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1.
T.C. Sharma 《水文科学杂志》2013,58(3):549-569
Abstract A hydrological drought magnitude (M T ) expressed in standardized terms is predicted on annual, monthly and weekly time scales for a sampling period of T years in streamflow data from the Canadian prairies. The drought episodes are considered to follow the Poisson law of probability and, when coupled with the gamma probability distribution function (pdf) of drought magnitude (M) in the extreme number theorem, culminate in a relationship capable of evaluating the expected value, E(M T ). The parameters of the underlying pdf of M are determined based on the assumption that the drought intensity follows a truncated normal pdf. The E(M T ) can be evaluated using only standard deviation (σ), lag-1 autocorrelation (ρ) of the standardized hydrological index (SHI) sequence, and a weighting parameter Φ (ranging from 0 to 1) to account for the extreme drought duration (L T ), as well as the mean drought duration (Lm ), in a characteristic drought length (Lc ). The SHI is treated as standard normal variate, equivalent to the commonly-used standardized precipitation index. A closed-form relationship can be used for the estimation of first-order conditional probabilities, which can also be estimated from historical streamflow records. For all rivers, at the annual time scale, the value of Φ was found equal to 0.5, but it tends to vary (in the range 0 to 1) from river to river at monthly and weekly time scales. However, for a particular river, the Φ value was nearly constant at monthly and weekly time scales. The proposed method estimates E(M T ) satisfactorily comparable to the observed counterpart. At the annual time scale, the assumption of a normal pdf for drought magnitude tends to yield results in close proximity to that of a gamma pdf. The M T , when transformed into deficit-volume, can form a basis for designing water storage facilities and for planning water management strategies during drought periods. Editor D. Koutsoyiannis; Associate editor C. Onof Citation Sharma, T.C. and Panu, U.S., 2013. A semi-empirical method for predicting hydrological drought magnitudes in the Canadian prairies. Hydrological Sciences Journal, 58 (3), 549–569. 相似文献
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T.C. Sharma 《水文科学杂志》2013,58(4):705-722
Abstract Hydrological drought durations (lengths) in the Canadian prairies were modelled using the standardized hydrological index (SHI) sequences derived from the streamflow series at annual, monthly and weekly time scales. The rivers chosen for the study present high levels of persistence (as indicated by values exceeding 0.95 for lag-1 autocorrelation in weekly SHI sequences), because they encompass large catchment areas (2210–119 000 km2) and traverse, or originate in, lakes. For such rivers, Markov chain models were found to be simple and efficient tools for predicting the drought duration (year, month, or week) based on annual, monthly and weekly SHI sequences. The prediction of drought durations was accomplished at threshold levels corresponding to median flow (Q50) (drought probability, q?=?0.5) to Q95 (drought probability, q?=?0.05) exceedence levels in the SHI sequences. The first-order Markov chain or the random model was found to be acceptable for the prediction of annual drought lengths, based on the Hazen plotting position formula for exceedence probability, because of the small sample size of annual streamflows. On monthly and weekly time scales, the second-order Markov chain model was found to be satisfactory using the Weibull plotting position formula for exceedence probability. The crucial element in modelling drought lengths is the reliable estimation of parameters (conditional probabilities) of the first- and second-order persistence, which were estimated using the notions implicit in the discrete autoregressive moving average class of models. The variance of drought durations is of particular significance, because it plays a crucial role in the accurate estimation of persistence parameters. Although, the counting method of the estimation of persistence parameters was found to be unsatisfactory, it proved useful in setting the initial values and also in subsequent adjustment of the variance-based estimates of persistence parameters. At low threshold levels corresponding to q < 0.20, even the first-order Markov chain can be construed as a satisfactory model for predicting drought durations based on monthly and weekly SHI sequences. Editor D. Koutsoyiannis; Associate editor C. Onof Citation Sharma, T.C. and Panu, U.S., 2012. Prediction of hydrological drought durations based on Markov chains in the Canadian prairies. Hydrological Sciences Journal, 57 (4), 705–722. 相似文献
3.
T. C. Sharma 《水文科学杂志》2013,58(1):79-92
Abstract Two entities of importance in hydrological droughts, viz. the longest duration, LT , and the largest magnitude, MT (in standardized terms) over a desired time period (which could also correspond to a specific return period) T, have been analysed for weekly flow sequences of Canadian rivers. Analysis has been carried out in terms of week-by-week standardized values of flow sequences, designated as SHI (standardized hydrological index). The SHI sequence is truncated at the median level for identification and evaluation of expected values of the above random variables, E(LT ) and E(MT ). SHI sequences tended to be strongly autocorrelated and are modelled as autoregressive order-1, order-2 or autoregressive moving average order-1,1. The drought model built on the theorem of extremes of random numbers of random variables was found to be less satisfactory for the prediction of E(LT ) and E(MT ) on a weekly basis. However, the model has worked well on a monthly (weakly Markovian) and an annual (random) basis. An alternative procedure based on a second-order Markov chain model provided satisfactory prediction of E(LT ). Parameters such as the mean, standard deviation (or coefficient of variation), and lag-1 serial correlation of the original weekly flow sequences (obeying a gamma probability distribution function) were used to estimate the simple and first-order drought probabilities through closed-form equations. Second-order probabilities have been estimated based on the original flow sequences as well as SHI sequences, utilizing a counting method. The E(MT ) can be predicted as a product of drought intensity (which obeys the truncated normal distribution) and E(LT ) (which is based on a mixture of first- and second-order Markov chains). Citation Sharma, T. C. & Panu, U. S. (2010) Analytical procedures for weekly hydrological droughts: a case of Canadian rivers. Hydrol. Sci. J. 55(1), 79–92. 相似文献
4.
T.C. Sharma 《水文科学杂志》2017,62(5):760-773
Methods based on the recursive probability, the extreme number theorem, and Markov chain (MC) concepts were applied to predict drought lengths (duration) on the standardized (termed as standardized hydrological index, SHI) sequences of monthly and annual river flows from Atlantic Canada. Results of the study indicated that the MC-based method is the most efficient, reliable and versatile method for predicting drought durations followed by the extreme-number-based method. The recursive-probability-based method was found to be computationally intensive and less efficient, although it provided a powerful means for calibrating the empirical plotting position formula needed in the MC-based method. The Weibull plotting position formula turned out to be a suitable measure of the exceedance probability in MC methodology for predicting drought lengths in Atlantic Canada. Based on results, it can be inferred that the MC-based method can be extended to MC2 and higher-order chains for predicting drought lengths on SHI sequences. The predictive capability of the extreme-number-theorem-based method is limited only to independent or weakly first-order persistent SHI sequences.
EDITOR D. KoutsoyiannisASSOCIATE EDITOR Q. Zhang 相似文献
5.
《水文科学杂志》2013,58(3):503-518
Abstract Two parameters of importance in hydrological droughts viz. the longest duration, LT and the largest severity, ST (in standardized form) over a desired return period, T years, have been analysed for monthly flow sequences of Canadian rivers. An important point in the analysis is that monthly sequences are non-stationary (periodic-stochastic) as against annual flows, which fulfil the conditions of stochastic stationarity. The parameters mean, μ, standard deviation, σ (or coefficient of variation), lag1 serial correlation, ρ, and skewness, γ (which is helpful in identifying the probability distribution function) of annual flow sequences, when used in the analytical relationships, are able to predict expected values of the longest duration, E(LT ) in years and the largest standardized severity, E(ST ). For monthly flow sequences, there are 12 sets of these parameters and thus the issue is how to involve these parameters to derive the estimates of E(LT ) and E(ST ). Moreover, the truncation level (i.e. the monthly mean value) varies from month to month. The analysis in this paper demonstrates that the drought analysis on an annual basis can be extended to monthly droughts simply by standardizing the flows for each month. Thus, the variable truncation levels corresponding to the mean monthly flows were transformed into one unified truncation level equal to zero. The runs of deficits in the standardized sequences are treated as drought episodes and thus the theory of runs forms an essential tool for analysis. Estimates of the above parameters (denoted as μav, σav, ρav, and γav) for use in the analytical relationships were obtained by averaging 12 monthly values for each parameter. The product- and L-moment ratio analyses indicated that the monthly flows in the Canadian rivers fit the gamma probability distribution reasonably well, which resulted in the satisfactory prediction of E(LT ). However, the prediction of E(ST ) tended to be more satisfactory with the assumption of a Markovian normal model and the relationship E(ST ) ≈ E(LT ) was observed to perform better. 相似文献
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Abstract Techniques are proposed for developing a monthly and weekly drought outlook and the drought outlook components are evaluated. A drought index, the surface water supply index (SWSI) was modified and used for the drought outlook. A water balance model (abcd) was successfully calibrated using a regional regression, including monthly and weekly factors, and was used to convert meteorology to hydrology. For the monthly drought outlook, an ensemble technique was applied, both with and without monthly industrial meteorology information (MIMI). For the weekly drought outlook, a deterministic forecasting technique was applied employing the Global Data Assimilation and Prediction System (GDAPS). The methodologies were applied to the Geum River basin in Korea. While only the weekly outlook using the GDAPS has sufficient forecasting capability to suggest it might be useful, the accuracy of the monthly drought outlook is expected to improve as the climate forecast accuracy increases. Editor Z.W. Kundzewicz; Associate editor D. Hughes Citation Kim, Y.-O., Lee, J.-K., and Palmer, R.N., 2012. A drought outlook study in Korea. Hydrological Sciences Journal, 57 (6), 1141–1153. 相似文献
8.
Abstract The aim of this paper is to quantify meteorological droughts and assign return periods to these droughts. Moreover, the relation between meteorological and hydrological droughts is explored. This has been done for the River Meuse basin in Western Europe at different spatial and temporal scales to enable comparison between different data sources (e.g. stations and climate models). Meteorological drought is assessed in two ways: using annual minimum precipitation amounts as a function of return period, and using troughs under threshold as a function of return period. The Weibull extreme value type 3 distribution has been fitted to both sources of information. Results show that the trough-under-threshold precipitation is larger than the annual minimum precipitation for a specific return period. Annual minimum precipitation values increase with spatial scale, being most pronounced for small temporal scales. The uncertainty in annual minimum point precipitation varies between 68% for the 30-day precipitation with a return period of 100 years, and 8% for the 120-day precipitation with a return period of 10 years. For spatially-averaged values, these numbers are slightly lower. The annual discharge deficit is significantly related to the annual minimum precipitation. Citation Booij, M. J. & de Wit, M. J. M. (2010) Extreme value statistics for annual minimum and trough-under-threshold precipitation at different spatio-temporal scales. Hydrol. Sci. J. 55(8), 1289–1301. 相似文献
9.
Dimitrios Myronidis Dimitrios Fotakis Konstantinos Ioannou Konstantina Sgouropoulou 《水文科学杂志》2013,58(15-16):2005-2019
ABSTRACTTen notable meteorological drought indices were compared on tracking the effect of drought on streamflow. A 730-month dataset of precipitation, temperature and evapotranspiration for 88 catchments in Oregon, USA, representing pristine conditions, was used to compute the drought indices. These indices were correlated with the monthly streamflow datasets of the minimum, maximum and mean discharge, and the discharge monthly fluctuation; it was revealed that the 3-month Z-score drought index (Z3) has the best association with the four streamflow variables. The Mann-Kendall trend detection test applied to the latter index time series mainly highlighted a downward trend in the autumn and winter drought magnitude (DM) and an upward trend in the spring and summer DM (p = 0.05). Finally, the Pettitt test indicated an abrupt decline in the annual and autumn DM, which began in 1984 and 1986, respectively. 相似文献
10.
T. C. Sharma 《水文研究》1998,12(4):597-611
In many arid and semi-arid environments of the world, years of extended droughts are not uncommon. The occurrence of a drought can be reflected by the deficiency of the rainfall or stream flow sequences below the long-term mean value, which is generally taken as the truncation level for the identification of the droughts. The commonly available statistics for the above processes are mean, coefficient of variation and the lag-one serial correlation coefficient, and at times some indication of the probability distribution function (pdf) of the sequences. The important elements of a drought phenomenon are the longest duration and the largest severity for a desired return period, which form a basis for designing facilities to meet exigencies arising as a result of droughts. The sequences of drought variable, such as annual rainfall or stream flow, may follow normal, log-normal or gamma distributions, and may evolve in a Markovian fashion and are bound to influence extremal values of the duration and severity. The effect of the aforesaid statistical parameters on the extremal drought durations and severity have been analysed in the present paper. A formula in terms of the extremal severity and the return period ‘T’ in years has been suggested in parallel to the flood frequency formula, commonly cited in the hydrological texts. © 1998 John Wiley & Sons, Ltd. 相似文献
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AbstractLarge errors in peak discharge estimates at catchment scales can be ascribed to errors in the estimation of catchment response time. The time parameters most frequently used to express catchment response time are the time of concentration (TC), lag time (TL) and time to peak (TP). This paper presents a review of the time parameter estimation methods used internationally, with selected comparisons in medium and large catchments in the C5 secondary drainage region in South Africa. The comparison of different time parameter estimation methods with recommended methods used in South Africa confirmed that the application of empirical methods, with no local correction factors, beyond their original developmental regions, must be avoided. The TC is recognized as the most frequently used time parameter, followed by TL. In acknowledging this, as well as the basic assumptions of the approximations TL = 0.6TC and TC ≈ TP, along with the similarity between the definitions of the TP and the conceptual TC, it was evident that the latter two time parameters should be further investigated to develop an alternative approach to estimate representative response times that result in improved estimates of peak discharge at these catchment scales.
Editor Z.W. Kundzewicz; Associate editor Qiang Zhang 相似文献
13.
W. H. Ward 《水文科学杂志》2013,58(1):85-101
AbstractA new method is presented to generate stationary multi-site hydrological time series. The proposed method can handle flexible time-step length, and it can be applied to both continuous and intermittent input series. The algorithm is a departure from standard decomposition models and the Box-Jenkins approach. It relies instead on the recent advances in statistical science that deal with generation of correlated random variables with arbitrary statistical distribution functions. The proposed method has been tested on 11 historic weekly input series, of which the first seven contain flow data and the last four have precipitation data. The article contains an extensive review of the results.Editor D. KoutsoyiannisCitation Ilich, N., 2014. An effective three-step algorithm for multi-site generation of stochastic weekly hydrological time series. Hydrological Sciences Journal, 59 (1), 85–98. 相似文献
14.
Abstract Pooling of flood data is widely used to provide a framework to estimate design floods by the Index Flood method. Design flood estimation with this approach involves derivation of a growth curve which shows the relationship between XT and the return period T, where XT ?=?QT /QI and QI is the index flood at the site of interest. An implicit assumption with the Index Flood procedure of pooling analysis is that the XT –T relationship is the same at all sites in a homogeneous pooling group, although this assumption would generally be violated to some extent in practical cases, i.e. some degree of heterogeneity exists. In fact, in only some cases is the homogeneity criterion effectively satisfied for Irish conditions. In this paper, the performance of the index-flood pooling analysis is assessed in the Irish low CV (coefficient of variation) hydrology context considering that heterogeneity is taken into account. It is found that the performance of the pooling method is satisfactory provided there are at least 350 station years of data included. Also it is found that, in a highly heterogeneous group, it is more desirable to have many sites with short record lengths than a smaller number of sites with long record lengths. Increased heterogeneity decreases the advantage of pooling group-based estimation over at-site estimation. Only a heterogeneity measure (H1) less than 4.0 can render the pooled estimation preferable to that obtained for at-site estimation for the estimation of 100-year flood. In moderately to highly heterogeneous regions it is preferable to conduct at-site analysis for the estimation of 100-year flood if the record length at the site concerned exceeds 50. Editor Z.W. Kundzewicz; Associate editor A. Carsteanu Citation Das, S. and Cunnane, C., 2012. Performance of flood frequency pooling analysis in a low CV context. Hydrological Sciences Journal, 57 (3), 433–444. 相似文献
15.
ABSTRACTThe aim of the present paper was to improve understanding of the rainfall dynamics in Bas-Congo and Kinshasa provinces, in Democratic Republic of Congo (DRC). The first objective of the study was achieved by analysing the spatial correlations of monthly, seasonal, annual and individual monthly rainfall amounts of Kinshasa and Bas-Congo. The second objective was achieved through investigating and quantifying the temporal trends and their spatial variations. The results demonstrated notably high average inter-station correlation of +0.63 for dry season series, followed by monthly rainfall series with an average inter-station correlation of +0.58. However, there was no station with a stable monthly rainfall regime, i.e. with mean precipitation concentration index lower than 10% (it varies between 14.2 and 21.9%). Moreover, Kinshasa experienced an increase of rainfall with an average annual rate of change of +4.59 mm/year for the period 1961–2006. The results will be helpful for efficient water resources management and for mitigating the adverse impacts of future extreme drought or flood occurrences.
Editor M.C. Acreman Associate editor N. Verhoest 相似文献
16.
T. C. SHARMA 《水文科学杂志》2013,58(6):803-814
Abstract The important elements of a drought phenomenon are the longest duration and the largest severity for a desired return period. These elements form a basis for designing water storage systems to cope with droughts. At times, a third element, drought intensity, is also used and is defined as the ratio of severity to duration. The commonly available statistics for the causative drought variables such as annual rainfall or runoff sequences are the mean, the coefficient of variation and the lag one serial correlation coefficient, and occasionally some indication of the probability distribution function (pdf) of the sequences. The extremal values of the duration and severity are modelled in the present paper using information on the aforesaid parameters at the truncation level equal to the mean of the drought sequence, which is generally taken as the truncation level in the analysis of droughts. The drought severity has been modelled as the product of the duration and intensity with the assumption of independence between them. An estimate of drought intensity has been realized from the concept of the truncated normal distribution of the standardized form of the drought sequences in the normalized domain. A formula in terms of the extremal severity and the T-year return period has been suggested similar to the flood frequency formulae, commonly cited in hydrological texts. 相似文献
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水文干旱多变量联合设计及水库影响评估 总被引：2，自引：1，他引：1
基于东江流域博罗站月径流数据,采用游程理论提取水文干旱事件.选用Meta-Gaussian Copula函数,统计模拟水文干旱指标的多变量联合分布.采用Kendall联合重现期和最大可能权函数,设计给定联合超越重现期的水文干旱指标组合值,并定量评估水库径流调节作用对水文干旱多变量联合特征的影响.结果表明:东江流域水文干旱历时、强度和峰值的统计优选分布均为韦布尔分布.干旱指标之间具有较高的正相关性,Meta-Gaussian Copula能够很好地模拟水文干旱指标两变量和三变量联合分布.基于任意两个变量联合设计和三变量联合设计,干旱指标设计组合值位于同频位置附近,且同一个干旱指标设计值在不同变量组合之间差别较小.水库径流调节作用对于缓解东江流域水文干旱效果明显,同一组干旱指标的多变量联合超越重现期在水库影响下明显变大.联合超越重现期越小,水库对联合设计值的影响程度越大.根据目前水库运行模式,若要满足河道内最小管理流量目标,联合超越重现期10 a一遇的干旱历时、强度和峰值依然达到了约3.89~4.04月、7.20~7.97亿m3和2.99~3.12亿m3. 相似文献
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Abstract Statistical analysis of extreme events is often carried out to predict large return period events. In this paper, the use of partial L-moments (PL-moments) for estimating hydrological extremes from censored data is compared to that of simple L-moments. Expressions of parameter estimation are derived to fit the generalized logistic (GLO) distribution based on the PL-moments approach. Monte Carlo analysis is used to examine the sampling properties of PL-moments in fitting the GLO distribution to both GLO and non-GLO samples. Finally, both PL-moments and L-moments are used to fit the GLO distribution to 37 annual maximum rainfall series of raingauge station Kampung Lui (3118102) in Selangor, Malaysia, and it is found that analysis of censored rainfall samples of PL-moments would improve the estimation of large return period events. Editor D. Koutsoyiannis; Associate editor K. Hamed Citation Zakaria, Z.A., Shabri, A. and Ahmad, U.N., 2012. Estimation of the generalized logistic distribution of extreme events using partial L-moments. Hydrological Sciences Journal, 57 (3), 424–432. 相似文献
19.
利用西江下游马口水文站1959 2009年月径流量数据计算径流干旱指数,经游程理论提取了水文干旱特征值.应用Copula函数分析水文干旱强度和历时之间的联合概率分布.对构建的干旱历时和强度联合分布模式进行分析,结果表明:(1)径流干旱历时和强度之间具有高关联性,秩相关系数达0.617;(2)三参数Weibull分布较好地描述了干旱历时和强度的边缘分布特征;(3)经拟合优度检验结果优选的干旱历时和强度之间的较优连接函数为Archimedean类的Gumbel-Hougaard Copula函数;(4)5～10年重现期和20年重现期的水文干旱分别达到了重旱级别和特旱级别;(5)干旱历时和强度之间的遭遇概率可为特定干旱历时与水文干旱级别或特定干旱强度与干旱历时之间的对应关系提供概率意义上的干旱特征诊断与预测. 相似文献
20.
A. H. M. GÖRGENS 《水文科学杂志》2013,58(4):485-498
ABSTRACT A monthly conceptual rainfall—runoff model that enjoys fairly widespread use in South Africa was calibrated for each of 50 calibration samples of lengths 3–20 years, drawn from a synthetic 101-year semiarid streamflow time series generated with the Stanford Watershed Model. The ability of Pitman's model to reconstruct the original 101 years of monthly streamflow for each of the 50 calibrations was then examined against a set of statistics of monthly and annual streamflows. The variabilities of key model parameters associated with different lengths of calibration period were also investigated. The results show that it is well worthwhile to increase the calibration period to about 15 years in order to reduce errors in reconstructed flow statistics. Merely increasing the length of calibration period from 6 to 10 years may decrease the error in most regenerated flow statistics by 30–50%. A fair amount of variability in “optimum” parameters, however, seems unavoidable, even at longer calibration periods, though this may also partly be due to imperfect model calibration. The effects of this variability are greatly attenuated in the reconstructed flow statistics due to parameter interdependence. 相似文献