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1.
This study presents copula‐based multivariate probabilistic approach to model severity–duration–frequency (S‐D‐F) relationship of drought events in western Rajasthan, India. Drought occurrences are analysed using standardized precipitation index computed on monthly mean areal precipitation, aggregated at a time scale of 6 months. After testing with a series of probability density functions, the drought variable severity is found to be better represented with log‐normal distribution, whereas duration is well fitted with exponential distribution. Four different classes of bivariate copulas – Archimedean, extreme value, Plackett, and elliptical families are evaluated for modelling joint distribution of drought characteristics. It is observed that the extreme value copula – Gumbel–Hougaard copula – performed better as compared with other classes of copulas, based on results of various statistical tests and upper tail dependence coefficient. The joint distribution obtained from best performing copula is then employed to determine conditional return period and to derive drought severity‐duration‐frequency (S‐D‐F) curves for the study region. The results of the study suggests that the copula method can be used effectively to derive the drought S‐D‐F curves, which can be helpful in planning and adopting suitable drought mitigation strategies in drought‐prone areas. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
2.
M. Janga Reddy Vijay P. Singh 《Stochastic Environmental Research and Risk Assessment (SERRA)》2014,28(3):475-489
This study investigated the utility of two meta-heuristic algorithms to estimate parameters of copula models and for derivation of drought severity–duration–frequency (S–D–F) curves. Drought is a natural event, which has huge impact on both the society and the natural environment. Drought events are mainly characterized by their severity, duration and intensity. The study adopts standardized precipitation index for drought characterization, and copula method for multivariate risk analysis of droughts. For accurate estimation of copula model parameters, two meta-heuristic methods namely genetic algorithm and particle swarm optimization are applied. The proposed methodology is applied to a case study in Trans Pecos, an arid region in Texas, USA. First, drought severity and duration are separately modeled by various probability distribution functions and then the best fitted models are selected for copula modeling. For modeling the joint dependence of drought variables, different classes of copulas, namely, extreme value copulas, Plackett and Student’s t copulas are employed and their performance is evaluated using standard performance measures. It is found that for the study region, the Gumbel–Hougaard copula is the best fitted copula model as compared to the others and is used for the development of drought S–D–F curves. Results of the study suggest that the meta-heuristic methods have greater utility in copula-based multivariate risk assessment of droughts. 相似文献
3.
M. Janga Reddy Poulomi Ganguli 《Stochastic Environmental Research and Risk Assessment (SERRA)》2013,27(8):1975-1989
This study presents spatio-temporal analysis of droughts in one of the most drought prone region in India–western Rajasthan and develops drought intensity-area-frequency curves for the region. The meteorological drought conditions are analyzed using 6-month standardized precipitation index (SPI-6) estimated at spatial resolution of 0.5° × 0.5°. Spatio-temporal analysis of SPI-6 indicates increase in frequency of droughts at the central part of the region. The non-parametric Mann–Kendall test for seasonal trend analysis showed increase in number of grids under drought during the study period. Further, bivariate frequency analysis of drought characteristics—intensity and areal extent is carried out using copula methods. For modeling joint dependence between drought variables, three copula families namely Gumbel-Hougaard, Frank and Plackett copulas are evaluated. Based on goodness-of-fit as well as upper tail dependence tests, it is found that the Gumbel-Hougaard copula best represents the drought properties. The copula-based joint distribution is used to compute conditional return periods and drought intensity–area–frequency (I–A–F) curves. The I–A–F curves could be helpful in risk evaluation of droughts in the region. 相似文献
4.
In this study, the climate teleconnections with meteorological droughts are analysed and used to develop ensemble drought prediction models using a support vector machine (SVM)–copula approach over Western Rajasthan (India). The meteorological droughts are identified using the Standardized Precipitation Index (SPI). In the analysis of large‐scale climate forcing represented by climate indices such as El Niño Southern Oscillation, Indian Ocean Dipole Mode and Atlantic Multidecadal Oscillation on regional droughts, it is found that regional droughts exhibits interannual as well as interdecadal variability. On the basis of potential teleconnections between regional droughts and climate indices, SPI‐based drought forecasting models are developed with up to 3 months' lead time. As traditional statistical forecast models are unable to capture nonlinearity and nonstationarity associated with drought forecasts, a machine learning technique, namely, support vector regression (SVR), is adopted to forecast the drought index, and the copula method is used to model the joint distribution of observed and predicted drought index. The copula‐based conditional distribution of an observed drought index conditioned on predicted drought index is utilized to simulate ensembles of drought forecasts. Two variants of drought forecast models are developed, namely a single model for all the periods in a year and separate models for each of the four seasons in a year. The performance of developed models is validated for predicting drought time series for 10 years' data. Improvement in ensemble prediction of drought indices is observed for combined seasonal model over the single model without seasonal partitions. The results show that the proposed SVM–copula approach improves the drought prediction capability and provides estimation of uncertainty associated with drought predictions. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
5.
Droughts are one of the normal and recurrent climatic phenomena on Earth. However, recurring prolonged droughts have caused far‐reaching and diverse impacts because of water deficits. This study aims to investigate the hydrological droughts of the Yellow River in northern China. Since drought duration and drought severity exhibit significant correlation, a bivariate distribution is used to model the drought duration and severity jointly. However, drought duration and drought severity are often modelled by different distributions; the commonly used bivariate distributions cannot be applied. In this study, a copula is employed to construct the bivariate drought distribution. The copula is a function that links the univariate marginal distributions to form the bivariate distribution. The bivariate return periods are also established to explore the drought characteristics of the historically noticeable droughts. The results show that the return period of the drought that occurred in late 1920s to early 1930s is 105 years. The significant 1997 dry‐up phenomenon that occurred in the downstream Yellow River (resulting from the 1997–1998 drought) only has a return period of 4·4 years and is probably induced by two successive droughts and deteriorated by other factors, such as human activities. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
6.
In this study, the patterns of past and future drought occurrences in the Seoul region were analysed using observed historical data from the Seoul weather station located in the Korean Peninsula and four different types of general circulation models (GCMs), namely, GFDL:CM2_1, CONS:ECHO‐G, MRI:CGCM2_3_2 and UKMO:HADGEM1. To analyse statistical properties such as drought frequency duration and return period, the Standardized Precipitation Index was used to derive the severity–duration–frequency (SDF) curve from the drought frequency analysis. In addition, a drought spell analysis was conducted to estimate the frequency and change of drought duration for each drought classification. The results of the analysis suggested a decrease in the frequency of mild droughts and an increase in the frequency of severe and extreme droughts in the future. Furthermore, the average duration of droughts is expected to increase. A comparison of the SDF relationship derived from the observed data with that derived via the GCMs indicated that the drought severity for each return period was reduced as drought duration increased and that the drought severity derived from the GCMs was severer than the severity obtained using the observed data for the same duration and return period. Furthermore, among the four types of GCMs used in this study, the MRI model predicted the most severe future drought for the Seoul region, and the SDF curve derived using the MRI model also resulted in the highest degree of drought severity compared with the other GCMs. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
7.
Xinjun Tu Xiaohong Chen Mingwei Ma Qiang Zhang Yong Zhao 《Stochastic Environmental Research and Risk Assessment (SERRA)》2016,30(5):1317-1334
There are two kinds of uncertainty factors in modeling the bivariate distribution of hydrological droughts: the alteration of predefined critical ratios for pooling droughts and excluding minor droughts and the temporal variability of univariate and/or bivariate characteristics of droughts due to the impact of human activities. Daily flow data covering a period of 56 hydrological years from two gauging stations from a humid region in South China are used. The influences of alterations of threshold values of flow and critical ratios of pooling droughts and excluding minor droughts on drought properties are analyzed. Six conventional univariate models and three Archimedean copulas are employed to fit the marginal and joint distributions of drought properties, the Kolmogorov–Smirnov and Anderson–Darling methods are used for testing the goodness-of-fit of the univariate model, and the Cramer-von Mises method based on Rosenblatt’s transform is applied for the test of the bivariate model. The change point analysis of the copula parameter of bivariate distribution of droughts is first made. Results demonstrate that both the statistical characteristics of each drought property and their bivariate joint distributions are sensitive to the critical ratio of excluding minor droughts. A model can be selected to fit the marginal distribution for drought deficit volume or maximum deficit, but it is not determined for drought duration with the lower ratios of the pooling and excluding droughts. The statistical uncertainty of drought duration makes the modeling of bivariate joint distribution of drought duration and deficit volume or of drought duration and maximum deficit undermined. Change points significantly occurred in the period from the late 1970s to the middle 1980s for a single drought property and the copula parameter of their joint distribution due to the impact of human activities. The difference between two subseries separated by the change point is remarkable in the magnitudes of drought properties and the joint return periods. A copula function can be selected to optimally fit the bivariate distribution, provided that the critical ratios of pooling and excluding droughts are great enough such as the optimal value of 0.4 in the case study. It is valuable that the modeling and designing of the bivariate joint correlation and distribution of drought properties can be performed on the subseries separated by the change point of the copula parameter. 相似文献
8.
In recent decades, copula functions have been applied in bivariate drought duration and severity frequency analysis. Among several potential copulas, Clayton has been mostly used in drought analysis. In this research, we studied the influence of the tail shape of various copula functions (i.e. Gumbel, Frank, Clayton and Gaussian) on drought bivariate frequency analysis. The appropriateness of Clayton copula for the characterization of drought characteristics is also investigated. Drought data are extracted from standardized precipitation index time series for four stations in Canada (La Tuque and Grande Prairie) and Iran (Anzali and Zahedan). Both duration and severity data sets are positively skewed. Different marginal distributions were first fitted to drought duration and severity data. The gamma and exponential distributions were selected for drought duration and severity, respectively, according to the positive skewness and Kolmogorov–Smirnov test. The results of copula modelling show that the Clayton copula function is not an appropriate choice for the used data sets in the current study and does not give more drought risk information than an independent model for which the duration and severity dependence is not significant. The reason is that the dependence of two variables in the upper tail of Clayton copula is very weak and similar to the independent case, whereas the observed data in the transformed domain of cumulative density function show high association in the upper tail. Instead, the Frank and Gumbel copula functions show better performance than Clayton function for drought bivariate frequency analysis. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
9.
Hydrological drought analysis is very important in the design of hydrotechnical projects and water resources management and planning. In this study, a methodology is proposed for the analysis of streamflow droughts using the threshold level approach. The method has been applied to Yermasoyia semiarid basin in Cyprus based on 30‐year daily discharge data. Severity was defined as the accumulated water deficit volume occurring during a drought event, in respect with a target threshold. Fixed and variable thresholds (seasonal, monthly, and daily) were employed to derive the drought characteristics. The threshold levels were determined based on the Q50 percentiles of flow extracted from the corresponding flow duration curves for each threshold. The aim is to investigate the sensitivity of these thresholds in the estimation of maximum drought severities for various return periods and the derivation of severity–duration–frequency curves. The block maxima and the peaks over threshold approaches were used to perform the extreme value analysis. Three pooling procedures (moving average, interevent time criterion, and interevent time and volume criterion) were employed to remove the dependent and minor droughts. The application showed that the interevent time and volume criterion is the most unbiased pooling method. Therefore, it was selected to estimate the drought characteristics. The results of this study indicate that monthly and daily variable thresholds are able to capture abnormal drought events that occur during the whole hydrological year whereas the other two, only the severe ones. They are also more sensitive in the estimation of maximum drought severities and the derivation of the curves because they incorporate better the effect of drought durations. 相似文献
10.
Multivariate drought characteristics using trivariate Gaussian and Student t copulas 总被引：4，自引：0，他引：4
This study aims to investigate the changing properties of drought events in Weihe River basin, China, by modeling the multivariate joint distribution of drought duration, severity and peak using trivariate Gaussian and Student t copulas. Monthly precipitations of Xi'an gauge are used to illustrate the meta‐elliptical copula‐based methodology for a single‐station application. Gaussian and Student t copulas are found to produce a better fit comparing with other six symmetrical and asymmetrical Archimedean copulas, and, checked by the goodness‐of‐fit tests based on a modified bootstrap version of Rosenblatt's transformation, both of them are acceptable to model the multivariate joint distribution of drought variables. Gaussian copula, the best fitting, is employed to construct the dependence structures of positively associated drought variables so as to obtain the multivariate joint and conditional probabilities of droughts. A Kendall's return period (KRP) introduced by Salvadori and De Michele (2010) is then adopted to assess the multivariate recurrent properties of drought events, and its spatial distributions indicate that prolonged droughts are likely to break out with rather short recurrence intervals in the whole region, while drought status in the southeast seems to be severer than the northwest. The study is of some merits in terms of multivariate drought modeling using a preferable copula‐based method, the results of which could serve as a reference for regional drought defense and water resources management. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
11.
In recent years, the bivariate frequency analysis of drought duration and severity using independent drought events and copula functions has been under extensive application. Meanwhile, emphasis on the procedure of independent drought data collection leads to the omission of the actual potential of short-term extreme droughts within a long-term independent drought. However, a long-term individual continuous drought as an Unconnected Drought Runs can be considered as a combination of short-term Connected Drought Runs. Thus, an advanced and new procedure of data collection in the bivariate drought characteristics analysis has been developed in this study. The results indicated a high relative advantage of the new proposed procedure in analysing bivariate drought characteristics (i.e., drought duration and severity frequency analysis). This advantage has been reflected in the more appropriate determination of the best copula and significant reduction in the uncertainty of bivariate drought frequency analysis. 相似文献
12.
Exploring spatiotemporal relationships among meteorological,agricultural, and hydrological droughts in Southwest China 总被引：3，自引：1，他引：2
Zhiyong Wu Yun Mao Xiaoyan Li Guihua Lu Qingxia Lin Huating Xu 《Stochastic Environmental Research and Risk Assessment (SERRA)》2016,30(3):1033-1044
Each type of drought has different characteristics in different regions. It is important to distinguish different types of droughts and their correlations. Based on gauged precipitation, temperature, simulated soil moisture, and runoff data during the period 1951–2012, the relationships among meteorological, agricultural, and hydrological droughts were analyzed at different time scales in Southwest China. The standardized precipitation evapotranspiration index (SPEI), soil moisture anomaly percentage index (SMAPI), and standardized runoff index (SRI) were used to describe meteorological, agricultural, and hydrological droughts, respectively. The results show that there was a good correlation among the three indices. SMAPI had the best correlation with the 3 month SPEI and SRI values. It indicates that agricultural drought was characterized by a 3-month scale. The three drought indices displayed the similar special features such as drought scope, drought level, and drought center during the extreme drought of 2009–2010. However, the scope and level of SPEI were bigger than those of SMAPI and SRI. The propagation characteristics of the three types of droughts were significantly different. The temporal drought process in typical grids reflect that the meteorological drought occurred ahead of agricultural and hydrological droughts by about 1 and 3 months, respectively. Agricultural drought showed a stable drought process and reasonable time periods for the drought beginning and end. These results showed the quantitative relationships among three types of drought and thus provided an important supporting evidence for regional drought monitoring and strategic decisions. 相似文献
13.
Revisiting hydrological drought propagation and recovery considering water quantity and quality 总被引：2，自引：0，他引：2
Climate extremes, in particular droughts, are significant driving forces towards riverine ecosystem disturbance. Drought impacts on stream ecosystems include losses that can be either direct (e.g., destruction of habitat for aquatic species) or indirect (e.g., deterioration of water quality, soil quality, and increased chance of wildfires). This paper combines hydrologic drought and water quality changes during droughts and represents a multistage framework to detect and characterize hydrological droughts while considering water quality parameters. This method is applied to 52 streamflow stations in the state of California, USA, over the study period of 1950–2010. The framework is assessed and validated based on two drought events declared by the state in 2002 and 2008. Results show that there are two opposite drought propagation patterns in northern and southern California. In general, northern California indicates more frequent droughts with shorter time to recover. Chronology of drought shows that stations located in southern California have not followed a specific pattern but they experienced longer drought episodes with prolonged drought recovery. When considering water quality, results show that droughts either deteriorate or enhance water systems, depending on the parameter of interest. Undesirable changes (e.g., increased temperature and decreased dissolved oxygen) are observed during droughts. In contrast, decreased turbidity is detected in rivers during drought episodes, which is desirable in water systems. Nevertheless, water quality deteriorates during drought recovery, even after drought termination. Depending on climatic and streamflow characteristics of the watersheds, it was found that it would take nearly 2 months on average for water quality to recover after drought termination. 相似文献
14.
Evaluation of water‐use policies for baseflow recovery during droughts in an agricultural intensive karst watershed: Case study of the lower Apalachicola–Chattahoochee–Flint River Basin,southeastern United States 
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下载免费PDF全文 The lower Apalachicola–Chattahoochee–Flint River Basin in the Southeast United States represents a major agricultural area underlain by the highly productive karstic Upper Floridan aquifer (UFA). During El Niño Southern Oscillation‐induced droughts, intense groundwater withdrawal for irrigation lowers streamflow in the Flint River due to its hydraulic connectivity with the UFA and threatens the habitat of the federally listed and endangered aquatic biota. This study assessed the compounding hydrologic effects of increased irrigation pumping during drought years (2010–2012) on stream–aquifer water exchange (stream–aquifer flux) between the Flint River and UFA using the United States Geological Survey modular finite element groundwater flow model. Principal component and K‐means clustering analyses were used to identify critical stream reaches and tributaries that are adversely affected by irrigation pumping. Additionally, the effectiveness of possible water restriction scenarios on stream–aquifer flux was also analysed. Moreover, a cost–benefit analysis of acreage buyout procedure was conducted for various water restriction scenarios. Results indicate that increased groundwater withdrawal in Water Year 2011 decreased baseflow in the lower Apalachicola–Chattahoochee–Flint River Basin, particularly, in Spring Creek, where irrigation pumping during April, June, and July changed the creek condition from a gaining to losing stream. Results from sensitivity analysis and simulated water restrictions suggest that reducing pumping in selected sensitive areas is more effective in streamflow recovery (approximately 78%) than is reducing irrigation intensity by a prescribed percentage of current pumping rates, such as 15% or 30%, throughout the basin. Moreover, analysis of acreage buyout indicates that restrictions on irrigation withdrawal can have significant impacts on stream–aquifer flux in the Basin, especially in critical watersheds such as Spring and Ichawaynochaway Creeks. The proposed procedure for ranking of stream reaches (sensitivity analysis) in this study can be replicated in other study areas/models. This study provides useful information to policymakers for devising alternate irrigation water withdrawal policies during droughts for maintaining flow levels in the study area. 相似文献
15.
Drought may affect all components of the water cycle and covers commonly a large part of the catchment area. This paper examines drought propagation at the catchment scale using spatially aggregated drought characteristics and illustrates the importance of catchment processes in modifying the drought signal in both time and space. Analysis is conducted using monthly time series covering the period 1961–1997 for the Pang catchment, UK. The time series include observed rainfall and groundwater recharge, head and discharge simulated by physically-based soil water and groundwater models. Drought events derived separately for each unit area and variable are combined to yield catchment scale drought characteristics. The study reveals relatively large differences in the spatial and temporal characteristics of drought for the different variables. Meteorological droughts cover frequently the whole catchment; and they are more numerous and last for a short time (1–2 months). In comparison, droughts in recharge and hydraulic head cover typically a smaller area and last longer (4–5 months). Hydraulic head and groundwater discharge exhibit similar drought characteristics, which can be expected in a groundwater fed catchment. Deficit volume is considered a robust measure of the severity of a drought event over the catchment area for all variables; whereas, duration is less sensitive, particular for rainfall. Spatial variability in drought characteristics for groundwater recharge, head and discharge are primarily controlled by catchment properties. It is recommended not to use drought area separately as a measure of drought severity at the catchment scale, rather it should be used in combination with other drought characteristics like duration and deficit volume. 相似文献
16.
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
17.
In semi‐arid Kenya, episodes of agricultural droughts of varying severity and duration occur. The occurrence of these agricultural droughts is associated with seasonal rainfall variability and can be reflected by seasonal soil moisture deficits that significantly affect crop performance and yield. The objective of this study was to stochastically simulate the behaviour of dry and wet spells and rainfall amounts in Iiuni watershed, Kenya. The stochastic behaviour of the longest dry and wet spells (runs) and largest rainfall amounts were simulated using a Markov (order 1) model. There were eight raingauge stations within the watershed. The entire analysis was carried out using probability parameters, i.e. mean, variance, simple and conditional probabilities of dry and rain days. An analysis of variance test (ANOVA ) was used to establish significant differences in rainfall characteristics between the eight stations. An analysis of the number of rain days and rainfall amount per rain day was done on a monthly basis to establish the distribution and reliability of seasonal rainfall. The graphic comparison of simulated cumulative distribution functions (Cdfs) of the longest spells and largest rainfall amounts showed Markovian dependence or persistence. The longest dry spells could extend to 24 days in the long rainy season and 12 in the short rainy season. At 50% (median) probability level, the largest rainfall amounts were 91 mm for the long rainy season and 136 mm for the short rainy season. The short rains were more reliable for crop production than the long rains. The Markov model performed well and gave adequate simulations of the spells and rainfall amounts under semi‐arid conditions. Copyright © 2004 John Wiley & Sons, Ltd. 相似文献
18.
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
19.
Javier Tomasella Laura S. Borma José A. Marengo Daniel A. Rodriguez Luz A. Cuartas Carlos A. Nobre Maria C. R. Prado 《水文研究》2011,25(8):1228-1242
Severe hydrological droughts in the Amazon have generally been associated with strong El Niño events. More than 100 years of stage record at Manaus harbour confirms that minimum water levels generally coincide with intense warming in the tropical Pacific sea waters. During 2005, however, the Amazon experienced a severe drought which was not associated with an El Niño event. Unless what usually occurs during strong El Niño events, when negative rainfall anomalies usually affect central and eastern Amazon drainage basin; rainfall deficiencies in the drought of 2005 were spatially constrained to the west and southwest of the basin. In spite of this, discharge stations at the main‐stem recorded minimum water levels as low as those observed during the basin‐wide 1996–1997 El Niño‐related drought. The analysis of river discharges along the main‐stem and major tributaries during the drought of 2004–2005 revealed that the recession on major tributaries began almost simultaneously. This was not the case in the 1996–1997 drought, when above‐normal contribution of some tributaries for a short period during high water was crucial to partially counterbalance high discharge deficits of the other tributaries. Since time‐lagged contributions of major tributaries are fundamental to damp the extremes in the main‐stem, an almost coincident recession in almost all tributaries caused a rapid decrease in water discharges during the 2005 event. Copyright © 2010 John Wiley & Sons, Ltd. 相似文献
20.
Spatiotemporal analysis of climate variability (1971–2010) in spring and summer on the Loess Plateau,China 下载免费PDF全文
下载免费PDF全文 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