Linear combinations of order statistics to estimate the quantiles of generalized pareto and extreme values distributions

 Ad hoc techniques for estimating the quantiles of the Generalized Pareto (GP) and the Generalized Extreme Values (GEV) distributions are introduced. The estimators proposed are based on new estimators of the position and the scale parameters recently introduced in the Literature. They provide valuable estimates of the quantiles of interest both when the shape parameter is known and when it is unknown (this latter case being of great relevance in practical applications). In addition, weakly-consistent estimators are introduced, whose calculation does not require the knowledge of any parameter. The procedures are tested on simulated data, and comparisons with other techniques are shown. The research was partially supported by Contract n. ENV4-CT97-0529 within the project “FRAMEWORK” of the European Community – D.G. XII. Grants by “Progetto Giovani Ricercatori” are also acknowledged.     

Linear combinations of order statistics to estimate the position and scale parameters of the Generalized Extreme Values distribution

 Ad hoc techniques for estimating the position and the scale parameters of the Generalized Extreme Values distribution are introduced. The estimators proposed are simple linear combinations of the order statistics: they provide valuable estimates of the parameters of interest both when the shape parameter is known and when it is unknown (this latter case being of great relevance in practical applications), and show a good performance as well when the sample size is small. In addition, weakly-consistent estimators of the position parameter are introduced, whose calculation does not require the knowledge of any of the remaining parameters. The procedures are tested on simulated data, and comparisons with other techniques are shown.     

Sensitivity analysis of a no-crossflow model for the transient flowmeter test

 Logarithmic sensitivities and plausible relative errors are studied in a simple no-crossflow model of a transient flowmeter test (TFMT). This model is identical to the model of a constant-rate pumping test conducted on a fully penetrating well with wellbore storage, surrounded by a thick skin zone, and situated in a homogeneous confined aquifer. The sensitivities of wellbore drawdown and wellface flowrate to aquifer and skin parameters are independent of the pumping rate. However, the plausible relative errors in the aquifer and skin parameters estimated from drawdown and wellface flowrate data can be proportionally decreased by increasing the pumping rate. The plausible relative errors vary by many orders of magnitude from the beginning of the TFMT. The practically important flowrate and drawdown measurements in this test, for which the plausible relative errors vary by less than one order of magnitude from the minimum plausible relative errors, can begin approximately when the dimensionless wellface flowrate exceeds q _D =q/Q≈0.4. During most of this stage of the test, the plausible relative errors in aquifer hydraulic conductivity (K _a ) are generally an order of magnitude smaller than those in aquifer specific storativity. The plausible relative errors in the skin hydraulic conductivity (K _s ) are generally larger than the plausible relative errors in the aquifer specific storativity when the thick skin is normal (K _s >K _a ) and smaller when the thick skin is damaged (K _s <K _a ). The specific storativity of the skin zone would be so biased that one should not even attempt to estimate it from the TFMT. We acknowledge Wiebe H. van der Molen for recommending the De Hoog algorithm and sharing his code. This research was partially supported by the US Geological Survey, USGS Agreement #1434-HQ-96-GR-02689 and North Carolina Water Resources Research Institute, WRRI Project #70165.     

Application of a conceptual method for separating runoff components in daily hydrographs in Kimakia forest catchments,Kenya

This paper highlights the use of a conceptual method for separating runoff components in daily hydrographs, contrary to the traditionally used graphical method of separation. In the conceptual method, the components, viz. surface flow, interflow and baseflow, are regarded as high, medium and low frequency signals and their separation is done using the principle of a recursive digital filter commonly used in signal analysis and processing. It requires estimates of the direct runoff (β_d) and surface runoff (β_s) filter parameters which are obtained by a least‐squares procedure involving baseflow and interflow indices based on graphical and recursive digital filter estimation techniques. The method thus circumvents the subjective element associated with the graphical procedure of hydrograph separation, in which case the eye approximation and/or one's skill at plotting is the prime basis for the whole analysis. The analysis based on three forest catchments in Kimakia, Kenya, East Africa, revealed that β_d=K_b and β_s=K_i , where K_b and K_i are the baseflow and interflow recession constants. Copyright © 1999 John Wiley & Sons, Ltd.     

Sensitivity of soil parameters in unsaturated zone modelling and the relation between effective,laboratory and in situ estimates

Simulation of soil moisture content requires effective soil hydraulic parameters that are valid at the modelling scale. This study investigates how these parameters can be estimated by inverse modelling using soil moisture measurements at 25 locations at three different depths (at the surface, at 30 and 60 cm depth) on an 80 by 20 m hillslope. The study presents two global sensitivity analyses to investigate the sensitivity in simulated soil moisture content of the different hydraulic parameters used in a one‐dimensional unsaturated zone model based on Richards' equation. For estimation of the effective parameters the shuffled complex evolution algorithm is applied. These estimated parameters are compared to their measured laboratory and in situ equivalents. Soil hydraulic functions were estimated in the laboratory on 100 cm³ undisturbed soil cores collected at 115 locations situated in two horizons in three profile pits along the hillslope. Furthermore, in situ field saturated hydraulic conductivity was estimated at 120 locations using single‐ring pressure infiltrometer measurements. The sensitivity analysis of 13 soil physical parameters (saturated hydraulic conductivity (K_s), saturated moisture content (θ_s), residual moisture content (θ_r), inverse of the air‐entry value (α), van Genuchten shape parameter (n), Averjanov shape parameter (N) for both horizons, and depth (d) from surface to B horizon) in a two‐layer single column model showed that the parameter N is the least sensitive parameter. K_s of both horizons, θ_s of the A horizon and d were found to be the most sensitive parameters. Distributions over all locations of the effective parameters and the distributions of the estimated soil physical parameters from the undisturbed soil samples and the single‐ring pressure infiltrometer estimates were found significantly different at a 5% level for all parameters except for α of the A horizon and K_s and θ_s of the B horizon. Different reasons are discussed to explain these large differences. Copyright © 2004 John Wiley & Sons, Ltd.     

Estimation of unconfined aquifer parameters by genetic algorithms

Abstract

Unconfined aquifer parameters, viz. transmissivity, storage coefficient, specific yield and delay index from a pumping test are estimated using the genetic algorithm optimization (GA) technique. The parameter estimation problem is formulated as a least-squares optimization, in which the parameters are optimized by minimizing the deviations between the field-observed and the model-predicted time–drawdown data. Boulton's convolution integral for the determination of drawdown is coupled with the GA optimization technique. The bias induced by three different objective functions: (a) the sum of squares of absolute deviations between the observed and computed drawdown; (b) the sum of squares of normalized deviations with respect to the observed drawdown; and (c) the sum of squares of normalized deviations with respect to the computed drawdown, is statistically analysed. It is observed that, when the time–drawdown data contain no errors, the objective functions do not induce any bias in the parameter estimates and the true parameters are uniquely identified. However, in the presence of noise, these objective functions induce bias in the parameter estimates. For the case considered, defining the objective function as the sum of the squares of absolute deviations between the observed and simulated drawdowns resulted in the best possible estimates. A comparison of the GA technique with the curve-matching procedure and a conventional optimization technique, such as the sequential unconstrained minimization technique (SUMT), is made in estimating the aquifer parameters from a reported field pumping test in an unconfined aquifer. For the case considered, the GA technique performed better than the other two techniques in parameter estimation, with the sum-of-squares errors obtained from the GA about one fourth of those obtained by the curve matching procedure, and about half of those obtained by SUMT.

Citation Rajesh, M., Kashyap, D. & Hari Prasad, K. S. (2010) Estimation of unconfined aquifer parameters by genetic algorithms. Hydrol. Sci. J. 55(3), 403–413.     

Investigating the uncertainty and transferability of parameters in SWAT model under climate change

ABSTRACT

There is an implicit assumption in most work that the parameters calibrated based on observations remain valid for future climatic conditions. However, this might not be true due to parameter instability. This paper investigates the uncertainty and transferability of parameters in a hydrological model under climate change. Parameter transferability is investigated with three parameter sets identified for different climatic conditions, which are: wet, intermediate and dry. A parameter set based on the baseline period (1961–1990) is also investigated for comparison. For uncertainty analysis, a k-simulation set approach is proposed instead of employing the traditional optimization method which uses a single best-fit parameter set. The results show that the parameter set from the wet sub-period performs the best when transferred into wet climate condition, while the parameter set from the baseline period is the most appropriate when transferred into dry climate condition. The largest uncertainty of simulated daily high flows for 2011–2040 is from the parameter set trained in the dry sub-period, while that of simulated daily medium and low flows lies in the parameter set from the intermediate calibration sub-period. For annual changes in the future period, the uncertainty with the parameter set from the intermediate sub-period is the largest, followed by the wet sub-period and dry sub-period. Compared with high and medium flows/runoffs, the uncertainty of low flows/runoffs is much smaller for both simulated daily flows and annual runoffs. For seasonal runoffs, the largest uncertainty is from the intermediate sub-period, while the smallest is from the dry sub-period. Apart from that, the largest uncertainty can be observed for spring runoffs and the lowest one for autumn runoffs. Compared with the traditional optimization method, the k-simulation set approach shows many more advantages, particularly being able to provide uncertainty information to decision support for watershed management under climate change.

EDITOR Z.W. Kundzewicz ASSOCIATE EDITOR not assigned     

Development of an automatic calibration scheme for the HBV hydrological model

An automatic calibration scheme for the HBV model (ACSH) was developed. The ACSH was based on the physical significance of the model parameters and structure. The inference of hydrologists in the manual calibration was adopted as the guideline. A slight modification of the model structure of the soil routine was suggested to avoid interdependence of the parameters. In total nine parameters, except the snow routine, Fc and MAXBAS, were calibrated automatically in two stages; first the soil moisture routine and then the others. There are six sets in two stages in total. Using the Powell method, the parameters in each step were calibrated simultaneously with carefully selected objective functions, and in particular a powerful objective function for the soil moisture routine. The steps were in a fixed order in the ACSH according to the model structure. The optimal values of the model parameters were stable, with the different initial values varying in considerable ranges. The automatic calibration gave the same model performance as the manual calibration when the ACSH was tested in two basins. The automatic calibration can thus be used as a reference or as an alternative solution of the model. © 1997 John Wiley & Sons, Ltd.     

Seismological model parameters for northeastern and its surrounding region of India

A point source seismological model is used in this study to model the available strong motion accelerograms recorded by 17 events and to calculate three seismological model parameters, the source, path, and quality factor. Due to the paucity of recorded events, this is the first time these model parameters have been obtained for the northeastern and its surrounding region of India. The quality factors of the horizontal and vertical components of recorded events with corresponding standard deviations are Q_H(f) = 188.55f^0.94, σ₁ value (25, 0.025) and Q_V(f) = 169.76f^0.93, σ₁ value (20, 0.03), respectively. The source parameter stress drop values (μσ) vary within 124–180 bars for the subduction region and 80–169 bars for the active region. The Kappa factors for the horizontal and vertical components of recorded events on the soft rock site are 0.06 and 0.05, respectively. These seismological model parameters obtained in this study will be useful for future work deriving a ground motion attenuation relation based on a spectral model. Finally, these results are useful for seismic hazard assessment of a region having sparsely recorded events.     

山东长岛地区地震波非弹性衰减Q值、场地响应及震源参数研究

利用山东台网记录的长岛震群2017年2月14日—9月1日期间的波形与震相资料研究长岛地区非弹性衰减系数,得到该地区介质平均Q值与频率f的关系式为Q(f)=363.9f1.374 1。采用Moya等[1]提出的利用遗传算法联合反演得到长岛周边台站的场地响应,根据Brune模型震源参数计算公式求解长岛震群序列地震震源参数。结果显示,各个震源参数之间均存在一定的相关关系,地震矩随ML震级的增大而增加,地震矩与破裂半径R之间存在半对数关系,拐角频率fc随地震矩的增大而减少;长岛地震序列的应力降数值普遍偏小,最大不超过0.9MPa,这意味着长岛震源区整体构造应力较低,也可能指示长岛震群为低摩擦应力的断层作用;震源参数随时间的变化方面,整体而言,长岛震群地震应力降变化起伏很大,在M4.1地震发生前,拐角频率与应力降均发生快速下降后随即翻转上升的现象,证明在M4.1地震发生前震源区整体应力的挤压逐渐增强。     

Robust H∞ control for aseismic structures with uncertainties in model parameters

This paper presents a robust H∞ output feedback control approach for structural systems with uncertainties in model parameters by using available acceleration measurements and proposes conditions for the existence of such a robust output feedback controller. The uncertainties of structural stiffness, damping and mass parameters are assumed to be norm-bounded. The proposed control approach is formulated within the framework of linear matrix inequalities, for which existing convex optimization techniques, such as the LMI toolbox in MATLAB, can be used effectively and conveniently. To illustrate the effectiveness of the proposed robust H∞ strategy, a six-story building was subjected both to the 1940 El Centro earthquake record and to a suddenly applied Kanai-Tajimi filtered white noise random excitation. The results show that the proposed robust H∞ controller provides satisfactory results with or without variation of the structural stiffness, damping and mass parameters.     

Possible configurations of the magnetic field in the outer magnetosphere during geomagnetic polarity reversals

Possible configurations of the magnetic field in the outer magnetosphere during geomagnetic polarity reversals are investigated by considering the idealized problem of a magnetic multipole of order m and degree n located at the centre of a spherical cavity surrounded by a boundless perfect diamagnetic medium. In this illustrative idealization, the fixed spherical (magnetopause) boundary layer behaves as a perfectly conducting surface that shields the external diamagnetic medium from the compressed multipole magnetic field, which is therefore confined within the spherical cavity. For a general magnetic multipole of degree n, the non-radial components of magnetic induction just inside the magnetopause are increased by the factor 1 + [(n + 1)/n] relative to their corresponding values in the absence of the perfectly conducting spherical magnetopause. An exact equation is derived for the magnetic field lines of an individual zonal (m = 0), or axisymmetric, magnetic multipole of arbitrary degree n located at the centre of the magnetospheric cavity. For such a zonal magnetic multipole, there are always two neutral points and n – 1 neutral rings on the spherical magnetopause surface. The two neutral points are located at the poles of the spherical magnetopause. If n is even, one of the neutral rings is coincident with the equator; otherwise, the neutral rings are located symmetrically with respect to the equator. The actual existence of idealized higher-degree (n > 1) axisymmetric magnetospheres would necessarily imply multiple (n + 1) magnetospheric cusps and multiple (n) ring currents. Exact equations are also derived for the magnetic field lines of an individual non-axisymmetric magnetic multipole, confined by a perfectly conducting spherical magnetopause, in two special cases; namely, a symmetric sectorial multipole (m = n) and an antisymmetric sectorial multipole (m = n – 1). For both these non-axisymmetric magnetic multipoles, there exists on the spherical magnetopause surface a set of neutral points linked by a network of magnetic field lines. Novel magnetospheric processes are likely to arise from the existence of magnetic neutral lines that extend from the magnetopause to the surface of the Earth. Finally, magnetic field lines that are confined to, or perpendicular to, either special meridional planes or the equatorial plane, when the multipole is in free space, continue to be confined to, or perpendicular to, these same planes when the perfectly conducting magnetopause is present.Also Honorary Research Associate, Rutherford Appleton Laboratory, Chilton, Didcot, Oxon OX11 0QX, UK and Visiting Reader in Physics. University of Sussex, Falmer, Brighton BN1 9QH, UK     

Parameter identification and uncertainty analysis for simulating streamflow in a river basin of Eastern India

Uncertainty is inherent in modelling studies. However, the quantification of uncertainties associated with a model is a challenging task, and hence, such studies are somewhat limited. As distributed or semi‐distributed hydrological models are being increasingly used these days to simulate hydrological processes, it is vital that these models should be equipped with robust calibration and uncertainty analysis techniques. The goal of the present study was to calibrate and validate the Soil and Water Assessment Tool (SWAT) model for simulating streamflow in a river basin of Eastern India, and to evaluate the performance of salient optimization techniques in quantifying uncertainties. The SWAT model for the study basin was developed and calibrated using Parameter Solution (ParaSol), Sequential Uncertainty Fitting Algorithm (SUFI‐2) and Generalized Likelihood Uncertainty Estimation (GLUE) optimization techniques. The daily observed streamflow data from 1998 to 2003 were used for model calibration, and those for 2004–2005 were used for model validation. Modelling results indicated that all the three techniques invariably yield better results for the monthly time step than for the daily time step during both calibration and validation. The model performances for the daily streamflow simulation using ParaSol and SUFI‐2 during calibration are reasonably good with a Nash–Sutcliffe efficiency and mean absolute error (MAE) of 0.88 and 9.70 m³/s for ParaSol, and 0.86 and 10.07 m³/s for SUFI‐2, respectively. The simulation results of GLUE revealed that the model simulates daily streamflow during calibration with the highest accuracy in the case of GLUE (R² = 0.88, MAE = 9.56 m³/s and root mean square error = 19.70 m³/s). The results of uncertainty analyses by SUFI‐2 and GLUE were compared in terms of parameter uncertainty. It was found that SUFI‐2 is capable of estimating uncertainties in complex hydrological models like SWAT, but it warrants sound knowledge of the parameters and their effects on the model output. On the other hand, GLUE predicts more reliable uncertainty ranges (R‐factor = 0.52 for daily calibration and 0.48 for validation) compared to SUFI‐2 (R‐factor = 0.59 for daily calibration and 0.55 for validation), though it is computationally demanding. Although both SUFI‐2 and GLUE appear to be promising techniques for the uncertainty analysis of modelling results, more and more studies in this direction are required under varying agro‐climatic conditions for assessing their generic capability. Copyright © 2015 John Wiley & Sons, Ltd.     

Estimation of water cloud model vegetation parameters using a genetic algorithm

Abstract

The water cloud model is used to account for the effect of vegetation water content on radar backscatter data. The model generally comprises two parameters that characterize the vegetated terrain, A and B, and two bare soil parameters, C and D. In the present study, parameters A and B were estimated using a genetic algorithm (GA) optimization technique and compared with estimates obtained by the sequential unconstrained minimization technique (SUMT) from measured backscatter data. The parameter estimation was formulated as a least squares optimization problem by minimizing the deviations between the backscatter coefficients retrieved from the ENVISAT ASAR image and those predicted by the water cloud model. The bias induced by three different objective functions was statistically analysed by generating synthetic backscatter data. It was observed that, when the backscatter coefficient data contain no errors, the objective functions do not induce any bias in the parameter estimation and the true parameters are uniquely identified. However, in the presence of noise, these objective functions induce bias in the parameter estimates. For the cases considered, the objective function based on the sum of squares of normalized deviations with respect to the computed backscatter coefficient resulted in the best possible estimates. A comparison of the GA technique with the SUMT was undertaken in estimating the water cloud model parameters. For the case considered, the GA technique performed better than the SUMT in parameter estimation, where the root mean squared error obtained from the GA was about half of that obtained by the SUMT.

Editor D. Koutsoyiannis; Associate editor L. See

Citation Kumar, K., Hari Prasad, K.S. and Arora, M.K., 2012. Estimation of water cloud model vegetation parameters using a genetic algorithm. Hydrological Sciences Journal, 57 (4), 776–789.     

基于VSP直达波资料的粘弹介质参数遗传算法反演

粘弹性参数变得越来越重要,其反演算法也逐渐成为众多研究者的研究热点。而遗传算法是一种随机、自适应、启发式的算法, 具有很好的鲁棒性和全局收敛性, 本文基于VSP直达波方程,引入了遗传算法来进行粘弹参数反演, 首先将频率域直达波方程表示为复速度的函数,然后通过遗传算法反演出复速度。而复速度和品质因子又是复速度的函数,从而便可很容易的得出。但若直接反演复速度, 反演参数太多, 不容易实现, 所以又将复速度表示成参数C0和C∞的函数,以减少反演参数数量。最后给出了理论模型实验,以证明该算法的有效性。     

Spectral characteristics of natural and artificial seismic events in the Lop Nor test site, China

Seismic discriminants based on the spectral seismogram and spectral magnitude techniques have been tested to discriminate between three events; a nuclear explosion which took place in Lop Nor, China with m _b 6.1 and two earthquakes from the closest area with m _b 5.5 and 5.3, respectively. The spectral seismogram of the three events shows that the frequency content of the nuclear explosion differs from that of the earthquakes where the P wave is richier in high frequency content in the nuclear explosion than the corresponding earthquakes. It is also observed that the energy decays more rapidly for the nuclear explosion than for the earthquakes. Furthermore, the spectral magnitudes reveal significant differences in the spectra between the nuclear explosion and the two earthquakes. The observed differences appear to be quite enough to provide a reliable discriminant. The estimated stress drop from the magnitude spectra indicates a higher stress drop of the nuclear explosion relative to the earthquakes of the same tectonic region.     

Spatial scale effect on the upper soil effective parameters of a distributed hydrological model

Nonlinear dynamics and spatial variability in hydrological systems make the formulation of scaling theories difficult. Therefore, the development of knowledge related to scale effects, scaling techniques, parameterization and linkages of parameters across scales is highly relevant. The main purpose of this work is to analyse the spatial effect of the static storage capacity parameter H_u and the saturated hydraulic conductivity parameter k_s from microscale (sub‐grid level) to mesoscale (grid level) and its implication to the definition of an optimum cell size. These two parameters describe the upper soil water characteristics in the infiltration process conceptualization of the TETIS hydrological model. At microscale, the spatial heterogeneity of H_u and k_s was obtained generating random parameter fields through probability distribution functions and a spatial dependence model with pre‐established correlation lengths. The effective parameters at mesoscale were calculated by solving the inverse problem for each parameter field. Results indicate that the adopted inverse formulation allows transferring the nonlinearity of the system from microscale to the mesoscale via non‐stationary effective parameters. Their values at each cell and time step are in the range of zero to the mean value of the parameter at microscale. The stochastic simulations showed that the variance of the estimated effective parameters decreases when the ratio between mesoscale cell size and correlation length at microscale increases. For a ratio greater than 1, we found cell sizes having the characteristics of a representative elementary area (REA); in such case, the microscale variability pattern did not affect the system response at mesoscale. Copyright © 2011 John Wiley & Sons, Ltd.     

Global sensitivity analyses for a complex hydrological model applied in an Alpine watershed

The increasing complexity of hydrological models results in a large number of parameters to be estimated. In order to better understand how these complex models work, efficient screening methods are required in order to identify the most important parameters. This is of particular importance for models that are used within an operational real‐time forecasting chain such as HQsim. The objectives of this investigation are to (i) identify the most sensitive parameters of the complex HQsim model applied in the Alpine Lech catchment and (ii) compare model parameter sensitivity rankings attained from three global sensitivity analysis techniques. The techniques presented are the (i) regional sensitivity analysis, (ii) Morris analysis and (iii) state‐dependent parameter modelling. The results indicate that parameters affecting snow melt as well as processes in the unsaturated soil zone reveal high significance in the analysed catchment. The snow melt parameters show clear temporal patterns in the sensitivity whereas most of the parameters affecting processes in the unsaturated soil zone do not vary in importance across the year. Overall, the maximum degree day factor (meltfunc_max) has been identified to play a key role within the HQsim model. Although the parameter sensitivity rankings are equivalent between methods for a number of parameters, for several key parameters differing results were obtained. An uncertainty analysis demonstrates that a parameter ranking attained from only one method is subjected to large uncertainty. Copyright © 2012 John Wiley & Sons, Ltd.