, soil and vegetation data to drive the three-layer VIC model, both non-VIC and VIC-based PIs are investigated to examine their performances for drought characterization and detection. Results indicate that VIC hydrologic model would allow for adjustments in statistical properties of computed PDSI and VIC-based SPDI is also preferable to PDSI for better statistical robustness and spatio-temporal consistency/comparability. Moreover, the joint SPDI-JDI has the strength of integrating multi-scale probabilistic properties and drought information released by individual SPDI, providing overall drought conditions that take into account the onset, persistence and termination of droughts. At proposed 0.25° grid scale, the VIC-based SPDI-JDI indicates high frequency and long total time of drought condition in the Yellow River basin (YRB), China. Although no significant temporal trends are found in identified drought duration and severity, both the seasonal and annual drought index values demonstrate a downward trend (higher drought intensity) for considerable proportions of the YRB. These findings imply high drought risk and potential drying stress for this region. The new framework of hydrologic model-based PIs can help to strengthen our knowledge and/or practices in regional drought monitoring and assessment.  相似文献   

5.
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.  相似文献   

6.
By using the Variable Infiltration Capacity model with Palmer Drought Severity Index (VIC‐PDSI) model and Standardized Precipitation Index (SPI), spatiotemporal trends of climate variation during the main growing seasons for plants of Loess Plateau between 1971 and 2010 were detected and characterized. The VIC‐PDSI model is established by combining the VIC model with PDSI. The simulation results and the grids system of VIC were applied to substitute for the two‐layer bucket‐type model to do the hydrological accounting, which could improve the physical mechanism of PDSI and expand its application range. Our results suggest that the climate of the study area has experienced a drying and warming trend during the past four decades. Apart from some individual years and regions, there was a perpetuation of water deficit over the Plateau both in spring and summer. The drought frequency increased from southeast to northwest in spring, while the drought frequency decreased from southeast to northwest in summer. The climate in the southern part of the Loess Plateau, accounting for 23.3% of the study region, showed a significant drying and warming trend in spring over the past four decades. The climate variability detected by VIC‐PDSI model shows good agreement with that monitored by SPI. Since a large part of the study region frequently suffered from water shortage during the main growing seasons for plants, people living in such drought‐prone areas should take measures to prevent the negative effects on agricultural production, reforestation, and regional food security caused by drought. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

7.
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.  相似文献   

8.
Drought is a temporary, random and regional climatic phenomenon, originating due to lack of precipitation leading to water deficit and causing economic loss. Success in drought alleviation depends on how well droughts are defined and their severity quantified. A quantitative definition identifies the beginning, end, spatial extent and the severity of drought. Among the available indices, no single index is capable of fully describing all the physical characteristics of drought. Therefore, in most cases it is useful and necessary to consider several indices, examine their sensitivity and accuracy, and investigate for correlation among them. In this study, the geographical information system‐based Spatial and Time Series Information Modeling (SPATSIM) and Daily Water Resources Assessment Modeling (DWRAM) software were used for drought analysis on monthly and daily bases respectively and its spatial distribution in both dry and wet years. SPATSIM utilizes standardized precipitation index (SPI), effective drought index (EDI), deciles index and departure from long‐term mean and median; and DWRAM employs only EDI. The analysis of data from the Kalahandi and Nuapada districts of Orissa (India) revealed that (a) droughts in this region occurred with a frequency of once in every 3 to 4 years, (b) droughts occurred in the year when the ratio of annual rainfall to potential evapotranspiration (Pae/PET) was less than 0·6, (c) EDI better represented the droughts in the area than any other index; (d) all SPI, EDI and annual deviation from the mean showed a similar trend of drought severity. The comparison of all indices and results of analysis led to several useful and pragmatic inferences in understanding the drought attributes of the study area. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

9.
The creeping characteristics of drought make it possible to mitigate drought’s effects with accurate forecasting models. Drought forecasts are inevitably plagued by uncertainties, making it necessary to derive forecasts in a probabilistic framework. In this study, we proposed a new probabilistic scheme to forecast droughts that used a discrete-time finite state-space hidden Markov model (HMM) aggregated with the Representative Concentration Pathway 8.5 (RCP) precipitation projection (HMM-RCP). The standardized precipitation index (SPI) with a 3-month time scale was employed to represent the drought status over the selected stations in South Korea. The new scheme used a reversible jump Markov chain Monte Carlo algorithm for inference on the model parameters and performed an RCP precipitation projection transformed SPI (RCP-SPI) weight-corrected post-processing for the HMM-based drought forecasting to perform a probabilistic forecast of SPI at the 3-month time scale that considered uncertainties. The point forecasts which were derived as the HMM-RCP forecast mean values, as measured by forecasting skill scores, were much more accurate than those from conventional models and a climatology reference model at various lead times. We also used probabilistic forecast verification and found that the HMM-RCP provided a probabilistic forecast with satisfactory evaluation for different drought categories, even at long lead times. In a drought event analysis, the HMM-RCP accurately predicted about 71.19 % of drought events during the validation period and forecasted the mean duration with an error of less than 1.8 months and a mean severity error of <0.57. The results showed that the HMM-RCP had good potential in probabilistic drought forecasting.  相似文献   

10.
Considering the drawbacks of the original Palmer drought severity index (PDSI) in terms of its simplified hydrologic algorithm and spatio-temporal inconsistency, we compare six variants of PDSI derived from different combinations of two hydrologic algorithms and three standard processes so as to provide deep insights into the individual impacts of hydrological processing and standardization on final PDSI values as well as their combined effects. Investigations are conducted in whole Yellow River basin. On basis of 52 years’ (1961–2012) hydro-meteorological data, comprehensive analysis on multiple drought characteristics are carried out for each PDSI variant, combined with comparison of three crucial intermediate variables of PDSI. Results show that variable infiltration capacity (VIC) model based modification in the hydrologic accounting section significantly improve drought trends with more reasonable spatial distributions presented. For the statistical characteristics of drought areas and frequency, comparable performance is found between VIC-based modification and self-calibrating standard procedure-based modification, though they are derived from different mechanisms. However, in case of the coupling of these two modifications, indices derived from combined modifications perform poorly than single modification-based indices with unexpected high frequency of extreme events detected in certain regions. This reflects the complicated mechanism of PDSI and it is essential to propose an appropriate standardization to match the hydrological algorithm and further improve the performance of relevant drought index. With the crucial findings mentioned above, this study is promising to provide some theoretical supports and serve as a competent reference for future PDSI based researches.  相似文献   

11.
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.  相似文献   

12.
《水文科学杂志》2013,58(6):1114-1124
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.  相似文献   

13.
Local dry/wet conditions and extreme rainfall events are of great concern in regional water resource and disaster risk management. Extensive studies have been carried out to investigate the change of dry/wet conditions and the adaptive responses to extreme rainfall events within the context of climate change. However, applicable tools and their usefulness are still not sufficiently studied, and in Hunan Province, a major grain-producing area in China that has been frequently hit by flood and drought, relevant research is even more limited. This paper investigates the spatiotemporal variation of dry/wet conditions and their annual/seasonal trends in Hunan with the standardized precipitation index (SPI) at various time scales. Furthermore, to verify the potential usefulness of SPI for drought/flood monitoring, the correlation between river discharge and SPI at multiple time scales was examined, and the relation between extreme SPI and the occurrence of historical drought/flood events is explored. The results indicate that the upper reaches of the major rivers in Hunan Province have experienced more dry years than the middle and lower reaches over the past 57 years, and the region shows a trend of becoming drier in the spring and autumn seasons and wetter in the summer and winter seasons. We also found a strong correlation between river discharge and SPI series, with the maximum correlation coefficient occurred at the time scale of 2 months. SPI at different time scales may vary in its usefulness in drought/flood monitoring, and this highlights the need for a comprehensive consideration of various time scales when SPI is employed to monitor droughts and floods.  相似文献   

14.
《水文科学杂志》2012,57(2):254-268
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.  相似文献   

15.
ABSTRACT

In this research, the Bayesian quantile regression model is applied to investigate the teleconnections between large oceanic–atmospheric indices and drought standardized precipitation index (SPI) in Iran. The 12-month SPI time series from 138 synoptic stations for 1952–2014 were selected as the drought index. Three oceanic–atmospheric indices, the North Atlantic Oscillation (NAO), the Southern Oscillation Index (SOI) and the Multivariate El Niño/Southern Oscillation Index (MEI), were selected as covariates. The results show that NAO has the weakest impact on drought in different quantiles and different regions in Iran. La Niña conditions amplified droughts through all SPI quantiles in western, Caspian Sea coastal regions and southern regions. The positive phase of MEI significantly modulates low SPI quantiles (i.e. drought conditions) throughout the Zagros region, Caspian Sea coastal regions and southern regions. The study shows that the effect of large oceanic–atmospheric indices have heterogeneous impacts on extreme dry and wet conditions.  相似文献   

16.
Heilongjiang Province is a major grain production base in China, and its agricultural development plays an important role in China’s social economy. Drought and flood events are the primary disasters in Heilongjiang Province and have considerable impacts on agriculture. In this study, relatively complete monthly precipitation data from 26 meteorological stations in Heilongjiang Province during the period of 1958–2013 were analyzed using the standardized precipitation index (SPI) combined with principal component analysis, Mann–Kendall trend analysis and Morlet wavelet analysis to determine the spatial and temporal distributions of drought and flood events in this province. The results were as follows: (1) the whole of Heilongjiang exhibited an aridity trend. In northern Heilongjiang, spring and summer experienced a wetting trend, and autumn and winter experienced an aridity trend. (2) The SPI3 exhibited 8- and 16-year periodic variation characteristics in spring, 10- and 22-year periodic variation characteristics in summer, and 10- and 32-year periodic variation characteristics in autumn. In addition to the 10-year periodic variation characteristics in winter, other periodic variation characteristics were observed. (3) The increasing trend in the percentage of stations affected by flood was more obvious than that affected by drought. Therefore, Heilongjiang Province is more vulnerable to flooding. (4) The influence of drought and flood disasters in Heilongjiang Province showed a growth trend, but the flood effect was more remarkable. (5) The agricultural area affected by drought and flood disasters in Heilongjiang Province showed an increasing trend. Although there was a greater increase in flood disaster area, the main types of disasters were drought-dominated.  相似文献   

17.
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.  相似文献   

18.
This paper presented trend analysis of droughts in Kerala, Telangana, and Orissa meteorological subdivisions in India and proposed a framework for drought prediction by employing the Empirical Mode Decomposition (EMD)‐based prediction models. The study used 3‐month standardized precipitation index (SPI3) for drought analysis. The trend analysis of SPI3 series for the period 1871–2012 using Mann–Kendall method showed statistically significant increasing trend in Kerala and Telangana subdivisions and a decreasing trend in Orissa subdivision. In addition, the non‐linear trend component extracted from EMD showed statistically significant changes in all the three subdivisions. Then, the study proposed a hybrid approach for prediction of short‐term droughts by coupling multivariate extension of EMD (MEMD) with stepwise linear regression (SLR) and genetic programming (GP) methods. First, the multivariate dataset comprising the SPI3 series of current and lagged time steps are decomposed using the MEMD. Then, SLR/GP models are developed to predict each subseries of SPI3 of desired time step considering the subseries of predictor variables at the corresponding timescales as inputs. The resulting models at different timescales are recombined to obtain the SPI3 values of the desired time step. The method is applied for prediction of short‐term droughts in the three subdivisions. The results obtained by the hybrid models are compared with that obtained by conventional prediction models using M5 Model Trees and GP. The rigorous performance evaluation based on multiple statistical criteria clearly exhibited the superiority of the hybrid approaches (i.e., prediction models with MEMD‐based decomposition over models without decomposition) for prediction of SPI3 in three subdivisions. Further, the study found that MEMD‐GP model performs marginally better than the MEMD‐SLR model due to its efficacy in modelling high frequency modes.  相似文献   

19.
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.  相似文献   

20.
A log-linear modelling for 3-dimensional contingency tables was used with categorical time series of SPI drought class transitions for prediction of monthly drought severity. Standardized Precipitation Index (SPI) time series in 12- and 6-month time scales were computed for 10 precipitation time series relative to GPCC datasets with 2.5° spatial resolution located over Portugal and with 112 years length (1902–2014). The aim was modelling two-month step class transitions for the wet and dry seasons of the year and then obtain probability ratios – Odds – as well as their respective confidence intervals to estimate how probable a transition is compared to another. The prediction results produced by the modelling applied to wet and dry season separately, for the 6- and the 12-month SPI time scale, were compared with the results produced by the same modelling without the split, using skill scores computed for the entire time series length. Results point to good prediction performances ranging from 70 to 80% in the percentage of corrects (PC) and 50–70% in the Heidke skill score (HSS), with the highest scores obtained when the modelling is applied to the SPI12. The adding up of the wet and dry seasons introduced in the modelling brought improvements in the predictions, of about 0.9–4% in the PC and 1.3–6.8% in the HSS, being the highest improvements obtained in the SPI6 application.  相似文献   

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