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1.
Egypt is almost totally dependent on the River Nile for satisfying about 95% of its water requirements. The River Nile has three main tributaries: White Nile, Blue Nile, and River Atbara. The Blue Nile contributes about 60% of total annual flow reached the River Nile at Aswan High Dam. The goal of this research is to develop a reliable stochastic model for the monthly streamflow of the Blue Nile at Eldiem station, where the Grand Ethiopian Renaissance Dam (GERD) is currently under construction with a storage capacity of about 74 billion m3. The developed model may help to carry out a reliable study on the filling scenarios of GERD reservoir and to minimize its expected negative side effects on Sudan and Egypt. The linear models: Deseasonalized AutoRegressive Moving Average (DARMA) model, Periodic AutoRegressive Moving Average (PARMA) model and Seasonal AutoRegressive Integrated Moving Average (SARIMA) model; and the nonlinear Artificial Neural Network (ANN) model are selected for modeling monthly streamflow at Eldiem station. The performance of various models during calibration and validation were evaluated using the statistical indices: Mean Absolute Error, Root Mean Square Error and coefficient of determination (R2) which indicate the strength of fitting between observed and forecasted values. The results show that the performance of the nonlinear model (ANN) was much better than all investigated linear models (DARMA, PARMA and SARIMA) in forecasting the monthly flow discharges at Eldiem station. 相似文献
2.
Considerable uncertainty occurs in the parameter estimates of traditional rainfall–water level transfer function noise (TFN) models, especially with the models built using monthly time step datasets. This is due to the equal weights assigned for rainfall occurring during both water level rise and water level drop events while estimating the TFN model parameters using the least square technique. As an alternative to this approach, a threshold rainfall-based binary-weighted least square method was adopted to estimate the TFN model parameters. The efficacy of this binary-weighted approach in estimating the TFN model parameters was tested on 26 observation wells distributed across the Adyar River basin in Southern India. Model performance indices such as mean absolute error and coefficient of determination values showed that the proposed binary-weighted approach of fitting independent threshold-based TFN models for water level rise and water level drop scenarios considerably improves the model accuracy over other traditional TFN models.
EDITOR D. KoutsoyiannisASSOCIATE EDITOR A. Fiori 相似文献
3.
Geomagnetic pulsations of the serpentine-emission (SE) type are considered. A method for estimating the frequency and amplitude parameters in the form of a time function for pulsations—SE and the accompanying spectral components—is suggested. An estimation algorithm is developed on the basis of local approximating polyharmonic models and weighted moving average filtration. Examples of the estimation of the frequency and amplitude parameters of SE pulsations are given. It is proposed that the procedure be used to calculate the estimation errors in SE pulsation frequency parameters and to choose the tuning parameters. 相似文献
4.
Na Liu Thomas N. Buckley Xinguang He Xinping Zhang Cicheng Zhang Zidong Luo Hailong Wang Nasrin Sterling Huade Guan 《水文研究》2019,33(12):1670-1685
Plant transpiration depends on environmental conditions, and soil water availability is its primary control under water deficit conditions. In this study, we improve a simplified process‐based model (hereafter “BTA”) by including soil water potential (ψsoil) to explicitly represent the dependence of plant transpiration on root‐zone moisture conditions. The improved model is denoted as the BTA‐ψ model. We assessed the performance of the BTA and BTA‐ψ models in a subtropical monsoon climate and a Mediterranean climate with different levels of water stress. The BTA model performed reasonably in estimating daily and hourly transpiration under sufficient water conditions, but it failed during dry periods. Overall, the BTA‐ψ model provided a significant improvement for estimating transpiration under a wide range of soil moisture conditions. Although both models could estimate transpiration (sap flow) at night, BTA‐ψ was superior to BTA in this regard. Species differences in the calibrated parameters of both models were consistent with leaf‐level photosynthetic measurements on each species, as expected given the physiological basis of these parameters. With a simplified representation of physiological regulation and reasonable performance across a range of soil moisture conditions, the BTA‐ψ model provides a useful alternative to purely empirical models for modelling transpiration. 相似文献
5.
The Budyko formula for estimating the long‐term average annual evaporation is applied to calculate the long‐term water balance in 29 humid watersheds of southern China. As a result of overestimation of evaporation, the long‐term average annual runoff is underestimated, with the Nash‐Sutcliffe efficiency (NSE) at just ? 17%. A one‐variable linear regression model is employed to find that the Budyko scatter and the relative errors of Budyko runoff and evaporation estimates are all closely related to the long‐term aridity index. Through combining the original Budyko formula with the different linear regression models for estimating the Budyko estimation errors, three forms of revised Budyko equation for estimating the long‐term average annual runoff are derived, with all their NSE values to be around 66%. After calibration, both one‐parameter Turc‐Pike and one‐parameter Fu equations lead to the NSE value of 60% in estimating long‐term average annual runoff. Two conclusions are made, with the first one being that, the nonparametric Budyko formula, although very intuitive and very simple, does not apply well in calculating long‐term water balance in 29 humid watersheds in southern China. The second one is that, the parametric evaporation formulae, with locally optimized parameter values, can achieve better accuracy in estimating long‐term average annual evaporation and runoff than the nonparametric Budyko evaporation formula. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
6.
Nermin Sarlak 《水文研究》2008,22(17):3403-3409
Classical autoregressive models (AR) have been used for forecasting streamflow data in spite of restrictive assumptions, such as the normality assumption for innovations. The main reason for making this assumption is the difficulties faced in finding model parameters for non‐normal distribution functions. However, the modified maximum likelihood (MML) procedure used for estimating autoregressive model parameters assumes a non‐normally distributed residual series. The aim in this study is to compare the performance of the AR(1) model with asymmetric innovations with that of the classical autoregressive model for hydrological annual data. The models considered are applied to annual streamflow data obtained from two streamflow gauging stations in K?z?l?rmak Basin, Turkey. Copyright © 2008 John Wiley & Sons, Ltd. 相似文献
7.
Higher-order approximation techniques for estimating stochastic parameter of the non-homogeneous Poisson (NHP) model are
presented. The NHP model is characterized by a two-parameter cumulative probability distribution function (CDF) of sediment
displacement. Those two parameters are the temporal and spatial intensity functions, physically representing the inverse of
the average rest period and step length of sediment particles, respectively. Difficulty of estimating the parameters has,
however, restricted the applications of the NHP model. The approximation techniques are proposed to address such problem.
The basic idea of the method is to approximate a model involving stochastic parameters by Taylor series expansion. The expansion
preserves certain higher-order terms of interest. Using the experimental (laboratory or field) data, one can determine the
model parameters through a system of equations that are simplified by the approximation technique. The parameters so determined
are used to predict the cumulative distribution of sediment displacement. The second-order approximation leads to a significant
reduction of the CDF error (of the order of 47%) compared to the first-order approximation. Error analysis is performed to
evaluate the accuracy of the first- and second-order approximations with respect to the experimental data. The higher-order
approximations provide better estimations of the sediment transport and deposition that are critical factors for such environment
as spawning gravel-bed. 相似文献
8.
9.
F.-C. Wu C.-K. Wang 《Stochastic Environmental Research and Risk Assessment (SERRA)》1998,12(6):359-375
Higher-order approximation techniques for estimating stochastic parameter of the non-homogeneous Poisson (NHP) model are
presented. The NHP model is characterized by a two-parameter cumulative probability distribution function (CDF) of sediment
displacement. Those two parameters are the temporal and spatial intensity functions, physically representing the inverse of
the average rest period and step length of sediment particles, respectively. Difficulty of estimating the parameters has,
however, restricted the applications of the NHP model. The approximation techniques are proposed to address such problem.
The basic idea of the method is to approximate a model involving stochastic parameters by Taylor series expansion. The expansion
preserves certain higher-order terms of interest. Using the experimental (laboratory or field) data, one can determine the
model parameters through a system of equations that are simplified by the approximation technique. The parameters so determined
are used to predict the cumulative distribution of sediment displacement. The second-order approximation leads to a significant
reduction of the CDF error (of the order of 47%) compared to the first-order approximation. Error analysis is performed to
evaluate the accuracy of the first- and second-order approximations with respect to the experimental data. The higher-order
approximations provide better estimations of the sediment transport and deposition that are critical factors for such environment
as spawning gravel-bed. 相似文献
10.
Ambiguity in parameter identification represents a potentially serious limitation to the application of models of surface water acidification. Previous work has concentrated on manipulation of two of the three factors affecting model identifiability, namely model structure and estimator properties. A new technique is proposed which uses different modes of response within the data to improve parameter identification. Preliminary results, obtained using the Birkenes model of surface water acidification, appear to show promise. The technique is robust in recovering model parameters from synthetic data, with and without error, and in assimilating problems of structural error. 相似文献
11.
Abstract. A simple closed-form expression relating saturated hydraulic conductivity to the van Genuchten capillary retention model parameters is derived. Application of this equation to an experimental data set shows reasonable agreement between measured and predicted saturated conductivity values. The proposed equation provides a consistent theoretical basis for estimating both saturated and unsaturated hydraulic conductivity from statistical pore structure models. 相似文献
12.
A geographic information system (GIS) is utilized to model wetness potential for a portion of Uwharrie National Forest, North Carolina. The wetness index is derived from TOPMODEL, a hillslope-scale runoff simulation model. The wetness index is a distributed-parameter model, with the input parameters obtained from a digital elevation model (DEM) and Soil Conservation Service (SCS) soils data. The primary objectives of the research are to: (1) compare methods of estimating soil parameters for input into the wetness potential model; and (2) determine how the model outputs vary spatially as a consequence of different methods of estimating soil parameters. Three methods of estimating soil parameters are used: (a) assuming uniform soil properties; (b) using SCS data presented as ranges; and (c) using alternative literature-based estimates of soil parameters. Results indicate that the wetness model responds similarly regardless of how the soil parameters are estimated, but differences in the spatial variability of the wetness potentials occur as a result of estimating soil parameters through alternative approaches. Correlation, pair-wise regression and analysis of regression residuals are used to compare model responses within a GIS environment. 相似文献
13.
Accuracy of the Copernicus snow water equivalent (SWE) product and the impact of SWE calibration and assimilation on modelled SWE and streamflow was evaluated. Daily snowpack measurements were made at 12 locations from 2016 to 2019 across a 4104 km2 mixed-forest basin in the Great Lakes region of central Ontario, Canada. Sub-basin daily SWE calculated from these sites, observed discharge, and lake levels were used to calibrate a hydrologic model developed using the Raven modelling framework. Copernicus SWE was bias corrected during the melt period using mean bias subtraction and was compared to daily basin average SWE calculated from the measured data. Bias corrected Copernicus SWE was assimilated into the models using a range of parameters and the parameterizations from the model calibration. The bias corrected Copernicus product agreed well with measured data and provided a good estimate of mean basin SWE demonstrating that the product shows promise for hydrology applications within the study region. Calibration to spatially distributed SWE substantially improved the basin scale SWE estimate while only slightly degrading the flow simulation demonstrating the value of including SWE in a multi-objective calibration formulation. The particle filter experiments yielded the best SWE estimation but moderately degraded the flow simulation. The particle filter experiments constrained by the calibrated snow parameters produced similar results to the experiments using the upper and lower bounds indicating that, in this study, model calibration prior to assimilation was not valuable. The calibrated models exhibited varying levels of skill in estimating SWE but demonstrated similar streamflow performance. This indicates that basin outlet streamflow can be accurately estimated using a model with a poor representation of distributed SWE. This may be sufficient for applications where estimating flow is the primary water management objective. However, in applications where understanding the physical processes of snow accumulation, melt and streamflow generation are important, such as assessing the impact of climate change on water resources, accurate representations of SWE are required and can be improved via multi-objective calibration or data assimilation, as demonstrated in this study. 相似文献
14.
Using geostatistical simulation to disaggregate air quality model results for individual exposure estimation on GPS tracks 总被引：1，自引：1，他引：0
Lydia E. Gerharz Edzer Pebesma 《Stochastic Environmental Research and Risk Assessment (SERRA)》2013,27(1):223-234
In this work, we address the mismatch in spatio-temporal resolution between individual, point-location based exposure and grid cell based air quality model predictions by disaggregating the grid model results. Variability of PM10 point measurements was modelled within each grid cell by the exponential variogram, using point support concentration measurements. Variogram parameters were estimated over the study area globally using constant estimates, and locally by multiple regression models using traffic, weather and land use data. Model predictions of spatio-temporal variability were used for geostatistical unconditional simulation, estimating the deviation of point values from grid cell averages on GPS tracks. The distribution of deviations can be used as an estimate of uncertainty for individual exposure. Results showed a relevant impact of the disaggregation uncertainties compared to other uncertainty sources, dependent of the model used for spatio-temporal variability. Depending on individual behaviour and variability of the pollutant, these uncertainties average out again over time. 相似文献
15.
The use of historical data can significantly reduce the uncertainty around estimates of the magnitude of rare events obtained with extreme value statistical models. For historical data to be included in the statistical analysis a number of their properties, e.g. their number and magnitude, need to be known with a reasonable level of confidence. Another key aspect of the historical data which needs to be known is the coverage period of the historical information, i.e. the period of time over which it is assumed that all large events above a certain threshold are known. It might be the case though, that it is not possible to easily retrieve with sufficient confidence information on the coverage period, which therefore needs to be estimated. In this paper methods to perform such estimation are introduced and evaluated. The statistical definition of the problem corresponds to estimating the size of a population for which only few data points are available. This problem is generally refereed to as the German tanks problem, which arose during the second world war, when statistical estimates of the number of tanks available to the German army were obtained. Different estimators can be derived using different statistical estimation approaches, with the maximum spacing estimator being the minimum-variance unbiased estimator. The properties of three estimators are investigated by means of a simulation study, both for the simple estimation of the historical coverage and for the estimation of the extreme value statistical model. The maximum spacing estimator is confirmed to be a good approach to the estimation of the historical period coverage for practical use and its application for a case study in Britain is presented. 相似文献
16.
High‐resolution seismic monitoring of instrumented buildings using a model‐based state observer 
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下载免费PDF全文 This paper proposes a model‐based state observer to perform high‐definition response estimation in partially instrumented building structures. The proposed estimator is verified in a simulated five‐story shear‐building structure and validated using measurements from a seven‐story reinforced concrete building slice tested at the NEES‐University of California at San Diego shake table. In both cases the proposed estimator yielded satisfactory results by estimating the time history of shear forces, bending moments, displacements, and strains at various points/sections of interest. The proposed algorithm can be used in instrumented buildings for various practical applications such as post‐earthquake damage assessment, structural control, and building code calibration. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
17.
《Ground Water Monitoring & Remediation》2000,20(3):147-158
Recovery wells remain the principle technology for removal of free-product hydrocarbon liquids from the subsurface. This paper presents simple models for estimating hydrocarbon recovery rates using wells and vacuum-enhanced systems. Use of LNAPL volume balance between LNAPL recovery rate and formation free-product volume leads to development of algebraic equations that can be used to estimate recovery times. Selection of model parameters is discussed, model comparisons are made, and applications are presented for design and analysis of recovery systems using wells. Model validation is also discussed. 相似文献
18.
A Neural Network model has been developed for estimating the total electron content (TEC) of the ionosphere. TEC is proportional
to the delay suffered by electromagnetic signals crossing the ionosphere and is among the errors that impact GNSS (Global
Navigation Satellite Systems) observations. Ionospheric delay is particularly a problem for single frequency receivers, which
cannot eliminate the (first-order) ionospheric delay by combining observations at two frequencies. Single frequency users
rely on applying corrections based on prediction models or on regional models formed based on actual data collected by a network
of receivers. A regional model based on a neural network has been designed and tested using data sets collected by the Brazilian
GPS Network (RMBC) covering periods of low and high solar activity. Analysis of the results indicates that the model is capable
of recovering, on average, 85% of TEC values. 相似文献
19.
Ye Tian Martijn J. Booij Yue-Ping Xu 《Stochastic Environmental Research and Risk Assessment (SERRA)》2014,28(2):319-332
This paper aims to investigate the uncertainty in simulated extreme low and high flows originating from hydrological model structure and parameters. To this end, three different rainfall-runoff models, namely GR4J, HBV and Xinanjiang, are applied to two subbasins of Qiantang River basin, eastern China. The Generalised Likelihood Uncertainty Estimation approach is used for estimating the uncertainty of the three models due to parameter values, henceforth referred as parameter uncertainty. Uncertainty in simulated extreme flows is evaluated by means of the annual maximum discharge and mean annual 7-day minimum discharge. The results show that although the models have good performance for the daily flows, the uncertainty in the extreme flows could not be neglected. The uncertainty originating from parameters is larger than uncertainty due to model structure. The parameter uncertainty of the extreme flows increases with the observed discharge. The parameter uncertainty in both the extreme high flows and the extreme low flows is the largest for the HBV model and the smallest for the Xinanjiang model. It is noted that the extreme low flows are mostly underestimated by all models with optimum parameter sets for both subbasins. The largest underestimation is from Xinanjiang model. Therefore it is not reliable enough to use only one set of the parameters to make the prediction and carrying out the uncertainty study in the extreme discharge simulation could give an overall picture for the planners. 相似文献
20.
探讨了利用气旋风场分布的经验模型估算热带气旋尺度(8级大风圈半径)的方法.用美国联合台风警报中心整编的2001年西北太平洋热带气旋的“最佳尺度”资料,确定了各模型的经验常数,并计算了各模型的估算精度.结果表明,“VBogus”模型能获得热带气旋(Tropical Cyclone,简称TC)尺度的较好估算.基于“VBogus”模型,通过拟合热带气旋尺度的非对称分布,构造了能描述热带气旋非对称风场的"修正VBogus"模型,并估算了该模型中各参数在不同季节和不同地理区域的取值,为热带气旋尺度变化和非对称结构机制等问题的研究和应用提供新依据. 相似文献