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1.
The inverse problem of parameter structure identification in a distributed parameter system remains challenging. Identifying a more complex parameter structure requires more data. There is also the problem of over-parameterization. In this study, we propose a modified Tabu search for parameter structure identification. We embed an adjoint state procedure in the search process to improve the efficiency of the Tabu search. We use Voronoi tessellation for automatic parameterization to reduce the dimension of the distributed parameter. Additionally, a coarse-fine grid technique is applied to further improve the effectiveness and efficiency of the proposed methodology. To avoid over-parameterization, at each level of parameter complexity we calculate the residual error for parameter fitting, the parameter uncertainty error and a modified Akaike Information Criterion. To demonstrate the proposed methodology, we conduct numerical experiments with synthetic data that simulate both discrete hydraulic conductivity zones and a continuous hydraulic conductivity distribution. Our results indicate that the Tabu search allied with the adjoint state method significantly improves computational efficiency and effectiveness in solving the inverse problem of parameter structure identification. 相似文献
2.
Estimating erroneous parameters in ensemble based snow data assimilation system has been given little attention in the literature. Little is known about the related methods’ effectiveness, performance, and sensitivity to other error sources such as model structural error. This research tackles these questions by running synthetic one-dimensional snow data assimilation with the ensemble Kalman filter (EnKF), in which both state and parameter are simultaneously updated. The first part of the paper investigates the effectiveness of this parameter estimation approach in a perfect-model-structure scenario, and the second part focuses on its dependence on model structure error. The results from first part research demonstrate the advantages of this parameter estimation approach in reducing the systematic error of snow water equivalent (SWE) estimates, and retrieving the correct parameter value. The second part results indicate that, at least in our experiment, there is an evident dependence of parameter search convergence on model structural error. In the imperfect-model-structure run, the parameter search diverges, although it can simulate the state variable well. This result suggest that, good data assimilation performance in estimating state variables is not a sufficient indicator of reliable parameter retrieval in the presence of model structural error. The generality of this conclusion needs to be tested by data assimilation experiments with more complex structural error configurations. 相似文献
3.
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. 相似文献
4.
This study aims at evaluating the uncertainty in the prediction of soil moisture (1D, vertical column) from an offline land surface model (LSM) forced by hydro-meteorological and radiation data. We focus on two types of uncertainty: an input error due to satellite rainfall retrieval uncertainty, and, LSM soil-parametric error. The study is facilitated by in situ and remotely sensed data-driven (precipitation, radiation, soil moisture) simulation experiments comprising a LSM and stochastic models for error characterization. The parametric uncertainty is represented by the generalized likelihood uncertainty estimation (GLUE) technique, which models the parameter non-uniqueness against direct observations. Half-hourly infra-red (IR) sensor retrievals were used as satellite rainfall estimates. The IR rain retrieval uncertainty is characterized on the basis of a satellite rainfall error model (SREM). The combined uncertainty (i.e., SREM + GLUE) is compared with the partial assessment of uncertainty. It is found that precipitation (IR) error alone may explain moderate to low proportion of the soil moisture simulation uncertainty, depending on the level of model accuracy—50–60% for high model accuracy, and 20–30% for low model accuracy. Comparisons on the basis of two different sites also yielded an increase (50–100%) in soil moisture prediction uncertainty for the more vegetated site. This study exemplified the need for detailed investigations of the rainfall retrieval-modeling parameter error interaction within a comprehensive space-time stochastic framework for achieving optimal integration of satellite rain retrievals in land data assimilation systems. 相似文献
5.
A joint strategy for parameter estimation which can systematically identify the important model parameters is presented. the strategy includes a regionalized sensitivity analysis (RSA) and an automatic parameter calibration technique (APCT). the RSA is based on a large number of Monte-Carlo simulations to identify the sensitive parameters and to establish a range of appropriate values for each sensitive parameter. the APCT adjusts the values of the sensitive parameters based on changes in the residual variances between the predicted and observed values. the strategy is applied to the watershed acidification model—ILWAS. the strategy succeeds in identifying the sensitive parameter and increases the likelihood of obtaining a global optimal parameter set. Improvements in the model prediction of the streamflow and chemistry are obtained. 相似文献
6.
B.J. Cosby A. Jenkins R.C. Ferrier J.D. Miller T.A.B. Walker 《Journal of Hydrology》1990,120(1-4):143-162
A conceptual model of the combined effects of afforestation and acidic deposition is applied to two forested sites in central Scotland. Refinements are made to the model inputs specifically to include: increased dry deposition to the forests (in excess of the dry deposition expected for moorland sites) as the forest canopy develops; uptake of ions by the growing forests; and increased evapotranspiration (and thus decreased water yield) as the forests mature. The model is calibrated using a fuzzy optimisation technique which incorporates uncertainty in target variables (stream base cation concentrations and soil exchangeable bases) and uncertainty in selecting values for fixed and adjustable parameters which describe the physico-chemical characteristics of the catchments. Simulated present-day stream and soil chemistry closely match observed values at both sites. The calibrated models indicate that while the patterns of acidification in the two catchments are broadly similar, some differences do exist between the sites in the responses of the soils to acidic deposition and afforestation. It is concluded that the calibrated models provide a tool for: (a) comparison of the relative effects of deposition and afforestation on soil and surface water acidification; (b) assessment of the likely effects of reductions in future deposition combined with future forestry management practices. 相似文献
7.
The forested Coalburn catchment (1·5 km2) in northern England experiences episodic stream acidification. To plan for sustainable management of the plantation forest cycle, an understanding is required of the flow pathways and hydrochemical routing signatures of the organic and mineral soils that make up the source areas for runoff. A tentative mixing model, based on simple water chemistry exists for the major (terrestrial) sources and buffers of acidification; it is being expanded and consolidated by a detailed approach to the organic components of runoff, via sampling and analysis of the luminescence of surface waters at the catchment outlet and in two distinctive feeder streams. Luminescence measurements are presented that permit a simple apportionment of source areas. However, the technique also appears to have potential for identifying differential flow sourcing between the acrotelm and catotelm of intact peat deposits and for clarifying the influence of forest root systems in altering the organic chemistry of infiltrating waters. Applications may include the monitoring and prediction of coloured water events for the water supply industry. Copyright © 2001 John Wiley & Sons, Ltd. 相似文献
8.
A. Jenkins B. J. Cosby R. C. Ferrier T. A. B. Walker J. D. Miller 《Journal of Hydrology》1990,120(1-4):163-181
A model of the combined long-term effects of acidic deposition and forest growth has been developed and calibrated for an upland site in Scotland. The model is used to perform a series of simulation experiments to assess the relative effects of afforestation and acidic deposition on soil and surface water chemistry. The experiments compare and contrast: (a) the simulated historical effects of increased acidic deposition and forest growth, both individually and in combination; (b) the simulated future effects of various levels of reduction of deposition in combination with the forestry strategies of harvesting with and without replanting. Results indicate that historical acidification of surface waters in areas receiving high levels of acidic deposition has been exacerbated by afforestation practices. Afforestation in the absence of acidic deposition, however, has had a lesser effect on surface water acidification even though the nutrient demands of forest growth have caused significant soil acidification. Comparisons of future forest management strategies in conjunction with likely deposition reductions indicate that, in sensitive areas, replanting of a felled forest without treatment of the soil by addition of base cations, should not be undertaken even if significant deposition reductions are realised. 相似文献
9.
Haishen Lü Xiaoli Li Zhongbo Yu Robert Horton Yonghua Zhu Zhenchun Hao Long Xiang 《水文研究》2010,24(25):3648-3660
Root zone soil water content impacts plant water availability, land energy and water balances. Because of unknown hydrological model error, observation errors and the statistical characteristics of the errors, the widely used Kalman filter (KF) and its extensions are challenged to retrieve the root zone soil water content using the surface soil water content. If the soil hydraulic parameters are poorly estimated, the KF and its extensions fail to accurately estimate the root zone soil water. The H‐infinity filter (HF) represents a robust version of the KF. The HF is widely used in data assimilation and is superior to the KF, especially when the performance of the model is not well understood. The objective of this study is to study the impact of uncertain soil hydraulic parameters, initial soil moisture content and observation period on the ability of HF assimilation to predict in situ soil water content. In this article, we study seven cases. The results show that the soil hydraulic parameters hold a critical role in the course of assimilation. When the soil hydraulic parameters are poorly estimated, an accurate estimation of root soil water content cannot be retrieved by the HF assimilation approach. When the estimated soil hydraulic parameters are similar to actual values, the soil water content at various depths can be accurately retrieved by the HF assimilation. The HF assimilation is not very sensitive to the initial soil water content, and the impact of the initial soil water content on the assimilation scheme can be eliminated after about 5–7 days. The observation interval is important for soil water profile distribution retrieval with the HF, and the shorter the observation interval, the shorter the time required to achieve actual soil water content. However, the retrieval results are not very accurate at a depth of 100 cm. Also it is complex to determine the weighting coefficient and the error attenuation parameter in the HF assimilation. In this article, the trial‐and‐error method was used to determine the weighting coefficient and the error attenuation parameter. After the first establishment of limited range of the parameters, ‘the best parameter set’ was selected from the range of values. For the soil conditions investigated, the HF assimilation results are better than the open‐loop results. Copyright © 2010 John Wiley & Sons, Ltd. 相似文献
10.
John E. Lane Takis Kasparis Philip T. Metzger W. Linwood Jones 《Acta Geophysica》2014,62(6):1450-1477
In situ calibration is a proposed strategy for continuous as well as initial calibration of an impact disdrometer. In previous work, a collocated tipping bucket had been utilized to provide a rainfall rate based ～11/3 moment reference to an impact disdrometer’s signal processing system for implementation of adaptive calibration. Using rainfall rate only, transformation of impulse amplitude to a drop volume based on a simple power law was used to define an error surface in the model’s parameter space. By incorporating optical extinction second moment measurements with rainfall rate data, an improved in situ disdrometer calibration algorithm results due to utilization of multiple (two or more) independent moments of the drop size distribution in the error function definition. The resulting improvement in calibration performance can be quantified by detailed examination of the parameter space error surface using simulation as well as real data. 相似文献
11.
Data assimilation for distributed hydrological catchment modeling via ensemble Kalman filter 总被引：4，自引：0，他引：4
Catchment scale hydrological models are critical decision support tools for water resources management and environment remediation. However, the reliability of hydrological models is inevitably affected by limited measurements and imperfect models. Data assimilation techniques combine complementary information from measurements and models to enhance the model reliability and reduce predictive uncertainties. As a sequential data assimilation technique, the ensemble Kalman filter (EnKF) has been extensively studied in the earth sciences for assimilating in-situ measurements and remote sensing data. Although the EnKF has been demonstrated in land surface data assimilations, there are no systematic studies to investigate its performance in distributed modeling with high dimensional states and parameters. In this paper, we present an assessment on the EnKF with state augmentation for combined state-parameter estimation on the basis of a physical-based hydrological model, Soil and Water Assessment Tool (SWAT). Through synthetic simulation experiments, the capability of the EnKF is demonstrated by assimilating the runoff and other measurements, and its sensitivities are analyzed with respect to the error specification, the initial realization and the ensemble size. It is found that the EnKF provides an efficient approach for obtaining a set of acceptable model parameters and satisfactory runoff, soil water content and evapotranspiration estimations. The EnKF performance could be improved after augmenting with other complementary data, such as soil water content and evapotranspiration from remote sensing retrieval. Sensitivity studies demonstrate the importance of consistent error specification and the potential with small ensemble size in the data assimilation system. 相似文献
12.
Non‐linear structural identification problems have raised considerable research efforts since decades, in which the Bouc–Wen model is generally utilized to simulate non‐linear structural constitutive characteristic. Support vector regression (SVR), a promising data processing method, is studied for versatile‐typed structural identification. First, a model selection strategy is utilized to determine the unknown power parameter of the Bouc–Wen model. Meanwhile, optimum SVR parameters are selected automatically, instead of tuning manually. Consequently, the non‐linear structural equation is rewritten in linear form, and is solved by the SVR technique. A five‐floor versatile‐type structure is studied to show the effectiveness of the proposed method, in which both power parameter known and unknown cases are investigated. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
13.
14.
Several recent studies have shown the significance of representing groundwater in land surface hydrologic simulations. However, optimal methods for model parameter calibration in order to realistically simulate baseflow and groundwater depth have received little attention. Most studies still use globally constant groundwater parameters due to the lack of available datasets for calibration. Moreover, when models are calibrated, various parameter combinations are found to exhibit equifinality in simulated total runoff due to model parameter interactions. In this study, a simple lumped groundwater model is incorporated into the Community Land Model (CLM), in which the water table is interactively coupled to soil moisture through the groundwater recharge fluxes. The coupled model (CLMGW) is successfully validated in Illinois using a 22-year (1984–2005) monthly observational dataset. Baseflow estimates from the digital recursive filter technique are used to calibrate the CLMGW parameters. The advantage obtained from incorporating baseflow calibration in addition to traditional calibration based on measured streamflow alone is demonstrated by a Monte Carlo-type simulation analysis. Using the optimal parameter sets identified from baseflow calibration, flow partitioning and water table depth simulations using CLMGW are improved, and the equifinality problem is alleviated. For other regions that lack observations of water table depth, the baseflow calibration approach can be used to enhance parameter estimation and constrain water table depth simulations. 相似文献
15.
Calibration is typically used for improving the predictability of mechanistic simulation models by adjusting a set of model parameters and fitting model predictions to observations. Calibration does not, however, account for or correct potential misspecifications in the model structure, limiting the accuracy of modeled predictions. This paper presents a new approach that addresses both parameter error and model structural error to improve the predictive capabilities of a model. The new approach simultaneously conducts a numeric search for model parameter estimation and a symbolic (regression) search to determine a function to correct misspecifications in model equations. It is based on an evolutionary computation approach that integrates genetic algorithm and genetic programming operators. While this new approach is designed generically and can be applied to a broad array of mechanistic models, it is demonstrated for an illustrative case study involving water quality modeling and prediction. Results based on extensive testing and evaluation, show that the new procedure performs consistently well in fitting a set of training data as well as predicting a set of validation data, and outperforms a calibration procedure and an empirical model fitting procedure. 相似文献
16.
The hydrological sensitivities to long-term climate change of a watershed in Eastern Canada were analysed using a deterministic watershed runoff model developed to simulate watershed acidification. This model was modified to study atmospheric change effects in the watershed. Water balance modelling techniques, modified for assessing climate effects, were developed and tested for a watershed using atmospheric change scenarios from both state of the art general circulation models and a series of hypothetical scenarios. The model computed daily surface, inter- and groundwater flows from the watershed. The moisture, infiltration and recharge rate are also computed in the soil reservoirs. The thirty years of simulated data can be used to evaluate the effects of climatic change on soil moisture, recharge rate and surface and subsurface flow systems. The interaction between surface and subsurface water is discussed in relation to climate change. These hydrological results raise the possibility of major environmental and socioeconomic difficulties and have significant implications for future water resource planning and management. © 1997 John Wiley & Sons, Ltd. 相似文献
17.
Sea surface temperature (SST) from a near real-time data set produced from satellites data has been assimilated into a coupled
ice–ocean forecasting model (Canadian East Coast Ocean Model) using an efficient data assimilation method. The method is based
on an optimal interpolation scheme by which SST is melded into the model through the adjustment of surface heat flux. The
magnitude and space–time variation of the adjustment depend on the depth of heat diffusion into the water column in response
to changes in surface flux, the correlation time scale of the data, and model and data errors. The diffusion depth is scaled
by the eddy diffusivity for temperature. The ratio of the model and data errors is treated as an adjustable parameter. To
evaluate the quality of the assimilation, the results from the model with and without assimilation are compared to independent
ship data from the Atlantic Zone Monitoring Program and the World Ocean Circulation Experiment. It is shown that the assimilation
has a significant impact on the modeled SST, reducing the root mean square difference (RMSD) between the model SST and the
ship SST by 0.63°C or 37%. The RMSD of the assimilated SST is smaller than that of the satellite SST by 0.23°C. This suggests
that model simulations or predictions with data assimilation can provide the best estimate of the true SST. A sensitivity
study is performed to examine the change of the model RMSD with the adjustable parameter in the assimilation equation. The
results show that there is an optimal value of the parameter and the model SST is not very sensitive to the parameter. 相似文献
18.
The main objective of this study was to use an uncertainty version of a widely used monthly time step, semi-distributed model (the Pitman model) to explore the equifinalities in the way in which the main hydrological processes are simulated and any identifiable linkages with uncertainties in the available observational data. The study area is the Zambezi River basin and 17 gauged sub-basins have been included in the analyses. Unfortunately, it is not generally possible to quantify some of the observational uncertainties in such a data scarce area and mostly we are limited to identifying where these data are clearly deficient (i.e., erroneous or non-representative). The overall conclusion is that the equifinalities in the model are hugely dominant in terms of the uncertainties in the relative occurrence of different runoff generating processes, although water use uncertainties in the semi-arid parts of the basin can contribute to these uncertainties. The identification of landscape features that suggest the occurrence of saturation excess surface runoff provides some information to constrain the model. Improved independent estimates of groundwater recharge is also identified as a key source of observational data that would help a great deal in constraining the model parameter space and therefore reducing some of the model equifinality. 相似文献
19.
Gregoire Broquet Pierre Brasseur David Rozier Jean-Michel Brankart Jacques Verron 《Ocean Dynamics》2008,58(1):1-17
The characterization of model errors is an essential step for effective data assimilation into open-ocean and shelf-seas models.
In this paper, we propose an experimental protocol to properly estimate the error statistics generated by imperfect atmospheric
forcings in a regional model of the Bay of Biscay, nested in a basin-scale North Atlantic configuration. The model used is
the Hybrid Coordinate Ocean Model (HYCOM), and the experimental protocol involves Monte Carlo (or ensemble) simulations. The
spatial structure of the model error is analyzed using the representer technique, which allows us to anticipate the subsequent
impact in data assimilation systems. The results show that the error is essentially anisotropic and inhomogeneous, affecting
mainly the model layers close to the surface. Even when the forcings errors are centered around zero, a divergence is observed
between the central forecast and the mean forecast of the Monte Carlo simulations as a result of nonlinearities. The 3D structure
of the representers characterizes the capacity of different types of measurement (sea level, sea surface temperature, surface
velocities, subsurface temperature, and salinity) to control the circulation. Finally, data assimilation experiments demonstrate
the superiority of the proposed methodology for the implementation of reduced-order Kalman filters. 相似文献
20.
This study proposes an inverse solution algorithm through which both the aquifer parameters and the zone structure of these parameters can be determined based on a given set of observations on piezometric heads. In the zone structure identification problem fuzzy c-means (FCM) clustering method is used. The association of the zone structure with the transmissivity distribution is accomplished through an optimization model. The meta-heuristic harmony search (HS) algorithm, which is conceptualized using the musical process of searching for a perfect state of harmony, is used as an optimization technique. The optimum parameter zone structure is identified based on three criteria which are the residual error, parameter uncertainty, and structure discrimination. A numerical example given in the literature is solved to demonstrate the performance of the proposed algorithm. Also, a sensitivity analysis is performed to test the performance of the HS algorithm for different sets of solution parameters. Results indicate that the proposed solution algorithm is an effective way in the simultaneous identification of aquifer parameters and their corresponding zone structures. 相似文献