共查询到20条相似文献，搜索用时 172 毫秒
1.
ABSTRACTThe potential of the most recent pre-processing tool, namely, complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), is examined for providing AI models (artificial neural network, ANN; M5-model tree, M5-MT; and multivariate adaptive regression spline, MARS) with more informative input–output data and, thence, evaluate their forecasting accuracy. A 130-year inflow dataset for Aswan High Dam, Egypt, is considered for training, validating and testing the proposed models to forecast the reservoir inflow up to six months ahead. The results show that, after the pre-processing analysis, there is a significant enhancement in the forecasting accuracy. The MARS model combined with CEEMDAN gave superior performance compared to the other models – CEEMDAN-ANN and CEEMDAN-M5-MT – with an increase in accuracy of, respectively, about 13–25% and 6–20% in terms of the root mean square error. 相似文献
2.
Daily river inflow time series are highly valuable for water resources and water environment management of large lakes. However, the availability of continuous inflow data for large lakes is still relatively limited, especially for large lakes situated within humid plain regions with tens or even hundreds of tributaries. In this study, we choose the fifth largest freshwater Lake Chaohu in China as our study area to introduce a new approach to reconstruct historical daily inflows at ungauged subcatchments of large lakes. This approach makes use of water level, lake surface rainfall, evaporation from the lake, and catchment rainfall observations. Rainfall–runoff relationship at a reference catchment was analysed to select rainfall input and estimate run‐off coefficient firstly, and the run‐off coefficient was then transferred to ungauged subcatchments to initially estimate daily inflows. Run‐off coefficient was scaled to adjust daily inflows at ungauged subcatchments according to water balance of the lake. This approach was evaluated using sparsely measured inflows at eight subcatchments of Lake Chaohu and compared with the commonly used drainage area ratio method. Results suggest that the inflow time series reconstructed from this approach consistent well to corresponding observations, with mean R2 and Nash–Sutcliffe efficiency values of 0.69 and 0.6, respectively. This approach outperforms drainage area ratio method in terms of mean R2 and Nash–Sutcliffe efficiency values. Accuracy of this approach holds well when the number of water‐level station being used decreased from four to one. 相似文献
3.
Abstract A real-time operational methodology has been developed for multipurpose reservoir operation for irrigation and hydropower generation with application to the Bhadra reservoir system in the state of Karnataka, India. The methodology consists of three phases of computer modelling. In the first phase, the optimal release policy for a given initial storage and inflow is determined using a stochastic dynamic programming (SDP) model. Streamflow forecasting using an adaptive AutoRegressive Integrated Moving Average (ARIMA) model constitutes the second phase. A real-time simulation model is developed in the third phase using the forecast inflows of phase 2 and the operating policy of phase 1. A comparison of the optimal monthly real-time operation with the historical operation demonstrates the relevance, applicability and the relative advantage of the proposed methodology. 相似文献
4.
Abstract Time series modelling approaches are useful tools for simulating and forecasting hydrological variables and their change through time. Although linear time series models are common in hydrology, the nonlinear time series model, the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model, has rarely been used in hydrology and water resources engineering. The GARCH model considers the conditional variance remaining in the residuals of the linear time series models, such as an ARMA or an ARIMA model. In the present study, the advantages of a GARCH model against a linear ARIMA model are investigated using three classes of the GARCH approach, namely Power GARCH, Threshold GARCH and Exponential GARCH models. A daily streamflow time series of the Matapedia River, Quebec, Canada, is selected for this study. It is shown that the ARIMA (13,1,4) model is adequate for modelling streamflow time series of Matapedia River, but the Engle test shows the existence of heteroscedasticity in the residuals of the ARIMA model. Therefore, an ARIMA (13,1,4)-GARCH (3,1) error model is fitted to the data. The residuals of this model are examined for the existence of heteroscedasticity. The Engle test indicates that the GARCH model has considerably reduced the heteroscedasticity of the residuals. However, the Exponential GARCH model seems to completely remove the heteroscedasticity from the residuals. The multi-criteria evaluation for model performance also proves that the Exponential GARCH model is the best model among ARIMA and GARCH models. Therefore, the application of a GARCH model is strongly suggested for hydrological time series modelling as the conditional variance of the residuals of the linear models can be removed and the efficiency of the model will be improved. Editor D. Koutsoyiannis; Associate editor C. Onof Citation Modarres, R. and Ouarda, T.B.M.J., 2013. Modelling heteroscedasticty of streamflow times series. Hydrological Sciences Journal, 58 (1), 1–11. 相似文献
5.
Janesh Devkota 《水文科学杂志》2013,58(10):1666-1689
AbstractA three-dimensional Environmental Fluid Dynamics Code model was developed for a 17-km segment of the Mobile River, Alabama, USA. The model external forcing factors include river inflows from upstream, tides from downstream, and atmospheric conditions. The model was calibrated against measured water levels, velocities, and temperatures from 26 April to 29 August 2011. The Nash-Sutcliffe coefficients for water levels were greater than 0.94 and for water temperatures ranged from 0.88 to 0.99. The calibrated model was extended approximately 13 km upstream for simulating unsteady flow, dye, and temperature distributions in the Mobile River under different upstream inflows and downstream harmonic tides. Velocity profiles and distributions of flow, dye, and temperature at various locations were analyzed and show that flow recirculation could only occur under small inflow (50 m3 s-1) when downstream tides control the flow pattern in the Mobile River. The model results reveal complex interactions among discharges from a power plant, inflows, and tides.
Editor D. Koutsoyiannis; Associate editor D. Yang 相似文献
6.
TOMMY S. W. WONG 《水文科学杂志》2013,58(5):663-666
Abstract Due to changes in physical characteristics, the valley side of a drainage basin may be represented by a series of overland planes. In such a situation, the downstream outflow from one plane becomes the upstream inflow for the subsequent plane. Based on the kinematic wave equations, two time of concentration (time to equilibrium) formulae are derived for planes subject to uniform rainfall excess and with a constant upstream inflow. For practical applications, the formulae are further developed in terms of the Manning resistance coefficient. The derived formulae are all consistent with those published for the case of zero upstream inflow. 相似文献
7.
Abstract Artificial neural networks provide a promising alternative to hydrological time series modelling. However, there are still many fundamental problems requiring further analyses, such as structure identification, parameter estimation, generalization, performance improvement, etc. Based on a proposed clustering algorithm for the training pairs, a new neural network, namely the range-dependent neural network (RDNN) has been developed for better accuracy in hydrological time series prediction. The applicability and potentials of the RDNN in daily streamflow and annual reservoir inflow prediction are examined using data from two watersheds in China. Empirical comparisons of the predictive accuracy, in terms of the model efficiency R2 and absolute relative errors (ARE), between the RDNN, back-propagation (BP) networks and the threshold auto-regressive (TAR) model are made. The case studies demonstrated that the RDNN network performed significantly better than the BP network, especially for reproducing low-flow events. 相似文献
8.
Abstract The data-based mechanistic (DBM) modelling methodology is applied to the study of reservoir sedimentation. A lumped-parameter, discrete-time model has been developed which directly relates rainfall to suspended sediment load (SSL) at the reservoir outflow from the two years of measured data at Wyresdale Park Reservoir (Lancashire, UK). This nonlinear DBM model comprises two components: a rainfall to SSL model and a second model, relating the SSL at the reservoir inflow to the SSL at the reservoir spillway. Using a daily measured rainfall series as the input, this model is used to reconstruct daily deposition rates between 1911 and 1996. This synthetic sediment accretion sequence is compared with the variations in sand content within sediment cores collected from the reservoir floor. These profiles show good general agreement, reflecting the importance of low reoccurrence, high magnitude events. This preliminary study highlights the potential of this DBM approach, which could be readily applied to other sites. 相似文献
9.
In this study, the nature of basin‐scale hydroclimatic association for Indian subcontinent is investigated. It is found that, the large‐scale circulation information from Indian Ocean is also equally important in addition to the El Niño‐Southern Oscillation (ENSO), owing to the geographical location of Indian subcontinent. The hydroclimatic association of the variation of monsoon inflow into the Hirakud reservoir in India is investigated using ENSO and EQUatorial INdian Ocean Oscillation (EQUINOO, the atmospheric part of Indian Ocean Dipole mode) as the large‐scale circulation information from tropical Pacific Ocean and Indian Ocean regions respectively. Individual associations of ENSO & EQUINOO indices with inflow into Hirakud reservoir are also assessed and found to be weak. However, the association of inflows into Hirakud reservoir with the composite index (CI) of ENSO and EQUINOO is quite strong. Thus, the large‐scale circulation information from Indian Ocean is also important apart form the ENSO. The potential of the combined information of ENSO and EQUINOO for predicting the inflows during monsoon is also investigated with promising results. The results of this study will be helpful to water resources managers due to fact that the nature of monsoon inflow is becoming available as an early prediction. Copyright © 2009 John Wiley & Sons, Ltd. 相似文献
10.
Abstract A hydrological modelling framework was assembled to simulate the daily discharge of the Mandovi River on the Indian west coast. Approximately 90% of the west-coast rainfall, and therefore discharge, occurs during the summer monsoon (June–September), with a peak during July–August. The modelling framework consisted of a digital elevation model (DEM) called GLOBE, a hydrological routing algorithm, the Terrestrial Hydrological Model with Biogeochemistry (THMB), an algorithm to map the rainfall recorded by sparse raingauges to the model grid, and a modified Soil Conservation Service Curve Number (SCS-CN) method. A series of discharge simulations (with and without the SCS method) was carried out. The best simulation was obtained after incorporating spatio-temporal variability in the SCS parameters, which was achieved by an objective division of the season into five regimes: the lean season, monsoon onset, peak monsoon, end-monsoon, and post-monsoon. A novel attempt was made to incorporate objectively the different regimes encountered before, during and after the Indian monsoon, into a hydrological modelling framework. The strength of our method lies in the low demand it makes on hydrological data. Apart from information on the average soil type in a region, the entire parameterization is built on the basis of the rainfall that is used to force the model. That the model does not need to be calibrated separately for each river is important, because most of the Indian west-coast basins are ungauged. Hence, even though the model has been validated only for the Mandovi basin, its potential region of application is considerable. In the context of the Prediction in Ungauged Basins (PUB) framework, the potential of the proposed approach is significant, because the discharge of these (ungauged) rivers into the eastern Arabian Sea is not small, making them an important element of the local climate system. Editor D. Koutsoyiannis; Associate editor S. Grimaldi Citation Suprit, K., Shankar, D., Venugopal, V. and Bhatkar, N.V., 2012. Simulating the daily discharge of the Mandovi River, west coast of India. Hydrological Sciences Journal, 57 (4), 686–704. 相似文献
11.
Abstract Reservoir silting is one of the principal problems affecting the performance of dams in Algeria from the standpoint of reservoir capacity for storage. Foum El Kherza Reservoir (also known as Foum El Gherza), near Biskra Town, Algeria, is subject to dredging operations with the intent of recovering 70% of its initial storage capacity of 47 hm3 (million cubic metres). The forecasting of sediment volume trapped in the reservoir is essential to plan the future use of this resource and to sustain irrigation for the palm groves characteristic of the region. However, there are currently no sediment data, nor a sediment rating curve, for predicting sediment inflow based on hydrological data. This paper describes the optimization of a cumulative trapped sediment curve for Foum El Kherza Reservoir based on 44 years of daily inflows, by using a spreadsheet optimization tool, Microsoft Excel® Solver to calibrate the cumulative sediment load against the cumulative sediment inflow as documented by eight bathymetric surveys since the dam construction. Editor D. Koutsoyiannis; Associate editor A. Montanari Citation Tebbi, F.Z., Dridi, H., and Morris, G.L., 2012. Optimization of cumulative trapped sediment curve for an arid zone reservoir: Foum El Kherza (Biskra, Algeria). Hydrological Sciences Journal, 57 (7), 1368–1377. 相似文献
12.
《水文科学杂志》2013,58(6)
Abstract A stochastic weather generator has been developed to simulate long daily sequences of areal rainfall and station temperature for the Belgian and French sub-basins of the River Meuse. The weather generator is based on the principle of nearest-neighbour resampling. In this method rainfall and temperature data are sampled simultaneously from multiple historical records with replacement such that the temporal and spatial correlations are well preserved. Particular emphasis is given to the use of a small number of long station records in the resampling algorithm. The distribution of the 10-day winter maxima of basin-average rainfall is quite well reproduced. The generated sequences were used as input for hydrological simulations with the semi-distributed HBV rainfall–runoff model. Though this model is capable of reproducing the flood peaks of December 1993 and January 1995, it tends to underestimate the less extreme daily peak discharges. This underestimation does not show up in the 10-day average discharges. The hydrological simulations with the generated daily rainfall and temperature data reproduce the distribution of the winter maxima of the 10-day average discharges well. Resampling based on long station records leads to lower rainfall and discharge extremes than resampling from the data over a shorter period for which areal rainfall was available. 相似文献
13.
ARIMA forecasting of ambient air pollutants (O3, NO, NO2 and CO) 总被引：1，自引：0，他引：1
Ujjwal Kumar V. K. Jain 《Stochastic Environmental Research and Risk Assessment (SERRA)》2010,24(5):751-760
In the present study, a stationary stochastic ARMA/ARIMA [Autoregressive Moving (Integrated) Average] modelling approach has
been adapted to forecast daily mean ambient air pollutants (O3, CO, NO and NO2) concentration at an urban traffic site (ITO) of Delhi, India. Suitable variance stabilizing transformation has been applied
to each time series in order to make them covariance stationary in a consistent way. A combination of different information-criterions,
namely, AIC (Akaike Information Criterion), HIC (Hannon–Quinn Information Criterion), BIC (Bayesian Information criterion),
and FPE (Final Prediction Error) in addition to ACF (autocorrelation function) and PACF (partial autocorrelation function)
inspection, has been tried out to obtain suitable orders of autoregressive (p) and moving average (q) parameters for the ARMA(p,q)/ARIMA(p,d,q)
models. Forecasting performance of the selected ARMA(p,q)/ARIMA(p,d,q) models has been evaluated on the basis of MAPE (mean
absolute percentage error), MAE (mean absolute error) and RMSE (root mean square error) indicators. For 20 out of sample forecasts,
one step (i.e., one day) ahead MAPE for CO, NO2, NO and O3, have been found to be 13.6, 12.1, 21.8 and 24.1%, respectively. Given the stochastic nature of air pollutants data and in
the light of earlier reported studies regarding air pollutants forecasts, the forecasting performance of the present approach
is satisfactory and the suggested forecasting procedure can be effectively utilized for short term air quality forewarning
purposes. 相似文献
14.
Including spatial distribution in a data‐driven rainfall‐runoff model to improve reservoir inflow forecasting in Taiwan 
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下载免费PDF全文 Multi‐step ahead inflow forecasting has a critical role to play in reservoir operation and management in Taiwan during typhoons as statutory legislation requires a minimum of 3‐h warning to be issued before any reservoir releases are made. However, the complex spatial and temporal heterogeneity of typhoon rainfall, coupled with a remote and mountainous physiographic context, makes the development of real‐time rainfall‐runoff models that can accurately predict reservoir inflow several hours ahead of time challenging. Consequently, there is an urgent, operational requirement for models that can enhance reservoir inflow prediction at forecast horizons of more than 3 h. In this paper, we develop a novel semi‐distributed, data‐driven, rainfall‐runoff model for the Shihmen catchment, north Taiwan. A suite of Adaptive Network‐based Fuzzy Inference System solutions is created using various combinations of autoregressive, spatially lumped radar and point‐based rain gauge predictors. Different levels of spatially aggregated radar‐derived rainfall data are used to generate 4, 8 and 12 sub‐catchment input drivers. In general, the semi‐distributed radar rainfall models outperform their less complex counterparts in predictions of reservoir inflow at lead times greater than 3 h. Performance is found to be optimal when spatial aggregation is restricted to four sub‐catchments, with up to 30% improvements in the performance over lumped and point‐based models being evident at 5‐h lead times. The potential benefits of applying semi‐distributed, data‐driven models in reservoir inflow modelling specifically, and hydrological modelling more generally, are thus demonstrated. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
15.
AbstractThe seasonal flood-limited water level (FLWL), which reflects the seasonal flood information, plays an important role in governing the trade-off between reservoir flood control and conservation. A risk analysis model for flood control operation of seasonal FLWL incorporating the inflow forecasting error was proposed and developed. The variable kernel estimation is implemented for deriving the inflow forecasting error density. The synthetic inflow incorporating forecasting error is simulated by Monte Carlo simulation (MCS) according to the inflow forecasting error density. The risk analysis for seasonal FLWL control was estimated by MCS based on a combination of the forecasting inflow lead-time, seasonal design flood hydrographs and seasonal operation rules. The Three Gorges reservoir is selected as a case study. The application results indicate that the seasonal FLWL control can effectively enhance flood water utilization rate without lowering the annual flood control standard.
Editor D. Koutsoyiannis; Associate editor A. ViglioneCitation Zhou, Y.-L. and Guo, S.-L., 2014. Risk analysis for flood control operation of seasonal flood-limited water level incorporating inflow forecasting error. Hydrological Sciences Journal, 59 (5), 1006–1019. 相似文献
16.
ABSTRACTAssessment of forecast precipitation is required before it can be used as input to hydrological models. Using radar observations in southeastern Australia, forecast rainfall from the Australian Community Climate Earth-System Simulator (ACCESS) was evaluated for 2010 and 2011. Radar rain intensities were first calibrated to gauge rainfall data from four research rainfall stations at hourly time steps. It is shown that the Australian ACCESS model (ACCESS-A) overestimated rainfall in low precipitation areas and underestimated elevated accumulations in high rainfall areas. The forecast errors were found to be dependent on the rainfall magnitude. Since the cumulative rainfall observations varied across the area and through the year, the relative error (RE) in the forecasts varied considerably with space and time, such that there was no consistent bias across the study area. Moreover, further analysis indicated that both location and magnitude errors were the main sources of forecast uncertainties on hourly accumulations, while magnitude was the dominant error on the daily time scale. Consequently, the precipitation output from ACCESS-A may not be useful for direct application in hydrological modelling, and pre-processing approaches such as bias correction or exceedance probability correction will likely be necessary for application of the numerical weather prediction (NWP) outputs.
EDITOR M.C. Acreman ASSOCIATE EDITOR A. Viglione 相似文献
17.
B. D. TRAFFORD 《水文科学杂志》2013,58(4):431-440
ABSTRACT Irrigation equipment was used to create strong flows in agricultural drains of clayware and plastic pipes, the latter in both smooth and corrugated conformations. The piezometric heads at 10 m intervals along the drains were analysed to show that the inflow per unit length varied greatly. Both inflows and outflows were found; some drains had substantial inflows at the origin. For given conditions the flow rates were as much as 17 per cent less than flow rates determined for similar conditions in the laboratory. 相似文献
18.
《水文科学杂志》2013,58(4)
Abstract Abstract An annual water balance model of Lake Victoria is derived for the period 1925–2000. Regression techniques are used to derive annual inputs to the water balance, based on lake rainfall data, measured and derived inflows and estimated evaporation during the historical period. This approach acknowledges that runoff is a nonlinear function of lake rainfall. A longer inflow series is produced here which is representative of the whole inflow to the lake, rather than just from individual tributaries. The results show a good simulation of annual lake levels and outflows and capture the high lake level in 1997–1998. Climate change scenarios, from a recent global climate model experiment, are applied to the lake rainfall inflow series and evaporation data to estimate future water balances of the lake. The scenarios produce a potential fall in lake levels by the 2030s horizon, and a rise by the 2080s horizon. A discussion of the application of climate change data to this complex hydrological system is presented. 相似文献
19.
Janine B. Adams 《水文科学杂志》2014,59(3-4):451-465
AbstractEnvironmental flow requirements of estuaries have been ignored in the past, mostly because of the lack of long-term monitoring data or understanding of the responses to changes in freshwater inflow. In some cases, it was incorrectly assumed that the minimum flows determined for rivers would protect downstream processes and in others the omission of environmental water requirement studies for estuaries was as a result of the sectoral management of water resources or lack of applicable legislation. Three main countries have developed methods for estuaries, i.e. Australia, South Africa and the USA, from practical applications and a learning-by-doing approach. Recent methods take a holistic and adaptive standpoint and are presented as frameworks that include a number of steps and have elements of risk assessment and adaptive management. Most approaches are data rich and emphasize long-term monitoring. This review showed that, although methods are available, implementation is slow and will require strong governance structures, stakeholder participation, monitoring and feedback in an adaptive management cycle.
Editor Z.W. Kundzewicz; Guest editor M. Acreman 相似文献
20.
Arthur J. Askew 《水文科学杂志》2013,58(1):195-196
Abstract A snowmelt runoff model is derived for relatively small rivers. The model involves the main components of the catchment water budget, physiographical and some other factors: water equivalent of snow cover, precipitation, antecedent moisture content, daily snowmelt, non-uniformity of snow cover, retention capacity of the basin, and percentage of forest area. The model structure includes calculations of the daily values of snowmelt excess and the transformation of these values into discharges at the outlet of the basin based on meteorological observations and appropriate distribution functions. Both calculations are made separately for open and forest areas. The parameters of the model were derived by optimization methods. The linear model based on the superposition principle is used to transform the discharges of a small river into total inflow into a large reservoir. The combined model was used to forecast for five days in advance daily mean inflows into the Gorky and Kuibyshev reservoirs (on the River Volga), using the observed and forecast discharges of the small rivers as input. 相似文献