共查询到20条相似文献，搜索用时 140 毫秒
1.
Multi-scale analysis of meteorological drought risks based on a Bayesian interpolation approach in Huai River basin,China 总被引：4，自引：4，他引：0
Kai Duan Weihua Xiao Yadong Mei Dedi Liu 《Stochastic Environmental Research and Risk Assessment (SERRA)》2014,28(8):1985-1998
A scheme for meteorological drought analysis at various temporal and spatial scales based on a spatial Bayesian interpolation of drought severity derived from Standardized Precipitation Index (SPI) values at observed stations is presented and applied to the Huai River basin of China in this paper, using monthly precipitation record from 1961 to 2006 in 30 meteorological stations across the basin. After dividing the study area into regular grids, drought condition in gauged sites are classified into extreme, severe, moderate and non drought according to SPIs at month, seasonal and annual time scales respectively while that in ungauged grids are explained as risks of various drought severities instead of single state by a Bayesian interpolation. Subsequently, temporal and spatial patterns of drought risks are investigated statistically. Main conclusions of the research are as follows: (1) drought at seasonal scale was more threatening than the other two time scales with a larger number of observed drought events and more notable variation; (2) results of the Mann–Kendall test revealed an upward trend of drought risk in April and September; (3) there were larger risks of extreme and severe drought in southern and northwestern parts of the basin while the northeastern areas tended to face larger risks of moderate drought. The case study in Huai River basin suggests that the proposed approach is a viable and flexible tool for monitoring meteorological drought at multiple scales with a more specific insight into drought characteristics at each severity level. 相似文献
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
3.
The spatial–temporal variation of dry and wet periods in Iran based on comparing SPI and RDI indices
Drought is a natural hazard which can cause harmful effects on water resources. To monitor drought, the use of an indicator and determination of wet and dry period trend seem to have an important role in quantifying the drought analysis. In this paper, in addition to the comparison of Reconnaissance Drought Index (RDI) and Standardized Precipitation Index (SPI), based on the most appropriate probability distribution function, it was tried to examine the trends of dry and wet periods based on the mentioned indices. Accordingly, the meteorological data of 30 synoptic stations in Iran (1960–2014) was used and the trend was analyzed using the Mann–Kendall test by eliminating the effect of any significant autocorrelation coefficients at 95% confidence level (modified Mann–Kendall). Comparing results between the time series of RDI and SPI drought indices based on statistical indicators (RMSE?<?0.434, R2?>?0.819 and T-statistic?<?0.419) in all studied stations revealed that the behavior of the two indices was roughly the same and the difference between them was not significant. The trend analysis results of RDI and SPI indices based on modified Mann–Kendall test showed that the variation of dry and wet periods was decreasing in most of the studied stations (five cases were significant). In addition, the results of the trend line slope of dry and wet periods related to the drought indices in the studied area indicated that the slope was negative for SPI and RDI indices in 70% and 50% of stations, respectively. 相似文献
4.
AbstractThe 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. 相似文献
5.
Adaptive Neuro-Fuzzy Inference System for drought forecasting 总被引：3，自引：2，他引：1
Ulker Guner Bacanli Mahmut Firat Fatih Dikbas 《Stochastic Environmental Research and Risk Assessment (SERRA)》2009,23(8):1143-1154
Drought causes huge losses in agriculture and has many negative influences on natural ecosystems. In this study, the applicability
of Adaptive Neuro-Fuzzy Inference System (ANFIS) for drought forecasting and quantitative value of drought indices, the Standardized
Precipitation Index (SPI), is investigated. For this aim, 10 rainfall gauging stations located in Central Anatolia, Turkey
are selected as study area. Monthly mean rainfall and SPI values are used for constructing the ANFIS forecasting models. For
all stations, data sets include a total of 516 data records measured between in 1964 and 2006 years and data sets are divided
into two subsets, training and testing. Different ANFIS forecasting models for SPI at time scales 1–12 months were trained
and tested. The results of ANFIS forecasting models and observed values are compared and performances of models were evaluated.
Moreover, the best fit models have been also trained and tested by Feed Forward Neural Networks (FFNN). The results demonstrate
that ANFIS can be successfully applied and provide high accuracy and reliability for drought forecasting. 相似文献
6.
Elsa E. Moreira João T. Mexia Luís S. Pereira 《Stochastic Environmental Research and Risk Assessment (SERRA)》2013,27(1):183-193
In the present study, an ANOVA-like inference technique is used aiming at to assess if Alentejo, southern Portugal, could be considered a homogeneous region for drought management purposes. First, Alentejo was divided into four sub-regions according to latitude (north and south), and longitude (west and east). Inside each sub-region, 10 weather stations were considered. The time series of the Standardized Precipitation Index (SPI) were obtained for these stations using precipitation data for the period 1932–1999 (67 years). Contingency tables for the transitions between SPI drought classes were obtained for these time series. Loglinear models were fitted to these contingency tables to estimate the probabilities for drought class transitions. An ANOVA-like inference was applied considering the four sub-regions like treatments of a two way layout with two factors, latitude and longitude, each one with two levels, north and south, and west and east respectively. The weather stations of each sub-region were treated as replicates. Significant differences between west and east were found, that allowed to consider that Alentejo could be composed by two sub-regions. 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.
Water Resources - The regional peculiarities of annual atmospheric moistening in European Russia are investigated using Standardized Precipitation and Evapotranspiration Index (SPEI). It was found... 相似文献
9.
中国东部诸流域的干旱和湿润期:模式和预测 总被引：1，自引：0，他引：1
降水观测记录是近50a来中国九大流域干旱和湿润期时空变化分析的基础.以两年为时间尺度引入标准降水指数(SPI)来分析评价气候变化情景,结果表明黄河流域、长江流域和淮河(或珠江)流域等三个主要的区域表现为低频率变化指数:另外分析显示北方地区自20世纪70年代以来干旱更频繁的出现,在SPI时间序列中呈现负趋势变化.这也许与表征SPI信号的长周期有关(24a和48a周期).与这些长周期一起,也有一些其它方面的因素有助于频谱变化,范围从3a到9a不等.在指数时间序列中这些周期成分的存在为长期预测干旱和湿润期提供了很好的条件. 相似文献
10.
The survey of climatic drought trend in Iran 总被引：5，自引：3，他引：2
Hossein Bari Abarghouei Mohammad Amin Asadi Zarch Mohammad Taghi Dastorani Mohammad Reza Kousari Mehdi Safari Zarch 《Stochastic Environmental Research and Risk Assessment (SERRA)》2011,25(6):851-863
Drought is one of the most important natural hazards in Iran. Therefore, drought monitoring has become a point of concern
for most of the researchers. In the present study, the changes and trend of drought was surveyed, under the current global
climate changes, by non parametric Mann–Kendall statistical test for 42 synoptic stations at different places of Iran. Standardized
Precipitation Index (SPI) was calculated to recognize the drought condition at different time scales (3, 6, 9, 12, 18 and
24 months’ time series) for analyzing the drought trend in the recent 30 years. The obtained results have indicated a significant
negative trend of drought in many parts of Iran, especially the South-East, West and South-West regions of the country. According
to the results, although some parts of Iran such as North (around the Caspian Sea) and Northeast show no significant trend
but in other parts of country, the severity of drought has increased during the last 30 years. 相似文献
11.
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
12.
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. 相似文献
13.
Drought modeling is essential to water resources management and planning. In this study, Fourier spectral analysis is used to examine the cyclic structure for drought patterns and develop a long-term periodic model. A case study for historical precipitation data, obtained from the arid region of Kuwait for the period spanning from January 1967 to December 2009, are converted to drought measurements following the Standardized Precipitation Index (SPI) criterion. The SPI calculations are performed for two time scales of 12 and 24 months. The periodogram technique used for both time scales reveals periodicities of 12, 14, 19, 26, 31, 43, 64, 103 and 258 months. It is advocated here that the 26- and 258-month periods present in the data are attributed, respectively, to a Quasi-Biennial Oscillation pattern and a solar cycle over which the magnetic polarity of the sun first reverses then reverts to its former state. The detected periods are manipulated in the SPI model to produce drought forecasts, which suggest that until the end of year 2024 the climate is considered normal to very wet. This finding may be implemented to assess policy requirements related to water resources management. 相似文献
14.
Temporal trends and spatial characteristics of drought and rainfall in arid and semiarid regions of Iran 总被引：5，自引：0，他引：5
Drought, a normal recurrent event in arid and semiarid lands such as Iran, is typically of a temporary nature usually leaving little permanent aftermath. In the current study, the rainfall and drought severity time series were analyzed at 10 stations in the eastern half of Iran for the period 1966–2005. The drought severity was computed using the Standardized Precipitation Index (SPI) for a 12‐month timescale. The trend analyses of the data were also performed using the Kendall and Spearman tests. The results of this study showed that the rainfall and drought severity data had high variations to average values in the study period, and these variations increased with increasing aridity towards the south of the study area. The negative serial correlations found in the seasonal and annual rainfall time series were mostly insignificant. The trend tests detected a significant decreasing trend in the spring rainfall series of Birjand station at the rate of 8.56 mm per season per decade and a significant increasing trend in the summer rainfall series of Torbateheydarieh station at the rate of 0.14 mm per season per decade, whereas the rest of the trends were insignificant. Furthermore, the 12‐month values of the standardized precipitation index decreased at all the stations except Zabol during the past four decades. During the study period, all of the stations experienced at least one extreme drought which mainly occurred in the winter season. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
15.
The present study focuses on the analysis of dryness/wetness conditions in the Danube River catchment area from 1901 to 2013 based on reanalysis data. The spatio‐temporal variability of dryness/wetness conditions is analyzed by means of the Standardized Precipitation Index (SPI) for an accumulation periods of 6 months. To characterize the spatial variability of SPI6 at monthly time scales, an empirical orthogonal function (EOF) analysis was applied. The leading mode of SPI variability captures in‐phase variability of SPI over the entire catchment area of Danube River. The leading mode of dryness/wetness variability was found to be strongly related to the different phases of the Arctic Oscillation. The second and third modes of variability show a more regional character of the dryness/wetness variability over the Danube River catchment area. Based on a composite map analysis, between the time series corresponding to the first three leading modes of dryness/wetness variability and the geopotential height at 850 mb and precipitation totals, it is shown that dryness (wetness) conditions over the Danube catchment area are associated with an anticyclonic (cyclonic) circulation, transport of dry (humid) air towards the Danube catchment area and reduced (enhanced) number of rain days. Copyright © 2015 John Wiley & Sons, Ltd. 相似文献
16.
Application of linear stochastic models for drought forecasting in the Büyük Menderes river basin, western Turkey 总被引：6，自引：3，他引：3
Ömer Faruk Durdu 《Stochastic Environmental Research and Risk Assessment (SERRA)》2010,24(8):1145-1162
In the present study, a seasonal and non-seasonal prediction of the Standardized Precipitation Index (SPI) time series is
addressed by means of linear stochastic models. The methodology presented here is to develop adequate linear stochastic models
known as autoregressive integrated moving average (ARIMA) and multiplicative seasonal autoregressive integrated moving average
(SARIMA) to predict drought in the Büyük Menderes river basin using SPI as drought index. Temporal characteristics of droughts
based on SPI as an indicator of drought severity indicate that the basin is affected by severe and more or less prolonged
periods of drought from 1975 to 2006. Therefore, drought prediction plays an important role for water resources management.
ARIMA modeling approach involves the following three steps: model identification, parameter estimation, diagnostic checking.
In model identification step, considering the autocorrelation function (ACF) and partial autocorrelation function (PACF) results
of the SPI series, different ARIMA models are identified. The model gives the minimum Akaike Information Criterion (AIC) and
Schwarz Bayesian Criterion (SBC) is selected as the best fit model. Parameter estimation step indicates that the estimated
model parameters are significantly different from zero. Diagnostic check step is applied to the residuals of the selected
ARIMA models and the results indicated that the residuals are independent, normally distributed and homoscedastic. For the
model validation purposes, the predicted results using the best ARIMA models are compared to the observed data. The predicted
data show reasonably good agreement with the actual data. The ARIMA models developed to predict drought found to give acceptable
results up to 2 months ahead. The stochastic models developed for the Büyük Menderes river basin can be employed to predict
droughts up to 2 months of lead time with reasonably accuracy. 相似文献
17.
Mou Leong Tan Liew Juneng Fredolin T. Tangang Ngai Weng Chan Sheau Tieh Ngai 《水文科学杂志》2019,64(8):921-933
Water scarcity issues in the Johor River Basin (JRB) could affect the populations of Malaysia and Singapore. This study provides an overview of future hydro-meteorological droughts using climate projections from an ensemble of four Coordinated Regional Climate Downscaling Experiments – Southeast Asia (CORDEX-SEA) domain outputs under the Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios for the 2021–2050 and 2071–2100 periods. The climate projections were bias corrected using the quantile mapping approach before being incorporated into the Soil and Water Assessment Tool (SWAT) hydrological model. The Standardized Precipitation Index (SPI) and Standardized Streamflow Index (SSI) were used to examine the meteorological and hydrological droughts, respectively. Overall, future annual precipitation, streamflow, and maximum and minimum temperatures are projected to change by about ?44.2 to 24.3%, ?88.7 to 42.2%, 0.8 to 3.7ºC and 0.7 to 4.7ºC, respectively. The results show that the JRB is likely to receive more frequent meteorological droughts in the future. 相似文献
18.
A drought index is one of the main methods used for measuring drought and represents the basis of drought monitoring, early warning, and classification. On the basis of an analysis of the advantages and limitations of the Standardized Precipitation Evapotranspiration Index (SPEI), the Standardized Precipitation Crop Evapotranspiration Index (SPCEI), which is a drought index of rainfed agriculture, was constructed in this study. The applicable conditions of the SPCEI were then investigated, and the results showed that the SPCEI was suitable for dryland crops under non‐irrigated conditions in arid and semi‐arid areas. The difference between the SPEI and SPCEI is analysed. Compared with the SPEI, the SPCEI considers crop evapotranspiration and the crop growth stage and was found to be more suitable for monitoring agricultural drought. Qigihar, which is located in a semi‐arid area in western Heilongjiang Province, China, was then analysed as an example. The characteristics of the spatial and temporal variability of regional agricultural drought were analysed based on maize and soybean in dryland areas. The results for the different growth stages of maize and soybean showed that drought intensity is more serious in the initial stage in the middle part. In crop development, mid‐season and late season stage, the drought conditions gradually increased from north to south. The drought degree of the two crops at the initial stage gradually increased, and the drought degree at the crop development stage gradually decreased. The main reason is that precipitation gradually increases during the crop development stage. 相似文献
19.
Meteorological drought in the Beijiang River basin,South China: current observations and future projections 总被引：1，自引：1，他引：0
Chuanhao Wu Zhuoyan Xian Guoru Huang 《Stochastic Environmental Research and Risk Assessment (SERRA)》2016,30(7):1821-1834
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. 相似文献
20.
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