共查询到20条相似文献，搜索用时 973 毫秒
1.
A general Bayesian framework for calibrating and evaluating stochastic models of annual multi-site hydrological data 总被引：1，自引：0，他引：1
Andrew J. Frost Mark A. Thyer R. Srikanthan George Kuczera 《Journal of Hydrology》2007,340(3-4):129-148
Multi-site simulation of hydrological data are required for drought risk assessment of large multi-reservoir water supply systems. In this paper, a general Bayesian framework is presented for the calibration and evaluation of multi-site hydrological data at annual timescales. Models included within this framework are the hidden Markov model (HMM) and the widely used lag-1 autoregressive (AR(1)) model. These models are extended by the inclusion of a Box–Cox transformation and a spatial correlation function in a multi-site setting. Parameter uncertainty is evaluated using Markov chain Monte Carlo techniques. Models are evaluated by their ability to reproduce a range of important extreme statistics and compared using Bayesian model selection techniques which evaluate model probabilities. The case study, using multi-site annual rainfall data situated within catchments which contribute to Sydney’s main water supply, provided the following results: Firstly, in terms of model probabilities and diagnostics, the inclusion of the Box–Cox transformation was preferred. Secondly the AR(1) and HMM performed similarly, while some other proposed AR(1)/HMM models with regionally pooled parameters had greater posterior probability than these two models. The practical significance of parameter and model uncertainty was illustrated using a case study involving drought security analysis for urban water supply. It was shown that ignoring parameter uncertainty resulted in a significant overestimate of reservoir yield and an underestimation of system vulnerability to severe drought. 相似文献
2.
This study proposed a methodology using the empirical orthogonal function (EOF) and multivariate time series model for the analysis of drought both in time and space. The methodology proposed was then applied to evaluate the vulnerability of agricultural drought of major river basins in Korea. First, the three-month SPI data from 59 rain gauge stations over the Korean Peninsula were analyzed by deriving and spatially characterizing the EOFs. The shapes of major estimated EOFs were found to well reflect the observed spatial pattern of droughts. Second, the coefficient time series of estimated EOFs were then fitted by a multivariate time series model to generate the SPI data for 10,000 years, which were used to derive the annual maxima series of areal average drought severity over the Korean Peninsula. These annual maxima series were then analyzed to determine the mean drought severity for given return periods. Four typical spatial patterns of drought severity could also be selected for those return periods considered. This result shows that the southern part of the Korean Peninsula is most vulnerable to drought than the other parts. Finally, the agricultural drought vulnerability was evaluated by considering the potential water supply from dams. In an ideal case, when all the maximum dam storage was assumed to be assigned to agriculture, all river basins in Korea were found to have the potential to overcome a 30-year drought. However, under more realistic conditions considering average dam storage and water allocation priorities, most of the river basins could not overcome a 30-year drought. 相似文献
3.
4.
An ensemble of stochastic daily rainfall projections has been generated for 30 stations across south‐eastern Australia using the downscaling nonhomogeneous hidden Markov model, which was driven by atmospheric predictors from four climate models for three IPCC emissions scenarios (A1B, A2, and B1) and for two periods (2046–2065 and 2081–2100). The results indicate that the annual rainfall is projected to decrease for both periods for all scenarios and climate models, with the exception of a few scenarios of no statistically significant changes. However, there is a seasonal difference: two downscaled GCMs consistently project a decline of summer rainfall, and two an increase. In contrast, all four downscaled GCMs show a decrease of winter rainfall. Because winter rainfall accounts for two‐thirds of the annual rainfall and produces the majority of streamflow for this region, this decrease in winter rainfall would cause additional water availability concerns in the southern Murray–Darling basin, given that water shortage is already a critical problem in the region. In addition, the annual maximum daily rainfall is projected to intensify in the future, particularly by the end of the 21st century; the maximum length of consecutive dry days is projected to increase, and correspondingly, the maximum length of consecutive wet days is projected to decrease. These changes in daily sequencing, combined with fewer events of reduced amount, could lead to drier catchment soil profiles and further reduce runoff potential and, hence, also have streamflow and water availability implications. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
5.
AbstractThe standardized series of monthly and weekly flow sequences, referred to as standardized hydrological index (SHI) series, from five rivers in the Canadian prairies were subjected to return period (Tr) analysis of drought length (L). The SHI series were truncated at drought probability levels q ranging from 0.5 to 0.05 with the intention of deducing drought events and corresponding drought lengths. The values of L were fitted to the Pearson 3, the gamma (2-parameter), the exponential (1-parameter), the Weibull 3 and the Weibull (2-parameter) probability density functions (pdfs). A priori assignment of one week or one month for the location parameter in the Pearson 3 pdf proved logical and also facilitated the rapid estimation of other parameters using either the method of moments or the method of maximum likelihood. The Pearson 3 turns out to be the most suitable pdf to describe and to estimate return periods of drought lengths. At the monthly and weekly time scales, it was inferred that the sample size (T, months or weeks) of SHI series could be treated equivalent to the return period of the largest recorded drought length. At the annual time scale, however, the sample size (T, years) should be modified using either the Hazen or the Gringorten plotting position formula to reflect the actual return period of the largest recorded drought length in years.
Editor D. Koutsoyiannis; Associate editor E. Gargouri 相似文献
6.
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
7.
8.
《水文科学杂志》2013,58(4)
Abstract Because droughts cover extensive areas, it is important to consider multisite droughts in a region. Probability distribution of joint droughts at a number of sites is derived assuming that flows are cross-correlated first-order Markov processes. A geometric distribution is found with a parameter that depends on the threshold probability, lag-one autocorrelation coefficients, and the multivariate probability of remaining below the threshold. Computation of the parameter of the geometric distribution is discussed. An expression is obtained for the return period of multisite droughts. Application of the derived expression is shown in an example. 相似文献
9.
Estimation of regional meteorological and hydrological drought characteristics: a case study for Denmark 总被引：6，自引：0，他引：6
Information on regional drought characteristics provides critical information for adequate water resource management. This study introduces a method to calculate the probability of a specific area to be affected by a drought of a given severity and demonstrates its potential for calculating both meteorological and hydrological drought characteristics. The method is demonstrated using Denmark as a case study. The calculation procedure was applied to monthly precipitation and streamflow series separately, which were linearly transformed by the Empirical Orthogonal Functions (EOF) method. Denmark was divided into 260 grid-cells of 14×17 km, and the monthly mean and the EOF-weight coefficients were interpolated by kriging. The frequency distributions of the first two (streamflow) or three (precipitation) amplitude functions were then derived. By performing Monte Carlo simulations, amplitude functions corresponding to 1000 years of data were generated. Based on these simulated functions as well as interpolated mean and weight coefficients, long time series of precipitation and streamflow were simulated for each grid-cell. The probability distribution functions of the area covered by a drought and the drought deficit volumes were then derived and combined to produce drought severity-area-frequency curves. These curves allowed an estimation of the probability of an area of a certain extent to have a drought of a given severity, and thereby return periods could be assigned to historical drought events. A comparison of drought characteristics showed that streamflow droughts are less homogeneous over the region, less frequent and last for longer time periods than precipitation droughts. 相似文献
10.
Aníbal Ojeda Kuvvet Atakan Eullia Masana Pere Santanach María-Jos Jimnez Mariano García-Fernndez 《Soil Dynamics and Earthquake Engineering》2002,22(9-12):911-916
In this study, the influence of paleoseismic and geologic data in the seismic hazard estimation for the Catalan coastal ranges is analysed. We computed the probabilistic seismic hazard using area seismic sources with a Poissonian assumption for the earthquake occurrence. For the computations, a previously published attenuation relationship based on European strong motion data was applied. The resulting hazard estimates show similarities to the previous assessments in the region. These results were then used as a reference for comparison with other new models. In order to analyse the influence of the paleoseismic data three different models were tested. Since the number of faults that are investigated in detail are few, the same area sources that were used in the Poissonian assumption were kept in all three new models. In addition, the new paleoseismic data with faults expressed as line sources were used. In this case, a cyclic earthquake occurrence was assumed. The three models were based on the paleoseismic data with different assumptions on the time elapsed since last event. The time elapsed was set to 0, 10 and 85% of the recurrence interval in each model. The results are presented as maps showing the difference between the three models and the reference model with the Poissonian assumption. The results are given in horizontal peak ground acceleration contour maps for different return periods, also taking into account large return periods as high as 25,000 years. This is done to demonstrate the effect of large recurrence intervals found for some of the active faults. In general, we observe that for short return periods (<1000 years), the Poissonian assumption of earthquake occurrence is probably sufficient and provides a robust estimate of the hazard. However, for longer return periods (>5000 years) the effects of the paleoseismic data become increasingly significant. In order to estimate the true seismic hazard potential of this apparently low seismicity area, long-term behaviour of the possible active faults in the region needs to be investigated systematically. 相似文献
11.
In Part 1 we demonstrated the applicability of stochastic models to predicting the characteristics of point drought events within any planning period by means of a case study (Mohan S, Sahoo PK (2007) Hydrological Processes 21 : this issue). In addition, studies on regional droughts are important in the context of regional level planning and evolving management strategies. The small number of drought events from a particular streamflow or rainfall series, when subjected to statistical analysis in order to predict future occurrences, produces results that are not very reliable. To overcome this difficulty, we propose using a long sequence of synthetically generated annual rainfall series at various rain‐gauge stations of a region, and multiyear regional droughts were derived from both historic and generated series. The key parameters for a successful regional multiyear drought study are the critical area ratio and the critical level, and the area affected by the drought can be ascertained using these parameters. The important regional drought parameters were determined and their suitable probability distributions were arrived at by studying a total of nine possible probability models; these models can be used in predicting the longest regional drought duration and the greatest regional drought severity with a given return period. The effect of change of critical parameters on the regional drought parameters is also studied and reported. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
12.
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
13.
《水文科学杂志》2013,58(6):1121-1136
Abstract One of the most significant anticipated consequences of global climate change is the change in frequency of hydrological extremes. Predictions of climate change impacts on the regime of hydrological extremes have traditionally been conducted by a top-down approach that involves a high degree of uncertainty associated with the temporal and spatial characteristics of general circulation model (GCM) outputs and the choice of downscaling technique. This study uses the inverse approach to model hydrological risk and vulnerability to changing climate conditions in the Seyhan River basin, Turkey. With close collaboration with the end users, the approach first identifies critical hydrological exposures that may lead to local failures in the Seyhan River basin. The Hydro-BEAM hydrological model is used to inversely transform the main hydrological exposures, such as floods and droughts, into corresponding meteorological conditions. The frequency of critical meteorological conditions is investigated under present and future climate scenarios by means of a weather generator based on the improved K-nearest neighbour algorithm. The weather generator, linked with the output of GCMs in the last step of the proposed methodology, allows for the creation of an ensemble of scenarios and easy updating when improved GCM outputs become available. Two main conclusions were drawn from the application of the inverse approach to the Seyhan River basin. First, floods of 100-, 200- and 300-year return periods under present conditions will have 102-, 293- and 1370-year return periods under the future conditions; that is, critical flood events will occur much less frequently under the changing climate conditions. Second, the drought return period will change from 5.3 years under present conditions to 2.0 years under the future conditions; that is, critical drought events will occur much more frequently under the changing climate conditions. 相似文献
14.
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
15.
Youcun Liu Miaojie Lu Xueli Huo Yonghong Hao Hongkai Gao Yan Liu Yonghui Fan Yuhuan Cui Francois Metivier 《水文研究》2016,30(3):424-432
Global climate change models have predicted the intensification of extreme events, and these predictions are already occurring. For disaster management and adaptation of extreme events, it is essential to improve the accuracy of extreme value statistical models. In this study, Bayes' Theorem is introduced to estimate parameters in Generalized Pareto Distribution (GPD), and then the GPD is applied to simulate the distribution of minimum monthly runoff during dry periods in mountain areas of the Ürümqi River, Northwest China. Bayes' Theorem treats parameters as random variables and provides a robust way to convert the prior distribution of parameters into a posterior distribution. Statistical inferences based on posterior distribution can provide a more comprehensive representation of the parameters. An improved Markov Chain Monte Carlo (MCMC) method, which can solve high‐dimensional integral computation in the Bayes equation, is used to generate parameter simulations from the posterior distribution. Model diagnosis plots are made to guarantee the fitted GPD is appropriate. Then based on the GPD with Bayesian parameter estimates, monthly runoff minima corresponding to different return periods can be calculated. The results show that the improved MCMC method is able to make Markov chains converge faster. The monthly runoff minima corresponding to 10a, 25a, 50a and 100a return periods are 0.60 m3/s, 0.44 m3/s, 0.32 m3/s and 0.20 m3/s respectively. The lower boundary of 95% confidence interval of 100a return level is below zero, which implies that the Ürümqi River is likely to cease to flow when 100a return level appears in dry periods. Copyright © 2015 John Wiley & Sons, Ltd. 相似文献
16.
Streamflow drought time series forecasting 总被引：5，自引：2，他引：5
Reza Modarres 《Stochastic Environmental Research and Risk Assessment (SERRA)》2007,21(3):223-233
Drought is considered to be an extreme climatic event causing significant damage both in the natural environment and in human
lives. Due to the important role of drought forecasting in water resources planning and management and the stochastic behavior
of drought, a multiplicative seasonal autoregressive integrated moving average (SARIMA) model is applied to the monthly streamflow
forecasting of the Zayandehrud River in western Isfahan province, Iran. After forecasting 12 leading month streamflow, four
drought thresholds including streamflow mean, monthly streamflow mean, 2-, 5-, 10- and 20-year return period monthly drought
and standardized streamflow index were chosen. Both observed and forecasted streamflow showed a drought period with different
severity in the lead-time. This study also demonstrates the usefulness of SARIMA models in forecasting, water resources planning
and management. 相似文献
17.
A bivariate pareto model for drought 总被引：2，自引：2，他引：0
Saralees Nadarajah 《Stochastic Environmental Research and Risk Assessment (SERRA)》2009,23(6):811-822
Univariate Pareto distributions have been so widely used in hydrology. It seems however that bivariate or multivariate Pareto
distributions have not yet found applications in hydrology, especially with respect to drought. In this note, a drought application
is described by assuming a bivariate Pareto model for the joint distribution drought durations and drought severity in the
State of Nebraska. Based on this model, exact distributions are derived for the inter arrival time, magnitude and the proportion
of droughts. Estimates of 2, 5, 10, 20, 50 and 100 year return periods are derived for the three variables, drought duration,
drought severity and the pairwise combinations: (drought duration, drought severity), (inter arrival time of drought, proportion
of drought) and (drought duration, drought magnitude). These return period estimates could have an important role in hydrology,
for example, with respect to measures of vegetation water stress for plants in water-controlled ecosystems. 相似文献
18.
Drought forecasting using stochastic models 总被引：8，自引：4，他引：8
A. K. Mishra V. R. Desai 《Stochastic Environmental Research and Risk Assessment (SERRA)》2005,19(5):326-339
Drought is a global phenomenon that occurs virtually in all landscapes causing significant damage both in natural environment
and in human lives. Due to the random nature of contributing factors, occurrence and severity of droughts can be treated as
stochastic in nature. Early indication of possible drought can help to set out drought mitigation strategies and measures
in advance. Therefore drought forecasting plays an important role in the planning and management of water resource systems.
In this study, linear stochastic models known as ARIMA and multiplicative Seasonal Autoregressive Integrated Moving Average
(SARIMA) models were used to forecast droughts based on the procedure of model development. The models were applied to forecast
droughts using standardized precipitation index (SPI) series in the Kansabati river basin in India, which lies in the Purulia
district of West Bengal state in eastern India. The predicted results using the best models were compared with the observed
data. The predicted results show reasonably good agreement with the actual data, 1–2 months ahead. The predicted value decreases
with increase in lead-time. So the models can be used to forecast droughts up to 2 months of lead-time with reasonably accuracy. 相似文献
19.
Christian Onof 《水文研究》2013,27(11):1600-1614
Under future climate scenarios, possible changes of drought patterns pose new challenges for water resources management. For quantifying and qualifying drought characteristics in the UK, the drought severity indices of six catchments are investigated and modelled by two stochastic methods: autoregressive integrated moving average (ARIMA) models and the generalized linear model (GLM) approach. From the ARIMA models, autocorrelation structures are first identified for the drought index series, and the unexplained variance of the series is used to establish empirical relationships between drought and climate variables. Based on the ARIMA results, mean sea level pressure and possibly the North Atlantic Oscillation index are found to be significant climate variables for seasonal drought forecasting. Using the GLM approach, occurrences and amounts of rainfall are simulated with conditioning on climate variables. From the GLM‐simulated rainfall for the 1980s and 2080s, the probabilistic characteristics of the drought severity are derived and assessed. Results indicate that the drought pattern in the 2080s is less certain than for the 1961–1990 period, based on the Shannon entropy, but that droughts are expected to be more clustered and intermittent. The 10th and 50th quantiles of drought are likely higher in the 2080s scenarios, but there is no evidence showing the changes in the 90th quantile extreme droughts. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
20.
Accurate representation of groundwater-surface water interactions is critical to modeling low river flows in the semi-arid southwestern United States. Although a number of groundwater-surface water models exist, they are seldom integrated with river operation/management models. A link between the object-oriented river and reservoir operations model, RiverWare, and the groundwater model, MODFLOW, was developed to incorporate groundwater-surface water interaction processes, such as river seepage/gains, riparian evapotranspiration, and irrigation return flows, into a rule-based water allocations model. An explicit approach is used in which the two models run in tandem, exchanging data once in each computational time step. Because the MODFLOW grid is typically at a finer resolution than RiverWare objects, the linked model employs spatial interpolation and summation for compatible communication of exchanged variables. The performance of the linked model is illustrated through two applications in the Middle Rio Grande Basin in New Mexico where overappropriation impacts endangered species habitats. In one application, the linked model results are compared with historical data; the other illustrates use of the linked model for determining management strategies needed to attain an in-stream flow target. The flows predicted by the linked model at gauge locations are reasonably accurate except during a few very low flow periods when discrepancies may be attributable to stream gaging uncertainties or inaccurate documentation of diversions. The linked model accounted for complex diversions, releases, groundwater pumpage, irrigation return flows, and seepage between the groundwater system and canals/drains to achieve a schedule of releases that satisfied the in-stream target flow. 相似文献