Nitrous oxide emissions from cropland: a procedure for calibrating the DayCent biogeochemical model using inverse modelling

USGS Publications Warehouse

Rafique, Rashad; Fienen, Michael N.; Parkin, Timothy B.; Anex, Robert P.

2013-01-01

DayCent is a biogeochemical model of intermediate complexity widely used to simulate greenhouse gases (GHG), soil organic carbon and nutrients in crop, grassland, forest and savannah ecosystems. Although this model has been applied to a wide range of ecosystems, it is still typically parameterized through a traditional “trial and error” approach and has not been calibrated using statistical inverse modelling (i.e. algorithmic parameter estimation). The aim of this study is to establish and demonstrate a procedure for calibration of DayCent to improve estimation of GHG emissions. We coupled DayCent with the parameter estimation (PEST) software for inverse modelling. The PEST software can be used for calibration through regularized inversion as well as model sensitivity and uncertainty analysis. The DayCent model was analysed and calibrated using N2O flux data collected over 2 years at the Iowa State University Agronomy and Agricultural Engineering Research Farms, Boone, IA. Crop year 2003 data were used for model calibration and 2004 data were used for validation. The optimization of DayCent model parameters using PEST significantly reduced model residuals relative to the default DayCent parameter values. Parameter estimation improved the model performance by reducing the sum of weighted squared residual difference between measured and modelled outputs by up to 67 %. For the calibration period, simulation with the default model parameter values underestimated mean daily N2O flux by 98 %. After parameter estimation, the model underestimated the mean daily fluxes by 35 %. During the validation period, the calibrated model reduced sum of weighted squared residuals by 20 % relative to the default simulation. Sensitivity analysis performed provides important insights into the model structure providing guidance for model improvement.

Hand-Eye Calibration in Visually-Guided Robot Grinding.

PubMed

Li, Wen-Long; Xie, He; Zhang, Gang; Yan, Si-Jie; Yin, Zhou-Ping

2016-11-01

Visually-guided robot grinding is a novel and promising automation technique for blade manufacturing. One common problem encountered in robot grinding is hand-eye calibration, which establishes the pose relationship between the end effector (hand) and the scanning sensor (eye). This paper proposes a new calibration approach for robot belt grinding. The main contribution of this paper is its consideration of both joint parameter errors and pose parameter errors in a hand-eye calibration equation. The objective function of the hand-eye calibration is built and solved, from which 30 compensated values (corresponding to 24 joint parameters and six pose parameters) are easily calculated in a closed solution. The proposed approach is economic and simple because only a criterion sphere is used to calculate the calibration parameters, avoiding the need for an expensive and complicated tracking process using a laser tracker. The effectiveness of this method is verified using a calibration experiment and a blade grinding experiment. The code used in this approach is attached in the Appendix.

PLS-NIR determination of five parameters in different types of Chinese rice wine

NASA Astrophysics Data System (ADS)

Yu, Haiyan; Ying, Yibin; Fu, Xiaping; Lu, Huishan

2005-11-01

To evaluate the applicability of near infrared spectroscopy for determination of the five enological parameters (alcoholic degree, pH value, total acid and amino acid nitrogen, °Brix) of Chinese rice wine, transmission spectra were collected in the spectral range from 12500 to 3800 cm-1 in a 1 mm path length rectangular quartz cuvette with air as reference at room temperature. Five calibration equations for the five parameters were established between the reference data and spectra by partial least squares (PLS) regression, separately. The best calibration results were achieved for the determination of alcoholic degree and °Brix. The RPD (ration of the standard deviation of the samples to the SECV) values of the calibration for both alcoholic degree and °Brix were higher than 3 (4.30 and 7.94, respectively), which demonstrated the robustness and power of the calibration models. The determination coefficients (R2) for alcoholic degree and °Brix were 0.987 and 0.991, respectively. The performance of pH, total acid and amino acid nitrogen was not as good as that of alcoholic degree and °Brix. The RPD values for the three parameters were 1.48, 1.85 and 1.82, respectively, and R2 values were 0.964, 0.970 and 0.971, respectively. In validation step, R2 value of the five parameters are all higher than 0.7, especially for alcoholic degree and °Brix (0.968 and 0.956, respectively). The results demonstrated that NIR spectroscopy could be used to predict the concentration of the five enological parameters in Chinese rice wine.

ON THE CALIBRATION OF DK-02 AND KID DOSIMETERS (in Estonian)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ehvaert, H.

1963-01-01

For the periodic calibration of the DK-02 and WD dosimeters, the rotating stand method which is more advantageous than the usual method is recommended. The calibration can be accomplished in a strong gamma field, reducing considerably the time necessary for calibration. Using a point source, the dose becomes a simple function of time and geometrical parameters. The experimental values are in good agreement with theoretical values. (tr-auth)

Using HEC-HMS: Application to Karkheh river basin

USDA-ARS?s Scientific Manuscript database

This paper aims to facilitate the use of HEC-HMS model using a systematic event-based technique for manual calibration of soil moisture accounting and snowmelt degree-day parameters. Manual calibration, which helps ensure the HEC-HMS parameter values are physically-relevant, is often a time-consumin...

Parameter regionalization of a monthly water balance model for the conterminous United States

USGS Publications Warehouse

Bock, Andrew R.; Hay, Lauren E.; McCabe, Gregory J.; Markstrom, Steven L.; Atkinson, R. Dwight

2016-01-01

A parameter regionalization scheme to transfer parameter values from gaged to ungaged areas for a monthly water balance model (MWBM) was developed and tested for the conterminous United States (CONUS). The Fourier Amplitude Sensitivity Test, a global-sensitivity algorithm, was implemented on a MWBM to generate parameter sensitivities on a set of 109 951 hydrologic response units (HRUs) across the CONUS. The HRUs were grouped into 110 calibration regions based on similar parameter sensitivities. Subsequently, measured runoff from 1575 streamgages within the calibration regions were used to calibrate the MWBM parameters to produce parameter sets for each calibration region. Measured and simulated runoff at the 1575 streamgages showed good correspondence for the majority of the CONUS, with a median computed Nash–Sutcliffe efficiency coefficient of 0.76 over all streamgages. These methods maximize the use of available runoff information, resulting in a calibrated CONUS-wide application of the MWBM suitable for providing estimates of water availability at the HRU resolution for both gaged and ungaged areas of the CONUS.

Parameter regionalization of a monthly water balance model for the conterminous United States

NASA Astrophysics Data System (ADS)

Bock, Andrew R.; Hay, Lauren E.; McCabe, Gregory J.; Markstrom, Steven L.; Atkinson, R. Dwight

2016-07-01

A parameter regionalization scheme to transfer parameter values from gaged to ungaged areas for a monthly water balance model (MWBM) was developed and tested for the conterminous United States (CONUS). The Fourier Amplitude Sensitivity Test, a global-sensitivity algorithm, was implemented on a MWBM to generate parameter sensitivities on a set of 109 951 hydrologic response units (HRUs) across the CONUS. The HRUs were grouped into 110 calibration regions based on similar parameter sensitivities. Subsequently, measured runoff from 1575 streamgages within the calibration regions were used to calibrate the MWBM parameters to produce parameter sets for each calibration region. Measured and simulated runoff at the 1575 streamgages showed good correspondence for the majority of the CONUS, with a median computed Nash-Sutcliffe efficiency coefficient of 0.76 over all streamgages. These methods maximize the use of available runoff information, resulting in a calibrated CONUS-wide application of the MWBM suitable for providing estimates of water availability at the HRU resolution for both gaged and ungaged areas of the CONUS.

Calibration process of highly parameterized semi-distributed hydrological model

NASA Astrophysics Data System (ADS)

Vidmar, Andrej; Brilly, Mitja

2017-04-01

Hydrological phenomena take place in the hydrological system, which is governed by nature, and are essentially stochastic. These phenomena are unique, non-recurring, and changeable across space and time. Since any river basin with its own natural characteristics and any hydrological event therein, are unique, this is a complex process that is not researched enough. Calibration is a procedure of determining the parameters of a model that are not known well enough. Input and output variables and mathematical model expressions are known, while only some parameters are unknown, which are determined by calibrating the model. The software used for hydrological modelling nowadays is equipped with sophisticated algorithms for calibration purposes without possibility to manage process by modeler. The results are not the best. We develop procedure for expert driven process of calibration. We use HBV-light-CLI hydrological model which has command line interface and coupling it with PEST. PEST is parameter estimation tool which is used widely in ground water modeling and can be used also on surface waters. Process of calibration managed by expert directly, and proportionally to the expert knowledge, affects the outcome of the inversion procedure and achieves better results than if the procedure had been left to the selected optimization algorithm. First step is to properly define spatial characteristic and structural design of semi-distributed model including all morphological and hydrological phenomena, like karstic area, alluvial area and forest area. This step includes and requires geological, meteorological, hydraulic and hydrological knowledge of modeler. Second step is to set initial parameter values at their preferred values based on expert knowledge. In this step we also define all parameter and observation groups. Peak data are essential in process of calibration if we are mainly interested in flood events. Each Sub Catchment in the model has own observations group. Third step is to set appropriate bounds to parameters in their range of realistic values. Fourth step is to use of singular value decomposition (SVD) ensures that PEST maintains numerical stability, regardless of how ill-posed is the inverse problem Fifth step is to run PWTADJ1. This creates a new PEST control file in which weights are adjusted such that the contribution made to the total objective function by each observation group is the same. This prevents the information content of any group from being invisible to the inversion process. Sixth step is to add Tikhonov regularization to the PEST control file by running the ADDREG1 utility (Doherty, J, 2013). In adding regularization to the PEST control file ADDREG1 automatically provides a prior information equation for each parameter in which the preferred value of that parameter is equated to its initial value. Last step is to run PEST. We run BeoPEST which a parallel version of PEST and can be run on multiple computers in parallel in same time on TCP communications and this speedup process of calibrations. The case study with results of calibration and validation of the model will be presented.

An Open-Source Auto-Calibration Routine Supporting the Stormwater Management Model

NASA Astrophysics Data System (ADS)

Tiernan, E. D.; Hodges, B. R.

2017-12-01

The stormwater management model (SWMM) is a clustered model that relies on subcatchment-averaged parameter assignments to correctly capture catchment stormwater runoff behavior. Model calibration is considered a critical step for SWMM performance, an arduous task that most stormwater management designers undertake manually. This research presents an open-source, automated calibration routine that increases the efficiency and accuracy of the model calibration process. The routine makes use of a preliminary sensitivity analysis to reduce the dimensions of the parameter space, at which point a multi-objective function, genetic algorithm (modified Non-dominated Sorting Genetic Algorithm II) determines the Pareto front for the objective functions within the parameter space. The solutions on this Pareto front represent the optimized parameter value sets for the catchment behavior that could not have been reasonably obtained through manual calibration.

Muscle Synergies May Improve Optimization Prediction of Knee Contact Forces During Walking

PubMed Central

Walter, Jonathan P.; Kinney, Allison L.; Banks, Scott A.; D'Lima, Darryl D.; Besier, Thor F.; Lloyd, David G.; Fregly, Benjamin J.

2014-01-01

The ability to predict patient-specific joint contact and muscle forces accurately could improve the treatment of walking-related disorders. Muscle synergy analysis, which decomposes a large number of muscle electromyographic (EMG) signals into a small number of synergy control signals, could reduce the dimensionality and thus redundancy of the muscle and contact force prediction process. This study investigated whether use of subject-specific synergy controls can improve optimization prediction of knee contact forces during walking. To generate the predictions, we performed mixed dynamic muscle force optimizations (i.e., inverse skeletal dynamics with forward muscle activation and contraction dynamics) using data collected from a subject implanted with a force-measuring knee replacement. Twelve optimization problems (three cases with four subcases each) that minimized the sum of squares of muscle excitations were formulated to investigate how synergy controls affect knee contact force predictions. The three cases were: (1) Calibrate+Match where muscle model parameter values were calibrated and experimental knee contact forces were simultaneously matched, (2) Precalibrate+Predict where experimental knee contact forces were predicted using precalibrated muscle model parameters values from the first case, and (3) Calibrate+Predict where muscle model parameter values were calibrated and experimental knee contact forces were simultaneously predicted, all while matching inverse dynamic loads at the hip, knee, and ankle. The four subcases used either 44 independent controls or five synergy controls with and without EMG shape tracking. For the Calibrate+Match case, all four subcases closely reproduced the measured medial and lateral knee contact forces (R2 ≥ 0.94, root-mean-square (RMS) error < 66 N), indicating sufficient model fidelity for contact force prediction. For the Precalibrate+Predict and Calibrate+Predict cases, synergy controls yielded better contact force predictions (0.61 < R2 < 0.90, 83 N < RMS error < 161 N) than did independent controls (-0.15 < R2 < 0.79, 124 N < RMS error < 343 N) for corresponding subcases. For independent controls, contact force predictions improved when precalibrated model parameter values or EMG shape tracking was used. For synergy controls, contact force predictions were relatively insensitive to how model parameter values were calibrated, while EMG shape tracking made lateral (but not medial) contact force predictions worse. For the subject and optimization cost function analyzed in this study, use of subject-specific synergy controls improved the accuracy of knee contact force predictions, especially for lateral contact force when EMG shape tracking was omitted, and reduced prediction sensitivity to uncertainties in muscle model parameter values. PMID:24402438

Muscle synergies may improve optimization prediction of knee contact forces during walking.

PubMed

Walter, Jonathan P; Kinney, Allison L; Banks, Scott A; D'Lima, Darryl D; Besier, Thor F; Lloyd, David G; Fregly, Benjamin J

2014-02-01

The ability to predict patient-specific joint contact and muscle forces accurately could improve the treatment of walking-related disorders. Muscle synergy analysis, which decomposes a large number of muscle electromyographic (EMG) signals into a small number of synergy control signals, could reduce the dimensionality and thus redundancy of the muscle and contact force prediction process. This study investigated whether use of subject-specific synergy controls can improve optimization prediction of knee contact forces during walking. To generate the predictions, we performed mixed dynamic muscle force optimizations (i.e., inverse skeletal dynamics with forward muscle activation and contraction dynamics) using data collected from a subject implanted with a force-measuring knee replacement. Twelve optimization problems (three cases with four subcases each) that minimized the sum of squares of muscle excitations were formulated to investigate how synergy controls affect knee contact force predictions. The three cases were: (1) Calibrate+Match where muscle model parameter values were calibrated and experimental knee contact forces were simultaneously matched, (2) Precalibrate+Predict where experimental knee contact forces were predicted using precalibrated muscle model parameters values from the first case, and (3) Calibrate+Predict where muscle model parameter values were calibrated and experimental knee contact forces were simultaneously predicted, all while matching inverse dynamic loads at the hip, knee, and ankle. The four subcases used either 44 independent controls or five synergy controls with and without EMG shape tracking. For the Calibrate+Match case, all four subcases closely reproduced the measured medial and lateral knee contact forces (R2 ≥ 0.94, root-mean-square (RMS) error < 66 N), indicating sufficient model fidelity for contact force prediction. For the Precalibrate+Predict and Calibrate+Predict cases, synergy controls yielded better contact force predictions (0.61 < R2 < 0.90, 83 N < RMS error < 161 N) than did independent controls (-0.15 < R2 < 0.79, 124 N < RMS error < 343 N) for corresponding subcases. For independent controls, contact force predictions improved when precalibrated model parameter values or EMG shape tracking was used. For synergy controls, contact force predictions were relatively insensitive to how model parameter values were calibrated, while EMG shape tracking made lateral (but not medial) contact force predictions worse. For the subject and optimization cost function analyzed in this study, use of subject-specific synergy controls improved the accuracy of knee contact force predictions, especially for lateral contact force when EMG shape tracking was omitted, and reduced prediction sensitivity to uncertainties in muscle model parameter values.

Calibration of infiltration parameters on hydrological tank model using runoff coefficient of rational method

NASA Astrophysics Data System (ADS)

Suryoputro, Nugroho; Suhardjono, Soetopo, Widandi; Suhartanto, Ery

2017-09-01

In calibrating hydrological models, there are generally two stages of activity: 1) determining realistic model initial parameters in representing natural component physical processes, 2) entering initial parameter values which are then processed by trial error or automatically to obtain optimal values. To determine a realistic initial value, it takes experience and user knowledge of the model. This is a problem for beginner model users. This paper will present another approach to estimate the infiltration parameters in the tank model. The parameters will be approximated by the runoff coefficient of rational method. The value approach of infiltration parameter is simply described as the result of the difference in the percentage of total rainfall minus the percentage of runoff. It is expected that the results of this research will accelerate the calibration process of tank model parameters. The research was conducted on the sub-watershed Kali Bango in Malang Regency with an area of 239,71 km2. Infiltration measurements were carried out in January 2017 to March 2017. Analysis of soil samples at Soil Physics Laboratory, Department of Soil Science, Faculty of Agriculture, Universitas Brawijaya. Rainfall and discharge data were obtained from UPT PSAWS Bango Gedangan in Malang. Temperature, evaporation, relative humidity, wind speed data was obtained from BMKG station of Karang Ploso, Malang. The results showed that the infiltration coefficient at the top tank outlet can be determined its initial value by using the approach of the coefficient of runoff rational method with good result.

Auto-calibration of a one-dimensional hydrodynamic-ecological model using a Monte Carlo approach: simulation of hypoxic events in a polymictic lake

NASA Astrophysics Data System (ADS)

Luo, L.

2011-12-01

Automated calibration of complex deterministic water quality models with a large number of biogeochemical parameters can reduce time-consuming iterative simulations involving empirical judgements of model fit. We undertook auto-calibration of the one-dimensional hydrodynamic-ecological lake model DYRESM-CAEDYM, using a Monte Carlo sampling (MCS) method, in order to test the applicability of this procedure for shallow, polymictic Lake Rotorua (New Zealand). The calibration procedure involved independently minimising the root-mean-square-error (RMSE), maximizing the Pearson correlation coefficient (r) and Nash-Sutcliffe efficient coefficient (Nr) for comparisons of model state variables against measured data. An assigned number of parameter permutations was used for 10,000 simulation iterations. The 'optimal' temperature calibration produced a RMSE of 0.54 °C, Nr-value of 0.99 and r-value of 0.98 through the whole water column based on comparisons with 540 observed water temperatures collected between 13 July 2007 - 13 January 2009. The modeled bottom dissolved oxygen concentration (20.5 m below surface) was compared with 467 available observations. The calculated RMSE of the simulations compared with the measurements was 1.78 mg L-1, the Nr-value was 0.75 and the r-value was 0.87. The autocalibrated model was further tested for an independent data set by simulating bottom-water hypoxia events for the period 15 January 2009 to 8 June 2011 (875 days). This verification produced an accurate simulation of five hypoxic events corresponding to DO < 2 mg L-1 during summer of 2009-2011. The RMSE was 2.07 mg L-1, Nr-value 0.62 and r-value of 0.81, based on the available data set of 738 days. The auto-calibration software of DYRESM-CAEDYM developed here is substantially less time-consuming and more efficient in parameter optimisation than traditional manual calibration which has been the standard tool practiced for similar complex water quality models.

Calibration of groundwater vulnerability mapping using the generalized reduced gradient method.

PubMed

Elçi, Alper

2017-12-01

Groundwater vulnerability assessment studies are essential in water resources management. Overlay-and-index methods such as DRASTIC are widely used for mapping of groundwater vulnerability, however, these methods mainly suffer from a subjective selection of model parameters. The objective of this study is to introduce a calibration procedure that results in a more accurate assessment of groundwater vulnerability. The improvement of the assessment is formulated as a parameter optimization problem using an objective function that is based on the correlation between actual groundwater contamination and vulnerability index values. The non-linear optimization problem is solved with the generalized-reduced-gradient (GRG) method, which is numerical algorithm based optimization method. To demonstrate the applicability of the procedure, a vulnerability map for the Tahtali stream basin is calibrated using nitrate concentration data. The calibration procedure is easy to implement and aims the maximization of correlation between observed pollutant concentrations and groundwater vulnerability index values. The influence of each vulnerability parameter in the calculation of the vulnerability index is assessed by performing a single-parameter sensitivity analysis. Results of the sensitivity analysis show that all factors are effective on the final vulnerability index. Calibration of the vulnerability map improves the correlation between index values and measured nitrate concentrations by 19%. The regression coefficient increases from 0.280 to 0.485. It is evident that the spatial distribution and the proportions of vulnerability class areas are significantly altered with the calibration process. Although the applicability of the calibration method is demonstrated on the DRASTIC model, the applicability of the approach is not specific to a certain model and can also be easily applied to other overlay-and-index methods. Copyright © 2017 Elsevier B.V. All rights reserved.

Calibration of groundwater vulnerability mapping using the generalized reduced gradient method

NASA Astrophysics Data System (ADS)

Elçi, Alper

2017-12-01

Groundwater vulnerability assessment studies are essential in water resources management. Overlay-and-index methods such as DRASTIC are widely used for mapping of groundwater vulnerability, however, these methods mainly suffer from a subjective selection of model parameters. The objective of this study is to introduce a calibration procedure that results in a more accurate assessment of groundwater vulnerability. The improvement of the assessment is formulated as a parameter optimization problem using an objective function that is based on the correlation between actual groundwater contamination and vulnerability index values. The non-linear optimization problem is solved with the generalized-reduced-gradient (GRG) method, which is numerical algorithm based optimization method. To demonstrate the applicability of the procedure, a vulnerability map for the Tahtali stream basin is calibrated using nitrate concentration data. The calibration procedure is easy to implement and aims the maximization of correlation between observed pollutant concentrations and groundwater vulnerability index values. The influence of each vulnerability parameter in the calculation of the vulnerability index is assessed by performing a single-parameter sensitivity analysis. Results of the sensitivity analysis show that all factors are effective on the final vulnerability index. Calibration of the vulnerability map improves the correlation between index values and measured nitrate concentrations by 19%. The regression coefficient increases from 0.280 to 0.485. It is evident that the spatial distribution and the proportions of vulnerability class areas are significantly altered with the calibration process. Although the applicability of the calibration method is demonstrated on the DRASTIC model, the applicability of the approach is not specific to a certain model and can also be easily applied to other overlay-and-index methods.

Neuromusculoskeletal Model Calibration Significantly Affects Predicted Knee Contact Forces for Walking

PubMed Central

Serrancolí, Gil; Kinney, Allison L.; Fregly, Benjamin J.; Font-Llagunes, Josep M.

2016-01-01

Though walking impairments are prevalent in society, clinical treatments are often ineffective at restoring lost function. For this reason, researchers have begun to explore the use of patient-specific computational walking models to develop more effective treatments. However, the accuracy with which models can predict internal body forces in muscles and across joints depends on how well relevant model parameter values can be calibrated for the patient. This study investigated how knowledge of internal knee contact forces affects calibration of neuromusculoskeletal model parameter values and subsequent prediction of internal knee contact and leg muscle forces during walking. Model calibration was performed using a novel two-level optimization procedure applied to six normal walking trials from the Fourth Grand Challenge Competition to Predict In Vivo Knee Loads. The outer-level optimization adjusted time-invariant model parameter values to minimize passive muscle forces, reserve actuator moments, and model parameter value changes with (Approach A) and without (Approach B) tracking of experimental knee contact forces. Using the current guess for model parameter values but no knee contact force information, the inner-level optimization predicted time-varying muscle activations that were close to experimental muscle synergy patterns and consistent with the experimental inverse dynamic loads (both approaches). For all the six gait trials, Approach A predicted knee contact forces with high accuracy for both compartments (average correlation coefficient r = 0.99 and root mean square error (RMSE) = 52.6 N medial; average r = 0.95 and RMSE = 56.6 N lateral). In contrast, Approach B overpredicted contact force magnitude for both compartments (average RMSE = 323 N medial and 348 N lateral) and poorly matched contact force shape for the lateral compartment (average r = 0.90 medial and −0.10 lateral). Approach B had statistically higher lateral muscle forces and lateral optimal muscle fiber lengths but lower medial, central, and lateral normalized muscle fiber lengths compared to Approach A. These findings suggest that poorly calibrated model parameter values may be a major factor limiting the ability of neuromusculoskeletal models to predict knee contact and leg muscle forces accurately for walking. PMID:27210105

Global Sensitivity Analysis and Parameter Calibration for an Ecosystem Carbon Model

NASA Astrophysics Data System (ADS)

Safta, C.; Ricciuto, D. M.; Sargsyan, K.; Najm, H. N.; Debusschere, B.; Thornton, P. E.

2013-12-01

We present uncertainty quantification results for a process-based ecosystem carbon model. The model employs 18 parameters and is driven by meteorological data corresponding to years 1992-2006 at the Harvard Forest site. Daily Net Ecosystem Exchange (NEE) observations were available to calibrate the model parameters and test the performance of the model. Posterior distributions show good predictive capabilities for the calibrated model. A global sensitivity analysis was first performed to determine the important model parameters based on their contribution to the variance of NEE. We then proceed to calibrate the model parameters in a Bayesian framework. The daily discrepancies between measured and predicted NEE values were modeled as independent and identically distributed Gaussians with prescribed daily variance according to the recorded instrument error. All model parameters were assumed to have uninformative priors with bounds set according to expert opinion. The global sensitivity results show that the rate of leaf fall (LEAFALL) is responsible for approximately 25% of the total variance in the average NEE for 1992-2005. A set of 4 other parameters, Nitrogen use efficiency (NUE), base rate for maintenance respiration (BR_MR), growth respiration fraction (RG_FRAC), and allocation to plant stem pool (ASTEM) contribute between 5% and 12% to the variance in average NEE, while the rest of the parameters have smaller contributions. The posterior distributions, sampled with a Markov Chain Monte Carlo algorithm, exhibit significant correlations between model parameters. However LEAFALL, the most important parameter for the average NEE, is not informed by the observational data, while less important parameters show significant updates between their prior and posterior densities. The Fisher information matrix values, indicating which parameters are most informed by the experimental observations, are examined to augment the comparison between the calibration and global sensitivity analysis results.

Calibration of HEC-Ras hydrodynamic model using gauged discharge data and flood inundation maps

NASA Astrophysics Data System (ADS)

Tong, Rui; Komma, Jürgen

2017-04-01

The estimation of flood is essential for disaster alleviation. Hydrodynamic models are implemented to predict the occurrence and variance of flood in different scales. In practice, the calibration of hydrodynamic models aims to search the best possible parameters for the representation the natural flow resistance. Recent years have seen the calibration of hydrodynamic models being more actual and faster following the advance of earth observation products and computer based optimization techniques. In this study, the Hydrologic Engineering River Analysis System (HEC-Ras) model was set up with high-resolution digital elevation model from Laser scanner for the river Inn in Tyrol, Austria. 10 largest flood events from 19 hourly discharge gauges and flood inundation maps were selected to calibrate the HEC-Ras model. Manning roughness values and lateral inflow factors as parameters were automatically optimized with the Shuffled complex with Principal component analysis (SP-UCI) algorithm developed from the Shuffled Complex Evolution (SCE-UA). Different objective functions (Nash-Sutcliffe model efficiency coefficient, the timing of peak, peak value and Root-mean-square deviation) were used in single or multiple way. It was found that the lateral inflow factor was the most sensitive parameter. SP-UCI algorithm could avoid the local optimal and achieve efficient and effective parameters in the calibration of HEC-Ras model using flood extension images. As results showed, calibration by means of gauged discharge data and flood inundation maps, together with objective function of Nash-Sutcliffe model efficiency coefficient, was very robust to obtain more reliable flood simulation, and also to catch up with the peak value and the timing of peak.

TNT Prout-Tompkins Kinetics Calibration with PSUADE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wemhoff, A P; Hsieh, H

2007-04-11

We used the code PSUADE to calibrate Prout-Tompkins kinetic parameters for pure recrystallized TNT. The calibration was based on ALE3D simulations of a series of One Dimensional Time to Explosion (ODTX) experiments. The resultant kinetic parameters differed from TNT data points with an average error of 28%, which is slightly higher than the value of 23% previously calculated using a two-point optimization. The methodology described here provides a basis for future calibration studies using PSUADE. The files used in the procedure are listed in the Appendix.

K-ε Turbulence Model Parameter Estimates Using an Approximate Self-similar Jet-in-Crossflow Solution

DOE PAGES

DeChant, Lawrence; Ray, Jaideep; Lefantzi, Sophia; ...

2017-06-09

The k-ε turbulence model has been described as perhaps “the most widely used complete turbulence model.” This family of heuristic Reynolds Averaged Navier-Stokes (RANS) turbulence closures is supported by a suite of model parameters that have been estimated by demanding the satisfaction of well-established canonical flows such as homogeneous shear flow, log-law behavior, etc. While this procedure does yield a set of so-called nominal parameters, it is abundantly clear that they do not provide a universally satisfactory turbulence model that is capable of simulating complex flows. Recent work on the Bayesian calibration of the k-ε model using jet-in-crossflow wind tunnelmore » data has yielded parameter estimates that are far more predictive than nominal parameter values. In this paper, we develop a self-similar asymptotic solution for axisymmetric jet-in-crossflow interactions and derive analytical estimates of the parameters that were inferred using Bayesian calibration. The self-similar method utilizes a near field approach to estimate the turbulence model parameters while retaining the classical far-field scaling to model flow field quantities. Our parameter values are seen to be far more predictive than the nominal values, as checked using RANS simulations and experimental measurements. They are also closer to the Bayesian estimates than the nominal parameters. A traditional simplified jet trajectory model is explicitly related to the turbulence model parameters and is shown to yield good agreement with measurement when utilizing the analytical derived turbulence model coefficients. Finally, the close agreement between the turbulence model coefficients obtained via Bayesian calibration and the analytically estimated coefficients derived in this paper is consistent with the contention that the Bayesian calibration approach is firmly rooted in the underlying physical description.« less

The Value of Hydrograph Partitioning Curves for Calibrating Hydrological Models in Glacierized Basins

NASA Astrophysics Data System (ADS)

He, Zhihua; Vorogushyn, Sergiy; Unger-Shayesteh, Katy; Gafurov, Abror; Kalashnikova, Olga; Omorova, Elvira; Merz, Bruno

2018-03-01

This study refines the method for calibrating a glacio-hydrological model based on Hydrograph Partitioning Curves (HPCs), and evaluates its value in comparison to multidata set optimization approaches which use glacier mass balance, satellite snow cover images, and discharge. The HPCs are extracted from the observed flow hydrograph using catchment precipitation and temperature gradients. They indicate the periods when the various runoff processes, such as glacier melt or snow melt, dominate the basin hydrograph. The annual cumulative curve of the difference between average daily temperature and melt threshold temperature over the basin, as well as the annual cumulative curve of average daily snowfall on the glacierized areas are used to identify the starting and end dates of snow and glacier ablation periods. Model parameters characterizing different runoff processes are calibrated on different HPCs in a stepwise and iterative way. Results show that the HPC-based method (1) delivers model-internal consistency comparably to the tri-data set calibration method; (2) improves the stability of calibrated parameter values across various calibration periods; and (3) estimates the contributions of runoff components similarly to the tri-data set calibration method. Our findings indicate the potential of the HPC-based approach as an alternative for hydrological model calibration in glacierized basins where other calibration data sets than discharge are often not available or very costly to obtain.

Augmenting epidemiological models with point-of-care diagnostics data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pullum, Laura L.; Ramanathan, Arvind; Nutaro, James J.

Although adoption of newer Point-of-Care (POC) diagnostics is increasing, there is a significant challenge using POC diagnostics data to improve epidemiological models. In this work, we propose a method to process zip-code level POC datasets and apply these processed data to calibrate an epidemiological model. We specifically develop a calibration algorithm using simulated annealing and calibrate a parsimonious equation-based model of modified Susceptible-Infected-Recovered (SIR) dynamics. The results show that parsimonious models are remarkably effective in predicting the dynamics observed in the number of infected patients and our calibration algorithm is sufficiently capable of predicting peak loads observed in POC diagnosticsmore » data while staying within reasonable and empirical parameter ranges reported in the literature. Additionally, we explore the future use of the calibrated values by testing the correlation between peak load and population density from Census data. Our results show that linearity assumptions for the relationships among various factors can be misleading, therefore further data sources and analysis are needed to identify relationships between additional parameters and existing calibrated ones. As a result, calibration approaches such as ours can determine the values of newly added parameters along with existing ones and enable policy-makers to make better multi-scale decisions.« less

Augmenting epidemiological models with point-of-care diagnostics data

DOE PAGES

Pullum, Laura L.; Ramanathan, Arvind; Nutaro, James J.; ...

2016-04-20

Although adoption of newer Point-of-Care (POC) diagnostics is increasing, there is a significant challenge using POC diagnostics data to improve epidemiological models. In this work, we propose a method to process zip-code level POC datasets and apply these processed data to calibrate an epidemiological model. We specifically develop a calibration algorithm using simulated annealing and calibrate a parsimonious equation-based model of modified Susceptible-Infected-Recovered (SIR) dynamics. The results show that parsimonious models are remarkably effective in predicting the dynamics observed in the number of infected patients and our calibration algorithm is sufficiently capable of predicting peak loads observed in POC diagnosticsmore » data while staying within reasonable and empirical parameter ranges reported in the literature. Additionally, we explore the future use of the calibrated values by testing the correlation between peak load and population density from Census data. Our results show that linearity assumptions for the relationships among various factors can be misleading, therefore further data sources and analysis are needed to identify relationships between additional parameters and existing calibrated ones. As a result, calibration approaches such as ours can determine the values of newly added parameters along with existing ones and enable policy-makers to make better multi-scale decisions.« less

Uncertainty analyses of the calibrated parameter values of a water quality model

NASA Astrophysics Data System (ADS)

Rode, M.; Suhr, U.; Lindenschmidt, K.-E.

2003-04-01

For river basin management water quality models are increasingly used for the analysis and evaluation of different management measures. However substantial uncertainties exist in parameter values depending on the available calibration data. In this paper an uncertainty analysis for a water quality model is presented, which considers the impact of available model calibration data and the variance of input variables. The investigation was conducted based on four extensive flowtime related longitudinal surveys in the River Elbe in the years 1996 to 1999 with varying discharges and seasonal conditions. For the model calculations the deterministic model QSIM of the BfG (Germany) was used. QSIM is a one dimensional water quality model and uses standard algorithms for hydrodynamics and phytoplankton dynamics in running waters, e.g. Michaelis Menten/Monod kinetics, which are used in a wide range of models. The multi-objective calibration of the model was carried out with the nonlinear parameter estimator PEST. The results show that for individual flow time related measuring surveys very good agreements between model calculation and measured values can be obtained. If these parameters are applied to deviating boundary conditions, substantial errors in model calculation can occur. These uncertainties can be decreased with an increased calibration database. More reliable model parameters can be identified, which supply reasonable results for broader boundary conditions. The extension of the application of the parameter set on a wider range of water quality conditions leads to a slight reduction of the model precision for the specific water quality situation. Moreover the investigations show that highly variable water quality variables like the algal biomass always allow a smaller forecast accuracy than variables with lower coefficients of variation like e.g. nitrate.

THE ON-SITE ON-LINE TOOL FOR SITE ASSESSMENT CALCULATIONS

EPA Science Inventory

State and Federal Agency personnel often receive modeling reports with undocumented parameter values. The reports give parameter values, but often no indication if the value was measured, taken from the literature, the result of calibration, or some type of estimate. Recent examp...

Parameter regionalization of a monthly water balance model for the conterminous United States

NASA Astrophysics Data System (ADS)

Bock, A. R.; Hay, L. E.; McCabe, G. J.; Markstrom, S. L.; Atkinson, R. D.

2015-09-01

A parameter regionalization scheme to transfer parameter values and model uncertainty information from gaged to ungaged areas for a monthly water balance model (MWBM) was developed and tested for the conterminous United States (CONUS). The Fourier Amplitude Sensitivity Test, a global-sensitivity algorithm, was implemented on a MWBM to generate parameter sensitivities on a set of 109 951 hydrologic response units (HRUs) across the CONUS. The HRUs were grouped into 110 calibration regions based on similar parameter sensitivities. Subsequently, measured runoff from 1575 streamgages within the calibration regions were used to calibrate the MWBM parameters to produce parameter sets for each calibration region. Measured and simulated runoff at the 1575 streamgages showed good correspondence for the majority of the CONUS, with a median computed Nash-Sutcliffe Efficiency coefficient of 0.76 over all streamgages. These methods maximize the use of available runoff information, resulting in a calibrated CONUS-wide application of the MWBM suitable for providing estimates of water availability at the HRU resolution for both gaged and ungaged areas of the CONUS.

Thermodynamically consistent model calibration in chemical kinetics

PubMed Central

2011-01-01

Background The dynamics of biochemical reaction systems are constrained by the fundamental laws of thermodynamics, which impose well-defined relationships among the reaction rate constants characterizing these systems. Constructing biochemical reaction systems from experimental observations often leads to parameter values that do not satisfy the necessary thermodynamic constraints. This can result in models that are not physically realizable and may lead to inaccurate, or even erroneous, descriptions of cellular function. Results We introduce a thermodynamically consistent model calibration (TCMC) method that can be effectively used to provide thermodynamically feasible values for the parameters of an open biochemical reaction system. The proposed method formulates the model calibration problem as a constrained optimization problem that takes thermodynamic constraints (and, if desired, additional non-thermodynamic constraints) into account. By calculating thermodynamically feasible values for the kinetic parameters of a well-known model of the EGF/ERK signaling cascade, we demonstrate the qualitative and quantitative significance of imposing thermodynamic constraints on these parameters and the effectiveness of our method for accomplishing this important task. MATLAB software, using the Systems Biology Toolbox 2.1, can be accessed from http://www.cis.jhu.edu/~goutsias/CSS lab/software.html. An SBML file containing the thermodynamically feasible EGF/ERK signaling cascade model can be found in the BioModels database. Conclusions TCMC is a simple and flexible method for obtaining physically plausible values for the kinetic parameters of open biochemical reaction systems. It can be effectively used to recalculate a thermodynamically consistent set of parameter values for existing thermodynamically infeasible biochemical reaction models of cellular function as well as to estimate thermodynamically feasible values for the parameters of new models. Furthermore, TCMC can provide dimensionality reduction, better estimation performance, and lower computational complexity, and can help to alleviate the problem of data overfitting. PMID:21548948

Development of a precipitation-runoff model to simulate unregulated streamflow in the South Fork Flathead River Basin, Montana

USGS Publications Warehouse

Chase, K.J.

2011-01-01

This report documents the development of a precipitation-runoff model for the South Fork Flathead River Basin, Mont. The Precipitation-Runoff Modeling System model, developed in cooperation with the Bureau of Reclamation, can be used to simulate daily mean unregulated streamflow upstream and downstream from Hungry Horse Reservoir for water-resources planning. Two input files are required to run the model. The time-series data file contains daily precipitation data and daily minimum and maximum air-temperature data from climate stations in and near the South Fork Flathead River Basin. The parameter file contains values of parameters that describe the basin topography, the flow network, the distribution of the precipitation and temperature data, and the hydrologic characteristics of the basin soils and vegetation. A primary-parameter file was created for simulating streamflow during the study period (water years 1967-2005). The model was calibrated for water years 1991-2005 using the primary-parameter file. This calibration was further refined using snow-covered area data for water years 2001-05. The model then was tested for water years 1967-90. Calibration targets included mean monthly and daily mean unregulated streamflow upstream from Hungry Horse Reservoir, mean monthly unregulated streamflow downstream from Hungry Horse Reservoir, basin mean monthly solar radiation and potential evapotranspiration, and daily snapshots of basin snow-covered area. Simulated streamflow generally was in better agreement with observed streamflow at the upstream gage than at the downstream gage. Upstream from the reservoir, simulated mean annual streamflow was within 0.0 percent of observed mean annual streamflow for the calibration period and was about 2 percent higher than observed mean annual streamflow for the test period. Simulated mean April-July streamflow upstream from the reservoir was about 1 percent lower than observed streamflow for the calibration period and about 4 percent higher than observed for the test period. Downstream from the reservoir, simulated mean annual streamflow was 17 percent lower than observed streamflow for the calibration period and 12 percent lower than observed streamflow for the test period. Simulated mean April-July streamflow downstream from the reservoir was 13 percent lower than observed streamflow for the calibration period and 6 percent lower than observed streamflow for the test period. Calibrating to solar radiation, potential evapotranspiration, and snow-covered area improved the model representation of evapotranspiration, snow accumulation, and snowmelt processes. Simulated basin mean monthly solar radiation values for both the calibration and test periods were within 9 percent of observed values except during the month of December (28 percent different). Simulated basin potential evapotranspiration values for both the calibration and test periods were within 10 percent of observed values except during the months of January (100 percent different) and February (13 percent different). The larger percent errors in simulated potential evaporation occurred in the winter months when observed potential evapotranspiration values were very small; in January the observed value was 0.000 inches and in February the observed value was 0.009 inches. Simulated start of melting of the snowpack occurred at about the same time as observed start of melting. The simulated snowpack accumulated to 90-100 percent snow-covered area 1 to 3 months earlier than observed snowpack. This overestimated snowpack during the winter corresponded to underestimated streamflow during the same period. In addition to the primary-parameter file, four other parameter files were created: for a "recent" period (1991-2005), a historical period (1967-90), a "wet" period (1989-97), and a "dry" period (1998-2005). For each data file of projected precipitation and air temperature, a single parameter file can be used to simulate a s

Bayesian calibration of the Community Land Model using surrogates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ray, Jaideep; Hou, Zhangshuan; Huang, Maoyi

2014-02-01

We present results from the Bayesian calibration of hydrological parameters of the Community Land Model (CLM), which is often used in climate simulations and Earth system models. A statistical inverse problem is formulated for three hydrological parameters, conditional on observations of latent heat surface fluxes over 48 months. Our calibration method uses polynomial and Gaussian process surrogates of the CLM, and solves the parameter estimation problem using a Markov chain Monte Carlo sampler. Posterior probability densities for the parameters are developed for two sites with different soil and vegetation covers. Our method also allows us to examine the structural errormore » in CLM under two error models. We find that surrogate models can be created for CLM in most cases. The posterior distributions are more predictive than the default parameter values in CLM. Climatologically averaging the observations does not modify the parameters' distributions significantly. The structural error model reveals a correlation time-scale which can be used to identify the physical process that could be contributing to it. While the calibrated CLM has a higher predictive skill, the calibration is under-dispersive.« less

Parameter interdependence and uncertainty induced by lumping in a hydrologic model

NASA Astrophysics Data System (ADS)

Gallagher, Mark R.; Doherty, John

2007-05-01

Throughout the world, watershed modeling is undertaken using lumped parameter hydrologic models that represent real-world processes in a manner that is at once abstract, but nevertheless relies on algorithms that reflect real-world processes and parameters that reflect real-world hydraulic properties. In most cases, values are assigned to the parameters of such models through calibration against flows at watershed outlets. One criterion by which the utility of the model and the success of the calibration process are judged is that realistic values are assigned to parameters through this process. This study employs regularization theory to examine the relationship between lumped parameters and corresponding real-world hydraulic properties. It demonstrates that any kind of parameter lumping or averaging can induce a substantial amount of "structural noise," which devices such as Box-Cox transformation of flows and autoregressive moving average (ARMA) modeling of residuals are unlikely to render homoscedastic and uncorrelated. Furthermore, values estimated for lumped parameters are unlikely to represent average values of the hydraulic properties after which they are named and are often contaminated to a greater or lesser degree by the values of hydraulic properties which they do not purport to represent at all. As a result, the question of how rigidly they should be bounded during the parameter estimation process is still an open one.

Research on the calibration methods of the luminance parameter of radiation luminance meters

NASA Astrophysics Data System (ADS)

Cheng, Weihai; Huang, Biyong; Lin, Fangsheng; Li, Tiecheng; Yin, Dejin; Lai, Lei

2017-10-01

This paper introduces standard diffusion reflection white plate method and integrating sphere standard luminance source method to calibrate the luminance parameter. The paper compares the effects of calibration results by using these two methods through principle analysis and experimental verification. After using two methods to calibrate the same radiation luminance meter, the data obtained verifies the testing results of the two methods are both reliable. The results show that the display value using standard white plate method has fewer errors and better reproducibility. However, standard luminance source method is more convenient and suitable for on-site calibration. Moreover, standard luminance source method has wider range and can test the linear performance of the instruments.

Calibration-induced uncertainty of the EPIC model to estimate climate change impact on global maize yield

NASA Astrophysics Data System (ADS)

Xiong, Wei; Skalský, Rastislav; Porter, Cheryl H.; Balkovič, Juraj; Jones, James W.; Yang, Di

2016-09-01

Understanding the interactions between agricultural production and climate is necessary for sound decision-making in climate policy. Gridded and high-resolution crop simulation has emerged as a useful tool for building this understanding. Large uncertainty exists in this utilization, obstructing its capacity as a tool to devise adaptation strategies. Increasing focus has been given to sources of uncertainties for climate scenarios, input-data, and model, but uncertainties due to model parameter or calibration are still unknown. Here, we use publicly available geographical data sets as input to the Environmental Policy Integrated Climate model (EPIC) for simulating global-gridded maize yield. Impacts of climate change are assessed up to the year 2099 under a climate scenario generated by HadEM2-ES under RCP 8.5. We apply five strategies by shifting one specific parameter in each simulation to calibrate the model and understand the effects of calibration. Regionalizing crop phenology or harvest index appears effective to calibrate the model for the globe, but using various values of phenology generates pronounced difference in estimated climate impact. However, projected impacts of climate change on global maize production are consistently negative regardless of the parameter being adjusted. Different values of model parameter result in a modest uncertainty at global level, with difference of the global yield change less than 30% by the 2080s. The uncertainty subjects to decrease if applying model calibration or input data quality control. Calibration has a larger effect at local scales, implying the possible types and locations for adaptation.

Bayesian integration of flux tower data into a process-based simulator for quantifying uncertainty in simulated output

NASA Astrophysics Data System (ADS)

Raj, Rahul; van der Tol, Christiaan; Hamm, Nicholas Alexander Samuel; Stein, Alfred

2018-01-01

Parameters of a process-based forest growth simulator are difficult or impossible to obtain from field observations. Reliable estimates can be obtained using calibration against observations of output and state variables. In this study, we present a Bayesian framework to calibrate the widely used process-based simulator Biome-BGC against estimates of gross primary production (GPP) data. We used GPP partitioned from flux tower measurements of a net ecosystem exchange over a 55-year-old Douglas fir stand as an example. The uncertainties of both the Biome-BGC parameters and the simulated GPP values were estimated. The calibrated parameters leaf and fine root turnover (LFRT), ratio of fine root carbon to leaf carbon (FRC : LC), ratio of carbon to nitrogen in leaf (C : Nleaf), canopy water interception coefficient (Wint), fraction of leaf nitrogen in RuBisCO (FLNR), and effective soil rooting depth (SD) characterize the photosynthesis and carbon and nitrogen allocation in the forest. The calibration improved the root mean square error and enhanced Nash-Sutcliffe efficiency between simulated and flux tower daily GPP compared to the uncalibrated Biome-BGC. Nevertheless, the seasonal cycle for flux tower GPP was not reproduced exactly and some overestimation in spring and underestimation in summer remained after calibration. We hypothesized that the phenology exhibited a seasonal cycle that was not accurately reproduced by the simulator. We investigated this by calibrating the Biome-BGC to each month's flux tower GPP separately. As expected, the simulated GPP improved, but the calibrated parameter values suggested that the seasonal cycle of state variables in the simulator could be improved. It was concluded that the Bayesian framework for calibration can reveal features of the modelled physical processes and identify aspects of the process simulator that are too rigid.

Calibration of a complex activated sludge model for the full-scale wastewater treatment plant.

PubMed

Liwarska-Bizukojc, Ewa; Olejnik, Dorota; Biernacki, Rafal; Ledakowicz, Stanislaw

2011-08-01

In this study, the results of the calibration of the complex activated sludge model implemented in BioWin software for the full-scale wastewater treatment plant are presented. Within the calibration of the model, sensitivity analysis of its parameters and the fractions of carbonaceous substrate were performed. In the steady-state and dynamic calibrations, a successful agreement between the measured and simulated values of the output variables was achieved. Sensitivity analysis revealed that upon the calculations of normalized sensitivity coefficient (S(i,j)) 17 (steady-state) or 19 (dynamic conditions) kinetic and stoichiometric parameters are sensitive. Most of them are associated with growth and decay of ordinary heterotrophic organisms and phosphorus accumulating organisms. The rankings of ten most sensitive parameters established on the basis of the calculations of the mean square sensitivity measure (δ(msqr)j) indicate that irrespective of the fact, whether the steady-state or dynamic calibration was performed, there is an agreement in the sensitivity of parameters.

On the relationship between NMR-derived amide order parameters and protein backbone entropy changes

PubMed Central

Sharp, Kim A.; O’Brien, Evan; Kasinath, Vignesh; Wand, A. Joshua

2015-01-01

Molecular dynamics simulations are used to analyze the relationship between NMR-derived squared generalized order parameters of amide NH groups and backbone entropy. Amide order parameters (O2NH) are largely determined by the secondary structure and average values appear unrelated to the overall flexibility of the protein. However, analysis of the more flexible subset (O2NH < 0.8) shows that these report both on the local flexibility of the protein and on a different component of the conformational entropy than that reported by the side chain methyl axis order parameters, O2axis. A calibration curve for backbone entropy vs. O2NH is developed which accounts for both correlations between amide group motions of different residues, and correlations between backbone and side chain motions. This calibration curve can be used with experimental values of O2NH changes obtained by NMR relaxation measurements to extract backbone entropy changes, e.g. upon ligand binding. In conjunction with our previous calibration for side chain entropy derived from measured O2axis values this provides a prescription for determination of the total protein conformational entropy changes from NMR relaxation measurements. PMID:25739366

On the relationship between NMR-derived amide order parameters and protein backbone entropy changes.

PubMed

Sharp, Kim A; O'Brien, Evan; Kasinath, Vignesh; Wand, A Joshua

2015-05-01

Molecular dynamics simulations are used to analyze the relationship between NMR-derived squared generalized order parameters of amide NH groups and backbone entropy. Amide order parameters (O(2) NH ) are largely determined by the secondary structure and average values appear unrelated to the overall flexibility of the protein. However, analysis of the more flexible subset (O(2) NH  < 0.8) shows that these report both on the local flexibility of the protein and on a different component of the conformational entropy than that reported by the side chain methyl axis order parameters, O(2) axis . A calibration curve for backbone entropy vs. O(2) NH is developed, which accounts for both correlations between amide group motions of different residues, and correlations between backbone and side chain motions. This calibration curve can be used with experimental values of O(2) NH changes obtained by NMR relaxation measurements to extract backbone entropy changes, for example, upon ligand binding. In conjunction with our previous calibration for side chain entropy derived from measured O(2) axis values this provides a prescription for determination of the total protein conformational entropy changes from NMR relaxation measurements. © 2015 Wiley Periodicals, Inc.

Determination of Stark parameters by cross-calibration in a multi-element laser-induced plasma

NASA Astrophysics Data System (ADS)

Liu, Hao; Truscott, Benjamin S.; Ashfold, Michael N. R.

2016-05-01

We illustrate a Stark broadening analysis of the electron density Ne and temperature Te in a laser-induced plasma (LIP), using a model free of assumptions regarding local thermodynamic equilibrium (LTE). The method relies on Stark parameters determined also without assuming LTE, which are often unknown and unavailable in the literature. Here, we demonstrate that the necessary values can be obtained in situ by cross-calibration between the spectral lines of different charge states, and even different elements, given determinations of Ne and Te based on appropriate parameters for at least one observed transition. This approach enables essentially free choice between species on which to base the analysis, extending the range over which these properties can be measured and giving improved access to low-density plasmas out of LTE. Because of the availability of suitable tabulated values for several charge states of both Si and C, the example of a SiC LIP is taken to illustrate the consistency and accuracy of the procedure. The cross-calibrated Stark parameters are at least as reliable as values obtained by other means, offering a straightforward route to extending the literature in this area.

The benefits of using remotely sensed soil moisture in parameter identification of large-scale hydrological models

NASA Astrophysics Data System (ADS)

Wanders, N.; Bierkens, M. F. P.; de Jong, S. M.; de Roo, A.; Karssenberg, D.

2014-08-01

Large-scale hydrological models are nowadays mostly calibrated using observed discharge. As a result, a large part of the hydrological system, in particular the unsaturated zone, remains uncalibrated. Soil moisture observations from satellites have the potential to fill this gap. Here we evaluate the added value of remotely sensed soil moisture in calibration of large-scale hydrological models by addressing two research questions: (1) Which parameters of hydrological models can be identified by calibration with remotely sensed soil moisture? (2) Does calibration with remotely sensed soil moisture lead to an improved calibration of hydrological models compared to calibration based only on discharge observations, such that this leads to improved simulations of soil moisture content and discharge? A dual state and parameter Ensemble Kalman Filter is used to calibrate the hydrological model LISFLOOD for the Upper Danube. Calibration is done using discharge and remotely sensed soil moisture acquired by AMSR-E, SMOS, and ASCAT. Calibration with discharge data improves the estimation of groundwater and routing parameters. Calibration with only remotely sensed soil moisture results in an accurate identification of parameters related to land-surface processes. For the Upper Danube upstream area up to 40,000 km2, calibration on both discharge and soil moisture results in a reduction by 10-30% in the RMSE for discharge simulations, compared to calibration on discharge alone. The conclusion is that remotely sensed soil moisture holds potential for calibration of hydrological models, leading to a better simulation of soil moisture content throughout the catchment and a better simulation of discharge in upstream areas. This article was corrected on 15 SEP 2014. See the end of the full text for details.

Financial model calibration using consistency hints.

PubMed

Abu-Mostafa, Y S

2001-01-01

We introduce a technique for forcing the calibration of a financial model to produce valid parameters. The technique is based on learning from hints. It converts simple curve fitting into genuine calibration, where broad conclusions can be inferred from parameter values. The technique augments the error function of curve fitting with consistency hint error functions based on the Kullback-Leibler distance. We introduce an efficient EM-type optimization algorithm tailored to this technique. We also introduce other consistency hints, and balance their weights using canonical errors. We calibrate the correlated multifactor Vasicek model of interest rates, and apply it successfully to Japanese Yen swaps market and US dollar yield market.

Impulse Current Waveform Compliance with IEC 60060-1

NASA Astrophysics Data System (ADS)

Sato, Shuji; Harada, Tatsuya; Yokoyama, Taizou; Sakaguchi, Sumiko; Ebana, Takao; Saito, Tatsunori

After numerous simulations, authors could unsuccessfully design an impulse current calibrator, whose output's time parameters (front time, T1 and time to half the peak, T2 ) are quite close to ideals defined in IEC 60060-1. The investigation for the failed trial was commenced. Using normalized damped oscillating waveform e-tsin(ωt), a relationship of the ratio T2/T1 and undershoot value are studied for all possible value for . With this relationship, it is derived that 1) one cannot generate an ideal wave form unless one has to accept a certain margin for the two parameters, 2) even with the allowable margin, one can generate a wave form only in a case a value for T1 is smaller and T2 is larger than standard values. In the paper, possible time parameter combination, which fulfils IEC 60060-1 requirements, is illustrated for a calibrator design.

OT calibration and service maintenance manual.

DOT National Transportation Integrated Search

2012-01-01

The machine conditions, as well as the values at the calibration and control parameters, may determine the quality of each test results obtained. In order to keep consistency and accuracy, the conditions, performance and measurements of an OT must be...

Automatic Calibration of a Distributed Rainfall-Runoff Model, Using the Degree-Day Formulation for Snow Melting, Within DMIP2 Project

NASA Astrophysics Data System (ADS)

Frances, F.; Orozco, I.

2010-12-01

This work presents the assessment of the TETIS distributed hydrological model in mountain basins of the American and Carson rivers in Sierra Nevada (USA) at hourly time discretization, as part of the DMIP2 Project. In TETIS each cell of the spatial grid conceptualizes the water cycle using six tanks connected among them. The relationship between tanks depends on the case, although at the end in most situations, simple linear reservoirs and flow thresholds schemes are used with exceptional results (Vélez et al., 1999; Francés et al., 2002). In particular, within the snow tank, snow melting is based in this work on the simple degree-day method with spatial constant parameters. The TETIS model includes an automatic calibration module, based on the SCE-UA algorithm (Duan et al., 1992; Duan et al., 1994) and the model effective parameters are organized following a split structure, as presented by Francés and Benito (1995) and Francés et al. (2007). In this way, the calibration involves in TETIS up to 9 correction factors (CFs), which correct globally the different parameter maps instead of each parameter cell value, thus reducing drastically the number of variables to be calibrated. This strategy allows for a fast and agile modification in different hydrological processes preserving the spatial structure of each parameter map. With the snowmelt submodel, automatic model calibration was carried out in three steps, separating the calibration of rainfall-runoff and snowmelt parameters. In the first step, the automatic calibration of the CFs during the period 05/20/1990 to 07/31/1990 in the American River (without snow influence), gave a Nash-Sutcliffe Efficiency (NSE) index of 0.92. The calibration of the three degree-day parameters was done using all the SNOTEL stations in the American and Carson rivers. Finally, using previous calibrations as initial values, the complete calibration done in the Carson River for the period 10/01/1992 to 07/31/1993 gave a NSE index of 0.86. The temporal and spatial validation using five periods must be considered in both rivers excellent for discharges (NSEs higher than 0.76) and good for snow distribution (daily spatial coverage errors ranging from -10 to 27%). In conclusion, this work demonstrates: 1.- The viability of automatic calibration of distributed models, with the corresponding personal time saving and maximum exploitation of the available information. 2.- The good performance of the degree-day snowmelt formulation even at hourly time discretization, in spite of its simplicity.

Regional estimation of response routine parameters

NASA Astrophysics Data System (ADS)

Tøfte, Lena S.

2015-04-01

Reducing the number of calibration parameters is of a considerable advantage when area distributed hydrological models are to be calibrated, both due to equifinality and over-parameterization of the model in general, and for making the calibration process more efficient. A simple non-threshold response model for drainage in natural catchments based on among others Kirchner's article in WRR 2009 is implemented in the gridded hydrological model in the ENKI framework. This response model takes only the hydrogram into account; it has one state and two parameters, and is adapted to catchments that are dominated by terrain drainage. In former analyses of natural discharge series from a large number of catchments in different regions of Norway, we found that these response model parameters can be calculated from some known catchment characteristics, as catchment area and lake percentage, found in maps or data bases, meaning that the parameters can easily be found also for ungauged catchments. In the presented work from the EU project COMPLEX a large region in Mid-Norway containing 27 simulated catchments of different sizes and characteristics is calibrated. Results from two different calibration strategies are compared: 1) removing the response parameters from the calibration by calculating them in advance, based on the results from our former studies, and 2) including the response parameters in the calibration, both as maps with different values for each catchment, and as a constant number for the total region. The resulting simulation performances are compared and discussed.

The cost of uniqueness in groundwater model calibration

NASA Astrophysics Data System (ADS)

Moore, Catherine; Doherty, John

2006-04-01

Calibration of a groundwater model requires that hydraulic properties be estimated throughout a model domain. This generally constitutes an underdetermined inverse problem, for which a solution can only be found when some kind of regularization device is included in the inversion process. Inclusion of regularization in the calibration process can be implicit, for example through the use of zones of constant parameter value, or explicit, for example through solution of a constrained minimization problem in which parameters are made to respect preferred values, or preferred relationships, to the degree necessary for a unique solution to be obtained. The "cost of uniqueness" is this: no matter which regularization methodology is employed, the inevitable consequence of its use is a loss of detail in the calibrated field. This, in turn, can lead to erroneous predictions made by a model that is ostensibly "well calibrated". Information made available as a by-product of the regularized inversion process allows the reasons for this loss of detail to be better understood. In particular, it is easily demonstrated that the estimated value for an hydraulic property at any point within a model domain is, in fact, a weighted average of the true hydraulic property over a much larger area. This averaging process causes loss of resolution in the estimated field. Where hydraulic conductivity is the hydraulic property being estimated, high averaging weights exist in areas that are strategically disposed with respect to measurement wells, while other areas may contribute very little to the estimated hydraulic conductivity at any point within the model domain, this possibly making the detection of hydraulic conductivity anomalies in these latter areas almost impossible. A study of the post-calibration parameter field covariance matrix allows further insights into the loss of system detail incurred through the calibration process to be gained. A comparison of pre- and post-calibration parameter covariance matrices shows that the latter often possess a much smaller spectral bandwidth than the former. It is also demonstrated that, as an inevitable consequence of the fact that a calibrated model cannot replicate every detail of the true system, model-to-measurement residuals can show a high degree of spatial correlation, a fact which must be taken into account when assessing these residuals either qualitatively, or quantitatively in the exploration of model predictive uncertainty. These principles are demonstrated using a synthetic case in which spatial parameter definition is based on pilot points, and calibration is implemented using both zones of piecewise constancy and constrained minimization regularization.

Modulation of enzyme catalytic properties and biosensor calibration parameters with chlorides: studies with glucose oxidase.

PubMed

Kagan, Margarita; Kivirand, Kairi; Rinken, Toonika

2013-09-10

We studied the modulation of calibration parameters of biosensors, in which glucose oxidase was used for bio-recognition, in the presence of different chlorides by following the transient phase dynamics of oxygen concentration with an oxygen optrode. The mechanism of modulation was characterized with the changes of the glucose oxidase catalytic constant and oxygen diffusion constant. The modulation of two biosensor calibration parameters were studied: the maximum calculated signal change was amplified for about 20% in the presence of sodium and magnesium chlorides; the value of the kinetic parameter decreased along with the addition of salts and increased only at sodium chloride concentrations over 0.5 mM. Besides glucose bioassay, the amplification of calibration parameters was also studied in cascaded two-enzyme lactose biosensor, where the initial step of lactose bio-recognition, the β-galactosidase - catalyzed lactose hydrolysis, was additionally accelerated by magnesium ions. Copyright © 2013 Elsevier Inc. All rights reserved.

Impact of the hard-coded parameters on the hydrologic fluxes of the land surface model Noah-MP

NASA Astrophysics Data System (ADS)

Cuntz, Matthias; Mai, Juliane; Samaniego, Luis; Clark, Martyn; Wulfmeyer, Volker; Attinger, Sabine; Thober, Stephan

2016-04-01

Land surface models incorporate a large number of processes, described by physical, chemical and empirical equations. The process descriptions contain a number of parameters that can be soil or plant type dependent and are typically read from tabulated input files. Land surface models may have, however, process descriptions that contain fixed, hard-coded numbers in the computer code, which are not identified as model parameters. Here we searched for hard-coded parameters in the computer code of the land surface model Noah with multiple process options (Noah-MP) to assess the importance of the fixed values on restricting the model's agility during parameter estimation. We found 139 hard-coded values in all Noah-MP process options, which are mostly spatially constant values. This is in addition to the 71 standard parameters of Noah-MP, which mostly get distributed spatially by given vegetation and soil input maps. We performed a Sobol' global sensitivity analysis of Noah-MP to variations of the standard and hard-coded parameters for a specific set of process options. 42 standard parameters and 75 hard-coded parameters were active with the chosen process options. The sensitivities of the hydrologic output fluxes latent heat and total runoff as well as their component fluxes were evaluated. These sensitivities were evaluated at twelve catchments of the Eastern United States with very different hydro-meteorological regimes. Noah-MP's hydrologic output fluxes are sensitive to two thirds of its standard parameters. The most sensitive parameter is, however, a hard-coded value in the formulation of soil surface resistance for evaporation, which proved to be oversensitive in other land surface models as well. Surface runoff is sensitive to almost all hard-coded parameters of the snow processes and the meteorological inputs. These parameter sensitivities diminish in total runoff. Assessing these parameters in model calibration would require detailed snow observations or the calculation of hydrologic signatures of the runoff data. Latent heat and total runoff exhibit very similar sensitivities towards standard and hard-coded parameters in Noah-MP because of their tight coupling via the water balance. It should therefore be comparable to calibrate Noah-MP either against latent heat observations or against river runoff data. Latent heat and total runoff are sensitive to both, plant and soil parameters. Calibrating only a parameter sub-set of only soil parameters, for example, thus limits the ability to derive realistic model parameters. It is thus recommended to include the most sensitive hard-coded model parameters that were exposed in this study when calibrating Noah-MP.

Simulation of daily streamflow for 12 river basins in western Iowa using the Precipitation-Runoff Modeling System

USGS Publications Warehouse

Christiansen, Daniel E.; Haj, Adel E.; Risley, John C.

2017-10-24

The U.S. Geological Survey, in cooperation with the Iowa Department of Natural Resources, constructed Precipitation-Runoff Modeling System models to estimate daily streamflow for 12 river basins in western Iowa that drain into the Missouri River. The Precipitation-Runoff Modeling System is a deterministic, distributed-parameter, physical-process-based modeling system developed to evaluate the response of streamflow and general drainage basin hydrology to various combinations of climate and land use. Calibration periods for each basin varied depending on the period of record available for daily mean streamflow measurements at U.S. Geological Survey streamflow-gaging stations.A geographic information system tool was used to delineate each basin and estimate initial values for model parameters based on basin physical and geographical features. A U.S. Geological Survey automatic calibration tool that uses a shuffled complex evolution algorithm was used for initial calibration, and then manual modifications were made to parameter values to complete the calibration of each basin model. The main objective of the calibration was to match daily discharge values of simulated streamflow to measured daily discharge values. The Precipitation-Runoff Modeling System model was calibrated at 42 sites located in the 12 river basins in western Iowa.The accuracy of the simulated daily streamflow values at the 42 calibration sites varied by river and by site. The models were satisfactory at 36 of the sites based on statistical results. Unsatisfactory performance at the six other sites can be attributed to several factors: (1) low flow, no flow, and flashy flow conditions in headwater subbasins having a small drainage area; (2) poor representation of the groundwater and storage components of flow within a basin; (3) lack of accounting for basin withdrawals and water use; and (4) limited availability and accuracy of meteorological input data. The Precipitation-Runoff Modeling System models of 12 river basins in western Iowa will provide water-resource managers with a consistent and documented method for estimating streamflow at ungaged sites and aid in environmental studies, hydraulic design, water management, and water-quality projects.

Parameter Set Cloning Based on Catchment Similarity for Large-scale Hydrologic Modeling

NASA Astrophysics Data System (ADS)

Liu, Z.; Kaheil, Y.; McCollum, J.

2016-12-01

Parameter calibration is a crucial step to ensure the accuracy of hydrological models. However, streamflow gauges are not available everywhere for calibrating a large-scale hydrologic model globally. Thus, assigning parameters appropriately for regions where the calibration cannot be performed directly has been a challenge for large-scale hydrologic modeling. Here we propose a method to estimate the model parameters in ungauged regions based on the values obtained through calibration in areas where gauge observations are available. This parameter set cloning is performed according to a catchment similarity index, a weighted sum index based on four catchment characteristic attributes. These attributes are IPCC Climate Zone, Soil Texture, Land Cover, and Topographic Index. The catchments with calibrated parameter values are donors, while the uncalibrated catchments are candidates. Catchment characteristic analyses are first conducted for both donors and candidates. For each attribute, we compute a characteristic distance between donors and candidates. Next, for each candidate, weights are assigned to the four attributes such that higher weights are given to properties that are more directly linked to the hydrologic dominant processes. This will ensure that the parameter set cloning emphasizes the dominant hydrologic process in the region where the candidate is located. The catchment similarity index for each donor - candidate couple is then created as the sum of the weighted distance of the four properties. Finally, parameters are assigned to each candidate from the donor that is "most similar" (i.e. with the shortest weighted distance sum). For validation, we applied the proposed method to catchments where gauge observations are available, and compared simulated streamflows using the parameters cloned by other catchments to the results obtained by calibrating the hydrologic model directly using gauge data. The comparison shows good agreement between the two models for different river basins as we show here. This method has been applied globally to the Hillslope River Routing (HRR) model using gauge observations obtained from the Global Runoff Data Center (GRDC). As next step, more catchment properties can be taken into account to further improve the representation of catchment similarity.

On the applicability of surrogate-based Markov chain Monte Carlo-Bayesian inversion to the Community Land Model: Case studies at flux tower sites: SURROGATE-BASED MCMC FOR CLM

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Maoyi; Ray, Jaideep; Hou, Zhangshuan

2016-07-04

The Community Land Model (CLM) has been widely used in climate and Earth system modeling. Accurate estimation of model parameters is needed for reliable model simulations and predictions under current and future conditions, respectively. In our previous work, a subset of hydrological parameters has been identified to have significant impact on surface energy fluxes at selected flux tower sites based on parameter screening and sensitivity analysis, which indicate that the parameters could potentially be estimated from surface flux observations at the towers. To date, such estimates do not exist. In this paper, we assess the feasibility of applying a Bayesianmore » model calibration technique to estimate CLM parameters at selected flux tower sites under various site conditions. The parameters are estimated as a joint probability density function (PDF) that provides estimates of uncertainty of the parameters being inverted, conditional on climatologically-average latent heat fluxes derived from observations. We find that the simulated mean latent heat fluxes from CLM using the calibrated parameters are generally improved at all sites when compared to those obtained with CLM simulations using default parameter sets. Further, our calibration method also results in credibility bounds around the simulated mean fluxes which bracket the measured data. The modes (or maximum a posteriori values) and 95% credibility intervals of the site-specific posterior PDFs are tabulated as suggested parameter values for each site. Analysis of relationships between the posterior PDFs and site conditions suggests that the parameter values are likely correlated with the plant functional type, which needs to be confirmed in future studies by extending the approach to more sites.« less

On the applicability of surrogate-based MCMC-Bayesian inversion to the Community Land Model: Case studies at Flux tower sites

DOE PAGES

Huang, Maoyi; Ray, Jaideep; Hou, Zhangshuan; ...

2016-06-01

The Community Land Model (CLM) has been widely used in climate and Earth system modeling. Accurate estimation of model parameters is needed for reliable model simulations and predictions under current and future conditions, respectively. In our previous work, a subset of hydrological parameters has been identified to have significant impact on surface energy fluxes at selected flux tower sites based on parameter screening and sensitivity analysis, which indicate that the parameters could potentially be estimated from surface flux observations at the towers. To date, such estimates do not exist. In this paper, we assess the feasibility of applying a Bayesianmore » model calibration technique to estimate CLM parameters at selected flux tower sites under various site conditions. The parameters are estimated as a joint probability density function (PDF) that provides estimates of uncertainty of the parameters being inverted, conditional on climatologically average latent heat fluxes derived from observations. We find that the simulated mean latent heat fluxes from CLM using the calibrated parameters are generally improved at all sites when compared to those obtained with CLM simulations using default parameter sets. Further, our calibration method also results in credibility bounds around the simulated mean fluxes which bracket the measured data. The modes (or maximum a posteriori values) and 95% credibility intervals of the site-specific posterior PDFs are tabulated as suggested parameter values for each site. As a result, analysis of relationships between the posterior PDFs and site conditions suggests that the parameter values are likely correlated with the plant functional type, which needs to be confirmed in future studies by extending the approach to more sites.« less

On the applicability of surrogate-based MCMC-Bayesian inversion to the Community Land Model: Case studies at Flux tower sites

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Maoyi; Ray, Jaideep; Hou, Zhangshuan

The Community Land Model (CLM) has been widely used in climate and Earth system modeling. Accurate estimation of model parameters is needed for reliable model simulations and predictions under current and future conditions, respectively. In our previous work, a subset of hydrological parameters has been identified to have significant impact on surface energy fluxes at selected flux tower sites based on parameter screening and sensitivity analysis, which indicate that the parameters could potentially be estimated from surface flux observations at the towers. To date, such estimates do not exist. In this paper, we assess the feasibility of applying a Bayesianmore » model calibration technique to estimate CLM parameters at selected flux tower sites under various site conditions. The parameters are estimated as a joint probability density function (PDF) that provides estimates of uncertainty of the parameters being inverted, conditional on climatologically average latent heat fluxes derived from observations. We find that the simulated mean latent heat fluxes from CLM using the calibrated parameters are generally improved at all sites when compared to those obtained with CLM simulations using default parameter sets. Further, our calibration method also results in credibility bounds around the simulated mean fluxes which bracket the measured data. The modes (or maximum a posteriori values) and 95% credibility intervals of the site-specific posterior PDFs are tabulated as suggested parameter values for each site. As a result, analysis of relationships between the posterior PDFs and site conditions suggests that the parameter values are likely correlated with the plant functional type, which needs to be confirmed in future studies by extending the approach to more sites.« less

On the applicability of surrogate-based Markov chain Monte Carlo-Bayesian inversion to the Community Land Model: Case studies at flux tower sites

NASA Astrophysics Data System (ADS)

Huang, Maoyi; Ray, Jaideep; Hou, Zhangshuan; Ren, Huiying; Liu, Ying; Swiler, Laura

2016-07-01

The Community Land Model (CLM) has been widely used in climate and Earth system modeling. Accurate estimation of model parameters is needed for reliable model simulations and predictions under current and future conditions, respectively. In our previous work, a subset of hydrological parameters has been identified to have significant impact on surface energy fluxes at selected flux tower sites based on parameter screening and sensitivity analysis, which indicate that the parameters could potentially be estimated from surface flux observations at the towers. To date, such estimates do not exist. In this paper, we assess the feasibility of applying a Bayesian model calibration technique to estimate CLM parameters at selected flux tower sites under various site conditions. The parameters are estimated as a joint probability density function (PDF) that provides estimates of uncertainty of the parameters being inverted, conditional on climatologically average latent heat fluxes derived from observations. We find that the simulated mean latent heat fluxes from CLM using the calibrated parameters are generally improved at all sites when compared to those obtained with CLM simulations using default parameter sets. Further, our calibration method also results in credibility bounds around the simulated mean fluxes which bracket the measured data. The modes (or maximum a posteriori values) and 95% credibility intervals of the site-specific posterior PDFs are tabulated as suggested parameter values for each site. Analysis of relationships between the posterior PDFs and site conditions suggests that the parameter values are likely correlated with the plant functional type, which needs to be confirmed in future studies by extending the approach to more sites.

A new methodology based on sensitivity analysis to simplify the recalibration of functional-structural plant models in new conditions.

PubMed

Mathieu, Amélie; Vidal, Tiphaine; Jullien, Alexandra; Wu, QiongLi; Chambon, Camille; Bayol, Benoit; Cournède, Paul-Henry

2018-06-19

Functional-structural plant models (FSPMs) describe explicitly the interactions between plants and their environment at organ to plant scale. However, the high level of description of the structure or model mechanisms makes this type of model very complex and hard to calibrate. A two-step methodology to facilitate the calibration process is proposed here. First, a global sensitivity analysis method was applied to the calibration loss function. It provided first-order and total-order sensitivity indexes that allow parameters to be ranked by importance in order to select the most influential ones. Second, the Akaike information criterion (AIC) was used to quantify the model's quality of fit after calibration with different combinations of selected parameters. The model with the lowest AIC gives the best combination of parameters to select. This methodology was validated by calibrating the model on an independent data set (same cultivar, another year) with the parameters selected in the second step. All the parameters were set to their nominal value; only the most influential ones were re-estimated. Sensitivity analysis applied to the calibration loss function is a relevant method to underline the most significant parameters in the estimation process. For the studied winter oilseed rape model, 11 out of 26 estimated parameters were selected. Then, the model could be recalibrated for a different data set by re-estimating only three parameters selected with the model selection method. Fitting only a small number of parameters dramatically increases the efficiency of recalibration, increases the robustness of the model and helps identify the principal sources of variation in varying environmental conditions. This innovative method still needs to be more widely validated but already gives interesting avenues to improve the calibration of FSPMs.

Demonstration of a vectorial optical field generator with adaptive close loop control.

PubMed

Chen, Jian; Kong, Lingjiang; Zhan, Qiwen

2017-12-01

We experimentally demonstrate a vectorial optical field generator (VOF-Gen) with an adaptive close loop control. The close loop control capability is illustrated with the calibration of polarization modulation of the system. To calibrate the polarization ratio modulation, we generate 45° linearly polarized beam and make it propagate through a linear analyzer whose transmission axis is orthogonal to the incident beam. For the retardation calibration, circularly polarized beam is employed and a circular polarization analyzer with the opposite chirality is placed in front of the CCD as the detector. In both cases, the close loop control automatically changes the value of the corresponding calibration parameters in the pre-set ranges to generate the phase patterns applied to the spatial light modulators and records the intensity distribution of the output beam by the CCD camera. The optimized calibration parameters are determined corresponding to the minimum total intensity in each case. Several typical kinds of vectorial optical beams are created with and without the obtained calibration parameters, and the full Stokes parameter measurements are carried out to quantitatively analyze the polarization distribution of the generated beams. The comparisons among these results clearly show that the obtained calibration parameters could remarkably improve the accuracy of the polarization modulation of the VOF-Gen, especially for generating elliptically polarized beam with large ellipticity, indicating the significance of the presented close loop in enhancing the performance of the VOF-Gen.

[Study on the characteristics of radiance calibration using nonuniformity extended source].

PubMed

Wang, Jian-Wei; Huang, Min; Xiangli, Bin; Tu, Xiao-Long

2013-07-01

Integrating sphere and diffuser are always used as extended source, and they have different effects on radiance calibration of imaging spectrometer with parameter difference. In the present paper, a mathematical model based on the theory of radiative transfer and calibration principle is founded to calculate the irradiance and calibration coefficients on CCD, taking relatively poor uniformity lights-board calibration system for example. The effects of the nonuniformity on the calibration was analyzed, which makes up the correlation of calibration coefficient matrix under ideal and unideal situation. The results show that the nonuniformity makes the viewing angle and the position of the point of intersection of the optical axis and the diffuse reflection plate have relatively large effects on calibration, while the observing distance's effect is small; under different viewing angles, a deviation value can be found that makes the calibration results closest to the desired results. So, the calibration error can be reduced by choosing appropriate deviation value.

Nonlinear method for including the mass uncertainty of standards and the system measurement errors in the fitting of calibration curves

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pickles, W.L.; McClure, J.W.; Howell, R.H.

1978-01-01

A sophisticated non-linear multiparameter fitting program has been used to produce a best fit calibration curve for the response of an x-ray fluorescence analyzer to uranium nitrate, freeze dried, 0.2% accurate, gravimetric standards. The program is based on unconstrained minimization subroutine, VA02A. The program considers the mass values of the gravimetric standards as parameters to be fit along with the normal calibration curve parameters. The fitting procedure weights with the system errors and the mass errors in a consistent way. The resulting best fit calibration curve parameters reflect the fact that the masses of the standard samples are measured quantitiesmore » with a known error. Error estimates for the calibration curve parameters can be obtined from the curvature of the Chi-Squared Matrix or from error relaxation techniques. It has been shown that non-dispersive x-ray fluorescence analysis of 0.1 to 1 mg freeze-dried UNO/sub 3/ can have an accuracy of 0.2% in 1000 sec.« less

Use of a non-linear method for including the mass uncertainty of gravimetric standards and system measurement errors in the fitting of calibration curves for XRFA freeze-dried UNO/sub 3/ standards

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pickles, W.L.; McClure, J.W.; Howell, R.H.

1978-05-01

A sophisticated nonlinear multiparameter fitting program was used to produce a best fit calibration curve for the response of an x-ray fluorescence analyzer to uranium nitrate, freeze dried, 0.2% accurate, gravimetric standards. The program is based on unconstrained minimization subroutine, VA02A. The program considers the mass values of the gravimetric standards as parameters to be fit along with the normal calibration curve parameters. The fitting procedure weights with the system errors and the mass errors in a consistent way. The resulting best fit calibration curve parameters reflect the fact that the masses of the standard samples are measured quantities withmore » a known error. Error estimates for the calibration curve parameters can be obtained from the curvature of the ''Chi-Squared Matrix'' or from error relaxation techniques. It was shown that nondispersive XRFA of 0.1 to 1 mg freeze-dried UNO/sub 3/ can have an accuracy of 0.2% in 1000 s.« less

Calibration of micro-capacitance measurement system for thermal barrier coating testing

NASA Astrophysics Data System (ADS)

Ren, Yuan; Chen, Dixiang; Wan, Chengbiao; Tian, Wugang; Pan, Mengchun

2018-06-01

In order to comprehensively evaluate the thermal barrier coating system of an engine blade, an integrated planar sensor combining electromagnetic coils with planar capacitors is designed, in which the capacitance measurement accuracy of the planar capacitor is a key factor. The micro-capacitance measurement system is built based on an impedance analyzer. Because of the influence of non-ideal factors on the measuring system, there is an obvious difference between the measured value and the actual value. It is necessary to calibrate the measured results and eliminate the difference. In this paper, the measurement model of a planar capacitive sensor is established, and the relationship between the measured value and the actual value of capacitance is deduced. The model parameters are estimated with the least square method, and the calibration accuracy is evaluated with experiments under different dielectric conditions. The capacitance measurement error is reduced from 29% ˜ 46.5% to around 1% after calibration, which verifies the feasibility of the calibration method.

Synthetic calibration of a Rainfall-Runoff Model

USGS Publications Warehouse

Thompson, David B.; Westphal, Jerome A.; ,

1990-01-01

A method for synthetically calibrating storm-mode parameters for the U.S. Geological Survey's Precipitation-Runoff Modeling System is described. Synthetic calibration is accomplished by adjusting storm-mode parameters to minimize deviations between the pseudo-probability disributions represented by regional regression equations and actual frequency distributions fitted to model-generated peak discharge and runoff volume. Results of modeling storm hydrographs using synthetic and analytic storm-mode parameters are presented. Comparisons are made between model results from both parameter sets and between model results and observed hydrographs. Although mean storm runoff is reproducible to within about 26 percent of the observed mean storm runoff for five or six parameter sets, runoff from individual storms is subject to large disparities. Predicted storm runoff volume ranged from 2 percent to 217 percent of commensurate observed values. Furthermore, simulation of peak discharges was poor. Predicted peak discharges from individual storm events ranged from 2 percent to 229 percent of commensurate observed values. The model was incapable of satisfactorily executing storm-mode simulations for the study watersheds. This result is not considered a particular fault of the model, but instead is indicative of deficiencies in similar conceptual models.

Simultaneous calibration of end-member thermodynamic data and solution properties with correlated uncertainties

NASA Astrophysics Data System (ADS)

Antoshechkina, P. M.; Wolf, A. S.; Hamecher, E. A.; Asimow, P. D.; Ghiorso, M. S.

2013-12-01

Community databases such as EarthChem, LEPR, and AMCSD both increase demand for quantitative petrological tools, including thermodynamic models like the MELTS family of algorithms, and are invaluable in development of such tools. The need to extend existing solid solution models to include minor components such as Cr and Na has been evident for years but as the number of components increases it becomes impossible to completely separate derivation of end-member thermodynamic data from calibration of solution properties. In Hamecher et al. (2012; 2013) we developed a calibration scheme that directly interfaces with a MySQL database based on LEPR, with volume data from AMCSD and elsewhere. Here we combine that scheme with a Bayesian approach, where independent constraints on parameter values (e.g. existence of miscibility gaps) are combined with uncertainty propagation to give a more reliable best-fit along with associated model uncertainties. We illustrate the scheme with a new model of molar volume for (Ca,Fe,Mg,Mn,Na)3(Al,Cr,Fe3+,Fe2+,Mg,Mn,Si,Ti)2Si3O12 cubic garnets. For a garnet in this chemical system, the model molar volume is obtained by adding excess volume terms to a linear combination of nine independent end-member volumes. The model calibration is broken into three main stages: (1) estimation of individual end-member thermodynamic properties; (2) calibration of standard state volumes for all available independent and dependent end members; (3) fitting of binary and mixed composition data. For each calibration step, the goodness-of-fit includes weighted residuals as well as χ2-like penalty terms representing the (not necessarily Gaussian) prior constraints on parameter values. Using the Bayesian approach, uncertainties are correctly propagated forward to subsequent steps, allowing determination of final parameter values and correlated uncertainties that account for the entire calibration process. For the aluminosilicate garnets, optimal values of the bulk modulus and its pressure derivative are obtained by fitting published compression data using the Vinet equation of state, with the Mie-Grüneisen-Debye thermal pressure formalism to model thermal expansion. End-member thermal parameters are obtained by fitting volume data while ensuring that the heat capacity is consistent with the thermodynamic database of Berman and co-workers. For other end members, data for related compositions are used where such data exist; otherwise ultrasonic data or density functional theory results are taken or, for thermal parameters, systematics in cation radii are used. In stages (2) and (3) the remaining data at ambient conditions are fit. Using this step-wise calibration scheme, most parameters are modified little by subsequent calibration steps but some, such as the standard state volume of the Ti-bearing end member, can vary within calculated uncertainties. The final model satisfies desired criteria and fits almost all the data (more than 1000 points); only excess parameters that are justified by the data are activated. The scheme can be easily extended to calibration of end-member and solution properties from experimental phase equilibria. As a first step we obtain the internally consistent standard state entropy and enthalpy of formation for knorringite and discuss differences between our results and those of Klemme and co-workers.

Simulation of streamflow in small drainage basins in the southern Yampa River basin, Colorado

USGS Publications Warehouse

Parker, R.S.; Norris, J.M.

1989-01-01

Coal mining operations in northwestern Colorado commonly are located in areas that have minimal available water-resource information. Drainage-basin models can be a method for extending water-resource information to include periods for which there are no records or to transfer the information to areas that have no streamflow-gaging stations. To evaluate the magnitude and variability of the components of the water balance in the small drainage basins monitored, and to provide some method for transfer of hydrologic data, the U.S. Geological Survey 's Precipitation-Runoff Modeling System was used for small drainage basins in the southern Yampa River basin to simulate daily mean streamflow using daily precipitation and air-temperature data. The study area was divided into three hydrologic regions, and in each of these regions, three drainage basins were monitored. Two of the drainage basins in each region were used to calibrate the Precipitation-Runoff Modeling System. The model was not calibrated for the third drainage basin in each region; instead, parameter values were transferred from the model that was calibrated for the two drainage basins. For all of the drainage basins except one, period of record used for calibration and verification included water years 1976-81. Simulated annual volumes of streamflow for drainage basins used in calibration compared well with observed values; individual hydrographs indicated timing differences between the observed and simulated daily mean streamflow. Observed and simulated annual average streamflows compared well for the periods of record, but values of simulated high and low streamflows were different than observed values. Similar results were obtained when calibrated model parameter values were transferred to drainage basins that were uncalibrated. (USGS)

Use of In-Situ and Remotely Sensed Snow Observations for the National Water Model in Both an Analysis and Calibration Framework.

NASA Astrophysics Data System (ADS)

Karsten, L. R.; Gochis, D.; Dugger, A. L.; McCreight, J. L.; Barlage, M. J.; Fall, G. M.; Olheiser, C.

2017-12-01

Since version 1.0 of the National Water Model (NWM) has gone operational in Summer 2016, several upgrades to the model have occurred to improve hydrologic prediction for the continental United States. Version 1.1 of the NWM (Spring 2017) includes upgrades to parameter datasets impacting land surface hydrologic processes. These parameter datasets were upgraded using an automated calibration workflow that utilizes the Dynamic Data Search (DDS) algorithm to adjust parameter values using observed streamflow. As such, these upgrades to parameter values took advantage of various observations collected for snow analysis. In particular, in-situ SNOTEL observations in the Western US, volunteer in-situ observations across the entire US, gamma-derived snow water equivalent (SWE) observations courtesy of the NWS NOAA Corps program, gridded snow depth and SWE products from the Jet Propulsion Laboratory (JPL) Airborne Snow Observatory (ASO), gridded remotely sensed satellite-based snow products (MODIS,AMSR2,VIIRS,ATMS), and gridded SWE from the NWS Snow Data Assimilation System (SNODAS). This study explores the use of these observations to quantify NWM error and improvements from version 1.0 to version 1.1, along with subsequent work since then. In addition, this study explores the use of snow observations for use within the automated calibration workflow. Gridded parameter fields impacting the accumulation and ablation of snow states in the NWM were adjusted and calibrated using gridded remotely sensed snow states, SNODAS products, and in-situ snow observations. This calibration adjustment took place over various ecological regions in snow-dominated parts of the US for a retrospective period of time to capture a variety of climatological conditions. Specifically, the latest calibrated parameters impacting streamflow were held constant and only parameters impacting snow physics were tuned using snow observations and analysis. The adjusted parameter datasets were then used to force the model over an independent period for analysis against both snow and streamflow observations to see if improvements took place. The goal of this work is to further improve snow physics in the NWM, along with identifying areas where further work will take place in the future, such as data assimilation or further forcing improvements.

A comparison of single- and multi-site calibration and validation: a case study of SWAT in the Miyun Reservoir watershed, China

NASA Astrophysics Data System (ADS)

Bai, Jianwen; Shen, Zhenyao; Yan, Tiezhu

2017-09-01

An essential task in evaluating global water resource and pollution problems is to obtain the optimum set of parameters in hydrological models through calibration and validation. For a large-scale watershed, single-site calibration and validation may ignore spatial heterogeneity and may not meet the needs of the entire watershed. The goal of this study is to apply a multi-site calibration and validation of the Soil andWater Assessment Tool (SWAT), using the observed flow data at three monitoring sites within the Baihe watershed of the Miyun Reservoir watershed, China. Our results indicate that the multi-site calibration parameter values are more reasonable than those obtained from single-site calibrations. These results are mainly due to significant differences in the topographic factors over the large-scale area, human activities and climate variability. The multi-site method involves the division of the large watershed into smaller watersheds, and applying the calibrated parameters of the multi-site calibration to the entire watershed. It was anticipated that this case study could provide experience of multi-site calibration in a large-scale basin, and provide a good foundation for the simulation of other pollutants in followup work in the Miyun Reservoir watershed and other similar large areas.

Evaluation of Collision Cross Section Calibrants for Structural Analysis of Lipids by Traveling Wave Ion Mobility-Mass Spectrometry

PubMed Central

2016-01-01

Collision cross section (CCS) measurement of lipids using traveling wave ion mobility-mass spectrometry (TWIM-MS) is of high interest to the lipidomics field. However, currently available calibrants for CCS measurement using TWIM are predominantly peptides that display quite different physical properties and gas-phase conformations from lipids, which could lead to large CCS calibration errors for lipids. Here we report the direct CCS measurement of a series of phosphatidylcholines (PCs) and phosphatidylethanolamines (PEs) in nitrogen using a drift tube ion mobility (DTIM) instrument and an evaluation of the accuracy and reproducibility of PCs and PEs as CCS calibrants for phospholipids against different classes of calibrants, including polyalanine (PolyAla), tetraalkylammonium salts (TAA), and hexakis(fluoroalkoxy)phosphazines (HFAP), in both positive and negative modes in TWIM-MS analysis. We demonstrate that structurally mismatched calibrants lead to larger errors in calibrated CCS values while the structurally matched calibrants, PCs and PEs, gave highly accurate and reproducible CCS values at different traveling wave parameters. Using the lipid calibrants, the majority of the CCS values of several classes of phospholipids measured by TWIM are within 2% error of the CCS values measured by DTIM. The development of phospholipid CCS calibrants will enable high-accuracy structural studies of lipids and add an additional level of validation in the assignment of identifications in untargeted lipidomics experiments. PMID:27321977

Assessing the applicability of WRF optimal parameters under the different precipitation simulations in the Greater Beijing Area

NASA Astrophysics Data System (ADS)

Di, Zhenhua; Duan, Qingyun; Wang, Chen; Ye, Aizhong; Miao, Chiyuan; Gong, Wei

2018-03-01

Forecasting skills of the complex weather and climate models have been improved by tuning the sensitive parameters that exert the greatest impact on simulated results based on more effective optimization methods. However, whether the optimal parameter values are still work when the model simulation conditions vary, which is a scientific problem deserving of study. In this study, a highly-effective optimization method, adaptive surrogate model-based optimization (ASMO), was firstly used to tune nine sensitive parameters from four physical parameterization schemes of the Weather Research and Forecasting (WRF) model to obtain better summer precipitation forecasting over the Greater Beijing Area in China. Then, to assess the applicability of the optimal parameter values, simulation results from the WRF model with default and optimal parameter values were compared across precipitation events, boundary conditions, spatial scales, and physical processes in the Greater Beijing Area. The summer precipitation events from 6 years were used to calibrate and evaluate the optimal parameter values of WRF model. Three boundary data and two spatial resolutions were adopted to evaluate the superiority of the calibrated optimal parameters to default parameters under the WRF simulations with different boundary conditions and spatial resolutions, respectively. Physical interpretations of the optimal parameters indicating how to improve precipitation simulation results were also examined. All the results showed that the optimal parameters obtained by ASMO are superior to the default parameters for WRF simulations for predicting summer precipitation in the Greater Beijing Area because the optimal parameters are not constrained by specific precipitation events, boundary conditions, and spatial resolutions. The optimal values of the nine parameters were determined from 127 parameter samples using the ASMO method, which showed that the ASMO method is very highly-efficient for optimizing WRF model parameters.

Impact of the calibration period on the conceptual rainfall-runoff model parameter estimates

NASA Astrophysics Data System (ADS)

Todorovic, Andrijana; Plavsic, Jasna

2015-04-01

A conceptual rainfall-runoff model is defined by its structure and parameters, which are commonly inferred through model calibration. Parameter estimates depend on objective function(s), optimisation method, and calibration period. Model calibration over different periods may result in dissimilar parameter estimates, while model efficiency decreases outside calibration period. Problem of model (parameter) transferability, which conditions reliability of hydrologic simulations, has been investigated for decades. In this paper, dependence of the parameter estimates and model performance on calibration period is analysed. The main question that is addressed is: are there any changes in optimised parameters and model efficiency that can be linked to the changes in hydrologic or meteorological variables (flow, precipitation and temperature)? Conceptual, semi-distributed HBV-light model is calibrated over five-year periods shifted by a year (sliding time windows). Length of the calibration periods is selected to enable identification of all parameters. One water year of model warm-up precedes every simulation, which starts with the beginning of a water year. The model is calibrated using the built-in GAP optimisation algorithm. The objective function used for calibration is composed of Nash-Sutcliffe coefficient for flows and logarithms of flows, and volumetric error, all of which participate in the composite objective function with approximately equal weights. Same prior parameter ranges are used in all simulations. The model is calibrated against flows observed at the Slovac stream gauge on the Kolubara River in Serbia (records from 1954 to 2013). There are no trends in precipitation nor in flows, however, there is a statistically significant increasing trend in temperatures at this catchment. Parameter variability across the calibration periods is quantified in terms of standard deviations of normalised parameters, enabling detection of the most variable parameters. Correlation coefficients among optimised model parameters and total precipitation P, mean temperature T and mean flow Q are calculated to give an insight into parameter dependence on the hydrometeorological drivers. The results reveal high sensitivity of almost all model parameters towards calibration period. The highest variability is displayed by the refreezing coefficient, water holding capacity, and temperature gradient. The only statistically significant (decreasing) trend is detected in the evapotranspiration reduction threshold. Statistically significant correlation is detected between the precipitation gradient and precipitation depth, and between the time-area histogram base and flows. All other correlations are not statistically significant, implying that changes in optimised parameters cannot generally be linked to the changes in P, T or Q. As for the model performance, the model reproduces the observed runoff satisfactorily, though the runoff is slightly overestimated in wet periods. The Nash-Sutcliffe efficiency coefficient (NSE) ranges from 0.44 to 0.79. Higher NSE values are obtained over wetter periods, what is supported by statistically significant correlation between NSE and flows. Overall, no systematic variations in parameters or in model performance are detected. Parameter variability may therefore rather be attributed to errors in data or inadequacies in the model structure. Further research is required to examine the impact of the calibration strategy or model structure on the variability in optimised parameters in time.

The impact of standard and hard-coded parameters on the hydrologic fluxes in the Noah-MP land surface model

NASA Astrophysics Data System (ADS)

Thober, S.; Cuntz, M.; Mai, J.; Samaniego, L. E.; Clark, M. P.; Branch, O.; Wulfmeyer, V.; Attinger, S.

2016-12-01

Land surface models incorporate a large number of processes, described by physical, chemical and empirical equations. The agility of the models to react to different meteorological conditions is artificially constrained by having hard-coded parameters in their equations. Here we searched for hard-coded parameters in the computer code of the land surface model Noah with multiple process options (Noah-MP) to assess the model's agility during parameter estimation. We found 139 hard-coded values in all Noah-MP process options in addition to the 71 standard parameters. We performed a Sobol' global sensitivity analysis to variations of the standard and hard-coded parameters. The sensitivities of the hydrologic output fluxes latent heat and total runoff, their component fluxes, as well as photosynthesis and sensible heat were evaluated at twelve catchments of the Eastern United States with very different hydro-meteorological regimes. Noah-MP's output fluxes are sensitive to two thirds of its standard parameters. The most sensitive parameter is, however, a hard-coded value in the formulation of soil surface resistance for evaporation, which proved to be oversensitive in other land surface models as well. Latent heat and total runoff show very similar sensitivities towards standard and hard-coded parameters. They are sensitive to both soil and plant parameters, which means that model calibrations of hydrologic or land surface models should take both soil and plant parameters into account. Sensible and latent heat exhibit almost the same sensitivities so that calibration or sensitivity analysis can be performed with either of the two. Photosynthesis has almost the same sensitivities as transpiration, which are different from the sensitivities of latent heat. Including photosynthesis and latent heat in model calibration might therefore be beneficial. Surface runoff is sensitive to almost all hard-coded snow parameters. These sensitivities get, however, diminished in total runoff. It is thus recommended to include the most sensitive hard-coded model parameters that were exposed in this study when calibrating Noah-MP.

Estimating parameter values of a socio-hydrological flood model

NASA Astrophysics Data System (ADS)

Holkje Barendrecht, Marlies; Viglione, Alberto; Kreibich, Heidi; Vorogushyn, Sergiy; Merz, Bruno; Blöschl, Günter

2018-06-01

Socio-hydrological modelling studies that have been published so far show that dynamic coupled human-flood models are a promising tool to represent the phenomena and the feedbacks in human-flood systems. So far these models are mostly generic and have not been developed and calibrated to represent specific case studies. We believe that applying and calibrating these type of models to real world case studies can help us to further develop our understanding about the phenomena that occur in these systems. In this paper we propose a method to estimate the parameter values of a socio-hydrological model and we test it by applying it to an artificial case study. We postulate a model that describes the feedbacks between floods, awareness and preparedness. After simulating hypothetical time series with a given combination of parameters, we sample few data points for our variables and try to estimate the parameters given these data points using Bayesian Inference. The results show that, if we are able to collect data for our case study, we would, in theory, be able to estimate the parameter values for our socio-hydrological flood model.

The benefits of using remotely sensed soil moisture in parameter identification of large-scale hydrological models

NASA Astrophysics Data System (ADS)

Karssenberg, D.; Wanders, N.; de Roo, A.; de Jong, S.; Bierkens, M. F.

2013-12-01

Large-scale hydrological models are nowadays mostly calibrated using observed discharge. As a result, a large part of the hydrological system that is not directly linked to discharge, in particular the unsaturated zone, remains uncalibrated, or might be modified unrealistically. Soil moisture observations from satellites have the potential to fill this gap, as these provide the closest thing to a direct measurement of the state of the unsaturated zone, and thus are potentially useful in calibrating unsaturated zone model parameters. This is expected to result in a better identification of the complete hydrological system, potentially leading to improved forecasts of the hydrograph as well. Here we evaluate this added value of remotely sensed soil moisture in calibration of large-scale hydrological models by addressing two research questions: 1) Which parameters of hydrological models can be identified by calibration with remotely sensed soil moisture? 2) Does calibration with remotely sensed soil moisture lead to an improved calibration of hydrological models compared to approaches that calibrate only with discharge, such that this leads to improved forecasts of soil moisture content and discharge as well? To answer these questions we use a dual state and parameter ensemble Kalman filter to calibrate the hydrological model LISFLOOD for the Upper Danube area. Calibration is done with discharge and remotely sensed soil moisture acquired by AMSR-E, SMOS and ASCAT. Four scenarios are studied: no calibration (expert knowledge), calibration on discharge, calibration on remote sensing data (three satellites) and calibration on both discharge and remote sensing data. Using a split-sample approach, the model is calibrated for a period of 2 years and validated for the calibrated model parameters on a validation period of 10 years. Results show that calibration with discharge data improves the estimation of groundwater parameters (e.g., groundwater reservoir constant) and routing parameters. Calibration with only remotely sensed soil moisture results in an accurate calibration of parameters related to land surface process (e.g., the saturated conductivity of the soil), which is not possible when calibrating on discharge alone. For the upstream area up to 40000 km2, calibration on both discharge and soil moisture results in a reduction by 10-30 % in the RMSE for discharge simulations, compared to calibration on discharge alone. For discharge in the downstream area, the model performance due to assimilation of remotely sensed soil moisture is not increased or slightly decreased, most probably due to the longer relative importance of the routing and contribution of groundwater in downstream areas. When microwave soil moisture is used for calibration the RMSE of soil moisture simulations decreases from 0.072 m3m-3 to 0.062 m3m-3. The conclusion is that remotely sensed soil moisture holds potential for calibration of hydrological models leading to a better simulation of soil moisture content throughout and a better simulation of discharge in upstream areas, particularly if discharge observations are sparse.

When to Make Mountains out of Molehills: The Pros and Cons of Simple and Complex Model Calibration Procedures

NASA Astrophysics Data System (ADS)

Smith, K. A.; Barker, L. J.; Harrigan, S.; Prudhomme, C.; Hannaford, J.; Tanguy, M.; Parry, S.

2017-12-01

Earth and environmental models are relied upon to investigate system responses that cannot otherwise be examined. In simulating physical processes, models have adjustable parameters which may, or may not, have a physical meaning. Determining the values to assign to these model parameters is an enduring challenge for earth and environmental modellers. Selecting different error metrics by which the models results are compared to observations will lead to different sets of calibrated model parameters, and thus different model results. Furthermore, models may exhibit `equifinal' behaviour, where multiple combinations of model parameters lead to equally acceptable model performance against observations. These decisions in model calibration introduce uncertainty that must be considered when model results are used to inform environmental decision-making. This presentation focusses on the uncertainties that derive from the calibration of a four parameter lumped catchment hydrological model (GR4J). The GR models contain an inbuilt automatic calibration algorithm that can satisfactorily calibrate against four error metrics in only a few seconds. However, a single, deterministic model result does not provide information on parameter uncertainty. Furthermore, a modeller interested in extreme events, such as droughts, may wish to calibrate against more low flows specific error metrics. In a comprehensive assessment, the GR4J model has been run with 500,000 Latin Hypercube Sampled parameter sets across 303 catchments in the United Kingdom. These parameter sets have been assessed against six error metrics, including two drought specific metrics. This presentation compares the two approaches, and demonstrates that the inbuilt automatic calibration can outperform the Latin Hypercube experiment approach in single metric assessed performance. However, it is also shown that there are many merits of the more comprehensive assessment, which allows for probabilistic model results, multi-objective optimisation, and better tailoring to calibrate the model for specific applications such as drought event characterisation. Modellers and decision-makers may be constrained in their choice of calibration method, so it is important that they recognise the strengths and limitations of their chosen approach.

Basic calibrations of the photographic RGU system. III - Intermediate and extreme Population II dwarf stars

NASA Astrophysics Data System (ADS)

Buser, R.; Fenkart, R. P.

1990-11-01

This paper presents an extended calibration of the color-magnitude and two-color diagrams and the metal-abundance parameter for the intermediate Population II and the extreme halo dwarfs observed in the Basel Palomar-Schmidt RGU three-color photometric surveys of the galaxy. The calibration covers the metallicity range between values +0.50 and -3.00. It is shown that the calibrations presented are sufficiently accurate to be useful for the future analyses of photographic survey data.

Accounting for temporal variation in soil hydrological properties when simulating surface runoff on tilled plots

NASA Astrophysics Data System (ADS)

Chahinian, Nanée; Moussa, Roger; Andrieux, Patrick; Voltz, Marc

2006-07-01

Tillage operations are known to greatly influence local overland flow, infiltration and depressional storage by altering soil hydraulic properties and soil surface roughness. The calibration of runoff models for tilled fields is not identical to that of untilled fields, as it has to take into consideration the temporal variability of parameters due to the transient nature of surface crusts. In this paper, we seek the application of a rainfall-runoff model and the development of a calibration methodology to take into account the impact of tillage on overland flow simulation at the scale of a tilled plot (3240 m 2) located in southern France. The selected model couples the (Morel-Seytoux, H.J., 1978. Derivation of equations for variable rainfall infiltration. Water Resources Research. 14(4), 561-568). Infiltration equation to a transfer function based on the diffusive wave equation. The parameters to be calibrated are the hydraulic conductivity at natural saturation Ks, the surface detention Sd and the lag time ω. A two-step calibration procedure is presented. First, eleven rainfall-runoff events are calibrated individually and the variability of the calibrated parameters are analysed. The individually calibrated Ks values decrease monotonously according to the total amount of rainfall since tillage. No clear relationship is observed between the two parameters Sd and ω, and the date of tillage. However, the lag time ω increases inversely with the peakflow of the events. Fairly good agreement is observed between the simulated and measured hydrographs of the calibration set. Simple mathematical laws describing the evolution of Ks and ω are selected, while Sd is considered constant. The second step involves the collective calibration of the law of evolution of each parameter on the whole calibration set. This procedure is calibrated on 11 events and validated on ten runoff inducing and four non-runoff inducing rainfall events. The suggested calibration methodology seems robust and can be transposed to other gauged sites.

Calibration of two complex ecosystem models with different likelihood functions

NASA Astrophysics Data System (ADS)

Hidy, Dóra; Haszpra, László; Pintér, Krisztina; Nagy, Zoltán; Barcza, Zoltán

2014-05-01

The biosphere is a sensitive carbon reservoir. Terrestrial ecosystems were approximately carbon neutral during the past centuries, but they became net carbon sinks due to climate change induced environmental change and associated CO2 fertilization effect of the atmosphere. Model studies and measurements indicate that the biospheric carbon sink can saturate in the future due to ongoing climate change which can act as a positive feedback. Robustness of carbon cycle models is a key issue when trying to choose the appropriate model for decision support. The input parameters of the process-based models are decisive regarding the model output. At the same time there are several input parameters for which accurate values are hard to obtain directly from experiments or no local measurements are available. Due to the uncertainty associated with the unknown model parameters significant bias can be experienced if the model is used to simulate the carbon and nitrogen cycle components of different ecosystems. In order to improve model performance the unknown model parameters has to be estimated. We developed a multi-objective, two-step calibration method based on Bayesian approach in order to estimate the unknown parameters of PaSim and Biome-BGC models. Biome-BGC and PaSim are a widely used biogeochemical models that simulate the storage and flux of water, carbon, and nitrogen between the ecosystem and the atmosphere, and within the components of the terrestrial ecosystems (in this research the developed version of Biome-BGC is used which is referred as BBGC MuSo). Both models were calibrated regardless the simulated processes and type of model parameters. The calibration procedure is based on the comparison of measured data with simulated results via calculating a likelihood function (degree of goodness-of-fit between simulated and measured data). In our research different likelihood function formulations were used in order to examine the effect of the different model goodness metric on calibration. The different likelihoods are different functions of RMSE (root mean squared error) weighted by measurement uncertainty: exponential / linear / quadratic / linear normalized by correlation. As a first calibration step sensitivity analysis was performed in order to select the influential parameters which have strong effect on the output data. In the second calibration step only the sensitive parameters were calibrated (optimal values and confidence intervals were calculated). In case of PaSim more parameters were found responsible for the 95% of the output data variance than is case of BBGC MuSo. Analysis of the results of the optimized models revealed that the exponential likelihood estimation proved to be the most robust (best model simulation with optimized parameter, highest confidence interval increase). The cross-validation of the model simulations can help in constraining the highly uncertain greenhouse gas budget of grasslands.

Optimum data weighting and error calibration for estimation of gravitational parameters

NASA Technical Reports Server (NTRS)

Lerch, Francis J.

1989-01-01

A new technique was developed for the weighting of data from satellite tracking systems in order to obtain an optimum least-squares solution and an error calibration for the solution parameters. Data sets from optical, electronic, and laser systems on 17 satellites in GEM-T1 Goddard Earth Model-T1 (GEM-T1) were employed toward application of this technique for gravity field parameters. Also GEM-T2 (31 satellites) was recently computed as a direct application of the method and is summarized. The method employs subset solutions of the data associated with the complete solution to agree with their error estimates. With the adjusted weights the process provides for an automatic calibration of the error estimates for the solution parameters. The data weights derived are generally much smaller than corresponding weights obtained from nominal values of observation accuracy or residuals. Independent tests show significant improvement for solutions with optimal weighting. The technique is general and may be applied to orbit parameters, station coordinates, or other parameters than the gravity model.

Revision and proposed modification for a total maximum daily load model for Upper Klamath Lake, Oregon

USGS Publications Warehouse

Wherry, Susan A.; Wood, Tamara M.; Anderson, Chauncey W.

2015-01-01

Using the extended 1991–2010 external phosphorus loading dataset, the lake TMDL model was recalibrated following the same procedures outlined in the Phase 1 review. The version of the model selected for further development incorporated an updated sediment initial condition, a numerical solution method for the chlorophyll a model, changes to light and phosphorus factors limiting algal growth, and a new pH-model regression, which removed Julian day dependence in order to avoid discontinuities in pH at year boundaries. This updated lake TMDL model was recalibrated using the extended dataset in order to compare calibration parameters to those obtained from a calibration with the original 7.5-year dataset. The resulting algal settling velocity calibrated from the extended dataset was more than twice the value calibrated with the original dataset, and, because the calibrated values of algal settling velocity and recycle rate are related (more rapid settling required more rapid recycling), the recycling rate also was larger than that determined with the original dataset. These changes in calibration parameters highlight the uncertainty in critical rates in the Upper Klamath Lake TMDL model and argue for their direct measurement in future data collection to increase confidence in the model predictions.

Near infrared spectroscopy (NIRS) for on-line determination of quality parameters in intact olives.

PubMed

Salguero-Chaparro, Lourdes; Baeten, Vincent; Fernández-Pierna, Juan A; Peña-Rodríguez, Francisco

2013-08-15

The acidity, moisture and fat content in intact olive fruits were determined on-line using a NIR diode array instrument, operating on a conveyor belt. Four sets of calibrations models were obtained by means of different combinations from samples collected during 2009-2010 and 2010-2011, using full-cross and external validation. Several preprocessing treatments such as derivatives and scatter correction were investigated by using the root mean square error of cross-validation (RMSECV) and prediction (RMSEP), as control parameters. The results obtained showed RMSECV values of 2.54-3.26 for moisture, 2.35-2.71 for fat content and 2.50-3.26 for acidity parameters, depending on the calibration model developed. Calibrations for moisture, fat content and acidity gave residual predictive deviation (RPD) values of 2.76, 2.37 and 1.60, respectively. Although, it is concluded that the on-line NIRS prediction results were acceptable for the three parameters measured in intact olive samples in movement, the models developed must be improved in order to increase their accuracy before final NIRS implementation at mills. Copyright © 2013 Elsevier Ltd. All rights reserved.

Design and Calibration of the X-33 Flush Airdata Sensing (FADS) System

NASA Technical Reports Server (NTRS)

Whitmore, Stephen A.; Cobleigh, Brent R.; Haering, Edward A.

1998-01-01

This paper presents the design of the X-33 Flush Airdata Sensing (FADS) system. The X-33 FADS uses a matrix of pressure orifices on the vehicle nose to estimate airdata parameters. The system is designed with dual-redundant measurement hardware, which produces two independent measurement paths. Airdata parameters that correspond to the measurement path with the minimum fit error are selected as the output values. This method enables a single sensor failure to occur with minimal degrading of the system performance. The paper shows the X-33 FADS architecture, derives the estimating algorithms, and demonstrates a mathematical analysis of the FADS system stability. Preliminary aerodynamic calibrations are also presented here. The calibration parameters, the position error coefficient (epsilon), and flow correction terms for the angle of attack (delta alpha), and angle of sideslip (delta beta) are derived from wind tunnel data. Statistical accuracy of' the calibration is evaluated by comparing the wind tunnel reference conditions to the airdata parameters estimated. This comparison is accomplished by applying the calibrated FADS algorithm to the sensed wind tunnel pressures. When the resulting accuracy estimates are compared to accuracy requirements for the X-33 airdata, the FADS system meets these requirements.

Understanding controls of hydrologic processes across two headwater monolithological catchments using model-data synthesis

NASA Astrophysics Data System (ADS)

Xiao, D.; Shi, Y.; Hoagland, B.; Del Vecchio, J.; Russo, T. A.; DiBiase, R. A.; Li, L.

2017-12-01

How do watershed hydrologic processes differ in catchments derived from different lithology? This study compares two first order, deciduous forest watersheds in Pennsylvania, a sandstone watershed, Garner Run (GR, 1.34 km2), and a shale-derived watershed, Shale Hills (SH, 0.08 km2). Both watersheds are simulated using a combination of national datasets and field measurements, and a physics-based land surface hydrologic model, Flux-PIHM. We aim to evaluate the effects of lithology on watershed hydrology and assess if we can simulate a new watershed without intensive measurements, i.e., directly use calibration information from one watershed (SH) to reproduce hydrologic dynamics of another watershed (GR). Without any calibration, the model at GR based on national datasets and calibration inforamtion from SH cannot capture some discharge peaks or the baseflow during dry periods. The model prediction agrees well with the GR field discharge and soil moisture after calibrating the soil hydraulic parameters using the uncertainty based Hornberger-Spear-Young algorithm and the Latin Hypercube Sampling method. Agreeing with the field observation and national datasets, the difference in parameter values shows that the sandstone watershed has a larger averaged soil pore diameter, greater water storage created by porosity, lower water retention ability, and greater preferential flow. The water budget calculation shows that the riparian zone and the colluvial valley serves as buffer zones that stores water at GR. Using the same procedure, we compared Flux-PIHM simulations with and without a field measured surface boulder map at GR. When the boulder map is used, the prediction of areal averaged soil moisture is improved, without performing extra calibration. When calibrated separately, the cases with or without boulder map yield different calibration values, but their hydrologic predictions are similar, showing equifinality. The calibrated soil hydraulic parameter values in the with boulder map case is more physically plausible than the without boulder map case. We switched the topography and soil properties between GR and SH, and results indicate that the hydrologic processes are more sensitive to changes in domain topography than to changes in the soil properties.

Medical color displays and their color calibration: investigations of various calibration methods, tools, and potential improvement in color difference ΔE

NASA Astrophysics Data System (ADS)

Roehrig, Hans; Hashmi, Syed F.; Dallas, William J.; Krupinski, Elizabeth A.; Rehm, Kelly; Fan, Jiahua

2010-08-01

Our laboratory has investigated the efficacy of a suite of color calibration and monitor profiling packages which employ a variety of color measurement sensors. Each of the methods computes gamma correction tables for the red, green and blue color channels of a monitor that attempt to: a) match a desired luminance range and tone reproduction curve; and b) maintain a target neutral point across the range of grey values. All of the methods examined here produce International Color Consortium (ICC) profiles that describe the color rendering capabilities of the monitor after calibration. Color profiles incorporate a transfer matrix that establishes the relationship between RGB driving levels and the International Commission on Illumination (CIE) XYZ (tristimulus) values of the resulting on-screen color; the matrix is developed by displaying color patches of known RGB values on the monitor and measuring the tristimulus values with a sensor. The number and chromatic distribution of color patches varies across methods and is usually not under user control. In this work we examine the effect of employing differing calibration and profiling methods on rendition of color images. A series of color patches encoded in sRGB color space were presented on the monitor using color-management software that utilized the ICC profile produced by each method. The patches were displayed on the calibrated monitor and measured with a Minolta CS200 colorimeter. Differences in intended and achieved luminance and chromaticity were computed using the CIE DE2000 color-difference metric, in which a value of ΔE = 1 is generally considered to be approximately one just noticeable difference (JND) in color. We observed between one and 17 JND's for individual colors, depending on calibration method and target. As an extension of this fundamental work1, we further improved our calibration method by defining concrete calibration parameters for the display, using the NEC wide gamut puck, and making sure that those calibration parameters did conform, with the help of a state of the art Spectroradiometer, PR670. As a result of this addition of the PR670, and also an in-house developed method of profiling and characterization, it appears that there was much improvement in ΔE, the color difference.

Application of a parameter-estimation technique to modeling the regional aquifer underlying the eastern Snake River plain, Idaho

USGS Publications Warehouse

Garabedian, Stephen P.

1986-01-01

A nonlinear, least-squares regression technique for the estimation of ground-water flow model parameters was applied to the regional aquifer underlying the eastern Snake River Plain, Idaho. The technique uses a computer program to simulate two-dimensional, steady-state ground-water flow. Hydrologic data for the 1980 water year were used to calculate recharge rates, boundary fluxes, and spring discharges. Ground-water use was estimated from irrigated land maps and crop consumptive-use figures. These estimates of ground-water withdrawal, recharge rates, and boundary flux, along with leakance, were used as known values in the model calibration of transmissivity. Leakance values were adjusted between regression solutions by comparing model-calculated to measured spring discharges. In other simulations, recharge and leakance also were calibrated as prior-information regression parameters, which limits the variation of these parameters using a normalized standard error of estimate. Results from a best-fit model indicate a wide areal range in transmissivity from about 0.05 to 44 feet squared per second and in leakance from about 2.2x10 -9 to 6.0 x 10 -8 feet per second per foot. Along with parameter values, model statistics also were calculated, including the coefficient of correlation between calculated and observed head (0.996), the standard error of the estimates for head (40 feet), and the parameter coefficients of variation (about 10-40 percent). Additional boundary flux was added in some areas during calibration to achieve proper fit to ground-water flow directions. Model fit improved significantly when areas that violated model assumptions were removed. It also improved slightly when y-direction (northwest-southeast) transmissivity values were larger than x-direction (northeast-southwest) transmissivity values. The model was most sensitive to changes in recharge, and in some areas, to changes in transmissivity, particularly near the spring discharge area from Milner Dam to King Hill.

Coupling HYDRUS-1D Code with PA-DDS Algorithms for Inverse Calibration

NASA Astrophysics Data System (ADS)

Wang, Xiang; Asadzadeh, Masoud; Holländer, Hartmut

2017-04-01

Numerical modelling requires calibration to predict future stages. A standard method for calibration is inverse calibration where generally multi-objective optimization algorithms are used to find a solution, e.g. to find an optimal solution of the van Genuchten Mualem (VGM) parameters to predict water fluxes in the vadose zone. We coupled HYDRUS-1D with PA-DDS to add a new, robust function for inverse calibration to the model. The PA-DDS method is a recently developed multi-objective optimization algorithm, which combines Dynamically Dimensioned Search (DDS) and Pareto Archived Evolution Strategy (PAES). The results were compared to a standard method (Marquardt-Levenberg method) implemented in HYDRUS-1D. Calibration performance is evaluated using observed and simulated soil moisture at two soil layers in the Southern Abbotsford, British Columbia, Canada in the terms of the root mean squared error (RMSE) and the Nash-Sutcliffe Efficiency (NSE). Results showed low RMSE values of 0.014 and 0.017 and strong NSE values of 0.961 and 0.939. Compared to the results by the Marquardt-Levenberg method, we received better calibration results for deeper located soil sensors. However, VGM parameters were similar comparing with previous studies. Both methods are equally computational efficient. We claim that a direct implementation of PA-DDS into HYDRUS-1D should reduce the computation effort further. This, the PA-DDS method is efficient for calibrating recharge for complex vadose zone modelling with multiple soil layer and can be a potential tool for calibration of heat and solute transport. Future work should focus on the effectiveness of PA-DDS for calibrating more complex versions of the model with complex vadose zone settings, with more soil layers, and against measured heat and solute transport. Keywords: Recharge, Calibration, HYDRUS-1D, Multi-objective Optimization

Optimizing the learning rate for adaptive estimation of neural encoding models

PubMed Central

2018-01-01

Closed-loop neurotechnologies often need to adaptively learn an encoding model that relates the neural activity to the brain state, and is used for brain state decoding. The speed and accuracy of adaptive learning algorithms are critically affected by the learning rate, which dictates how fast model parameters are updated based on new observations. Despite the importance of the learning rate, currently an analytical approach for its selection is largely lacking and existing signal processing methods vastly tune it empirically or heuristically. Here, we develop a novel analytical calibration algorithm for optimal selection of the learning rate in adaptive Bayesian filters. We formulate the problem through a fundamental trade-off that learning rate introduces between the steady-state error and the convergence time of the estimated model parameters. We derive explicit functions that predict the effect of learning rate on error and convergence time. Using these functions, our calibration algorithm can keep the steady-state parameter error covariance smaller than a desired upper-bound while minimizing the convergence time, or keep the convergence time faster than a desired value while minimizing the error. We derive the algorithm both for discrete-valued spikes modeled as point processes nonlinearly dependent on the brain state, and for continuous-valued neural recordings modeled as Gaussian processes linearly dependent on the brain state. Using extensive closed-loop simulations, we show that the analytical solution of the calibration algorithm accurately predicts the effect of learning rate on parameter error and convergence time. Moreover, the calibration algorithm allows for fast and accurate learning of the encoding model and for fast convergence of decoding to accurate performance. Finally, larger learning rates result in inaccurate encoding models and decoders, and smaller learning rates delay their convergence. The calibration algorithm provides a novel analytical approach to predictably achieve a desired level of error and convergence time in adaptive learning, with application to closed-loop neurotechnologies and other signal processing domains. PMID:29813069

Optimizing the learning rate for adaptive estimation of neural encoding models.

PubMed

Hsieh, Han-Lin; Shanechi, Maryam M

2018-05-01

Closed-loop neurotechnologies often need to adaptively learn an encoding model that relates the neural activity to the brain state, and is used for brain state decoding. The speed and accuracy of adaptive learning algorithms are critically affected by the learning rate, which dictates how fast model parameters are updated based on new observations. Despite the importance of the learning rate, currently an analytical approach for its selection is largely lacking and existing signal processing methods vastly tune it empirically or heuristically. Here, we develop a novel analytical calibration algorithm for optimal selection of the learning rate in adaptive Bayesian filters. We formulate the problem through a fundamental trade-off that learning rate introduces between the steady-state error and the convergence time of the estimated model parameters. We derive explicit functions that predict the effect of learning rate on error and convergence time. Using these functions, our calibration algorithm can keep the steady-state parameter error covariance smaller than a desired upper-bound while minimizing the convergence time, or keep the convergence time faster than a desired value while minimizing the error. We derive the algorithm both for discrete-valued spikes modeled as point processes nonlinearly dependent on the brain state, and for continuous-valued neural recordings modeled as Gaussian processes linearly dependent on the brain state. Using extensive closed-loop simulations, we show that the analytical solution of the calibration algorithm accurately predicts the effect of learning rate on parameter error and convergence time. Moreover, the calibration algorithm allows for fast and accurate learning of the encoding model and for fast convergence of decoding to accurate performance. Finally, larger learning rates result in inaccurate encoding models and decoders, and smaller learning rates delay their convergence. The calibration algorithm provides a novel analytical approach to predictably achieve a desired level of error and convergence time in adaptive learning, with application to closed-loop neurotechnologies and other signal processing domains.

Simulation of nutrient and sediment concentrations and loads in the Delaware inland bays watershed: Extension of the hydrologic and water-quality model to ungaged segments

USGS Publications Warehouse

Gutierrez-Magness, Angelica L.

2006-01-01

Rapid population increases, agriculture, and industrial practices have been identified as important sources of excessive nutrients and sediments in the Delaware Inland Bays watershed. The amount and effect of excessive nutrients and sediments in the Inland Bays watershed have been well documented by the Delaware Geological Survey, the Delaware Department of Natural Resources and Environmental Control, the U.S. Environmental Protection Agency's National Estuary Program, the Delaware Center for Inland Bays, the University of Delaware, and other agencies. This documentation and data previously were used to develop a hydrologic and water-quality model of the Delaware Inland Bays watershed to simulate nutrients and sediment concentrations and loads, and to calibrate the model by comparing concentrations and streamflow data at six stations in the watershed over a limited period of time (October 1998 through April 2000). Although the model predictions of nutrient and sediment concentrations for the calibrated segments were fairly accurate, the predictions for the 28 ungaged segments located near tidal areas, where stream data were not available, were above the range of values measured in the area. The cooperative study established in 2000 by the Delaware Department of Natural Resources and Environmental Control, the Delaware Geological Survey, and the U.S. Geological Survey was extended to evaluate the model predictions in ungaged segments and to ensure that the model, developed as a planning and management tool, could accurately predict nutrient and sediment concentrations within the measured range of values in the area. The evaluation of the predictions was limited to the period of calibration (1999) of the 2003 model. To develop estimates on ungaged watersheds, parameter values from calibrated segments are transferred to the ungaged segments; however, accurate predictions are unlikely where parameter transference is subject to error. The unexpected nutrient and sediment concentrations simulated with the 2003 model were likely the result of inappropriate criteria for the transference of parameter values. From a model-simulation perspective, it is a common practice to transfer parameter values based on the similarity of soils or the similarity of land-use proportions between segments. For the Inland Bays model, the similarity of soils between segments was used as the basis to transfer parameter values. An alternative approach, which is documented in this report, is based on the similarity of the spatial distribution of the land use between segments and the similarity of land-use proportions, as these can be important factors for the transference of parameter values in lumped models. Previous work determined that the difference in the variation of runoff due to various spatial distributions of land use within a watershed can cause substantialloss of accuracy in the model predictions. The incorporation of the spatial distribution of land use to transfer parameter values from calibrated to uncalibrated segments provided more consistent and rational predictions of flow, especially during the summer, and consequently, predictions of lower nutrient concentrations during the same period. For the segments where the similarity of spatial distribution of land use was not clearly established with a calibrated segment, the similarity of the location of the most impervious areas was also used as a criterion for the transference of parameter values. The model predictions from the 28 ungaged segments were verified through comparison with measured in-stream concentrations from local and nearby streams provided by the Delaware Department of Natural Resources and Environmental Control. Model results indicated that the predicted edge-of-stream total suspended solids loads in the Inland Bays watershed were low in comparison to loads reported for the Eastern Shore of Maryland from the Chesapeake Bay watershed model. The flatness of the ter

Probabilistic calibration of the SPITFIRE fire spread model using Earth observation data

NASA Astrophysics Data System (ADS)

Gomez-Dans, Jose; Wooster, Martin; Lewis, Philip; Spessa, Allan

2010-05-01

There is a great interest in understanding how fire affects vegetation distribution and dynamics in the context of global vegetation modelling. A way to include these effects is through the development of embedded fire spread models. However, fire is a complex phenomenon, thus difficult to model. Statistical models based on fire return intervals, or fire danger indices need large amounts of data for calibration, and are often prisoner to the epoch they were calibrated to. Mechanistic models, such as SPITFIRE, try to model the complete fire phenomenon based on simple physical rules, making these models mostly independent of calibration data. However, the processes expressed in models such as SPITFIRE require many parameters. These parametrisations are often reliant on site-specific experiments, or in some other cases, paremeters might not be measured directly. Additionally, in many cases, changes in temporal and/or spatial resolution result in parameters becoming effective. To address the difficulties with parametrisation and the often-used fitting methodologies, we propose using a probabilistic framework to calibrate some areas of the SPITFIRE fire spread model. We calibrate the model against Earth Observation (EO) data, a global and ever-expanding source of relevant data. We develop a methodology that tries to incorporate the limitations of the EO data, reasonable prior values for parameters and that results in distributions of parameters, which can be used to infer uncertainty due to parameter estimates. Additionally, the covariance structure of parameters and observations is also derived, whcih can help inform data gathering efforts and model development, respectively. For this work, we focus on Southern African savannas, an important ecosystem for fire studies, and one with a good amount of EO data relevnt to fire studies. As calibration datasets, we use burned area data, estimated number of fires and vegetation moisture dynamics.

The importance of diverse data types to calibrate a watershed model of the Trout Lake Basin, Northern Wisconsin, USA

USGS Publications Warehouse

Hunt, R.J.; Feinstein, D.T.; Pint, C.D.; Anderson, M.P.

2006-01-01

As part of the USGS Water, Energy, and Biogeochemical Budgets project and the NSF Long-Term Ecological Research work, a parameter estimation code was used to calibrate a deterministic groundwater flow model of the Trout Lake Basin in northern Wisconsin. Observations included traditional calibration targets (head, lake stage, and baseflow observations) as well as unconventional targets such as groundwater flows to and from lakes, depth of a lake water plume, and time of travel. The unconventional data types were important for parameter estimation convergence and allowed the development of a more detailed parameterization capable of resolving model objectives with well-constrained parameter values. Independent estimates of groundwater inflow to lakes were most important for constraining lakebed leakance and the depth of the lake water plume was important for determining hydraulic conductivity and conceptual aquifer layering. The most important target overall, however, was a conventional regional baseflow target that led to correct distribution of flow between sub-basins and the regional system during model calibration. The use of an automated parameter estimation code: (1) facilitated the calibration process by providing a quantitative assessment of the model's ability to match disparate observed data types; and (2) allowed assessment of the influence of observed targets on the calibration process. The model calibration required the use of a 'universal' parameter estimation code in order to include all types of observations in the objective function. The methods described in this paper help address issues of watershed complexity and non-uniqueness common to deterministic watershed models. ?? 2005 Elsevier B.V. All rights reserved.

Autocalibration of a one-dimensional hydrodynamic-ecological model (DYRESM 4.0-CAEDYM 3.1) using a Monte Carlo approach: simulations of hypoxic events in a polymictic lake

NASA Astrophysics Data System (ADS)

Luo, Liancong; Hamilton, David; Lan, Jia; McBride, Chris; Trolle, Dennis

2018-03-01

Automated calibration of complex deterministic water quality models with a large number of biogeochemical parameters can reduce time-consuming iterative simulations involving empirical judgements of model fit. We undertook autocalibration of the one-dimensional hydrodynamic-ecological lake model DYRESM-CAEDYM, using a Monte Carlo sampling (MCS) method, in order to test the applicability of this procedure for shallow, polymictic Lake Rotorua (New Zealand). The calibration procedure involved independently minimizing the root-mean-square error (RMSE), maximizing the Pearson correlation coefficient (r) and Nash-Sutcliffe efficient coefficient (Nr) for comparisons of model state variables against measured data. An assigned number of parameter permutations was used for 10 000 simulation iterations. The "optimal" temperature calibration produced a RMSE of 0.54 °C, Nr value of 0.99, and r value of 0.98 through the whole water column based on comparisons with 540 observed water temperatures collected between 13 July 2007 and 13 January 2009. The modeled bottom dissolved oxygen concentration (20.5 m below surface) was compared with 467 available observations. The calculated RMSE of the simulations compared with the measurements was 1.78 mg L-1, the Nr value was 0.75, and the r value was 0.87. The autocalibrated model was further tested for an independent data set by simulating bottom-water hypoxia events from 15 January 2009 to 8 June 2011 (875 days). This verification produced an accurate simulation of five hypoxic events corresponding to DO < 2 mg L-1 during summer of 2009-2011. The RMSE was 2.07 mg L-1, Nr value 0.62, and r value of 0.81, based on the available data set of 738 days. The autocalibration software of DYRESM-CAEDYM developed here is substantially less time-consuming and more efficient in parameter optimization than traditional manual calibration which has been the standard tool practiced for similar complex water quality models.

Limits of Predictability in Commuting Flows in the Absence of Data for Calibration

PubMed Central

Yang, Yingxiang; Herrera, Carlos; Eagle, Nathan; González, Marta C.

2014-01-01

The estimation of commuting flows at different spatial scales is a fundamental problem for different areas of study. Many current methods rely on parameters requiring calibration from empirical trip volumes. Their values are often not generalizable to cases without calibration data. To solve this problem we develop a statistical expression to calculate commuting trips with a quantitative functional form to estimate the model parameter when empirical trip data is not available. We calculate commuting trip volumes at scales from within a city to an entire country, introducing a scaling parameter α to the recently proposed parameter free radiation model. The model requires only widely available population and facility density distributions. The parameter can be interpreted as the influence of the region scale and the degree of heterogeneity in the facility distribution. We explore in detail the scaling limitations of this problem, namely under which conditions the proposed model can be applied without trip data for calibration. On the other hand, when empirical trip data is available, we show that the proposed model's estimation accuracy is as good as other existing models. We validated the model in different regions in the U.S., then successfully applied it in three different countries. PMID:25012599

Impact of influent data frequency and model structure on the quality of WWTP model calibration and uncertainty.

PubMed

Cierkens, Katrijn; Plano, Salvatore; Benedetti, Lorenzo; Weijers, Stefan; de Jonge, Jarno; Nopens, Ingmar

2012-01-01

Application of activated sludge models (ASMs) to full-scale wastewater treatment plants (WWTPs) is still hampered by the problem of model calibration of these over-parameterised models. This either requires expert knowledge or global methods that explore a large parameter space. However, a better balance in structure between the submodels (ASM, hydraulic, aeration, etc.) and improved quality of influent data result in much smaller calibration efforts. In this contribution, a methodology is proposed that links data frequency and model structure to calibration quality and output uncertainty. It is composed of defining the model structure, the input data, an automated calibration, confidence interval computation and uncertainty propagation to the model output. Apart from the last step, the methodology is applied to an existing WWTP using three models differing only in the aeration submodel. A sensitivity analysis was performed on all models, allowing the ranking of the most important parameters to select in the subsequent calibration step. The aeration submodel proved very important to get good NH(4) predictions. Finally, the impact of data frequency was explored. Lowering the frequency resulted in larger deviations of parameter estimates from their default values and larger confidence intervals. Autocorrelation due to high frequency calibration data has an opposite effect on the confidence intervals. The proposed methodology opens doors to facilitate and improve calibration efforts and to design measurement campaigns.

Hydrologic Modeling in the Kenai River Watershed using Event Based Calibration

NASA Astrophysics Data System (ADS)

Wells, B.; Toniolo, H. A.; Stuefer, S. L.

2015-12-01

Understanding hydrologic changes is key for preparing for possible future scenarios. On the Kenai Peninsula in Alaska the yearly salmon runs provide a valuable stimulus to the economy. It is the focus of a large commercial fishing fleet, but also a prime tourist attraction. Modeling of anadromous waters provides a tool that assists in the prediction of future salmon run size. Beaver Creek, in Kenai, Alaska, is a lowlands stream that has been modeled using the Army Corps of Engineers event based modeling package HEC-HMS. With the use of historic precipitation and discharge data, the model was calibrated to observed discharge values. The hydrologic parameters were measured in the field or calculated, while soil parameters were estimated and adjusted during the calibration. With the calibrated parameter for HEC-HMS, discharge estimates can be used by other researches studying the area and help guide communities and officials to make better-educated decisions regarding the changing hydrology in the area and the tied economic drivers.

Inverse models: A necessary next step in ground-water modeling

USGS Publications Warehouse

Poeter, E.P.; Hill, M.C.

1997-01-01

Inverse models using, for example, nonlinear least-squares regression, provide capabilities that help modelers take full advantage of the insight available from ground-water models. However, lack of information about the requirements and benefits of inverse models is an obstacle to their widespread use. This paper presents a simple ground-water flow problem to illustrate the requirements and benefits of the nonlinear least-squares repression method of inverse modeling and discusses how these attributes apply to field problems. The benefits of inverse modeling include: (1) expedited determination of best fit parameter values; (2) quantification of the (a) quality of calibration, (b) data shortcomings and needs, and (c) confidence limits on parameter estimates and predictions; and (3) identification of issues that are easily overlooked during nonautomated calibration.Inverse models using, for example, nonlinear least-squares regression, provide capabilities that help modelers take full advantage of the insight available from ground-water models. However, lack of information about the requirements and benefits of inverse models is an obstacle to their widespread use. This paper presents a simple ground-water flow problem to illustrate the requirements and benefits of the nonlinear least-squares regression method of inverse modeling and discusses how these attributes apply to field problems. The benefits of inverse modeling include: (1) expedited determination of best fit parameter values; (2) quantification of the (a) quality of calibration, (b) data shortcomings and needs, and (c) confidence limits on parameter estimates and predictions; and (3) identification of issues that are easily overlooked during nonautomated calibration.

Using the GOCE star trackers for validating the calibration of its accelerometers

NASA Astrophysics Data System (ADS)

Visser, P. N. A. M.

2017-12-01

A method for validating the calibration parameters of the six accelerometers on board the Gravity field and steady-state Ocean Circulation Explorer (GOCE) from star tracker observations that was originally tested by an end-to-end simulation, has been updated and applied to real data from GOCE. It is shown that the method provides estimates of scale factors for all three axes of the six GOCE accelerometers that are consistent at a level significantly better than 0.01 compared to the a priori calibrated value of 1. In addition, relative accelerometer biases and drift terms were estimated consistent with values obtained by precise orbit determination, where the first GOCE accelerometer served as reference. The calibration results clearly reveal the different behavior of the sensitive and less-sensitive accelerometer axes.

Simulation of streamflow in the Pleasant, Narraguagus, Sheepscot, and Royal Rivers, Maine, using watershed models

USGS Publications Warehouse

Dudley, Robert W.; Nielsen, Martha G.

2011-01-01

The U.S. Geological Survey (USGS) began a study in 2008 to investigate anticipated changes in summer streamflows and stream temperatures in four coastal Maine river basins and the potential effects of those changes on populations of endangered Atlantic salmon. To achieve this purpose, it was necessary to characterize the quantity and timing of streamflow in these rivers by developing and evaluating a distributed-parameter watershed model for a part of each river basin by using the USGS Precipitation-Runoff Modeling System (PRMS). The GIS (geographic information system) Weasel, a USGS software application, was used to delineate the four study basins and their many subbasins, and to derive parameters for their geographic features. The models were calibrated using a four-step optimization procedure in which model output was evaluated against four datasets for calibrating solar radiation, potential evapotranspiration, annual and seasonal water balances, and daily streamflows. The calibration procedure involved thousands of model runs that used the USGS software application Luca (Let us calibrate). Luca uses the Shuffled Complex Evolution (SCE) global search algorithm to calibrate the model parameters. The calibrated watershed models performed satisfactorily, in that Nash-Sutcliffe efficiency (NSE) statistic values for the calibration periods ranged from 0.59 to 0.75 (on a scale of negative infinity to 1) and NSE statistic values for the evaluation periods ranged from 0.55 to 0.73. The calibrated watershed models simulate daily streamflow at many locations in each study basin. These models enable natural resources managers to characterize the timing and amount of streamflow in order to support a variety of water-resources efforts including water-quality calculations, assessments of water use, modeling of population dynamics and migration of Atlantic salmon, modeling and assessment of habitat, and simulation of anticipated changes to streamflow and water temperature resulting from changes forecast for air temperature and precipitation.

The impact of standard and hard-coded parameters on the hydrologic fluxes in the Noah-MP land surface model

NASA Astrophysics Data System (ADS)

Cuntz, Matthias; Mai, Juliane; Samaniego, Luis; Clark, Martyn; Wulfmeyer, Volker; Branch, Oliver; Attinger, Sabine; Thober, Stephan

2016-09-01

Land surface models incorporate a large number of process descriptions, containing a multitude of parameters. These parameters are typically read from tabulated input files. Some of these parameters might be fixed numbers in the computer code though, which hinder model agility during calibration. Here we identified 139 hard-coded parameters in the model code of the Noah land surface model with multiple process options (Noah-MP). We performed a Sobol' global sensitivity analysis of Noah-MP for a specific set of process options, which includes 42 out of the 71 standard parameters and 75 out of the 139 hard-coded parameters. The sensitivities of the hydrologic output fluxes latent heat and total runoff as well as their component fluxes were evaluated at 12 catchments within the United States with very different hydrometeorological regimes. Noah-MP's hydrologic output fluxes are sensitive to two thirds of its applicable standard parameters (i.e., Sobol' indexes above 1%). The most sensitive parameter is, however, a hard-coded value in the formulation of soil surface resistance for direct evaporation, which proved to be oversensitive in other land surface models as well. Surface runoff is sensitive to almost all hard-coded parameters of the snow processes and the meteorological inputs. These parameter sensitivities diminish in total runoff. Assessing these parameters in model calibration would require detailed snow observations or the calculation of hydrologic signatures of the runoff data. Latent heat and total runoff exhibit very similar sensitivities because of their tight coupling via the water balance. A calibration of Noah-MP against either of these fluxes should therefore give comparable results. Moreover, these fluxes are sensitive to both plant and soil parameters. Calibrating, for example, only soil parameters hence limit the ability to derive realistic model parameters. It is thus recommended to include the most sensitive hard-coded model parameters that were exposed in this study when calibrating Noah-MP.

Development of a new calibration procedure and its experimental validation applied to a human motion capture system.

PubMed

Royo Sánchez, Ana Cristina; Aguilar Martín, Juan José; Santolaria Mazo, Jorge

2014-12-01

Motion capture systems are often used for checking and analyzing human motion in biomechanical applications. It is important, in this context, that the systems provide the best possible accuracy. Among existing capture systems, optical systems are those with the highest accuracy. In this paper, the development of a new calibration procedure for optical human motion capture systems is presented. The performance and effectiveness of that new calibration procedure are also checked by experimental validation. The new calibration procedure consists of two stages. In the first stage, initial estimators of intrinsic and extrinsic parameters are sought. The camera calibration method used in this stage is the one proposed by Tsai. These parameters are determined from the camera characteristics, the spatial position of the camera, and the center of the capture volume. In the second stage, a simultaneous nonlinear optimization of all parameters is performed to identify the optimal values, which minimize the objective function. The objective function, in this case, minimizes two errors. The first error is the distance error between two markers placed in a wand. The second error is the error of position and orientation of the retroreflective markers of a static calibration object. The real co-ordinates of the two objects are calibrated in a co-ordinate measuring machine (CMM). The OrthoBio system is used to validate the new calibration procedure. Results are 90% lower than those from the previous calibration software and broadly comparable with results from a similarly configured Vicon system.

Modeling Soot Oxidation and Gasification with Bayesian Statistics

DOE PAGES

Josephson, Alexander J.; Gaffin, Neal D.; Smith, Sean T.; ...

2017-08-22

This paper presents a statistical method for model calibration using data collected from literature. The method is used to calibrate parameters for global models of soot consumption in combustion systems. This consumption is broken into two different submodels: first for oxidation where soot particles are attacked by certain oxidizing agents; second for gasification where soot particles are attacked by H 2O or CO 2 molecules. Rate data were collected from 19 studies in the literature and evaluated using Bayesian statistics to calibrate the model parameters. Bayesian statistics are valued in their ability to quantify uncertainty in modeling. The calibrated consumptionmore » model with quantified uncertainty is presented here along with a discussion of associated implications. The oxidation results are found to be consistent with previous studies. Significant variation is found in the CO 2 gasification rates.« less

Modeling Soot Oxidation and Gasification with Bayesian Statistics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Josephson, Alexander J.; Gaffin, Neal D.; Smith, Sean T.

This paper presents a statistical method for model calibration using data collected from literature. The method is used to calibrate parameters for global models of soot consumption in combustion systems. This consumption is broken into two different submodels: first for oxidation where soot particles are attacked by certain oxidizing agents; second for gasification where soot particles are attacked by H 2O or CO 2 molecules. Rate data were collected from 19 studies in the literature and evaluated using Bayesian statistics to calibrate the model parameters. Bayesian statistics are valued in their ability to quantify uncertainty in modeling. The calibrated consumptionmore » model with quantified uncertainty is presented here along with a discussion of associated implications. The oxidation results are found to be consistent with previous studies. Significant variation is found in the CO 2 gasification rates.« less

Recommended direct simulation Monte Carlo collision model parameters for modeling ionized air transport processes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Swaminathan-Gopalan, Krishnan; Stephani, Kelly A., E-mail: ksteph@illinois.edu

2016-02-15

A systematic approach for calibrating the direct simulation Monte Carlo (DSMC) collision model parameters to achieve consistency in the transport processes is presented. The DSMC collision cross section model parameters are calibrated for high temperature atmospheric conditions by matching the collision integrals from DSMC against ab initio based collision integrals that are currently employed in the Langley Aerothermodynamic Upwind Relaxation Algorithm (LAURA) and Data Parallel Line Relaxation (DPLR) high temperature computational fluid dynamics solvers. The DSMC parameter values are computed for the widely used Variable Hard Sphere (VHS) and the Variable Soft Sphere (VSS) models using the collision-specific pairing approach.more » The recommended best-fit VHS/VSS parameter values are provided over a temperature range of 1000-20 000 K for a thirteen-species ionized air mixture. Use of the VSS model is necessary to achieve consistency in transport processes of ionized gases. The agreement of the VSS model transport properties with the transport properties as determined by the ab initio collision integral fits was found to be within 6% in the entire temperature range, regardless of the composition of the mixture. The recommended model parameter values can be readily applied to any gas mixture involving binary collisional interactions between the chemical species presented for the specified temperature range.« less

Crop physiology calibration in the CLM

DOE PAGES

Bilionis, I.; Drewniak, B. A.; Constantinescu, E. M.

2015-04-15

Farming is using more of the land surface, as population increases and agriculture is increasingly applied for non-nutritional purposes such as biofuel production. This agricultural expansion exerts an increasing impact on the terrestrial carbon cycle. In order to understand the impact of such processes, the Community Land Model (CLM) has been augmented with a CLM-Crop extension that simulates the development of three crop types: maize, soybean, and spring wheat. The CLM-Crop model is a complex system that relies on a suite of parametric inputs that govern plant growth under a given atmospheric forcing and available resources. CLM-Crop development used measurementsmore » of gross primary productivity (GPP) and net ecosystem exchange (NEE) from AmeriFlux sites to choose parameter values that optimize crop productivity in the model. In this paper, we calibrate these parameters for one crop type, soybean, in order to provide a faithful projection in terms of both plant development and net carbon exchange. Calibration is performed in a Bayesian framework by developing a scalable and adaptive scheme based on sequential Monte Carlo (SMC). The model showed significant improvement of crop productivity with the new calibrated parameters. We demonstrate that the calibrated parameters are applicable across alternative years and different sites.« less

Crop physiology calibration in the CLM

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bilionis, I.; Drewniak, B. A.; Constantinescu, E. M.

Farming is using more of the land surface, as population increases and agriculture is increasingly applied for non-nutritional purposes such as biofuel production. This agricultural expansion exerts an increasing impact on the terrestrial carbon cycle. In order to understand the impact of such processes, the Community Land Model (CLM) has been augmented with a CLM-Crop extension that simulates the development of three crop types: maize, soybean, and spring wheat. The CLM-Crop model is a complex system that relies on a suite of parametric inputs that govern plant growth under a given atmospheric forcing and available resources. CLM-Crop development used measurementsmore » of gross primary productivity (GPP) and net ecosystem exchange (NEE) from AmeriFlux sites to choose parameter values that optimize crop productivity in the model. In this paper, we calibrate these parameters for one crop type, soybean, in order to provide a faithful projection in terms of both plant development and net carbon exchange. Calibration is performed in a Bayesian framework by developing a scalable and adaptive scheme based on sequential Monte Carlo (SMC). The model showed significant improvement of crop productivity with the new calibrated parameters. We demonstrate that the calibrated parameters are applicable across alternative years and different sites.« less

Simulation of the Quantity, Variability, and Timing of Streamflow in the Dennys River Basin, Maine, by Use of a Precipitation-Runoff Watershed Model

USGS Publications Warehouse

Dudley, Robert W.

2008-01-01

The U.S. Geological Survey (USGS), in cooperation with the Maine Department of Marine Resources Bureau of Sea Run Fisheries and Habitat, began a study in 2004 to characterize the quantity, variability, and timing of streamflow in the Dennys River. The study included a synoptic summary of historical streamflow data at a long-term streamflow gage, collecting data from an additional four short-term streamflow gages, and the development and evaluation of a distributed-parameter watershed model for the Dennys River Basin. The watershed model used in this investigation was the USGS Precipitation-Runoff Modeling System (PRMS). The Geographic Information System (GIS) Weasel was used to delineate the Dennys River Basin and subbasins and derive parameters for their physical geographic features. Calibration of the models used in this investigation involved a four-step procedure in which model output was evaluated against four calibration data sets using computed objective functions for solar radiation, potential evapotranspiration, annual and seasonal water budgets, and daily streamflows. The calibration procedure involved thousands of model runs and was carried out using the USGS software application Luca (Let us calibrate). Luca uses the Shuffled Complex Evolution (SCE) global search algorithm to calibrate the model parameters. The SCE method reliably produces satisfactory solutions for large, complex optimization problems. The primary calibration effort went into the Dennys main stem watershed model. Calibrated parameter values obtained for the Dennys main stem model were transferred to the Cathance Stream model, and a similar four-step SCE calibration procedure was performed; this effort was undertaken to determine the potential to transfer modeling information to a nearby basin in the same region. The calibrated Dennys main stem watershed model performed with Nash-Sutcliffe efficiency (NSE) statistic values for the calibration period and evaluation period of 0.79 and 0.76, respectively. The Cathance Stream model had an NSE value of 0.68. The Dennys River Basin models make use of limited streamflow-gaging station data and provide information to characterize subbasin hydrology. The calibrated PRMS watershed models of the Dennys River Basin provide simulated daily streamflow time series from October 1, 1985, through September 30, 2006, for nearly any location within the basin. These models enable natural-resources managers to characterize the timing and quantity of water moving through the basin to support many endeavors including geochemical calculations, water-use assessment, Atlantic salmon population dynamics and migration modeling, habitat modeling and assessment, and other resource-management scenario evaluations. Characterizing streamflow contributions from subbasins in the basin and the relative amounts of surface- and ground-water contributions to streamflow throughout the basin will lead to a better understanding of water quantity and quality in the basin. Improved water-resources information will support Atlantic salmon protection efforts.

High-precision method of binocular camera calibration with a distortion model.

PubMed

Li, Weimin; Shan, Siyu; Liu, Hui

2017-03-10

A high-precision camera calibration method for binocular stereo vision system based on a multi-view template and alternative bundle adjustment is presented in this paper. The proposed method could be achieved by taking several photos on a specially designed calibration template that has diverse encoded points in different orientations. In this paper, the method utilized the existing algorithm used for monocular camera calibration to obtain the initialization, which involves a camera model, including radial lens distortion and tangential distortion. We created a reference coordinate system based on the left camera coordinate to optimize the intrinsic parameters of left camera through alternative bundle adjustment to obtain optimal values. Then, optimal intrinsic parameters of the right camera can be obtained through alternative bundle adjustment when we create a reference coordinate system based on the right camera coordinate. We also used all intrinsic parameters that were acquired to optimize extrinsic parameters. Thus, the optimal lens distortion parameters and intrinsic and extrinsic parameters were obtained. Synthetic and real data were used to test the method. The simulation results demonstrate that the maximum mean absolute relative calibration errors are about 3.5e-6 and 1.2e-6 for the focal length and the principal point, respectively, under zero-mean Gaussian noise with 0.05 pixels standard deviation. The real result shows that the reprojection error of our model is about 0.045 pixels with the relative standard deviation of 1.0e-6 over the intrinsic parameters. The proposed method is convenient, cost-efficient, highly precise, and simple to carry out.

Reliable noninvasive measurement of blood gases

DOEpatents

Thomas, Edward V.; Robinson, Mark R.; Haaland, David M.; Alam, Mary K.

1994-01-01

Methods and apparatus for, preferably, determining noninvasively and in vivo at least two of the five blood gas parameters (i.e., pH, PCO.sub.2, [HCO.sub.3.sup.- ], PO.sub.2, and O.sub.2 sat.) in a human. The non-invasive method includes the steps of: generating light at three or more different wavelengths in the range of 500 nm to 2500 nm; irradiating blood containing tissue; measuring the intensities of the wavelengths emerging from the blood containing tissue to obtain a set of at least three spectral intensities v. wavelengths; and determining the unknown values of at least two of pH, [HCO.sub.3.sup.- ], PCO.sub.2 and a measure of oxygen concentration. The determined values are within the physiological ranges observed in blood containing tissue. The method also includes the steps of providing calibration samples, determining if the spectral intensities v. wavelengths from the tissue represents an outlier, and determining if any of the calibration samples represents an outlier. The determination of the unknown values is performed by at least one multivariate algorithm using two or more variables and at least one calibration model. Preferably, there is a separate calibration for each blood gas parameter being determined. The method can be utilized in a pulse mode and can also be used invasively. The apparatus includes a tissue positioning device, a source, at least one detector, electronics, a microprocessor, memory, and apparatus for indicating the determined values.

Simulations of potential future conditions in the cache critical groundwater area, Arkansas

USGS Publications Warehouse

Rashid, Haveen M.; Clark, Brian R.; Mahdi, Hanan H.; Rifai, Hanadi S.; Al-Shukri, Haydar J.

2015-01-01

A three-dimensional finite-difference model for part of the Mississippi River Valley alluvial aquifer in the Cache Critical Groundwater Area of eastern Arkansas was constructed to simulate potential future conditions of groundwater flow. The objectives of this study were to test different pilot point distributions to find reasonable estimates of aquifer properties for the alluvial aquifer, to simulate flux from rivers, and to demonstrate how changes in pumping rates for different scenarios affect areas of long-term water-level declines over time. The model was calibrated using the parameter estimation code. Additional calibration was achieved using pilot points with regularization and singular value decomposition. Pilot point parameter values were estimated at a number of discrete locations in the study area to obtain reasonable estimates of aquifer properties. Nine pumping scenarios for the years 2011 to 2020 were tested and compared to the simulated water-level heads from 2010. Hydraulic conductivity values from pilot point calibration ranged between 42 and 173 m/d. Specific yield values ranged between 0.19 and 0.337. Recharge rates ranged between 0.00009 and 0.0006 m/d. The model was calibrated using 2,322 hydraulic head measurements for the years 2000 to 2010 from 150 observation wells located in the study area. For all scenarios, the volume of water depleted ranged between 5.7 and 23.3 percent, except in Scenario 2 (minimum pumping rates), in which the volume increased by 2.5 percent.

Mathematical Model and Calibration Procedure of a PSD Sensor Used in Local Positioning Systems.

PubMed

Rodríguez-Navarro, David; Lázaro-Galilea, José Luis; Bravo-Muñoz, Ignacio; Gardel-Vicente, Alfredo; Domingo-Perez, Francisco; Tsirigotis, Georgios

2016-09-15

Here, we propose a mathematical model and a calibration procedure for a PSD (position sensitive device) sensor equipped with an optical system, to enable accurate measurement of the angle of arrival of one or more beams of light emitted by infrared (IR) transmitters located at distances of between 4 and 6 m. To achieve this objective, it was necessary to characterize the intrinsic parameters that model the system and obtain their values. This first approach was based on a pin-hole model, to which system nonlinearities were added, and this was used to model the points obtained with the nA currents provided by the PSD. In addition, we analyzed the main sources of error, including PSD sensor signal noise, gain factor imbalances and PSD sensor distortion. The results indicated that the proposed model and method provided satisfactory calibration and yielded precise parameter values, enabling accurate measurement of the angle of arrival with a low degree of error, as evidenced by the experimental results.

Method for calibrating mass spectrometers

DOEpatents

Anderson, Gordon A [Benton City, WA; Brands, Michael D [Richland, WA; Bruce, James E [Schwenksville, PA; Pasa-Tolic, Ljiljana [Richland, WA; Smith, Richard D [Richland, WA

2002-12-24

A method whereby a mass spectra generated by a mass spectrometer is calibrated by shifting the parameters used by the spectrometer to assign masses to the spectra in a manner which reconciles the signal of ions within the spectra having equal mass but differing charge states, or by reconciling ions having known differences in mass to relative values consistent with those known differences. In this manner, the mass spectrometer is calibrated without the need for standards while allowing the generation of a highly accurate mass spectra by the instrument.

Calibration and data collection protocols for reliable lattice parameter values in electron pair distribution function studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abeykoon, A. M. Milinda; Hu, Hefei; Wu, Lijun

2015-01-30

Different protocols for calibrating electron pair distribution function (ePDF) measurements are explored and described for quantitative studies on nanomaterials. It is found that the most accurate approach to determine the camera length is to use a standard calibration sample of Au nanoparticles from the National Institute of Standards and Technology. Different protocols for data collection are also explored, as are possible operational errors, to find the best approaches for accurate data collection for quantitative ePDF studies.

Calibration and data collection protocols for reliable lattice parameter values in electron pair distribution function (ePDF) studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abeykoon, A. M. Milinda; Hu, Hefei; Wu, Lijun

2015-02-01

We explore and describe different protocols for calibrating electron pair distribution function (ePDF) measurements for quantitative studies on nano-materials. We find the most accurate approach to determine the camera-length is to use a standard calibration sample of Au nanoparticles from National Institute of Standards and Technology. Different protocols for data collection are also explored, as are possible operational errors, to find the best approaches for accurate data collection for quantitative ePDF studies.

Resolving model parameter values from carbon and nitrogen stock measurements in a wide range of tropical mature forests using nonlinear inversion and regression trees

USGS Publications Warehouse

Liu, S.; Anderson, P.; Zhou, G.; Kauffman, B.; Hughes, F.; Schimel, D.; Watson, Vicente; Tosi, Joseph

2008-01-01

Objectively assessing the performance of a model and deriving model parameter values from observations are critical and challenging in landscape to regional modeling. In this paper, we applied a nonlinear inversion technique to calibrate the ecosystem model CENTURY against carbon (C) and nitrogen (N) stock measurements collected from 39 mature tropical forest sites in seven life zones in Costa Rica. Net primary productivity from the Moderate-Resolution Imaging Spectroradiometer (MODIS), C and N stocks in aboveground live biomass, litter, coarse woody debris (CWD), and in soils were used to calibrate the model. To investigate the resolution of available observations on the number of adjustable parameters, inversion was performed using nine setups of adjustable parameters. Statistics including observation sensitivity, parameter correlation coefficient, parameter sensitivity, and parameter confidence limits were used to evaluate the information content of observations, resolution of model parameters, and overall model performance. Results indicated that soil organic carbon content, soil nitrogen content, and total aboveground biomass carbon had the highest information contents, while measurements of carbon in litter and nitrogen in CWD contributed little to the parameter estimation processes. The available information could resolve the values of 2-4 parameters. Adjusting just one parameter resulted in under-fitting and unacceptable model performance, while adjusting five parameters simultaneously led to over-fitting. Results further indicated that the MODIS NPP values were compressed as compared with the spatial variability of net primary production (NPP) values inferred from inverse modeling. Using inverse modeling to infer NPP and other sensitive model parameters from C and N stock observations provides an opportunity to utilize data collected by national to regional forest inventory systems to reduce the uncertainties in the carbon cycle and generate valuable databases to validate and improve MODIS NPP algorithms.

Potential application of item-response theory to interpretation of medical codes in electronic patient records

PubMed Central

2011-01-01

Background Electronic patient records are generally coded using extensive sets of codes but the significance of the utilisation of individual codes may be unclear. Item response theory (IRT) models are used to characterise the psychometric properties of items included in tests and questionnaires. This study asked whether the properties of medical codes in electronic patient records may be characterised through the application of item response theory models. Methods Data were provided by a cohort of 47,845 participants from 414 family practices in the UK General Practice Research Database (GPRD) with a first stroke between 1997 and 2006. Each eligible stroke code, out of a set of 202 OXMIS and Read codes, was coded as either recorded or not recorded for each participant. A two parameter IRT model was fitted using marginal maximum likelihood estimation. Estimated parameters from the model were considered to characterise each code with respect to the latent trait of stroke diagnosis. The location parameter is referred to as a calibration parameter, while the slope parameter is referred to as a discrimination parameter. Results There were 79,874 stroke code occurrences available for analysis. Utilisation of codes varied between family practices with intraclass correlation coefficients of up to 0.25 for the most frequently used codes. IRT analyses were restricted to 110 Read codes. Calibration and discrimination parameters were estimated for 77 (70%) codes that were endorsed for 1,942 stroke patients. Parameters were not estimated for the remaining more frequently used codes. Discrimination parameter values ranged from 0.67 to 2.78, while calibration parameters values ranged from 4.47 to 11.58. The two parameter model gave a better fit to the data than either the one- or three-parameter models. However, high chi-square values for about a fifth of the stroke codes were suggestive of poor item fit. Conclusion The application of item response theory models to coded electronic patient records might potentially contribute to identifying medical codes that offer poor discrimination or low calibration. This might indicate the need for improved coding sets or a requirement for improved clinical coding practice. However, in this study estimates were only obtained for a small proportion of participants and there was some evidence of poor model fit. There was also evidence of variation in the utilisation of codes between family practices raising the possibility that, in practice, properties of codes may vary for different coders. PMID:22176509

Computer-Based Model Calibration and Uncertainty Analysis: Terms and Concepts

DTIC Science & Technology

2015-07-01

uncertainty analyses throughout the lifecycle of planning, designing, and operating of Civil Works flood risk management projects as described in...value 95% of the time. In the frequentist approach to PE, model parameters area regarded as having true values, and their estimate is based on the...in catchment models. 1. Evaluating parameter uncertainty. Water Resources Research 19(5):1151–1172. Lee, P. M. 2012. Bayesian statistics: An

Resolving model parameter values from carbon and nitrogen stock measurements in a wide range of tropical mature forests using nonlinear inversion and regression trees

Treesearch

Shuguang Liua; Pamela Anderson; Guoyi Zhoud; Boone Kauffman; Flint Hughes; David Schimel; Vicente Watson; Joseph Tosi

2008-01-01

Objectively assessing the performance of a model and deriving model parameter values from observations are critical and challenging in landscape to regional modeling. In this paper, we applied a nonlinear inversion technique to calibrate the ecosystem model CENTURY against carbon (C) and nitrogen (N) stock measurements collected from 39 mature tropical forest sites in...

Detecting influential observations in nonlinear regression modeling of groundwater flow

USGS Publications Warehouse

Yager, Richard M.

1998-01-01

Nonlinear regression is used to estimate optimal parameter values in models of groundwater flow to ensure that differences between predicted and observed heads and flows do not result from nonoptimal parameter values. Parameter estimates can be affected, however, by observations that disproportionately influence the regression, such as outliers that exert undue leverage on the objective function. Certain statistics developed for linear regression can be used to detect influential observations in nonlinear regression if the models are approximately linear. This paper discusses the application of Cook's D, which measures the effect of omitting a single observation on a set of estimated parameter values, and the statistical parameter DFBETAS, which quantifies the influence of an observation on each parameter. The influence statistics were used to (1) identify the influential observations in the calibration of a three-dimensional, groundwater flow model of a fractured-rock aquifer through nonlinear regression, and (2) quantify the effect of omitting influential observations on the set of estimated parameter values. Comparison of the spatial distribution of Cook's D with plots of model sensitivity shows that influential observations correspond to areas where the model heads are most sensitive to certain parameters, and where predicted groundwater flow rates are largest. Five of the six discharge observations were identified as influential, indicating that reliable measurements of groundwater flow rates are valuable data in model calibration. DFBETAS are computed and examined for an alternative model of the aquifer system to identify a parameterization error in the model design that resulted in overestimation of the effect of anisotropy on horizontal hydraulic conductivity.

Calibration and compensation method of three-axis geomagnetic sensor based on pre-processing total least square iteration

NASA Astrophysics Data System (ADS)

Zhou, Y.; Zhang, X.; Xiao, W.

2018-04-01

As the geomagnetic sensor is susceptible to interference, a pre-processing total least square iteration method is proposed for calibration compensation. Firstly, the error model of the geomagnetic sensor is analyzed and the correction model is proposed, then the characteristics of the model are analyzed and converted into nine parameters. The geomagnetic data is processed by Hilbert transform (HHT) to improve the signal-to-noise ratio, and the nine parameters are calculated by using the combination of Newton iteration method and the least squares estimation method. The sifter algorithm is used to filter the initial value of the iteration to ensure that the initial error is as small as possible. The experimental results show that this method does not need additional equipment and devices, can continuously update the calibration parameters, and better than the two-step estimation method, it can compensate geomagnetic sensor error well.

Calibration of CR-39-based thoron progeny device.

PubMed

Fábián, F; Csordás, A; Shahrokhi, A; Somlai, J; Kovács, T

2014-07-01

Radon isotopes and their progenies have proven significant role in respiratory tumour formation. In most cases, the radiological effect of one of the radon isotopes (thoron) and its progenies has been neglected together with its measurement technique; however, latest surveys proved that thoron's existence is expectable in flats and in workplace in Europe. Detectors based on different track detector measurement technologies have recently spread for measuring thoron progenies; however, the calibration is not yet completely elaborated. This study deals with the calibration of the track detector measurement method suitable for measuring thoron progenies using different devices with measurement techniques capable of measuring several progenies (Pylon AB5 and WLx, Sarad EQF 3220). The calibration factor values related to the thoron progeny monitors, the measurement uncertainty, reproducibility and other parameters were found using the calibration chamber. In the future, the effects of the different parameters (aerosol distribution, etc.) will be determined. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Optimum data weighting and error calibration for estimation of gravitational parameters

NASA Technical Reports Server (NTRS)

Lerch, F. J.

1989-01-01

A new technique was developed for the weighting of data from satellite tracking systems in order to obtain an optimum least squares solution and an error calibration for the solution parameters. Data sets from optical, electronic, and laser systems on 17 satellites in GEM-T1 (Goddard Earth Model, 36x36 spherical harmonic field) were employed toward application of this technique for gravity field parameters. Also, GEM-T2 (31 satellites) was recently computed as a direct application of the method and is summarized here. The method employs subset solutions of the data associated with the complete solution and uses an algorithm to adjust the data weights by requiring the differences of parameters between solutions to agree with their error estimates. With the adjusted weights the process provides for an automatic calibration of the error estimates for the solution parameters. The data weights derived are generally much smaller than corresponding weights obtained from nominal values of observation accuracy or residuals. Independent tests show significant improvement for solutions with optimal weighting as compared to the nominal weighting. The technique is general and may be applied to orbit parameters, station coordinates, or other parameters than the gravity model.

A Regionalization Approach to select the final watershed parameter set among the Pareto solutions

NASA Astrophysics Data System (ADS)

Park, G. H.; Micheletty, P. D.; Carney, S.; Quebbeman, J.; Day, G. N.

2017-12-01

The calibration of hydrological models often results in model parameters that are inconsistent with those from neighboring basins. Considering that physical similarity exists within neighboring basins some of the physically related parameters should be consistent among them. Traditional manual calibration techniques require an iterative process to make the parameters consistent, which takes additional effort in model calibration. We developed a multi-objective optimization procedure to calibrate the National Weather Service (NWS) Research Distributed Hydrological Model (RDHM), using the Nondominant Sorting Genetic Algorithm (NSGA-II) with expert knowledge of the model parameter interrelationships one objective function. The multi-objective algorithm enables us to obtain diverse parameter sets that are equally acceptable with respect to the objective functions and to choose one from the pool of the parameter sets during a subsequent regionalization step. Although all Pareto solutions are non-inferior, we exclude some of the parameter sets that show extremely values for any of the objective functions to expedite the selection process. We use an apriori model parameter set derived from the physical properties of the watershed (Koren et al., 2000) to assess the similarity for a given parameter across basins. Each parameter is assigned a weight based on its assumed similarity, such that parameters that are similar across basins are given higher weights. The parameter weights are useful to compute a closeness measure between Pareto sets of nearby basins. The regionalization approach chooses the Pareto parameter sets that minimize the closeness measure of the basin being regionalized. The presentation will describe the results of applying the regionalization approach to a set of pilot basins in the Upper Colorado basin as part of a NASA-funded project.

Out-of-Focus Projector Calibration Method with Distortion Correction on the Projection Plane in the Structured Light Three-Dimensional Measurement System.

PubMed

Zhang, Jiarui; Zhang, Yingjie; Chen, Bo

2017-12-20

The three-dimensional measurement system with a binary defocusing technique is widely applied in diverse fields. The measurement accuracy is mainly determined by out-of-focus projector calibration accuracy. In this paper, a high-precision out-of-focus projector calibration method that is based on distortion correction on the projection plane and nonlinear optimization algorithm is proposed. To this end, the paper experimentally presents the principle that the projector has noticeable distortions outside its focus plane. In terms of this principle, the proposed method uses a high-order radial and tangential lens distortion representation on the projection plane to correct the calibration residuals caused by projection distortion. The final accuracy parameters of out-of-focus projector were obtained using a nonlinear optimization algorithm with good initial values, which were provided by coarsely calibrating the parameters of the out-of-focus projector on the focal and projection planes. Finally, the experimental results demonstrated that the proposed method can accuracy calibrate an out-of-focus projector, regardless of the amount of defocusing.

A new calibration of the effective scattering albedo and soil roughness parameters in the SMOS SM retrieval algorithm

NASA Astrophysics Data System (ADS)

Fernandez-Moran, R.; Wigneron, J.-P.; De Lannoy, G.; Lopez-Baeza, E.; Parrens, M.; Mialon, A.; Mahmoodi, A.; Al-Yaari, A.; Bircher, S.; Al Bitar, A.; Richaume, P.; Kerr, Y.

2017-10-01

This study focuses on the calibration of the effective vegetation scattering albedo (ω) and surface soil roughness parameters (HR, and NRp, p = H,V) in the Soil Moisture (SM) retrieval from L-band passive microwave observations using the L-band Microwave Emission of the Biosphere (L-MEB) model. In the current Soil Moisture and Ocean Salinity (SMOS) Level 2 (L2), v620, and Level 3 (L3), v300, SM retrieval algorithms, low vegetated areas are parameterized by ω = 0 and HR = 0.1, whereas values of ω = 0.06 - 0.08 and HR = 0.3 are used for forests. Several parameterizations of the vegetation and soil roughness parameters (ω, HR and NRp, p = H,V) were tested in this study, treating SMOS SM retrievals as homogeneous over each pixel instead of retrieving SM over a representative fraction of the pixel, as implemented in the operational SMOS L2 and L3 algorithms. Globally-constant values of ω = 0.10, HR = 0.4 and NRp = -1 (p = H,V) were found to yield SM retrievals that compared best with in situ SM data measured at many sites worldwide from the International Soil Moisture Network (ISMN). The calibration was repeated for collections of in situ sites classified in different land cover categories based on the International Geosphere-Biosphere Programme (IGBP) scheme. Depending on the IGBP land cover class, values of ω and HR varied, respectively, in the range 0.08-0.12 and 0.1-0.5. A validation exercise based on in situ measurements confirmed that using either a global or an IGBP-based calibration, there was an improvement in the accuracy of the SM retrievals compared to the SMOS L3 SM product considering all statistical metrics (R = 0.61, bias = -0.019 m3 m-3, ubRMSE = 0.062 m3 m-3 for the IGBP-based calibration; against R = 0.54, bias = -0.034 m3 m-3 and ubRMSE = 0.070 m3 m-3 for the SMOS L3 SM product). This result is a key step in the calibration of the roughness and vegetation parameters in the operational SMOS retrieval algorithm. The approach presented here is the core of a new forthcoming SMOS optimized SM product.

Global Parameter Optimization of CLM4.5 Using Sparse-Grid Based Surrogates

NASA Astrophysics Data System (ADS)

Lu, D.; Ricciuto, D. M.; Gu, L.

2016-12-01

Calibration of the Community Land Model (CLM) is challenging because of its model complexity, large parameter sets, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near-optimal solution within an affordable time. The goal of this study is to calibrate some of the CLM parameters in order to improve model projection of carbon fluxes. To this end, we propose a computationally efficient global optimization procedure using sparse-grid based surrogates. We first use advanced sparse grid (SG) interpolation to construct a surrogate system of the actual CLM model, and then we calibrate the surrogate model in the optimization process. As the surrogate model is a polynomial whose evaluation is fast, it can be efficiently evaluated with sufficiently large number of times in the optimization, which facilitates the global search. We calibrate five parameters against 12 months of GPP, NEP, and TLAI data from the U.S. Missouri Ozark (US-MOz) tower. The results indicate that an accurate surrogate model can be created for the CLM4.5 with a relatively small number of SG points (i.e., CLM4.5 simulations), and the application of the optimized parameters leads to a higher predictive capacity than the default parameter values in the CLM4.5 for the US-MOz site.

Inverse modeling of hydrologic parameters using surface flux and runoff observations in the Community Land Model

NASA Astrophysics Data System (ADS)

Sun, Y.; Hou, Z.; Huang, M.; Tian, F.; Leung, L. Ruby

2013-12-01

This study demonstrates the possibility of inverting hydrologic parameters using surface flux and runoff observations in version 4 of the Community Land Model (CLM4). Previous studies showed that surface flux and runoff calculations are sensitive to major hydrologic parameters in CLM4 over different watersheds, and illustrated the necessity and possibility of parameter calibration. Both deterministic least-square fitting and stochastic Markov-chain Monte Carlo (MCMC)-Bayesian inversion approaches are evaluated by applying them to CLM4 at selected sites with different climate and soil conditions. The unknowns to be estimated include surface and subsurface runoff generation parameters and vadose zone soil water parameters. We find that using model parameters calibrated by the sampling-based stochastic inversion approaches provides significant improvements in the model simulations compared to using default CLM4 parameter values, and that as more information comes in, the predictive intervals (ranges of posterior distributions) of the calibrated parameters become narrower. In general, parameters that are identified to be significant through sensitivity analyses and statistical tests are better calibrated than those with weak or nonlinear impacts on flux or runoff observations. Temporal resolution of observations has larger impacts on the results of inverse modeling using heat flux data than runoff data. Soil and vegetation cover have important impacts on parameter sensitivities, leading to different patterns of posterior distributions of parameters at different sites. Overall, the MCMC-Bayesian inversion approach effectively and reliably improves the simulation of CLM under different climates and environmental conditions. Bayesian model averaging of the posterior estimates with different reference acceptance probabilities can smooth the posterior distribution and provide more reliable parameter estimates, but at the expense of wider uncertainty bounds.

Inverse estimation of parameters for an estuarine eutrophication model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shen, J.; Kuo, A.Y.

1996-11-01

An inverse model of an estuarine eutrophication model with eight state variables is developed. It provides a framework to estimate parameter values of the eutrophication model by assimilation of concentration data of these state variables. The inverse model using the variational technique in conjunction with a vertical two-dimensional eutrophication model is general enough to be applicable to aid model calibration. The formulation is illustrated by conducting a series of numerical experiments for the tidal Rappahannock River, a western shore tributary of the Chesapeake Bay. The numerical experiments of short-period model simulations with different hypothetical data sets and long-period model simulationsmore » with limited hypothetical data sets demonstrated that the inverse model can be satisfactorily used to estimate parameter values of the eutrophication model. The experiments also showed that the inverse model is useful to address some important questions, such as uniqueness of the parameter estimation and data requirements for model calibration. Because of the complexity of the eutrophication system, degrading of speed of convergence may occur. Two major factors which cause degradation of speed of convergence are cross effects among parameters and the multiple scales involved in the parameter system.« less

A Bayesian procedure for evaluating the frequency of calibration factor updates in highway safety manual (HSM) applications.

PubMed

Saha, Dibakar; Alluri, Priyanka; Gan, Albert

2017-01-01

The Highway Safety Manual (HSM) presents statistical models to quantitatively estimate an agency's safety performance. The models were developed using data from only a few U.S. states. To account for the effects of the local attributes and temporal factors on crash occurrence, agencies are required to calibrate the HSM-default models for crash predictions. The manual suggests updating calibration factors every two to three years, or preferably on an annual basis. Given that the calibration process involves substantial time, effort, and resources, a comprehensive analysis of the required calibration factor update frequency is valuable to the agencies. Accordingly, the objective of this study is to evaluate the HSM's recommendation and determine the required frequency of calibration factor updates. A robust Bayesian estimation procedure is used to assess the variation between calibration factors computed annually, biennially, and triennially using data collected from over 2400 miles of segments and over 700 intersections on urban and suburban facilities in Florida. Bayesian model yields a posterior distribution of the model parameters that give credible information to infer whether the difference between calibration factors computed at specified intervals is credibly different from the null value which represents unaltered calibration factors between the comparison years or in other words, zero difference. The concept of the null value is extended to include the range of values that are practically equivalent to zero. Bayesian inference shows that calibration factors based on total crash frequency are required to be updated every two years in cases where the variations between calibration factors are not greater than 0.01. When the variations are between 0.01 and 0.05, calibration factors based on total crash frequency could be updated every three years. Copyright © 2016 Elsevier Ltd. All rights reserved.

Evaluation of Potential Evapotranspiration from a Hydrologic Model on a National Scale

NASA Astrophysics Data System (ADS)

Hakala, K. A.; Hay, L.; Markstrom, S. L.

2014-12-01

The US Geological Survey has developed a National Hydrologic Model (NHM) to support coordinated, comprehensive and consistent hydrologic model development and facilitate the application of simulations on the scale of the continental US. The NHM has a consistent geospatial fabric for modeling, consisting of over 100,000 hydrologic response units (HRUs). Each HRU requires accurate parameter estimates, some of which are attained from automated calibration. However, improved calibration can be achieved by initially utilizing as many parameters as possible from national data sets. This presentation investigates the effectiveness of calculating potential evapotranspiration (PET) parameters based on mean monthly values from the NOAA PET Atlas. Additional PET products are then used to evaluate the PET parameters. Effectively utilizing existing national-scale data sets can simplify the effort in establishing a robust NHM.

Approaches to highly parameterized inversion: A guide to using PEST for model-parameter and predictive-uncertainty analysis

USGS Publications Warehouse

Doherty, John E.; Hunt, Randall J.; Tonkin, Matthew J.

2010-01-01

Analysis of the uncertainty associated with parameters used by a numerical model, and with predictions that depend on those parameters, is fundamental to the use of modeling in support of decisionmaking. Unfortunately, predictive uncertainty analysis with regard to models can be very computationally demanding, due in part to complex constraints on parameters that arise from expert knowledge of system properties on the one hand (knowledge constraints) and from the necessity for the model parameters to assume values that allow the model to reproduce historical system behavior on the other hand (calibration constraints). Enforcement of knowledge and calibration constraints on parameters used by a model does not eliminate the uncertainty in those parameters. In fact, in many cases, enforcement of calibration constraints simply reduces the uncertainties associated with a number of broad-scale combinations of model parameters that collectively describe spatially averaged system properties. The uncertainties associated with other combinations of parameters, especially those that pertain to small-scale parameter heterogeneity, may not be reduced through the calibration process. To the extent that a prediction depends on system-property detail, its postcalibration variability may be reduced very little, if at all, by applying calibration constraints; knowledge constraints remain the only limits on the variability of predictions that depend on such detail. Regrettably, in many common modeling applications, these constraints are weak. Though the PEST software suite was initially developed as a tool for model calibration, recent developments have focused on the evaluation of model-parameter and predictive uncertainty. As a complement to functionality that it provides for highly parameterized inversion (calibration) by means of formal mathematical regularization techniques, the PEST suite provides utilities for linear and nonlinear error-variance and uncertainty analysis in these highly parameterized modeling contexts. Availability of these utilities is particularly important because, in many cases, a significant proportion of the uncertainty associated with model parameters-and the predictions that depend on them-arises from differences between the complex properties of the real world and the simplified representation of those properties that is expressed by the calibrated model. This report is intended to guide intermediate to advanced modelers in the use of capabilities available with the PEST suite of programs for evaluating model predictive error and uncertainty. A brief theoretical background is presented on sources of parameter and predictive uncertainty and on the means for evaluating this uncertainty. Applications of PEST tools are then discussed for overdetermined and underdetermined problems, both linear and nonlinear. PEST tools for calculating contributions to model predictive uncertainty, as well as optimization of data acquisition for reducing parameter and predictive uncertainty, are presented. The appendixes list the relevant PEST variables, files, and utilities required for the analyses described in the document.

Application of nonlinear least-squares regression to ground-water flow modeling, west-central Florida

USGS Publications Warehouse

Yobbi, D.K.

2000-01-01

A nonlinear least-squares regression technique for estimation of ground-water flow model parameters was applied to an existing model of the regional aquifer system underlying west-central Florida. The regression technique minimizes the differences between measured and simulated water levels. Regression statistics, including parameter sensitivities and correlations, were calculated for reported parameter values in the existing model. Optimal parameter values for selected hydrologic variables of interest are estimated by nonlinear regression. Optimal estimates of parameter values are about 140 times greater than and about 0.01 times less than reported values. Independently estimating all parameters by nonlinear regression was impossible, given the existing zonation structure and number of observations, because of parameter insensitivity and correlation. Although the model yields parameter values similar to those estimated by other methods and reproduces the measured water levels reasonably accurately, a simpler parameter structure should be considered. Some possible ways of improving model calibration are to: (1) modify the defined parameter-zonation structure by omitting and/or combining parameters to be estimated; (2) carefully eliminate observation data based on evidence that they are likely to be biased; (3) collect additional water-level data; (4) assign values to insensitive parameters, and (5) estimate the most sensitive parameters first, then, using the optimized values for these parameters, estimate the entire data set.

Uncertainty quantification and propagation in dynamic models using ambient vibration measurements, application to a 10-story building

NASA Astrophysics Data System (ADS)

Behmanesh, Iman; Yousefianmoghadam, Seyedsina; Nozari, Amin; Moaveni, Babak; Stavridis, Andreas

2018-07-01

This paper investigates the application of Hierarchical Bayesian model updating for uncertainty quantification and response prediction of civil structures. In this updating framework, structural parameters of an initial finite element (FE) model (e.g., stiffness or mass) are calibrated by minimizing error functions between the identified modal parameters and the corresponding parameters of the model. These error functions are assumed to have Gaussian probability distributions with unknown parameters to be determined. The estimated parameters of error functions represent the uncertainty of the calibrated model in predicting building's response (modal parameters here). The focus of this paper is to answer whether the quantified model uncertainties using dynamic measurement at building's reference/calibration state can be used to improve the model prediction accuracies at a different structural state, e.g., damaged structure. Also, the effects of prediction error bias on the uncertainty of the predicted values is studied. The test structure considered here is a ten-story concrete building located in Utica, NY. The modal parameters of the building at its reference state are identified from ambient vibration data and used to calibrate parameters of the initial FE model as well as the error functions. Before demolishing the building, six of its exterior walls were removed and ambient vibration measurements were also collected from the structure after the wall removal. These data are not used to calibrate the model; they are only used to assess the predicted results. The model updating framework proposed in this paper is applied to estimate the modal parameters of the building at its reference state as well as two damaged states: moderate damage (removal of four walls) and severe damage (removal of six walls). Good agreement is observed between the model-predicted modal parameters and those identified from vibration tests. Moreover, it is shown that including prediction error bias in the updating process instead of commonly-used zero-mean error function can significantly reduce the prediction uncertainties.

The worth of data to reduce predictive uncertainty of an integrated catchment model by multi-constraint calibration

NASA Astrophysics Data System (ADS)

Koch, J.; Jensen, K. H.; Stisen, S.

2017-12-01

Hydrological models that integrate numerical process descriptions across compartments of the water cycle are typically required to undergo thorough model calibration in order to estimate suitable effective model parameters. In this study, we apply a spatially distributed hydrological model code which couples the saturated zone with the unsaturated zone and the energy portioning at the land surface. We conduct a comprehensive multi-constraint model calibration against nine independent observational datasets which reflect both the temporal and the spatial behavior of hydrological response of a 1000km2 large catchment in Denmark. The datasets are obtained from satellite remote sensing and in-situ measurements and cover five keystone hydrological variables: discharge, evapotranspiration, groundwater head, soil moisture and land surface temperature. Results indicate that a balanced optimization can be achieved where errors on objective functions for all nine observational datasets can be reduced simultaneously. The applied calibration framework was tailored with focus on improving the spatial pattern performance; however results suggest that the optimization is still more prone to improve the temporal dimension of model performance. This study features a post-calibration linear uncertainty analysis. This allows quantifying parameter identifiability which is the worth of a specific observational dataset to infer values to model parameters through calibration. Furthermore the ability of an observation to reduce predictive uncertainty is assessed as well. Such findings determine concrete implications on the design of model calibration frameworks and, in more general terms, the acquisition of data in hydrological observatories.

Characterization and Uncertainty Analysis of a Reference Pressure Measurement System for Wind Tunnels

NASA Technical Reports Server (NTRS)

Amer, Tahani; Tripp, John; Tcheng, Ping; Burkett, Cecil; Sealey, Bradley

2004-01-01

This paper presents the calibration results and uncertainty analysis of a high-precision reference pressure measurement system currently used in wind tunnels at the NASA Langley Research Center (LaRC). Sensors, calibration standards, and measurement instruments are subject to errors due to aging, drift with time, environment effects, transportation, the mathematical model, the calibration experimental design, and other factors. Errors occur at every link in the chain of measurements and data reduction from the sensor to the final computed results. At each link of the chain, bias and precision uncertainties must be separately estimated for facility use, and are combined to produce overall calibration and prediction confidence intervals for the instrument, typically at a 95% confidence level. The uncertainty analysis and calibration experimental designs used herein, based on techniques developed at LaRC, employ replicated experimental designs for efficiency, separate estimation of bias and precision uncertainties, and detection of significant parameter drift with time. Final results, including calibration confidence intervals and prediction intervals given as functions of the applied inputs, not as a fixed percentage of the full-scale value are presented. System uncertainties are propagated beginning with the initial reference pressure standard, to the calibrated instrument as a working standard in the facility. Among the several parameters that can affect the overall results are operating temperature, atmospheric pressure, humidity, and facility vibration. Effects of factors such as initial zeroing and temperature are investigated. The effects of the identified parameters on system performance and accuracy are discussed.

An efficient multistage algorithm for full calibration of the hemodynamic model from BOLD signal responses.

PubMed

Zambri, Brian; Djellouli, Rabia; Laleg-Kirati, Taous-Meriem

2017-11-01

We propose a computational strategy that falls into the category of prediction/correction iterative-type approaches, for calibrating the hemodynamic model. The proposed method is used to estimate consecutively the values of the two sets of model parameters. Numerical results corresponding to both synthetic and real functional magnetic resonance imaging measurements for a single stimulus as well as for multiple stimuli are reported to highlight the capability of this computational methodology to fully calibrate the considered hemodynamic model. Copyright © 2017 John Wiley & Sons, Ltd.

GNSS VTEC calibration using satellite altimetry and LEO data

NASA Astrophysics Data System (ADS)

Alizadeh, M. Mahdi; Schuh, Harald

2015-04-01

Among different systems remote sensing the ionosphere, space geodetic techniques have turned into a promising tool for monitoring and modeling the ionospheric parameters. Due to the fact that ionosphere is a dispersive medium, the signals travelling through this medium provide information about the parameters of the ionosphere in terms of Total Electron Content (TEC) or electron density along the ray path. The classical input data for development of Global Ionosphere Maps (GIM) of the Vertical Total Electron Content (VTEC) is obtained from the dual-frequency Global Navigation Satellite Systems (GNSS) ground-based observations. Nevertheless due to the fact that GNSS ground stations are in-homogeneously distributed with poor coverage over the oceans (namely southern Pacific and southern Atlantic) and also parts of Africa, the precision of VTEC maps are rather low in these areas. From long term analyses it is believed that the International GNSS Service (IGS) VTEC maps have an accuracy of 1-2 TECU in areas well covered with GNSS receivers; conversely, in areas with poor coverage the accuracy can be degraded by a factor of up to five. On the other hand dual-frequency satellite altimetry missions (such as Jason-1&2) provide direct VTEC values exactly over the oceans, and furthermore the Low Earth Orbiting (LEO) satellites such as the Formosat-3/COSMIC (F/C) provide about a great number of globally distributed occultation measurements per day, which can be used to obtain VTEC values. Combining these data with the ground-based data improves the accuracy and reliability of the VTEC maps by closing of observation gaps that arise when using ground-based data only. In this approach an essential step is the evaluation and calibration of the different data sources used for the combination procedure. This study investigates the compatibility of calibrated TEC observables derived from GNSS dual-frequency data, recorded at global ground-based station networks, with space-based TEC values from satellite altimetry and F/C observations. In the current procedure the ground-based GNSS observations have been used to develop a GNSS-only GIM, using the parameter estimation technique. The VTEC values extracted from these models have been quantified and calibrated with the raw altimetry and LEO measurements. The calibrated values have been consequently used for developing the combined GIMs of the VTEC.

Effect of numerical dispersion as a source of structural noise in the calibration of a highly parameterized saltwater intrusion model

USGS Publications Warehouse

Langevin, Christian D.; Hughes, Joseph D.

2010-01-01

A model with a small amount of numerical dispersion was used to represent saltwater 7 intrusion in a homogeneous aquifer for a 10-year historical calibration period with one 8 groundwater withdrawal location followed by a 10-year prediction period with two groundwater 9 withdrawal locations. Time-varying groundwater concentrations at arbitrary locations in this low-10 dispersion model were then used as observations to calibrate a model with a greater amount of 11 numerical dispersion. The low-dispersion model was solved using a Total Variation Diminishing 12 numerical scheme; an implicit finite difference scheme with upstream weighting was used for 13 the calibration simulations. Calibration focused on estimating a three-dimensional hydraulic 14 conductivity field that was parameterized using a regular grid of pilot points in each layer and a 15 smoothness constraint. Other model parameters (dispersivity, porosity, recharge, etc.) were 16 fixed at the known values. The discrepancy between observed and simulated concentrations 17 (due solely to numerical dispersion) was reduced by adjusting hydraulic conductivity through the 18 calibration process. Within the transition zone, hydraulic conductivity tended to be lower than 19 the true value for the calibration runs tested. The calibration process introduced lower hydraulic 20 conductivity values to compensate for numerical dispersion and improve the match between 21 observed and simulated concentration breakthrough curves at monitoring locations. 22 Concentrations were underpredicted at both groundwater withdrawal locations during the 10-23 year prediction period.

An Approach to Remove the Systematic Bias from the Storm Surge forecasts in the Venice Lagoon

NASA Astrophysics Data System (ADS)

Canestrelli, A.

2017-12-01

In this work a novel approach is proposed for removing the systematic bias from the storm surge forecast computed by a two-dimensional shallow-water model. The model covers both the Adriatic and Mediterranean seas and provides the forecast at the entrance of the Venice Lagoon. The wind drag coefficient at the water-air interface is treated as a calibration parameter, with a different value for each range of wind velocities and wind directions. This sums up to a total of 16-64 parameters to be calibrated, depending on the chosen resolution. The best set of parameters is determined by means of an optimization procedure, which minimizes the RMS error between measured and modeled water level in Venice for the period 2011-2015. It is shown that a bias is present, for which the peaks of wind velocities provided by the weather forecast are largely underestimated, and that the calibration procedure removes this bias. When the calibrated model is used to reproduce events not included in the calibration dataset, the forecast error is strongly reduced, thus confirming the quality of our procedure. The proposed approach it is not site-specific and could be applied to different situations, such as storm surges caused by intense hurricanes.

Learning an Eddy Viscosity Model Using Shrinkage and Bayesian Calibration: A Jet-in-Crossflow Case Study

DOE PAGES

Ray, Jaideep; Lefantzi, Sophia; Arunajatesan, Srinivasan; ...

2017-09-07

In this paper, we demonstrate a statistical procedure for learning a high-order eddy viscosity model (EVM) from experimental data and using it to improve the predictive skill of a Reynolds-averaged Navier–Stokes (RANS) simulator. The method is tested in a three-dimensional (3D), transonic jet-in-crossflow (JIC) configuration. The process starts with a cubic eddy viscosity model (CEVM) developed for incompressible flows. It is fitted to limited experimental JIC data using shrinkage regression. The shrinkage process removes all the terms from the model, except an intercept, a linear term, and a quadratic one involving the square of the vorticity. The shrunk eddy viscositymore » model is implemented in an RANS simulator and calibrated, using vorticity measurements, to infer three parameters. The calibration is Bayesian and is solved using a Markov chain Monte Carlo (MCMC) method. A 3D probability density distribution for the inferred parameters is constructed, thus quantifying the uncertainty in the estimate. The phenomenal cost of using a 3D flow simulator inside an MCMC loop is mitigated by using surrogate models (“curve-fits”). A support vector machine classifier (SVMC) is used to impose our prior belief regarding parameter values, specifically to exclude nonphysical parameter combinations. The calibrated model is compared, in terms of its predictive skill, to simulations using uncalibrated linear and CEVMs. Finally, we find that the calibrated model, with one quadratic term, is more accurate than the uncalibrated simulator. The model is also checked at a flow condition at which the model was not calibrated.« less

Learning an Eddy Viscosity Model Using Shrinkage and Bayesian Calibration: A Jet-in-Crossflow Case Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ray, Jaideep; Lefantzi, Sophia; Arunajatesan, Srinivasan

In this paper, we demonstrate a statistical procedure for learning a high-order eddy viscosity model (EVM) from experimental data and using it to improve the predictive skill of a Reynolds-averaged Navier–Stokes (RANS) simulator. The method is tested in a three-dimensional (3D), transonic jet-in-crossflow (JIC) configuration. The process starts with a cubic eddy viscosity model (CEVM) developed for incompressible flows. It is fitted to limited experimental JIC data using shrinkage regression. The shrinkage process removes all the terms from the model, except an intercept, a linear term, and a quadratic one involving the square of the vorticity. The shrunk eddy viscositymore » model is implemented in an RANS simulator and calibrated, using vorticity measurements, to infer three parameters. The calibration is Bayesian and is solved using a Markov chain Monte Carlo (MCMC) method. A 3D probability density distribution for the inferred parameters is constructed, thus quantifying the uncertainty in the estimate. The phenomenal cost of using a 3D flow simulator inside an MCMC loop is mitigated by using surrogate models (“curve-fits”). A support vector machine classifier (SVMC) is used to impose our prior belief regarding parameter values, specifically to exclude nonphysical parameter combinations. The calibrated model is compared, in terms of its predictive skill, to simulations using uncalibrated linear and CEVMs. Finally, we find that the calibrated model, with one quadratic term, is more accurate than the uncalibrated simulator. The model is also checked at a flow condition at which the model was not calibrated.« less

Predicting in ungauged basins using a parsimonious rainfall-runoff model

NASA Astrophysics Data System (ADS)

Skaugen, Thomas; Olav Peerebom, Ivar; Nilsson, Anna

2015-04-01

Prediction in ungauged basins is a demanding, but necessary test for hydrological model structures. Ideally, the relationship between model parameters and catchment characteristics (CC) should be hydrologically justifiable. Many studies, however, report on failure to obtain significant correlations between model parameters and CCs. Under the hypothesis that the lack of correlations stems from non-identifiability of model parameters caused by overparameterization, the relatively new parameter parsimonious DDD (Distance Distribution Dynamics) model was tested for predictions in ungauged basins in Norway. In DDD, the capacity of the subsurface water reservoir M is the only parameter to be calibrated whereas the runoff dynamics is completely parameterised from observed characteristics derived from GIS and runoff recession analysis. Water is conveyed through the soils to the river network by waves with celerities determined by the level of saturation in the catchment. The distributions of distances between points in the catchment to the nearest river reach and of the river network give, together with the celerities, distributions of travel times, and, consequently unit hydrographs. DDD has 6 parameters less to calibrate in the runoff module than, for example, the well-known Swedish HBV model. In this study, multiple regression equations relating CCs and model parameters were trained from 84 calibrated catchments located all over Norway and all model parameters showed significant correlations with catchment characteristics. The significant correlation coefficients (with p- value < 0.05) ranged from 0.22-0.55. The suitability of DDD for predictions in ungauged basins was tested for 17 catchments not used to estimate the multiple regression equations. For 10 of the 17 catchments, deviations in Nash-Suthcliffe Efficiency (NSE) criteria between the calibrated and regionalised model were less than 0.1. The median NSE for the regionalised DDD for the 17 catchments, for two different time series was 0.66 and 0.72. Deviations in NSE between calibrated and regionalised models are well explained by the deviations between calibrated and regressed parameters describing spatial snow distribution and snowmelt, respectively. This latter result indicates the topic for further improvements in the model structure of DDD.

Hydro-abrasive erosion on coated Pelton runners: Partial calibration of the IEC model based on measurements in HPP Fieschertal

NASA Astrophysics Data System (ADS)

Felix, D.; Abgottspon, A.; Albayrak, I.; Boes, R. M.

2016-11-01

At medium- and high-head hydropower plants (HPPs) on sediment-laden rivers, hydro-abrasive erosion on hydraulic turbines is a major economic issue. For optimization of such HPPs, there is an interest in equations to predict erosion depths. Such a semi-empirical equation suitable for engineering practice is proposed in the relevant guideline of the International Electrotechnical Commission (IEC 62364). However, for Pelton turbines no numerical values of the model's calibration parameters have been available yet. In the scope of a research project at the high-head HPP Fieschertal, Switzerland, the particle load and the erosion on the buckets of two hard-coated 32 MW-Pelton runners have been measured since 2012. Based on three years of field data, the numerical values of a group of calibration parameters of the IEC erosion model were determined for five application cases: (i) reduction of splitter height, (ii) increase of splitter width and (iii) increase of cut-out depth due to erosion of mainly base material, as well as erosion of coating on (iv) the splitter crests and (v) inside the buckets. Further laboratory and field investigations are recommended to quantify the effects of individual parameters as well as to improve, generalize and validate erosion models for uncoated and coated Pelton turbines.

Simulated discharge trends indicate robustness of hydrological models in a changing climate

NASA Astrophysics Data System (ADS)

Addor, Nans; Nikolova, Silviya; Seibert, Jan

2016-04-01

Assessing the robustness of hydrological models under contrasted climatic conditions should be part any hydrological model evaluation. Robust models are particularly important for climate impact studies, as models performing well under current conditions are not necessarily capable of correctly simulating hydrological perturbations caused by climate change. A pressing issue is the usually assumed stationarity of parameter values over time. Modeling experiments using conceptual hydrological models revealed that assuming transposability of parameters values in changing climatic conditions can lead to significant biases in discharge simulations. This raises the question whether parameter values should to be modified over time to reflect changes in hydrological processes induced by climate change. Such a question denotes a focus on the contribution of internal processes (i.e., catchment processes) to discharge generation. Here we adopt a different perspective and explore the contribution of external forcing (i.e., changes in precipitation and temperature) to changes in discharge. We argue that in a robust hydrological model, discharge variability should be induced by changes in the boundary conditions, and not by changes in parameter values. In this study, we explore how well the conceptual hydrological model HBV captures transient changes in hydrological signatures over the period 1970-2009. Our analysis focuses on research catchments in Switzerland undisturbed by human activities. The precipitation and temperature forcing are extracted from recently released 2km gridded data sets. We use a genetic algorithm to calibrate HBV for the whole 40-year period and for the eight successive 5-year periods to assess eventual trends in parameter values. Model calibration is run multiple times to account for parameter uncertainty. We find that in alpine catchments showing a significant increase of winter discharge, this trend can be captured reasonably well with constant parameter values over the whole reference period. Further, preliminary results suggest that some trends in parameter values do not reflect changes in hydrological processes, as reported by others previously, but instead might stem from a modeling artifact related to the parameterization of evapotranspiration, which is overly sensitive to temperature increase. We adopt a trading-space-for-time approach to better understand whether robust relationships between parameter values and forcing can be established, and to critically explore the rationale behind time-dependent parameter values in conceptual hydrological models.

Sensitivity analysis of a multilayer, finite-difference model of the Southeastern Coastal Plain regional aquifer system; Mississippi, Alabama, Georgia, and South Carolina

USGS Publications Warehouse

Pernik, Meribeth

1987-01-01

The sensitivity of a multilayer finite-difference regional flow model was tested by changing the calibrated values for five parameters in the steady-state model and one in the transient-state model. The parameters that changed under the steady-state condition were those that had been routinely adjusted during the calibration process as part of the effort to match pre-development potentiometric surfaces, and elements of the water budget. The tested steady-state parameters include: recharge, riverbed conductance, transmissivity, confining unit leakance, and boundary location. In the transient-state model, the storage coefficient was adjusted. The sensitivity of the model to changes in the calibrated values of these parameters was evaluated with respect to the simulated response of net base flow to the rivers, and the mean value of the absolute head residual. To provide a standard measurement of sensitivity from one parameter to another, the standard deviation of the absolute head residual was calculated. The steady-state model was shown to be most sensitive to changes in rates of recharge. When the recharge rate was held constant, the model was more sensitive to variations in transmissivity. Near the rivers, the riverbed conductance becomes the dominant parameter in controlling the heads. Changes in confining unit leakance had little effect on simulated base flow, but greatly affected head residuals. The model was relatively insensitive to changes in the location of no-flow boundaries and to moderate changes in the altitude of constant head boundaries. The storage coefficient was adjusted under transient conditions to illustrate the model 's sensitivity to changes in storativity. The model is less sensitive to an increase in storage coefficient than it is to a decrease in storage coefficient. As the storage coefficient decreased, the aquifer drawdown increases, the base flow decreased. The opposite response occurred when the storage coefficient was increased. (Author 's abstract)

Nuclear Track Detector Characterization via Alpha-Spectrometry for Radioprotection Use

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morelli, D.; Imme, G.; Catalano, R.

2011-12-13

Solid Nuclear Track Detectors (SNTDs), CR-39 type, are usually adopted to monitor radon gas concentrations. In order to characterize the detectors according to track geometrical parameters, detectors were irradiated inside a vacuum chamber by alpha particles at twelve energy values, obtained by different Mylar foils in front of a {sup 241}Am source. The alpha energy values were verified using a Si detector. After the exposure to the alpha particles, the detectors were chemically etched to enlarge the tracks, which were then analyzed by means of a semiautomatic system composed of an optical microscope equipped with a CCD camera connected tomore » a personal computer to store images. A suitable routine analyzed the track parameters: major and minor axis length and mean grey level, allowing us to differentiate tracks according to the incident alpha energy and then to individuate the discrimination factors for radon alpha tracks. The combined use of geometrical and optical parameters allows one to overcome the ambiguity in the alpha energy determination due to the non-monotonicity of each parameter versus energy. After track parameter determination, a calibration procedure was performed by means of a radon chamber. The calibration was verified through an inter-comparing survey.« less

Numerical modelling of gravel unconstrained flow experiments with the DAN3D and RASH3D codes

NASA Astrophysics Data System (ADS)

Sauthier, Claire; Pirulli, Marina; Pisani, Gabriele; Scavia, Claudio; Labiouse, Vincent

2015-12-01

Landslide continuum dynamic models have improved considerably in the last years, but a consensus on the best method of calibrating the input resistance parameter values for predictive analyses has not yet emerged. In the present paper, numerical simulations of a series of laboratory experiments performed at the Laboratory for Rock Mechanics of the EPF Lausanne were undertaken with the RASH3D and DAN3D numerical codes. They aimed at analysing the possibility to use calibrated ranges of parameters (1) in a code different from that they were obtained from and (2) to simulate potential-events made of a material with the same characteristics as back-analysed past-events, but involving a different volume and propagation path. For this purpose, one of the four benchmark laboratory tests was used as past-event to calibrate the dynamic basal friction angle assuming a Coulomb-type behaviour of the sliding mass, and this back-analysed value was then used to simulate the three other experiments, assumed as potential-events. The computational findings show good correspondence with experimental results in terms of characteristics of the final deposits (i.e., runout, length and width). Furthermore, the obtained best fit values of the dynamic basal friction angle for the two codes turn out to be close to each other and within the range of values measured with pseudo-dynamic tilting tests.

Atmospheric stellar parameters from cross-correlation functions

NASA Astrophysics Data System (ADS)

Malavolta, L.; Lovis, C.; Pepe, F.; Sneden, C.; Udry, S.

2017-08-01

The increasing number of spectra gathered by spectroscopic sky surveys and transiting exoplanet follow-up has pushed the community to develop automated tools for atmospheric stellar parameters determination. Here we present a novel approach that allows the measurement of temperature (Teff), metallicity ([Fe/H]) and gravity (log g) within a few seconds and in a completely automated fashion. Rather than performing comparisons with spectral libraries, our technique is based on the determination of several cross-correlation functions (CCFs) obtained by including spectral features with different sensitivity to the photospheric parameters. We use literature stellar parameters of high signal-to-noise (SNR), high-resolution HARPS spectra of FGK main-sequence stars to calibrate Teff, [Fe/H] and log g as a function of CCF parameters. Our technique is validated using low-SNR spectra obtained with the same instrument. For FGK stars we achieve a precision of σ _{{T_eff}} = 50 K, σlog g = 0.09 dex and σ _{{{[Fe/H]}}} =0.035 dex at SNR = 50, while the precision for observation with SNR ≳ 100 and the overall accuracy are constrained by the literature values used to calibrate the CCFs. Our approach can easily be extended to other instruments with similar spectral range and resolution or to other spectral range and stars other than FGK dwarfs if a large sample of reference stars is available for the calibration. Additionally, we provide the mathematical formulation to convert synthetic equivalent widths to CCF parameters as an alternative to direct calibration. We have made our tool publicly available.

Estimation of soil hydraulic properties with microwave techniques

NASA Technical Reports Server (NTRS)

Oneill, P. E.; Gurney, R. J.; Camillo, P. J.

1985-01-01

Useful quantitative information about soil properties may be obtained by calibrating energy and moisture balance models with remotely sensed data. A soil physics model solves heat and moisture flux equations in the soil profile and is driven by the surface energy balance. Model generated surface temperature and soil moisture and temperature profiles are then used in a microwave emission model to predict the soil brightness temperature. The model hydraulic parameters are varied until the predicted temperatures agree with the remotely sensed values. This method is used to estimate values for saturated hydraulic conductivity, saturated matrix potential, and a soil texture parameter. The conductivity agreed well with a value measured with an infiltration ring and the other parameters agreed with values in the literature.

The Gaia-ESO Survey: Calibration strategy

NASA Astrophysics Data System (ADS)

Pancino, E.; Lardo, C.; Altavilla, G.; Marinoni, S.; Ragaini, S.; Cocozza, G.; Bellazzini, M.; Sabbi, E.; Zoccali, M.; Donati, P.; Heiter, U.; Koposov, S. E.; Blomme, R.; Morel, T.; Símon-Díaz, S.; Lobel, A.; Soubiran, C.; Montalban, J.; Valentini, M.; Casey, A. R.; Blanco-Cuaresma, S.; Jofré, P.; Worley, C. C.; Magrini, L.; Hourihane, A.; François, P.; Feltzing, S.; Gilmore, G.; Randich, S.; Asplund, M.; Bonifacio, P.; Drew, J. E.; Jeffries, R. D.; Micela, G.; Vallenari, A.; Alfaro, E. J.; Allende Prieto, C.; Babusiaux, C.; Bensby, T.; Bragaglia, A.; Flaccomio, E.; Hambly, N.; Korn, A. J.; Lanzafame, A. C.; Smiljanic, R.; Van Eck, S.; Walton, N. A.; Bayo, A.; Carraro, G.; Costado, M. T.; Damiani, F.; Edvardsson, B.; Franciosini, E.; Frasca, A.; Lewis, J.; Monaco, L.; Morbidelli, L.; Prisinzano, L.; Sacco, G. G.; Sbordone, L.; Sousa, S. G.; Zaggia, S.; Koch, A.

2017-02-01

The Gaia-ESO survey (GES) is now in its fifth and last year of observations and has produced tens of thousands of high-quality spectra of stars in all Milky Way components. This paper presents the strategy behind the selection of astrophysical calibration targets, ensuring that all GES results on radial velocities, atmospheric parameters, and chemical abundance ratios will be both internally consistent and easily comparable with other literature results, especially from other large spectroscopic surveys and from Gaia. The calibration of GES is particularly delicate because of (I) the large space of parameters covered by its targets, ranging from dwarfs to giants, from O to M stars; these targets have a large wide of metallicities and also include fast rotators, emission line objects, and stars affected by veiling; (II) the variety of observing setups, with different wavelength ranges and resolution; and (III) the choice of analyzing the data with many different state-of-the-art methods, each stronger in a different region of the parameter space, which ensures a better understanding of systematic uncertainties. An overview of the GES calibration and homogenization strategy is also given, along with some examples of the usage and results of calibrators in GES iDR4, which is the fourth internal GES data release and will form the basis of the next GES public data release. The agreement between GES iDR4 recommended values and reference values for the calibrating objects are very satisfactory. The average offsets and spreads are generally compatible with the GES measurement errors, which in iDR4 data already meet the requirements set by the main GES scientific goals. Based on data products from observations made with ESO Telescopes at the La Silla Paranal Observatory under programme IDs 188.B-3002 and 193.B-0936.Full Table 2 is only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/598/A5

Development of a generic auto-calibration package for regional ecological modeling and application in the Central Plains of the United States

USGS Publications Warehouse

Wu, Yiping; Liu, Shuguang; Li, Zhengpeng; Dahal, Devendra; Young, Claudia J.; Schmidt, Gail L.; Liu, Jinxun; Davis, Brian; Sohl, Terry L.; Werner, Jeremy M.; Oeding, Jennifer

2014-01-01

Process-oriented ecological models are frequently used for predicting potential impacts of global changes such as climate and land-cover changes, which can be useful for policy making. It is critical but challenging to automatically derive optimal parameter values at different scales, especially at regional scale, and validate the model performance. In this study, we developed an automatic calibration (auto-calibration) function for a well-established biogeochemical model—the General Ensemble Biogeochemical Modeling System (GEMS)-Erosion Deposition Carbon Model (EDCM)—using data assimilation technique: the Shuffled Complex Evolution algorithm and a model-inversion R package—Flexible Modeling Environment (FME). The new functionality can support multi-parameter and multi-objective auto-calibration of EDCM at the both pixel and regional levels. We also developed a post-processing procedure for GEMS to provide options to save the pixel-based or aggregated county-land cover specific parameter values for subsequent simulations. In our case study, we successfully applied the updated model (EDCM-Auto) for a single crop pixel with a corn–wheat rotation and a large ecological region (Level II)—Central USA Plains. The evaluation results indicate that EDCM-Auto is applicable at multiple scales and is capable to handle land cover changes (e.g., crop rotations). The model also performs well in capturing the spatial pattern of grain yield production for crops and net primary production (NPP) for other ecosystems across the region, which is a good example for implementing calibration and validation of ecological models with readily available survey data (grain yield) and remote sensing data (NPP) at regional and national levels. The developed platform for auto-calibration can be readily expanded to incorporate other model inversion algorithms and potential R packages, and also be applied to other ecological models.

Sensitivity analysis and calibration of a dynamic physically based slope stability model

NASA Astrophysics Data System (ADS)

Zieher, Thomas; Rutzinger, Martin; Schneider-Muntau, Barbara; Perzl, Frank; Leidinger, David; Formayer, Herbert; Geitner, Clemens

2017-06-01

Physically based modelling of slope stability on a catchment scale is still a challenging task. When applying a physically based model on such a scale (1 : 10 000 to 1 : 50 000), parameters with a high impact on the model result should be calibrated to account for (i) the spatial variability of parameter values, (ii) shortcomings of the selected model, (iii) uncertainties of laboratory tests and field measurements or (iv) parameters that cannot be derived experimentally or measured in the field (e.g. calibration constants). While systematic parameter calibration is a common task in hydrological modelling, this is rarely done using physically based slope stability models. In the present study a dynamic, physically based, coupled hydrological-geomechanical slope stability model is calibrated based on a limited number of laboratory tests and a detailed multitemporal shallow landslide inventory covering two landslide-triggering rainfall events in the Laternser valley, Vorarlberg (Austria). Sensitive parameters are identified based on a local one-at-a-time sensitivity analysis. These parameters (hydraulic conductivity, specific storage, angle of internal friction for effective stress, cohesion for effective stress) are systematically sampled and calibrated for a landslide-triggering rainfall event in August 2005. The identified model ensemble, including 25 behavioural model runs with the highest portion of correctly predicted landslides and non-landslides, is then validated with another landslide-triggering rainfall event in May 1999. The identified model ensemble correctly predicts the location and the supposed triggering timing of 73.0 % of the observed landslides triggered in August 2005 and 91.5 % of the observed landslides triggered in May 1999. Results of the model ensemble driven with raised precipitation input reveal a slight increase in areas potentially affected by slope failure. At the same time, the peak run-off increases more markedly, suggesting that precipitation intensities during the investigated landslide-triggering rainfall events were already close to or above the soil's infiltration capacity.

Evaluation of Potential Evapotranspiration from a Hydrologic Model on a National Scale

NASA Astrophysics Data System (ADS)

Hakala, Kirsti; Markstrom, Steven; Hay, Lauren

2015-04-01

The U.S. Geological Survey has developed a National Hydrologic Model (NHM) to support coordinated, comprehensive and consistent hydrologic model development and facilitate the application of simulations on the scale of the continental U.S. The NHM has a consistent geospatial fabric for modeling, consisting of over 100,000 hydrologic response units HRUs). Each HRU requires accurate parameter estimates, some of which are attained from automated calibration. However, improved calibration can be achieved by initially utilizing as many parameters as possible from national data sets. This presentation investigates the effectiveness of calculating potential evapotranspiration (PET) parameters based on mean monthly values from the NOAA PET Atlas. Additional PET products are then used to evaluate the PET parameters. Effectively utilizing existing national-scale data sets can simplify the effort in establishing a robust NHM.

Methods for Calibration of Prout-Tompkins Kinetics Parameters Using EZM Iteration and GLO

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wemhoff, A P; Burnham, A K; de Supinski, B

2006-11-07

This document contains information regarding the standard procedures used to calibrate chemical kinetics parameters for the extended Prout-Tompkins model to match experimental data. Two methods for calibration are mentioned: EZM calibration and GLO calibration. EZM calibration matches kinetics parameters to three data points, while GLO calibration slightly adjusts kinetic parameters to match multiple points. Information is provided regarding the theoretical approach and application procedure for both of these calibration algorithms. It is recommended that for the calibration process, the user begin with EZM calibration to provide a good estimate, and then fine-tune the parameters using GLO. Two examples have beenmore » provided to guide the reader through a general calibrating process.« less

Using Multiple Outcomes of Sexual Behavior to Provide Insights Into Chlamydia Transmission and the Effectiveness of Prevention Interventions in Adolescents.

PubMed

Enns, Eva Andrea; Kao, Szu-Yu; Kozhimannil, Katy Backes; Kahn, Judith; Farris, Jill; Kulasingam, Shalini L

2017-10-01

Mathematical models are important tools for assessing prevention and management strategies for sexually transmitted infections. These models are usually developed for a single infection and require calibration to observed epidemiological trends in the infection of interest. Incorporating other outcomes of sexual behavior into the model, such as pregnancy, may better inform the calibration process. We developed a mathematical model of chlamydia transmission and pregnancy in Minnesota adolescents aged 15 to 19 years. We calibrated the model to statewide rates of reported chlamydia cases alone (chlamydia calibration) and in combination with pregnancy rates (dual calibration). We evaluated the impact of calibrating to different outcomes of sexual behavior on estimated input parameter values, predicted epidemiological outcomes, and predicted impact of chlamydia prevention interventions. The two calibration scenarios produced different estimates of the probability of condom use, the probability of chlamydia transmission per sex act, the proportion of asymptomatic infections, and the screening rate among men. These differences resulted in the dual calibration scenario predicting lower prevalence and incidence of chlamydia compared with calibrating to chlamydia cases alone. When evaluating the impact of a 10% increase in condom use, the dual calibration scenario predicted fewer infections averted over 5 years compared with chlamydia calibration alone [111 (6.8%) vs 158 (8.5%)]. While pregnancy and chlamydia in adolescents are often considered separately, both are outcomes of unprotected sexual activity. Incorporating both as calibration targets in a model of chlamydia transmission resulted in different parameter estimates, potentially impacting the intervention effectiveness predicted by the model.

Establishment of replacement batches for heparin low-molecular-mass for calibration CRS, and the International Standard Low Molecular Weight Heparin for Calibration.

PubMed

Mulloy, B; Heath, A; Behr-Gross, M-E

2007-12-01

An international collaborative study involving fourteen laboratories has taken place, organised by the European Directorate for the Quality of Medicines & HealthCare (EDQM) with National Institute for Biological Standards & Control (NIBSC) (in its capacity as a World Health Organisation (WHO) Laboratory for Biological Standardisation) to provide supporting data for the establishment of replacement batches of Heparin Low-Molecular-Mass (LMM) for Calibration Chemical Reference Substance (CRS), and of the International Reference Reagent (IRR) Low Molecular Weight Heparin for Molecular Weight Calibration. A batch of low-molecular-mass heparin was donated to the organisers and candidate preparations of freeze-dried heparin were produced at NIBSC and EDQM. The establishment study was organised in two phases: a prequalification (phase 1, performed in 3 laboratories in 2005) followed by an international collaborative study (phase 2). In phase 2, started in March 2006, molecular mass parameters were determined for seven different LMM heparin samples using the current CRS batch and two batches of candidate replacement material with a defined number average relative molecular mass (Mn) of 3,700, determined in phase 1. The values calculated using the candidates as standard were systematically different from values calculated using the current batch with its assigned number-average molecular mass (Mna) of 3,700. Using raw data supplied by participants, molecular mass parameters were recalculated using the candidates as standard with values for Mna of 3,800 and 3,900. Values for these parameters agreed more closely with those calculated using the current batch supporting the fact that the candidates, though similar to batch 1 in view of the production processes used, differ slightly in terms of molecular mass distribution. Therefore establishment of the candidates was recommended with an assigned Mna value of 3,800 that is both consistent with phase 1 results and guarantees continuity with the current CRS batch. In phase 2, participants also determined molecular weight parameters for the seven different LMM heparin samples using both the 1st IRR (90/686) and its Broad Standard Table and the candidate World Health Organization (WHO) 2nd International Standard (05/112) (2nd IS) using a Broad Standard Table established in phase 1. Mean molecular weights calculated using 2nd IS were slightly higher than with 1st IRR, and participants in the study indicated that this systematic difference precluded establishment of 2nd IS with the table supplied. A replacement Broad Standard Table has been devised on the basis of the central recalculations of raw data supplied by participants; this table gives improved agreement between values derived using the 1st IRR and the candidate 2nd IS. On the basis of this study a recommendation was made for the establishment of 2nd IS and its proposed Broad Standard Table as a replacement for the 1st International Reference Reagent Low Molecular Weight Heparin for Molecular Weight Calibration. Unlike the 1st IRR however, the candidate material 2nd IS is not suitable for use with the method of Nielsen. The candidate materials were established as heparin low-molecular-mass for calibration batches 2 and 3 by the Ph. Eur. Commission in March 2007 and as 2nd IS low-molecular-weight heparin for molecular weight calibration (05/112) by the Expert Committee on Biological Standardization in November 2007.

Cross-calibration between airborne SAR sensors

NASA Technical Reports Server (NTRS)

Zink, Manfred; Olivier, Philippe; Freeman, Anthony

1993-01-01

As Synthetic Aperture Radar (SAR) system performance and experience in SAR signature evaluation increase, quantitative analysis becomes more and more important. Such analyses require an absolute radiometric calibration of the complete SAR system. To keep the expenditure on calibration of future multichannel and multisensor remote sensing systems (e.g., X-SAR/SIR-C) within a tolerable level, data from different tracks and different sensors (channels) must be cross calibrated. The 1989 joint E-SAR/DC-8 SAR calibration campaign gave a first opportunity for such an experiment, including cross sensor and cross track calibration. A basic requirement for successful cross calibration is the stability of the SAR systems. The calibration parameters derived from different tracks and the polarimetric properties of the uncalibrated data are used to describe this stability. Quality criteria for a successful cross calibration are the agreement of alpha degree values and the consistency of radar cross sections of equally sized corner reflectors. Channel imbalance and cross talk provide additional quality in case of the polarimetric DC-8 SAR.

Land-surface parameter optimisation using data assimilation techniques: the adJULES system V1.0

NASA Astrophysics Data System (ADS)

Raoult, Nina M.; Jupp, Tim E.; Cox, Peter M.; Luke, Catherine M.

2016-08-01

Land-surface models (LSMs) are crucial components of the Earth system models (ESMs) that are used to make coupled climate-carbon cycle projections for the 21st century. The Joint UK Land Environment Simulator (JULES) is the land-surface model used in the climate and weather forecast models of the UK Met Office. JULES is also extensively used offline as a land-surface impacts tool, forced with climatologies into the future. In this study, JULES is automatically differentiated with respect to JULES parameters using commercial software from FastOpt, resulting in an analytical gradient, or adjoint, of the model. Using this adjoint, the adJULES parameter estimation system has been developed to search for locally optimum parameters by calibrating against observations. This paper describes adJULES in a data assimilation framework and demonstrates its ability to improve the model-data fit using eddy-covariance measurements of gross primary production (GPP) and latent heat (LE) fluxes. adJULES also has the ability to calibrate over multiple sites simultaneously. This feature is used to define new optimised parameter values for the five plant functional types (PFTs) in JULES. The optimised PFT-specific parameters improve the performance of JULES at over 85 % of the sites used in the study, at both the calibration and evaluation stages. The new improved parameters for JULES are presented along with the associated uncertainties for each parameter.

Linked Sensitivity Analysis, Calibration, and Uncertainty Analysis Using a System Dynamics Model for Stroke Comparative Effectiveness Research.

PubMed

Tian, Yuan; Hassmiller Lich, Kristen; Osgood, Nathaniel D; Eom, Kirsten; Matchar, David B

2016-11-01

As health services researchers and decision makers tackle more difficult problems using simulation models, the number of parameters and the corresponding degree of uncertainty have increased. This often results in reduced confidence in such complex models to guide decision making. To demonstrate a systematic approach of linked sensitivity analysis, calibration, and uncertainty analysis to improve confidence in complex models. Four techniques were integrated and applied to a System Dynamics stroke model of US veterans, which was developed to inform systemwide intervention and research planning: Morris method (sensitivity analysis), multistart Powell hill-climbing algorithm and generalized likelihood uncertainty estimation (calibration), and Monte Carlo simulation (uncertainty analysis). Of 60 uncertain parameters, sensitivity analysis identified 29 needing calibration, 7 that did not need calibration but significantly influenced key stroke outcomes, and 24 not influential to calibration or stroke outcomes that were fixed at their best guess values. One thousand alternative well-calibrated baselines were obtained to reflect calibration uncertainty and brought into uncertainty analysis. The initial stroke incidence rate among veterans was identified as the most influential uncertain parameter, for which further data should be collected. That said, accounting for current uncertainty, the analysis of 15 distinct prevention and treatment interventions provided a robust conclusion that hypertension control for all veterans would yield the largest gain in quality-adjusted life years. For complex health care models, a mixed approach was applied to examine the uncertainty surrounding key stroke outcomes and the robustness of conclusions. We demonstrate that this rigorous approach can be practical and advocate for such analysis to promote understanding of the limits of certainty in applying models to current decisions and to guide future data collection. © The Author(s) 2016.

Calibration of Passive Samplers for the Monitoring of Pharmaceuticals in Water-Sampling Rate Variation.

PubMed

Męczykowska, Hanna; Kobylis, Paulina; Stepnowski, Piotr; Caban, Magda

2017-05-04

Passive sampling is one of the most efficient methods of monitoring pharmaceuticals in environmental water. The reliability of the process relies on a correctly performed calibration experiment and a well-defined sampling rate (R s ) for target analytes. Therefore, in this review the state-of-the-art methods of passive sampler calibration for the most popular pharmaceuticals: antibiotics, hormones, β-blockers and non-steroidal anti-inflammatory drugs (NSAIDs), along with the sampling rate variation, were presented. The advantages and difficulties in laboratory and field calibration were pointed out, according to the needs of control of the exact conditions. Sampling rate calculating equations and all the factors affecting the R s value - temperature, flow, pH, salinity of the donor phase and biofouling - were discussed. Moreover, various calibration parameters gathered from the literature published in the last 16 years, including the device types, were tabled and compared. What is evident is that the sampling rate values for pharmaceuticals are impacted by several factors, whose influence is still unclear and unpredictable, while there is a big gap in experimental data. It appears that the calibration procedure needs to be improved, for example, there is a significant deficiency of PRCs (Performance Reference Compounds) for pharmaceuticals. One of the suggestions is to introduce correction factors for R s values estimated in laboratory conditions.

A New Online Calibration Method Based on Lord's Bias-Correction.

PubMed

He, Yinhong; Chen, Ping; Li, Yong; Zhang, Shumei

2017-09-01

Online calibration technique has been widely employed to calibrate new items due to its advantages. Method A is the simplest online calibration method and has attracted many attentions from researchers recently. However, a key assumption of Method A is that it treats person-parameter estimates θ ^ s (obtained by maximum likelihood estimation [MLE]) as their true values θ s , thus the deviation of the estimated θ ^ s from their true values might yield inaccurate item calibration when the deviation is nonignorable. To improve the performance of Method A, a new method, MLE-LBCI-Method A, is proposed. This new method combines a modified Lord's bias-correction method (named as maximum likelihood estimation-Lord's bias-correction with iteration [MLE-LBCI]) with the original Method A in an effort to correct the deviation of θ ^ s which may adversely affect the item calibration precision. Two simulation studies were carried out to explore the performance of both MLE-LBCI and MLE-LBCI-Method A under several scenarios. Simulation results showed that MLE-LBCI could make a significant improvement over the ML ability estimates, and MLE-LBCI-Method A did outperform Method A in almost all experimental conditions.

BOREAS RSS-14 Level -3 Gridded Radiometer and Satellite Surface Radiation Images

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Nickeson, Jaime (Editor); Hodges, Gary; Smith, Eric A.

2000-01-01

The BOREAS RSS-14 team collected and processed GOES-7 and -8 images of the BOREAS region as part of its effort to characterize the incoming, reflected, and emitted radiation at regional scales. This data set contains surface radiation parameters, such as net radiation and net solar radiation, that have been interpolated from GOES-7 images and AMS data onto the standard BOREAS mapping grid at a resolution of 5 km N-S and E-W. While some parameters are taken directly from the AMS data set, others have been corrected according to calibrations carried out during IFC-2 in 1994. The corrected values as well as the uncorrected values are included. For example, two values of net radiation are provided: an uncorrected value (Rn), and a value that has been corrected according to the calibrations (Rn-COR). The data are provided in binary image format data files. Some of the data files on the BOREAS CD-ROMs have been compressed using the Gzip program. See section 8.2 for details. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Ground-Water Flow in the Vicinity of the Ho-Chunk Nation Communities of Indian Mission and Sand Pillow, Jackson County, Wisconsin

USGS Publications Warehouse

Dunning, Charles P.; Mueller, Gregory D.; Juckem, Paul F.

2008-01-01

An analytic element ground-water-flow model was constructed to help understand the ground-water-flow system in the vicinity of the Ho-Chunk Nation communities of Indian Mission and Sand Pillow in Jackson County, Wisconsin. Data from interpretive reports, well-drillers' construction reports, and an exploratory augering program in 2003 indicate that sand and gravel of varying thickness (0-150 feet[ft]) and porous sandstone make up a composite aquifer that overlies Precambrian crystalline rock. The geometric mean values for horizontal hydraulic conductivity were estimated from specific-capacity data to be 61.3 feet per day (ft/d) for sand and gravel, 6.6 ft/d for sandstone, and 12.0 ft/d for the composite aquifer. A ground-water flow model was constructed, the near field of which encompassed the Levis and Morrison Creeks Watershed. The flow model was coupled to the parameter-estimation program UCODE to obtain a best fit between simulated and measured values of ground-water levels and estimated Q50 flow duration (base flow). Calibration of the model with UCODE provided a ground-water recharge rate of 9 inches per year and a horizontal hydraulic conductivity of 13 ft/d for the composite aquifer. Using these calibrated parameter values, simulated heads from the model were on average within 5 ft of the measured water levels. In addition, these parameter values provided an acceptable base-flow calibration for Hay, Dickey, and Levis Creeks; the calibration was particularly close for Levis Creek, which was the most frequently measured stream in the study area. The calibrated model was used to simulate ground-water levels and to determine the direction of ground-water flow in the vicinity of Indian Mission and Sand Pillow communities. Backward particle tracking was conducted for Sand Pillow production wells under two pumping simulations to determine their 20-year contributing areas. In the first simulation, new production wells 6, 7, and 8 were each pumped at 50 gallons per minute (gal/min). In the second simulation, new production wells 6, 7, and 8 and existing production well 5 were each pumped at 50 gal/min. The second simulation demonstrated interference between the existing production well 5 and the new production wells when all were pumping at 50 gal/min.

Direct determination of geometric alignment parameters for cone-beam scanners

PubMed Central

Mennessier, C; Clackdoyle, R; Noo, F

2009-01-01

This paper describes a comprehensive method for determining the geometric alignment parameters for cone-beam scanners (often called calibrating the scanners or performing geometric calibration). The method is applicable to x-ray scanners using area detectors, or to SPECT systems using pinholes or cone-beam converging collimators. Images of an alignment test object (calibration phantom) fixed in the field of view of the scanner are processed to determine the nine geometric parameters for each view. The parameter values are found directly using formulae applied to the projected positions of the test object marker points onto the detector. Each view is treated independently, and no restrictions are made on the position of the cone vertex, or on the position or orientation of the detector. The proposed test object consists of 14 small point-like objects arranged with four points on each of three orthogonal lines, and two points on a diagonal line. This test object is shown to provide unique solutions for all possible scanner geometries, even when partial measurement information is lost by points superimposing in the calibration scan. For the many situations where the cone vertex stays reasonably close to a central plane (for circular, planar, or near-planar trajectories), a simpler version of the test object is appropriate. The simpler object consists of six points, two per orthogonal line, but with some restrictions on the positioning of the test object. This paper focuses on the principles and mathematical justifications for the method. Numerical simulations of the calibration process and reconstructions using estimated parameters are also presented to validate the method and to provide evidence of the robustness of the technique. PMID:19242049

SU-G-IeP3-01: Better Kerma-Area-Product (KAP) Estimation Using the System Parameters in Radiography and Fluoroscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, D; MacDougall, R

2016-06-15

Purpose: Accurate values for Kerma-Area-Product (KAP) are needed for patient dosimetry and quality control for exams utilizing radiographic and/or fluoroscopic imaging. The KAP measured using a typical direct KAP meter built with parallel-plate transmission ionization chamber is not precise and depends on the energy spectrum of diagnostic x-rays. This study compared the accuracy and reproducibility of KAP derived from system parameters with values measured with a direct KAP meter. Methods: IEC tolerance for displayed KAP is specified up to ± 35% above 2.5 Gy-cm{sup 2} and manufacturer’s specifications are typically ± 25%. KAP values from the direct KAP meter driftsmore » with time leading to replacement or re-calibration. More precise and consistent KAP is achievable utilizing a database of known radiation output for various system parameters. The integrated KAP meter was removed from a radiography system. A total of 48 measurements of air kerma were acquired at x-ray tube potential from 40 to 150 kVp with 10 kVp increment using ion chamber type external dosimeter at free-in-air geometry for four different types of filter combinations following the manufacturer’s service procedure. These data were used to create updated correction factors that determine air kerma computationally for given system parameters. Results of calculated KAP were evaluated against results using a calibrated ion chamber based dosimeter and a computed radiography imaging plate to measure x-ray field size. Results: The accuracy of calculated KAP from the system parameters was better within 4% deviation in all diagnostic x-ray tube potentials tested from 50 to 140 kVp. In contrast, deviations of up to 25% were measured from KAP displayed from the direct KAP meter. Conclusion: The “calculated KAP” approach provides the nominal advantage of improved accuracy and precision of displayed KAP as well as reduced cost of calibrating or replacing integrated KAP meters.« less

Calibration of the ``Simplified Simple Biosphere Model—SSiB'' for the Brazilian Northeast Caatinga

NASA Astrophysics Data System (ADS)

do Amaral Cunha, Ana Paula Martins; dos Santos Alvalá, Regina Célia; Correia, Francis Wagner Silva; Kubota, Paulo Yoshio

2009-03-01

The Brazilian Northeast region is covered largely by vegetation adapted to the arid conditions and with varied physiognomy, called caatinga. It occupies an extension of about 800.000 km2 that corresponds to 70% of the region. In recent decades, considerable progress in understanding the micrometeorological processes has been reached, with results that were incorporated into soil-vegetation-atmosphere transfer schemes (SVATS) to study the momentum, energy, water vapor, carbon cycle and vegetation dynamics changes of different ecosystems. Notwithstanding, the knowledge of the parameters and physical or physiological characteristics of the vegetation and soil of the caatinga region is very scarce. So, the objective of this work was performing a calibration of the parameters of the SSiB model for the Brazilian Northeast Caatinga. Micrometeorological and hydrological data collected from July 2004 to June 2005, obtained in the Agricultural Research Center of the Semi-Arid Tropic (CPATSA), were used. Preceding the calibration process, a sensibility study of the SSiB model was performed in order to find the parameters that are sensible to the exchange processes between the surface and atmosphere. The results showed that the B parameter, soil moisture potential at saturation (ψs), hydraulic conductivity of saturated soil (ks) and the volumetric moisture at saturation (θs) present high variations on turbulent fluxes. With the initial parameters, the SSiB model showed best results for net radiation, and the latent heat (sensible heat) flux was over-estimated (under-estimated) for all simulation periods. Considering the calibrated parameters, better values of latent flux and sensible flux were obtained. The calibrated parameters were also used for a validation of the surface fluxes considering data from July 2005 to September 2005. The results showed that the model generated better estimations of latent heat and sensible heat fluxes, with low root mean square error. With better estimations of the turbulent fluxes, it was possible to obtain a more representative energy partitioning for the caatinga. Therefore, it is expected that from this calibrated SSiB model, coupled to the meteorological models, it will be possible to obtain more realistic climate and weather forecasts for the Brazilian Northeast region.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Raoult, Nina M.; Jupp, Tim E.; Cox, Peter M.

Land-surface models (LSMs) are crucial components of the Earth system models (ESMs) that are used to make coupled climate–carbon cycle projections for the 21st century. The Joint UK Land Environment Simulator (JULES) is the land-surface model used in the climate and weather forecast models of the UK Met Office. JULES is also extensively used offline as a land-surface impacts tool, forced with climatologies into the future. In this study, JULES is automatically differentiated with respect to JULES parameters using commercial software from FastOpt, resulting in an analytical gradient, or adjoint, of the model. Using this adjoint, the adJULES parameter estimationmore » system has been developed to search for locally optimum parameters by calibrating against observations. This paper describes adJULES in a data assimilation framework and demonstrates its ability to improve the model–data fit using eddy-covariance measurements of gross primary production (GPP) and latent heat (LE) fluxes. adJULES also has the ability to calibrate over multiple sites simultaneously. This feature is used to define new optimised parameter values for the five plant functional types (PFTs) in JULES. The optimised PFT-specific parameters improve the performance of JULES at over 85 % of the sites used in the study, at both the calibration and evaluation stages. Furthermore, the new improved parameters for JULES are presented along with the associated uncertainties for each parameter.« less

Priority design parameters of industrialized optical fiber sensors in civil engineering

NASA Astrophysics Data System (ADS)

Wang, Huaping; Jiang, Lizhong; Xiang, Ping

2018-03-01

Considering the mechanical effects and the different paths for transferring deformation, optical fiber sensors commonly used in civil engineering have been systematically classified. Based on the strain transfer theory, the relationship between the strain transfer coefficient and allowable testing error is established. The proposed relationship is regarded as the optimal control equation to obtain the optimal value of sensors that satisfy the requirement of measurement precision. Furthermore, specific optimization design methods and priority design parameters of the classified sensors are presented. This research indicates that (1) strain transfer theory-based optimization design method is much suitable for the sensor that depends on the interfacial shear stress to transfer the deformation; (2) the priority design parameters are bonded (sensing) length, interfacial bonded strength, elastic modulus and radius of protective layer and thickness of adhesive layer; (3) the optimization design of sensors with two anchor pieces at two ends is independent of strain transfer theory as the strain transfer coefficient can be conveniently calibrated by test, and this kind of sensors has no obvious priority design parameters. Improved calibration test is put forward to enhance the accuracy of the calibration coefficient of end-expanding sensors. By considering the practical state of sensors and the testing accuracy, comprehensive and systematic analyses on optical fiber sensors are provided from the perspective of mechanical actions, which could scientifically instruct the application design and calibration test of industrialized optical fiber sensors.

Calibration of a distributed hydrologic model for six European catchments using remote sensing data

NASA Astrophysics Data System (ADS)

Stisen, S.; Demirel, M. C.; Mendiguren González, G.; Kumar, R.; Rakovec, O.; Samaniego, L. E.

2017-12-01

While observed streamflow has been the single reference for most conventional hydrologic model calibration exercises, the availability of spatially distributed remote sensing observations provide new possibilities for multi-variable calibration assessing both spatial and temporal variability of different hydrologic processes. In this study, we first identify the key transfer parameters of the mesoscale Hydrologic Model (mHM) controlling both the discharge and the spatial distribution of actual evapotranspiration (AET) across six central European catchments (Elbe, Main, Meuse, Moselle, Neckar and Vienne). These catchments are selected based on their limited topographical and climatic variability which enables to evaluate the effect of spatial parameterization on the simulated evapotranspiration patterns. We develop a European scale remote sensing based actual evapotranspiration dataset at a 1 km grid scale driven primarily by land surface temperature observations from MODIS using the TSEB approach. Using the observed AET maps we analyze the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mHM model. This model allows calibrating one-basin-at-a-time or all-basins-together using its unique structure and multi-parameter regionalization approach. Results will indicate any tradeoffs between spatial pattern and discharge simulation during model calibration and through validation against independent internal discharge locations. Moreover, added value on internal water balances will be analyzed.

Development of genetic algorithm-based optimization module in WHAT system for hydrograph analysis and model application

NASA Astrophysics Data System (ADS)

Lim, Kyoung Jae; Park, Youn Shik; Kim, Jonggun; Shin, Yong-Chul; Kim, Nam Won; Kim, Seong Joon; Jeon, Ji-Hong; Engel, Bernard A.

2010-07-01

Many hydrologic and water quality computer models have been developed and applied to assess hydrologic and water quality impacts of land use changes. These models are typically calibrated and validated prior to their application. The Long-Term Hydrologic Impact Assessment (L-THIA) model was applied to the Little Eagle Creek (LEC) watershed and compared with the filtered direct runoff using BFLOW and the Eckhardt digital filter (with a default BFI max value of 0.80 and filter parameter value of 0.98), both available in the Web GIS-based Hydrograph Analysis Tool, called WHAT. The R2 value and the Nash-Sutcliffe coefficient values were 0.68 and 0.64 with BFLOW, and 0.66 and 0.63 with the Eckhardt digital filter. Although these results indicate that the L-THIA model estimates direct runoff reasonably well, the filtered direct runoff values using BFLOW and Eckhardt digital filter with the default BFI max and filter parameter values do not reflect hydrological and hydrogeological situations in the LEC watershed. Thus, a BFI max GA-Analyzer module (BFI max Genetic Algorithm-Analyzer module) was developed and integrated into the WHAT system for determination of the optimum BFI max parameter and filter parameter of the Eckhardt digital filter. With the automated recession curve analysis method and BFI max GA-Analyzer module of the WHAT system, the optimum BFI max value of 0.491 and filter parameter value of 0.987 were determined for the LEC watershed. The comparison of L-THIA estimates with filtered direct runoff using an optimized BFI max and filter parameter resulted in an R2 value of 0.66 and the Nash-Sutcliffe coefficient value of 0.63. However, L-THIA estimates calibrated with the optimized BFI max and filter parameter increased by 33% and estimated NPS pollutant loadings increased by more than 20%. This indicates L-THIA model direct runoff estimates can be incorrect by 33% and NPS pollutant loading estimation by more than 20%, if the accuracy of the baseflow separation method is not validated for the study watershed prior to model comparison. This study shows the importance of baseflow separation in hydrologic and water quality modeling using the L-THIA model.

Soil Moisture and Temperature Measuring Networks in the Tibetan Plateau and Their Hydrological Applications

NASA Astrophysics Data System (ADS)

Yang, Kun; Chen, Yingying; Qin, Jun; Lu, Hui

2017-04-01

Multi-sphere interactions over the Tibetan Plateau directly impact its surrounding climate and environment at a variety of spatiotemporal scales. Remote sensing and modeling are expected to provide hydro-meteorological data needed for these process studies, but in situ observations are required to support their calibration and validation. For this purpose, we have established two networks on the Tibetan Plateau to measure densely two state variables (soil moisture and temperature) and four soil depths (0 5, 10, 20, and 40 cm). The experimental area is characterized by low biomass, high soil moisture dynamic range, and typical freeze-thaw cycle. As auxiliary parameters of these networks, soil texture and soil organic carbon content are measured at each station to support further studies. In order to guarantee continuous and high-quality data, tremendous efforts have been made to protect the data logger from soil water intrusion, to calibrate soil moisture sensors, and to upscale the point measurements. One soil moisture network is located in a semi-humid area in central Tibetan Plateau (Naqu), which consists of 56 stations with their elevation varying over 4470 4950 m and covers three spatial scales (1.0, 0.3, 0.1 degree). The other is located in a semi-arid area in southern Tibetan Plateau (Pali), which consists of 25 stations and covers an area of 0.25 degree. The spatiotemporal characteristics of the former network were analyzed, and a new spatial upscaling method was developed to obtain the regional mean soil moisture truth from the point measurements. Our networks meet the requirement for evaluating a variety of soil moisture products, developing new algorithms, and analyzing soil moisture scaling. Three applications with the network data are presented in this paper. 1. Evaluation of Current remote sensing and LSM products. The in situ data have been used to evaluate AMSR-E, AMSR2, SMOS and SMAP products and four modeled outputs by the Global Land Data Assimilation System (GLDAS). 2. Development of New Products. We developed a dual-pass land data assimilation system. The essential idea of the system is to calibrate a land data assimilation system before a normal data assimilation. The calibration is based on satellite data rather than in situ data. Through this way, we may alleviate the impact of uncertainties in determining the error covariance of both observation operator and model operation, as it is always tough to determine the covariance. The performance of the data assimilation system is presented through comparison against the Tibetan Plateau soil moisture measuring networks. And the results are encouraging. 3. Estimation of Soil Parameter Values in a Land Surface Model. We explored the possibility to estimate soil parameter values by assimilating AMSR-E brightness temperature (TB) data. In the assimilation system, the TB is simulated by the coupled system of a land surface model (LSM) and a radiative transfer model (RTM), and the simulation errors highly depend on parameters in both the LSM and the RTM. Thus, sensitive soil parameters may be inversely estimated through minimizing the TB errors. The effectiveness of the estimated parameter values is evaluated against intensive measurements of soil parameters and soil moisture in three grasslands of the Tibetan Plateau and the Mongolian Plateau. The results indicate that this satellite data-based approach can improve the data quality of soil porosity, a key parameter for soil moisture modeling, and LSM simulations with the estimated parameter values reasonably reproduce the measured soil moisture. This demonstrates it is feasible to calibrate LSMs for soil moisture simulations at grid scale by assimilating microwave satellite data, although more efforts are expected to improve the robustness of the model calibration.

Description of the National Hydrologic Model for use with the Precipitation-Runoff Modeling System (PRMS)

USGS Publications Warehouse

Regan, R. Steven; Markstrom, Steven L.; Hay, Lauren E.; Viger, Roland J.; Norton, Parker A.; Driscoll, Jessica M.; LaFontaine, Jacob H.

2018-01-08

This report documents several components of the U.S. Geological Survey National Hydrologic Model of the conterminous United States for use with the Precipitation-Runoff Modeling System (PRMS). It provides descriptions of the (1) National Hydrologic Model, (2) Geospatial Fabric for National Hydrologic Modeling, (3) PRMS hydrologic simulation code, (4) parameters and estimation methods used to compute spatially and temporally distributed default values as required by PRMS, (5) National Hydrologic Model Parameter Database, and (6) model extraction tool named Bandit. The National Hydrologic Model Parameter Database contains values for all PRMS parameters used in the National Hydrologic Model. The methods and national datasets used to estimate all the PRMS parameters are described. Some parameter values are derived from characteristics of topography, land cover, soils, geology, and hydrography using traditional Geographic Information System methods. Other parameters are set to long-established default values and computation of initial values. Additionally, methods (statistical, sensitivity, calibration, and algebraic) were developed to compute parameter values on the basis of a variety of nationally-consistent datasets. Values in the National Hydrologic Model Parameter Database can periodically be updated on the basis of new parameter estimation methods and as additional national datasets become available. A companion ScienceBase resource provides a set of static parameter values as well as images of spatially-distributed parameters associated with PRMS states and fluxes for each Hydrologic Response Unit across the conterminuous United States.

On the use of water phantom images to calibrate and correct eddy current induced artefacts in MR diffusion tensor imaging.

PubMed

Bastin, M E; Armitage, P A

2000-07-01

The accurate determination of absolute measures of diffusion anisotropy in vivo using single-shot, echo-planar imaging techniques requires the acquisition of a set of high signal-to-noise ratio, diffusion-weighted images that are free from eddy current induced image distortions. Such geometric distortions can be characterized and corrected in brain imaging data using magnification (M), translation (T), and shear (S) distortion parameters derived from separate water phantom calibration experiments. Here we examine the practicalities of using separate phantom calibration data to correct high b-value diffusion tensor imaging data by investigating the stability of these distortion parameters, and hence the eddy currents, with time. It is found that M, T, and S vary only slowly with time (i.e., on the order of weeks), so that calibration scans need not be performed after every patient examination. This not only minimises the scan time required to collect the calibration data, but also the computational time needed to characterize these eddy current induced distortions. Examples of how measurements of diffusion anisotropy are improved using this post-processing scheme are also presented.

Hydrochemical tracers in the middle Rio Grande Basin, USA: 2. Calibration of a groundwater-flow model

USGS Publications Warehouse

Sanford, W.E.; Plummer, Niel; McAda, D.P.; Bexfield, L.M.; Anderholm, S.K.

2004-01-01

The calibration of a groundwater model with the aid of hydrochemical data has demonstrated that low recharge rates in the Middle Rio Grande Basin may be responsible for a groundwater trough in the center of the basin and for a substantial amount of Rio Grande water in the regional flow system. Earlier models of the basin had difficulty reproducing these features without any hydrochemical data to constrain the rates and distribution of recharge. The objective of this study was to use the large quantity of available hydrochemical data to help calibrate the model parameters, including the recharge rates. The model was constructed using the US Geological Survey's software MODFLOW, MODPATH, and UCODE, and calibrated using 14C activities and the positions of certain flow zones defined by the hydrochemical data. Parameter estimation was performed using a combination of nonlinear regression techniques and a manual search for the minimum difference between field and simulated observations. The calibrated recharge values were substantially smaller than those used in previous models. Results from a 30,000-year transient simulation suggest that recharge was at a maximum about 20,000 years ago and at a minimum about 10,000 years ago. ?? Springer-Verlag 2004.

Interactions of solutes and streambed sediment: 2. A dynamic analysis of coupled hydrologic and chemical processes that determine solute transport

USGS Publications Warehouse

Bencala, Kenneth E.

1984-01-01

Solute transport in streams is determined by the interaction of physical and chemical processes. Data from an injection experiment for chloride and several cations indicate significant influence of solutestreambed processes on transport in a mountain stream. These data are interpreted in terms of transient storage processes for all tracers and sorption processes for the cations. Process parameter values are estimated with simulations based on coupled quasi-two-dimensional transport and first-order mass transfer sorption. Comparative simulations demonstrate the relative roles of the physical and chemical processes in determining solute transport. During the first 24 hours of the experiment, chloride concentrations were attenuated relative to expected plateau levels. Additional attenuation occurred for the sorbing cation strontium. The simulations account for these storage processes. Parameter values determined by calibration compare favorably with estimates from other studies in mountain streams. Without further calibration, the transport of potassium and lithium is adequately simulated using parameters determined in the chloride-strontium simulation and with measured cation distribution coefficients.

A Method to Solve Interior and Exterior Camera Calibration Parameters for Image Resection

NASA Technical Reports Server (NTRS)

Samtaney, Ravi

1999-01-01

An iterative method is presented to solve the internal and external camera calibration parameters, given model target points and their images from one or more camera locations. The direct linear transform formulation was used to obtain a guess for the iterative method, and herein lies one of the strengths of the present method. In all test cases, the method converged to the correct solution. In general, an overdetermined system of nonlinear equations is solved in the least-squares sense. The iterative method presented is based on Newton-Raphson for solving systems of nonlinear algebraic equations. The Jacobian is analytically derived and the pseudo-inverse of the Jacobian is obtained by singular value decomposition.

Calibration of a distributed hydrologic model using observed spatial patterns from MODIS data

NASA Astrophysics Data System (ADS)

Demirel, Mehmet C.; González, Gorka M.; Mai, Juliane; Stisen, Simon

2016-04-01

Distributed hydrologic models are typically calibrated against streamflow observations at the outlet of the basin. Along with these observations from gauging stations, satellite based estimates offer independent evaluation data such as remotely sensed actual evapotranspiration (aET) and land surface temperature. The primary objective of the study is to compare model calibrations against traditional downstream discharge measurements with calibrations against simulated spatial patterns and combinations of both types of observations. While the discharge based model calibration typically improves the temporal dynamics of the model, it seems to give rise to minimum improvement of the simulated spatial patterns. In contrast, objective functions specifically targeting the spatial pattern performance could potentially increase the spatial model performance. However, most modeling studies, including the model formulations and parameterization, are not designed to actually change the simulated spatial pattern during calibration. This study investigates the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mesoscale hydrologic model (mHM). This model is selected as it allows for a change in the spatial distribution of key soil parameters through the optimization of pedo-transfer function parameters and includes options for using fully distributed daily Leaf Area Index (LAI) values directly as input. In addition the simulated aET can be estimated at a spatial resolution suitable for comparison to the spatial patterns observed with MODIS data. To increase our control on spatial calibration we introduced three additional parameters to the model. These new parameters are part of an empirical equation to the calculate crop coefficient (Kc) from daily LAI maps and used to update potential evapotranspiration (PET) as model inputs. This is done instead of correcting/updating PET with just a uniform (or aspect driven) factor used in the mHM model (version 5.3). We selected the 20 most important parameters out of 53 mHM parameters based on a comprehensive sensitivity analysis (Cuntz et al., 2015). We calibrated 1km-daily mHM for the Skjern basin in Denmark using the Shuffled Complex Evolution (SCE) algorithm and inputs at different spatial scales i.e. meteorological data at 10km and morphological data at 250 meters. We used correlation coefficients between observed monthly (summer months only) MODIS data calculated from cloud free days over the calibration period from 2001 to 2008 and simulated aET from mHM over the same period. Similarly other metrics, e.g mapcurves and fraction skill-score, are also included in our objective function to assess the co-location of the grid-cells. The preliminary results show that multi-objective calibration of mHM against observed streamflow and spatial patterns together does not significantly reduce the spatial errors in aET while it improves the streamflow simulations. This is a strong signal for further investigation of the multi parameter regionalization affecting spatial aET patterns and weighting the spatial metrics in the objective function relative to the streamflow metrics.

Calibration of water distribution network of the Ramnagar zone in Nagpur City using online pressure and flow data

NASA Astrophysics Data System (ADS)

Jadhao, Ramrao D.; Gupta, Rajesh

2018-03-01

Calibration of hydraulic model of a water distribution network is required to match the model results of flows and pressures with those obtained in the field. This is a challenging task considering the involvement of a large number of parameters. Having more precise data helps in reducing time and results in better calibration as shown herein with a case study of one hydraulic zone served from the Ramnagar Ground Service Reservoir in Nagpur City. Flow and pressure values for the entire day were obtained through data loggers. Network details regarding pipe lengths, diameters, installation year and material were obtained with the largest possible accuracy. Locations of consumers on the network were noted and average nodal consumptions were obtained from the billing records. The non-revenue water losses were uniformly allocated to all junctions. Valve positions and their operating status were noted from the field and used. The pipe roughness coefficients were adjusted to match the model values with field values of pressures at observation nodes by minimizing the sum of square of difference between them. This paper aims at describing the entire process from collection of the required data to the calibration of the network.

An approach to derive some simple empirical equations to calibrate nuclear and acoustic well logging tools.

PubMed

Mohammad Al Alfy, Ibrahim

2018-01-01

A set of three pads was constructed from primary materials (sand, gravel and cement) to calibrate the gamma-gamma density tool. A simple equation was devised to convert the qualitative cps values to quantitative g/cc values. The neutron-neutron porosity tool measures the qualitative cps porosity values. A direct equation was derived to calculate the porosity percentage from the cps porosity values. Cement-bond log illustrates the cement quantities, which surround well pipes. This log needs a difficult process due to the existence of various parameters, such as: drilling well diameter as well as internal diameter, thickness and type of well pipes. An equation was invented to calculate the cement percentage at standard conditions. This equation can be modified according to varying conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Calibrating the sqHIMMELI v1.0 wetland methane emission model with hierarchical modeling and adaptive MCMC

NASA Astrophysics Data System (ADS)

Susiluoto, Jouni; Raivonen, Maarit; Backman, Leif; Laine, Marko; Makela, Jarmo; Peltola, Olli; Vesala, Timo; Aalto, Tuula

2018-03-01

Estimating methane (CH4) emissions from natural wetlands is complex, and the estimates contain large uncertainties. The models used for the task are typically heavily parameterized and the parameter values are not well known. In this study, we perform a Bayesian model calibration for a new wetland CH4 emission model to improve the quality of the predictions and to understand the limitations of such models.The detailed process model that we analyze contains descriptions for CH4 production from anaerobic respiration, CH4 oxidation, and gas transportation by diffusion, ebullition, and the aerenchyma cells of vascular plants. The processes are controlled by several tunable parameters. We use a hierarchical statistical model to describe the parameters and obtain the posterior distributions of the parameters and uncertainties in the processes with adaptive Markov chain Monte Carlo (MCMC), importance resampling, and time series analysis techniques. For the estimation, the analysis utilizes measurement data from the Siikaneva flux measurement site in southern Finland. The uncertainties related to the parameters and the modeled processes are described quantitatively. At the process level, the flux measurement data are able to constrain the CH4 production processes, methane oxidation, and the different gas transport processes. The posterior covariance structures explain how the parameters and the processes are related. Additionally, the flux and flux component uncertainties are analyzed both at the annual and daily levels. The parameter posterior densities obtained provide information regarding importance of the different processes, which is also useful for development of wetland methane emission models other than the square root HelsinkI Model of MEthane buiLd-up and emIssion for peatlands (sqHIMMELI). The hierarchical modeling allows us to assess the effects of some of the parameters on an annual basis. The results of the calibration and the cross validation suggest that the early spring net primary production could be used to predict parameters affecting the annual methane production. Even though the calibration is specific to the Siikaneva site, the hierarchical modeling approach is well suited for larger-scale studies and the results of the estimation pave way for a regional or global-scale Bayesian calibration of wetland emission models.

Attitude Sensor and Gyro Calibration for Messenger

NASA Technical Reports Server (NTRS)

O'Shaughnessy, Daniel; Pittelkau, Mark E.

2007-01-01

The Redundant Inertial Measurement Unit Attitude Determination/Calibration (RADICAL(TM)) filter was used to estimate star tracker and gyro calibration parameters using MESSENGER telemetry data from three calibration events. We present an overview of the MESSENGER attitude sensors and their configuration is given, the calibration maneuvers are described, the results are compared with previous calibrations, and variations and trends in the estimated calibration parameters are examined. The warm restart and covariance bump features of the RADICAL(TM) filter were used to estimate calibration parameters from two disjoint telemetry streams. Results show that the calibration parameters converge faster with much less transient variation during convergence than when the filter is cold-started at the start of each telemetry stream.

Novel quantitative calibration approach for multi-configuration electromagnetic induction (EMI) systems using data acquired at multiple elevations

NASA Astrophysics Data System (ADS)

Tan, Xihe; Mester, Achim; von Hebel, Christian; van der Kruk, Jan; Zimmermann, Egon; Vereecken, Harry; van Waasen, Stefan

2017-04-01

Electromagnetic induction (EMI) systems offer a great potential to obtain highly resolved layered electrical conductivity models of the shallow subsurface. State-of-the-art inversion procedures require quantitative calibration of EMI data, especially for short-offset EMI systems where significant data shifts are often observed. These shifts are caused by external influences such as the presence of the operator, zero-leveling procedures, the field setup used to move the EMI system and/or cables close by. Calibrations can be performed by using collocated electrical resistivity measurements or taking soil samples, however, these two methods take a lot of time in the field. To improve the calibration in a fast and concise way, we introduce a novel on-site calibration method using a series of apparent electrical conductivity (ECa) values acquired at multiple elevations for a multi-configuration EMI system. No additional instrument or pre-knowledge of the subsurface is needed to acquire quantitative ECa data. By using this calibration method, we correct each coil configuration, i.e., transmitter and receiver coil separation and the horizontal or vertical coplanar (HCP or VCP) coil orientation with a unique set of calibration parameters. A multi-layer soil structure at the corresponding measurement location is inverted together with the calibration parameters using full-solution Maxwell equations for the forward modelling within the shuffled complex evolution (SCE) algorithm to find the optimum solution under a user-defined parameter space. Synthetic data verified the feasibility for calibrating HCP and VCP measurements of a custom made six-coil EMI system with coil offsets between 0.35 m and 1.8 m for quantitative data inversions. As a next step, we applied the calibration approach on acquired experimental data from a bare soil test field (Selhausen, Germany) for the considered EMI system. The obtained calibration parameters were applied to measurements over a 30 m transect line that covers a range of conductivities between 5 and 40 mS/m. Inverted calibrated EMI data of the transect line showed very similar electrical conductivity distributions and layer interfaces of the subsurface compared to reference data obtained from vertical electrical sounding (VES) measurements. These results show that a combined calibration and inversion of multi-configuration EMI data is possible when including measurements at different elevations, which will speed up the measurement process to obtain quantitative EMI data since the labor intensive electrical resistivity measurement or soil coring is not necessary anymore.

Linking Item Parameters to a Base Scale

ERIC Educational Resources Information Center

Kang, Taehoon; Petersen, Nancy S.

2012-01-01

This paper compares three methods of item calibration--concurrent calibration, separate calibration with linking, and fixed item parameter calibration--that are frequently used for linking item parameters to a base scale. Concurrent and separate calibrations were implemented using BILOG-MG. The Stocking and Lord in "Appl Psychol Measure"…

Land-surface parameter optimisation using data assimilation techniques: the adJULES system V1.0

DOE PAGES

Raoult, Nina M.; Jupp, Tim E.; Cox, Peter M.; ...

2016-08-25

Land-surface models (LSMs) are crucial components of the Earth system models (ESMs) that are used to make coupled climate–carbon cycle projections for the 21st century. The Joint UK Land Environment Simulator (JULES) is the land-surface model used in the climate and weather forecast models of the UK Met Office. JULES is also extensively used offline as a land-surface impacts tool, forced with climatologies into the future. In this study, JULES is automatically differentiated with respect to JULES parameters using commercial software from FastOpt, resulting in an analytical gradient, or adjoint, of the model. Using this adjoint, the adJULES parameter estimationmore » system has been developed to search for locally optimum parameters by calibrating against observations. This paper describes adJULES in a data assimilation framework and demonstrates its ability to improve the model–data fit using eddy-covariance measurements of gross primary production (GPP) and latent heat (LE) fluxes. adJULES also has the ability to calibrate over multiple sites simultaneously. This feature is used to define new optimised parameter values for the five plant functional types (PFTs) in JULES. The optimised PFT-specific parameters improve the performance of JULES at over 85 % of the sites used in the study, at both the calibration and evaluation stages. Furthermore, the new improved parameters for JULES are presented along with the associated uncertainties for each parameter.« less

Improving the Fit of a Land-Surface Model to Data Using its Adjoint

NASA Astrophysics Data System (ADS)

Raoult, Nina; Jupp, Tim; Cox, Peter; Luke, Catherine

2016-04-01

Land-surface models (LSMs) are crucial components of the Earth System Models (ESMs) which are used to make coupled climate-carbon cycle projections for the 21st century. The Joint UK Land Environment Simulator (JULES) is the land-surface model used in the climate and weather forecast models of the UK Met Office. In this study, JULES is automatically differentiated using commercial software from FastOpt, resulting in an analytical gradient, or adjoint, of the model. Using this adjoint, the adJULES parameter estimation system has been developed, to search for locally optimum parameter sets by calibrating against observations. We present an introduction to the adJULES system and demonstrate its ability to improve the model-data fit using eddy covariance measurements of gross primary production (GPP) and latent heat (LE) fluxes. adJULES also has the ability to calibrate over multiple sites simultaneously. This feature is used to define new optimised parameter values for the 5 Plant Functional Types (PFTS) in JULES. The optimised PFT-specific parameters improve the performance of JULES over 90% of the FLUXNET sites used in the study. These reductions in error are shown and compared to reductions found due to site-specific optimisations. Finally, we show that calculation of the 2nd derivative of JULES allows us to produce posterior probability density functions of the parameters and how knowledge of parameter values is constrained by observations.

Application of iterative robust model-based optimal experimental design for the calibration of biocatalytic models.

PubMed

Van Daele, Timothy; Gernaey, Krist V; Ringborg, Rolf H; Börner, Tim; Heintz, Søren; Van Hauwermeiren, Daan; Grey, Carl; Krühne, Ulrich; Adlercreutz, Patrick; Nopens, Ingmar

2017-09-01

The aim of model calibration is to estimate unique parameter values from available experimental data, here applied to a biocatalytic process. The traditional approach of first gathering data followed by performing a model calibration is inefficient, since the information gathered during experimentation is not actively used to optimize the experimental design. By applying an iterative robust model-based optimal experimental design, the limited amount of data collected is used to design additional informative experiments. The algorithm is used here to calibrate the initial reaction rate of an ω-transaminase catalyzed reaction in a more accurate way. The parameter confidence region estimated from the Fisher Information Matrix is compared with the likelihood confidence region, which is not only more accurate but also a computationally more expensive method. As a result, an important deviation between both approaches is found, confirming that linearization methods should be applied with care for nonlinear models. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:1278-1293, 2017. © 2017 American Institute of Chemical Engineers.

Not All Stars Are the Sun: Empirical Calibration of the Mixing Length for Metal-poor Stars Using One-dimensional Stellar Evolution Models

NASA Astrophysics Data System (ADS)

Joyce, M.; Chaboyer, B.

2018-03-01

Theoretical stellar evolution models are constructed and tailored to the best known, observationally derived characteristics of metal-poor ([Fe/H] ∼ ‑2.3) stars representing a range of evolutionary phases: subgiant HD 140283, globular cluster M92, and four single, main sequence stars with well-determined parallaxes: HIP 46120, HIP 54639, HIP 106924, and WOLF 1137. It is found that the use of a solar-calibrated value of the mixing length parameter α MLT in models of these objects is ineffective at reproducing their observed properties. Empirically calibrated values of α MLT are presented for each object, accounting for uncertainties in the input physics employed in the models. It is advocated that the implementation of an adaptive mixing length is necessary in order for stellar evolution models to maintain fidelity in the era of high-precision observations.

The on-orbit calibration of geometric parameters of the Tian-Hui 1 (TH-1) satellite

NASA Astrophysics Data System (ADS)

Wang, Jianrong; Wang, Renxiang; Hu, Xin; Su, Zhongbo

2017-02-01

The on-orbit calibration of geometric parameters is a key step in improving the location accuracy of satellite images without using Ground Control Points (GCPs). Most methods of on-orbit calibration are based on the self-calibration using additional parameters. When using additional parameters, different number of additional parameters may lead to different results. The triangulation bundle adjustment is another way to calibrate the geometric parameters of camera, which can describe the changes in each geometric parameter. When triangulation bundle adjustment method is applied to calibrate geometric parameters, a prerequisite is that the strip model can avoid systematic deformation caused by the rate of attitude changes. Concerning the stereo camera, the influence of the intersection angle should be considered during calibration. The Equivalent Frame Photo (EFP) bundle adjustment based on the Line-Matrix CCD (LMCCD) image can solve the systematic distortion of the strip model, and obtain high accuracy location without using GCPs. In this paper, the triangulation bundle adjustment is used to calibrate the geometric parameters of TH-1 satellite cameras based on LMCCD image. During the bundle adjustment, the three-line array cameras are reconstructed by adopting the principle of inverse triangulation. Finally, the geometric accuracy is validated before and after on-orbit calibration using 5 testing fields. After on-orbit calibration, the 3D geometric accuracy is improved to 11.8 m from 170 m. The results show that the location accuracy of TH-1 without using GCPs is significantly improved using the on-orbit calibration of the geometric parameters.

Linking Item Parameters to a Base Scale. ACT Research Report Series, 2009-2

ERIC Educational Resources Information Center

Kang, Taehoon; Petersen, Nancy S.

2009-01-01

This paper compares three methods of item calibration--concurrent calibration, separate calibration with linking, and fixed item parameter calibration--that are frequently used for linking item parameters to a base scale. Concurrent and separate calibrations were implemented using BILOG-MG. The Stocking and Lord (1983) characteristic curve method…

Data reduction and calibration for LAMOST survey

NASA Astrophysics Data System (ADS)

Luo, Ali; Zhang, Jiannan; Chen, Jianjun; Song, Yihan; Wu, Yue; Bai, Zhongrui; Wang, Fengfei; Du, Bing; Zhang, Haotong

2014-01-01

There are three data pipelines for LAMOST survey. The raw data is reduced to one dimension spectra by the data reduction pipeline(2D pipeline), the extracted spectra are classified and measured by the spectral analysis pipeline(1D pipeline), while stellar parameters are measured by LASP pipeline. (a) The data reduction pipeline. The main tasks of the data reduction pipeline include bias calibration, flat field, spectra extraction, sky subtraction, wavelength calibration, exposure merging and wavelength band connection. (b) The spectra analysis pipeline. This pipeline is designed to classify and identify objects from the extracted spectra and to measure their redshift (or radial velocity). The PCAZ (Glazebrook et al. 1998) method is applied to do the classification and redshift measurement. (c) Stellar parameters LASP. Stellar parameters pipeline (LASP) is to estimate stellar atmospheric parameters, e.g. effective temperature Teff, surface gravity log g, and metallicity [Fe/H], for F, G and K type stars. To effectively determine those fundamental stellar measurements, three steps with different methods are employed. The first step utilizes the line indices to approximately define the effective temperature range of the analyzed star. Secondly, a set of the initial approximate values of the three parameters are given based on template fitting method. Finally, we exploit ULySS (Koleva et al. 2009) to give the final values of parameters through minimizing the χ 2 value between the observed spectrum and a multidimensional grid of model spectra which is generated by an interpolating of ELODIE library. There are two other classification for A type star and M type star. For A type star, standard MK system is employed (Gray et al. 2009) to give each object temperature class and luminosity type. For M type star, they are classified into subclasses by an improved Hammer method, and metallicity of each objects is also given. During the pilot survey, algorithms were improved and the pipelines were tested. The products of LAMOST survey will include extracted and calibrated spectra in FITS format, a catalog of FGK stars with stellar parameters, a catalog of M dwarf with subclass and metallicity, and a catalog of A type star with MK classification. A part of the pilot survey data, including about 319 000 high quality spectra with SNR > 10, a catalog of stellar parameters of FGK stars and another catalog of a subclass of M type stars have been released to the public in August 2012 (Luo et al. 2012). The general survey started from October 2012, and completed the first year survey. The formal data release one (DR1) is being prepared, which will include both pilot survey and first year general survey, and planed to be released under the LAMOST data policy.

Watershed model calibration framework developed using an influence coefficient algorithm and a genetic algorithm and analysis of pollutant discharge characteristics and load reduction in a TMDL planning area.

PubMed

Cho, Jae Heon; Lee, Jong Ho

2015-11-01

Manual calibration is common in rainfall-runoff model applications. However, rainfall-runoff models include several complicated parameters; thus, significant time and effort are required to manually calibrate the parameters individually and repeatedly. Automatic calibration has relative merit regarding time efficiency and objectivity but shortcomings regarding understanding indigenous processes in the basin. In this study, a watershed model calibration framework was developed using an influence coefficient algorithm and genetic algorithm (WMCIG) to automatically calibrate the distributed models. The optimization problem used to minimize the sum of squares of the normalized residuals of the observed and predicted values was solved using a genetic algorithm (GA). The final model parameters were determined from the iteration with the smallest sum of squares of the normalized residuals of all iterations. The WMCIG was applied to a Gomakwoncheon watershed located in an area that presents a total maximum daily load (TMDL) in Korea. The proportion of urbanized area in this watershed is low, and the diffuse pollution loads of nutrients such as phosphorus are greater than the point-source pollution loads because of the concentration of rainfall that occurs during the summer. The pollution discharges from the watershed were estimated for each land-use type, and the seasonal variations of the pollution loads were analyzed. Consecutive flow measurement gauges have not been installed in this area, and it is difficult to survey the flow and water quality in this area during the frequent heavy rainfall that occurs during the wet season. The Hydrological Simulation Program-Fortran (HSPF) model was used to calculate the runoff flow and water quality in this basin. Using the water quality results, a load duration curve was constructed for the basin, the exceedance frequency of the water quality standard was calculated for each hydrologic condition class, and the percent reduction required to achieve the water quality standard was estimated. The R(2) value for the calibrated BOD5 was 0.60, which is a moderate result, and the R(2) value for the TP was 0.86, which is a good result. The percent differences obtained for the calibrated BOD5 and TP were very good; therefore, the calibration results using WMCIG were satisfactory. From the load duration curve analysis, the WQS exceedance frequencies of the BOD5 under dry conditions and low-flow conditions were 75.7% and 65%, respectively, and the exceedance frequencies under moist and mid-range conditions were higher than under other conditions. The exceedance frequencies of the TP for the high-flow, moist and mid-range conditions were high and the exceedance rate for the high-flow condition was particularly high. Most of the data from the high-flow conditions exceeded the WQSs. Thus, nonpoint-source pollutants from storm-water runoff substantially affected the TP concentration in the Gomakwoncheon. Copyright © 2015 Elsevier Ltd. All rights reserved.

A suggestion for computing objective function in model calibration

USGS Publications Warehouse

Wu, Yiping; Liu, Shuguang

2014-01-01

A parameter-optimization process (model calibration) is usually required for numerical model applications, which involves the use of an objective function to determine the model cost (model-data errors). The sum of square errors (SSR) has been widely adopted as the objective function in various optimization procedures. However, ‘square error’ calculation was found to be more sensitive to extreme or high values. Thus, we proposed that the sum of absolute errors (SAR) may be a better option than SSR for model calibration. To test this hypothesis, we used two case studies—a hydrological model calibration and a biogeochemical model calibration—to investigate the behavior of a group of potential objective functions: SSR, SAR, sum of squared relative deviation (SSRD), and sum of absolute relative deviation (SARD). Mathematical evaluation of model performance demonstrates that ‘absolute error’ (SAR and SARD) are superior to ‘square error’ (SSR and SSRD) in calculating objective function for model calibration, and SAR behaved the best (with the least error and highest efficiency). This study suggests that SSR might be overly used in real applications, and SAR may be a reasonable choice in common optimization implementations without emphasizing either high or low values (e.g., modeling for supporting resources management).

Evaluating the Community Land Model (CLM4.5) at a coniferous forest site in northwestern United States using flux and carbon-isotope measurements

DOE PAGES

Duarte, Henrique F.; Raczka, Brett M.; Ricciuto, Daniel M.; ...

2017-09-28

Droughts in the western United States are expected to intensify with climate change. Thus, an adequate representation of ecosystem response to water stress in land models is critical for predicting carbon dynamics. The goal of this study was to evaluate the performance of the Community Land Model (CLM) version 4.5 against observations at an old-growth coniferous forest site in the Pacific Northwest region of the United States (Wind River AmeriFlux site), characterized by a Mediterranean climate that subjects trees to water stress each summer. CLM was driven by site-observed meteorology and calibrated primarily using parameter values observed at the site ormore » at similar stands in the region. Key model adjustments included parameters controlling specific leaf area and stomatal conductance. Default values of these parameters led to significant underestimation of gross primary production, overestimation of evapotranspiration, and consequently overestimation of photosynthetic 13C discrimination, reflected in reduced 13C: 12C ratios of carbon fluxes and pools. Adjustments in soil hydraulic parameters within CLM were also critical, preventing significant underestimation of soil water content and unrealistic soil moisture stress during summer. After calibration, CLM was able to simulate energy and carbon fluxes, leaf area index, biomass stocks, and carbon isotope ratios of carbon fluxes and pools in reasonable agreement with site observations. Overall, the calibrated CLM was able to simulate the observed response of canopy conductance to atmospheric vapor pressure deficit (VPD) and soil water content, reasonably capturing the impact of water stress on ecosystem functioning. Both simulations and observations indicate that stomatal response from water stress at Wind River was primarily driven by VPD and not soil moisture. The calibration of the Ball–Berry stomatal conductance slope ( m bb) at Wind River aligned with findings from recent CLM experiments at sites characterized by the same plant functional type (needleleaf evergreen temperate forest), despite significant differences in stand composition and age and climatology, suggesting that CLM could benefit from a revised m bb value of 6, rather than the default value of 9, for this plant functional type. Conversely, Wind River required a unique calibration of the hydrology submodel to simulate soil moisture, suggesting that the default hydrology has a more limited applicability. Here, this study demonstrates that carbon isotope data can be used to constrain stomatal conductance and intrinsic water use efficiency in CLM, as an alternative to eddy covariance flux measurements. It also demonstrates that carbon isotopes can expose structural weaknesses in the model and provide a key constraint that may guide future model development.« less

Evaluating the Community Land Model (CLM4.5) at a coniferous forest site in northwestern United States using flux and carbon-isotope measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Duarte, Henrique F.; Raczka, Brett M.; Ricciuto, Daniel M.

Droughts in the western United States are expected to intensify with climate change. Thus, an adequate representation of ecosystem response to water stress in land models is critical for predicting carbon dynamics. The goal of this study was to evaluate the performance of the Community Land Model (CLM) version 4.5 against observations at an old-growth coniferous forest site in the Pacific Northwest region of the United States (Wind River AmeriFlux site), characterized by a Mediterranean climate that subjects trees to water stress each summer. CLM was driven by site-observed meteorology and calibrated primarily using parameter values observed at the site ormore » at similar stands in the region. Key model adjustments included parameters controlling specific leaf area and stomatal conductance. Default values of these parameters led to significant underestimation of gross primary production, overestimation of evapotranspiration, and consequently overestimation of photosynthetic 13C discrimination, reflected in reduced 13C: 12C ratios of carbon fluxes and pools. Adjustments in soil hydraulic parameters within CLM were also critical, preventing significant underestimation of soil water content and unrealistic soil moisture stress during summer. After calibration, CLM was able to simulate energy and carbon fluxes, leaf area index, biomass stocks, and carbon isotope ratios of carbon fluxes and pools in reasonable agreement with site observations. Overall, the calibrated CLM was able to simulate the observed response of canopy conductance to atmospheric vapor pressure deficit (VPD) and soil water content, reasonably capturing the impact of water stress on ecosystem functioning. Both simulations and observations indicate that stomatal response from water stress at Wind River was primarily driven by VPD and not soil moisture. The calibration of the Ball–Berry stomatal conductance slope ( m bb) at Wind River aligned with findings from recent CLM experiments at sites characterized by the same plant functional type (needleleaf evergreen temperate forest), despite significant differences in stand composition and age and climatology, suggesting that CLM could benefit from a revised m bb value of 6, rather than the default value of 9, for this plant functional type. Conversely, Wind River required a unique calibration of the hydrology submodel to simulate soil moisture, suggesting that the default hydrology has a more limited applicability. Here, this study demonstrates that carbon isotope data can be used to constrain stomatal conductance and intrinsic water use efficiency in CLM, as an alternative to eddy covariance flux measurements. It also demonstrates that carbon isotopes can expose structural weaknesses in the model and provide a key constraint that may guide future model development.« less

Evaluating the Community Land Model (CLM4.5) at a coniferous forest site in northwestern United States using flux and carbon-isotope measurements

NASA Astrophysics Data System (ADS)

Duarte, Henrique F.; Raczka, Brett M.; Ricciuto, Daniel M.; Lin, John C.; Koven, Charles D.; Thornton, Peter E.; Bowling, David R.; Lai, Chun-Ta; Bible, Kenneth J.; Ehleringer, James R.

2017-09-01

Droughts in the western United States are expected to intensify with climate change. Thus, an adequate representation of ecosystem response to water stress in land models is critical for predicting carbon dynamics. The goal of this study was to evaluate the performance of the Community Land Model (CLM) version 4.5 against observations at an old-growth coniferous forest site in the Pacific Northwest region of the United States (Wind River AmeriFlux site), characterized by a Mediterranean climate that subjects trees to water stress each summer. CLM was driven by site-observed meteorology and calibrated primarily using parameter values observed at the site or at similar stands in the region. Key model adjustments included parameters controlling specific leaf area and stomatal conductance. Default values of these parameters led to significant underestimation of gross primary production, overestimation of evapotranspiration, and consequently overestimation of photosynthetic 13C discrimination, reflected in reduced 13C : 12C ratios of carbon fluxes and pools. Adjustments in soil hydraulic parameters within CLM were also critical, preventing significant underestimation of soil water content and unrealistic soil moisture stress during summer. After calibration, CLM was able to simulate energy and carbon fluxes, leaf area index, biomass stocks, and carbon isotope ratios of carbon fluxes and pools in reasonable agreement with site observations. Overall, the calibrated CLM was able to simulate the observed response of canopy conductance to atmospheric vapor pressure deficit (VPD) and soil water content, reasonably capturing the impact of water stress on ecosystem functioning. Both simulations and observations indicate that stomatal response from water stress at Wind River was primarily driven by VPD and not soil moisture. The calibration of the Ball-Berry stomatal conductance slope (mbb) at Wind River aligned with findings from recent CLM experiments at sites characterized by the same plant functional type (needleleaf evergreen temperate forest), despite significant differences in stand composition and age and climatology, suggesting that CLM could benefit from a revised mbb value of 6, rather than the default value of 9, for this plant functional type. Conversely, Wind River required a unique calibration of the hydrology submodel to simulate soil moisture, suggesting that the default hydrology has a more limited applicability. This study demonstrates that carbon isotope data can be used to constrain stomatal conductance and intrinsic water use efficiency in CLM, as an alternative to eddy covariance flux measurements. It also demonstrates that carbon isotopes can expose structural weaknesses in the model and provide a key constraint that may guide future model development.

Calibration facility for environment dosimetry instruments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bercea, Sorin; Celarel, Aurelia; Cenusa, Constantin

2013-12-16

In the last ten years, the nuclear activities, as well as the major nuclear events (see Fukushima accident) had an increasing impact on the environment, merely by contamination with radioactive materials. The most conferment way to quickly identify the presence of some radioactive elements in the environment, is to measure the dose-equivalent rate H. In this situation, information concerning the values of H due only to the natural radiation background must exist. Usually, the values of H due to the natural radiation background, are very low (∼10{sup −9} - 10{sup −8} Sv/h). A correct measurement of H in this rangemore » involve a performing calibration of the measuring instruments in the measuring range corresponding to the natural radiation background lead to important problems due to the presence of the natural background itself the best way to overlap this difficulty is to set up the calibration stand in an area with very low natural radiation background. In Romania, we identified an area with such special conditions at 200 m dept, in a salt mine. This paper deals with the necessary requirements for such a calibration facility, as well as with the calibration stand itself. The paper includes also, a description of the calibration stand (and images) as well as the radiological and metrological parameters. This calibration facilities for environment dosimetry is one of the few laboratories in this field in Europe.« less

Generalized Calibration of the Polarimetric Albedo Scale of Asteroids

NASA Astrophysics Data System (ADS)

Lupishko, D. F.

2018-03-01

Six different calibrations of the polarimetric albedo scale of asteroids have been published so far. Each of them contains its particular random and systematic errors and yields its values of geometric albedo. On the one hand, this complicates their analysis and comparison; on the other hand, it becomes more and more difficult to decide which of the proposed calibrations should be used. Moreover, in recent years, new databases on the albedo of asteroids obtained from the radiometric surveys of the sky with the orbital space facilities (the InfraRed Astronomical Satellite (IRAS), the Japanese astronomical satellite AKARI (which means "light"), the Wide-field Infrared Survey Explorer (WISE), and the Near-Earth Object Wide-field Survey Explorer (NEOWISE)) have appeared; and the database on the diameters and albedos of asteroids obtained from their occultations of stars has substantially increased. Here, we critically review the currently available calibrations and propose a new generalized calibration derived from the interrelations between the slope h and the albedo and between P min and the albedo. This calibration is based on all of the available series of the asteroid albedos and the most complete data on the polarization parameters of asteroids. The generalized calibration yields the values of the polarimetric albedo of asteroids in the system unified with the radiometric albedos and the albedos obtained from occultations of stars by asteroids. This, in turn, removes the difficulties in their comparison, joint analysis, etc.

Model Calibration Efforts for the International Space Station's Solar Array Mast

NASA Technical Reports Server (NTRS)

Elliott, Kenny B.; Horta, Lucas G.; Templeton, Justin D.; Knight, Norman F., Jr.

2012-01-01

The International Space Station (ISS) relies on sixteen solar-voltaic blankets to provide electrical power to the station. Each pair of blankets is supported by a deployable boom called the Folding Articulated Square Truss Mast (FAST Mast). At certain ISS attitudes, the solar arrays can be positioned in such a way that shadowing of either one or three longerons causes an unexpected asymmetric thermal loading that if unchecked can exceed the operational stability limits of the mast. Work in this paper documents part of an independent NASA Engineering and Safety Center effort to assess the existing operational limits. Because of the complexity of the system, the problem is being worked using a building-block progression from components (longerons), to units (single or multiple bays), to assembly (full mast). The paper presents results from efforts to calibrate the longeron components. The work includes experimental testing of two types of longerons (straight and tapered), development of Finite Element (FE) models, development of parameter uncertainty models, and the establishment of a calibration and validation process to demonstrate adequacy of the models. Models in the context of this paper refer to both FE model and probabilistic parameter models. Results from model calibration of the straight longerons show that the model is capable of predicting the mean load, axial strain, and bending strain. For validation, parameter values obtained from calibration of straight longerons are used to validate experimental results for the tapered longerons.

Soybean Physiology Calibration in the Community Land Model

NASA Astrophysics Data System (ADS)

Drewniak, B. A.; Bilionis, I.; Constantinescu, E. M.

2014-12-01

With the large influence of agricultural land use on biophysical and biogeochemical cycles, integrating cultivation into Earth System Models (ESMs) is increasingly important. The Community Land Model (CLM) was augmented with a CLM-Crop extension that simulates the development of three crop types: maize, soybean, and spring wheat. The CLM-Crop model is a complex system that relies on a suite of parametric inputs that govern plant growth under a given atmospheric forcing and available resources. However, the strong nonlinearity of ESMs makes parameter fitting a difficult task. In this study, our goal is to calibrate ten of the CLM-Crop parameters for one crop type, soybean, in order to improve model projection of plant development and carbon fluxes. We used measurements of gross primary productivity, net ecosystem exchange, and plant biomass from AmeriFlux sites to choose parameter values that optimize crop productivity in the model. Calibration is performed in a Bayesian framework by developing a scalable and adaptive scheme based on sequential Monte Carlo (SMC). Our scheme can perform model calibration using very few evaluations and, by exploiting parallelism, at a fraction of the time required by plain vanilla Markov Chain Monte Carlo (MCMC). We present the results from a twin experiment (self-validation) and calibration results and validation using real observations from an AmeriFlux tower site in the Midwestern United States, for the soybean crop type. The improved model will help researchers understand how climate affects crop production and resulting carbon fluxes, and additionally, how cultivation impacts climate.

Posterior uncertainty of GEOS-5 L-band radiative transfer model parameters and brightness temperatures after calibration with SMOS observations

NASA Astrophysics Data System (ADS)

De Lannoy, G. J.; Reichle, R. H.; Vrugt, J. A.

2012-12-01

Simulated L-band (1.4 GHz) brightness temperatures are very sensitive to the values of the parameters in the radiative transfer model (RTM). We assess the optimum RTM parameter values and their (posterior) uncertainty in the Goddard Earth Observing System (GEOS-5) land surface model using observations of multi-angular brightness temperature over North America from the Soil Moisture Ocean Salinity (SMOS) mission. Two different parameter estimation methods are being compared: (i) a particle swarm optimization (PSO) approach, and (ii) an MCMC simulation procedure using the differential evolution adaptive Metropolis (DREAM) algorithm. Our results demonstrate that both methods provide similar "optimal" parameter values. Yet, DREAM exhibits better convergence properties, resulting in a reduced spread of the posterior ensemble. The posterior parameter distributions derived with both methods are used for predictive uncertainty estimation of brightness temperature. This presentation will highlight our model-data synthesis framework and summarize our initial findings.

Experimental techniques for the calibration of lidar depolarization channels in EARLINET

NASA Astrophysics Data System (ADS)

Belegante, Livio; Bravo-Aranda, Juan Antonio; Freudenthaler, Volker; Nicolae, Doina; Nemuc, Anca; Ene, Dragos; Alados-Arboledas, Lucas; Amodeo, Aldo; Pappalardo, Gelsomina; D'Amico, Giuseppe; Amato, Francesco; Engelmann, Ronny; Baars, Holger; Wandinger, Ulla; Papayannis, Alexandros; Kokkalis, Panos; Pereira, Sérgio N.

2018-02-01

Particle depolarization ratio retrieved from lidar measurements are commonly used for aerosol-typing studies, microphysical inversion, or mass concentration retrievals. The particle depolarization ratio is one of the primary parameters that can differentiate several major aerosol components but only if the measurements are accurate enough. The accuracy related to the retrieval of particle depolarization ratios is the driving factor for assessing and improving the uncertainties of the depolarization products. This paper presents different depolarization calibration procedures used to improve the quality of the depolarization data. The results illustrate a significant improvement of the depolarization lidar products for all the selected lidar stations that have implemented depolarization calibration procedures. The calibrated volume and particle depolarization profiles at 532 nm show values that fall within a range that is generally accepted in the literature.

Temperature corrected-calibration of GRACE's accelerometer

NASA Astrophysics Data System (ADS)

Encarnacao, J.; Save, H.; Siemes, C.; Doornbos, E.; Tapley, B. D.

2017-12-01

Since April 2011, the thermal control of the accelerometers on board the GRACE satellites has been turned off. The time series of along-track bias clearly show a drastic change in the behaviour of this parameter, while the calibration model has remained unchanged throughout the entire mission lifetime. In an effort to improve the quality of the gravity field models produced at CSR in future mission-long re-processing of GRACE data, we quantify the added value of different calibration strategies. In one approach, the temperature effects that distort the raw accelerometer measurements collected without thermal control are corrected considering the housekeeping temperature readings. In this way, one single calibration strategy can be consistently applied during the whole mission lifetime, since it is valid to thermal the conditions before and after April 2011. Finally, we illustrate that the resulting calibrated accelerations are suitable for neutral thermospheric density studies.

OPR-PPR, a Computer Program for Assessing Data Importance to Model Predictions Using Linear Statistics

USGS Publications Warehouse

Tonkin, Matthew J.; Tiedeman, Claire; Ely, D. Matthew; Hill, Mary C.

2007-01-01

The OPR-PPR program calculates the Observation-Prediction (OPR) and Parameter-Prediction (PPR) statistics that can be used to evaluate the relative importance of various kinds of data to simulated predictions. The data considered fall into three categories: (1) existing observations, (2) potential observations, and (3) potential information about parameters. The first two are addressed by the OPR statistic; the third is addressed by the PPR statistic. The statistics are based on linear theory and measure the leverage of the data, which depends on the location, the type, and possibly the time of the data being considered. For example, in a ground-water system the type of data might be a head measurement at a particular location and time. As a measure of leverage, the statistics do not take into account the value of the measurement. As linear measures, the OPR and PPR statistics require minimal computational effort once sensitivities have been calculated. Sensitivities need to be calculated for only one set of parameter values; commonly these are the values estimated through model calibration. OPR-PPR can calculate the OPR and PPR statistics for any mathematical model that produces the necessary OPR-PPR input files. In this report, OPR-PPR capabilities are presented in the context of using the ground-water model MODFLOW-2000 and the universal inverse program UCODE_2005. The method used to calculate the OPR and PPR statistics is based on the linear equation for prediction standard deviation. Using sensitivities and other information, OPR-PPR calculates (a) the percent increase in the prediction standard deviation that results when one or more existing observations are omitted from the calibration data set; (b) the percent decrease in the prediction standard deviation that results when one or more potential observations are added to the calibration data set; or (c) the percent decrease in the prediction standard deviation that results when potential information on one or more parameters is added.

Validation and calibration of structural models that combine information from multiple sources.

PubMed

Dahabreh, Issa J; Wong, John B; Trikalinos, Thomas A

2017-02-01

Mathematical models that attempt to capture structural relationships between their components and combine information from multiple sources are increasingly used in medicine. Areas covered: We provide an overview of methods for model validation and calibration and survey studies comparing alternative approaches. Expert commentary: Model validation entails a confrontation of models with data, background knowledge, and other models, and can inform judgments about model credibility. Calibration involves selecting parameter values to improve the agreement of model outputs with data. When the goal of modeling is quantitative inference on the effects of interventions or forecasting, calibration can be viewed as estimation. This view clarifies issues related to parameter identifiability and facilitates formal model validation and the examination of consistency among different sources of information. In contrast, when the goal of modeling is the generation of qualitative insights about the modeled phenomenon, calibration is a rather informal process for selecting inputs that result in model behavior that roughly reproduces select aspects of the modeled phenomenon and cannot be equated to an estimation procedure. Current empirical research on validation and calibration methods consists primarily of methodological appraisals or case-studies of alternative techniques and cannot address the numerous complex and multifaceted methodological decisions that modelers must make. Further research is needed on different approaches for developing and validating complex models that combine evidence from multiple sources.

Stochastic isotropic hyperelastic materials: constitutive calibration and model selection

NASA Astrophysics Data System (ADS)

Mihai, L. Angela; Woolley, Thomas E.; Goriely, Alain

2018-03-01

Biological and synthetic materials often exhibit intrinsic variability in their elastic responses under large strains, owing to microstructural inhomogeneity or when elastic data are extracted from viscoelastic mechanical tests. For these materials, although hyperelastic models calibrated to mean data are useful, stochastic representations accounting also for data dispersion carry extra information about the variability of material properties found in practical applications. We combine finite elasticity and information theories to construct homogeneous isotropic hyperelastic models with random field parameters calibrated to discrete mean values and standard deviations of either the stress-strain function or the nonlinear shear modulus, which is a function of the deformation, estimated from experimental tests. These quantities can take on different values, corresponding to possible outcomes of the experiments. As multiple models can be derived that adequately represent the observed phenomena, we apply Occam's razor by providing an explicit criterion for model selection based on Bayesian statistics. We then employ this criterion to select a model among competing models calibrated to experimental data for rubber and brain tissue under single or multiaxial loads.

40 CFR Appendix I to Part 92 - Emission Related Locomotive and Engine Parameters and Specifications

Code of Federal Regulations, 2010 CFR

2010-07-01

.... b. Idle mixture. c. Transient enrichment system calibration. d. Starting enrichment system... shutoff system calibration. d. Starting enrichment system calibration. e. Transient enrichment system... parameters and calibrations. b. Transient enrichment system calibration. c. Air-fuel flow calibration. d...

Point Cloud Refinement with a Target-Free Intrinsic Calibration of a Mobile Multi-Beam LIDAR System

NASA Astrophysics Data System (ADS)

Nouiraa, H.; Deschaud, J. E.; Goulettea, F.

2016-06-01

LIDAR sensors are widely used in mobile mapping systems. The mobile mapping platforms allow to have fast acquisition in cities for example, which would take much longer with static mapping systems. The LIDAR sensors provide reliable and precise 3D information, which can be used in various applications: mapping of the environment; localization of objects; detection of changes. Also, with the recent developments, multi-beam LIDAR sensors have appeared, and are able to provide a high amount of data with a high level of detail. A mono-beam LIDAR sensor mounted on a mobile platform will have an extrinsic calibration to be done, so the data acquired and registered in the sensor reference frame can be represented in the body reference frame, modeling the mobile system. For a multibeam LIDAR sensor, we can separate its calibration into two distinct parts: on one hand, we have an extrinsic calibration, in common with mono-beam LIDAR sensors, which gives the transformation between the sensor cartesian reference frame and the body reference frame. On the other hand, there is an intrinsic calibration, which gives the relations between the beams of the multi-beam sensor. This calibration depends on a model given by the constructor, but the model can be non optimal, which would bring errors and noise into the acquired point clouds. In the litterature, some optimizations of the calibration parameters are proposed, but need a specific routine or environment, which can be constraining and time-consuming. In this article, we present an automatic method for improving the intrinsic calibration of a multi-beam LIDAR sensor, the Velodyne HDL-32E. The proposed approach does not need any calibration target, and only uses information from the acquired point clouds, which makes it simple and fast to use. Also, a corrected model for the Velodyne sensor is proposed. An energy function which penalizes points far from local planar surfaces is used to optimize the different proposed parameters for the corrected model, and we are able to give a confidence value for the calibration parameters found. Optimization results on both synthetic and real data are presented.

Nutrient modeling for a semi-intensive IMC pond: an MS-Excel approach.

PubMed

Ray, Lala I P; Mal, B C; Moulick, S

2017-11-01

Semi-intensive Indian Major Carp (IMC) culture was practised in polythene lined dugout ponds at the Aquacultural Farm of Indian Institute of Technology, Kharagpur, West Bengal for 3 consecutive years at three different stocking densities (S.D), viz., 20,000, 35,000 and 50,000 numbers of fingerlings per hectare of water spread area. Fingerlings of Catla, Rohu and Mrigal were raised at a stocking ratio of 4:3:3. Total ammonia nitrogen (TAN) value along with other fishpond water quality parameters was monitored at 1 day intervals to ensure a good water ecosystem for a better fish growth. Water exchange was carried out before the TAN reached the critical limit. Field data on TAN obtained from the cultured fishponds stocked with three different stocking densities were used to study the dynamics of TAN. A developed model used to study the nutrient dynamics in shrimp pond was used to validate the observed data in the IMC pond ecosystem. Two years of observed TAN data were used to calibrate the spreadsheet model and the same model was validated using the third year observed data. The manual calibration based on the trial and error process of parameters adjustments was used and several simulations were performed by changing the model parameters. After adjustment of each parameter, the simulated and measured values of the water quality parameters were compared to judge the improvement in the model prediction. Forward finite difference discretization method was used in a MS-Excel spreadsheet to calibrate and validate the model for obtaining the TAN levels during the culture period. Observed data from the cultured fishponds of three different S.D were used to standardize 13 model parameters. The efficiency of the developed spreadsheet model was found to be more than 90% for the TAN estimation in the IMC cultured fishponds.

Calibration of a turbidity meter for making estimates of total suspended solids concentrations and beam attenuation coefficients in field experiments

NASA Technical Reports Server (NTRS)

Usry, J. W.; Whitlock, C. H.

1981-01-01

Management of water resources such as a reservoir requires using analytical models which describe such parameters as the suspended sediment field. To select or develop an appropriate model requires making many measurements to describe the distribution of this parameter in the water column. One potential method for making those measurements expeditiously is to measure light transmission or turbidity and relate that parameter to total suspended solids concentrations. An instrument which may be used for this purpose was calibrated by generating curves of transmission measurements plotted against measured values of total suspended solids concentrations and beam attenuation coefficients. Results of these experiments indicate that field measurements made with this instrument using curves generated in this study should correlate with total suspended solids concentrations and beam attenuation coefficients in the water column within 20 percent.

Calibration of a dual-PTZ camera system for stereo vision

NASA Astrophysics Data System (ADS)

Chang, Yau-Zen; Hou, Jung-Fu; Tsao, Yi Hsiang; Lee, Shih-Tseng

2010-08-01

In this paper, we propose a calibration process for the intrinsic and extrinsic parameters of dual-PTZ camera systems. The calibration is based on a complete definition of six coordinate systems fixed at the image planes, and the pan and tilt rotation axes of the cameras. Misalignments between estimated and ideal coordinates of image corners are formed into cost values to be solved by the Nelder-Mead simplex optimization method. Experimental results show that the system is able to obtain 3D coordinates of objects with a consistent accuracy of 1 mm when the distance between the dual-PTZ camera set and the objects are from 0.9 to 1.1 meters.

Application of the US Geological Survey's precipitation-runoff modeling system to Williams Draw and Bush Draw basins, Jackson County, Colorado

USGS Publications Warehouse

Kuhn, Gerhard

1988-01-01

The U.S. Geological Survey 's precipitation-runoff modeling system was calibrated for this study by using daily streamflow data for April through September, 1980 and 1981, from the Williams Draw basin in Jackson County, Colorado. The calibrated model then was verified by using daily streamflow data for April through September, 1982 and 1983. Transferability of the model was tested by application to adjoining Bush Draw basin by using daily streamflow data for April through September, 1981 through 1983. Four model parameters were optimized in the calibration: (1) BST, base air temperature used to determine the form of precipitation (rain, snow, or a mixture); (2) SMAX, maximum available water-holding capacity of the soil zone; (3) TRNCF, transmission coefficient for the vegetation canopy over the snowpack; and (4) DSCOR, daily precipitation correction factor for snow. For calibration and verification, volume and timing of simulated streamflow were reasonably close to recorded streamflow; differences were least during years that had considerable snowpack accumulation and were most during years that had minimal or no snowpack accumulation. Calibration and optimization of parameters were facilitated by snowpack water-equivalent data. Application of the model to Bush Draw basin to test for transferability indicated inaccurate results in simulation of streamflow volume. Weighted values of SMAX, TRNCF, and DSCOR from the calibration basin were used for Bush Draw. The inadequate results obtained by use of weighted parameters indicate that snowpack water-equivalent data are needed for successful application of the precipitation-runoff modeling system in this area, because frequent windy conditions cause variations in snowpack accumulation. (USGS)

Technical note: Bayesian calibration of dynamic ruminant nutrition models.

PubMed

Reed, K F; Arhonditsis, G B; France, J; Kebreab, E

2016-08-01

Mechanistic models of ruminant digestion and metabolism have advanced our understanding of the processes underlying ruminant animal physiology. Deterministic modeling practices ignore the inherent variation within and among individual animals and thus have no way to assess how sources of error influence model outputs. We introduce Bayesian calibration of mathematical models to address the need for robust mechanistic modeling tools that can accommodate error analysis by remaining within the bounds of data-based parameter estimation. For the purpose of prediction, the Bayesian approach generates a posterior predictive distribution that represents the current estimate of the value of the response variable, taking into account both the uncertainty about the parameters and model residual variability. Predictions are expressed as probability distributions, thereby conveying significantly more information than point estimates in regard to uncertainty. Our study illustrates some of the technical advantages of Bayesian calibration and discusses the future perspectives in the context of animal nutrition modeling. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Sorption testing and generalized composite surface complexation models for determining uranium sorption parameters at a proposed in-situ recovery site

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, Raymond H.; Truax, Ryan A.; Lankford, David A.

Solid-phase iron concentrations and generalized composite surface complexation models were used to evaluate procedures in determining uranium sorption on oxidized aquifer material at a proposed U in situ recovery (ISR) site. At the proposed Dewey Burdock ISR site in South Dakota, USA, oxidized aquifer material occurs downgradient of the U ore zones. Solid-phase Fe concentrations did not explain our batch sorption test results,though total extracted Fe appeared to be positively correlated with overall measured U sorption. Batch sorption test results were used to develop generalized composite surface complexation models that incorporated the full genericsorption potential of each sample, without detailedmore » mineralogiccharacterization. The resultant models provide U sorption parameters (site densities and equilibrium constants) for reactive transport modeling. The generalized composite surface complexation sorption models were calibrated to batch sorption data from three oxidized core samples using inverse modeling, and gave larger sorption parameters than just U sorption on the measured solidphase Fe. These larger sorption parameters can significantly influence reactive transport modeling, potentially increasing U attenuation. Because of the limited number of calibration points, inverse modeling required the reduction of estimated parameters by fixing two parameters. The best-fit models used fixed values for equilibrium constants, with the sorption site densities being estimated by the inversion process. While these inverse routines did provide best-fit sorption parameters, local minima and correlated parameters might require further evaluation. Despite our limited number of proxy samples, the procedures presented provide a valuable methodology to consider for sites where metal sorption parameters are required. Furthermore, these sorption parameters can be used in reactive transport modeling to assess downgradient metal attenuation, especially when no other calibration data are available, such as at proposed U ISR sites.« less

Sorption testing and generalized composite surface complexation models for determining uranium sorption parameters at a proposed in-situ recovery site

DOE PAGES

Johnson, Raymond H.; Truax, Ryan A.; Lankford, David A.; ...

2016-02-03

Solid-phase iron concentrations and generalized composite surface complexation models were used to evaluate procedures in determining uranium sorption on oxidized aquifer material at a proposed U in situ recovery (ISR) site. At the proposed Dewey Burdock ISR site in South Dakota, USA, oxidized aquifer material occurs downgradient of the U ore zones. Solid-phase Fe concentrations did not explain our batch sorption test results,though total extracted Fe appeared to be positively correlated with overall measured U sorption. Batch sorption test results were used to develop generalized composite surface complexation models that incorporated the full genericsorption potential of each sample, without detailedmore » mineralogiccharacterization. The resultant models provide U sorption parameters (site densities and equilibrium constants) for reactive transport modeling. The generalized composite surface complexation sorption models were calibrated to batch sorption data from three oxidized core samples using inverse modeling, and gave larger sorption parameters than just U sorption on the measured solidphase Fe. These larger sorption parameters can significantly influence reactive transport modeling, potentially increasing U attenuation. Because of the limited number of calibration points, inverse modeling required the reduction of estimated parameters by fixing two parameters. The best-fit models used fixed values for equilibrium constants, with the sorption site densities being estimated by the inversion process. While these inverse routines did provide best-fit sorption parameters, local minima and correlated parameters might require further evaluation. Despite our limited number of proxy samples, the procedures presented provide a valuable methodology to consider for sites where metal sorption parameters are required. Furthermore, these sorption parameters can be used in reactive transport modeling to assess downgradient metal attenuation, especially when no other calibration data are available, such as at proposed U ISR sites.« less

Gaia FGK benchmark stars: Metallicity

NASA Astrophysics Data System (ADS)

Jofré, P.; Heiter, U.; Soubiran, C.; Blanco-Cuaresma, S.; Worley, C. C.; Pancino, E.; Cantat-Gaudin, T.; Magrini, L.; Bergemann, M.; González Hernández, J. I.; Hill, V.; Lardo, C.; de Laverny, P.; Lind, K.; Masseron, T.; Montes, D.; Mucciarelli, A.; Nordlander, T.; Recio Blanco, A.; Sobeck, J.; Sordo, R.; Sousa, S. G.; Tabernero, H.; Vallenari, A.; Van Eck, S.

2014-04-01

Context. To calibrate automatic pipelines that determine atmospheric parameters of stars, one needs a sample of stars, or "benchmark stars", with well-defined parameters to be used as a reference. Aims: We provide detailed documentation of the iron abundance determination of the 34 FGK-type benchmark stars that are selected to be the pillars for calibration of the one billion Gaia stars. They cover a wide range of temperatures, surface gravities, and metallicities. Methods: Up to seven different methods were used to analyze an observed spectral library of high resolutions and high signal-to-noise ratios. The metallicity was determined by assuming a value of effective temperature and surface gravity obtained from fundamental relations; that is, these parameters were known a priori and independently from the spectra. Results: We present a set of metallicity values obtained in a homogeneous way for our sample of benchmark stars. In addition to this value, we provide detailed documentation of the associated uncertainties. Finally, we report a value of the metallicity of the cool giant ψ Phe for the first time. Based on NARVAL and HARPS data obtained within the Gaia DPAC (Data Processing and Analysis Consortium) and coordinated by the GBOG (Ground-Based Observations for Gaia) working group and on data retrieved from the ESO-ADP database.Tables 6-76 are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/564/A133

Using land subsidence observations for groundwater model calibration

NASA Astrophysics Data System (ADS)

Tufekci, Nesrin; Schoups, Gerrit; Faitouri, Mohamed Al; Mahapatra, Pooja; van de Giesen, Nick; Hanssen, Ramon

2017-04-01

PS-InSAR derived subsidence and groundwater level time series are used to calibrate a groundwater model of Tazerbo well field, Libya, by estimating spatially varying elastic skeletal storage (Sske) and hydraulic conductivity (Hk) of the model area. Tazerbo well field is a part of the Great Man-Made River Project (GMMRP) designed with 108 wells and total pumping rate of 1 million m3/day. The water is pumped from the deep sandstone aquifer (Nubian sandstone), which is overlaid by a thick mudstone-siltstone aquitard. Pumping related deformation patterns around Tazerbo well field are obtained by processing 20 descending Envisat scenes for the period between 2004 and 2010, which yield a concentrated deformation around the well field with the maximum deformation rate around 4 mm/yr. The trends of time series of groundwater head and subsidence are in good agreement for observation wells located in the vicinity of the pumping wells and the pattern of subsidence correlates with the locations of active wells. At the beginning of calibration, different pairs of Sske and Hk are assigned at observation well locations by trial and error so that the simulation results of the forward model would approximate heads and mean linear deformation velocity at these locations. Accordingly, the estimated initial parameters suggest relatively constant Hk(5 m/d) and increasing Sske from south to north (1x10-6 m-1 - 5x10-6 m-1). In order to refine their spatial distribution, representative values of Sske and Hk are assigned at 25 equidistant points over the area, which are restricted by the predetermined values. To calibrate the parameters at assigned locations UCODE is used along with MATLAB. Once the convergence is achieved the estimated parameter values at these locations are held constant and new "in between - equidistant" locations are determined to estimate Sske and Hk in order to spatially refine their distribution. This approach is followed until the relation between observed and simulated results cannot be improved anymore. The final results, show good relation in the areas close to well sites, while difference between simulated and observed values increases towards the southeast boundary of PS-InSAR observations. This divergence can be explained by i) the uncertainty in the parameters at the southeast part of the model area, due to lack of deformation observations, ii) Sske may have been underestimated at the locations with thin aquifer and thick aquitard material.

Uncertainty and the Social Cost of Methane Using Bayesian Constrained Climate Models

NASA Astrophysics Data System (ADS)

Errickson, F. C.; Anthoff, D.; Keller, K.

2016-12-01

Social cost estimates of greenhouse gases are important for the design of sound climate policies and are also plagued by uncertainty. One major source of uncertainty stems from the simplified representation of the climate system used in the integrated assessment models that provide these social cost estimates. We explore how uncertainty over the social cost of methane varies with the way physical processes and feedbacks in the methane cycle are modeled by (i) coupling three different methane models to a simple climate model, (ii) using MCMC to perform a Bayesian calibration of the three coupled climate models that simulates direct sampling from the joint posterior probability density function (pdf) of model parameters, and (iii) producing probabilistic climate projections that are then used to calculate the Social Cost of Methane (SCM) with the DICE and FUND integrated assessment models. We find that including a temperature feedback in the methane cycle acts as an additional constraint during the calibration process and results in a correlation between the tropospheric lifetime of methane and several climate model parameters. This correlation is not seen in the models lacking this feedback. Several of the estimated marginal pdfs of the model parameters also exhibit different distributional shapes and expected values depending on the methane model used. As a result, probabilistic projections of the climate system out to the year 2300 exhibit different levels of uncertainty and magnitudes of warming for each of the three models under an RCP8.5 scenario. We find these differences in climate projections result in differences in the distributions and expected values for our estimates of the SCM. We also examine uncertainty about the SCM by performing a Monte Carlo analysis using a distribution for the climate sensitivity while holding all other climate model parameters constant. Our SCM estimates using the Bayesian calibration are lower and exhibit less uncertainty about extremely high values in the right tail of the distribution compared to the Monte Carlo approach. This finding has important climate policy implications and suggests previous work that accounts for climate model uncertainty by only varying the climate sensitivity parameter may overestimate the SCM.

Calibration of Watershed Lag Time Equation for Philippine Hydrology using RADARSAT Digital Elevation Models

NASA Astrophysics Data System (ADS)

Cipriano, F. R.; Lagmay, A. M. A.; Horritt, M.; Mendoza, J.; Sabio, G.; Punay, K. N.; Taniza, H. J.; Uichanco, C.

2015-12-01

Widespread flooding is a major problem in the Philippines. The country experiences heavy amount of rainfall throughout the year and several areas are prone to flood hazards because of its unique topography. Human casualties and destruction of infrastructure are just some of the damages caused by flooding and the Philippine government has undertaken various efforts to mitigate these hazards. One of the solutions was to create flood hazard maps of different floodplains and use them to predict the possible catastrophic results of different rain scenarios. To produce these maps with accurate output, different input parameters were needed and one of those is calculating hydrological components from topographical data. This paper presents how a calibrated lag time (TL) equation was obtained using measurable catchment parameters. Lag time is an essential input in flood mapping and is defined as the duration between the peak rainfall and peak discharge of the watershed. The lag time equation involves three measurable parameters, namely, watershed length (L), maximum potential retention (S) derived from the curve number, and watershed slope (Y), all of which were available from RADARSAT Digital Elevation Models (DEM). This approach was based on a similar method developed by CH2M Hill and Horritt for Taiwan, which has a similar set of meteorological and hydrological parameters with the Philippines. Rainfall data from fourteen water level sensors covering 67 storms from all the regions in the country were used to estimate the actual lag time. These sensors were chosen by using a screening process that considers the distance of the sensors from the sea, the availability of recorded data, and the catchment size. The actual lag time values were plotted against the values obtained from the Natural Resource Conservation Management handbook lag time equation. Regression analysis was used to obtain the final calibrated equation that would be used to calculate the lag time specifically for rivers in the Philippine setting. The calculated lag time values could then be used as a parameter for modeling different flood scenarios in the country.

Ground Albedo Neutron Sensing (GANS) method for measurements of soil moisture in cropped fields

NASA Astrophysics Data System (ADS)

Andres Rivera Villarreyes, Carlos; Baroni, Gabriele; Oswald, Sascha E.

2013-04-01

Measurement of soil moisture at the plot or hill-slope scale is an important link between local vadose zone hydrology and catchment hydrology. However, so far only few methods are on the way to close this gap between point measurements and remote sensing. This study evaluates the applicability of the Ground Albedo Neutron Sensing (GANS) for integral quantification of seasonal soil moisture in the root zone at the scale of a field or small watershed, making use of the crucial role of hydrogen as neutron moderator relative to other landscape materials. GANS measurements were performed at two locations in Germany under different vegetative situations and seasonal conditions. Ground albedo neutrons were measured at (i) a lowland Bornim farmland (Brandenburg) cropped with sunflower in 2011 and winter rye in 2012, and (ii) a mountainous farmland catchment (Schaefertal, Harz Mountains) since middle 2011. At both sites depth profiles of soil moisture were measured at several locations in parallel by frequency domain reflectometry (FDR) for comparison and calibration. Initially, calibration parameters derived from a previous study with corn cover were tested under sunflower and winter rye periods at the same farmland. GANS soil moisture based on these parameters showed a large discrepancy compared to classical soil moisture measurements. Therefore, two new calibration approaches and four different ways of integration the soil moisture profile to an integral value for GANS were evaluated in this study. This included different sets of calibration parameters based on different growing periods of sunflower. New calibration parameters showed a good agreement with FDR network during sunflower period (RMSE = 0.023 m3 m-3), but they underestimated soil moisture in the winter rye period. The GANS approach resulted to be highly affected by temporal changes of biomass and crop types which suggest the need of neutron corrections for long-term observations with crop rotation. Finally, Bornim sunflower parameters were transferred to Schaefertal catchment for further evaluation. This study proves GANS potential to close the measurement gap between point scale and remote sensing scale; however, its calibration needs to be adapted for vegetation in cropped fields.

Microbial models with data-driven parameters predict stronger soil carbon responses to climate change.

PubMed

Hararuk, Oleksandra; Smith, Matthew J; Luo, Yiqi

2015-06-01

Long-term carbon (C) cycle feedbacks to climate depend on the future dynamics of soil organic carbon (SOC). Current models show low predictive accuracy at simulating contemporary SOC pools, which can be improved through parameter estimation. However, major uncertainty remains in global soil responses to climate change, particularly uncertainty in how the activity of soil microbial communities will respond. To date, the role of microbes in SOC dynamics has been implicitly described by decay rate constants in most conventional global carbon cycle models. Explicitly including microbial biomass dynamics into C cycle model formulations has shown potential to improve model predictive performance when assessed against global SOC databases. This study aimed to data-constrained parameters of two soil microbial models, evaluate the improvements in performance of those calibrated models in predicting contemporary carbon stocks, and compare the SOC responses to climate change and their uncertainties between microbial and conventional models. Microbial models with calibrated parameters explained 51% of variability in the observed total SOC, whereas a calibrated conventional model explained 41%. The microbial models, when forced with climate and soil carbon input predictions from the 5th Coupled Model Intercomparison Project (CMIP5), produced stronger soil C responses to 95 years of climate change than any of the 11 CMIP5 models. The calibrated microbial models predicted between 8% (2-pool model) and 11% (4-pool model) soil C losses compared with CMIP5 model projections which ranged from a 7% loss to a 22.6% gain. Lastly, we observed unrealistic oscillatory SOC dynamics in the 2-pool microbial model. The 4-pool model also produced oscillations, but they were less prominent and could be avoided, depending on the parameter values. © 2014 John Wiley & Sons Ltd.

Using sensitivity analysis in model calibration efforts

USGS Publications Warehouse

Tiedeman, Claire; Hill, Mary C.

2003-01-01

In models of natural and engineered systems, sensitivity analysis can be used to assess relations among system state observations, model parameters, and model predictions. The model itself links these three entities, and model sensitivities can be used to quantify the links. Sensitivities are defined as the derivatives of simulated quantities (such as simulated equivalents of observations, or model predictions) with respect to model parameters. We present four measures calculated from model sensitivities that quantify the observation-parameter-prediction links and that are especially useful during the calibration and prediction phases of modeling. These four measures are composite scaled sensitivities (CSS), prediction scaled sensitivities (PSS), the value of improved information (VOII) statistic, and the observation prediction (OPR) statistic. These measures can be used to help guide initial calibration of models, collection of field data beneficial to model predictions, and recalibration of models updated with new field information. Once model sensitivities have been calculated, each of the four measures requires minimal computational effort. We apply the four measures to a three-layer MODFLOW-2000 (Harbaugh et al., 2000; Hill et al., 2000) model of the Death Valley regional ground-water flow system (DVRFS), located in southern Nevada and California. D’Agnese et al. (1997, 1999) developed and calibrated the model using nonlinear regression methods. Figure 1 shows some of the observations, parameters, and predictions for the DVRFS model. Observed quantities include hydraulic heads and spring flows. The 23 defined model parameters include hydraulic conductivities, vertical anisotropies, recharge rates, evapotranspiration rates, and pumpage. Predictions of interest for this regional-scale model are advective transport paths from potential contamination sites underlying the Nevada Test Site and Yucca Mountain.

Validation of geometric models for fisheye lenses

NASA Astrophysics Data System (ADS)

Schneider, D.; Schwalbe, E.; Maas, H.-G.

The paper focuses on the photogrammetric investigation of geometric models for different types of optical fisheye constructions (equidistant, equisolid-angle, sterographic and orthographic projection). These models were implemented and thoroughly tested in a spatial resection and a self-calibrating bundle adjustment. For this purpose, fisheye images were taken with a Nikkor 8 mm fisheye lens on a Kodak DSC 14n Pro digital camera in a hemispherical calibration room. Both, the spatial resection and the bundle adjustment resulted in a standard deviation of unit weight of 1/10 pixel with a suitable set of simultaneous calibration parameters introduced into the camera model. The camera-lens combination was treated with all of the four basic models mentioned above. Using the same set of additional lens distortion parameters, the differences between the models can largely be compensated, delivering almost the same precision parameters. The relative object space precision obtained from the bundle adjustment was ca. 1:10 000 of the object dimensions. This value can be considered as a very satisfying result, as fisheye images generally have a lower geometric resolution as a consequence of their large field of view and also have a inferior imaging quality in comparison to most central perspective lenses.

Parameterization and Uncertainty Analysis of SWAT model in Hydrological Simulation of Chaohe River Basin

NASA Astrophysics Data System (ADS)

Jie, M.; Zhang, J.; Guo, B. B.

2017-12-01

As a typical distributed hydrological model, the SWAT model also has a challenge in calibrating parameters and analysis their uncertainty. This paper chooses the Chaohe River Basin China as the study area, through the establishment of the SWAT model, loading the DEM data of the Chaohe river basin, the watershed is automatically divided into several sub-basins. Analyzing the land use, soil and slope which are on the basis of the sub-basins and calculating the hydrological response unit (HRU) of the study area, after running SWAT model, the runoff simulation values in the watershed are obtained. On this basis, using weather data, known daily runoff of three hydrological stations, combined with the SWAT-CUP automatic program and the manual adjustment method are used to analyze the multi-site calibration of the model parameters. Furthermore, the GLUE algorithm is used to analyze the parameters uncertainty of the SWAT model. Through the sensitivity analysis, calibration and uncertainty study of SWAT, the results indicate that the parameterization of the hydrological characteristics of the Chaohe river is successful and feasible which can be used to simulate the Chaohe river basin.

Calibration strategy for the COROT photometry

NASA Astrophysics Data System (ADS)

Buey, J.-T.; Auvergne, M.; Lapeyrere, V.; Boumier, P.

2004-01-01

Like Eddington, the COROT photometer will measure very small fluctutions on a large signal: the amplitudes of planetary transits and solar-like oscillations are expressed in ppm (parts per million). For such an instrument, specific calibration has to be done during the different phases of the development of the instrument and of all the subsystems. Two main things have to be taken into account: - the calibration during the study phase; - the calibration of the sub-systems and building of numerical models. The first item allows us to clearly understand all the perturbations (internal and external) and to identify their relative impacts on the expected signal (by numerical models including expected values of perturbations and sensitivity of the instrument). Methods and a schedule for the calibration process can also be introduced, in good agreement with the development plan of the instrument. The second item is more related to the measurement of the sensitivity of the instrument and all its sub-systems. As the instrument is designed to be as stable as possible, we have to mix measurements (with larger fluctuations of parameters than expected) and numerical models. Some typical reasons for that are: - there are many parameters to introduce in the measurements and results from some models (bread-board for example) may be extrapolated to the flight model; - larger fluctuations than expected are used (to measure precisely the sensitivity) and numerical models give the real value of noise with the expected fluctuations. - Characteristics of sub-systems may be measured and models used to give the sensitivity of the whole system built with them, as end-to-end measurements may be impossible (time, budget, physical limitations). Also, house-keeping measurements have to be set up on the critical parts of the sub-systems: measurements on thermal probes, power supply, pointing, etc. All these house-keeping data are used during ground calibration and during the flight, so that correct correlation between signal and house-keeping can be achieved.

Fragmentation modeling of a resin bonded sand

NASA Astrophysics Data System (ADS)

Hilth, William; Ryckelynck, David

2017-06-01

Cemented sands exhibit a complex mechanical behavior that can lead to sophisticated models, with numerous parameters without real physical meaning. However, using a rather simple generalized critical state bonded soil model has proven to be a relevant compromise between an easy calibration and good results. The constitutive model formulation considers a non-associated elasto-plastic formulation within the critical state framework. The calibration procedure, using standard laboratory tests, is complemented by the study of an uniaxial compression test observed by tomography. Using finite elements simulations, this test is simulated considering a non-homogeneous 3D media. The tomography of compression sample gives access to 3D displacement fields by using image correlation techniques. Unfortunately these fields have missing experimental data because of the low resolution of correlations for low displacement magnitudes. We propose a recovery method that reconstructs 3D full displacement fields and 2D boundary displacement fields. These fields are mandatory for the calibration of the constitutive parameters by using 3D finite element simulations. The proposed recovery technique is based on a singular value decomposition of available experimental data. This calibration protocol enables an accurate prediction of the fragmentation of the specimen.

System and method for calibrating a rotary absolute position sensor

NASA Technical Reports Server (NTRS)

Davis, Donald R. (Inventor); Permenter, Frank Noble (Inventor); Radford, Nicolaus A (Inventor)

2012-01-01

A system includes a rotary device, a rotary absolute position (RAP) sensor generating encoded pairs of voltage signals describing positional data of the rotary device, a host machine, and an algorithm. The algorithm calculates calibration parameters usable to determine an absolute position of the rotary device using the encoded pairs, and is adapted for linearly-mapping an ellipse defined by the encoded pairs to thereby calculate the calibration parameters. A method of calibrating the RAP sensor includes measuring the rotary position as encoded pairs of voltage signals, linearly-mapping an ellipse defined by the encoded pairs to thereby calculate the calibration parameters, and calculating an absolute position of the rotary device using the calibration parameters. The calibration parameters include a positive definite matrix (A) and a center point (q) of the ellipse. The voltage signals may include an encoded sine and cosine of a rotary angle of the rotary device.

Objective calibration of numerical weather prediction models

NASA Astrophysics Data System (ADS)

Voudouri, A.; Khain, P.; Carmona, I.; Bellprat, O.; Grazzini, F.; Avgoustoglou, E.; Bettems, J. M.; Kaufmann, P.

2017-07-01

Numerical weather prediction (NWP) and climate models use parameterization schemes for physical processes, which often include free or poorly confined parameters. Model developers normally calibrate the values of these parameters subjectively to improve the agreement of forecasts with available observations, a procedure referred as expert tuning. A practicable objective multi-variate calibration method build on a quadratic meta-model (MM), that has been applied for a regional climate model (RCM) has shown to be at least as good as expert tuning. Based on these results, an approach to implement the methodology to an NWP model is presented in this study. Challenges in transferring the methodology from RCM to NWP are not only restricted to the use of higher resolution and different time scales. The sensitivity of the NWP model quality with respect to the model parameter space has to be clarified, as well as optimize the overall procedure, in terms of required amount of computing resources for the calibration of an NWP model. Three free model parameters affecting mainly turbulence parameterization schemes were originally selected with respect to their influence on the variables associated to daily forecasts such as daily minimum and maximum 2 m temperature as well as 24 h accumulated precipitation. Preliminary results indicate that it is both affordable in terms of computer resources and meaningful in terms of improved forecast quality. In addition, the proposed methodology has the advantage of being a replicable procedure that can be applied when an updated model version is launched and/or customize the same model implementation over different climatological areas.

Design of a Two-Step Calibration Method of Kinematic Parameters for Serial Robots

NASA Astrophysics Data System (ADS)

WANG, Wei; WANG, Lei; YUN, Chao

2017-03-01

Serial robots are used to handle workpieces with large dimensions, and calibrating kinematic parameters is one of the most efficient ways to upgrade their accuracy. Many models are set up to investigate how many kinematic parameters can be identified to meet the minimal principle, but the base frame and the kinematic parameter are indistinctly calibrated in a one-step way. A two-step method of calibrating kinematic parameters is proposed to improve the accuracy of the robot's base frame and kinematic parameters. The forward kinematics described with respect to the measuring coordinate frame are established based on the product-of-exponential (POE) formula. In the first step the robot's base coordinate frame is calibrated by the unit quaternion form. The errors of both the robot's reference configuration and the base coordinate frame's pose are equivalently transformed to the zero-position errors of the robot's joints. The simplified model of the robot's positioning error is established in second-power explicit expressions. Then the identification model is finished by the least square method, requiring measuring position coordinates only. The complete subtasks of calibrating the robot's 39 kinematic parameters are finished in the second step. It's proved by a group of calibration experiments that by the proposed two-step calibration method the average absolute accuracy of industrial robots is updated to 0.23 mm. This paper presents that the robot's base frame should be calibrated before its kinematic parameters in order to upgrade its absolute positioning accuracy.

Assessing endothelial function and providing calibrated UFMD data using a blood pressure cuff

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maltz, Jonathan S.

Methods and apparatus are provided for assessing endothelial function in a mammal. In certain embodiments the methods involve using a cuff to apply pressure to an artery in a subject to determine a plurality of baseline values for a parameter related to endothelial function as a function of applied pressure (P.sub.m); b) applying a stimulus to the subject; and applying external pressure P.sub.m to the artery to determine a plurality of stimulus-effected values for the parameter related to endothelial function as a function of applied pressure (P.sub.m); where the baseline values are determined from measurements made when said mammal ismore » not substantially effected by said stimulus and differences in said baseline values and said stimulus-effected values provide a measure of endothelial function in said mammal.« less

Comparison of soil moisture retrieval algorithms based on the synergy between SMAP and SMOS-IC

NASA Astrophysics Data System (ADS)

Ebrahimi-Khusfi, Mohsen; Alavipanah, Seyed Kazem; Hamzeh, Saeid; Amiraslani, Farshad; Neysani Samany, Najmeh; Wigneron, Jean-Pierre

2018-05-01

This study was carried out to evaluate possible improvements of the soil moisture (SM) retrievals from the SMAP observations, based on the synergy between SMAP and SMOS. We assessed the impacts of the vegetation and soil roughness parameters on SM retrievals from SMAP observations. To do so, the effects of three key input parameters including the vegetation optical depth (VOD), effective scattering albedo (ω) and soil roughness (HR) parameters were assessed with the emphasis on the synergy with the VOD product derived from SMOS-IC, a new and simpler version of the SMOS algorithm, over two years of data (April 2015 to April 2017). First, a comprehensive comparison of seven SM retrieval algorithms was made to find the best one for SM retrievals from the SMAP observations. All results were evaluated against in situ measurements over 548 stations from the International Soil Moisture Network (ISMN) in terms of four statistical metrics: correlation coefficient (R), root mean square error (RMSE), bias and unbiased RMSE (UbRMSE). The comparison of seven SM retrieval algorithms showed that the dual channel algorithm based on the additional use of the SMOS-IC VOD product (selected algorithm) led to the best results of SM retrievals over 378, 399, 330 and 271 stations (out of a total of 548 stations) in terms of R, RMSE, UbRMSE and both R & UbRMSE, respectively. Moreover, comparing the measured and retrieved SM values showed that this synergy approach led to an increase in median R value from 0.6 to 0.65 and a decrease in median UbRMSE from 0.09 m3/m3 to 0.06 m3/m3. Second, using the algorithm selected in a first step and defined above, the ω and HR parameters were calibrated over 218 rather homogenous ISMN stations. 72 combinations of various values of ω and HR were used for the calibration over different land cover classes. In this calibration process, the optimal values of ω and HR were found for the different land cover classes. The obtained results indicated that the impact of the VOD parameter on SM retrievals is more considerable than the effects of HR and ω. Overall, the inclusion of the VOD parameter in the SMAP SM retrieval algorithm was found to be a very interesting approach and showed the large potential benefit of the synergy between SMAP and SMOS.

Initial sediment transport model of the mining-affected Aries River Basin, Romania

USGS Publications Warehouse

Friedel, Michael J.; Linard, Joshua I.

2008-01-01

The Romanian government is interested in understanding the effects of existing and future mining activities on long-term dispersal, storage, and remobilization of sediment-associated metals. An initial Soil and Water Assessment Tool (SWAT) model was prepared using available data to evaluate hypothetical failure of the Valea Sesei tailings dam at the Rosia Poieni mine in the Aries River basin. Using the available data, the initial Aries River Basin SWAT model could not be manually calibrated to accurately reproduce monthly streamflow values observed at the Turda gage station. The poor simulation of the monthly streamflow is attributed to spatially limited soil and precipitation data, limited constraint information due to spatially and temporally limited streamflow measurements, and in ability to obtain optimal parameter values when using a manual calibration process. Suggestions to improve the Aries River basin sediment transport model include accounting for heterogeneity in model input, a two-tier nonlinear calibration strategy, and analysis of uncertainty in predictions.

Inverse modeling with RZWQM2 to predict water quality

USGS Publications Warehouse

Nolan, Bernard T.; Malone, Robert W.; Ma, Liwang; Green, Christopher T.; Fienen, Michael N.; Jaynes, Dan B.

2011-01-01

This chapter presents guidelines for autocalibration of the Root Zone Water Quality Model (RZWQM2) by inverse modeling using PEST parameter estimation software (Doherty, 2010). Two sites with diverse climate and management were considered for simulation of N losses by leaching and in drain flow: an almond [Prunus dulcis (Mill.) D.A. Webb] orchard in the San Joaquin Valley, California and the Walnut Creek watershed in central Iowa, which is predominantly in corn (Zea mays L.)–soybean [Glycine max (L.) Merr.] rotation. Inverse modeling provides an objective statistical basis for calibration that involves simultaneous adjustment of model parameters and yields parameter confidence intervals and sensitivities. We describe operation of PEST in both parameter estimation and predictive analysis modes. The goal of parameter estimation is to identify a unique set of parameters that minimize a weighted least squares objective function, and the goal of predictive analysis is to construct a nonlinear confidence interval for a prediction of interest by finding a set of parameters that maximizes or minimizes the prediction while maintaining the model in a calibrated state. We also describe PEST utilities (PAR2PAR, TSPROC) for maintaining ordered relations among model parameters (e.g., soil root growth factor) and for post-processing of RZWQM2 outputs representing different cropping practices at the Iowa site. Inverse modeling provided reasonable fits to observed water and N fluxes and directly benefitted the modeling through: (i) simultaneous adjustment of multiple parameters versus one-at-a-time adjustment in manual approaches; (ii) clear indication by convergence criteria of when calibration is complete; (iii) straightforward detection of nonunique and insensitive parameters, which can affect the stability of PEST and RZWQM2; and (iv) generation of confidence intervals for uncertainty analysis of parameters and model predictions. Composite scaled sensitivities, which reflect the total information provided by the observations for a parameter, indicated that most of the RZWQM2 parameters at the California study site (CA) and Iowa study site (IA) could be reliably estimated by regression. Correlations obtained in the CA case indicated that all model parameters could be uniquely estimated by inverse modeling. Although water content at field capacity was highly correlated with bulk density (−0.94), the correlation is less than the threshold for nonuniqueness (0.95, absolute value basis). Additionally, we used truncated singular value decomposition (SVD) at CA to mitigate potential problems with highly correlated and insensitive parameters. Singular value decomposition estimates linear combinations (eigenvectors) of the original process-model parameters. Parameter confidence intervals (CIs) at CA indicated that parameters were reliably estimated with the possible exception of an organic pool transfer coefficient (R45), which had a comparatively wide CI. However, the 95% confidence interval for R45 (0.03–0.35) is mostly within the range of values reported for this parameter. Predictive analysis at CA generated confidence intervals that were compared with independently measured annual water flux (groundwater recharge) and median nitrate concentration in a collocated monitoring well as part of model evaluation. Both the observed recharge (42.3 cm yr−1) and nitrate concentration (24.3 mg L−1) were within their respective 90% confidence intervals, indicating that overall model error was within acceptable limits.

On the importance of appropriate precipitation gauge catch correction for hydrological modelling at mid to high latitudes

NASA Astrophysics Data System (ADS)

Stisen, S.; Højberg, A. L.; Troldborg, L.; Refsgaard, J. C.; Christensen, B. S. B.; Olsen, M.; Henriksen, H. J.

2012-11-01

Precipitation gauge catch correction is often given very little attention in hydrological modelling compared to model parameter calibration. This is critical because significant precipitation biases often make the calibration exercise pointless, especially when supposedly physically-based models are in play. This study addresses the general importance of appropriate precipitation catch correction through a detailed modelling exercise. An existing precipitation gauge catch correction method addressing solid and liquid precipitation is applied, both as national mean monthly correction factors based on a historic 30 yr record and as gridded daily correction factors based on local daily observations of wind speed and temperature. The two methods, named the historic mean monthly (HMM) and the time-space variable (TSV) correction, resulted in different winter precipitation rates for the period 1990-2010. The resulting precipitation datasets were evaluated through the comprehensive Danish National Water Resources model (DK-Model), revealing major differences in both model performance and optimised model parameter sets. Simulated stream discharge is improved significantly when introducing the TSV correction, whereas the simulated hydraulic heads and multi-annual water balances performed similarly due to recalibration adjusting model parameters to compensate for input biases. The resulting optimised model parameters are much more physically plausible for the model based on the TSV correction of precipitation. A proxy-basin test where calibrated DK-Model parameters were transferred to another region without site specific calibration showed better performance for parameter values based on the TSV correction. Similarly, the performances of the TSV correction method were superior when considering two single years with a much dryer and a much wetter winter, respectively, as compared to the winters in the calibration period (differential split-sample tests). We conclude that TSV precipitation correction should be carried out for studies requiring a sound dynamic description of hydrological processes, and it is of particular importance when using hydrological models to make predictions for future climates when the snow/rain composition will differ from the past climate. This conclusion is expected to be applicable for mid to high latitudes, especially in coastal climates where winter precipitation types (solid/liquid) fluctuate significantly, causing climatological mean correction factors to be inadequate.

Investigating the Metallicity–Mixing-length Relation

NASA Astrophysics Data System (ADS)

Viani, Lucas S.; Basu, Sarbani; Joel Ong J., M.; Bonaca, Ana; Chaplin, William J.

2018-05-01

Stellar models typically use the mixing-length approximation as a way to implement convection in a simplified manner. While conventionally the value of the mixing-length parameter, α, used is the solar-calibrated value, many studies have shown that other values of α are needed to properly model stars. This uncertainty in the value of the mixing-length parameter is a major source of error in stellar models and isochrones. Using asteroseismic data, we determine the value of the mixing-length parameter required to properly model a set of about 450 stars ranging in log g, {T}eff}, and [{Fe}/{{H}}]. The relationship between the value of α required and the properties of the star is then investigated. For Eddington atmosphere, non-diffusion models, we find that the value of α can be approximated by a linear model, in the form of α /{α }ȯ =5.426{--}0.101 {log}(g)-1.071 {log}({T}eff}) +0.437([{Fe}/{{H}}]). This process is repeated using a variety of model physics, as well as compared with previous studies and results from 3D convective simulations.

Calibration of a flexible measurement system based on industrial articulated robot and structured light sensor

NASA Astrophysics Data System (ADS)

Mu, Nan; Wang, Kun; Xie, Zexiao; Ren, Ping

2017-05-01

To realize online rapid measurement for complex workpieces, a flexible measurement system based on an articulated industrial robot with a structured light sensor mounted on the end-effector is developed. A method for calibrating the system parameters is proposed in which the hand-eye transformation parameters and the robot kinematic parameters are synthesized in the calibration process. An initial hand-eye calibration is first performed using a standard sphere as the calibration target. By applying the modified complete and parametrically continuous method, we establish a synthesized kinematic model that combines the initial hand-eye transformation and distal link parameters as a whole with the sensor coordinate system as the tool frame. According to the synthesized kinematic model, an error model is constructed based on spheres' center-to-center distance errors. Consequently, the error model parameters can be identified in a calibration experiment using a three-standard-sphere target. Furthermore, the redundancy of error model parameters is eliminated to ensure the accuracy and robustness of the parameter identification. Calibration and measurement experiments are carried out based on an ER3A-C60 robot. The experimental results show that the proposed calibration method enjoys high measurement accuracy, and this efficient and flexible system is suitable for online measurement in industrial scenes.

Stochastic calibration and learning in nonstationary hydroeconomic models

NASA Astrophysics Data System (ADS)

Maneta, M. P.; Howitt, R.

2014-05-01

Concern about water scarcity and adverse climate events over agricultural regions has motivated a number of efforts to develop operational integrated hydroeconomic models to guide adaptation and optimal use of water. Once calibrated, these models are used for water management and analysis assuming they remain valid under future conditions. In this paper, we present and demonstrate a methodology that permits the recursive calibration of economic models of agricultural production from noisy but frequently available data. We use a standard economic calibration approach, namely positive mathematical programming, integrated in a data assimilation algorithm based on the ensemble Kalman filter equations to identify the economic model parameters. A moving average kernel ensures that new and past information on agricultural activity are blended during the calibration process, avoiding loss of information and overcalibration for the conditions of a single year. A regularization constraint akin to the standard Tikhonov regularization is included in the filter to ensure its stability even in the presence of parameters with low sensitivity to observations. The results show that the implementation of the PMP methodology within a data assimilation framework based on the enKF equations is an effective method to calibrate models of agricultural production even with noisy information. The recursive nature of the method incorporates new information as an added value to the known previous observations of agricultural activity without the need to store historical information. The robustness of the method opens the door to the use of new remote sensing algorithms for operational water management.

Utilization of Expert Knowledge in a Multi-Objective Hydrologic Model Automatic Calibration Process

NASA Astrophysics Data System (ADS)

Quebbeman, J.; Park, G. H.; Carney, S.; Day, G. N.; Micheletty, P. D.

2016-12-01

Spatially distributed continuous simulation hydrologic models have a large number of parameters for potential adjustment during the calibration process. Traditional manual calibration approaches of such a modeling system is extremely laborious, which has historically motivated the use of automatic calibration procedures. With a large selection of model parameters, achieving high degrees of objective space fitness - measured with typical metrics such as Nash-Sutcliffe, Kling-Gupta, RMSE, etc. - can easily be achieved using a range of evolutionary algorithms. A concern with this approach is the high degree of compensatory calibration, with many similarly performing solutions, and yet grossly varying parameter set solutions. To help alleviate this concern, and mimic manual calibration processes, expert knowledge is proposed for inclusion within the multi-objective functions, which evaluates the parameter decision space. As a result, Pareto solutions are identified with high degrees of fitness, but also create parameter sets that maintain and utilize available expert knowledge resulting in more realistic and consistent solutions. This process was tested using the joint SNOW-17 and Sacramento Soil Moisture Accounting method (SAC-SMA) within the Animas River basin in Colorado. Three different elevation zones, each with a range of parameters, resulted in over 35 model parameters simultaneously calibrated. As a result, high degrees of fitness were achieved, in addition to the development of more realistic and consistent parameter sets such as those typically achieved during manual calibration procedures.

Improvements in Calibration and Analysis of the CTBT-relevant Radioxenon Isotopes with High Resolution SiPIN-based Electron Detectors

NASA Astrophysics Data System (ADS)

Khrustalev, K.

2016-12-01

Current process for the calibration of the beta-gamma detectors used for radioxenon isotope measurements for CTBT purposes is laborious and time consuming. It uses a combination of point sources and gaseous sources resulting in differences between energy and resolution calibrations. The emergence of high resolution SiPIN based electron detectors allows improvements in the calibration and analysis process to be made. Thanks to high electron resolution of SiPIN detectors ( 8-9 keV@129 keV) compared to plastic scintillators ( 35 keV@129keV) there are a lot more CE peaks (from radioxenon and radon progenies) can be resolved and used for energy and resolution calibration in the energy range of the CTBT-relevant radioxenon isotopes. The long term stability of the SiPIN energy calibration allows one to significantly reduce the time of the QC measurements needed for checking the stability of the E/R calibration. The currently used second order polynomials for the E/R calibration fitting are unphysical and shall be replaced by a linear energy calibration for NaI and SiPIN, owing to high linearity and dynamic range of the modern digital DAQ systems, and resolution calibration functions shall be modified to reflect the underlying physical processes. Alternatively, one can completely abandon the use of fitting functions and use only point-values of E/R (similar to the efficiency calibration currently used) at the energies relevant for the isotopes of interest (ROI - Regions Of Interest ). Current analysis considers the detector as a set of single channel analysers, with an established set of coefficients relating the positions of ROIs with the positions of the QC peaks. The analysis of the spectra can be made more robust using peak and background fitting in the ROIs with a single free parameter (peak area) of the potential peaks from the known isotopes and a fixed E/R calibration values set.

Strategy for determination of LOD and LOQ values--some basic aspects.

PubMed

Uhrovčík, Jozef

2014-02-01

The paper is devoted to the evaluation of limit of detection (LOD) and limit of quantification (LOQ) values in concentration domain by using 4 different approaches; namely 3σ and 10σ approaches, ULA2 approach, PBA approach and MDL approach. Brief theoretical analyses of all above mentioned approaches are given together with directions for their practical use. Calculations and correct calibration design are exemplified by using of electrothermal atomic absorption spectrometry for determination of lead in drinking water sample. These validation parameters reached 1.6 μg L(-1) (LOD) and 5.4 μg L(-1) (LOQ) by using 3σ and 10σ approaches. For obtaining relevant values of analyte concentration the influence of calibration design and measurement methodology were examined. The most preferred technique has proven to be a method of preconcentration of the analyte on the surface of the graphite cuvette (boost cycle). © 2013 Elsevier B.V. All rights reserved.

Regionalisation of a distributed method for flood quantiles estimation: Revaluation of local calibration hypothesis to enhance the spatial structure of the optimised parameter

NASA Astrophysics Data System (ADS)

Odry, Jean; Arnaud, Patrick

2016-04-01

The SHYREG method (Aubert et al., 2014) associates a stochastic rainfall generator and a rainfall-runoff model to produce rainfall and flood quantiles on a 1 km2 mesh covering the whole French territory. The rainfall generator is based on the description of rainy events by descriptive variables following probability distributions and is characterised by a high stability. This stochastic generator is fully regionalised, and the rainfall-runoff transformation is calibrated with a single parameter. Thanks to the stability of the approach, calibration can be performed against only flood quantiles associated with observated frequencies which can be extracted from relatively short time series. The aggregation of SHYREG flood quantiles to the catchment scale is performed using an areal reduction factor technique unique on the whole territory. Past studies demonstrated the accuracy of SHYREG flood quantiles estimation for catchments where flow data are available (Arnaud et al., 2015). Nevertheless, the parameter of the rainfall-runoff model is independently calibrated for each target catchment. As a consequence, this parameter plays a corrective role and compensates approximations and modelling errors which makes difficult to identify its proper spatial pattern. It is an inherent objective of the SHYREG approach to be completely regionalised in order to provide a complete and accurate flood quantiles database throughout France. Consequently, it appears necessary to identify the model configuration in which the calibrated parameter could be regionalised with acceptable performances. The revaluation of some of the method hypothesis is a necessary step before the regionalisation. Especially the inclusion or the modification of the spatial variability of imposed parameters (like production and transfer reservoir size, base flow addition and quantiles aggregation function) should lead to more realistic values of the only calibrated parameter. The objective of the work presented here is to develop a SHYREG evaluation scheme focusing on both local and regional performances. Indeed, it is necessary to maintain the accuracy of at site flood quantiles estimation while identifying a configuration leading to a satisfactory spatial pattern of the calibrated parameter. This ability to be regionalised can be appraised by the association of common regionalisation techniques and split sample validation tests on a set of around 1,500 catchments representing the whole diversity of France physiography. Also, the presence of many nested catchments and a size-based split sample validation make possible to assess the relevance of the calibrated parameter spatial structure inside the largest catchments. The application of this multi-objective evaluation leads to the selection of a version of SHYREG more suitable for regionalisation. References: Arnaud, P., Cantet, P., Aubert, Y., 2015. Relevance of an at-site flood frequency analysis method for extreme events based on stochastic simulation of hourly rainfall. Hydrological Sciences Journal: on press. DOI:10.1080/02626667.2014.965174 Aubert, Y., Arnaud, P., Ribstein, P., Fine, J.A., 2014. The SHYREG flow method-application to 1605 basins in metropolitan France. Hydrological Sciences Journal, 59(5): 993-1005. DOI:10.1080/02626667.2014.902061

Temperature, gravity, and bolometric correction scales for non-supergiant OB stars

NASA Astrophysics Data System (ADS)

Nieva, M.-F.

2013-02-01

Context. Precise and accurate determinations of the atmospheric parameters effective temperature and surface gravity are mandatory to derive reliable chemical abundances in OB stars. Furthermore, fundamental parameters like distances, masses, radii, luminosities can also be derived from the temperature and gravity of the stars. Aims: Atmospheric parameters recently determined at high precision with several independent spectroscopic indicators in non-local thermodynamic equilibrium, with typical uncertainties of ~300 K for temperature and of ~0.05 dex for gravity, are employed to calibrate photometric relationships. This is in order to investigate whether a faster tool to estimate atmospheric parameters can be provided. Methods: Temperatures and gravities of 30 calibrators, i.e. well-studied OB main sequence to giant stars in the solar neighbourhood, are compared to reddening-independent quantities of the Johnson and Strömgren photometric systems, assuming normal reddening. In addition, we examine the spectral and luminosity classification of the star sample and compute bolometric corrections. Results: Calibrations of temperatures and gravities are proposed for various photometric indices and spectral types. Once the luminosity of the stars is well known, effective temperatures can be determined at a precision of ~400 K for luminosity classes III/IV and ~800 K for luminosity class V. Furthermore, surface gravities can reach internal uncertainties as low as ~0.08 dex when using our calibration to the Johnson Q-parameter. Similar precision is achieved for gravities derived from the β-index and the precision is lower for both atmospheric parameters when using the Strömgren indices [c1] and [u - b] . In contrast, external uncertainties are larger for the Johnson than for the Strömgren calibrations. Our uncertainties are smaller than typical differences among other methods in the literature, reaching values up to ± 2000 K for temperature and ± 0.25 dex for gravity, and in extreme cases, + 6000 K and ± 0.4 dex, respectively. A parameter calibration for sub-spectral types is also proposed. Moreover, we present a new bolometric correction relation to temperature based on our empirical data, rather than on synthetic grids. Conclusions: The photometric calibrations presented here are useful tools to estimate effective temperatures and surface gravities of non-supergiant OB stars in a fast manner. This is also applicable to some single-line spectroscopic binaries, but caution has to be taken for undetected double-lined spectroscopic binaries and single objects with anomalous reddening-law, dubious photometric quantities and/or luminosity classes, for which the systematic uncertainties may increase significantly. We recommend to use these calibrations only as a first step of the parameter estimation, with subsequent refinements based on spectroscopy. A larger sample covering more uniformly the parameter space under consideration will allow refinements to the present calibrations. Based on observations collected at the Centro Astronómico Hispano Alemán (CAHA) at Calar Alto, operated jointly by the Max- Planck Institut für Astronomie and the Instituto de Astrofísica de Andalucía (CSIC), proposals H2001-2.2-011 and H2005-2.2-016.Based on observations collected at the European Southern Observatory, Chile, ESO 074.B-0455(A) and from the ESO Archive.Based on spectral data retrieved from the ELODIE archive at Observatoire de Haute-Provence (OHP).Appendices A and B are available in electronic form at http://www.aanda.org

Effects of temporal and spatial resolution of calibration data on integrated hydrologic water quality model identification

NASA Astrophysics Data System (ADS)

Jiang, Sanyuan; Jomaa, Seifeddine; Büttner, Olaf; Rode, Michael

2014-05-01

Hydrological water quality modeling is increasingly used for investigating runoff and nutrient transport processes as well as watershed management but it is mostly unclear how data availablity determins model identification. In this study, the HYPE (HYdrological Predictions for the Environment) model, which is a process-based, semi-distributed hydrological water quality model, was applied in two different mesoscale catchments (Selke (463 km2) and Weida (99 km2)) located in central Germany to simulate discharge and inorganic nitrogen (IN) transport. PEST and DREAM(ZS) were combined with the HYPE model to conduct parameter calibration and uncertainty analysis. Split-sample test was used for model calibration (1994-1999) and validation (1999-2004). IN concentration and daily IN load were found to be highly correlated with discharge, indicating that IN leaching is mainly controlled by runoff. Both dynamics and balances of water and IN load were well captured with NSE greater than 0.83 during validation period. Multi-objective calibration (calibrating hydrological and water quality parameters simultaneously) was found to outperform step-wise calibration in terms of model robustness. Multi-site calibration was able to improve model performance at internal sites, decrease parameter posterior uncertainty and prediction uncertainty. Nitrogen-process parameters calibrated using continuous daily averages of nitrate-N concentration observations produced better and more robust simulations of IN concentration and load, lower posterior parameter uncertainty and IN concentration prediction uncertainty compared to the calibration against uncontinuous biweekly nitrate-N concentration measurements. Both PEST and DREAM(ZS) are efficient in parameter calibration. However, DREAM(ZS) is more sound in terms of parameter identification and uncertainty analysis than PEST because of its capability to evolve parameter posterior distributions and estimate prediction uncertainty based on global search and Bayesian inference schemes.

Identification and synthetic modeling of factors affecting American black duck populations

USGS Publications Warehouse

Conroy, Michael J.; Miller, Mark W.; Hines, James E.

2002-01-01

We reviewed the literature on factors potentially affecting the population status of American black ducks (Anas rupribes). Our review suggests that there is some support for the influence of 4 major, continental-scope factors in limiting or regulating black duck populations: 1) loss in the quantity or quality of breeding habitats; 2) loss in the quantity or quality of wintering habitats; 3) harvest, and 4) interactions (competition, hybridization) with mallards (Anas platyrhychos) during the breeding and/or wintering periods. These factors were used as the basis of an annual life cycle model in which reproduction rates and survival rates were modeled as functions of the above factors, with parameters of the model describing the strength of these relationships. Variation in the model parameter values allows for consideration of scientific uncertainty as to the degree each of these factors may be contributing to declines in black duck populations, and thus allows for the investigation of the possible effects of management (e.g., habitat improvement, harvest reductions) under different assumptions. We then used available, historical data on black duck populations (abundance, annual reproduction rates, and survival rates) and possible driving factors (trends in breeding and wintering habitats, harvest rates, and abundance of mallards) to estimate model parameters. Our estimated reproduction submodel included parameters describing negative density feedback of black ducks, positive influence of breeding habitat, and negative influence of mallard densities; our survival submodel included terms for positive influence of winter habitat on reproduction rates, and negative influences of black duck density (i.e., compensation to harvest mortality). Individual models within each group (reproduction, survival) involved various combinations of these factors, and each was given an information theoretic weight for use in subsequent prediction. The reproduction model with highest AIC weight (0.70) predicted black duck age ratios increasing as a function of decreasing mallard abundance and increasing acreage of breeding habitat; all models considered involved negative density dependence for black ducks. The survival model with highest AIC weight (0.51) predicted nonharvest survival increasing as a function of increasing acreage of wintering habitat and decreasing harvest rates (additive mortality); models involving compensatory mortality effects received ≈0.12 total weight, vs. 0.88 for additive models. We used the combined model, together with our historical data set, to perform a series of 1-year population forecasts, similar to those that might be performed under adaptive management. Initial model forecasts over-predicted observed breeding populations by ≈25%. Least-squares calibration reduced the bias to ≈0.5% under prediction. After calibration, model-averaged predictions over the 16 alternative models (4 reproduction × 4 survival, weighted by AIC model weights) explained 67% of the variation in annual breeding population abundance for black ducks, suggesting that it might have utility as a predictive tool in adaptive management. We investigated the effects of statistical uncertainty in parameter values on predicted population growth rates for the combined annual model, via sensitivity analyses. Parameter sensitivity varied in relation to the parameter values over the estimated confidence intervals, and in relation to harvest rates and mallard abundance. Forecasts of black duck abundance were extremely sensitive to variation in parameter values for the coefficients for breeding and wintering habitat effects. Model-averaged forecasts of black duck abundance were also sensitive to changes in harvest rate and mallard abundance, with rapid declines in black duck abundance predicted for a range of harvest rates and mallard abundance higher than current levels of either factor, but easily envisaged, particularly given current rates of growth for mallard populations. Because of concerns about sensitivity to habitat coefficients, and particularly in light of deficiencies in the historical data used to estimate these parameters, we developed a simplified model that excludes habitat effects. We also developed alternative models involving a calibration adjustment for reproduction rates, survival rates, or neither. Calibration of survival rates performed best (AIC weight 0.59, % BIAS = -0.280, R2=0.679), with reproduction calibration somewhat inferior (AIC weight 0.41, % BIAS = -0.267, R2=0.672); models without calibration received virtually no AIC weight and were discarded. We recommend that the simplified model set (4 biological models × 2 alternative calibration factors) be retained as the best working set of alternative models for research and management. Finally, we provide some preliminary guidance for the development of adaptive harvest management for black ducks, using our working set of models.

Precise dielectric property measurements and E-field probe calibration for specific absorption rate measurements using a rectangular waveguide

PubMed Central

Hakim, B M; Beard, B B; Davis, C C

2018-01-01

Specific absorption rate (SAR) measurements require accurate calculations of the dielectric properties of tissue-equivalent liquids and associated calibration of E-field probes. We developed a precise tissue-equivalent dielectric measurement and E-field probe calibration system. The system consists of a rectangular waveguide, electric field probe, and data control and acquisition system. Dielectric properties are calculated using the field attenuation factor inside the tissue-equivalent liquid and power reflectance inside the waveguide at the air/dielectric-slab interface. Calibration factors were calculated using isotropicity measurements of the E-field probe. The frequencies used are 900 MHz and 1800 MHz. The uncertainties of the measured values are within ±3%, at the 95% confidence level. Using the same waveguide for dielectric measurements as well as calibrating E-field probes used in SAR assessments eliminates a source of uncertainty. Moreover, we clearly identified the system parameters that affect the overall uncertainty of the measurement system. PMID:29520129

Automated calibration of laser spectrometer measurements of δ18 O and δ2 H values in water vapour using a Dew Point Generator.

PubMed

Munksgaard, Niels C; Cheesman, Alexander W; Gray-Spence, Andrew; Cernusak, Lucas A; Bird, Michael I

2018-06-30

Continuous measurement of stable O and H isotope compositions in water vapour requires automated calibration for remote field deployments. We developed a new low-cost device for calibration of both water vapour mole fraction and isotope composition. We coupled a commercially available dew point generator (DPG) to a laser spectrometer and developed hardware for water and air handling along with software for automated operation and data processing. We characterised isotopic fractionation in the DPG, conducted a field test and assessed the influence of critical parameters on the performance of the device. An analysis time of 1 hour was sufficient to achieve memory-free analysis of two water vapour standards and the δ 18 O and δ 2 H values were found to be independent of water vapour concentration over a range of ≈20,000-33,000 ppm. The reproducibility of the standard vapours over a 10-day period was better than 0.14 ‰ and 0.75 ‰ for δ 18 O and δ 2 H values, respectively (1 σ, n = 11) prior to drift correction and calibration. The analytical accuracy was confirmed by the analysis of a third independent vapour standard. The DPG distillation process requires that isotope calibration takes account of DPG temperature, analysis time, injected water volume and air flow rate. The automated calibration system provides high accuracy and precision and is a robust, cost-effective option for long-term field measurements of water vapour isotopes. The necessary modifications to the DPG are minor and easily reversible. Copyright © 2018 John Wiley & Sons, Ltd.

Mixture EMOS model for calibrating ensemble forecasts of wind speed.

PubMed

Baran, S; Lerch, S

2016-03-01

Ensemble model output statistics (EMOS) is a statistical tool for post-processing forecast ensembles of weather variables obtained from multiple runs of numerical weather prediction models in order to produce calibrated predictive probability density functions. The EMOS predictive probability density function is given by a parametric distribution with parameters depending on the ensemble forecasts. We propose an EMOS model for calibrating wind speed forecasts based on weighted mixtures of truncated normal (TN) and log-normal (LN) distributions where model parameters and component weights are estimated by optimizing the values of proper scoring rules over a rolling training period. The new model is tested on wind speed forecasts of the 50 member European Centre for Medium-range Weather Forecasts ensemble, the 11 member Aire Limitée Adaptation dynamique Développement International-Hungary Ensemble Prediction System ensemble of the Hungarian Meteorological Service, and the eight-member University of Washington mesoscale ensemble, and its predictive performance is compared with that of various benchmark EMOS models based on single parametric families and combinations thereof. The results indicate improved calibration of probabilistic and accuracy of point forecasts in comparison with the raw ensemble and climatological forecasts. The mixture EMOS model significantly outperforms the TN and LN EMOS methods; moreover, it provides better calibrated forecasts than the TN-LN combination model and offers an increased flexibility while avoiding covariate selection problems. © 2016 The Authors Environmetrics Published by JohnWiley & Sons Ltd.

An analysis of the currently available calibrations in Strömgren photometry by using open clusters

NASA Astrophysics Data System (ADS)

Jordi, C.; Masana, E.; Figueras, F.; Torra, J.

1997-05-01

In recent years, several authors have revised the calibrations used to compute physical parameters (Mv, Teff, log g, [Fe/H]) from intrinsic colours in the uvby H_beta photometric system. For reddened stars, these intrinsic colours can be computed through the standard relations among colour indices for each of the regions defined by \\cite[Stromgren (1966)]{str66} on the HR diagram. We present a discussion of the coherence of these calibrations for main-sequence stars. Stars from open clusters are used to carry out this analysis. Assuming that individual reddening values and distances should be similar for all the members of a given open cluster, systematic differences among the calibrations used in each of the photometric regions might arise when comparing mean reddening values and distances for the members of each region. To classify the stars into Stromgren's regions we extended the algorithm presented by \\cite[Figueras et al. (1991)]{fig91} to a wider range of spectral types and luminosity classes. The observational ZAMS are compared with the theoretical ZAMS from stellar evolutionary models, in the range 6500-30000 K. The discrepancies are also discussed.

Stepwise calibration procedure for regional coupled hydrological-hydrogeological models

NASA Astrophysics Data System (ADS)

Labarthe, Baptiste; Abasq, Lena; de Fouquet, Chantal; Flipo, Nicolas

2014-05-01

Stream-aquifer interaction is a complex process depending on regional and local processes. Indeed, the groundwater component of hydrosystem and large scale heterogeneities control the regional flows towards the alluvial plains and the rivers. In second instance, the local distribution of the stream bed permeabilities controls the dynamics of stream-aquifer water fluxes within the alluvial plain, and therefore the near-river piezometric head distribution. In order to better understand the water circulation and pollutant transport in watersheds, the integration of these multi-dimensional processes in modelling platform has to be performed. Thus, the nested interfaces concept in continental hydrosystem modelling (where regional fluxes, simulated by large scale models, are imposed at local stream-aquifer interfaces) has been presented in Flipo et al (2014). This concept has been implemented in EauDyssée modelling platform for a large alluvial plain model (900km2) part of a 11000km2 multi-layer aquifer system, located in the Seine basin (France). The hydrosystem modelling platform is composed of four spatially distributed modules (Surface, Sub-surface, River and Groundwater), corresponding to four components of the terrestrial water cycle. Considering the large number of parameters to be inferred simultaneously, the calibration process of coupled models is highly computationally demanding and therefore hardly applicable to a real case study of 10000km2. In order to improve the efficiency of the calibration process, a stepwise calibration procedure is proposed. The stepwise methodology involves determining optimal parameters of all components of the coupled model, to provide a near optimum prior information for the global calibration. It starts with the surface component parameters calibration. The surface parameters are optimised based on the comparison between simulated and observed discharges (or filtered discharges) at various locations. Once the surface parameters have been determined, the groundwater component is calibrated. The calibration procedure is performed under steady state hypothesis (to minimize the procedure time length) using recharge rates given by the surface component calibration and imposed fluxes boundary conditions given by the regional model. The calibration is performed using pilot point where the prior variogram is calculated from observed transmissivities values. This procedure uses PEST (http//:www.pesthomepage.org/Home.php) as the inverse modelling tool and EauDyssée as the direct model. During the stepwise calibration process, each modules, even if they are actually dependant from each other, are run and calibrated independently, therefore contributions between each module have to be determined. For the surface module, groundwater and runoff contributions have been determined by hydrograph separation. Among the automated base-flow separation methods, the one-parameter Chapman filter (Chapman et al 1999) has been chosen. This filter is a decomposition of the actual base-flow between the previous base-flow and the discharge gradient weighted by functions of the recession coefficient. For the groundwater module, the recharge has been determined from surface and sub-surface module. References : Flipo, N., A. Mourhi, B. Labarthe, and S. Biancamaria (2014). Continental hydrosystem modelling : the concept of nested stream-aquifer interfaces. Hydrol. Earth Syst. Sci. Discuss. 11, 451-500. Chapman,TG. (1999). A comparison of algorithms for stream flow recession and base-flow separation. hydrological Processes 13, 701-714.

Method for lateral force calibration in atomic force microscope using MEMS microforce sensor.

PubMed

Dziekoński, Cezary; Dera, Wojciech; Jarząbek, Dariusz M

2017-11-01

In this paper we present a simple and direct method for the lateral force calibration constant determination. Our procedure does not require any knowledge about material or geometrical parameters of an investigated cantilever. We apply a commercially available microforce sensor with advanced electronics for direct measurement of the friction force applied by the cantilever's tip to a flat surface of the microforce sensor measuring beam. Due to the third law of dynamics, the friction force of the equal value tilts the AFM cantilever. Therefore, torsional (lateral force) signal is compared with the signal from the microforce sensor and the lateral force calibration constant is determined. The method is easy to perform and could be widely used for the lateral force calibration constant determination in many types of atomic force microscopes. Copyright © 2017 Elsevier B.V. All rights reserved.

Mesh refinement and numerical sensitivity analysis for parameter calibration of partial differential equations

NASA Astrophysics Data System (ADS)

Becker, Roland; Vexler, Boris

2005-06-01

We consider the calibration of parameters in physical models described by partial differential equations. This task is formulated as a constrained optimization problem with a cost functional of least squares type using information obtained from measurements. An important issue in the numerical solution of this type of problem is the control of the errors introduced, first, by discretization of the equations describing the physical model, and second, by measurement errors or other perturbations. Our strategy is as follows: we suppose that the user defines an interest functional I, which might depend on both the state variable and the parameters and which represents the goal of the computation. First, we propose an a posteriori error estimator which measures the error with respect to this functional. This error estimator is used in an adaptive algorithm to construct economic meshes by local mesh refinement. The proposed estimator requires the solution of an auxiliary linear equation. Second, we address the question of sensitivity. Applying similar techniques as before, we derive quantities which describe the influence of small changes in the measurements on the value of the interest functional. These numbers, which we call relative condition numbers, give additional information on the problem under consideration. They can be computed by means of the solution of the auxiliary problem determined before. Finally, we demonstrate our approach at hand of a parameter calibration problem for a model flow problem.

An Improved Interferometric Calibration Method Based on Independent Parameter Decomposition

NASA Astrophysics Data System (ADS)

Fan, J.; Zuo, X.; Li, T.; Chen, Q.; Geng, X.

2018-04-01

Interferometric SAR is sensitive to earth surface undulation. The accuracy of interferometric parameters plays a significant role in precise digital elevation model (DEM). The interferometric calibration is to obtain high-precision global DEM by calculating the interferometric parameters using ground control points (GCPs). However, interferometric parameters are always calculated jointly, making them difficult to decompose precisely. In this paper, we propose an interferometric calibration method based on independent parameter decomposition (IPD). Firstly, the parameters related to the interferometric SAR measurement are determined based on the three-dimensional reconstruction model. Secondly, the sensitivity of interferometric parameters is quantitatively analyzed after the geometric parameters are completely decomposed. Finally, each interferometric parameter is calculated based on IPD and interferometric calibration model is established. We take Weinan of Shanxi province as an example and choose 4 TerraDEM-X image pairs to carry out interferometric calibration experiment. The results show that the elevation accuracy of all SAR images is better than 2.54 m after interferometric calibration. Furthermore, the proposed method can obtain the accuracy of DEM products better than 2.43 m in the flat area and 6.97 m in the mountainous area, which can prove the correctness and effectiveness of the proposed IPD based interferometric calibration method. The results provide a technical basis for topographic mapping of 1 : 50000 and even larger scale in the flat area and mountainous area.

Model independent approach to the single photoelectron calibration of photomultiplier tubes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Saldanha, R.; Grandi, L.; Guardincerri, Y.

2017-08-01

The accurate calibration of photomultiplier tubes is critical in a wide variety of applications in which it is necessary to know the absolute number of detected photons or precisely determine the resolution of the signal. Conventional calibration methods rely on fitting the photomultiplier response to a low intensity light source with analytical approximations to the single photoelectron distribution, often leading to biased estimates due to the inability to accurately model the full distribution, especially at low charge values. In this paper we present a simple statistical method to extract the relevant single photoelectron calibration parameters without making any assumptions aboutmore » the underlying single photoelectron distribution. We illustrate the use of this method through the calibration of a Hamamatsu R11410 photomultiplier tube and study the accuracy and precision of the method using Monte Carlo simulations. The method is found to have significantly reduced bias compared to conventional methods and works under a wide range of light intensities, making it suitable for simultaneously calibrating large arrays of photomultiplier tubes.« less

Thermal regimes of Malaysian sedimentary basins

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abdul Halim, M.F.

1994-07-01

Properly corrected and calibrated thermal data are important in estimating source-rock maturation, diagenetics, evolution of reservoirs, pressure regimes, and hydrodynamics. Geothermal gradient, thermal conductivity, and heat flow have been determined for the sedimentary succession penetrated by exploratory wells in Malaysia. Geothermal gradient and heat-flow maps show that the highest average values are in the Malay Basin. The values in the Sarawak basin are intermediate between those of the Malay basin and the Sabah Basin, which contains the lowest average values. Temperature data were analyzed from more than 400 wells. An important parameter that was studied in detail is the circulationmore » time. The correct circulation time is essential in determining the correct geothermal gradient of a well. It was found that the most suitable circulation time for the Sabah Basin is 20 hr, 30 hr for the Sarawak Basin and 40 hr for the Malay Basin. Values of thermal conductivity, determined from measurement and calibrated calculations, were grouped according to depositional units and cycles in each basin.« less

An investigation of hydraulic conductivity estimation in a ground-water flow study of Northern Long Valley, New Jersey

USGS Publications Warehouse

Hill, Mary C.

1985-01-01

The purpose of this study was to develop a methodology to be used to investigate the aquifer characteristics and water supply potential of an aquifer system. In particular, the geohydrology of northern Long Valley, New Jersey, was investigated. Geohydrologic data were collected and analyzed to characterize the site. Analysis was accomplished by interpreting the available data and by using a numerical simulation of the watertable aquifer. Special attention was given to the estimation of hydraulic conductivity values and hydraulic conductivity structure which together define the hydraulic conductivity of the modeled aquifer. Hydraulic conductivity and all other aspects of the system were first estimated using the trial-and-error method of calibration. The estimation of hydraulic conductivity was improved using a least squares method to estimate hydraulic conductivity values and by improvements in the parameter structure. These efforts improved the calibration of the model far more than a preceding period of similar effort using the trial-and-error method of calibration. In addition, the proposed method provides statistical information on the reliability of estimated hydraulic conductivity values, calculated heads, and calculated flows. The methodology developed and applied in this work proved to be of substantial value in the evaluation of the aquifer considered.

METHODOLOGIES FOR CALIBRATION AND PREDICTIVE ANALYSIS OF A WATERSHED MODEL

EPA Science Inventory

The use of a fitted-parameter watershed model to address water quantity and quality management issues requires that it be calibrated under a wide range of hydrologic conditions. However, rarely does model calibration result in a unique parameter set. Parameter nonuniqueness can l...

Simulating muscular thin films using thermal contraction capabilities in finite element analysis tools.

PubMed

Webster, Victoria A; Nieto, Santiago G; Grosberg, Anna; Akkus, Ozan; Chiel, Hillel J; Quinn, Roger D

2016-10-01

In this study, new techniques for approximating the contractile properties of cells in biohybrid devices using Finite Element Analysis (FEA) have been investigated. Many current techniques for modeling biohybrid devices use individual cell forces to simulate the cellular contraction. However, such techniques result in long simulation runtimes. In this study we investigated the effect of the use of thermal contraction on simulation runtime. The thermal contraction model was significantly faster than models using individual cell forces, making it beneficial for rapidly designing or optimizing devices. Three techniques, Stoney׳s Approximation, a Modified Stoney׳s Approximation, and a Thermostat Model, were explored for calibrating thermal expansion/contraction parameters (TECPs) needed to simulate cellular contraction using thermal contraction. The TECP values were calibrated by using published data on the deflections of muscular thin films (MTFs). Using these techniques, TECP values that suitably approximate experimental deflections can be determined by using experimental data obtained from cardiomyocyte MTFs. Furthermore, a sensitivity analysis was performed in order to investigate the contribution of individual variables, such as elastic modulus and layer thickness, to the final calibrated TECP for each calibration technique. Additionally, the TECP values are applicable to other types of biohybrid devices. Two non-MTF models were simulated based on devices reported in the existing literature. Copyright © 2016 Elsevier Ltd. All rights reserved.

Non-destructive and fast identification of cotton-polyester blend fabrics by the portable near-infrared spectrometer.

PubMed

Li, Wen-xia; Li, Feng; Zhao, Guo-liang; Tang, Shi-jun; Liu, Xiao-ying

2014-12-01

A series of 376 cotton-polyester (PET) blend fabrics were studied by a portable near-infrared (NIR) spectrometer. A NIR semi-quantitative-qualitative calibration model was established by Partial Least Squares (PLS) method combined with qualitative identification coefficient. In this process, PLS method in a quantitative analysis was used as a correction method, and the qualitative identification coefficient was set by the content of cotton and polyester in blend fabrics. Cotton-polyester blend fabrics were identified qualitatively by the model and their relative contents were obtained quantitatively, the model can be used for semi-quantitative identification analysis. In the course of establishing the model, the noise and baseline drift of the spectra were eliminated by Savitzky-Golay(S-G) derivative. The influence of waveband selection and different pre-processing method was also studied in the qualitative calibration model. The major absorption bands of 100% cotton samples were in the 1400~1600 nm region, and the one for 100% polyester were around 1600~1800 nm, the absorption intensity was enhancing with the content increasing of cotton or polyester. Therefore, the cotton-polyester's major absorption region was selected as the base waveband, the optimal waveband (1100~2500 nm) was found by expanding the waveband in two directions (the correlation coefficient was 0.6, and wave-point number was 934). The validation samples were predicted by the calibration model, the results showed that the model evaluation parameters was optimum in the 1100~2500 nm region, and the combination of S-G derivative, multiplicative scatter correction (MSC) and mean centering was used as the pre-processing method. RC (relational coefficient of calibration) value was 0.978, RP (relational coefficient of prediction) value was 0.940, SEC (standard error of calibration) value was 1.264, SEP (standard error of prediction) value was 1.590, and the sample's recognition accuracy was up to 93.4%. It showed that the cotton-polyester blend fabrics could be predicted by the semi-quantitative-qualitative calibration model.

Estimation of Pulse Transit Time as a Function of Blood Pressure Using a Nonlinear Arterial Tube-Load Model.

PubMed

Gao, Mingwu; Cheng, Hao-Min; Sung, Shih-Hsien; Chen, Chen-Huan; Olivier, Nicholas Bari; Mukkamala, Ramakrishna

2017-07-01

pulse transit time (PTT) varies with blood pressure (BP) throughout the cardiac cycle, yet, because of wave reflection, only one PTT value at the diastolic BP level is conventionally estimated from proximal and distal BP waveforms. The objective was to establish a technique to estimate multiple PTT values at different BP levels in the cardiac cycle. a technique was developed for estimating PTT as a function of BP (to indicate the PTT value for every BP level) from proximal and distal BP waveforms. First, a mathematical transformation from one waveform to the other is defined in terms of the parameters of a nonlinear arterial tube-load model accounting for BP-dependent arterial compliance and wave reflection. Then, the parameters are estimated by optimally fitting the waveforms to each other via the model-based transformation. Finally, PTT as a function of BP is specified by the parameters. The technique was assessed in animals and patients in several ways including the ability of its estimated PTT-BP function to serve as a subject-specific curve for calibrating PTT to BP. the calibration curve derived by the technique during a baseline period yielded bias and precision errors in mean BP of 5.1 ± 0.9 and 6.6 ± 1.0 mmHg, respectively, during hemodynamic interventions that varied mean BP widely. the new technique may permit, for the first time, estimation of PTT values throughout the cardiac cycle from proximal and distal waveforms. the technique could potentially be applied to improve arterial stiffness monitoring and help realize cuff-less BP monitoring.

Imposing constraints on parameter values of a conceptual hydrological model using baseflow response

NASA Astrophysics Data System (ADS)

Dunn, S. M.

Calibration of conceptual hydrological models is frequently limited by a lack of data about the area that is being studied. The result is that a broad range of parameter values can be identified that will give an equally good calibration to the available observations, usually of stream flow. The use of total stream flow can bias analyses towards interpretation of rapid runoff, whereas water quality issues are more frequently associated with low flow condition. This paper demonstrates how model distinctions between surface an sub-surface runoff can be used to define a likelihood measure based on the sub-surface (or baseflow) response. This helps to provide more information about the model behaviour, constrain the acceptable parameter sets and reduce uncertainty in streamflow prediction. A conceptual model, DIY, is applied to two contrasting catchments in Scotland, the Ythan and the Carron Valley. Parameter ranges and envelopes of prediction are identified using criteria based on total flow efficiency, baseflow efficiency and combined efficiencies. The individual parameter ranges derived using the combined efficiency measures still cover relatively wide bands, but are better constrained for the Carron than the Ythan. This reflects the fact that hydrological behaviour in the Carron is dominated by a much flashier surface response than in the Ythan. Hence, the total flow efficiency is more strongly controlled by surface runoff in the Carron and there is a greater contrast with the baseflow efficiency. Comparisons of the predictions using different efficiency measures for the Ythan also suggest that there is a danger of confusing parameter uncertainties with data and model error, if inadequate likelihood measures are defined.

Basin-scale geothermal model calibration: experience from the Perth Basin, Australia

NASA Astrophysics Data System (ADS)

Wellmann, Florian; Reid, Lynn

2014-05-01

The calibration of large-scale geothermal models for entire sedimentary basins is challenging as direct measurements of rock properties and subsurface temperatures are commonly scarce and the basal boundary conditions poorly constrained. Instead of the often applied "trial-and-error" manual model calibration, we examine here if we can gain additional insight into parameter sensitivities and model uncertainty with a model analysis and calibration study. Our geothermal model is based on a high-resolution full 3-D geological model, covering an area of more than 100,000 square kilometers and extending to a depth of 55 kilometers. The model contains all major faults (>80 ) and geological units (13) for the entire basin. This geological model is discretised into a rectilinear mesh with a lateral resolution of 500 x 500 m, and a variable resolution at depth. The highest resolution of 25 m is applied to a depth range of 1000-3000 m where most temperature measurements are available. The entire discretised model consists of approximately 50 million cells. The top thermal boundary condition is derived from surface temperature measurements on land and ocean floor. The base of the model extents below the Moho, and we apply the heat flux over the Moho as a basal heat flux boundary condition. Rock properties (thermal conductivity, porosity, and heat production) have been compiled from several existing data sets. The conductive geothermal forward simulation is performed with SHEMAT, and we then use the stand-alone capabilities of iTOUGH2 for sensitivity analysis and model calibration. Simulated temperatures are compared to 130 quality weighted bottom hole temperature measurements. The sensitivity analysis provided a clear insight into the most sensitive parameters and parameter correlations. This proved to be of value as strong correlations, for example between basal heat flux and heat production in deep geological units, can significantly influence the model calibration procedure. The calibration resulted in a better determination of subsurface temperatures, and, in addition, provided an insight into model quality. Furthermore, a detailed analysis of the measurements used for calibration highlighted potential outliers, and limitations with the model assumptions. Extending the previously existing large-scale geothermal simulation with iTOUGH2 provided us with a valuable insight into the sensitive parameters and data in the model, which would clearly not be possible with a simple trial-and-error calibration method. Using the gained knowledge, future work will include more detailed studies on the influence of advection and convection.

New Method for Accurate Calibration of Micro-Channel Plate based Detection Systems and its use in the Fast Plasma Investigation of NASA's Magnetospheric MultiScale Mission

NASA Astrophysics Data System (ADS)

Gliese, U.; Avanov, L. A.; Barrie, A.; Kujawski, J. T.; Mariano, A. J.; Tucker, C. J.; Chornay, D. J.; Cao, N. T.; Zeuch, M.; Pollock, C. J.; Jacques, A. D.

2013-12-01

The Fast Plasma Investigation (FPI) of the NASA Magnetospheric MultiScale (MMS) mission employs 16 Dual Electron Spectrometers (DESs) and 16 Dual Ion Spectrometers (DISs) with 4 of each type on each of 4 spacecraft to enable fast (30ms for electrons; 150ms for ions) and spatially differentiated measurements of full the 3D particle velocity distributions. This approach presents a new and challenging aspect to the calibration and operation of these instruments on ground and in flight. The response uniformity and reliability of their calibration and the approach to handling any temporal evolution of these calibrated characteristics all assume enhanced importance in this application, where we attempt to understand the meaning of particle distributions within the ion and electron diffusion regions. Traditionally, the micro-channel plate (MCP) based detection systems for electrostatic particle spectrometers have been calibrated by setting a fixed detection threshold and, subsequently, measuring a detection system count rate plateau curve to determine the MCP voltage that ensures the count rate has reached a constant value independent of further variation in the MCP voltage. This is achieved when most of the MCP pulse height distribution (PHD) is located at higher values (larger pulses) than the detection amplifier threshold. This method is adequate in single-channel detection systems and in multi-channel detection systems with very low crosstalk between channels. However, in dense multi-channel systems, it can be inadequate. Furthermore, it fails to fully and individually characterize each of the fundamental parameters of the detection system. We present a new detection system calibration method that enables accurate and repeatable measurement and calibration of MCP gain, MCP efficiency, signal loss due to variation in gain and efficiency, crosstalk from effects both above and below the MCP, noise margin, and stability margin in one single measurement. The fundamental concepts of this method, named threshold scan, will be presented. It will be shown how to derive all the individual detection system parameters. This new method has been successfully applied to achieve a highly accurate calibration of the 16 Dual Electron Spectrometers and 16 Dual Ion Spectrometers of the MMS mission. The practical application of the method will be presented together with the achieved calibration results and their significance. Finally, it will be shown how this method will be applied to ensure the best possible in flight calibration during the mission.

Editor’s message: Groundwater modeling fantasies - Part 1, adrift in the details

USGS Publications Warehouse

Voss, Clifford I.

2011-01-01

Fools ignore complexity. Pragmatists suffer it. Some can avoid it. Geniuses remove it. …Simplicity does not precede complexity, but follows it. (Epigrams in Programming by Alan Perlis, a computer scientist; Perlis 1982).A doctoral student creating a groundwater model of a regional aquifer put individual circular regions around data points where he had hydraulic head measurements, so that each region’s parameter values could be adjusted to get perfect fit with the measurement at that point. Nearly every measurement point had its own parameter-value region. After calibration, the student was satisfied because his model correctly reproduced all of his data. Did he really get the true field values of parameters in this manner? Did this approach result in a realistic, meaningful and useful groundwater model?—truly doubtful. Is this story a sign of a common style of educating hydrogeology students these days? Where this is the case, major changes are needed to add back ‘common-sense hydrogeology’ to the curriculum. Worse, this type of modeling approach has become an industry trend in application of groundwater models to real systems, encouraged by the advent of automatic model calibration software that has no problem providing numbers for as many parameter value estimates as desired. Just because a computer program can easily create such values does not mean that they are in any sense useful—but unquestioning practitioners are happy to follow such software developments, perhaps because of an implied promise that highly parameterized models, here referred to as ‘complex’, are somehow superior. This and other fallacies are implicit in groundwater modeling studies, most usually not acknowledged when presenting results. This two-part Editor’s Message deals with the state of groundwater modeling: part 1 (here) focuses on problems and part 2 (Voss 2011) on prospects.

Comment on ;Evaluation of a physically based quasi-linear and a conceptually based nonlinear Muskingum methods; [J. Hydrol., 546, 437-449, 10.1016/j.jhydrol.2017.01.025

NASA Astrophysics Data System (ADS)

Barati, Reza

2017-07-01

Perumal et al. (2017) compared the performances of the variable parameter McCarthy-Muskingum (VPMM) model of Perumal and Price (2013) and the nonlinear Muskingum (NLM) model of Gill (1978) using hypothetical inflow hydrographs in an artificial channel. As input parameters, first model needs the initial condition, upstream boundary condition, Manning's roughness coefficient, length of the routing reach, cross-sections of the river reach and the bed slope, while the latter one requires the initial condition, upstream boundary condition and the hydrologic parameters (three parameters which can be calibrated using flood hydrographs of the upstream and downstream sections). The VPMM model was examined by available Manning's roughness values, whereas the NLM model was tested in both calibration and validation steps. As final conclusion, Perumal et al. (2017) claimed that the NLM model should be retired from the literature of the Muskingum model. While the author's intention is laudable, this comment examines some important issues in the subject matter of the original study.

Four years of Landsat-7 on-orbit geometric calibration and performance

USGS Publications Warehouse

Lee, D.S.; Storey, James C.; Choate, M.J.; Hayes, R.W.

2004-01-01

Unlike its predecessors, Landsat-7 has undergone regular geometric and radiometric performance monitoring and calibration since launch in April 1999. This ongoing activity, which includes issuing quarterly updates to calibration parameters, has generated a wealth of geometric performance data over the four-year on-orbit period of operations. A suite of geometric characterization (measurement and evaluation procedures) and calibration (procedures to derive improved estimates of instrument parameters) methods are employed by the Landsat-7 Image Assessment System to maintain the geometric calibration and to track specific aspects of geometric performance. These include geodetic accuracy, band-to-band registration accuracy, and image-to-image registration accuracy. These characterization and calibration activities maintain image product geometric accuracy at a high level - by monitoring performance to determine when calibration is necessary, generating new calibration parameters, and verifying that new parameters achieve desired improvements in accuracy. Landsat-7 continues to meet and exceed all geometric accuracy requirements, although aging components have begun to affect performance.

Muon Energy Calibration of the MINOS Detectors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miyagawa, Paul S.

MINOS is a long-baseline neutrino oscillation experiment designed to search for conclusive evidence of neutrino oscillations and to measure the oscillation parameters precisely. MINOS comprises two iron tracking calorimeters located at Fermilab and Soudan. The Calibration Detector at CERN is a third MINOS detector used as part of the detector response calibration programme. A correct energy calibration between these detectors is crucial for the accurate measurement of oscillation parameters. This thesis presents a calibration developed to produce a uniform response within a detector using cosmic muons. Reconstruction of tracks in cosmic ray data is discussed. This data is utilized tomore » calculate calibration constants for each readout channel of the Calibration Detector. These constants have an average statistical error of 1.8%. The consistency of the constants is demonstrated both within a single run and between runs separated by a few days. Results are presented from applying the calibration to test beam particles measured by the Calibration Detector. The responses are calibrated to within 1.8% systematic error. The potential impact of the calibration on the measurement of oscillation parameters by MINOS is also investigated. Applying the calibration reduces the errors in the measured parameters by ~ 10%, which is equivalent to increasing the amount of data by 20%.« less

Modelling the root system architecture of Poaceae. Can we simulate integrated traits from morphological parameters of growth and branching?

PubMed

Pagès, Loïc; Picon-Cochard, Catherine

2014-10-01

Our objective was to calibrate a model of the root system architecture on several Poaceae species and to assess its value to simulate several 'integrated' traits measured at the root system level: specific root length (SRL), maximum root depth and root mass. We used the model ArchiSimple, made up of sub-models that represent and combine the basic developmental processes, and an experiment on 13 perennial grassland Poaceae species grown in 1.5-m-deep containers and sampled at two different dates after planting (80 and 120 d). Model parameters were estimated almost independently using small samples of the root systems taken at both dates. The relationships obtained for calibration validated the sub-models, and showed species effects on the parameter values. The simulations of integrated traits were relatively correct for SRL and were good for root depth and root mass at the two dates. We obtained some systematic discrepancies that were related to the slight decline of root growth in the last period of the experiment. Because the model allowed correct predictions on a large set of Poaceae species without global fitting, we consider that it is a suitable tool for linking root traits at different organisation levels. © 2014 INRA. New Phytologist © 2014 New Phytologist Trust.

Synoptic thermal and oceanographic parameter distributions in the New York Bight Apex

NASA Technical Reports Server (NTRS)

Johnson, R. W.; Bahn, G. S.; Thomas, J. P.

1981-01-01

Concurrent surface water measurements made from a moving oceanographic research vessel were used to calibrate and interpret remotely sensed data collected over a plume in the New York Bight Apex on 23 June 1977. Multiple regression techniques were used to develop equations to map synoptic distributions of chlorophyll a and total suspended matter in the remotely sensed scene. Thermal (which did not have surface calibration values) and water quality parameter distributions indicated a cold mass of water in the Bight Apex with an overflowing nutrient-rich warm water plume that originated in the Sandy Hook Bay and flowed south near the New Jersey shoreline. Data analysis indicates that remotely sensed data may be particularly useful for studying physical and biological processes in the top several metres of surface water at plume boundaries.

Non-invasive technique to measure biogeochemical parameters (pH and O2) in a microenvironment: Design and applications

NASA Astrophysics Data System (ADS)

Li, Biting; Seliman, Ayman; Pales, Ashley; Liang, Weizhen; Sams, Allison; Darnault, Christophe; Devol, Timothy

2017-04-01

The primary objectives of this research are to do the pH and O2 sensor foils calibration and then to test them in applications. Potentially, this project can be utilized to monitor the fate and transport of radionuclides in porous media. The information for physical and chemical parameters (e.g. pH and O2) is crucial to know when determining contaminants' behavior and transport in the environment. As a non-invasive method, optical imaging technique using a DSLR camera could capture data on the foil when it fluoresces, and gives a high temporal and spatial resolution during the experimental period. The calibration procedures were done in cuvettes in a row. The preliminary experiments could measure pH value in the range from 4.5 to 7.5, and O2 concentration from 0 mg/L to 20.74 mg/L. Applications of sensor foils have involved nano zero valent and acid rain experiments in order to obtain a gradient of parameter changes.

Limits of detection and decision. Part 3

NASA Astrophysics Data System (ADS)

Voigtman, E.

2008-02-01

It has been shown that the MARLAP (Multi-Agency Radiological Laboratory Analytical Protocols) for estimating the Currie detection limit, which is based on 'critical values of the non-centrality parameter of the non-central t distribution', is intrinsically biased, even if no calibration curve or regression is used. This completed the refutation of the method, begun in Part 2. With the field cleared of obstructions, the true theory underlying Currie's limits of decision, detection and quantification, as they apply in a simple linear chemical measurement system (CMS) having heteroscedastic, Gaussian measurement noise and using weighted least squares (WLS) processing, was then derived. Extensive Monte Carlo simulations were performed, on 900 million independent calibration curves, for linear, "hockey stick" and quadratic noise precision models (NPMs). With errorless NPM parameters, all the simulation results were found to be in excellent agreement with the derived theoretical expressions. Even with as much as 30% noise on all of the relevant NPM parameters, the worst absolute errors in rates of false positives and false negatives, was only 0.3%.

Microthrix parvicella abundance associates with activated sludge settling velocity and rheology - Quantifying and modelling filamentous bulking.

PubMed

Wágner, Dorottya S; Ramin, Elham; Szabo, Peter; Dechesne, Arnaud; Plósz, Benedek Gy

2015-07-01

The objective of this work is to identify relevant settling velocity and rheology model parameters and to assess the underlying filamentous microbial community characteristics that can influence the solids mixing and transport in secondary settling tanks. Parameter values for hindered, transient and compression settling velocity functions were estimated by carrying out biweekly batch settling tests using a novel column setup through a four-month long measurement campaign. To estimate viscosity model parameters, rheological experiments were carried out on the same sludge sample using a rotational viscometer. Quantitative fluorescence in-situ hybridisation (qFISH) analysis, targeting Microthrix parvicella and phylum Chloroflexi, was used. This study finds that M. parvicella - predominantly residing inside the microbial flocs in our samples - can significantly influence secondary settling through altering the hindered settling velocity and yield stress parameter. Strikingly, this is not the case for Chloroflexi, occurring in more than double the abundance of M. parvicella, and forming filaments primarily protruding from the flocs. The transient and compression settling parameters show a comparably high variability, and no significant association with filamentous abundance. A two-dimensional, axi-symmetrical computational fluid dynamics (CFD) model was used to assess calibration scenarios to model filamentous bulking. Our results suggest that model predictions can significantly benefit from explicitly accounting for filamentous bulking by calibrating the hindered settling velocity function. Furthermore, accounting for the transient and compression settling velocity in the computational domain is crucial to improve model accuracy when modelling filamentous bulking. However, the case-specific calibration of transient and compression settling parameters as well as yield stress is not necessary, and an average parameter set - obtained under bulking and good settling conditions - can be used. Copyright © 2015 Elsevier Ltd. All rights reserved.

Calibration of the advanced microwave sounding unit-A for NOAA-K

NASA Technical Reports Server (NTRS)

Mo, Tsan

1995-01-01

The thermal-vacuum chamber calibration data from the Advanced Microwave Sounding Unit-A (AMSU-A) for NOAA-K, which will be launched in 1996, were analyzed to evaluate the instrument performance, including calibration accuracy, nonlinearity, and temperature sensitivity. The AMSU-A on NOAA-K consists of AMSU-A2 Protoflight Model and AMSU-A1 Flight Model 1. The results show that both models meet the instrument specifications, except the AMSU-A1 antenna beamwidths, which exceed the requirement of 3.3 +/- 10%. We also studied the instrument's radiometric characterizations which will be incorporated into the operational calibration algorithm for processing the in-orbit AMSU-A data from space. Particularly, the nonlinearity parameters which will be used for correcting the nonlinear contributions from an imperfect square-law detector were determined from this data analysis. It was found that the calibration accuracies (differences between the measured scene radiances and those calculated from a linear two-point calibration formula) are polarization-dependent. Channels with vertical polarizations show little cold biases at the lowest scene target temperature 84K, while those with horizontal polarizations all have appreciable cold biases, which can be up to 0.6K. It is unknown where these polarization-dependent cold biases originate, but it is suspected that some chamber contamination of hot radiances leaked into the cold scene target area. Further investigation in this matter is required. The existence and magnitude of nonlinearity in each channel were established and a quadratic formula for modeling these nonlinear contributions was developed. The model was characterized by a single parameter u, values of which were obtained for each channel via least-squares fit to the data. Using the best-fit u values, we performed a series of simulations of the quadratic corrections which would be expected from the space data after the launch of AMSU-A on NOAA-K. In these simulations, the cosmic background radiance corresponding to a cold space temperature 2.73K was adopted as one of the two reference points of calibration. The largest simulated nonlinear correction is about 0.3K, which occurs at channel 15 when the instrument temperature is at 38.09 deg C. Others are less than 0.2K in the remaining channels. Possible improvement for future instrument calibration is also discussed.

Determining the soil hydraulic conductivity by means of a field scale internal drainage

NASA Astrophysics Data System (ADS)

Severino, Gerardo; Santini, Alessandro; Sommella, Angelo

2003-03-01

Spatial variations of water content in large extents soils (vadose zone) are highly affected by the natural heterogeneity of the porous medium. This implies that the magnitude of the hydraulic properties, especially the conductivity, varies in an irregular manner with scale. Determining mean values of hydraulic properties will not suffice to accurately quantify water flow in the vadose zone. At field scale proper field measurements have to be carried out, similar to standard laboratory methods that also characterize the spatial variability of the hydraulic properties. Toward this aim an internal drainage test has been conducted at Ponticelli site near Naples (Italy) where water content and pressure head were monitored at 50 locations of a 2×50 m 2 plot. The present paper illustrates a method to quantify the mean value and the spatial variability of the hydraulic parameters needed to calibrate the soil conductivity curve at field scale (hereafter defined as field scale hydraulic conductivity). A stochastic model that regards the hydraulic parameters as random space functions (RSFs) is derived by adopting the stream tube approach of Dagan and Bresler (1979). Owing to the randomness of the hydraulic parameters, even the water content θ will be a RSF whose mean value (hereafter termed field scale water content) is obtained as an ensemble average over all the realizations of a local analytical solution of Richards' equation. It is shown that the most frequent data collection should be carried out in the initial stage of the internal drainage experiment, when the most significant changes in water content occur. The model parameters are obtained by a standard least square optimization procedure using water content data at a certain depth (z=30 cm) for several times ( t=5, 24, 48, 96, 144, 216, 312, 408, 576, 744, 912 h). The reliability of the proposed method is then evaluated by comparing the predicted water content with observations at different depths ( z=45, 60, 75, and 90 cm). The calibration procedure is further verified by comparing the cumulative distribution of measured water content at different times with corresponding distribution obtained from the calibrated model.

InGaAs tunnel diodes for the calibration of semi-classical and quantum mechanical band-to-band tunneling models

NASA Astrophysics Data System (ADS)

Smets, Quentin; Verreck, Devin; Verhulst, Anne S.; Rooyackers, Rita; Merckling, Clément; Van De Put, Maarten; Simoen, Eddy; Vandervorst, Wilfried; Collaert, Nadine; Thean, Voon Y.; Sorée, Bart; Groeseneken, Guido; Heyns, Marc M.

2014-05-01

Promising predictions are made for III-V tunnel-field-effect transistor (FET), but there is still uncertainty on the parameters used in the band-to-band tunneling models. Therefore, two simulators are calibrated in this paper; the first one uses a semi-classical tunneling model based on Kane's formalism, and the second one is a quantum mechanical simulator implemented with an envelope function formalism. The calibration is done for In0.53Ga0.47As using several p+/intrinsic/n+ diodes with different intrinsic region thicknesses. The dopant profile is determined by SIMS and capacitance-voltage measurements. Error bars are used based on statistical and systematic uncertainties in the measurement techniques. The obtained parameters are in close agreement with theoretically predicted values and validate the semi-classical and quantum mechanical models. Finally, the models are applied to predict the input characteristics of In0.53Ga0.47As n- and p-lineTFET, with the n-lineTFET showing competitive performance compared to MOSFET.

Hydrologic Model Development and Calibration: Contrasting a Single- and Multi-Objective Approach for Comparing Model Performance

NASA Astrophysics Data System (ADS)

Asadzadeh, M.; Maclean, A.; Tolson, B. A.; Burn, D. H.

2009-05-01

Hydrologic model calibration aims to find a set of parameters that adequately simulates observations of watershed behavior, such as streamflow, or a state variable, such as snow water equivalent (SWE). There are different metrics for evaluating calibration effectiveness that involve quantifying prediction errors, such as the Nash-Sutcliffe (NS) coefficient and bias evaluated for the entire calibration period, on a seasonal basis, for low flows, or for high flows. Many of these metrics are conflicting such that the set of parameters that maximizes the high flow NS differs from the set of parameters that maximizes the low flow NS. Conflicting objectives are very likely when different calibration objectives are based on different fluxes and/or state variables (e.g., NS based on streamflow versus SWE). One of the most popular ways to balance different metrics is to aggregate them based on their importance and find the set of parameters that optimizes a weighted sum of the efficiency metrics. Comparing alternative hydrologic models (e.g., assessing model improvement when a process or more detail is added to the model) based on the aggregated objective might be misleading since it represents one point on the tradeoff of desired error metrics. To derive a more comprehensive model comparison, we solved a bi-objective calibration problem to estimate the tradeoff between two error metrics for each model. Although this approach is computationally more expensive than the aggregation approach, it results in a better understanding of the effectiveness of selected models at each level of every error metric and therefore provides a better rationale for judging relative model quality. The two alternative models used in this study are two MESH hydrologic models (version 1.2) of the Wolf Creek Research basin that differ in their watershed spatial discretization (a single Grouped Response Unit, GRU, versus multiple GRUs). The MESH model, currently under development by Environment Canada, is a coupled land-surface and hydrologic model. Results will demonstrate the conclusions a modeller might make regarding the value of additional watershed spatial discretization under both an aggregated (single-objective) and multi-objective model comparison framework.

Effects of ring-porous and diffuse-porous stem wood anatomy on the hydraulic parameters used in a water flow and storage model.

PubMed

Steppe, Kathy; Lemeur, Raoul

2007-01-01

Calibration of a recently developed water flow and storage model based on experimental data for a young diffuse-porous beech tree (Fagus sylvatica L.) and a young ring-porous oak tree (Quercus robur L.) revealed that differences in stem wood anatomy between species strongly affect the calibrated values of the hydraulic model parameters. The hydraulic capacitance (C) of the stem storage tissue was higher in oak than in beech (939.8 versus 212.3 mg MPa(-1)). Model simulation of the elastic modulus (epsilon) revealed that this difference was linked to the higher elasticity of the stem storage tissue of oak compared with beech. Furthermore, the hydraulic resistance (R (x)) of beech was about twice that of oak (0.1829 versus 0.1072 MPa s mg(-1)). To determine the physiological meaning of the R (x) parameter identified by model calibration, we analyzed the stem wood anatomy of the beech and oak trees. Calculation of stem specific hydraulic conductivity (k (s)) of beech and oak with the Hagen-Poiseuille equation confirmed the differences in R (x) predicted by the model. The contributions of different vessel diameter classes to the total hydraulic conductivity of the xylem were calculated. As expected, the few big vessels contributed much more to total conductivity than the many small vessels. Compared with beech, the larger vessels of oak resulted in a higher k (s) (10.66 versus 4.90 kg m(-1) s(-1) MPa(-1)). The calculated ratio of k (s) of oak to beech was 2, confirming the R (x) ratio obtained by model calibration. Thus, validation of the R (x) parameter of the model led to identification of its physiological meaning.

40 CFR Appendix I to Part 94 - Emission-Related Engine Parameters and Specifications

Code of Federal Regulations, 2012 CFR

2012-07-01

.... Temperature control system calibration. 4. Maximum allowable inlet air restriction. III. Fuel System. 1. General. a. Engine idle speed. 2. Fuel injection—compression ignition engines. a. Control parameters and calibrations. b. Transient enrichment system calibration. c. Air-fuel flow calibration. d. Altitude...

40 CFR Appendix I to Part 94 - Emission-Related Engine Parameters and Specifications

Code of Federal Regulations, 2011 CFR

2011-07-01

.... Temperature control system calibration. 4. Maximum allowable inlet air restriction. III. Fuel System. 1. General. a. Engine idle speed. 2. Fuel injection—compression ignition engines. a. Control parameters and calibrations. b. Transient enrichment system calibration. c. Air-fuel flow calibration. d. Altitude...

40 CFR Appendix I to Part 94 - Emission-Related Engine Parameters and Specifications

Code of Federal Regulations, 2014 CFR

2014-07-01

.... Temperature control system calibration. 4. Maximum allowable inlet air restriction. III. Fuel System. 1. General. a. Engine idle speed. 2. Fuel injection—compression ignition engines. a. Control parameters and calibrations. b. Transient enrichment system calibration. c. Air-fuel flow calibration. d. Altitude...

40 CFR Appendix I to Part 94 - Emission-Related Engine Parameters and Specifications

Code of Federal Regulations, 2013 CFR

2013-07-01

.... Temperature control system calibration. 4. Maximum allowable inlet air restriction. III. Fuel System. 1. General. a. Engine idle speed. 2. Fuel injection—compression ignition engines. a. Control parameters and calibrations. b. Transient enrichment system calibration. c. Air-fuel flow calibration. d. Altitude...

Determination of calibration parameters of a VRX CT system using an “Amoeba” algorithm

PubMed Central

Jordan, Lawrence M.; DiBianca, Frank A.; Melnyk, Roman; Choudhary, Apoorva; Shukla, Hemant; Laughter, Joseph; Gaber, M. Waleed

2008-01-01

Efforts to improve the spatial resolution of CT scanners have focused mainly on reducing the source and detector element sizes, ignoring losses from the size of the secondary-ionization charge “clouds” created by the detected x-ray photons, i.e., the “physics limit.” This paper focuses on implementing a technique called “projective compression.” which allows further reduction in effective cell size while overcoming the physics limit as well. Projective compression signifies detector geometries in which the apparent cell size is smaller than the physical cell size, allowing large resolution boosts. A realization of this technique has been developed with a dual-arm “variable-resolution x-ray” (VRX) detector. Accurate values of the geometrical parameters are needed to convert VRX outputs to formats ready for optimal image reconstruction by standard CT techniques. The required calibrating data are obtained by scanning a rotating pin and fitting a theoretical parametric curve (using a multi-parameter minimization algorithm) to the resulting pin sinogram. Excellent fits are obtained for both detector-arm sections with an average (maximum) fit deviation of ~0.05 (0.1) detector cell width. Fit convergence and sensitivity to starting conditions are considered. Pre- and post-optimization reconstructions of the alignment pin and a biological subject reconstruction after calibration are shown. PMID:19430581

Determination of calibration parameters of a VRX CT system using an "Amoeba" algorithm.

PubMed

Jordan, Lawrence M; Dibianca, Frank A; Melnyk, Roman; Choudhary, Apoorva; Shukla, Hemant; Laughter, Joseph; Gaber, M Waleed

2004-01-01

Efforts to improve the spatial resolution of CT scanners have focused mainly on reducing the source and detector element sizes, ignoring losses from the size of the secondary-ionization charge "clouds" created by the detected x-ray photons, i.e., the "physics limit." This paper focuses on implementing a technique called "projective compression." which allows further reduction in effective cell size while overcoming the physics limit as well. Projective compression signifies detector geometries in which the apparent cell size is smaller than the physical cell size, allowing large resolution boosts. A realization of this technique has been developed with a dual-arm "variable-resolution x-ray" (VRX) detector. Accurate values of the geometrical parameters are needed to convert VRX outputs to formats ready for optimal image reconstruction by standard CT techniques. The required calibrating data are obtained by scanning a rotating pin and fitting a theoretical parametric curve (using a multi-parameter minimization algorithm) to the resulting pin sinogram. Excellent fits are obtained for both detector-arm sections with an average (maximum) fit deviation of ~0.05 (0.1) detector cell width. Fit convergence and sensitivity to starting conditions are considered. Pre- and post-optimization reconstructions of the alignment pin and a biological subject reconstruction after calibration are shown.

Power spectrum analysis with least-squares fitting: amplitude bias and its elimination, with application to optical tweezers and atomic force microscope cantilevers.

PubMed

Nørrelykke, Simon F; Flyvbjerg, Henrik

2010-07-01

Optical tweezers and atomic force microscope (AFM) cantilevers are often calibrated by fitting their experimental power spectra of Brownian motion. We demonstrate here that if this is done with typical weighted least-squares methods, the result is a bias of relative size between -2/n and +1/n on the value of the fitted diffusion coefficient. Here, n is the number of power spectra averaged over, so typical calibrations contain 10%-20% bias. Both the sign and the size of the bias depend on the weighting scheme applied. Hence, so do length-scale calibrations based on the diffusion coefficient. The fitted value for the characteristic frequency is not affected by this bias. For the AFM then, force measurements are not affected provided an independent length-scale calibration is available. For optical tweezers there is no such luck, since the spring constant is found as the ratio of the characteristic frequency and the diffusion coefficient. We give analytical results for the weight-dependent bias for the wide class of systems whose dynamics is described by a linear (integro)differential equation with additive noise, white or colored. Examples are optical tweezers with hydrodynamic self-interaction and aliasing, calibration of Ornstein-Uhlenbeck models in finance, models for cell migration in biology, etc. Because the bias takes the form of a simple multiplicative factor on the fitted amplitude (e.g. the diffusion coefficient), it is straightforward to remove and the user will need minimal modifications to his or her favorite least-squares fitting programs. Results are demonstrated and illustrated using synthetic data, so we can compare fits with known true values. We also fit some commonly occurring power spectra once-and-for-all in the sense that we give their parameter values and associated error bars as explicit functions of experimental power-spectral values.

An Empirical Calibration of the Mixing-Length Parameter α

NASA Astrophysics Data System (ADS)

Ferraro, Francesco R.; Valenti, Elena; Straniero, Oscar; Origlia, Livia

2006-05-01

We present an empirical calibration of the mixing-length free parameter α based on a homogeneous infrared database of 28 Galactic globular clusters spanning a wide metallicity range (-2.15<[Fe/H]<-0.2). Empirical estimates of the red giant effective temperatures have been obtained from infrared colors. Suitable relations linking these temperatures to the cluster metallicity have been obtained and compared to theoretical predictions. An appropriate set of models for the Sun and Population II giants has been computed by using both the standard solar metallicity (Z/X)solar=0.0275 and the most recently proposed value (Z/X)solar=0.0177. We find that when the standard solar metallicity is adopted, a unique value of α=2.17 can be used to reproduce both the solar radius and the Population II red giant temperature. Conversely, when the new solar metallicity is adopted, two different values of α are required: α=1.86 to fit the solar radius and α~2.0 to fit the red giant temperatures. However, it must be noted that regardless the adopted solar reference, the α-parameter does not show any significant dependence on metallicity. Based on observations collected at the European Southern Observatory (ESO), La Silla, Chile. Also based on observations made with the Italian Telescopio Nazionale Galileo (TNG) operated on the island of La Palma by the Fundacion Galileo Galilei of the INAF (Istituto Nazionale di Astrofisica) at the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofisica de Canarias.

Curve Number Application in Continuous Runoff Models: An Exercise in Futility?

NASA Astrophysics Data System (ADS)

Lamont, S. J.; Eli, R. N.

2006-12-01

The suitability of applying the NRCS (Natural Resource Conservation Service) Curve Number (CN) to continuous runoff prediction is examined by studying the dependence of CN on several hydrologic variables in the context of a complex nonlinear hydrologic model. The continuous watershed model Hydrologic Simulation Program-FORTRAN (HSPF) was employed using a simple theoretical watershed in two numerical procedures designed to investigate the influence of soil type, soil depth, storm depth, storm distribution, and initial abstraction ratio value on the calculated CN value. This study stems from a concurrent project involving the design of a hydrologic modeling system to support the Cumulative Hydrologic Impact Assessments (CHIA) of over 230 coal-mined watersheds throughout West Virginia. Because of the large number of watersheds and limited availability of data necessary for HSPF calibration, it was initially proposed that predetermined CN values be used as a surrogate for those HSPF parameters controlling direct runoff. A soil physics model was developed to relate CN values to those HSPF parameters governing soil moisture content and infiltration behavior, with the remaining HSPF parameters being adopted from previous calibrations on real watersheds. A numerical procedure was then adopted to back-calculate CN values from the theoretical watershed using antecedent moisture conditions equivalent to the NRCS Antecedent Runoff Condition (ARC) II. This procedure used the direct runoff produced from a cyclic synthetic storm event time series input to HSPF. A second numerical method of CN determination, using real time series rainfall data, was used to provide a comparison to those CN values determined using the synthetic storm event time series. It was determined that the calculated CN values resulting from both numerical methods demonstrated a nonlinear dependence on all of the computational variables listed above. It was concluded that the use of the Curve Number as a surrogate for the selected subset of HPSF parameters could not be justified. These results suggest that use of the Curve Number in other complex continuous time series hydrologic models may not be appropriate, given the limitations inherent in the definition of the NRCS CN method.

Use of a Stanton Tube for Skin-Friction Measurements

NASA Technical Reports Server (NTRS)

Abarbanel, S. S.; Hakkinen, R. J.; Trilling, L.

1959-01-01

A small total-pressure tube resting against a flat-plate surface was used as a Stanton tube and calibrated as a skin-friction meter at various subsonic and supersonic speeds. Laminar flow was maintained for the supersonic runs at a Mach number M(sub infinity) of 2. At speeds between M(sub infinity) = 1.33 and M(sub infinity) = 1.87, the calibrations were carried-out in a turbulent boundary layer. The subsonic flows were found to be in transition. The skin-friction readings of a floating-element type of balance served as the reference values against which the Stanton tube was calibrated. A theoretical model was developed which, for moderate values of the shear parameter tau, accurately predicts the performance of the Stanton tube in subsonic and supersonic flows. A "shear correction factor" was found to explain the deviations from the basic model when T became too large. Compressibility effects were important only in the case of turbulent supersonic flows, and they did not alter the form of the calibration curve. The test Reynolds numbers, based on the distance from the leading edge and free-stream conditions, ranged from 70,000 to 875,000. The turbulent-boundary-layer Reynolds numbers, based on momentum thickness, varied between 650 and 2,300. Both laminar and turbulent velocity profiles were taken and the effect of pressure gradient on the calibration was investigated.

Quality evaluation of frozen guava and yellow passion fruit pulps by NIR spectroscopy and chemometrics.

PubMed

Alamar, Priscila D; Caramês, Elem T S; Poppi, Ronei J; Pallone, Juliana A L

2016-07-01

The present study investigated the application of near infrared spectroscopy as a green, quick, and efficient alternative to analytical methods currently used to evaluate the quality (moisture, total sugars, acidity, soluble solids, pH and ascorbic acid) of frozen guava and passion fruit pulps. Fifty samples were analyzed by near infrared spectroscopy (NIR) and reference methods. Partial least square regression (PLSR) was used to develop calibration models to relate the NIR spectra and the reference values. Reference methods indicated adulteration by water addition in 58% of guava pulp samples and 44% of yellow passion fruit pulp samples. The PLS models produced lower values of root mean squares error of calibration (RMSEC), root mean squares error of prediction (RMSEP), and coefficient of determination above 0.7. Moisture and total sugars presented the best calibration models (RMSEP of 0.240 and 0.269, respectively, for guava pulp; RMSEP of 0.401 and 0.413, respectively, for passion fruit pulp) which enables the application of these models to determine adulteration in guava and yellow passion fruit pulp by water or sugar addition. The models constructed for calibration of quality parameters of frozen fruit pulps in this study indicate that NIR spectroscopy coupled with the multivariate calibration technique could be applied to determine the quality of guava and yellow passion fruit pulp. Copyright © 2016 Elsevier Ltd. All rights reserved.

Reducing equifinality of hydrological models by integrating Functional Streamflow Disaggregation

NASA Astrophysics Data System (ADS)

Lüdtke, Stefan; Apel, Heiko; Nied, Manuela; Carl, Peter; Merz, Bruno

2014-05-01

A universal problem of the calibration of hydrological models is the equifinality of different parameter sets derived from the calibration of models against total runoff values. This is an intrinsic problem stemming from the quality of the calibration data and the simplified process representation by the model. However, discharge data contains additional information which can be extracted by signal processing methods. An analysis specifically developed for the disaggregation of runoff time series into flow components is the Functional Streamflow Disaggregation (FSD; Carl & Behrendt, 2008). This method is used in the calibration of an implementation of the hydrological model SWIM in a medium sized watershed in Thailand. FSD is applied to disaggregate the discharge time series into three flow components which are interpreted as base flow, inter-flow and surface runoff. In addition to total runoff, the model is calibrated against these three components in a modified GLUE analysis, with the aim to identify structural model deficiencies, assess the internal process representation and to tackle equifinality. We developed a model dependent (MDA) approach calibrating the model runoff components against the FSD components, and a model independent (MIA) approach comparing the FSD of the model results and the FSD of calibration data. The results indicate, that the decomposition provides valuable information for the calibration. Particularly MDA highlights and discards a number of standard GLUE behavioural models underestimating the contribution of soil water to river discharge. Both, MDA and MIA yield to a reduction of the parameter ranges by a factor up to 3 in comparison to standard GLUE. Based on these results, we conclude that the developed calibration approach is able to reduce the equifinality of hydrological model parameterizations. The effect on the uncertainty of the model predictions is strongest by applying MDA and shows only minor reductions for MIA. Besides further validation of FSD, the next steps include an extension of the study to different catchments and other hydrological models with a similar structure.

Evaluating prediction uncertainty of areas contributing recharge to well fields of multiple water suppliers in the Hunt-Annaquatucket-Pettaquamscutt River Basins, Rhode Island

USGS Publications Warehouse

Friesz, Paul J.

2012-01-01

Three river basins in central Rhode Island-the Hunt River, the Annaquatucket River, and the Pettaquamscutt River-contain 15 production wells clustered in 4 pumping centers from which drinking water is withdrawn. These high-capacity production wells, operated by three water suppliers, are screened in coarse-grained deposits of glacial origin. The risk of contaminating water withdrawn by these well centers may be reduced if the areas contributing recharge to the well centers are delineated and these areas protected from land uses that may affect the water quality. The U.S. Geological Survey, in cooperation with the Rhode Island Department of Health, began an investigation in 2009 to improve the understanding of groundwater flow and delineate areas contributing recharge to the well centers as part of an effort to protect the source of water to these well centers. A groundwater-flow model was calibrated by inverse modeling using nonlinear regression to obtain the optimal set of parameter values, which provide a single, best representation of the area contributing recharge to a well center. Summary statistics from the calibrated model were used to evaluate the uncertainty associated with the predicted areas contributing recharge to the well centers. This uncertainty analysis was done so that the contributing areas to the well centers would not be underestimated, thereby leaving the well centers inadequately protected. The analysis led to contributing areas expressed as a probability distribution (probabilistic contributing areas) that differ from a single or deterministic contributing area. Groundwater flow was simulated in the surficial deposits and the underlying bedrock in the 47-square-mile study area. Observations (165 groundwater levels and 7 base flows) provided sufficient information to estimate parameters representing recharge and horizontal hydraulic conductivity of the glacial deposits and hydraulic conductance of streambeds. The calibrated value for recharge to valley-fill deposits was 27.3 inches per year (in/yr) and to upland till deposits was 18.7 in/yr. Calibrated values for horizontal hydraulic conductivity of the valley-fill deposits ranged from 20 to 480 feet per day (ft/d) and of the upland till deposits was 16.2 ft/d. Calibrated values of streambed hydraulic conductance ranged from 10,000 to 52,000 feet squared per day. Values of recharge and horizontal hydraulic conductivity of the valley-fill deposits were the most precisely estimated, whereas the horizontal hydraulic conductivity of till deposits was the least precisely estimated. Simulated areas contributing recharge to the well centers on the basis of the calibrated model ranged from 0.19 to 1.12 square miles (mi2) and covered a total area of 2.79 mi2 for average well center withdrawal rates during 2004-08 (235 to 1,858 gallons per minute (gal/min)). Simulated areas contributing recharge for the maximum well center pumping capacities (800 to 8,500 gal/min) ranged from 0.37 to 3.53 mi2 and covered a total area of 7.99 mi2 in the modeled area. Simulated areas contributing recharge extend upgradient of the well centers to upland till and to groundwater divides. Some areas contributing recharge include small, isolated areas remote from the well centers. Relatively short groundwater traveltimes from recharging locations to discharging wells indicated the wells are vulnerable to contamination from land-surface activities: median traveltimes ranged from 2.9 to 5.0 years for the well centers, and 78 to 93 percent of the traveltimes were 10 years or less for the well centers. Land cover in the areas contributing recharge includes a substantial amount of urban land use for the two well centers in the Hunt River Basin, agriculture and sand and gravel mining uses for the well center in the Annaquatucket River Basin, and, for the well center in the Pettaquamscutt River Basin, land use is primarily undeveloped. Model-prediction uncertainty was evaluated using a Monte Carlo analysis. The parameter variance-covariance matrix from nonlinear regression was used to create parameter sets that reflect the uncertainty of the parameter estimates and the correlation among parameters. The remaining parameters representing the glacial deposits (vertical anisotropy of valley-fill deposits and of till deposits, maximum groundwater evapotranspiration, and hydraulic conductance for headdependent cells representing a groundwater divide) that could not be estimated with nonlinear regression were incorporated into the variance-covariance matrix using prior information on parameters. Thus the uncertainty analysis was an outcome of calibrating the parameters to available observations and to information that the modeler provided. A water budget and model-fit statistical criteria were used to assess parameter sets so that prediction uncertainty was not overestimated. Because of the effects of parameter uncertainty, the size of the probabilistic contributing areas for each well center for both average and maximum pumping rates was larger than the size of the deterministic contributing areas for the well center. Thus, some areas not in the deterministic contributing area may actually be in the contributing area, including additional areas of urban and agricultural land use. Generally, areas closest to the well centers with short groundwater traveltimes are associated with higher probabilities, whereas areas distant from the well centers with long groundwater traveltimes are associated with lower probabilities. The deterministic contributing areas generally corresponded to areas associated with high probabilities (greater than 50 percent). Areas associated with low probabilities extended long distances along groundwater divides in the uplands remote from the well centers.

UCODE_2005 and six other computer codes for universal sensitivity analysis, calibration, and uncertainty evaluation constructed using the JUPITER API

USGS Publications Warehouse

Poeter, Eileen E.; Hill, Mary C.; Banta, Edward R.; Mehl, Steffen; Christensen, Steen

2006-01-01

This report documents the computer codes UCODE_2005 and six post-processors. Together the codes can be used with existing process models to perform sensitivity analysis, data needs assessment, calibration, prediction, and uncertainty analysis. Any process model or set of models can be used; the only requirements are that models have numerical (ASCII or text only) input and output files, that the numbers in these files have sufficient significant digits, that all required models can be run from a single batch file or script, and that simulated values are continuous functions of the parameter values. Process models can include pre-processors and post-processors as well as one or more models related to the processes of interest (physical, chemical, and so on), making UCODE_2005 extremely powerful. An estimated parameter can be a quantity that appears in the input files of the process model(s), or a quantity used in an equation that produces a value that appears in the input files. In the latter situation, the equation is user-defined. UCODE_2005 can compare observations and simulated equivalents. The simulated equivalents can be any simulated value written in the process-model output files or can be calculated from simulated values with user-defined equations. The quantities can be model results, or dependent variables. For example, for ground-water models they can be heads, flows, concentrations, and so on. Prior, or direct, information on estimated parameters also can be considered. Statistics are calculated to quantify the comparison of observations and simulated equivalents, including a weighted least-squares objective function. In addition, data-exchange files are produced that facilitate graphical analysis. UCODE_2005 can be used fruitfully in model calibration through its sensitivity analysis capabilities and its ability to estimate parameter values that result in the best possible fit to the observations. Parameters are estimated using nonlinear regression: a weighted least-squares objective function is minimized with respect to the parameter values using a modified Gauss-Newton method or a double-dogleg technique. Sensitivities needed for the method can be read from files produced by process models that can calculate sensitivities, such as MODFLOW-2000, or can be calculated by UCODE_2005 using a more general, but less accurate, forward- or central-difference perturbation technique. Problems resulting from inaccurate sensitivities and solutions related to the perturbation techniques are discussed in the report. Statistics are calculated and printed for use in (1) diagnosing inadequate data and identifying parameters that probably cannot be estimated; (2) evaluating estimated parameter values; and (3) evaluating how well the model represents the simulated processes. Results from UCODE_2005 and codes RESIDUAL_ANALYSIS and RESIDUAL_ANALYSIS_ADV can be used to evaluate how accurately the model represents the processes it simulates. Results from LINEAR_UNCERTAINTY can be used to quantify the uncertainty of model simulated values if the model is sufficiently linear. Results from MODEL_LINEARITY and MODEL_LINEARITY_ADV can be used to evaluate model linearity and, thereby, the accuracy of the LINEAR_UNCERTAINTY results. UCODE_2005 can also be used to calculate nonlinear confidence and predictions intervals, which quantify the uncertainty of model simulated values when the model is not linear. CORFAC_PLUS can be used to produce factors that allow intervals to account for model intrinsic nonlinearity and small-scale variations in system characteristics that are not explicitly accounted for in the model or the observation weighting. The six post-processing programs are independent of UCODE_2005 and can use the results of other programs that produce the required data-exchange files. UCODE_2005 and the other six codes are intended for use on any computer operating system. The programs con

Vegetation canopy cover effects on sediment erosion processes in the upper Colorado River Basin mancos shale formation, Price, Utah

USDA-ARS?s Scientific Manuscript database

This study provides new parameterizations for applying the Rangeland Hydrology and Erosion Model (RHEM) on the highly erosive, rangeland saline soils of the Mancos Shale formation in the Price-San Rafael River Basin in east central Utah. Calibrated hydrologic parameters (Kss and K') values are gener...

Summary and Outlook

NASA Astrophysics Data System (ADS)

Wuest, Martin; Robinson, David W.; Decoste, Dennis

Calibration is defined as a set of operations that establish, under specified conditions, the relationship between the values of quantities indicated by a measuring instrument or measuring system and the corresponding values realized by standards. Calibration of an instrument means determining by how much the instrument reading is in error by checking it against a measurement standard of known error.Space physics particle instrumentation needs to be calibrated on the ground and inflight to insure that the data can be properly interpreted.On the ground, calibration is performed by exposing the instrument to a well characterized incident particle beam. Not only the nominal range of parameters the instrument is designed to measure should be calibrated but the instrument should also be exposed to out-of-band exposure such as higher energies, angles outside of the nominal field-of-view and susceptibility to ultraviolet radiation.There are several challenges to laboratory calibration on the ground. The beam must be well characterized in energy, angle, mass and position. The particle flux must be uniform over the whole aperture area of the instrument to be calibrated. The beam must be very stable in time and space. One of the difficulties arises that in order to measure the incident particle flux the beam monitor is placed upstream in front of the instrument thereby blocking the incident beam and interrupting the beam detection by the device under test. A beam monitor placed outside of the field-of-view of the instrument to be calibrated is often in a region at the fringes of the beam where the beam is not very stable. This basically prevents the measuring of the same beam with a trusted reference detector and the instrument under test at the same time. Further, highly sensitive instruments are calibrated at flux levels too low to be detected with stable Faraday cup detectors. Present day windowless electron multiplier detectors are able to measure the low flux levels but are sensitive to degradation as a function of contamination and the amount of extracted charge. Windowless electron multipliers are therefore not very stable reference detectors. This makes it difficult to obtain a reliable absolute calibration traceable to a national measurement institute. Calibration is still a time consuming process. It involves testing the instrument at component, subsystem and integrated level. It is important that the instrument is not only operated using a special calibration configuration to save time, but also in its full flight configuration exercising the full path of the data through data compression and telemetry. Very seldom there is enough time available to calibrate all the desired points in parameter space. Usually only a subset can be calibrated for schedule and economic reasons. The number of calibration points is often further reduced since the available calibration time is cut due to development schedule slip and a fixed launch date. This increases the uncertainties as more parameters have to be interpolated or extrapolated. Calibration data should be evaluated preferably in near-real time to prevent losing valuable calibration time if something in the instrument or facility is not working properly. Computer simulation models should be used to obtain a thorough understanding of the actual flight instrument. In flight the instrument performance degrades due to contamination (outgassing), environmental effects (atomic oxygen, radiation) or aging. One of the most sensitive parts in today's instrument are their detectors. Microchannel plate detectors degrade as function of the extracted charge. Solid-state detectors experience radiation damage which increases their noise and the lower energy detection threshold. The goal of the in-flight calibration is to determine this instrument degradation. Calibration is then performed by comparing measurements taken with different bias voltage or discriminator threshold settings. If possible, the instrument data is compared with other sensors covering the same or at least a part of the same measurand on the same or on a different spacecraft. In-flight calibration is not easy, as no absolute calibration standard for particles exist in space and measuring the same physical quantity with two different spacecraft at the same environmental conditions is very challenging.

Multi-objective vs. single-objective calibration of a hydrologic model using single- and multi-objective screening

NASA Astrophysics Data System (ADS)

Mai, Juliane; Cuntz, Matthias; Shafii, Mahyar; Zink, Matthias; Schäfer, David; Thober, Stephan; Samaniego, Luis; Tolson, Bryan

2016-04-01

Hydrologic models are traditionally calibrated against observed streamflow. Recent studies have shown however, that only a few global model parameters are constrained using this kind of integral signal. They can be identified using prior screening techniques. Since different objectives might constrain different parameters, it is advisable to use multiple information to calibrate those models. One common approach is to combine these multiple objectives (MO) into one single objective (SO) function and allow the use of a SO optimization algorithm. Another strategy is to consider the different objectives separately and apply a MO Pareto optimization algorithm. In this study, two major research questions will be addressed: 1) How do multi-objective calibrations compare with corresponding single-objective calibrations? 2) How much do calibration results deteriorate when the number of calibrated parameters is reduced by a prior screening technique? The hydrologic model employed in this study is a distributed hydrologic model (mHM) with 52 model parameters, i.e. transfer coefficients. The model uses grid cells as a primary hydrologic unit, and accounts for processes like snow accumulation and melting, soil moisture dynamics, infiltration, surface runoff, evapotranspiration, subsurface storage and discharge generation. The model is applied in three distinct catchments over Europe. The SO calibrations are performed using the Dynamically Dimensioned Search (DDS) algorithm with a fixed budget while the MO calibrations are achieved using the Pareto Dynamically Dimensioned Search (PA-DDS) algorithm allowing for the same budget. The two objectives used here are the Nash Sutcliffe Efficiency (NSE) of the simulated streamflow and the NSE of the logarithmic transformation. It is shown that the SO DDS results are located close to the edges of the Pareto fronts of the PA-DDS. The MO calibrations are hence preferable due to their supply of multiple equivalent solutions from which the user can choose at the end due to the specific needs. The sequential single-objective parameter screening was employed prior to the calibrations reducing the number of parameters by at least 50% in the different catchments and for the different single objectives. The single-objective calibrations led to a faster convergence of the objectives and are hence beneficial when using a DDS on single-objectives. The above mentioned parameter screening technique is generalized for multi-objectives and applied before calibration using the PA-DDS algorithm. Two different alternatives of this MO-screening are tested. The comparison of the calibration results using all parameters and using only screened parameters shows for both alternatives that the PA-DDS algorithm does not profit in terms of trade-off size and function evaluations required to achieve converged pareto fronts. This is because the PA-DDS algorithm automatically reduces search space with progress of the calibration run. This automatic reduction should be different for other search algorithms. It is therefore hypothesized that prior screening can but must not be beneficial for parameter estimation dependent on the chosen optimization algorithm.

A Full-Envelope Air Data Calibration and Three-Dimensional Wind Estimation Method Using Global Output-Error Optimization and Flight-Test Techniques

NASA Technical Reports Server (NTRS)

Taylor, Brian R.

2012-01-01

A novel, efficient air data calibration method is proposed for aircraft with limited envelopes. This method uses output-error optimization on three-dimensional inertial velocities to estimate calibration and wind parameters. Calibration parameters are based on assumed calibration models for static pressure, angle of attack, and flank angle. Estimated wind parameters are the north, east, and down components. The only assumptions needed for this method are that the inertial velocities and Euler angles are accurate, the calibration models are correct, and that the steady-state component of wind is constant throughout the maneuver. A two-minute maneuver was designed to excite the aircraft over the range of air data calibration parameters and de-correlate the angle-of-attack bias from the vertical component of wind. Simulation of the X-48B (The Boeing Company, Chicago, Illinois) aircraft was used to validate the method, ultimately using data derived from wind-tunnel testing to simulate the un-calibrated air data measurements. Results from the simulation were accurate and robust to turbulence levels comparable to those observed in flight. Future experiments are planned to evaluate the proposed air data calibration in a flight environment.

Microscope self-calibration based on micro laser line imaging and soft computing algorithms

NASA Astrophysics Data System (ADS)

Apolinar Muñoz Rodríguez, J.

2018-06-01

A technique to perform microscope self-calibration via micro laser line and soft computing algorithms is presented. In this technique, the microscope vision parameters are computed by means of soft computing algorithms based on laser line projection. To implement the self-calibration, a microscope vision system is constructed by means of a CCD camera and a 38 μm laser line. From this arrangement, the microscope vision parameters are represented via Bezier approximation networks, which are accomplished through the laser line position. In this procedure, a genetic algorithm determines the microscope vision parameters by means of laser line imaging. Also, the approximation networks compute the three-dimensional vision by means of the laser line position. Additionally, the soft computing algorithms re-calibrate the vision parameters when the microscope vision system is modified during the vision task. The proposed self-calibration improves accuracy of the traditional microscope calibration, which is accomplished via external references to the microscope system. The capability of the self-calibration based on soft computing algorithms is determined by means of the calibration accuracy and the micro-scale measurement error. This contribution is corroborated by an evaluation based on the accuracy of the traditional microscope calibration.

Effect of correlated observation error on parameters, predictions, and uncertainty

USGS Publications Warehouse

Tiedeman, Claire; Green, Christopher T.

2013-01-01

Correlations among observation errors are typically omitted when calculating observation weights for model calibration by inverse methods. We explore the effects of omitting these correlations on estimates of parameters, predictions, and uncertainties. First, we develop a new analytical expression for the difference in parameter variance estimated with and without error correlations for a simple one-parameter two-observation inverse model. Results indicate that omitting error correlations from both the weight matrix and the variance calculation can either increase or decrease the parameter variance, depending on the values of error correlation (ρ) and the ratio of dimensionless scaled sensitivities (rdss). For small ρ, the difference in variance is always small, but for large ρ, the difference varies widely depending on the sign and magnitude of rdss. Next, we consider a groundwater reactive transport model of denitrification with four parameters and correlated geochemical observation errors that are computed by an error-propagation approach that is new for hydrogeologic studies. We compare parameter estimates, predictions, and uncertainties obtained with and without the error correlations. Omitting the correlations modestly to substantially changes parameter estimates, and causes both increases and decreases of parameter variances, consistent with the analytical expression. Differences in predictions for the models calibrated with and without error correlations can be greater than parameter differences when both are considered relative to their respective confidence intervals. These results indicate that including observation error correlations in weighting for nonlinear regression can have important effects on parameter estimates, predictions, and their respective uncertainties.

Development of NIRS models to predict protein and amylose content of brown rice and proximate compositions of rice bran.

PubMed

Bagchi, Torit Baran; Sharma, Srigopal; Chattopadhyay, Krishnendu

2016-01-15

With the escalating persuasion of economic and nutritional importance of rice grain protein and nutritional components of rice bran (RB), NIRS can be an effective tool for high throughput screening in rice breeding programme. Optimization of NIRS is prerequisite for accurate prediction of grain quality parameters. In the present study, 173 brown rice (BR) and 86 RB samples with a wide range of values were used to compare the calibration models generated by different chemometrics for grain protein (GPC) and amylose content (AC) of BR and proximate compositions (protein, crude oil, moisture, ash and fiber content) of RB. Various modified partial least square (mPLSs) models corresponding with the best mathematical treatments were identified for all components. Another set of 29 genotypes derived from the breeding programme were employed for the external validation of these calibration models. High accuracy of all these calibration and prediction models was ensured through pair t-test and correlation regression analysis between reference and predicted values. Copyright © 2015 Elsevier Ltd. All rights reserved.

Generator Dynamic Model Validation and Parameter Calibration Using Phasor Measurements at the Point of Connection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Zhenyu; Du, Pengwei; Kosterev, Dmitry

2013-05-01

Disturbance data recorded by phasor measurement units (PMU) offers opportunities to improve the integrity of dynamic models. However, manually tuning parameters through play-back events demands significant efforts and engineering experiences. In this paper, a calibration method using the extended Kalman filter (EKF) technique is proposed. The formulation of EKF with parameter calibration is discussed. Case studies are presented to demonstrate its validity. The proposed calibration method is cost-effective, complementary to traditional equipment testing for improving dynamic model quality.

A transition matrix approach to the Davenport gryo calibration scheme

NASA Technical Reports Server (NTRS)

Natanson, G. A.

1998-01-01

The in-flight gyro calibration scheme commonly used by NASA Goddard Space Flight Center (GSFC) attitude ground support teams closely follows an original version of the Davenport algorithm developed in the late seventies. Its basic idea is to minimize the least-squares differences between attitudes gyro- propagated over the course of a maneuver and those determined using post- maneuver sensor measurements. The paper represents the scheme in a recursive form by combining necessary partials into a rectangular matrix, which is propagated in exactly the same way as a Kalman filters square transition matrix. The nontrivial structure of the propagation matrix arises from the fact that attitude errors are not included in the state vector, and therefore their derivatives with respect to estimated a parameters do not appear in the transition matrix gyro defined in the conventional way. In cases when the required accuracy can be achieved by a single iteration, representation of the Davenport gyro calibration scheme in a recursive form allows one to discard each gyro measurement immediately after it was used to propagate the attitude and state transition matrix. Another advantage of the new approach is that it utilizes the same expression for the error sensitivity matrix as that used by the Kalman filter. As a result the suggested modification of the Davenport algorithm made it possible to reuse software modules implemented in the Kalman filter estimator, where both attitude errors and gyro calibration parameters are included in the state vector. The new approach has been implemented in the ground calibration utilities used to support the Tropical Rainfall Measuring Mission (TRMM). The paper analyzes some preliminary results of gyro calibration performed by the TRMM ground attitude support team. It is demonstrated that an effect of the second iteration on estimated values of calibration parameters is negligibly small, and therefore there is no need to store processed gyro data. This opens a promising opportunity for onboard implementation of the suggested recursive procedure by combining, it with the Kalman filter used to obtain necessary attitude solutions at the beginning and end of each maneuver.

Application of the dynamic calibration method to international monitoring system stations in Central Asia using natural seismicity data

NASA Astrophysics Data System (ADS)

Kedrov, O. K.; Kedrov, E. O.; Sergeyeva, N. A.; Zabarinskaya, L. P.; Gordon, V. R.

2008-05-01

The dynamic calibration method (DCM), using natural seismicity data and initially elaborated in [Kedrov, 2001; Kedrov et al., 2001; Kedrov and Kedrov, 2003], is applied to International Monitoring System (IMS) stations in Central Asia. The algorithm of the method is refined and a program is designed for calibrating diagnostic parameters (discriminants) that characterize a seismic source on the source-station traces. The DCM calibration of stations in relation to the region under study is performed by the choice of attenuation coefficients that adapt the diagnostic parameters to the conditions in a reference region. In this method, the stable Eurasia region is used as the latter. The calibration used numerical data samples taken from the archive of the International Data Centre (IDC) for the IMS stations MKAR, BVAR, EIL, ASF, and CMAR. In this paper, we used discriminants in the spectral and time domains that have the form D_i = X_i - a_m m_b - b_Δ log Δ and are independent of the magnitude m b and the epicentral distance Δ; these discriminants were elaborated in [Kedrov et al., 1990; Kedrov and Lyuke, 1999] on the basis of a method used for identification of events at regional distances in Eurasia. Prerequisites of the DCM are the assumptions that the coefficient a m is regionindependent and the coefficient b Δ depends only on the geotectonic characteristics of the medium and does not depend on the source type. Thus, b Δ can be evaluated only from a sample of earthquakes in the region studied; it is used for adapting the discriminants D( X i ) in the region studied to the reference region. The algorithm is constructed in such a way that corrected values of D( X i) are calculated from the found values of the calibration coefficients b Δ, after which natural events in the region under study are selected by filtering. Empirical estimates of the filtering efficiency as a function of a station vary in a range of 95 100%. The DCM was independently tested using records obtained at the IRIS (Incorporated Research Institutions for Seismology) stations BRVK and MAKZ from explosions detonated in India on May 11, 1998, and Pakistan on May 28, 1998; these stations are similar in location and recording instrumentation characteristics to the IMS stations BVAR and MKAR. This test resulted in correct recognition of the source type and thereby directly confirmed the validity of the proposed calibration method of stations with the use of natural seismicity data. It is shown that the calibration coefficients b Δ for traces similar in the conditions of signal propagation (e.g., the traces from Iran to the stations EIL and ASF) are comparable for nearly all diagnostic parameters. We arrive at the conclusion that the method of dynamic calibration of stations using natural seismicity data in a region where no explosions were detonated can be significant for a rapid and inexpensive calibration of IMS stations. The DCM can also be used for recognition of industrial chemical explosions that are sometimes erroneously classified in regional catalogs as earthquakes.

Optimization of Modeled Land-Atmosphere Exchanges of Water and Energy in an Isotopically-Enabled Land Surface Model by Bayesian Parameter Calibration

NASA Astrophysics Data System (ADS)

Wong, T. E.; Noone, D. C.; Kleiber, W.

2014-12-01

The single largest uncertainty in climate model energy balance is the surface latent heating over tropical land. Furthermore, the partitioning of the total latent heat flux into contributions from surface evaporation and plant transpiration is of great importance, but notoriously poorly constrained. Resolving these issues will require better exploiting information which lies at the interface between observations and advanced modeling tools, both of which are imperfect. There are remarkably few observations which can constrain these fluxes, placing strict requirements on developing statistical methods to maximize the use of limited information to best improve models. Previous work has demonstrated the power of incorporating stable water isotopes into land surface models for further constraining ecosystem processes. We present results from a stable water isotopically-enabled land surface model (iCLM4), including model experiments partitioning the latent heat flux into contributions from plant transpiration and surface evaporation. It is shown that the partitioning results are sensitive to the parameterization of kinetic fractionation used. We discuss and demonstrate an approach to calibrating select model parameters to observational data in a Bayesian estimation framework, requiring Markov Chain Monte Carlo sampling of the posterior distribution, which is shown to constrain uncertain parameters as well as inform relevant values for operational use. Finally, we discuss the application of the estimation scheme to iCLM4, including entropy as a measure of information content and specific challenges which arise in calibration models with a large number of parameters.

Integrating satellite actual evapotranspiration patterns into distributed model parametrization and evaluation for a mesoscale catchment

NASA Astrophysics Data System (ADS)

Demirel, M. C.; Mai, J.; Stisen, S.; Mendiguren González, G.; Koch, J.; Samaniego, L. E.

2016-12-01

Distributed hydrologic models are traditionally calibrated and evaluated against observations of streamflow. Spatially distributed remote sensing observations offer a great opportunity to enhance spatial model calibration schemes. For that it is important to identify the model parameters that can change spatial patterns before the satellite based hydrologic model calibration. Our study is based on two main pillars: first we use spatial sensitivity analysis to identify the key parameters controlling the spatial distribution of actual evapotranspiration (AET). Second, we investigate the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mesoscale Hydrologic Model (mHM). This distributed model is selected as it allows for a change in the spatial distribution of key soil parameters through the calibration of pedo-transfer function parameters and includes options for using fully distributed daily Leaf Area Index (LAI) directly as input. In addition the simulated AET can be estimated at the spatial resolution suitable for comparison to the spatial patterns observed using MODIS data. We introduce a new dynamic scaling function employing remotely sensed vegetation to downscale coarse reference evapotranspiration. In total, 17 parameters of 47 mHM parameters are identified using both sequential screening and Latin hypercube one-at-a-time sampling methods. The spatial patterns are found to be sensitive to the vegetation parameters whereas streamflow dynamics are sensitive to the PTF parameters. The results of multi-objective model calibration show that calibration of mHM against observed streamflow does not reduce the spatial errors in AET while they improve only the streamflow simulations. We will further examine the results of model calibration using only multi spatial objective functions measuring the association between observed AET and simulated AET maps and another case including spatial and streamflow metrics together.

SU-E-T-491: Importance of Energy Dependent Protons Per MU Calibration Factors in IMPT Dose Calculations Using Monte Carlo Technique

DOE Office of Scientific and Technical Information (OSTI.GOV)

Randeniya, S; Mirkovic, D; Titt, U

2014-06-01

Purpose: In intensity modulated proton therapy (IMPT), energy dependent, protons per monitor unit (MU) calibration factors are important parameters that determine absolute dose values from energy deposition data obtained from Monte Carlo (MC) simulations. Purpose of this study was to assess the sensitivity of MC-computed absolute dose distributions to the protons/MU calibration factors in IMPT. Methods: A “verification plan” (i.e., treatment beams applied individually to water phantom) of a head and neck patient plan was calculated using MC technique. The patient plan had three beams; one posterior-anterior (PA); two anterior oblique. Dose prescription was 66 Gy in 30 fractions. Ofmore » the total MUs, 58% was delivered in PA beam, 25% and 17% in other two. Energy deposition data obtained from the MC simulation were converted to Gy using energy dependent protons/MU calibrations factors obtained from two methods. First method is based on experimental measurements and MC simulations. Second is based on hand calculations, based on how many ion pairs were produced per proton in the dose monitor and how many ion pairs is equal to 1 MU (vendor recommended method). Dose distributions obtained from method one was compared with those from method two. Results: Average difference of 8% in protons/MU calibration factors between method one and two converted into 27 % difference in absolute dose values for PA beam; although dose distributions preserved the shape of 3D dose distribution qualitatively, they were different quantitatively. For two oblique beams, significant difference in absolute dose was not observed. Conclusion: Results demonstrate that protons/MU calibration factors can have a significant impact on absolute dose values in IMPT depending on the fraction of MUs delivered. When number of MUs increases the effect due to the calibration factors amplify. In determining protons/MU calibration factors, experimental method should be preferred in MC dose calculations. Research supported by National Cancer Institute grant P01CA021239.« less

Energy Calibration of a Silicon-Strip Detector for Photon-Counting Spectral CT by Direct Usage of the X-ray Tube Spectrum

NASA Astrophysics Data System (ADS)

Liu, Xuejin; Chen, Han; Bornefalk, Hans; Danielsson, Mats; Karlsson, Staffan; Persson, Mats; Xu, Cheng; Huber, Ben

2015-02-01

The variation among energy thresholds in a multibin detector for photon-counting spectral CT can lead to ring artefacts in the reconstructed images. Calibration of the energy thresholds can be used to achieve homogeneous threshold settings or to develop compensation methods to reduce the artefacts. We have developed an energy-calibration method for the different comparator thresholds employed in a photon-counting silicon-strip detector. In our case, this corresponds to specifying the linear relation between the threshold positions in units of mV and the actual deposited photon energies in units of keV. This relation is determined by gain and offset values that differ for different detector channels due to variations in the manufacturing process. Typically, the calibration is accomplished by correlating the peak positions of obtained pulse-height spectra to known photon energies, e.g. with the aid of mono-energetic x rays from synchrotron radiation, radioactive isotopes or fluorescence materials. Instead of mono-energetic x rays, the calibration method presented in this paper makes use of a broad x-ray spectrum provided by commercial x-ray tubes. Gain and offset as the calibration parameters are obtained by a regression analysis that adjusts a simulated spectrum of deposited energies to a measured pulse-height spectrum. Besides the basic photon interactions such as Rayleigh scattering, Compton scattering and photo-electric absorption, the simulation takes into account the effect of pulse pileup, charge sharing and the electronic noise of the detector channels. We verify the method for different detector channels with the aid of a table-top setup, where we find the uncertainty of the keV-value of a calibrated threshold to be between 0.1 and 0.2 keV.

The effects of numerical-model complexity and observation type on estimated porosity values

USGS Publications Warehouse

Starn, Jeffrey; Bagtzoglou, Amvrossios C.; Green, Christopher T.

2015-01-01

The relative merits of model complexity and types of observations employed in model calibration are compared. An existing groundwater flow model coupled with an advective transport simulation of the Salt Lake Valley, Utah (USA), is adapted for advective transport, and effective porosity is adjusted until simulated tritium concentrations match concentrations in samples from wells. Two calibration approaches are used: a “complex” highly parameterized porosity field and a “simple” parsimonious model of porosity distribution. The use of an atmospheric tracer (tritium in this case) and apparent ages (from tritium/helium) in model calibration also are discussed. Of the models tested, the complex model (with tritium concentrations and tritium/helium apparent ages) performs best. Although tritium breakthrough curves simulated by complex and simple models are very generally similar, and there is value in the simple model, the complex model is supported by a more realistic porosity distribution and a greater number of estimable parameters. Culling the best quality data did not lead to better calibration, possibly because of processes and aquifer characteristics that are not simulated. Despite many factors that contribute to shortcomings of both the models and the data, useful information is obtained from all the models evaluated. Although any particular prediction of tritium breakthrough may have large errors, overall, the models mimic observed trends.

Lamp mapping technique for independent determination of the water vapor mixing ratio calibration factor for a Raman lidar system

NASA Astrophysics Data System (ADS)

Venable, Demetrius D.; Whiteman, David N.; Calhoun, Monique N.; Dirisu, Afusat O.; Connell, Rasheen M.; Landulfo, Eduardo

2011-08-01

We have investigated a technique that allows for the independent determination of the water vapor mixing ratio calibration factor for a Raman lidar system. This technique utilizes a procedure whereby a light source of known spectral characteristics is scanned across the aperture of the lidar system's telescope and the overall optical efficiency of the system is determined. Direct analysis of the temperature-dependent differential scattering cross sections for vibration and vibration-rotation transitions (convolved with narrowband filters) along with the measured efficiency of the system, leads to a theoretical determination of the water vapor mixing ratio calibration factor. A calibration factor was also obtained experimentally from lidar measurements and radiosonde data. A comparison of the theoretical and experimentally determined values agrees within 5%. We report on the sensitivity of the water vapor mixing ratio calibration factor to uncertainties in parameters that characterize the narrowband transmission filters, the temperature-dependent differential scattering cross section, and the variability of the system efficiency ratios as the lamp is scanned across the aperture of the telescope used in the Howard University Raman Lidar system.

Multiple calibrator measurements improve accuracy and stability estimates of automated assays.

PubMed

Akbas, Neval; Budd, Jeffrey R; Klee, George G

2016-01-01

The effects of combining multiple calibrations on assay accuracy (bias) and measurement of calibration stability were investigated for total triiodothyronine (TT3), vitamin B12 and luteinizing hormone (LH) using Beckman Coulter's Access 2 analyzer. Three calibration procedures (CC1, CC2 and CC3) combined 12, 34 and 56 calibrator measurements over 1, 2, and 3 days. Bias was calculated between target values and average measured value over 3 consecutive days after calibration. Using regression analysis of calibrator measurements versus measurement date, calibration stability was determined as the maximum number of days before a calibrator measurement exceeded 5% tolerance limits. Competitive assays (TT3, vitamin B12) had positive time regression slopes, while sandwich assay (LH) had a negative slope. Bias values for TT3 were -2.49%, 1.49%, and -0.50% using CC1, CC2 and CC3 respectively, with calibrator stability of 32, 20, and 30 days. Bias values for vitamin B12 were 2.44%, 0.91%, and -0.50%, with calibrator stability of 4, 9, and 12 days. Bias values for LH were 2.26%, 1.44% and -0.29% with calibrator stability of >43, 39 and 36 days. Measured stability was more consistent across calibration procedures using percent change rather than difference from target: 26 days for TT3, 12 days for B12 and 31 days for LH. Averaging over multiple calibrations produced smaller bias, consistent with improved accuracy. Time regression slopes in percent change were unaffected by number of calibration measurements but calibrator stability measured from the target value was highly affected by the calibrator value at time zero.

Stability of Gradient Field Corrections for Quantitative Diffusion MRI.

PubMed

Rogers, Baxter P; Blaber, Justin; Welch, E Brian; Ding, Zhaohua; Anderson, Adam W; Landman, Bennett A

2017-02-11

In magnetic resonance diffusion imaging, gradient nonlinearity causes significant bias in the estimation of quantitative diffusion parameters such as diffusivity, anisotropy, and diffusion direction in areas away from the magnet isocenter. This bias can be substantially reduced if the scanner- and coil-specific gradient field nonlinearities are known. Using a set of field map calibration scans on a large (29 cm diameter) phantom combined with a solid harmonic approximation of the gradient fields, we predicted the obtained b-values and applied gradient directions throughout a typical field of view for brain imaging for a typical 32-direction diffusion imaging sequence. We measured the stability of these predictions over time. At 80 mm from scanner isocenter, predicted b-value was 1-6% different than intended due to gradient nonlinearity, and predicted gradient directions were in error by up to 1 degree. Over the course of one month the change in these quantities due to calibration-related factors such as scanner drift and variation in phantom placement was <0.5% for b-values, and <0.5 degrees for angular deviation. The proposed calibration procedure allows the estimation of gradient nonlinearity to correct b-values and gradient directions ahead of advanced diffusion image processing for high angular resolution data, and requires only a five-minute phantom scan that can be included in a weekly or monthly quality assurance protocol.

Calibration of the ARID robot

NASA Technical Reports Server (NTRS)

Doty, Keith L

1992-01-01

The author has formulated a new, general model for specifying the kinematic properties of serial manipulators. The new model kinematic parameters do not suffer discontinuities when nominally parallel adjacent axes deviate from exact parallelism. From this new theory the author develops a first-order, lumped-parameter, calibration-model for the ARID manipulator. Next, the author develops a calibration methodology for the ARID based on visual and acoustic sensing. A sensor platform, consisting of a camera and four sonars attached to the ARID end frame, performs calibration measurements. A calibration measurement consists of processing one visual frame of an accurately placed calibration image and recording four acoustic range measurements. A minimum of two measurement protocols determine the kinematics calibration-model of the ARID for a particular region: assuming the joint displacements are accurately measured, the calibration surface is planar, and the kinematic parameters do not vary rapidly in the region. No theoretical or practical limitations appear to contra-indicate the feasibility of the calibration method developed here.

Management of groundwater in-situ bioremediation system using reactive transport modelling under parametric uncertainty: field scale application

NASA Astrophysics Data System (ADS)

Verardo, E.; Atteia, O.; Rouvreau, L.

2015-12-01

In-situ bioremediation is a commonly used remediation technology to clean up the subsurface of petroleum-contaminated sites. Forecasting remedial performance (in terms of flux and mass reduction) is a challenge due to uncertainties associated with source properties and the uncertainties associated with contribution and efficiency of concentration reducing mechanisms. In this study, predictive uncertainty analysis of bio-remediation system efficiency is carried out with the null-space Monte Carlo (NSMC) method which combines the calibration solution-space parameters with the ensemble of null-space parameters, creating sets of calibration-constrained parameters for input to follow-on remedial efficiency. The first step in the NSMC methodology for uncertainty analysis is model calibration. The model calibration was conducted by matching simulated BTEX concentration to a total of 48 observations from historical data before implementation of treatment. Two different bio-remediation designs were then implemented in the calibrated model. The first consists in pumping/injection wells and the second in permeable barrier coupled with infiltration across slotted piping. The NSMC method was used to calculate 1000 calibration-constrained parameter sets for the two different models. Several variants of the method were implemented to investigate their effect on the efficiency of the NSMC method. The first variant implementation of the NSMC is based on a single calibrated model. In the second variant, models were calibrated from different initial parameter sets. NSMC calibration-constrained parameter sets were sampled from these different calibrated models. We demonstrate that in context of nonlinear model, second variant avoids to underestimate parameter uncertainty which may lead to a poor quantification of predictive uncertainty. Application of the proposed approach to manage bioremediation of groundwater in a real site shows that it is effective to provide support in management of the in-situ bioremediation systems. Moreover, this study demonstrates that the NSMC method provides a computationally efficient and practical methodology of utilizing model predictive uncertainty methods in environmental management.

Determination and correction of persistent biases in quantum annealers

PubMed Central

Perdomo-Ortiz, Alejandro; O’Gorman, Bryan; Fluegemann, Joseph; Biswas, Rupak; Smelyanskiy, Vadim N.

2016-01-01

Calibration of quantum computers is essential to the effective utilisation of their quantum resources. Specifically, the performance of quantum annealers is likely to be significantly impaired by noise in their programmable parameters, effectively misspecification of the computational problem to be solved, often resulting in spurious suboptimal solutions. We developed a strategy to determine and correct persistent, systematic biases between the actual values of the programmable parameters and their user-specified values. We applied the recalibration strategy to two D-Wave Two quantum annealers, one at NASA Ames Research Center in Moffett Field, California, and another at D-Wave Systems in Burnaby, Canada. We show that the recalibration procedure not only reduces the magnitudes of the biases in the programmable parameters but also enhances the performance of the device on a set of random benchmark instances. PMID:26783120

Automatic Calibration of a Semi-Distributed Hydrologic Model Using Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Bekele, E. G.; Nicklow, J. W.

2005-12-01

Hydrologic simulation models need to be calibrated and validated before using them for operational predictions. Spatially-distributed hydrologic models generally have a large number of parameters to capture the various physical characteristics of a hydrologic system. Manual calibration of such models is a very tedious and daunting task, and its success depends on the subjective assessment of a particular modeler, which includes knowledge of the basic approaches and interactions in the model. In order to alleviate these shortcomings, an automatic calibration model, which employs an evolutionary optimization technique known as Particle Swarm Optimizer (PSO) for parameter estimation, is developed. PSO is a heuristic search algorithm that is inspired by social behavior of bird flocking or fish schooling. The newly-developed calibration model is integrated to the U.S. Department of Agriculture's Soil and Water Assessment Tool (SWAT). SWAT is a physically-based, semi-distributed hydrologic model that was developed to predict the long term impacts of land management practices on water, sediment and agricultural chemical yields in large complex watersheds with varying soils, land use, and management conditions. SWAT was calibrated for streamflow and sediment concentration. The calibration process involves parameter specification, whereby sensitive model parameters are identified, and parameter estimation. In order to reduce the number of parameters to be calibrated, parameterization was performed. The methodology is applied to a demonstration watershed known as Big Creek, which is located in southern Illinois. Application results show the effectiveness of the approach and model predictions are significantly improved.

Stand level height-diameter mixed effects models: parameters fitted using loblolly pine but calibrated for sweetgum

Treesearch

Curtis L. Vanderschaaf

2008-01-01

Mixed effects models can be used to obtain site-specific parameters through the use of model calibration that often produces better predictions of independent data. This study examined whether parameters of a mixed effect height-diameter model estimated using loblolly pine plantation data but calibrated using sweetgum plantation data would produce reasonable...

Improvement of Gaofen-3 Absolute Positioning Accuracy Based on Cross-Calibration

PubMed Central

Deng, Mingjun; Li, Jiansong

2017-01-01

The Chinese Gaofen-3 (GF-3) mission was launched in August 2016, equipped with a full polarimetric synthetic aperture radar (SAR) sensor in the C-band, with a resolution of up to 1 m. The absolute positioning accuracy of GF-3 is of great importance, and in-orbit geometric calibration is a key technology for improving absolute positioning accuracy. Conventional geometric calibration is used to accurately calibrate the geometric calibration parameters of the image (internal delay and azimuth shifts) using high-precision ground control data, which are highly dependent on the control data of the calibration field, but it remains costly and labor-intensive to monitor changes in GF-3’s geometric calibration parameters. Based on the positioning consistency constraint of the conjugate points, this study presents a geometric cross-calibration method for the rapid and accurate calibration of GF-3. The proposed method can accurately calibrate geometric calibration parameters without using corner reflectors and high-precision digital elevation models, thus improving absolute positioning accuracy of the GF-3 image. GF-3 images from multiple regions were collected to verify the absolute positioning accuracy after cross-calibration. The results show that this method can achieve a calibration accuracy as high as that achieved by the conventional field calibration method. PMID:29240675

Metallicity determination of M dwarfs. Expanded parameter range in metallicity and effective temperature

NASA Astrophysics Data System (ADS)

Lindgren, Sara; Heiter, Ulrike

2017-08-01

Context. Reliable metallicity values for late K and M dwarfs are important for studies of the chemical evolution of the Galaxy and advancement of planet formation theory in low-mass environments. Historically it has been challenging to determine the stellar parameters of low-mass stars because of their low surface temperature, which causes several molecules to form in the photospheric layers. In our work we use the fact that infrared high-resolution spectrographs have opened up a new window for investigating M dwarfs. This enables us to use similar methods as for warmer solar-like stars. Aims: Metallicity determination with high-resolution spectra is more accurate than with low-resolution spectra, but it is rather time consuming. In this paper we expand our sample analyzed with this precise method both in metallicity and effective temperature to build a calibration sample for a future revised empirical calibration. Methods: Because of the relatively few molecular lines in the J band, continuum rectification is possible for high-resolution spectra, allowing the stellar parameters to be determined with greater accuracy than with optical spectra. We obtained high-resolution spectra with the CRIRES spectrograph at the Very Large Telescope (VLT). The metallicity was determined using synthetic spectral fitting of several atomic species. For M dwarfs that are cooler than 3575 K, the line strengths of FeH lines were used to determine the effective temperatures, while for warmer stars a photometric calibration was used. Results: We analyzed 16 targets with a range of effective temperature from 3350-4550 K. The resulting metallicities lie between -0.5< [M/H] < +0.4. A few targets have previously been analyzed using low-resolution spectra and we find a rather good agreement with our values. A comparison with available photometric calibrations shows varying agreement and the spread within all empirical calibrations is large. Conclusions: Including the targets from our previous paper, we analyzed 28 M dwarfs with high-resolution infrared spectra. The targets spread approximately one dex in metallicity and 1400 K in effective temperature. For individual M dwarfs we achieve uncertainties of 0.05 dex and 100 K on average. Based on data obtained at ESO-VLT, Paranal Observatory, Chile, Program ID 090.D-0796(A).

Efficient Reduction and Analysis of Model Predictive Error

NASA Astrophysics Data System (ADS)

Doherty, J.

2006-12-01

Most groundwater models are calibrated against historical measurements of head and other system states before being used to make predictions in a real-world context. Through the calibration process, parameter values are estimated or refined such that the model is able to reproduce historical behaviour of the system at pertinent observation points reasonably well. Predictions made by the model are deemed to have greater integrity because of this. Unfortunately, predictive integrity is not as easy to achieve as many groundwater practitioners would like to think. The level of parameterisation detail estimable through the calibration process (especially where estimation takes place on the basis of heads alone) is strictly limited, even where full use is made of modern mathematical regularisation techniques such as those encapsulated in the PEST calibration package. (Use of these mechanisms allows more information to be extracted from a calibration dataset than is possible using simpler regularisation devices such as zones of piecewise constancy.) Where a prediction depends on aspects of parameterisation detail that are simply not inferable through the calibration process (which is often the case for predictions related to contaminant movement, and/or many aspects of groundwater/surface water interaction), then that prediction may be just as much in error as it would have been if the model had not been calibrated at all. Model predictive error arises from two sources. These are (a) the presence of measurement noise within the calibration dataset through which linear combinations of parameters spanning the "calibration solution space" are inferred, and (b) the sensitivity of the prediction to members of the "calibration null space" spanned by linear combinations of parameters which are not inferable through the calibration process. The magnitude of the former contribution depends on the level of measurement noise. The magnitude of the latter contribution (which often dominates the former) depends on the "innate variability" of hydraulic properties within the model domain. Knowledge of both of these is a prerequisite for characterisation of the magnitude of possible model predictive error. Unfortunately, in most cases, such knowledge is incomplete and subjective. Nevertheless, useful analysis of model predictive error can still take place. The present paper briefly discusses the means by which mathematical regularisation can be employed in the model calibration process in order to extract as much information as possible on hydraulic property heterogeneity prevailing within the model domain, thereby reducing predictive error to the lowest that can be achieved on the basis of that dataset. It then demonstrates the means by which predictive error variance can be quantified based on information supplied by the regularised inversion process. Both linear and nonlinear predictive error variance analysis is demonstrated using a number of real-world and synthetic examples.

Perceptual Calibration for Immersive Display Environments

PubMed Central

Ponto, Kevin; Gleicher, Michael; Radwin, Robert G.; Shin, Hyun Joon

2013-01-01

The perception of objects, depth, and distance has been repeatedly shown to be divergent between virtual and physical environments. We hypothesize that many of these discrepancies stem from incorrect geometric viewing parameters, specifically that physical measurements of eye position are insufficiently precise to provide proper viewing parameters. In this paper, we introduce a perceptual calibration procedure derived from geometric models. While most research has used geometric models to predict perceptual errors, we instead use these models inversely to determine perceptually correct viewing parameters. We study the advantages of these new psychophysically determined viewing parameters compared to the commonly used measured viewing parameters in an experiment with 20 subjects. The perceptually calibrated viewing parameters for the subjects generally produced new virtual eye positions that were wider and deeper than standard practices would estimate. Our study shows that perceptually calibrated viewing parameters can significantly improve depth acuity, distance estimation, and the perception of shape. PMID:23428454

A multi-objective approach to improve SWAT model calibration in alpine catchments

NASA Astrophysics Data System (ADS)

Tuo, Ye; Marcolini, Giorgia; Disse, Markus; Chiogna, Gabriele

2018-04-01

Multi-objective hydrological model calibration can represent a valuable solution to reduce model equifinality and parameter uncertainty. The Soil and Water Assessment Tool (SWAT) model is widely applied to investigate water quality and water management issues in alpine catchments. However, the model calibration is generally based on discharge records only, and most of the previous studies have defined a unique set of snow parameters for an entire basin. Only a few studies have considered snow observations to validate model results or have taken into account the possible variability of snow parameters for different subbasins. This work presents and compares three possible calibration approaches. The first two procedures are single-objective calibration procedures, for which all parameters of the SWAT model were calibrated according to river discharge alone. Procedures I and II differ from each other by the assumption used to define snow parameters: The first approach assigned a unique set of snow parameters to the entire basin, whereas the second approach assigned different subbasin-specific sets of snow parameters to each subbasin. The third procedure is a multi-objective calibration, in which we considered snow water equivalent (SWE) information at two different spatial scales (i.e. subbasin and elevation band), in addition to discharge measurements. We tested these approaches in the Upper Adige river basin where a dense network of snow depth measurement stations is available. Only the set of parameters obtained with this multi-objective procedure provided an acceptable prediction of both river discharge and SWE. These findings offer the large community of SWAT users a strategy to improve SWAT modeling in alpine catchments.

Model calibration and issues related to validation, sensitivity analysis, post-audit, uncertainty evaluation and assessment of prediction data needs

USGS Publications Warehouse

Tiedeman, Claire; Hill, Mary C.

2007-01-01

When simulating natural and engineered groundwater flow and transport systems, one objective is to produce a model that accurately represents important aspects of the true system. However, using direct measurements of system characteristics, such as hydraulic conductivity, to construct a model often produces simulated values that poorly match observations of the system state, such as hydraulic heads, flows and concentrations (for example, Barth et al., 2001). This occurs because of inaccuracies in the direct measurements and because the measurements commonly characterize system properties at different scales from that of the model aspect to which they are applied. In these circumstances, the conservation of mass equations represented by flow and transport models can be used to test the applicability of the direct measurements, such as by comparing model simulated values to the system state observations. This comparison leads to calibrating the model, by adjusting the model construction and the system properties as represented by model parameter values, so that the model produces simulated values that reasonably match the observations.

Parameter estimation uncertainty: Comparing apples and apples?

NASA Astrophysics Data System (ADS)

Hart, D.; Yoon, H.; McKenna, S. A.

2012-12-01

Given a highly parameterized ground water model in which the conceptual model of the heterogeneity is stochastic, an ensemble of inverse calibrations from multiple starting points (MSP) provides an ensemble of calibrated parameters and follow-on transport predictions. However, the multiple calibrations are computationally expensive. Parameter estimation uncertainty can also be modeled by decomposing the parameterization into a solution space and a null space. From a single calibration (single starting point) a single set of parameters defining the solution space can be extracted. The solution space is held constant while Monte Carlo sampling of the parameter set covering the null space creates an ensemble of the null space parameter set. A recently developed null-space Monte Carlo (NSMC) method combines the calibration solution space parameters with the ensemble of null space parameters, creating sets of calibration-constrained parameters for input to the follow-on transport predictions. Here, we examine the consistency between probabilistic ensembles of parameter estimates and predictions using the MSP calibration and the NSMC approaches. A highly parameterized model of the Culebra dolomite previously developed for the WIPP project in New Mexico is used as the test case. A total of 100 estimated fields are retained from the MSP approach and the ensemble of results defining the model fit to the data, the reproduction of the variogram model and prediction of an advective travel time are compared to the same results obtained using NSMC. We demonstrate that the NSMC fields based on a single calibration model can be significantly constrained by the calibrated solution space and the resulting distribution of advective travel times is biased toward the travel time from the single calibrated field. To overcome this, newly proposed strategies to employ a multiple calibration-constrained NSMC approach (M-NSMC) are evaluated. Comparison of the M-NSMC and MSP methods suggests that M-NSMC can provide a computationally efficient and practical solution for predictive uncertainty analysis in highly nonlinear and complex subsurface flow and transport models. This material is based upon work supported as part of the Center for Frontiers of Subsurface Energy Security, an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences under Award Number DE-SC0001114. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

SU-D-304-06: Measurement of LET in Patient-Specific Proton Therapy Treatment Fields Using Optically Stimulated Luminescence Detectors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Granville, DA; Sahoo, N; Sawakuchi, GO

Purpose: To investigate the use of optically stimulated luminescence (OSL) detectors (OSLDs) for measurements of dose-averaged linear energy transfer (LET) in patient-specific proton therapy treatment fields. Methods: We used Al{sub 2}O{sub 3}:C OSLDs made from the same material as commercially available nanoDot OSLDs from Landauer, Inc. We calibrated two parameters of the OSL signal as functions of LET in therapeutic proton beams: the ratio of the ultraviolet and blue emission intensities (UV/blue ratio) and the OSL curve shape. These calibration curves were created by irradiating OSLDs in passively scattered beams of known LET (0.96 to 3.91 keV/µm). The LET valuesmore » were determined using a validated Monte Carlo model of the beamline. We then irradiated new OSLDs with the prescription dose (16 to 74 cGy absorbed dose to water) at the center of the spread-out Bragg peak (SOBP) of four patient-specific treatment fields. From readouts of these OSLDs, we determined both the UV/blue ratio and OSL curve shape parameters. Combining these parameters with the calibration curves, we were able to measure LET using the OSLDs. The measurements were compared to the theoretical LET values obtained from Monte Carlo simulations of the patient-specific treatments fields. Results: Using the UV/blue ratio parameter, we were able to measure LET within 3.8%, 6.2%, 5.6% and 8.6% of the Monte Carlo value for each of the patient fields. Similarly, using the OSL curve shape parameter, LET measurements agreed within 0.5%, 11.0%, 2.5% and 7.6% for each of the four fields. Conclusion: We have demonstrated a method to verify LET in patient-specific proton therapy treatment fields using OSLDs. The possibility of enhancing biological effectiveness of proton therapy treatment plans by including LET in the optimization has been previously shown. The LET verification method we have demonstrated will be useful in the quality assurance of such LET optimized treatment plans. DA Granville received financial support from the Natural Sciences and Engineering Research Council of Canada.« less

Estimation of future flow regime for a spatially varied Himalayan watershed using improved multi-site calibration method of SWAT model.

NASA Astrophysics Data System (ADS)

Pradhanang, S. M.; Hasan, M. A.; Booth, P.; Fallatah, O.

2016-12-01

The monsoon and snow driven regime in the Himalayan region has received increasing attention in the recent decade regarding the effects of climate change on hydrologic regimes. Modeling streamflow in such spatially varied catchment requires proper calibration and validation in hydrologic modeling. While calibration and validation are time consuming and computationally intensive, an effective regionalized approach with multi-site information is crucial for flow estimation, especially in daily scale. In this study, we adopted a multi-site approach to calibration and validation of the Soil Water Assessment Tool (SWAT) model for the Karnali river catchment, which is characterized as being the most vulnerable catchment to climate change in the Himalayan region. APHRODITE's (Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation) daily gridded precipitation data, one of the accurate and reliable weather date over this region were utilized in this study. The model evaluation of the entire catchment divided into four sub-catchments, utilizing discharge records from 1963 to 2010. In previous studies, multi-site calibration used only a single set of calibration parameters for all sub-catchment of a large watershed. In this study, we introduced a technique that can incorporate different sets of calibration parameters for each sub-basin, which eventually ameliorate the flow of the whole watershed. Results show that the calibrated model with new method can capture almost identical pattern of flow over the region. The predicted daily streamflow matched the observed values, with a Nash-Sutcliffe coefficient of 0.73 during calibration and 0.71 during validation period. The method perfumed better than existing multi-site calibration methods. To assess the influence of continued climate change on hydrologic processes, we modified the weather inputs for the model using precipitation and temperature changes for two Representative Concentration Pathways (RCPs) scenarios, RCP 4.5 and 8.5. Climate simulation for RCP scenarios were conducted from 1981-2100, where 1981-2005 was considered as baseline and 2006-2100 was considered as the future projection. The result shows that probability of flooding will eventually increase in future years due to increased flow in both scenarios.

A novel dual-camera calibration method for 3D optical measurement

NASA Astrophysics Data System (ADS)

Gai, Shaoyan; Da, Feipeng; Dai, Xianqiang

2018-05-01

A novel dual-camera calibration method is presented. In the classic methods, the camera parameters are usually calculated and optimized by the reprojection error. However, for a system designed for 3D optical measurement, this error does not denote the result of 3D reconstruction. In the presented method, a planar calibration plate is used. In the beginning, images of calibration plate are snapped from several orientations in the measurement range. The initial parameters of the two cameras are obtained by the images. Then, the rotation and translation matrix that link the frames of two cameras are calculated by using method of Centroid Distance Increment Matrix. The degree of coupling between the parameters is reduced. Then, 3D coordinates of the calibration points are reconstructed by space intersection method. At last, the reconstruction error is calculated. It is minimized to optimize the calibration parameters. This error directly indicates the efficiency of 3D reconstruction, thus it is more suitable for assessing the quality of dual-camera calibration. In the experiments, it can be seen that the proposed method is convenient and accurate. There is no strict requirement on the calibration plate position in the calibration process. The accuracy is improved significantly by the proposed method.

Calibration of Predictor Models Using Multiple Validation Experiments

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Kenny, Sean P.; Giesy, Daniel P.

2015-01-01

This paper presents a framework for calibrating computational models using data from several and possibly dissimilar validation experiments. The offset between model predictions and observations, which might be caused by measurement noise, model-form uncertainty, and numerical error, drives the process by which uncertainty in the models parameters is characterized. The resulting description of uncertainty along with the computational model constitute a predictor model. Two types of predictor models are studied: Interval Predictor Models (IPMs) and Random Predictor Models (RPMs). IPMs use sets to characterize uncertainty, whereas RPMs use random vectors. The propagation of a set through a model makes the response an interval valued function of the state, whereas the propagation of a random vector yields a random process. Optimization-based strategies for calculating both types of predictor models are proposed. Whereas the formulations used to calculate IPMs target solutions leading to the interval value function of minimal spread containing all observations, those for RPMs seek to maximize the models' ability to reproduce the distribution of observations. Regarding RPMs, we choose a structure for the random vector (i.e., the assignment of probability to points in the parameter space) solely dependent on the prediction error. As such, the probabilistic description of uncertainty is not a subjective assignment of belief, nor is it expected to asymptotically converge to a fixed value, but instead it casts the model's ability to reproduce the experimental data. This framework enables evaluating the spread and distribution of the predicted response of target applications depending on the same parameters beyond the validation domain.

Calibration of an agricultural-hydrological model (RZWQM2) using surrogate global optimization

DOE PAGES

Xi, Maolong; Lu, Dan; Gui, Dongwei; ...

2016-11-27

Robust calibration of an agricultural-hydrological model is critical for simulating crop yield and water quality and making reasonable agricultural management. However, calibration of the agricultural-hydrological system models is challenging because of model complexity, the existence of strong parameter correlation, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near-optimal solution within an affordable time, which greatly restricts the successful application of the model. The goal of this study is to locate the optimal solution of the Root Zone Water Quality Model (RZWQM2) given a limited simulation time, so asmore » to improve the model simulation and help make rational and effective agricultural-hydrological decisions. To this end, we propose a computationally efficient global optimization procedure using sparse-grid based surrogates. We first used advanced sparse grid (SG) interpolation to construct a surrogate system of the actual RZWQM2, and then we calibrate the surrogate model using the global optimization algorithm, Quantum-behaved Particle Swarm Optimization (QPSO). As the surrogate model is a polynomial with fast evaluation, it can be efficiently evaluated with a sufficiently large number of times during the optimization, which facilitates the global search. We calibrate seven model parameters against five years of yield, drain flow, and NO 3-N loss data from a subsurface-drained corn-soybean field in Iowa. Results indicate that an accurate surrogate model can be created for the RZWQM2 with a relatively small number of SG points (i.e., RZWQM2 runs). Compared to the conventional QPSO algorithm, our surrogate-based optimization method can achieve a smaller objective function value and better calibration performance using a fewer number of expensive RZWQM2 executions, which greatly improves computational efficiency.« less

Calibration of an agricultural-hydrological model (RZWQM2) using surrogate global optimization

NASA Astrophysics Data System (ADS)

Xi, Maolong; Lu, Dan; Gui, Dongwei; Qi, Zhiming; Zhang, Guannan

2017-01-01

Robust calibration of an agricultural-hydrological model is critical for simulating crop yield and water quality and making reasonable agricultural management. However, calibration of the agricultural-hydrological system models is challenging because of model complexity, the existence of strong parameter correlation, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near-optimal solution within an affordable time, which greatly restricts the successful application of the model. The goal of this study is to locate the optimal solution of the Root Zone Water Quality Model (RZWQM2) given a limited simulation time, so as to improve the model simulation and help make rational and effective agricultural-hydrological decisions. To this end, we propose a computationally efficient global optimization procedure using sparse-grid based surrogates. We first used advanced sparse grid (SG) interpolation to construct a surrogate system of the actual RZWQM2, and then we calibrate the surrogate model using the global optimization algorithm, Quantum-behaved Particle Swarm Optimization (QPSO). As the surrogate model is a polynomial with fast evaluation, it can be efficiently evaluated with a sufficiently large number of times during the optimization, which facilitates the global search. We calibrate seven model parameters against five years of yield, drain flow, and NO3-N loss data from a subsurface-drained corn-soybean field in Iowa. Results indicate that an accurate surrogate model can be created for the RZWQM2 with a relatively small number of SG points (i.e., RZWQM2 runs). Compared to the conventional QPSO algorithm, our surrogate-based optimization method can achieve a smaller objective function value and better calibration performance using a fewer number of expensive RZWQM2 executions, which greatly improves computational efficiency.

Calibration of an agricultural-hydrological model (RZWQM2) using surrogate global optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xi, Maolong; Lu, Dan; Gui, Dongwei

Robust calibration of an agricultural-hydrological model is critical for simulating crop yield and water quality and making reasonable agricultural management. However, calibration of the agricultural-hydrological system models is challenging because of model complexity, the existence of strong parameter correlation, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near-optimal solution within an affordable time, which greatly restricts the successful application of the model. The goal of this study is to locate the optimal solution of the Root Zone Water Quality Model (RZWQM2) given a limited simulation time, so asmore » to improve the model simulation and help make rational and effective agricultural-hydrological decisions. To this end, we propose a computationally efficient global optimization procedure using sparse-grid based surrogates. We first used advanced sparse grid (SG) interpolation to construct a surrogate system of the actual RZWQM2, and then we calibrate the surrogate model using the global optimization algorithm, Quantum-behaved Particle Swarm Optimization (QPSO). As the surrogate model is a polynomial with fast evaluation, it can be efficiently evaluated with a sufficiently large number of times during the optimization, which facilitates the global search. We calibrate seven model parameters against five years of yield, drain flow, and NO 3-N loss data from a subsurface-drained corn-soybean field in Iowa. Results indicate that an accurate surrogate model can be created for the RZWQM2 with a relatively small number of SG points (i.e., RZWQM2 runs). Compared to the conventional QPSO algorithm, our surrogate-based optimization method can achieve a smaller objective function value and better calibration performance using a fewer number of expensive RZWQM2 executions, which greatly improves computational efficiency.« less

Quantitative Rheological Model Selection

NASA Astrophysics Data System (ADS)

Freund, Jonathan; Ewoldt, Randy

2014-11-01

The more parameters in a rheological the better it will reproduce available data, though this does not mean that it is necessarily a better justified model. Good fits are only part of model selection. We employ a Bayesian inference approach that quantifies model suitability by balancing closeness to data against both the number of model parameters and their a priori uncertainty. The penalty depends upon prior-to-calibration expectation of the viable range of values that model parameters might take, which we discuss as an essential aspect of the selection criterion. Models that are physically grounded are usually accompanied by tighter physical constraints on their respective parameters. The analysis reflects a basic principle: models grounded in physics can be expected to enjoy greater generality and perform better away from where they are calibrated. In contrast, purely empirical models can provide comparable fits, but the model selection framework penalizes their a priori uncertainty. We demonstrate the approach by selecting the best-justified number of modes in a Multi-mode Maxwell description of PVA-Borax. We also quantify relative merits of the Maxwell model relative to powerlaw fits and purely empirical fits for PVA-Borax, a viscoelastic liquid, and gluten.

On-orbit calibration for star sensors without priori information.

PubMed

Zhang, Hao; Niu, Yanxiong; Lu, Jiazhen; Zhang, Chengfen; Yang, Yanqiang

2017-07-24

The star sensor is a prerequisite navigation device for a spacecraft. The on-orbit calibration is an essential guarantee for its operation performance. However, traditional calibration methods rely on ground information and are invalid without priori information. The uncertain on-orbit parameters will eventually influence the performance of guidance navigation and control system. In this paper, a novel calibration method without priori information for on-orbit star sensors is proposed. Firstly, the simplified back propagation neural network is designed for focal length and main point estimation along with system property evaluation, called coarse calibration. Then the unscented Kalman filter is adopted for the precise calibration of all parameters, including focal length, main point and distortion. The proposed method benefits from self-initialization and no attitude or preinstalled sensor parameter is required. Precise star sensor parameter estimation can be achieved without priori information, which is a significant improvement for on-orbit devices. Simulations and experiments results demonstrate that the calibration is easy for operation with high accuracy and robustness. The proposed method can satisfy the stringent requirement for most star sensors.

Establishment and correction of an Echelle cross-prism spectrogram reduction model

NASA Astrophysics Data System (ADS)

Zhang, Rui; Bayanheshig; Li, Xiaotian; Cui, Jicheng

2017-11-01

The accuracy of an echelle cross-prism spectrometer depends on the matching degree between the spectrum reduction model and the actual state of the spectrometer. However, the error of adjustment can change the actual state of the spectrometer and result in a reduction model that does not match. This produces an inaccurate wavelength calibration. Therefore, the calibration of a spectrogram reduction model is important for the analysis of any echelle cross-prism spectrometer. In this study, the spectrogram reduction model of an echelle cross-prism spectrometer was established. The image position laws of a spectrometer that varies with the system parameters were simulated to the influence of the changes in prism refractive index, focal length and so on, on the calculation results. The model was divided into different wavebands. The iterative method, least squares principle and element lamps with known characteristic wavelength were used to calibrate the spectral model in different wavebands to obtain the actual values of the system parameters. After correction, the deviation of actual x- and y-coordinates and the coordinates calculated by the model are less than one pixel. The model corrected by this method thus reflects the system parameters in the current spectrometer state and can assist in accurate wavelength extraction. The instrument installation and adjustment would be guided in model-repeated correction, reducing difficulty of equipment, respectively.

Forecasting financial asset processes: stochastic dynamics via learning neural networks.

PubMed

Giebel, S; Rainer, M

2010-01-01

Models for financial asset dynamics usually take into account their inherent unpredictable nature by including a suitable stochastic component into their process. Unknown (forward) values of financial assets (at a given time in the future) are usually estimated as expectations of the stochastic asset under a suitable risk-neutral measure. This estimation requires the stochastic model to be calibrated to some history of sufficient length in the past. Apart from inherent limitations, due to the stochastic nature of the process, the predictive power is also limited by the simplifying assumptions of the common calibration methods, such as maximum likelihood estimation and regression methods, performed often without weights on the historic time series, or with static weights only. Here we propose a novel method of "intelligent" calibration, using learning neural networks in order to dynamically adapt the parameters of the stochastic model. Hence we have a stochastic process with time dependent parameters, the dynamics of the parameters being themselves learned continuously by a neural network. The back propagation in training the previous weights is limited to a certain memory length (in the examples we consider 10 previous business days), which is similar to the maximal time lag of autoregressive processes. We demonstrate the learning efficiency of the new algorithm by tracking the next-day forecasts for the EURTRY and EUR-HUF exchange rates each.

The Rangeland Hydrology and Erosion Model: A Dynamic Approach for Predicting Soil Loss on Rangelands

NASA Astrophysics Data System (ADS)

Hernandez, Mariano; Nearing, Mark A.; Al-Hamdan, Osama Z.; Pierson, Frederick B.; Armendariz, Gerardo; Weltz, Mark A.; Spaeth, Kenneth E.; Williams, C. Jason; Nouwakpo, Sayjro K.; Goodrich, David C.; Unkrich, Carl L.; Nichols, Mary H.; Holifield Collins, Chandra D.

2017-11-01

In this study, we present the improved Rangeland Hydrology and Erosion Model (RHEM V2.3), a process-based erosion prediction tool specific for rangeland application. The article provides the mathematical formulation of the model and parameter estimation equations. Model performance is assessed against data collected from 23 runoff and sediment events in a shrub-dominated semiarid watershed in Arizona, USA. To evaluate the model, two sets of primary model parameters were determined using the RHEM V2.3 and RHEM V1.0 parameter estimation equations. Testing of the parameters indicated that RHEM V2.3 parameter estimation equations provided a 76% improvement over RHEM V1.0 parameter estimation equations. Second, the RHEM V2.3 model was calibrated to measurements from the watershed. The parameters estimated by the new equations were within the lowest and highest values of the calibrated parameter set. These results suggest that the new parameter estimation equations can be applied for this environment to predict sediment yield at the hillslope scale. Furthermore, we also applied the RHEM V2.3 to demonstrate the response of the model as a function of foliar cover and ground cover for 124 data points across Arizona and New Mexico. The dependence of average sediment yield on surface ground cover was moderately stronger than that on foliar cover. These results demonstrate that RHEM V2.3 predicts runoff volume, peak runoff, and sediment yield with sufficient accuracy for broad application to assess and manage rangeland systems.

Sensitivity of blackbody effective emissivity to wavelength and temperature: By genetic algorithm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ejigu, E. K.; Liedberg, H. G.

A variable-temperature blackbody (VTBB) is used to calibrate an infrared radiation thermometer (pyrometer). The effective emissivity (ε{sub eff}) of a VTBB is dependent on temperature and wavelength other than the geometry of the VTBB. In the calibration process the effective emissivity is often assumed to be constant within the wavelength and temperature range. There are practical situations where the sensitivity of the effective emissivity needs to be known and correction has to be applied. We present a method using a genetic algorithm to investigate the sensitivity of the effective emissivity to wavelength and temperature variation. Two matlab® programs are generated:more » the first to model the radiance temperature calculation and the second to connect the model to the genetic algorithm optimization toolbox. The effective emissivity parameter is taken as a chromosome and optimized at each wavelength and temperature point. The difference between the contact temperature (reading from a platinum resistance thermometer or liquid in glass thermometer) and radiance temperature (calculated from the ε{sub eff} values) is used as an objective function where merit values are calculated and best fit ε{sub eff} values selected. The best fit ε{sub eff} values obtained as a solution show how sensitive they are to temperature and wavelength parameter variation. Uncertainty components that arise from wavelength and temperature variation are determined based on the sensitivity analysis. Numerical examples are considered for illustration.« less

Multi-parameter Nonlinear Gain Correction of X-ray Transition Edge Sensors for the X-ray Integral Field Unit

NASA Astrophysics Data System (ADS)

Cucchetti, E.; Eckart, M. E.; Peille, P.; Porter, F. S.; Pajot, F.; Pointecouteau, E.

2018-04-01

With its array of 3840 Transition Edge Sensors (TESs), the Athena X-ray Integral Field Unit (X-IFU) will provide spatially resolved high-resolution spectroscopy (2.5 eV up to 7 keV) from 0.2 to 12 keV, with an absolute energy scale accuracy of 0.4 eV. Slight changes in the TES operating environment can cause significant variations in its energy response function, which may result in systematic errors in the absolute energy scale. We plan to monitor such changes at pixel level via onboard X-ray calibration sources and correct the energy scale accordingly using a linear or quadratic interpolation of gain curves obtained during ground calibration. However, this may not be sufficient to meet the 0.4 eV accuracy required for the X-IFU. In this contribution, we introduce a new two-parameter gain correction technique, based on both the pulse-height estimate of a fiducial line and the baseline value of the pixels. Using gain functions that simulate ground calibration data, we show that this technique can accurately correct deviations in detector gain due to changes in TES operating conditions such as heat sink temperature, bias voltage, thermal radiation loading and linear amplifier gain. We also address potential optimisations of the onboard calibration source and compare the performance of this new technique with those previously used.

Parameter Identification and Uncertainty Analysis for Visual MODFLOW based Groundwater Flow Model in a Small River Basin, Eastern India

NASA Astrophysics Data System (ADS)

Jena, S.

2015-12-01

The overexploitation of groundwater resulted in abandoning many shallow tube wells in the river Basin in Eastern India. For the sustainability of groundwater resources, basin-scale modelling of groundwater flow is essential for the efficient planning and management of the water resources. The main intent of this study is to develope a 3-D groundwater flow model of the study basin using the Visual MODFLOW package and successfully calibrate and validate it using 17 years of observed data. The sensitivity analysis was carried out to quantify the susceptibility of aquifer system to the river bank seepage, recharge from rainfall and agriculture practices, horizontal and vertical hydraulic conductivities, and specific yield. To quantify the impact of parameter uncertainties, Sequential Uncertainty Fitting Algorithm (SUFI-2) and Markov chain Monte Carlo (MCMC) techniques were implemented. Results from the two techniques were compared and the advantages and disadvantages were analysed. Nash-Sutcliffe coefficient (NSE) and coefficient of determination (R2) were adopted as two criteria during calibration and validation of the developed model. NSE and R2 values of groundwater flow model for calibration and validation periods were in acceptable range. Also, the MCMC technique was able to provide more reasonable results than SUFI-2. The calibrated and validated model will be useful to identify the aquifer properties, analyse the groundwater flow dynamics and the change in groundwater levels in future forecasts.

Standard Reference Specimens in Quality Control of Engineering Surfaces

PubMed Central

Song, J. F.; Vorburger, T. V.

1991-01-01

In the quality control of engineering surfaces, we aim to understand and maintain a good relationship between the manufacturing process and surface function. This is achieved by controlling the surface texture. The control process involves: 1) learning the functional parameters and their control values through controlled experiments or through a long history of production and use; 2) maintaining high accuracy and reproducibility with measurements not only of roughness calibration specimens but also of real engineering parts. In this paper, the characteristics, utilizations, and limitations of different classes of precision roughness calibration specimens are described. A measuring procedure of engineering surfaces, based on the calibration procedure of roughness specimens at NIST, is proposed. This procedure involves utilization of check specimens with waveform, wavelength, and other roughness parameters similar to functioning engineering surfaces. These check specimens would be certified under standardized reference measuring conditions, or by a reference instrument, and could be used for overall checking of the measuring procedure and for maintaining accuracy and agreement in engineering surface measurement. The concept of “surface texture design” is also suggested, which involves designing the engineering surface texture, the manufacturing process, and the quality control procedure to meet the optimal functional needs. PMID:28184115

Study of the Integration of LIDAR and Photogrammetric Datasets by in Situ Camera Calibration and Integrated Sensor Orientation

NASA Astrophysics Data System (ADS)

Mitishita, E.; Costa, F.; Martins, M.

2017-05-01

Photogrammetric and Lidar datasets should be in the same mapping or geodetic frame to be used simultaneously in an engineering project. Nowadays direct sensor orientation is a common procedure used in simultaneous photogrammetric and Lidar surveys. Although the direct sensor orientation technologies provide a high degree of automation process due to the GNSS/INS technologies, the accuracies of the results obtained from the photogrammetric and Lidar surveys are dependent on the quality of a group of parameters that models accurately the user conditions of the system at the moment the job is performed. This paper shows the study that was performed to verify the importance of the in situ camera calibration and Integrated Sensor Orientation without control points to increase the accuracies of the photogrammetric and LIDAR datasets integration. The horizontal and vertical accuracies of photogrammetric and Lidar datasets integration by photogrammetric procedure improved significantly when the Integrated Sensor Orientation (ISO) approach was performed using Interior Orientation Parameter (IOP) values estimated from the in situ camera calibration. The horizontal and vertical accuracies, estimated by the Root Mean Square Error (RMSE) of the 3D discrepancies from the Lidar check points, increased around of 37% and 198% respectively.

Polarization effects on hard target calibration of lidar systems

NASA Technical Reports Server (NTRS)

Kavaya, Michael J.

1987-01-01

The theory of hard target calibration of lidar backscatter data, including laboratory measurements of the pertinent target reflectance parameters, is extended to include the effects of polarization of the transmitted and received laser radiation. The bidirectional reflectance-distribution function model of reflectance is expanded to a 4 x 4 matrix allowing Mueller matrix and Stokes vector calculus to be employed. Target reflectance parameters for calibration of lidar backscatter data are derived for various lidar system polarization configurations from integrating sphere and monostatic reflectometer measurements. It is found that correct modeling of polarization effects is mandatory for accurate calibration of hard target reflectance parameters and, therefore, for accurate calibration of lidar backscatter data.

Kinetics of hydrophobic organic contaminant extraction from sediment by granular activated carbon.

PubMed

Rakowska, M I; Kupryianchyk, D; Smit, M P J; Koelmans, A A; Grotenhuis, J T C; Rijnaarts, H H M

2014-03-15

Ex situ solid phase extraction with granular activated carbon (GAC) is a promising technique to remediate contaminated sediments. The methods' efficiency depends on the rate by which contaminants are transferred from the sediment to the surface of GAC. Here, we derive kinetic parameters for extraction of polycyclic aromatic hydrocarbons (PAH) from sediment by GAC, using a first-order multi-compartment kinetic model. The parameters were obtained by modeling sediment-GAC exchange kinetic data following a tiered model calibration approach. First, parameters for PAH desorption from sediment were calibrated using data from systems with 50% (by weight) GAC acting as an infinite sink. Second, the estimated parameters were used as fixed input to obtain GAC uptake kinetic parameters in sediment slurries with 4% GAC, representing the ex situ remediation scenario. PAH uptake rate constants (kGAC) by GAC ranged from 0.44 to 0.0005 d(-1), whereas GAC sorption coefficients (KGAC) ranged from 10(5.57) to 10(8.57) L kg(-1). These values are the first provided for GAC in the presence of sediment and show that ex situ extraction with GAC is sufficiently fast and effective to reduce the risks of the most available PAHs among those studied, such as fluorene, phenanthrene and anthracene. Copyright © 2013 Elsevier Ltd. All rights reserved.

Improving the Fit of a Land-Surface Model to Data Using its Adjoint

NASA Astrophysics Data System (ADS)

Raoult, N.; Jupp, T. E.; Cox, P. M.; Luke, C.

2015-12-01

Land-surface models (LSMs) are of growing importance in the world of climate prediction. They are crucial components of larger Earth system models that are aimed at understanding the effects of land surface processes on the global carbon cycle. The Joint UK Land Environment Simulator (JULES) is the land-surface model used by the UK Met Office. It has been automatically differentiated using commercial software from FastOpt, resulting in an analytical gradient, or 'adjoint', of the model. Using this adjoint, the adJULES parameter estimation system has been developed, to search for locally optimum parameter sets by calibrating against observations. adJULES presents an opportunity to confront JULES with many different observations, and make improvements to the model parameterisation. In the newest version of adJULES, multiple sites can be used in the calibration, to giving a generic set of parameters that can be generalised over plant functional types. We present an introduction to the adJULES system and its applications to data from a variety of flux tower sites. We show that calculation of the 2nd derivative of JULES allows us to produce posterior probability density functions of the parameters and how knowledge of parameter values is constrained by observations.

Near-infrared spectroscopy (NIRS) for a real time monitoring of the biogas process.

PubMed

Stockl, Andrea; Lichti, Fabian

2018-01-01

In this research project Near-infrared spectroscopy (NIRS) was applied to monitor the content of specific process parameters in anaerobic digestion. A laboratory scaled biogas digester was constantly fed every four hours with maize- and grass silage to keep a base load with an organic loading rate (OLR) of 2.5 kg oDM/m 3  ∗ d. Daily impact loads with shredded wheat up to an OLR of 8 kg oDM/m 3  ∗ d were added in order to generate peaks at the parameters tested. The developed calibration models are capable to show changes in process parameters like volatile fatty acids (VFA), propionic acid, total inorganic carbon (TIC) and the ratio of the volatile fatty acids to the carbonate buffer (VFA/TIC). Based on the calibration of the models for VFA and TIC, the values could be predicted with an R 2 of 0.94 and 0.97, respectively. Moreover, the residual prediction deviations were 4.0 and 6.0 for VFA and TIC, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.

Integrating a Gravity Simulation and Groundwater Modeling on the Calibration of Specific Yield for Choshui Alluvial Fan

NASA Astrophysics Data System (ADS)

Chang, Liang Cheng; Tsai, Jui pin; Chen, Yu Wen; Way Hwang, Chein; Chung Cheng, Ching; Chiang, Chung Jung

2014-05-01

For sustainable management, accurate estimation of recharge can provide critical information. The accuracy of estimation is highly related to uncertainty of specific yield (Sy). Because Sy value is traditionally obtained by a multi-well pumping test, the available Sy values are usually limited due to high installation cost. Therefore, this information insufficiency of Sy may cause high uncertainty for recharge estimation. Because gravity is a function of a material mass and the inverse square of the distance, gravity measurement can assist to obtain the mass variation of a shallow groundwater system. Thus, the groundwater level observation data and gravity measurements are used for the calibration of Sy for a groundwater model. The calibration procedure includes four steps. First, gravity variations of three groundwater-monitoring wells, Si-jhou, Tu-ku and Ke-cuo, are observed in May, August and November 2012. To obtain the gravity caused by groundwater variation, this study filters the noises from other sources, such as ocean tide and land subsidence, in the collected data The refined data, which are data without noises, are named gravity residual. Second, this study develops a groundwater model using MODFLOW 2005 to simulate the water mass variation of the groundwater system. Third, we use Newton gravity integral to simulate the gravity variation caused by the simulated water mass variation during each of the observation periods. Fourth, comparing the ratio of the gravity variation between the two data sets, which are observed gravity residuals and simulated gravities. The values of Sy is continuously modified until the gravity variation ratios of the two data sets are the same. The Sy value of Si-jhou is 0.216, which is obtained by the multi-well pumping test. This Sy value is assigned to the simulation model. The simulation results show that the simulated gravity can well fit the observed gravity residual without parameter calibration. This result indicates that the proposed approach is correct and reasonable. In Tu-ku and Ke-cuo, the ratios of the gravity variation between observed gravity residuals and simulated gravities are approximate 1.8 and 50, respectively. The Sy values of these two stations are modified 1.8 and 50 times the original values. These modified Sy values are assigned to the groundwater morel. After the parameter re-assignment, the simulated gravities meet the gravity residuals in these two stations. In conclusion, the study results show that the proposed approach has the potential to identify Sy without installing wells. Therefore, the proposed approach can be used to increase the spatial density of Sy and can conduct the recharge estimation with low uncertainty.

Modeling actual evapotranspiration with routine meteorological variables in the data-scarce region of the Tibetan Plateau: Comparisons and implications

NASA Astrophysics Data System (ADS)

Ma, Ning; Zhang, Yinsheng; Xu, Chong-Yu; Szilagyi, Jozsef

2015-08-01

Quantitative estimation of actual evapotranspiration (ETa) by in situ measurements and mathematical modeling is a fundamental task for physical understanding of ETa as well as the feedback mechanisms between land and the ambient atmosphere. However, the ETa information in the Tibetan Plateau (TP) has been greatly impeded by the extremely sparse ground observation network in the region. Approaches for estimating ETa solely from routine meteorological variables are therefore important for investigating spatiotemporal variations of ETa in the data-scarce region of the TP. Motivated by this need, the complementary relationship (CR) and Penman-Monteith approaches were evaluated against in situ measurements of ETa on a daily basis in an alpine steppe region of the TP. The former includes the Nonlinear Complementary Relationship (Nonlinear-CR) as well as the Complementary Relationship Areal Evapotranspiration (CRAE) models, while the latter involves the Katerji-Perrier and the Todorovic models. Results indicate that the Nonlinear-CR, CRAE, and Katerji-Perrier models are all capable of efficiently simulating daily ETa, provided their parameter values were appropriately calibrated. The Katerji-Perrier model performed best since its site-specific parameters take the soil water status into account. The Nonlinear-CR model also performed well with the advantage of not requiring the user to choose between a symmetric and asymmetric CR. The CRAE model, even with a relatively low Nash-Sutcliffe efficiency (NSE) value, is also an acceptable approach in this data-scarce region as it does not need information of wind speed and ground surface conditions. In contrast, application of the Todorovic model was found to be inappropriate in the dry regions of the TP due to its significant overestimation of ETa as it neglects the effect of water stress on the bulk surface resistance. Sensitivity analysis of the parameter values demonstrated the relative importance of each parameter in the corresponding model. Overall, the Nonlinear-CR model is recommended in the absence of measured ETa for local calibration of the model parameter values.

TU-FG-209-04: Testing of Digital Image Receptors Using AAPM TG-150’s Draft Recommendations - Investigating the Impact of Different Processing Parameters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Finley, C; Dave, J

Purpose: To evaluate implementation of AAPM TG-150’s draft recommendations via a parameter study for testing the performance of digital image receptors. Methods: Flat field images were acquired from 9 calibrated digital image receptors associated with 9 new portable digital radiography systems (Carestream Health, Inc.) based on the draft recommendations and manufacturer-specified calibration conditions (set of 4 images at input detector air kerma ranging from 1 to 25 µGy). Effects of exposure response function (linearized and logarithmic), ‘Presentation Intent Type’ (‘For Processing’ and ‘For Presentation’), detector orientation with respect to the anode-cathode axis (4 orientations; 900 rotations per iteration), different ROImore » sizes (5×5–40×40 mm{sup 2}) and elimination of varying dimensions of image border (0 mm i.e., without boundary elimination to 150 mm) on signal, noise, signal-to-noise ratio (SNR) and the associated nonuniformities were evaluated. Images were analyzed in Matlab and quantities were compared using ANOVA. Results: Signal, noise and SNR values averaged over 9 systems with default parameter values in draft recommendations were 4837.2±139.4, 19.7±0.9 and 246.4±10.1 (mean ± standard deviation), respectively (at input detector air kerma: 12.5 µGy). Signal, noise and SNR showed characteristic dependency on exposure response function and on ‘Presentation Intent Type’. These values were not affected by ROI size and detector orientation, but analysis showed that eliminating the edge pixels along the boundary was required for the noise parameter (coefficient of variation range for noise: 72%–106% and 3%–4% without and with boundary elimination; respectively). Local and global nonuniformities showed a similar dependence on the need for boundary elimination. Interestingly, computed non-uniformities showed agreement with manufacturer-reported values except for noise non-uniformities in two units; artifacts were seen in images from these two units highlighting the importance of independent evaluations. Conclusion: The effect of different parameters on performance characterization of digital image receptors was evaluated based on TG-150’s draft recommendations.« less

Calibration of the maximum carboxylation velocity (vcmax) for the Caatinga for use in dynamic global vegetation models (DGVMs)

NASA Astrophysics Data System (ADS)

Rezende, L. C.; Arenque, B.; von Randow, C.; Moura, M. S.; Aidar, S. D.; Buckeridge, M. S.; Menezes, R.; Souza, L. S.; Ometto, J. P.

2013-12-01

The Caatinga biome in the semi-arid region of northeastern Brazil is extremely important due to its biodiversity and endemism. This biome, which is under high anthropogenic influences, presents high levels of environmental degradation, land use being among the main causes of such degradation. The simulations of land cover and the vegetation dynamic under different climate scenarios are important features for prediction of environmental risks and determination of sustainable pathways for the planet in the future. Modeling of the vegetation can be performed by use of dynamic global vegetation models (DGVMs). The DGVMs simulate the surface processes (e.g. transfer of energy, water, CO2 and momentum); plant physiology (e.g. photosynthesis, stomatal conductance) phenology; gross and net primary productivity, respiration, plant species classified by functional traits; competition for light, water and nutrients, soil characteristics and processes (e.g. nutrients, heterotrophic respiration). Currently, most of the parameters used in DGVMs are static pre-defined values, and the lack of observational information to aid choosing the most adequate values for these parameters is particularly critical for the semi-arid regions in the world. Through historical meteorological data and measurements of carbon assimilation we aim to calibrate the maximum carboxylation velocity (Vcmax), for the native species Poincianella microphylla, abundant in the Caatinga region. The field data (collected at Lat: 90 2' S, Lon: 40019' W) displayed two contrasting meteorological conditions, with precipitations of 16 mm and 104 mm prior to the sampling campaigns (April 9-13, 2012 and February 4-8, 2013; respectively). Calibration (obtaining values of Vcmax more suitable for vegetation of Caatinga) has been performed through an algorithm of pattern recognition: Classification And Regression Tree (CART) and calculation of the vapor pressure deficit (VPD), which was used as attribute for discrimination of data. CART can be utilized for classification or regression, being used in the context of this work for non-linear regression. Our results show that CART algorithm correctly classified data according to the two contrasting periods (i.e. correctly distinguished assimilation data measured during drier or rainy periods), and suggest average Vcmax values of 14.2 μmol CO2 m-2 s-1 for the drier period and of 102.5 μmol CO2 m-2 s-1 for the rainy period. Comparing the values obtained in this work with values obtained through a traditional parameter optimization technique, it is possible to gauge pros and cons of such a combination of field measurements and machine learning technique.

Parameter Estimation of Computationally Expensive Watershed Models Through Efficient Multi-objective Optimization and Interactive Decision Analytics

NASA Astrophysics Data System (ADS)

Akhtar, Taimoor; Shoemaker, Christine

2016-04-01

Watershed model calibration is inherently a multi-criteria problem. Conflicting trade-offs exist between different quantifiable calibration criterions indicating the non-existence of a single optimal parameterization. Hence, many experts prefer a manual approach to calibration where the inherent multi-objective nature of the calibration problem is addressed through an interactive, subjective, time-intensive and complex decision making process. Multi-objective optimization can be used to efficiently identify multiple plausible calibration alternatives and assist calibration experts during the parameter estimation process. However, there are key challenges to the use of multi objective optimization in the parameter estimation process which include: 1) multi-objective optimization usually requires many model simulations, which is difficult for complex simulation models that are computationally expensive; and 2) selection of one from numerous calibration alternatives provided by multi-objective optimization is non-trivial. This study proposes a "Hybrid Automatic Manual Strategy" (HAMS) for watershed model calibration to specifically address the above-mentioned challenges. HAMS employs a 3-stage framework for parameter estimation. Stage 1 incorporates the use of an efficient surrogate multi-objective algorithm, GOMORS, for identification of numerous calibration alternatives within a limited simulation evaluation budget. The novelty of HAMS is embedded in Stages 2 and 3 where an interactive visual and metric based analytics framework is available as a decision support tool to choose a single calibration from the numerous alternatives identified in Stage 1. Stage 2 of HAMS provides a goodness-of-fit measure / metric based interactive framework for identification of a small subset (typically less than 10) of meaningful and diverse set of calibration alternatives from the numerous alternatives obtained in Stage 1. Stage 3 incorporates the use of an interactive visual analytics framework for decision support in selection of one parameter combination from the alternatives identified in Stage 2. HAMS is applied for calibration of flow parameters of a SWAT model, (Soil and Water Assessment Tool) designed to simulate flow in the Cannonsville watershed in upstate New York. Results from the application of HAMS to Cannonsville indicate that efficient multi-objective optimization and interactive visual and metric based analytics can bridge the gap between the effective use of both automatic and manual strategies for parameter estimation of computationally expensive watershed models.

SDMProjectBuilder: SWAT Simulation and Calibration for Nutrient Fate and Transport

EPA Science Inventory

This tutorial reviews screens, icons, and basic functions for downloading flow, sediment, and nutrient observations for a watershed of interest; how to prepare SWAT-CUP input files for SWAT parameter calibration; and how to perform SWAT parameter calibration with SWAT-CUP. It dem...

A Method to Test Model Calibration Techniques

DOE Office of Scientific and Technical Information (OSTI.GOV)

Judkoff, Ron; Polly, Ben; Neymark, Joel

This paper describes a method for testing model calibration techniques. Calibration is commonly used in conjunction with energy retrofit audit models. An audit is conducted to gather information about the building needed to assemble an input file for a building energy modeling tool. A calibration technique is used to reconcile model predictions with utility data, and then the 'calibrated model' is used to predict energy savings from a variety of retrofit measures and combinations thereof. Current standards and guidelines such as BPI-2400 and ASHRAE-14 set criteria for 'goodness of fit' and assume that if the criteria are met, then themore » calibration technique is acceptable. While it is logical to use the actual performance data of the building to tune the model, it is not certain that a good fit will result in a model that better predicts post-retrofit energy savings. Therefore, the basic idea here is that the simulation program (intended for use with the calibration technique) is used to generate surrogate utility bill data and retrofit energy savings data against which the calibration technique can be tested. This provides three figures of merit for testing a calibration technique, 1) accuracy of the post-retrofit energy savings prediction, 2) closure on the 'true' input parameter values, and 3) goodness of fit to the utility bill data. The paper will also discuss the pros and cons of using this synthetic surrogate data approach versus trying to use real data sets of actual buildings.« less

A Method to Test Model Calibration Techniques: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Judkoff, Ron; Polly, Ben; Neymark, Joel

This paper describes a method for testing model calibration techniques. Calibration is commonly used in conjunction with energy retrofit audit models. An audit is conducted to gather information about the building needed to assemble an input file for a building energy modeling tool. A calibration technique is used to reconcile model predictions with utility data, and then the 'calibrated model' is used to predict energy savings from a variety of retrofit measures and combinations thereof. Current standards and guidelines such as BPI-2400 and ASHRAE-14 set criteria for 'goodness of fit' and assume that if the criteria are met, then themore » calibration technique is acceptable. While it is logical to use the actual performance data of the building to tune the model, it is not certain that a good fit will result in a model that better predicts post-retrofit energy savings. Therefore, the basic idea here is that the simulation program (intended for use with the calibration technique) is used to generate surrogate utility bill data and retrofit energy savings data against which the calibration technique can be tested. This provides three figures of merit for testing a calibration technique, 1) accuracy of the post-retrofit energy savings prediction, 2) closure on the 'true' input parameter values, and 3) goodness of fit to the utility bill data. The paper will also discuss the pros and cons of using this synthetic surrogate data approach versus trying to use real data sets of actual buildings.« less

New Multi-objective Uncertainty-based Algorithm for Water Resource Models' Calibration

NASA Astrophysics Data System (ADS)

Keshavarz, Kasra; Alizadeh, Hossein

2017-04-01

Water resource models are powerful tools to support water management decision making process and are developed to deal with a broad range of issues including land use and climate change impacts analysis, water allocation, systems design and operation, waste load control and allocation, etc. These models are divided into two categories of simulation and optimization models whose calibration has been addressed in the literature where great relevant efforts in recent decades have led to two main categories of auto-calibration methods of uncertainty-based algorithms such as GLUE, MCMC and PEST and optimization-based algorithms including single-objective optimization such as SCE-UA and multi-objective optimization such as MOCOM-UA and MOSCEM-UA. Although algorithms which benefit from capabilities of both types, such as SUFI-2, were rather developed, this paper proposes a new auto-calibration algorithm which is capable of both finding optimal parameters values regarding multiple objectives like optimization-based algorithms and providing interval estimations of parameters like uncertainty-based algorithms. The algorithm is actually developed to improve quality of SUFI-2 results. Based on a single-objective, e.g. NSE and RMSE, SUFI-2 proposes a routine to find the best point and interval estimation of parameters and corresponding prediction intervals (95 PPU) of time series of interest. To assess the goodness of calibration, final results are presented using two uncertainty measures of p-factor quantifying percentage of observations covered by 95PPU and r-factor quantifying degree of uncertainty, and the analyst has to select the point and interval estimation of parameters which are actually non-dominated regarding both of the uncertainty measures. Based on the described properties of SUFI-2, two important questions are raised, answering of which are our research motivation: Given that in SUFI-2, final selection is based on the two measures or objectives and on the other hand, knowing that there is no multi-objective optimization mechanism in SUFI-2, are the final estimations Pareto-optimal? Can systematic methods be applied to select the final estimations? Dealing with these questions, a new auto-calibration algorithm was proposed where the uncertainty measures were considered as two objectives to find non-dominated interval estimations of parameters by means of coupling Monte Carlo simulation and Multi-Objective Particle Swarm Optimization. Both the proposed algorithm and SUFI-2 were applied to calibrate parameters of water resources planning model of Helleh river basin, Iran. The model is a comprehensive water quantity-quality model developed in the previous researches using WEAP software in order to analyze the impacts of different water resources management strategies including dam construction, increasing cultivation area, utilization of more efficient irrigation technologies, changing crop pattern, etc. Comparing the Pareto frontier resulted from the proposed auto-calibration algorithm with SUFI-2 results, it was revealed that the new algorithm leads to a better and also continuous Pareto frontier, even though it is more computationally expensive. Finally, Nash and Kalai-Smorodinsky bargaining methods were used to choose compromised interval estimation regarding Pareto frontier.

Erratum to. Energy calibration of gamma spectra in plastic scintillators using Compton kinematics [Nucl. Instr. and Meth. A 594 (2008) 232–243

DOE Office of Scientific and Technical Information (OSTI.GOV)

Siciliano, Edward R.; Ely, James H.; Kouzes, Richard T.

2009-11-01

In recent work at our laboratory, we were re-examining our data and found an inconsistency between the values listed for 137Cs in Table 2 (Siciliano et al. 2008) and results plotted for that source in Figures 11 and 12. In the course of fitting the parabolic function (Equation 4) to the Compton maxima, two ranges of channels were used when determining the parameters for 137Cs. The parabolic fit curve shown in Figure 11 resulted from fitting channels 50 to 70. The parameters for that fit are: are: A = 0.972(12), B = 1.42(24) x 10 -3, and C NO =more » 60.2(5). The parameters for 137Cs listed in Table 2 (and also used to determine the calibration relations in Figure 12—the main result of this paper) came from fitting the 137Cs data in channels 40 to 80. Although the curves plotted from these two different sets of parameters would be visually distinguishable in Figure 11, when incorporated with the other isotope values shown in Figure 12 to obtain the linear energy-channel fit, the 50-70 channel parameter set plus the correction from the Compton maximum to the Compton edge gives a negligible change in the slope [6.470(41) as opposed to the reported 6.454(15) keV/channel] and a small change in the intercept [41(8) as opposed to 47(3) keV] for the dashed line. The conclusions of the article therefore do not change as a result of this inconsistency.« less

The complementary relationship (CR) approach aids evapotranspiration estimation in the data scarce region of Tibetan Plateau: symmetric and asymmetric perspectives

NASA Astrophysics Data System (ADS)

Ma, N.; Zhang, Y.; Szilagyi, J.; Xu, C. Y.

2015-12-01

While the land surface latent and sensible heat release in the Tibetan Plateau (TP) could greatly influence the Asian monsoon circulation, the actual evapotranspiration (ETa) information in the TP has been largely hindered by its extremely sparse ground observation network. Thus the complementary relationship (CR) theory lends great potential in estimating the ETa since it relies on solely routine meteorological observations. With the in-situ energy/water flux observation over the highest semiarid alpine steppe in the TP, the modifications of specific components within the CR were first implemented. We found that the symmetry of the CR could be achieved for dry regions of TP when (i) the Priestley-Taylor coefficient, (ii) the slope of the saturation vapor pressure curve and (iii) the wind function were locally calibrated by using the ETa observations in wet days, an estimate of the wet surface temperature and the Monin-Obukhov Similarity (MOS) theory, respectively. In this way, the error of the simulated ETa by the symmetric AA model could be decreased to a large extent. Besides, the asymmetric CR was confirmed in TP when the D20 above-ground and/or E601B sunken pan evaporation (Epan) were used as a proxy of the ETp. Thus daily ETa could also be estimated by coupling D20 above-ground and/or E601B sunken pans through CR. Additionally, to overcome the modification of the specific components in the CR, we also evaluated the Nonlinear-CR model and the Morton's CRAE model. The former does not need the pre-determination of the asymmetry of CR, while the latter does not require the wind speed data as input. We found that both models are also able to simulate the daily ETa well provided their parameter values have been locally calibrated. The sensitivity analysis shows that, if the measured ETa data are absence to calibrate the models' parameter values, the Nonlinear-CR model may be a particularly good way for estimating ETabecause of its mild sensitivity to the parameter values making possible to employ published parameter values derived under similar climatic and land cover conditions. The CRAE model should also be highlighted in the TP since the special topography make the wind speed data suffer large uncertainties when the advanced geo-statistical method was used to spatially interpolate the point-based meteorological records.

Microhardness and lattice parameter calibrations of the oxygen solid solutions of unalloyed alpha-titanium and Ti-6Al-2Sn-4Zr-2Mo

NASA Technical Reports Server (NTRS)

Wiedemann, K. E.; Shenoy, R. N.; Unnam, J.

1987-01-01

Standards were prepared for calibrating microanalyses of dissolved oxygen in unalloyed alpha-Ti and Ti-6Al-2Sn-4Zr-2Mo. Foils of both of these materials were homogenized for 120 hours in vacuum at 871 C following short exposures to the ambient atmosphere at 854 C that had partially oxidized the foils. The variation of Knoop microhardness with oxygen content was calibrated for both materials using 15-g and 5-g indentor loads. The unit-cell lattice parameters were calibrated for the unalloyed alpha-Ti. Example analyses demonstrate the usefulness of these calibrations and support an explanation of an anomaly in the lattice parameter variation. The results of the calibrations have been tabulated and summarized using predictive equations.

Sensitivity and Uncertainty Analysis for Streamflow Prediction Using Different Objective Functions and Optimization Algorithms: San Joaquin California

NASA Astrophysics Data System (ADS)

Paul, M.; Negahban-Azar, M.

2017-12-01

The hydrologic models usually need to be calibrated against observed streamflow at the outlet of a particular drainage area through a careful model calibration. However, a large number of parameters are required to fit in the model due to their unavailability of the field measurement. Therefore, it is difficult to calibrate the model for a large number of potential uncertain model parameters. This even becomes more challenging if the model is for a large watershed with multiple land uses and various geophysical characteristics. Sensitivity analysis (SA) can be used as a tool to identify most sensitive model parameters which affect the calibrated model performance. There are many different calibration and uncertainty analysis algorithms which can be performed with different objective functions. By incorporating sensitive parameters in streamflow simulation, effects of the suitable algorithm in improving model performance can be demonstrated by the Soil and Water Assessment Tool (SWAT) modeling. In this study, the SWAT was applied in the San Joaquin Watershed in California covering 19704 km2 to calibrate the daily streamflow. Recently, sever water stress escalating due to intensified climate variability, prolonged drought and depleting groundwater for agricultural irrigation in this watershed. Therefore it is important to perform a proper uncertainty analysis given the uncertainties inherent in hydrologic modeling to predict the spatial and temporal variation of the hydrologic process to evaluate the impacts of different hydrologic variables. The purpose of this study was to evaluate the sensitivity and uncertainty of the calibrated parameters for predicting streamflow. To evaluate the sensitivity of the calibrated parameters three different optimization algorithms (Sequential Uncertainty Fitting- SUFI-2, Generalized Likelihood Uncertainty Estimation- GLUE and Parameter Solution- ParaSol) were used with four different objective functions (coefficient of determination- r2, Nash-Sutcliffe efficiency- NSE, percent bias- PBIAS, and Kling-Gupta efficiency- KGE). The preliminary results showed that using the SUFI-2 algorithm with the objective function NSE and KGE has improved significantly the calibration (e.g. R2 and NSE is found 0.52 and 0.47 respectively for daily streamflow calibration).

Parameter estimation procedure for complex non-linear systems: calibration of ASM No. 1 for N-removal in a full-scale oxidation ditch.

PubMed

Abusam, A; Keesman, K J; van Straten, G; Spanjers, H; Meinema, K

2001-01-01

When applied to large simulation models, the process of parameter estimation is also called calibration. Calibration of complex non-linear systems, such as activated sludge plants, is often not an easy task. On the one hand, manual calibration of such complex systems is usually time-consuming, and its results are often not reproducible. On the other hand, conventional automatic calibration methods are not always straightforward and often hampered by local minima problems. In this paper a new straightforward and automatic procedure, which is based on the response surface method (RSM) for selecting the best identifiable parameters, is proposed. In RSM, the process response (output) is related to the levels of the input variables in terms of a first- or second-order regression model. Usually, RSM is used to relate measured process output quantities to process conditions. However, in this paper RSM is used for selecting the dominant parameters, by evaluating parameters sensitivity in a predefined region. Good results obtained in calibration of ASM No. 1 for N-removal in a full-scale oxidation ditch proved that the proposed procedure is successful and reliable.

Improved Detection System Description and New Method for Accurate Calibration of Micro-Channel Plate Based Instruments and Its Use in the Fast Plasma Investigation on NASA's Magnetospheric MultiScale Mission

NASA Technical Reports Server (NTRS)

Gliese, U.; Avanov, L. A.; Barrie, A. C.; Kujawski, J. T.; Mariano, A. J.; Tucker, C. J.; Chornay, D. J.; Cao, N. T.; Gershman, D. J.; Dorelli, J. C.;

Inverse Modeling of the Thermal Hydrodynamic and Chemical Processes During Exploitation of the Mutnovsky Geothermal Field (Kamchatka, Russia)

NASA Astrophysics Data System (ADS)

Kiryukhin, A. V.

2012-12-01

A TOUGH2-EOS1 3D rectangular numerical model of the Mutnovsky geothermal field (Kiryukhin, 1996) was re-calibrated using natural state and history exploitation data during the time period 1984-2006 years. Recalibration using iTOUGH2-EOS1+tracer inversion modeling capabilities, was useful to remove outliers from calibration data, identify sets of the estimated parameters of the model, and perform estimations. Chloride ion was used as a "tracer" in this modeling. Thermal hydrodynamic observational data which were used for model recalibration are as follows: 37 temperature and 1 pressure calibration points - for natural state, 13 production wells with monthly averaged enthalpies (650 values during the time period 1983-1987, 2000-2006 years) and 1 transient pressure monitoring wells (57 values during 2003-2006 years) - for exploitation history match. Chemical observational data includes transient mass chloride concentrations from 10 production wells and chloride hot spring sampling data (149 values during 1999-2006 years). The following features of Mutnovsky geothermal reservoir based on integrated inverse modeling analysis of natural state and exploitation data were estimated and better understood: 1. Reservoir permeability was found to be one order more comparable to model-1996, especially the lower part coinciding with intrusion contact zone (600-800 mD at -750 - -1250 masl); 2. Local meteoric inflow in the central part of the field accounting for 45 - 80 kg/s since year 2002; 3. Reinjection rates were estimated significantly lower, than officially reported as 100% of total fluid withdrawal; 4. Upflow fluid flows were estimated hotter (314oC) and the rates are larger (+50%), than assumed before; 5. Global double porosity parameters estimates are: fracture spacing - 5 - 10 m, void fraction N 10-3; 6. Main upflow zone chloride mass concentration estimate is 150 ppm. Conversion of the calibrated TOUGH2-EOS1+tracer model into electrical resistivity model using TOUGH2-EOS9 (L. Magnusdottir, 2012) may significantly improve efficiency of Electrical Resistivity Tomography (ETR) applications to detect spatial features of infiltration downflows and chloride enriched reinjected flows during reservoir exploitation.

Model simulations of flood and debris flow timing in steep catchments after wildfire

NASA Astrophysics Data System (ADS)

Rengers, F. K.; McGuire, L. A.; Kean, J. W.; Staley, D. M.; Hobley, D. E. J.

2016-08-01

Debris flows are a typical hazard on steep slopes after wildfire, but unlike debris flows that mobilize from landslides, most postwildfire debris flows are generated from water runoff. The majority of existing debris flow modeling has focused on landslide-triggered debris flows. In this study we explore the potential for using process-based rainfall-runoff models to simulate the timing of water flow and runoff-generated debris flows in recently burned areas. Two different spatially distributed hydrologic models with differing levels of complexity were used: the full shallow water equations and the kinematic wave approximation. Model parameter values were calibrated in two different watersheds, spanning two orders of magnitude in drainage area. These watersheds were affected by the 2009 Station Fire in the San Gabriel Mountains, CA, USA. Input data for the numerical models were constrained by time series of soil moisture, flow stage, and rainfall collected at field sites, as well as high-resolution lidar-derived digital elevation models. The calibrated parameters were used to model a third watershed in the burn area, and the results show a good match with observed timing of flow peaks. The calibrated roughness parameter (Manning's n) was generally higher when using the kinematic wave approximation relative to the shallow water equations, and decreased with increasing spatial scale. The calibrated effective watershed hydraulic conductivity was low for both models, even for storms occurring several months after the fire, suggesting that wildfire-induced changes to soil-water infiltration were retained throughout that time. Overall, the two model simulations were quite similar suggesting that a kinematic wave model, which is simpler and more computationally efficient, is a suitable approach for predicting flood and debris flow timing in steep, burned watersheds.

Model simulations of flood and debris flow timing in steep catchments after wildfire

USGS Publications Warehouse

Rengers, Francis K.; McGuire, Luke; Kean, Jason W.; Staley, Dennis M.; Hobley, D.E.J

2016-01-01

Debris flows are a typical hazard on steep slopes after wildfire, but unlike debris flows that mobilize from landslides, most post-wildfire debris flows are generated from water runoff. The majority of existing debris-flow modeling has focused on landslide-triggered debris flows. In this study we explore the potential for using process-based rainfall-runoff models to simulate the timing of water flow and runoff-generated debris flows in recently burned areas. Two different spatially distributed hydrologic models with differing levels of complexity were used: the full shallow water equations and the kinematic wave approximation. Model parameter values were calibrated in two different watersheds, spanning two orders of magnitude in drainage area. These watersheds were affected by the 2009 Station Fire in the San Gabriel Mountains, CA, USA. Input data for the numerical models were constrained by time series of soil moisture, flow stage, and rainfall collected at field sites, as well as high-resolution lidar-derived digital elevation models. The calibrated parameters were used to model a third watershed in the burn area, and the results show a good match with observed timing of flow peaks. The calibrated roughness parameter (Manning's $n$) was generally higher when using the kinematic wave approximation relative to the shallow water equations, and decreased with increasing spatial scale. The calibrated effective watershed hydraulic conductivity was low for both models, even for storms occurring several months after the fire, suggesting that wildfire-induced changes to soil-water infiltration were retained throughout that time. Overall the two model simulations were quite similar suggesting that a kinematic wave model, which is simpler and more computationally efficient, is a suitable approach for predicting flood and debris flow timing in steep, burned watersheds.

SURFplus Model Calibration for PBX 9502

DOE Office of Scientific and Technical Information (OSTI.GOV)

Menikoff, Ralph

2017-12-06

The SURFplus reactive burn model is calibrated for the TATB based explosive PBX 9502 at three initial temperatures; hot (75 C), ambient (23 C) and cold (-55 C). The CJ state depends on the initial temperature due to the variation in the initial density and initial specific energy of the PBX reactants. For the reactants, a porosity model for full density TATB is used. This allows the initial PBX density to be set to its measured value even though the coeffcient of thermal expansion for the TATB and the PBX differ. The PBX products EOS is taken as independent ofmore » the initial PBX state. The initial temperature also affects the sensitivity to shock initiation. The model rate parameters are calibrated to Pop plot data, the failure diameter, the limiting detonation speed just above the failure diameters, and curvature effect data for small curvature.« less

A stochastic multicloud convective parameterization in the NCEP Climate Forecast System (CFSv2) : implementation and calibration.

NASA Astrophysics Data System (ADS)

Goswami, B. B.; Khouider, B.; Krishna, R. P. M.; Mukhopadhyay, P.; Majda, A.

2017-12-01

A stochastic multicloud (SMCM) cumulus parameterization is implemented in the National Centres for Environmental Predictions (NCEP) Climate Forecast System version 2 (CFSv2) model, named as the CFSsmcm model. We present here results from a systematic attempt to understand the CFSsmcm model's sensitivity to the SMCM parameters. To asses the model-sentivity to the different SMCM parameters, we have analized a set of 14 5-year long climate simulations produced by the CFSsmcm model. The model is found to be resilient to minor changes in the parameter values. The middle tropospheric dryness (MTD) and the stratiform cloud decay timescale are found to be most crucial parameters in the SMCM formulation in the CFSsmcm model.

Improvements in world-wide intercomparison of PV module calibration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Salis, E.; Pavanello, D.; Field, M.

The calibration of the electrical performance of seven photovoltaic (PV) modules was compared between four reference laboratories on three continents. The devices included two samples in standard and two in high-efficiency crystalline silicon technology, two CI(G)S and one CdTe module. The reference value for each PV module parameter was calculated from the average of the results of all four laboratories, weighted by the respective measurement uncertainties. All single results were then analysed with respect to this reference value using the E n number approach. For the four modules in crystalline silicon technology, the results agreed in general within +/-0.5%, withmore » all values within +/-1% and all E n numbers well within [-1, 1], indicating further scope for reducing quoted measurement uncertainty. Regarding the three thin-film modules, deviations were on average roughly twice as large, i.e. in general from +/-1% to +/-2%. A number of inconsistent results were observable, although within the 5% that can be statistically expected on the basis of the E n number approach. Most inconsistencies can be traced to the preconditioning procedure of one participant, although contribution of other factors cannot be ruled out. After removing these obvious inconsistent results, only two real outliers remained, representing less than 2% of the total number of measurands. The results presented show improved agreement for the calibration of PV modules with respect to previous international exercises. For thin-film PV modules, the preconditioning of the devices prior to calibration measurements is the most critical factor for obtaining consistent results, while the measurement processes seem consistent and repeatable.« less

Improvements in world-wide intercomparison of PV module calibration

DOE PAGES

Salis, E.; Pavanello, D.; Field, M.; ...

2017-09-14

The calibration of the electrical performance of seven photovoltaic (PV) modules was compared between four reference laboratories on three continents. The devices included two samples in standard and two in high-efficiency crystalline silicon technology, two CI(G)S and one CdTe module. The reference value for each PV module parameter was calculated from the average of the results of all four laboratories, weighted by the respective measurement uncertainties. All single results were then analysed with respect to this reference value using the E n number approach. For the four modules in crystalline silicon technology, the results agreed in general within +/-0.5%, withmore » all values within +/-1% and all E n numbers well within [-1, 1], indicating further scope for reducing quoted measurement uncertainty. Regarding the three thin-film modules, deviations were on average roughly twice as large, i.e. in general from +/-1% to +/-2%. A number of inconsistent results were observable, although within the 5% that can be statistically expected on the basis of the E n number approach. Most inconsistencies can be traced to the preconditioning procedure of one participant, although contribution of other factors cannot be ruled out. After removing these obvious inconsistent results, only two real outliers remained, representing less than 2% of the total number of measurands. The results presented show improved agreement for the calibration of PV modules with respect to previous international exercises. For thin-film PV modules, the preconditioning of the devices prior to calibration measurements is the most critical factor for obtaining consistent results, while the measurement processes seem consistent and repeatable.« less

Temperature gradient scale length measurement: A high accuracy application of electron cyclotron emission without calibration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Houshmandyar, S., E-mail: houshmandyar@austin.utexas.edu; Phillips, P. E.; Rowan, W. L.

2016-11-15

Calibration is a crucial procedure in electron temperature (T{sub e}) inference from a typical electron cyclotron emission (ECE) diagnostic on tokamaks. Although the calibration provides an important multiplying factor for an individual ECE channel, the parameter ΔT{sub e}/T{sub e} is independent of any calibration. Since an ECE channel measures the cyclotron emission for a particular flux surface, a non-perturbing change in toroidal magnetic field changes the view of that channel. Hence the calibration-free parameter is a measure of T{sub e} gradient. B{sub T}-jog technique is presented here which employs the parameter and the raw ECE signals for direct measurement ofmore » electron temperature gradient scale length.« less

Altimeter waveform software design

NASA Technical Reports Server (NTRS)

Hayne, G. S.; Miller, L. S.; Brown, G. S.

1977-01-01

Techniques are described for preprocessing raw return waveform data from the GEOS-3 radar altimeter. Topics discussed include: (1) general altimeter data preprocessing to be done at the GEOS-3 Data Processing Center to correct altimeter waveform data for temperature calibrations, to convert between engineering and final data units and to convert telemetered parameter quantities to more appropriate final data distribution values: (2) time "tagging" of altimeter return waveform data quantities to compensate for various delays, misalignments and calculational intervals; (3) data processing procedures for use in estimating spacecraft attitude from altimeter waveform sampling gates; and (4) feasibility of use of a ground-based reflector or transponder to obtain in-flight calibration information on GEOS-3 altimeter performance.

Absolute magnitude calibration using trigonometric parallax - Incomplete, spectroscopic samples

NASA Technical Reports Server (NTRS)

Ratnatunga, Kavan U.; Casertano, Stefano

1991-01-01

A new numerical algorithm is used to calibrate the absolute magnitude of spectroscopically selected stars from their observed trigonometric parallax. This procedure, based on maximum-likelihood estimation, can retrieve unbiased estimates of the intrinsic absolute magnitude and its dispersion even from incomplete samples suffering from selection biases in apparent magnitude and color. It can also make full use of low accuracy and negative parallaxes and incorporate censorship on reported parallax values. Accurate error estimates are derived for each of the fitted parameters. The algorithm allows an a posteriori check of whether the fitted model gives a good representation of the observations. The procedure is described in general and applied to both real and simulated data.

Multiple frequency method for operating electrochemical sensors

DOEpatents

Martin, Louis P [San Ramon, CA

2012-05-15

A multiple frequency method for the operation of a sensor to measure a parameter of interest using calibration information including the steps of exciting the sensor at a first frequency providing a first sensor response, exciting the sensor at a second frequency providing a second sensor response, using the second sensor response at the second frequency and the calibration information to produce a calculated concentration of the interfering parameters, using the first sensor response at the first frequency, the calculated concentration of the interfering parameters, and the calibration information to measure the parameter of interest.

A calibrated agent-based computer model of stochastic cell dynamics in normal human colon crypts useful for in silico experiments.

PubMed

Bravo, Rafael; Axelrod, David E

2013-11-18

Normal colon crypts consist of stem cells, proliferating cells, and differentiated cells. Abnormal rates of proliferation and differentiation can initiate colon cancer. We have measured the variation in the number of each of these cell types in multiple crypts in normal human biopsy specimens. This has provided the opportunity to produce a calibrated computational model that simulates cell dynamics in normal human crypts, and by changing model parameter values, to simulate the initiation and treatment of colon cancer. An agent-based model of stochastic cell dynamics in human colon crypts was developed in the multi-platform open-source application NetLogo. It was assumed that each cell's probability of proliferation and probability of death is determined by its position in two gradients along the crypt axis, a divide gradient and in a die gradient. A cell's type is not intrinsic, but rather is determined by its position in the divide gradient. Cell types are dynamic, plastic, and inter-convertible. Parameter values were determined for the shape of each of the gradients, and for a cell's response to the gradients. This was done by parameter sweeps that indicated the values that reproduced the measured number and variation of each cell type, and produced quasi-stationary stochastic dynamics. The behavior of the model was verified by its ability to reproduce the experimentally observed monocolonal conversion by neutral drift, the formation of adenomas resulting from mutations either at the top or bottom of the crypt, and by the robust ability of crypts to recover from perturbation by cytotoxic agents. One use of the virtual crypt model was demonstrated by evaluating different cancer chemotherapy and radiation scheduling protocols. A virtual crypt has been developed that simulates the quasi-stationary stochastic cell dynamics of normal human colon crypts. It is unique in that it has been calibrated with measurements of human biopsy specimens, and it can simulate the variation of cell types in addition to the average number of each cell type. The utility of the model was demonstrated with in silico experiments that evaluated cancer therapy protocols. The model is available for others to conduct additional experiments.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, J; Li, X; Liu, G

Purpose: We compare and investigate the dosimetric impacts on pencil beam scanning (PBS) proton treatment plans generated with CT calibration curves from four different CT scanners and one averaged ‘global’ CT calibration curve. Methods: The four CT scanners are located at three different hospital locations within the same health system. CT density calibration curves were collected from these scanners using the same CT calibration phantom and acquisition parameters. Mass density to HU value tables were then commissioned in a commercial treatment planning system. Five disease sites were chosen for dosimetric comparisons at brain, lung, head and neck, adrenal, and prostate.more » Three types of PBS plans were generated at each treatment site using SFUD, IMPT, and robustness optimized IMPT techniques. 3D dose differences were investigated using 3D Gamma analysis. Results: The CT calibration curves for all four scanners display very similar shapes. Large HU differences were observed at both the high HU and low HU regions of the curves. Large dose differences were generally observed at the distal edges of the beams and they are beam angle dependent. Out of the five treatment sites, lung plans exhibits the most overall range uncertainties and prostate plans have the greatest dose discrepancy. There are no significant differences between the SFUD, IMPT, and the RO-IMPT methods. 3D gamma analysis with 3%, 3 mm criteria showed all plans with greater than 95% passing rate. Two of the scanners with close HU values have negligible dose difference except for lung. Conclusion: Our study shows that there are more than 5% dosimetric differences between different CT calibration curves. PBS treatment plans generated with SFUD, IMPT, and the robustness optimized IMPT has similar sensitivity to the CT density uncertainty. More patient data and tighter gamma criteria based on structure location and size will be used for further investigation.« less

The Darwin TCCON Site - CO2 Calibration and First Data

NASA Astrophysics Data System (ADS)

Deutscher, N. M.; Griffith, D. W.; Keppel-Aleks, G.; Washenfelder, R. A.; Wennberg, P. O.; Toon, G. C.

2007-12-01

This paper presents the first measurements from the solar observatory deployed to Darwin, Australia in August 2005. The observatory is the second dedicated instrument in the Total Carbon Column Observing Network (TCCON). The first two years of column values are presented, as well as comparison to integrated in situ aircraft profiles obtained during the Tropical Warm Pool - International Cloud Experiment (TWP-ICE) in January - February 2006. Sites in TCCON will provide ground-based validation and calibration for upcoming space-based instruments, such as the Orbiting Carbon Observatory (OCO) and Greenhouse Gases Observing Satellite (GOSAT), which measure the same atmospheric quantities. The TCCON stations are calibrated against integrated columns measured from aircraft by instruments calibrated on the accepted WMO CO2 scale. Two CO2 microwindows are calibrated independently, and the correction factors are determined to be 1.0143 ± 0.0004 (fit ± 95% confidence interval) and 1.0152 ± 0.0003, respectively, for the 6228 cm-1 and 6348 cm-1 bands. These values are in good agreement with similar comparisons made at Park Falls, and show an improvement in the absolute calibration, due to improved CO2 line parameters. The first two years of CO2 data from the solar FTS are analysed for secular and seasonal trends in the column average mixing ratio. These are compared to some surface in situ data trends for the same period. The column data capture the secular trend as observed in surface in situ measurements, however, the seasonal cycle is dampened relative to the surface data illustrating the need for high precision measurements, but also the potential to remove rectifier effects.

Evaluation of chiller modeling approaches and their usability for fault detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sreedharan, Priya

Selecting the model is an important and essential step in model based fault detection and diagnosis (FDD). Several factors must be considered in model evaluation, including accuracy, training data requirements, calibration effort, generality, and computational requirements. All modeling approaches fall somewhere between pure first-principles models, and empirical models. The objective of this study was to evaluate different modeling approaches for their applicability to model based FDD of vapor compression air conditioning units, which are commonly known as chillers. Three different models were studied: two are based on first-principles and the third is empirical in nature. The first-principles models are themore » Gordon and Ng Universal Chiller model (2nd generation), and a modified version of the ASHRAE Primary Toolkit model, which are both based on first principles. The DOE-2 chiller model as implemented in CoolTools{trademark} was selected for the empirical category. The models were compared in terms of their ability to reproduce the observed performance of an older chiller operating in a commercial building, and a newer chiller in a laboratory. The DOE-2 and Gordon-Ng models were calibrated by linear regression, while a direct-search method was used to calibrate the Toolkit model. The ''CoolTools'' package contains a library of calibrated DOE-2 curves for a variety of different chillers, and was used to calibrate the building chiller to the DOE-2 model. All three models displayed similar levels of accuracy. Of the first principles models, the Gordon-Ng model has the advantage of being linear in the parameters, which allows more robust parameter estimation methods to be used and facilitates estimation of the uncertainty in the parameter values. The ASHRAE Toolkit Model may have advantages when refrigerant temperature measurements are also available. The DOE-2 model can be expected to have advantages when very limited data are available to calibrate the model, as long as one of the previously identified models in the CoolTools library matches the performance of the chiller in question.« less

MODFLOW-2000 : the U.S. Geological Survey modular ground-water model--documentation of the Advective-Transport Observation (ADV2) Package

USGS Publications Warehouse

Anderman, Evan R.; Hill, Mary Catherine

2001-01-01

Observations of the advective component of contaminant transport in steady-state flow fields can provide important information for the calibration of ground-water flow models. This report documents the Advective-Transport Observation (ADV2) Package, version 2, which allows advective-transport observations to be used in the three-dimensional ground-water flow parameter-estimation model MODFLOW-2000. The ADV2 Package is compatible with some of the features in the Layer-Property Flow and Hydrogeologic-Unit Flow Packages, but is not compatible with the Block-Centered Flow or Generalized Finite-Difference Packages. The particle-tracking routine used in the ADV2 Package duplicates the semi-analytical method of MODPATH, as shown in a sample problem. Particles can be tracked in a forward or backward direction, and effects such as retardation can be simulated through manipulation of the effective-porosity value used to calculate velocity. Particles can be discharged at cells that are considered to be weak sinks, in which the sink applied does not capture all the water flowing into the cell, using one of two criteria: (1) if there is any outflow to a boundary condition such as a well or surface-water feature, or (2) if the outflow exceeds a user specified fraction of the cell budget. Although effective porosity could be included as a parameter in the regression, this capability is not included in this package. The weighted sum-of-squares objective function, which is minimized in the Parameter-Estimation Process, was augmented to include the square of the weighted x-, y-, and z-components of the differences between the simulated and observed advective-front locations at defined times, thereby including the direction of travel as well as the overall travel distance in the calibration process. The sensitivities of the particle movement to the parameters needed to minimize the objective function are calculated for any particle location using the exact sensitivity-equation approach; the equations are derived by taking the partial derivatives of the semi-analytical particle-tracking equation with respect to the parameters. The ADV2 Package is verified by showing that parameter estimation using advective-transport observations produces the true parameter values in a small but complicated test case when exact observations are used. To demonstrate how the ADV2 Package can be used in practice, a field application is presented. In this application, the ADV2 Package is used first in the Sensitivity-Analysis mode of MODFLOW-2000 to calculate measures of the importance of advective-transport observations relative to head-dependent flow observations when either or both are used in conjunction with hydraulic-head observations in a simulation of the sewage-discharge plume at Cape Cod, Massachusetts. The ADV2 Package is then used in the Parameter-Estimation mode of MODFLOW-2000 to determine best-fit parameter values. It is concluded that, for this problem, advective-transport observations improved the calibration of the model and the estimation of ground-water flow parameters, and the use of formal parameter-estimation methods and related techniques produced significant insight into the physical system.

Use of Multi-class Empirical Orthogonal Function for Identification of Hydrogeological Parameters and Spatiotemporal Pattern of Multiple Recharges in Groundwater Modeling

NASA Astrophysics Data System (ADS)

Huang, C. L.; Hsu, N. S.; Yeh, W. W. G.; Hsieh, I. H.

2017-12-01

This study develops an innovative calibration method for regional groundwater modeling by using multi-class empirical orthogonal functions (EOFs). The developed method is an iterative approach. Prior to carrying out the iterative procedures, the groundwater storage hydrographs associated with the observation wells are calculated. The combined multi-class EOF amplitudes and EOF expansion coefficients of the storage hydrographs are then used to compute the initial gauss of the temporal and spatial pattern of multiple recharges. The initial guess of the hydrogeological parameters are also assigned according to in-situ pumping experiment. The recharges include net rainfall recharge and boundary recharge, and the hydrogeological parameters are riverbed leakage conductivity, horizontal hydraulic conductivity, vertical hydraulic conductivity, storage coefficient, and specific yield. The first step of the iterative algorithm is to conduct the numerical model (i.e. MODFLOW) by the initial guess / adjusted values of the recharges and parameters. Second, in order to determine the best EOF combination of the error storage hydrographs for determining the correction vectors, the objective function is devised as minimizing the root mean square error (RMSE) of the simulated storage hydrographs. The error storage hydrograph are the differences between the storage hydrographs computed from observed and simulated groundwater level fluctuations. Third, adjust the values of recharges and parameters and repeat the iterative procedures until the stopping criterion is reached. The established methodology was applied to the groundwater system of Ming-Chu Basin, Taiwan. The study period is from January 1st to December 2ed in 2012. Results showed that the optimal EOF combination for the multiple recharges and hydrogeological parameters can decrease the RMSE of the simulated storage hydrographs dramatically within three calibration iterations. It represents that the iterative approach that using EOF techniques can capture the groundwater flow tendency and detects the correction vector of the simulated error sources. Hence, the established EOF-based methodology can effectively and accurately identify the multiple recharges and hydrogeological parameters.

Comparison of laser ablation and dried solution aerosol as sampling systems in inductively coupled plasma mass spectrometry.

PubMed

Coedo, A G; Padilla, I; Dorado, M T

2004-12-01

This paper describes a study designed to determine the possibility of using a dried aerosol solution for calibration in laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). The relative sensitivities of tested materials mobilized by laser ablation and by aqueous nebulization were established, and the experimentally determined relative sensitivity factors (RSFs) were used in conjunction with aqueous calibration for the analysis of solid steel samples. To such a purpose a set of CRM carbon steel samples (SS-451/1 to SS-460/1) were sampled into an ICP-MS instrument by solution nebulization using a microconcentric nebulizer with membrane desolvating (D-MCN) and by laser ablation (LA). Both systems were applied with the same ICP-MS operating parameters and the analyte signals were compared. The RSF (desolvated aerosol response/ablated solid response) values were close to 1 for the analytes Cr, Ni, Co, V, and W, about 1.3 for Mo, and 1.7 for As, P, and Mn. Complementary tests were carried out using CRM SS-455/1 as a solid standard for one-point calibration, applying LAMTRACE software for data reduction and quantification. The analytical results are in good agreement with the certified values in all cases, showing that the applicability of dried aerosol solutions is a good alternative calibration system for laser ablation sampling.

Local sensitivity analysis for inverse problems solved by singular value decomposition

USGS Publications Warehouse

Hill, M.C.; Nolan, B.T.

2010-01-01

Local sensitivity analysis provides computationally frugal ways to evaluate models commonly used for resource management, risk assessment, and so on. This includes diagnosing inverse model convergence problems caused by parameter insensitivity and(or) parameter interdependence (correlation), understanding what aspects of the model and data contribute to measures of uncertainty, and identifying new data likely to reduce model uncertainty. Here, we consider sensitivity statistics relevant to models in which the process model parameters are transformed using singular value decomposition (SVD) to create SVD parameters for model calibration. The statistics considered include the PEST identifiability statistic, and combined use of the process-model parameter statistics composite scaled sensitivities and parameter correlation coefficients (CSS and PCC). The statistics are complimentary in that the identifiability statistic integrates the effects of parameter sensitivity and interdependence, while CSS and PCC provide individual measures of sensitivity and interdependence. PCC quantifies correlations between pairs or larger sets of parameters; when a set of parameters is intercorrelated, the absolute value of PCC is close to 1.00 for all pairs in the set. The number of singular vectors to include in the calculation of the identifiability statistic is somewhat subjective and influences the statistic. To demonstrate the statistics, we use the USDA’s Root Zone Water Quality Model to simulate nitrogen fate and transport in the unsaturated zone of the Merced River Basin, CA. There are 16 log-transformed process-model parameters, including water content at field capacity (WFC) and bulk density (BD) for each of five soil layers. Calibration data consisted of 1,670 observations comprising soil moisture, soil water tension, aqueous nitrate and bromide concentrations, soil nitrate concentration, and organic matter content. All 16 of the SVD parameters could be estimated by regression based on the range of singular values. Identifiability statistic results varied based on the number of SVD parameters included. Identifiability statistics calculated for four SVD parameters indicate the same three most important process-model parameters as CSS/PCC (WFC1, WFC2, and BD2), but the order differed. Additionally, the identifiability statistic showed that BD1 was almost as dominant as WFC1. The CSS/PCC analysis showed that this results from its high correlation with WCF1 (-0.94), and not its individual sensitivity. Such distinctions, combined with analysis of how high correlations and(or) sensitivities result from the constructed model, can produce important insights into, for example, the use of sensitivity analysis to design monitoring networks. In conclusion, the statistics considered identified similar important parameters. They differ because (1) with CSS/PCC can be more awkward because sensitivity and interdependence are considered separately and (2) identifiability requires consideration of how many SVD parameters to include. A continuing challenge is to understand how these computationally efficient methods compare with computationally demanding global methods like Markov-Chain Monte Carlo given common nonlinear processes and the often even more nonlinear models.

Multi-objective Calibration of DHSVM Based on Hydrologic Key Elements in Jinhua River Basin, East China

NASA Astrophysics Data System (ADS)

Pan, S.; Liu, L.; Xu, Y. P.

2017-12-01

Abstract: In physically based distributed hydrological model, large number of parameters, representing spatial heterogeneity of watershed and various processes in hydrologic cycle, are involved. For lack of calibration module in Distributed Hydrology Soil Vegetation Model, this study developed a multi-objective calibration module using Epsilon-Dominance Non-Dominated Sorted Genetic Algorithm II (ɛ-NSGAII) and based on parallel computing of Linux cluster for DHSVM (ɛP-DHSVM). In this study, two hydrologic key elements (i.e., runoff and evapotranspiration) are used as objectives in multi-objective calibration of model. MODIS evapotranspiration obtained by SEBAL is adopted to fill the gap of lack of observation for evapotranspiration. The results show that good performance of runoff simulation in single objective calibration cannot ensure good simulation performance of other hydrologic key elements. Self-developed ɛP-DHSVM model can make multi-objective calibration more efficiently and effectively. The running speed can be increased by more than 20-30 times via applying ɛP-DHSVM. In addition, runoff and evapotranspiration can be simulated very well simultaneously by ɛP-DHSVM, with superior values for two efficiency coefficients (0.74 for NS of runoff and 0.79 for NS of evapotranspiration, -10.5% and -8.6% for PBIAS of runoff and evapotranspiration respectively).

Demonstration of emulator-based Bayesian calibration of safety analysis codes: Theory and formulation

DOE PAGES

Yurko, Joseph P.; Buongiorno, Jacopo; Youngblood, Robert

2015-05-28

System codes for simulation of safety performance of nuclear plants may contain parameters whose values are not known very accurately. New information from tests or operating experience is incorporated into safety codes by a process known as calibration, which reduces uncertainty in the output of the code and thereby improves its support for decision-making. The work reported here implements several improvements on classic calibration techniques afforded by modern analysis techniques. The key innovation has come from development of code surrogate model (or code emulator) construction and prediction algorithms. Use of a fast emulator makes the calibration processes used here withmore » Markov Chain Monte Carlo (MCMC) sampling feasible. This study uses Gaussian Process (GP) based emulators, which have been used previously to emulate computer codes in the nuclear field. The present work describes the formulation of an emulator that incorporates GPs into a factor analysis-type or pattern recognition-type model. This “function factorization” Gaussian Process (FFGP) model allows overcoming limitations present in standard GP emulators, thereby improving both accuracy and speed of the emulator-based calibration process. Calibration of a friction-factor example using a Method of Manufactured Solution is performed to illustrate key properties of the FFGP based process.« less

ACCOUNTING FOR CALIBRATION UNCERTAINTIES IN X-RAY ANALYSIS: EFFECTIVE AREAS IN SPECTRAL FITTING

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Hyunsook; Kashyap, Vinay L.; Drake, Jeremy J.

2011-04-20

While considerable advance has been made to account for statistical uncertainties in astronomical analyses, systematic instrumental uncertainties have been generally ignored. This can be crucial to a proper interpretation of analysis results because instrumental calibration uncertainty is a form of systematic uncertainty. Ignoring it can underestimate error bars and introduce bias into the fitted values of model parameters. Accounting for such uncertainties currently requires extensive case-specific simulations if using existing analysis packages. Here, we present general statistical methods that incorporate calibration uncertainties into spectral analysis of high-energy data. We first present a method based on multiple imputation that can bemore » applied with any fitting method, but is necessarily approximate. We then describe a more exact Bayesian approach that works in conjunction with a Markov chain Monte Carlo based fitting. We explore methods for improving computational efficiency, and in particular detail a method of summarizing calibration uncertainties with a principal component analysis of samples of plausible calibration files. This method is implemented using recently codified Chandra effective area uncertainties for low-resolution spectral analysis and is verified using both simulated and actual Chandra data. Our procedure for incorporating effective area uncertainty is easily generalized to other types of calibration uncertainties.« less

Exemplifying the Effects of Parameterization Shortcomings in the Numerical Simulation of Geological Energy and Mass Storage

NASA Astrophysics Data System (ADS)

Dethlefsen, Frank; Tilmann Pfeiffer, Wolf; Schäfer, Dirk

2016-04-01

Numerical simulations of hydraulic, thermal, geomechanical, or geochemical (THMC-) processes in the subsurface have been conducted for decades. Often, such simulations are commenced by applying a parameter set that is as realistic as possible. Then, a base scenario is calibrated on field observations. Finally, scenario simulations can be performed, for instance to forecast the system behavior after varying input data. In the context of subsurface energy and mass storage, however, these model calibrations based on field data are often not available, as these storage actions have not been carried out so far. Consequently, the numerical models merely rely on the parameter set initially selected, and uncertainties as a consequence of a lack of parameter values or process understanding may not be perceivable, not mentioning quantifiable. Therefore, conducting THMC simulations in the context of energy and mass storage deserves a particular review of the model parameterization with its input data, and such a review so far hardly exists to the required extent. Variability or aleatory uncertainty exists for geoscientific parameter values in general, and parameters for that numerous data points are available, such as aquifer permeabilities, may be described statistically thereby exhibiting statistical uncertainty. In this case, sensitivity analyses for quantifying the uncertainty in the simulation resulting from varying this parameter can be conducted. There are other parameters, where the lack of data quantity and quality implies a fundamental changing of ongoing processes when such a parameter value is varied in numerical scenario simulations. As an example for such a scenario uncertainty, varying the capillary entry pressure as one of the multiphase flow parameters can either allow or completely inhibit the penetration of an aquitard by gas. As the last example, the uncertainty of cap-rock fault permeabilities and consequently potential leakage rates of stored gases into shallow compartments are regarded as recognized ignorance by the authors of this study, as no realistic approach exists to determine this parameter and values are best guesses only. In addition to these aleatory uncertainties, an equivalent classification is possible for rating epistemic uncertainties describing the degree of understanding processes such as the geochemical and hydraulic effects following potential gas intrusions from deeper reservoirs into shallow aquifers. As an outcome of this grouping of uncertainties, prediction errors of scenario simulations can be calculated by sensitivity analyses, if the uncertainties are identified as statistical. However, if scenario uncertainties exist or even recognized ignorance has to be attested to a parameter or a process in question, the outcomes of simulations mainly depend on the decision of the modeler by choosing parameter values or by interpreting the occurring of processes. In that case, the informative value of numerical simulations is limited by ambiguous simulation results, which cannot be refined without improving the geoscientific database through laboratory or field studies on a longer term basis, so that the effects of the subsurface use may be predicted realistically. This discussion, amended by a compilation of available geoscientific data to parameterize such simulations, will be presented in this study.

Geomorphically based predictive mapping of soil thickness in upland watersheds

NASA Astrophysics Data System (ADS)

Pelletier, Jon D.; Rasmussen, Craig

2009-09-01

The hydrologic response of upland watersheds is strongly controlled by soil (regolith) thickness. Despite the need to quantify soil thickness for input into hydrologic models, there is currently no widely used, geomorphically based method for doing so. In this paper we describe and illustrate a new method for predictive mapping of soil thicknesses using high-resolution topographic data, numerical modeling, and field-based calibration. The model framework works directly with input digital elevation model data to predict soil thicknesses assuming a long-term balance between soil production and erosion. Erosion rates in the model are quantified using one of three geomorphically based sediment transport models: nonlinear slope-dependent transport, nonlinear area- and slope-dependent transport, and nonlinear depth- and slope-dependent transport. The model balances soil production and erosion locally to predict a family of solutions corresponding to a range of values of two unconstrained model parameters. A small number of field-based soil thickness measurements can then be used to calibrate the local value of those unconstrained parameters, thereby constraining which solution is applicable at a particular study site. As an illustration, the model is used to predictively map soil thicknesses in two small, ˜0.1 km2, drainage basins in the Marshall Gulch watershed, a semiarid drainage basin in the Santa Catalina Mountains of Pima County, Arizona. Field observations and calibration data indicate that the nonlinear depth- and slope-dependent sediment transport model is the most appropriate transport model for this site. The resulting framework provides a generally applicable, geomorphically based tool for predictive mapping of soil thickness using high-resolution topographic data sets.

Calibration of hydrological model with programme PEST

NASA Astrophysics Data System (ADS)

Brilly, Mitja; Vidmar, Andrej; Kryžanowski, Andrej; Bezak, Nejc; Šraj, Mojca

2016-04-01

PEST is tool based on minimization of an objective function related to the root mean square error between the model output and the measurement. We use "singular value decomposition", section of the PEST control file, and Tikhonov regularization method for successfully estimation of model parameters. The PEST sometimes failed if inverse problems were ill-posed, but (SVD) ensures that PEST maintains numerical stability. The choice of the initial guess for the initial parameter values is an important issue in the PEST and need expert knowledge. The flexible nature of the PEST software and its ability to be applied to whole catchments at once give results of calibration performed extremely well across high number of sub catchments. Use of parallel computing version of PEST called BeoPEST was successfully useful to speed up calibration process. BeoPEST employs smart slaves and point-to-point communications to transfer data between the master and slaves computers. The HBV-light model is a simple multi-tank-type model for simulating precipitation-runoff. It is conceptual balance model of catchment hydrology which simulates discharge using rainfall, temperature and estimates of potential evaporation. Version of HBV-light-CLI allows the user to run HBV-light from the command line. Input and results files are in XML form. This allows to easily connecting it with other applications such as pre and post-processing utilities and PEST itself. The procedure was applied on hydrological model of Savinja catchment (1852 km2) and consists of twenty one sub-catchments. Data are temporary processed on hourly basis.

Using floating car data to analyse the effects of its measures and eco-driving.

PubMed

Garcia-Castro, Alvaro; Monzon, Andres

2014-11-11

The road transportation sector is responsible for around 25% of total man-made CO2 emissions worldwide. Considerable efforts are therefore underway to reduce these emissions using several approaches, including improved vehicle technologies, traffic management and changing driving behaviour. Detailed traffic and emissions models are used extensively to assess the potential effects of these measures. However, if the input and calibration data are not sufficiently detailed there is an inherent risk that the results may be inaccurate. This article presents the use of Floating Car Data to derive useful speed and acceleration values in the process of traffic model calibration as a means of ensuring more accurate results when simulating the effects of particular measures. The data acquired includes instantaneous GPS coordinates to track and select the itineraries, and speed and engine performance extracted directly from the on-board diagnostics system. Once the data is processed, the variations in several calibration parameters can be analyzed by comparing the base case model with the measure application scenarios. Depending on the measure, the results show changes of up to 6.4% in maximum speed values, and reductions of nearly 15% in acceleration and braking levels, especially when eco-driving is applied.

Using Floating Car Data to Analyse the Effects of ITS Measures and Eco-Driving

PubMed Central

Garcia-Castro, Alvaro; Monzon, Andres

2014-01-01

The road transportation sector is responsible for around 25% of total man-made CO2 emissions worldwide. Considerable efforts are therefore underway to reduce these emissions using several approaches, including improved vehicle technologies, traffic management and changing driving behaviour. Detailed traffic and emissions models are used extensively to assess the potential effects of these measures. However, if the input and calibration data are not sufficiently detailed there is an inherent risk that the results may be inaccurate. This article presents the use of Floating Car Data to derive useful speed and acceleration values in the process of traffic model calibration as a means of ensuring more accurate results when simulating the effects of particular measures. The data acquired includes instantaneous GPS coordinates to track and select the itineraries, and speed and engine performance extracted directly from the on-board diagnostics system. Once the data is processed, the variations in several calibration parameters can be analyzed by comparing the base case model with the measure application scenarios. Depending on the measure, the results show changes of up to 6.4% in maximum speed values, and reductions of nearly 15% in acceleration and braking levels, especially when eco-driving is applied. PMID:25393787

3D artifact for calibrating kinematic parameters of articulated arm coordinate measuring machines

NASA Astrophysics Data System (ADS)

Zhao, Huining; Yu, Liandong; Xia, Haojie; Li, Weishi; Jiang, Yizhou; Jia, Huakun

2018-06-01

In this paper, a 3D artifact is proposed to calibrate the kinematic parameters of articulated arm coordinate measuring machines (AACMMs). The artifact is composed of 14 reference points with three different heights, which provides 91 different reference lengths, and a method is proposed to calibrate the artifact with laser tracker multi-stations. Therefore, the kinematic parameters of an AACMM can be calibrated in one setup of the proposed artifact, instead of having to adjust the 1D or 2D artifacts to different positions and orientations in the existing methods. As a result, it saves time to calibrate the AACMM with the proposed artifact in comparison with the traditional 1D or 2D artifacts. The performance of the AACMM calibrated with the proposed artifact is verified with a 600.003 mm gauge block. The result shows that the measurement accuracy of the AACMM is improved effectively through calibration with the proposed artifact.

DEM Calibration Approach: design of experiment

NASA Astrophysics Data System (ADS)

Boikov, A. V.; Savelev, R. V.; Payor, V. A.

2018-05-01

The problem of DEM models calibration is considered in the article. It is proposed to divide models input parameters into those that require iterative calibration and those that are recommended to measure directly. A new method for model calibration based on the design of the experiment for iteratively calibrated parameters is proposed. The experiment is conducted using a specially designed stand. The results are processed with technical vision algorithms. Approximating functions are obtained and the error of the implemented software and hardware complex is estimated. The prospects of the obtained results are discussed.

Modelling the impact of vegetation on marly catchments in the Southern Alps of France

NASA Astrophysics Data System (ADS)

Carriere, Alexandra; Le Bouteiller, Caroline; Tucker, Greg; Naaim, Mohamed

2017-04-01

The Southern Alps of France have been identified as a hot-spot in a global climate change context where the rainfall intensity increase may exacerbate the erosion of already badly erodible lands: Badlands. Vegetalization methods are a promising area of research for erosion control and slope and riverbed stabilization. Nevertheless the impact of vegetation on erosive dynamics is still poorly understood. We own data collected over the last thirty years on marly catchments in the Southern Alps of France from the Draix-Bléone Observatory, part of the Network of Drainage Basins RBV. These are temporal data of sedimentary flux at the scale of the precipitation event but also more recent topographic data on watersheds with areas ranging from 10-3 square kilometers to twenty square kilometers. Erosion rates in this landscape reach 1 cm per year. We simulate the topographic evolution of the catchments over a few decades to centuries with the landscape evolution model Landlab, using our data to calibrate and explicitly validate the model. This model, in comparison with other landscape evolution models, incorporates a more advanced vegetation module in terms of ecology. Nevertheless the erosion-vegetation coupling is not present in Landlab and we are working on its construction. To this end we use an erosion module and a vegetation module that we seek to couple. We want to see how the erosion laws parameters depend on the vegetation cover. We have implemented the calibration of parameters of a non-linear diffusion module coupled with a transport-limited law by comparing the simulated annual sediment flux with the one of the data of the observatory as a function of the percentage of vegetation cover of the ground. We obtained average values of parameters adjusted according to vegetation cover. We observe that the values of the erosion laws parameters are strongly affected by the percentage of vegetation cover. We will then spatialize these parameters on our vegetation maps in order to obtain different parameter values for different types of vegetation.

40 CFR Appendix I to Part 92 - Emission Related Locomotive and Engine Parameters and Specifications

Code of Federal Regulations, 2011 CFR

2011-07-01

... injection—non-compression ignition engines. a. Control parameters and calibrations. b. Idle mixture. c. Fuel...(s). i. Injector timing calibration. 4. Fuel injection—compression ignition engines. a. Control... restriction. III. Fuel System. 1. General. a. Engine idle speed. 2. Carburetion. a. Air-fuel flow calibration...

40 CFR Appendix I to Part 92 - Emission Related Locomotive and Engine Parameters and Specifications

Code of Federal Regulations, 2014 CFR

2014-07-01

... injection—non-compression ignition engines. a. Control parameters and calibrations. b. Idle mixture. c. Fuel...(s). i. Injector timing calibration. 4. Fuel injection—compression ignition engines. a. Control... restriction. III. Fuel System. 1. General. a. Engine idle speed. 2. Carburetion. a. Air-fuel flow calibration...

40 CFR Appendix I to Part 92 - Emission Related Locomotive and Engine Parameters and Specifications

Code of Federal Regulations, 2013 CFR

2013-07-01

... injection—non-compression ignition engines. a. Control parameters and calibrations. b. Idle mixture. c. Fuel...(s). i. Injector timing calibration. 4. Fuel injection—compression ignition engines. a. Control... restriction. III. Fuel System. 1. General. a. Engine idle speed. 2. Carburetion. a. Air-fuel flow calibration...

40 CFR Appendix I to Part 92 - Emission Related Locomotive and Engine Parameters and Specifications

Code of Federal Regulations, 2012 CFR

2012-07-01

... injection—non-compression ignition engines. a. Control parameters and calibrations. b. Idle mixture. c. Fuel...(s). i. Injector timing calibration. 4. Fuel injection—compression ignition engines. a. Control... restriction. III. Fuel System. 1. General. a. Engine idle speed. 2. Carburetion. a. Air-fuel flow calibration...

Parameter estimation for groundwater models under uncertain irrigation data

USGS Publications Warehouse

Demissie, Yonas; Valocchi, Albert J.; Cai, Ximing; Brozovic, Nicholas; Senay, Gabriel; Gebremichael, Mekonnen

2015-01-01

The success of modeling groundwater is strongly influenced by the accuracy of the model parameters that are used to characterize the subsurface system. However, the presence of uncertainty and possibly bias in groundwater model source/sink terms may lead to biased estimates of model parameters and model predictions when the standard regression-based inverse modeling techniques are used. This study first quantifies the levels of bias in groundwater model parameters and predictions due to the presence of errors in irrigation data. Then, a new inverse modeling technique called input uncertainty weighted least-squares (IUWLS) is presented for unbiased estimation of the parameters when pumping and other source/sink data are uncertain. The approach uses the concept of generalized least-squares method with the weight of the objective function depending on the level of pumping uncertainty and iteratively adjusted during the parameter optimization process. We have conducted both analytical and numerical experiments, using irrigation pumping data from the Republican River Basin in Nebraska, to evaluate the performance of ordinary least-squares (OLS) and IUWLS calibration methods under different levels of uncertainty of irrigation data and calibration conditions. The result from the OLS method shows the presence of statistically significant (p < 0.05) bias in estimated parameters and model predictions that persist despite calibrating the models to different calibration data and sample sizes. However, by directly accounting for the irrigation pumping uncertainties during the calibration procedures, the proposed IUWLS is able to minimize the bias effectively without adding significant computational burden to the calibration processes.

Classical vs. evolved quenching parameters and procedures in scintillation measurements: The importance of ionization quenching

NASA Astrophysics Data System (ADS)

Bagán, H.; Tarancón, A.; Rauret, G.; García, J. F.

2008-07-01

The quenching parameters used to model detection efficiency variations in scintillation measurements have not evolved since the decade of 1970s. Meanwhile, computer capabilities have increased enormously and ionization quenching has appeared in practical measurements using plastic scintillation. This study compares the results obtained in activity quantification by plastic scintillation of 14C samples that contain colour and ionization quenchers, using classical (SIS, SCR-limited, SCR-non-limited, SIS(ext), SQP(E)) and evolved (MWA-SCR and WDW) parameters and following three calibration approaches: single step, which does not take into account the quenching mechanism; two steps, which takes into account the quenching phenomena; and multivariate calibration. Two-step calibration (ionization followed by colour) yielded the lowest relative errors, which means that each quenching phenomenon must be specifically modelled. In addition, the sample activity was quantified more accurately when the evolved parameters were used. Multivariate calibration-PLS also yielded better results than those obtained using classical parameters, which confirms that the quenching phenomena must be taken into account. The detection limits for each calibration method and each parameter were close to those obtained theoretically using the Currie approach.

The new camera calibration system at the US Geological Survey

USGS Publications Warehouse

Light, D.L.

1992-01-01

Modern computerized photogrammetric instruments are capable of utilizing both radial and decentering camera calibration parameters which can increase plotting accuracy over that of older analog instrumentation technology from previous decades. Also, recent design improvements in aerial cameras have minimized distortions and increased the resolving power of camera systems, which should improve the performance of the overall photogrammetric process. In concert with these improvements, the Geological Survey has adopted the rigorous mathematical model for camera calibration developed by Duane Brown. An explanation of the Geological Survey's calibration facility and the additional calibration parameters now being provided in the USGS calibration certificate are reviewed. -Author

Radiometrie recalibration procedure for landsat-5 thematic mapper data

USGS Publications Warehouse

Chander, G.; Micijevic, E.; Hayes, R.W.; Barsi, J.A.

2008-01-01

The Landsat-5 (L5) satellite was launched on March 01, 1984, with a design life of three years. Incredibly, the L5 Thematic Mapper (TM) has collected data for 23 years. Over this time, the detectors have aged, and its radiometric characteristics have changed since launch. The calibration procedures and parameters have also changed with time. Revised radiometric calibrations have improved the radiometric accuracy of recently processed data; however, users with data that were processed prior to the calibration update do not benefit from the revisions. A procedure has been developed to give users the ability to recalibrate their existing Level 1 (L1) products without having to purchase reprocessed data from the U.S. Geological Survey (USGS). The accuracy of the recalibration is dependent on the knowledge of the prior calibration applied to the data. The ""Work Order" file, included with standard National Land Archive Production System (NLAFS) data products, gives parameters that define the applied calibration. These are the Internal Calibrator (IC) calibration parameters or the default prelaunch calibration, if there were problems with the IC calibration. This paper details the recalibration procedure for data processed using IC, in which users have the Work Order file. ?? 2001 IEEE.

Exploration of DGVM Parameter Solution Space Using Simulated Annealing: Implications for Forecast Uncertainties

NASA Astrophysics Data System (ADS)

Wells, J. R.; Kim, J. B.

2011-12-01

Parameters in dynamic global vegetation models (DGVMs) are thought to be weakly constrained and can be a significant source of errors and uncertainties. DGVMs use between 5 and 26 plant functional types (PFTs) to represent the average plant life form in each simulated plot, and each PFT typically has a dozen or more parameters that define the way it uses resource and responds to the simulated growing environment. Sensitivity analysis explores how varying parameters affects the output, but does not do a full exploration of the parameter solution space. The solution space for DGVM parameter values are thought to be complex and non-linear; and multiple sets of acceptable parameters may exist. In published studies, PFT parameters are estimated from published literature, and often a parameter value is estimated from a single published value. Further, the parameters are "tuned" using somewhat arbitrary, "trial-and-error" methods. BIOMAP is a new DGVM created by fusing MAPSS biogeography model with Biome-BGC. It represents the vegetation of North America using 26 PFTs. We are using simulated annealing, a global search method, to systematically and objectively explore the solution space for the BIOMAP PFTs and system parameters important for plant water use. We defined the boundaries of the solution space by obtaining maximum and minimum values from published literature, and where those were not available, using +/-20% of current values. We used stratified random sampling to select a set of grid cells representing the vegetation of the conterminous USA. Simulated annealing algorithm is applied to the parameters for spin-up and a transient run during the historical period 1961-1990. A set of parameter values is considered acceptable if the associated simulation run produces a modern potential vegetation distribution map that is as accurate as one produced by trial-and-error calibration. We expect to confirm that the solution space is non-linear and complex, and that multiple acceptable parameter sets exist. Further we expect to demonstrate that the multiple parameter sets produce significantly divergent future forecasts in NEP, C storage, and ET and runoff; and thereby identify a highly important source of DGVM uncertainty

How does higher frequency monitoring data affect the calibration of a process-based water quality model?

NASA Astrophysics Data System (ADS)

Jackson-Blake, Leah; Helliwell, Rachel

2015-04-01

Process-based catchment water quality models are increasingly used as tools to inform land management. However, for such models to be reliable they need to be well calibrated and shown to reproduce key catchment processes. Calibration can be challenging for process-based models, which tend to be complex and highly parameterised. Calibrating a large number of parameters generally requires a large amount of monitoring data, spanning all hydrochemical conditions. However, regulatory agencies and research organisations generally only sample at a fortnightly or monthly frequency, even in well-studied catchments, often missing peak flow events. The primary aim of this study was therefore to investigate how the quality and uncertainty of model simulations produced by a process-based, semi-distributed catchment model, INCA-P (the INtegrated CAtchment model of Phosphorus dynamics), were improved by calibration to higher frequency water chemistry data. Two model calibrations were carried out for a small rural Scottish catchment: one using 18 months of daily total dissolved phosphorus (TDP) concentration data, another using a fortnightly dataset derived from the daily data. To aid comparability, calibrations were carried out automatically using the Markov Chain Monte Carlo - DiffeRential Evolution Adaptive Metropolis (MCMC-DREAM) algorithm. Calibration to daily data resulted in improved simulation of peak TDP concentrations and improved model performance statistics. Parameter-related uncertainty in simulated TDP was large when fortnightly data was used for calibration, with a 95% credible interval of 26 μg/l. This uncertainty is comparable in size to the difference between Water Framework Directive (WFD) chemical status classes, and would therefore make it difficult to use this calibration to predict shifts in WFD status. The 95% credible interval reduced markedly with the higher frequency monitoring data, to 6 μg/l. The number of parameters that could be reliably auto-calibrated was lower for the fortnightly data, with a physically unrealistic TDP simulation being produced when too many parameters were allowed to vary during model calibration. Parameters should not therefore be varied spatially for models such as INCA-P unless there is solid evidence that this is appropriate, or there is a real need to do so for the model to fulfil its purpose. This study highlights the potential pitfalls of using low frequency timeseries of observed water quality to calibrate complex process-based models. For reliable model calibrations to be produced, monitoring programmes need to be designed which capture system variability, in particular nutrient dynamics during high flow events. In addition, there is a need for simpler models, so that all model parameters can be included in auto-calibration and uncertainty analysis, and to reduce the data needs during calibration.

Accuracy and calibration of integrated radiation output indicators in diagnostic radiology: A report of the AAPM Imaging Physics Committee Task Group 190

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, Pei-Jan P., E-mail: Pei-Jan.Lin@vcuhealth.org; Schueler, Beth A.; Balter, Stephen

2015-12-15

Due to the proliferation of disciplines employing fluoroscopy as their primary imaging tool and the prolonged extensive use of fluoroscopy in interventional and cardiovascular angiography procedures, “dose-area-product” (DAP) meters were installed to monitor and record the radiation dose delivered to patients. In some cases, the radiation dose or the output value is calculated, rather than measured, using the pertinent radiological parameters and geometrical information. The AAPM Task Group 190 (TG-190) was established to evaluate the accuracy of the DAP meter in 2008. Since then, the term “DAP-meter” has been revised to air kerma-area product (KAP) meter. The charge of TGmore » 190 (Accuracy and Calibration of Integrated Radiation Output Indicators in Diagnostic Radiology) has also been realigned to investigate the “Accuracy and Calibration of Integrated Radiation Output Indicators” which is reflected in the title of the task group, to include situations where the KAP may be acquired with or without the presence of a physical “meter.” To accomplish this goal, validation test protocols were developed to compare the displayed radiation output value to an external measurement. These test protocols were applied to a number of clinical systems to collect information on the accuracy of dose display values in the field.« less

Preflight calibration of the Imaging Magnetograph eXperiment polarization modulation package based on liquid-crystal variable retarders.

PubMed

Uribe-Patarroyo, Néstor; Alvarez-Herrero, Alberto; Martínez Pillet, Valentín

2012-07-20

We present the study, characterization, and calibration of the polarization modulation package (PMP) of the Imaging Magnetograph eXperiment (IMaX) instrument, a successful Stokes spectropolarimeter on board the SUNRISE balloon project within the NASA Long Duration Balloon program. IMaX was designed to measure the Stokes parameters of incoming light with a signal-to-noise ratio of at least 10³, using as polarization modulators two nematic liquid-crystal variable retarders (LCVRs). An ad hoc calibration system that reproduced the optical and environmental characteristics of IMaX was designed, assembled, and aligned. The system recreates the optical beam that IMaX receives from SUNRISE with known polarization across the image plane, as well as an optical system with the same characteristics of IMaX. The system was used to calibrate the IMaX PMP in vacuum and at different temperatures, with a thermal control resembling the in-flight one. The efficiencies obtained were very high, near theoretical maximum values: the total efficiency in vacuum calibration at nominal temperature was 0.972 (1 being the theoretical maximum). The condition number of the demodulation matrix of the same calibration was 0.522 (0.577 theoretical maximum). Some inhomogeneities of the LCVRs were clear during the pixel-by-pixel calibration of the PMP, but it can be concluded that the mere information of a pixel-per-pixel calibration is sufficient to maintain high efficiencies in spite of inhomogeneities of the LCVRs.

Planck 2015 results. XXIV. Cosmology from Sunyaev-Zeldovich cluster counts

NASA Astrophysics Data System (ADS)

Planck Collaboration; Ade, P. A. R.; Aghanim, N.; Arnaud, M.; Ashdown, M.; Aumont, J.; Baccigalupi, C.; Banday, A. J.; Barreiro, R. B.; Bartlett, J. G.; Bartolo, N.; Battaner, E.; Battye, R.; Benabed, K.; Benoît, A.; Benoit-Lévy, A.; Bernard, J.-P.; Bersanelli, M.; Bielewicz, P.; Bock, J. J.; Bonaldi, A.; Bonavera, L.; Bond, J. R.; Borrill, J.; Bouchet, F. R.; Bucher, M.; Burigana, C.; Butler, R. C.; Calabrese, E.; Cardoso, J.-F.; Catalano, A.; Challinor, A.; Chamballu, A.; Chary, R.-R.; Chiang, H. C.; Christensen, P. R.; Church, S.; Clements, D. L.; Colombi, S.; Colombo, L. P. L.; Combet, C.; Comis, B.; Couchot, F.; Coulais, A.; Crill, B. P.; Curto, A.; Cuttaia, F.; Danese, L.; Davies, R. D.; Davis, R. J.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Désert, F.-X.; Diego, J. M.; Dolag, K.; Dole, H.; Donzelli, S.; Doré, O.; Douspis, M.; Ducout, A.; Dupac, X.; Efstathiou, G.; Elsner, F.; Enßlin, T. A.; Eriksen, H. K.; Falgarone, E.; Fergusson, J.; Finelli, F.; Forni, O.; Frailis, M.; Fraisse, A. A.; Franceschi, E.; Frejsel, A.; Galeotta, S.; Galli, S.; Ganga, K.; Giard, M.; Giraud-Héraud, Y.; Gjerløw, E.; González-Nuevo, J.; Górski, K. M.; Gratton, S.; Gregorio, A.; Gruppuso, A.; Gudmundsson, J. E.; Hansen, F. K.; Hanson, D.; Harrison, D. L.; Henrot-Versillé, S.; Hernández-Monteagudo, C.; Herranz, D.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Holmes, W. A.; Hornstrup, A.; Hovest, W.; Huffenberger, K. M.; Hurier, G.; Jaffe, A. H.; Jaffe, T. R.; Jones, W. C.; Juvela, M.; Keihänen, E.; Keskitalo, R.; Kisner, T. S.; Kneissl, R.; Knoche, J.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lähteenmäki, A.; Lamarre, J.-M.; Lasenby, A.; Lattanzi, M.; Lawrence, C. R.; Leonardi, R.; Lesgourgues, J.; Levrier, F.; Liguori, M.; Lilje, P. B.; Linden-Vørnle, M.; López-Caniego, M.; Lubin, P. M.; Macías-Pérez, J. F.; Maggio, G.; Maino, D.; Mandolesi, N.; Mangilli, A.; Maris, M.; Martin, P. G.; Martínez-González, E.; Masi, S.; Matarrese, S.; McGehee, P.; Meinhold, P. R.; Melchiorri, A.; Melin, J.-B.; Mendes, L.; Mennella, A.; Migliaccio, M.; Mitra, S.; Miville-Deschênes, M.-A.; Moneti, A.; Montier, L.; Morgante, G.; Mortlock, D.; Moss, A.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Nati, F.; Natoli, P.; Netterfield, C. B.; Nørgaard-Nielsen, H. U.; Noviello, F.; Novikov, D.; Novikov, I.; Oxborrow, C. A.; Paci, F.; Pagano, L.; Pajot, F.; Paoletti, D.; Partridge, B.; Pasian, F.; Patanchon, G.; Pearson, T. J.; Perdereau, O.; Perotto, L.; Perrotta, F.; Pettorino, V.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Pietrobon, D.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Popa, L.; Pratt, G. W.; Prézeau, G.; Prunet, S.; Puget, J.-L.; Rachen, J. P.; Rebolo, R.; Reinecke, M.; Remazeilles, M.; Renault, C.; Renzi, A.; Ristorcelli, I.; Rocha, G.; Roman, M.; Rosset, C.; Rossetti, M.; Roudier, G.; Rubiño-Martín, J. A.; Rusholme, B.; Sandri, M.; Santos, D.; Savelainen, M.; Savini, G.; Scott, D.; Seiffert, M. D.; Shellard, E. P. S.; Spencer, L. D.; Stolyarov, V.; Stompor, R.; Sudiwala, R.; Sunyaev, R.; Sutton, D.; Suur-Uski, A.-S.; Sygnet, J.-F.; Tauber, J. A.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tristram, M.; Tucci, M.; Tuovinen, J.; Türler, M.; Umana, G.; Valenziano, L.; Valiviita, J.; Van Tent, B.; Vielva, P.; Villa, F.; Wade, L. A.; Wandelt, B. D.; Wehus, I. K.; Weller, J.; White, S. D. M.; Yvon, D.; Zacchei, A.; Zonca, A.

2016-09-01

We present cluster counts and corresponding cosmological constraints from the Planck full mission data set. Our catalogue consists of 439 clusters detected via their Sunyaev-Zeldovich (SZ) signal down to a signal-to-noise ratio of 6, and is more than a factor of 2 larger than the 2013 Planck cluster cosmology sample. The counts are consistent with those from 2013 and yield compatible constraints under the same modelling assumptions. Taking advantage of the larger catalogue, we extend our analysis to the two-dimensional distribution in redshift and signal-to-noise. We use mass estimates from two recent studies of gravitational lensing of background galaxies by Planck clusters to provide priors on the hydrostatic bias parameter, (1-b). In addition, we use lensing of cosmic microwave background (CMB) temperature fluctuations by Planck clusters as an independent constraint on this parameter. These various calibrations imply constraints on the present-day amplitude of matter fluctuations in varying degrees of tension with those from the Planck analysis of primary fluctuations in the CMB; for the lowest estimated values of (1-b) the tension is mild, only a little over one standard deviation, while it remains substantial (3.7σ) for the largest estimated value. We also examine constraints on extensions to the base flat ΛCDM model by combining the cluster and CMB constraints. The combination appears to favour non-minimal neutrino masses, but this possibility does little to relieve the overall tension because it simultaneously lowers the implied value of the Hubble parameter, thereby exacerbating the discrepancy with most current astrophysical estimates. Improving the precision of cluster mass calibrations from the current 10%-level to 1% would significantly strengthen these combined analyses and provide a stringent test of the base ΛCDM model.

Planck 2015 results: XXIV. Cosmology from Sunyaev-Zeldovich cluster counts

DOE PAGES

Ade, P. A. R.; Aghanim, N.; Arnaud, M.; ...

2016-09-20

In this work, we present cluster counts and corresponding cosmological constraints from the Planck full mission data set. Our catalogue consists of 439 clusters detected via their Sunyaev-Zeldovich (SZ) signal down to a signal-to-noise ratio of 6, and is more than a factor of 2 larger than the 2013 Planck cluster cosmology sample. The counts are consistent with those from 2013 and yield compatible constraints under the same modelling assumptions. Taking advantage of the larger catalogue, we extend our analysis to the two-dimensional distribution in redshift and signal-to-noise. We use mass estimates from two recent studies of gravitational lensing ofmore » background galaxies by Planck clusters to provide priors on the hydrostatic bias parameter, (1-b). In addition, we use lensing of cosmic microwave background (CMB) temperature fluctuations by Planck clusters as an independent constraint on this parameter. These various calibrations imply constraints on the present-day amplitude of matter fluctuations in varying degrees of tension with those from the Planck analysis of primary fluctuations in the CMB; for the lowest estimated values of (1-b) the tension is mild, only a little over one standard deviation, while it remains substantial (3.7σ) for the largest estimated value. We also examine constraints on extensions to the base flat ΛCDM model by combining the cluster and CMB constraints. The combination appears to favour non-minimal neutrino masses, but this possibility does little to relieve the overall tension because it simultaneously lowers the implied value of the Hubble parameter, thereby exacerbating the discrepancy with most current astrophysical estimates. In conclusion, improving the precision of cluster mass calibrations from the current 10%-level to 1% would significantly strengthen these combined analyses and provide a stringent test of the base ΛCDM model.« less

Planck 2015 results: XXIV. Cosmology from Sunyaev-Zeldovich cluster counts

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ade, P. A. R.; Aghanim, N.; Arnaud, M.

In this work, we present cluster counts and corresponding cosmological constraints from the Planck full mission data set. Our catalogue consists of 439 clusters detected via their Sunyaev-Zeldovich (SZ) signal down to a signal-to-noise ratio of 6, and is more than a factor of 2 larger than the 2013 Planck cluster cosmology sample. The counts are consistent with those from 2013 and yield compatible constraints under the same modelling assumptions. Taking advantage of the larger catalogue, we extend our analysis to the two-dimensional distribution in redshift and signal-to-noise. We use mass estimates from two recent studies of gravitational lensing ofmore » background galaxies by Planck clusters to provide priors on the hydrostatic bias parameter, (1-b). In addition, we use lensing of cosmic microwave background (CMB) temperature fluctuations by Planck clusters as an independent constraint on this parameter. These various calibrations imply constraints on the present-day amplitude of matter fluctuations in varying degrees of tension with those from the Planck analysis of primary fluctuations in the CMB; for the lowest estimated values of (1-b) the tension is mild, only a little over one standard deviation, while it remains substantial (3.7σ) for the largest estimated value. We also examine constraints on extensions to the base flat ΛCDM model by combining the cluster and CMB constraints. The combination appears to favour non-minimal neutrino masses, but this possibility does little to relieve the overall tension because it simultaneously lowers the implied value of the Hubble parameter, thereby exacerbating the discrepancy with most current astrophysical estimates. In conclusion, improving the precision of cluster mass calibrations from the current 10%-level to 1% would significantly strengthen these combined analyses and provide a stringent test of the base ΛCDM model.« less

Determining geometric error model parameters of a terrestrial laser scanner through Two-face, Length-consistency, and Network methods

PubMed Central

Wang, Ling; Muralikrishnan, Bala; Rachakonda, Prem; Sawyer, Daniel

2017-01-01

Terrestrial laser scanners (TLS) are increasingly used in large-scale manufacturing and assembly where required measurement uncertainties are on the order of few tenths of a millimeter or smaller. In order to meet these stringent requirements, systematic errors within a TLS are compensated in-situ through self-calibration. In the Network method of self-calibration, numerous targets distributed in the work-volume are measured from multiple locations with the TLS to determine parameters of the TLS error model. In this paper, we propose two new self-calibration methods, the Two-face method and the Length-consistency method. The Length-consistency method is proposed as a more efficient way of realizing the Network method where the length between any pair of targets from multiple TLS positions are compared to determine TLS model parameters. The Two-face method is a two-step process. In the first step, many model parameters are determined directly from the difference between front-face and back-face measurements of targets distributed in the work volume. In the second step, all remaining model parameters are determined through the Length-consistency method. We compare the Two-face method, the Length-consistency method, and the Network method in terms of the uncertainties in the model parameters, and demonstrate the validity of our techniques using a calibrated scale bar and front-face back-face target measurements. The clear advantage of these self-calibration methods is that a reference instrument or calibrated artifacts are not required, thus significantly lowering the cost involved in the calibration process. PMID:28890607

Calibrating the stress-time curve of a combined finite-discrete element method to a Split Hopkinson Pressure Bar experiment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Osthus, Dave; Godinez, Humberto C.; Rougier, Esteban

We presenmore » t a generic method for automatically calibrating a computer code to an experiment, with uncertainty, for a given “training” set of computer code runs. The calibration technique is general and probabilistic, meaning the calibration uncertainty is represented in the form of a probability distribution. We demonstrate the calibration method by calibrating a combined Finite-Discrete Element Method (FDEM) to a Split Hopkinson Pressure Bar (SHPB) experiment with a granite sample. The probabilistic calibration method combines runs of a FDEM computer simulation for a range of “training” settings and experimental uncertainty to develop a statistical emulator. The process allows for calibration of input parameters and produces output quantities with uncertainty estimates for settings where simulation results are desired. Input calibration and FDEM fitted results are presented. We find that the maximum shear strength σ t max and to a lesser extent maximum tensile strength σ n max govern the behavior of the stress-time curve before and around the peak, while the specific energy in Mode II (shear) E t largely governs the post-peak behavior of the stress-time curve. Good agreement is found between the calibrated FDEM and the SHPB experiment. Interestingly, we find the SHPB experiment to be rather uninformative for calibrating the softening-curve shape parameters (a, b, and c). This work stands as a successful demonstration of how a general probabilistic calibration framework can automatically calibrate FDEM parameters to an experiment.« less

Calibrating the stress-time curve of a combined finite-discrete element method to a Split Hopkinson Pressure Bar experiment

DOE PAGES

Osthus, Dave; Godinez, Humberto C.; Rougier, Esteban; ...

2018-05-01

We presenmore » t a generic method for automatically calibrating a computer code to an experiment, with uncertainty, for a given “training” set of computer code runs. The calibration technique is general and probabilistic, meaning the calibration uncertainty is represented in the form of a probability distribution. We demonstrate the calibration method by calibrating a combined Finite-Discrete Element Method (FDEM) to a Split Hopkinson Pressure Bar (SHPB) experiment with a granite sample. The probabilistic calibration method combines runs of a FDEM computer simulation for a range of “training” settings and experimental uncertainty to develop a statistical emulator. The process allows for calibration of input parameters and produces output quantities with uncertainty estimates for settings where simulation results are desired. Input calibration and FDEM fitted results are presented. We find that the maximum shear strength σ t max and to a lesser extent maximum tensile strength σ n max govern the behavior of the stress-time curve before and around the peak, while the specific energy in Mode II (shear) E t largely governs the post-peak behavior of the stress-time curve. Good agreement is found between the calibrated FDEM and the SHPB experiment. Interestingly, we find the SHPB experiment to be rather uninformative for calibrating the softening-curve shape parameters (a, b, and c). This work stands as a successful demonstration of how a general probabilistic calibration framework can automatically calibrate FDEM parameters to an experiment.« less

Definition and sensitivity of the conceptual MORDOR rainfall-runoff model parameters using different multi-criteria calibration strategies

NASA Astrophysics Data System (ADS)

Garavaglia, F.; Seyve, E.; Gottardi, F.; Le Lay, M.; Gailhard, J.; Garçon, R.

2014-12-01

MORDOR is a conceptual hydrological model extensively used in Électricité de France (EDF, French electric utility company) operational applications: (i) hydrological forecasting, (ii) flood risk assessment, (iii) water balance and (iv) climate change studies. MORDOR is a lumped, reservoir, elevation based model with hourly or daily areal rainfall and air temperature as the driving input data. The principal hydrological processes represented are evapotranspiration, direct and indirect runoff, ground water, snow accumulation and melt and routing. The model has been intensively used at EDF for more than 20 years, in particular for modeling French mountainous watersheds. In the matter of parameters calibration we propose and test alternative multi-criteria techniques based on two specific approaches: automatic calibration using single-objective functions and a priori parameter calibration founded on hydrological watershed features. The automatic calibration approach uses single-objective functions, based on Kling-Gupta efficiency, to quantify the good agreement between the simulated and observed runoff focusing on four different runoff samples: (i) time-series sample, (I) annual hydrological regime, (iii) monthly cumulative distribution functions and (iv) recession sequences.The primary purpose of this study is to analyze the definition and sensitivity of MORDOR parameters testing different calibration techniques in order to: (i) simplify the model structure, (ii) increase the calibration-validation performance of the model and (iii) reduce the equifinality problem of calibration process. We propose an alternative calibration strategy that reaches these goals. The analysis is illustrated by calibrating MORDOR model to daily data for 50 watersheds located in French mountainous regions.

Novel Calibration Algorithm for a Three-Axis Strapdown Magnetometer

PubMed Central

Liu, Yan Xia; Li, Xi Sheng; Zhang, Xiao Juan; Feng, Yi Bo

2014-01-01

A complete error calibration model with 12 independent parameters is established by analyzing the three-axis magnetometer error mechanism. The said model conforms to an ellipsoid restriction, the parameters of the ellipsoid equation are estimated, and the ellipsoid coefficient matrix is derived. However, the calibration matrix cannot be determined completely, as there are fewer ellipsoid parameters than calibration model parameters. Mathematically, the calibration matrix derived from the ellipsoid coefficient matrix by a different matrix decomposition method is not unique, and there exists an unknown rotation matrix R between them. This paper puts forward a constant intersection angle method (angles between the geomagnetic field and gravitational field are fixed) to estimate R. The Tikhonov method is adopted to solve the problem that rounding errors or other errors may seriously affect the calculation results of R when the condition number of the matrix is very large. The geomagnetic field vector and heading error are further corrected by R. The constant intersection angle method is convenient and practical, as it is free from any additional calibration procedure or coordinate transformation. In addition, the simulation experiment indicates that the heading error declines from ±1° calibrated by classical ellipsoid fitting to ±0.2° calibrated by a constant intersection angle method, and the signal-to-noise ratio is 50 dB. The actual experiment exhibits that the heading error is further corrected from ±0.8° calibrated by the classical ellipsoid fitting to ±0.3° calibrated by a constant intersection angle method. PMID:24831110

Uncertainties of flood frequency estimation approaches based on continuous simulation using data resampling

NASA Astrophysics Data System (ADS)

Arnaud, Patrick; Cantet, Philippe; Odry, Jean

2017-11-01

Flood frequency analyses (FFAs) are needed for flood risk management. Many methods exist ranging from classical purely statistical approaches to more complex approaches based on process simulation. The results of these methods are associated with uncertainties that are sometimes difficult to estimate due to the complexity of the approaches or the number of parameters, especially for process simulation. This is the case of the simulation-based FFA approach called SHYREG presented in this paper, in which a rainfall generator is coupled with a simple rainfall-runoff model in an attempt to estimate the uncertainties due to the estimation of the seven parameters needed to estimate flood frequencies. The six parameters of the rainfall generator are mean values, so their theoretical distribution is known and can be used to estimate the generator uncertainties. In contrast, the theoretical distribution of the single hydrological model parameter is unknown; consequently, a bootstrap method is applied to estimate the calibration uncertainties. The propagation of uncertainty from the rainfall generator to the hydrological model is also taken into account. This method is applied to 1112 basins throughout France. Uncertainties coming from the SHYREG method and from purely statistical approaches are compared, and the results are discussed according to the length of the recorded observations, basin size and basin location. Uncertainties of the SHYREG method decrease as the basin size increases or as the length of the recorded flow increases. Moreover, the results show that the confidence intervals of the SHYREG method are relatively small despite the complexity of the method and the number of parameters (seven). This is due to the stability of the parameters and takes into account the dependence of uncertainties due to the rainfall model and the hydrological calibration. Indeed, the uncertainties on the flow quantiles are on the same order of magnitude as those associated with the use of a statistical law with two parameters (here generalised extreme value Type I distribution) and clearly lower than those associated with the use of a three-parameter law (here generalised extreme value Type II distribution). For extreme flood quantiles, the uncertainties are mostly due to the rainfall generator because of the progressive saturation of the hydrological model.

Estimation of absorbed dose in clinical radiotherapy linear accelerator beams: Effect of ion chamber calibration and long-term stability

PubMed Central

Ravichandran, Ramamoorthy; Binukumar, Johnson Pichy; Davis, Cheriyathmanjiyil Antony

2013-01-01

The measured dose in water at reference point in phantom is a primary parameter for planning the treatment monitor units (MU); both in conventional and intensity modulated/image guided treatments. Traceability of dose accuracy therefore still depends mainly on the calibration factor of the ion chamber/dosimeter provided by the accredited Secondary Standard Dosimetry Laboratories (SSDLs), under International Atomic Energy Agency (IAEA) network of laboratories. The data related to Nd,water calibrations, thermoluminescent dosimetry (TLD) postal dose validation, inter-comparison of different dosimeter/electrometers, and validity of Nd,water calibrations obtained from different calibration laboratories were analyzed to find out the extent of accuracy achievable. Nd,w factors in Gray/Coulomb calibrated at IBA, GmBH, Germany showed a mean variation of about 0.2% increase per year in three Farmer chambers, in three subsequent calibrations. Another ion chamber calibrated in different accredited laboratory (PTW, Germany) showed consistent Nd,w for 9 years period. The Strontium-90 beta check source response indicated long-term stability of the ion chambers within 1% for three chambers. Results of IAEA postal TL “dose intercomparison” for three photon beams, 6 MV (two) and 15 MV (one), agreed well within our reported doses, with mean deviation of 0.03% (SD 0.87%) (n = 9). All the chamber/electrometer calibrated by a single SSDL realized absorbed doses in water within 0.13% standard deviations. However, about 1-2% differences in absorbed dose estimates observed when dosimeters calibrated from different calibration laboratories are compared in solid phantoms. Our data therefore imply that the dosimetry level maintained for clinical use of linear accelerator photon beams are within recommended levels of accuracy, and uncertainties are within reported values. PMID:24672156

Cycle 24 HST+COS Target Acquisition Monitor Summary

NASA Astrophysics Data System (ADS)

Penton, Steven V.; White, James

2018-06-01

HST/COS calibration program 14847 (P14857) was designed to verify that all three COS Target Acquisition (TA) modes were performing nominally during Cycle 24. The program was designed not only to determine if any of the COS TA flight software (FSW) patchable constants need updating but also to determine the values of any required parameter updates. All TA modes were determined to be performing nominally during the Cycle 24 calendar period of October 1, 2016 - October 1, 2017. No COS SIAF, TA subarray, or FSW parameter updates were required as a result of this program.

Sensitivity of GRETINA position resolution to hole mobility

DOE Office of Scientific and Technical Information (OSTI.GOV)

Prasher, V. S.; Cromaz, M.; Merchan, E.

The sensitivity of the position resolution of the gamma-ray tracking array GRETINA to the hole charge-carrier mobility parameter is investigated. The χ 2 results from a fit of averaged signal (“superpulse”) data exhibit a shallow minimum for hole mobilities 15% lower than the currently adopted values. Calibration data on position resolution is analyzed, together with simulations that isolate the hole mobility dependence of signal decomposition from other effects such as electronics cross-talk. Our results effectively exclude hole mobility as a dominant parameter for improving the position resolution for reconstruction of gamma-ray interaction points in GRETINA.

Sensitivity of GRETINA position resolution to hole mobility

DOE PAGES

Prasher, V. S.; Cromaz, M.; Merchan, E.; ...

2017-02-01

The sensitivity of the position resolution of the gamma-ray tracking array GRETINA to the hole charge-carrier mobility parameter is investigated. The χ 2 results from a fit of averaged signal (“superpulse”) data exhibit a shallow minimum for hole mobilities 15% lower than the currently adopted values. Calibration data on position resolution is analyzed, together with simulations that isolate the hole mobility dependence of signal decomposition from other effects such as electronics cross-talk. Our results effectively exclude hole mobility as a dominant parameter for improving the position resolution for reconstruction of gamma-ray interaction points in GRETINA.

On the Accurate Determination of Shock Wave Time-Pressure Profile in the Experimental Models of Blast-Induced Neurotrauma

PubMed Central

Skotak, Maciej; Alay, Eren; Chandra, Namas

2018-01-01

Measurement issues leading to the acquisition of artifact-free shock wave pressure-time profiles are discussed. We address the importance of in-house sensor calibration and data acquisition sampling rate. Sensor calibration takes into account possible differences between calibration methodology in a manufacturing facility, and those used in the specific laboratory. We found in-house calibration factors of brand new sensors differ by less than 10% from their manufacturer supplied data. Larger differences were noticeable for sensors that have been used for hundreds of experiments and were as high as 30% for sensors close to the end of their useful lifetime. These observations were despite the fact that typical overpressures in our experiments do not exceed 50 psi for sensors that are rated at 1,000 psi maximum pressure. We demonstrate that sampling rate of 1,000 kHz is necessary to capture the correct rise time values, but there were no statistically significant differences between peak overpressure and impulse values for low-intensity shock waves (Mach number <2) at lower rates. We discuss two sources of experimental errors originating from mechanical vibration and electromagnetic interference on the quality of a waveform recorded using state-of-the-art high-frequency pressure sensors. The implementation of preventive measures, pressure acquisition artifacts, and data interpretation with examples, are provided in this paper that will help the community at large to avoid these mistakes. In order to facilitate inter-laboratory data comparison, common reporting standards should be developed by the blast TBI research community. We noticed the majority of published literature on the subject limits reporting to peak overpressure; with much less attention directed toward other important parameters, i.e., duration, impulse, and dynamic pressure. These parameters should be included as a mandatory requirement in publications so the results can be properly compared with others. PMID:29467718

Investigating the relationship between a soils classification and the spatial parameters of a conceptual catchment-scale hydrological model

NASA Astrophysics Data System (ADS)

Dunn, S. M.; Lilly, A.

2001-10-01

There are now many examples of hydrological models that utilise the capabilities of Geographic Information Systems to generate spatially distributed predictions of behaviour. However, the spatial variability of hydrological parameters relating to distributions of soils and vegetation can be hard to establish. In this paper, the relationship between a soil hydrological classification Hydrology of Soil Types (HOST) and the spatial parameters of a conceptual catchment-scale model is investigated. A procedure involving inverse modelling using Monte-Carlo simulations on two catchments is developed to identify relative values for soil related parameters of the DIY model. The relative values determine the internal variability of hydrological processes as a function of the soil type. For three out of the four soil parameters studied, the variability between HOST classes was found to be consistent across two catchments when tested independently. Problems in identifying values for the fourth 'fast response distance' parameter have highlighted a potential limitation with the present structure of the model. The present assumption that this parameter can be related simply to soil type rather than topography appears to be inadequate. With the exclusion of this parameter, calibrated parameter sets from one catchment can be converted into equivalent parameter sets for the alternate catchment on the basis of their HOST distributions, to give a reasonable simulation of flow. Following further testing on different catchments, and modifications to the definition of the fast response distance parameter, the technique provides a methodology whereby it is possible to directly derive spatial soil parameters for new catchments.

Multielevation calibration of frequency-domain electromagnetic data

USGS Publications Warehouse

Minsley, Burke J.; Kass, M. Andy; Hodges, Greg; Smith, Bruce D.

2014-01-01

Systematic calibration errors must be taken into account because they can substantially impact the accuracy of inverted subsurface resistivity models derived from frequency-domain electromagnetic data, resulting in potentially misleading interpretations. We have developed an approach that uses data acquired at multiple elevations over the same location to assess calibration errors. A significant advantage is that this method does not require prior knowledge of subsurface properties from borehole or ground geophysical data (though these can be readily incorporated if available), and is, therefore, well suited to remote areas. The multielevation data were used to solve for calibration parameters and a single subsurface resistivity model that are self consistent over all elevations. The deterministic and Bayesian formulations of the multielevation approach illustrate parameter sensitivity and uncertainty using synthetic- and field-data examples. Multiplicative calibration errors (gain and phase) were found to be better resolved at high frequencies and when data were acquired over a relatively conductive area, whereas additive errors (bias) were reasonably resolved over conductive and resistive areas at all frequencies. The Bayesian approach outperformed the deterministic approach when estimating calibration parameters using multielevation data at a single location; however, joint analysis of multielevation data at multiple locations using the deterministic algorithm yielded the most accurate estimates of calibration parameters. Inversion results using calibration-corrected data revealed marked improvement in misfit, lending added confidence to the interpretation of these models.

Application of validation data for assessing spatial interpolation methods for 8-h ozone or other sparsely monitored constituents.

PubMed

Joseph, John; Sharif, Hatim O; Sunil, Thankam; Alamgir, Hasanat

2013-07-01

The adverse health effects of high concentrations of ground-level ozone are well-known, but estimating exposure is difficult due to the sparseness of urban monitoring networks. This sparseness discourages the reservation of a portion of the monitoring stations for validation of interpolation techniques precisely when the risk of overfitting is greatest. In this study, we test a variety of simple spatial interpolation techniques for 8-h ozone with thousands of randomly selected subsets of data from two urban areas with monitoring stations sufficiently numerous to allow for true validation. Results indicate that ordinary kriging with only the range parameter calibrated in an exponential variogram is the generally superior method, and yields reliable confidence intervals. Sparse data sets may contain sufficient information for calibration of the range parameter even if the Moran I p-value is close to unity. R script is made available to apply the methodology to other sparsely monitored constituents. Copyright © 2013 Elsevier Ltd. All rights reserved.

APEX/SPIN: a free test platform to measure speech intelligibility.

PubMed

Francart, Tom; Hofmann, Michael; Vanthornhout, Jonas; Van Deun, Lieselot; van Wieringen, Astrid; Wouters, Jan

2017-02-01

Measuring speech intelligibility in quiet and noise is important in clinical practice and research. An easy-to-use free software platform for conducting speech tests is presented, called APEX/SPIN. The APEX/SPIN platform allows the use of any speech material in combination with any noise. A graphical user interface provides control over a large range of parameters, such as number of loudspeakers, signal-to-noise ratio and parameters of the procedure. An easy-to-use graphical interface is provided for calibration and storage of calibration values. To validate the platform, perception of words in quiet and sentences in noise were measured both with APEX/SPIN and with an audiometer and CD player, which is a conventional setup in current clinical practice. Five normal-hearing listeners participated in the experimental evaluation. Speech perception results were similar for the APEX/SPIN platform and conventional procedures. APEX/SPIN is a freely available and open source platform that allows the administration of all kinds of custom speech perception tests and procedures.

A near-infrared reflectance spectroscopic method for the direct analysis of several fodder-related chemical components in drumstick (Moringa oleifera Lam.) leaves.

PubMed

Zhang, Junjie; Li, Shuqi; Lin, Mengfei; Yang, Endian; Chen, Xiaoyang

2018-05-01

The drumstick tree has traditionally been used as foodstuff and fodder in several countries. Due to its high nutritional value and good biomass production, interest in this plant has increased in recent years. It has therefore become important to rapidly and accurately evaluate drumstick quality. In this study, we addressed the optimization of Near-infrared spectroscopy (NIRS) to analyze crude protein, crude fat, crude fiber, iron (Fe), and potassium (K) in a variety of drumstick accessions (N = 111) representing different populations, cultivation programs, and climates. Partial least-squares regression with internal cross-validation was used to evaluate the models and identify possible spectral outliers. The calibration statistics for these fodder-related chemical components suggest that NIRS can predict these parameters in a wide range of drumstick types with high accuracy. The NIRS calibration models developed in this study will be useful in predicting drumstick forage quality for these five quality parameters.

Utilization of advanced calibration techniques in stochastic rock fall analysis of quarry slopes

NASA Astrophysics Data System (ADS)

Preh, Alexander; Ahmadabadi, Morteza; Kolenprat, Bernd

2016-04-01

In order to study rock fall dynamics, a research project was conducted by the Vienna University of Technology and the Austrian Central Labour Inspectorate (Federal Ministry of Labour, Social Affairs and Consumer Protection). A part of this project included 277 full-scale drop tests at three different quarries in Austria and recording key parameters of the rock fall trajectories. The tests involved a total of 277 boulders ranging from 0.18 to 1.8 m in diameter and from 0.009 to 8.1 Mg in mass. The geology of these sites included strong rock belonging to igneous, metamorphic and volcanic types. In this paper the results of the tests are used for calibration and validation a new stochastic computer model. It is demonstrated that the error of the model (i.e. the difference between observed and simulated results) has a lognormal distribution. Selecting two parameters, advanced calibration techniques including Markov Chain Monte Carlo Technique, Maximum Likelihood and Root Mean Square Error (RMSE) are utilized to minimize the error. Validation of the model based on the cross validation technique reveals that in general, reasonable stochastic approximations of the rock fall trajectories are obtained in all dimensions, including runout, bounce heights and velocities. The approximations are compared to the measured data in terms of median, 95% and maximum values. The results of the comparisons indicate that approximate first-order predictions, using a single set of input parameters, are possible and can be used to aid practical hazard and risk assessment.

Towards quantifying uncertainty in Greenland's contribution to 21st century sea-level rise

NASA Astrophysics Data System (ADS)

Perego, M.; Tezaur, I.; Price, S. F.; Jakeman, J.; Eldred, M.; Salinger, A.; Hoffman, M. J.

2015-12-01

We present recent work towards developing a methodology for quantifying uncertainty in Greenland's 21st century contribution to sea-level rise. While we focus on uncertainties associated with the optimization and calibration of the basal sliding parameter field, the methodology is largely generic and could be applied to other (or multiple) sets of uncertain model parameter fields. The first step in the workflow is the solution of a large-scale, deterministic inverse problem, which minimizes the mismatch between observed and computed surface velocities by optimizing the two-dimensional coefficient field in a linear-friction sliding law. We then expand the deviation in this coefficient field from its estimated "mean" state using a reduced basis of Karhunen-Loeve Expansion (KLE) vectors. A Bayesian calibration is used to determine the optimal coefficient values for this expansion. The prior for the Bayesian calibration can be computed using the Hessian of the deterministic inversion or using an exponential covariance kernel. The posterior distribution is then obtained using Markov Chain Monte Carlo run on an emulator of the forward model. Finally, the uncertainty in the modeled sea-level rise is obtained by performing an ensemble of forward propagation runs. We present and discuss preliminary results obtained using a moderate-resolution model of the Greenland Ice sheet. As demonstrated in previous work, the primary difficulty in applying the complete workflow to realistic, high-resolution problems is that the effective dimension of the parameter space is very large.

Parameter optimization of the QUAL2K model for a multiple-reach river using an influence coefficient algorithm.

PubMed

Cho, Jae Heon; Ha, Sung Ryong

2010-03-15

An influence coefficient algorithm and a genetic algorithm (GA) were introduced to develop an automatic calibration model for QUAL2K, the latest version of the QUAL2E river and stream water-quality model. The influence coefficient algorithm was used for the parameter optimization in unsteady state, open channel flow. The GA, used in solving the optimization problem, is very simple and comprehensible yet still applicable to any complicated mathematical problem, where it can find the global-optimum solution quickly and effectively. The previously established model QUAL2Kw was used for the automatic calibration of the QUAL2K. The parameter-optimization method using the influence coefficient and genetic algorithm (POMIG) developed in this study and QUAL2Kw were each applied to the Gangneung Namdaecheon River, which has multiple reaches, and the results of the two models were compared. In the modeling, the river reach was divided into two parts based on considerations of the water quality and hydraulic characteristics. The calibration results by POMIG showed a good correspondence between the calculated and observed values for most of water-quality variables. In the application of POMIG and QUAL2Kw, relatively large errors were generated between the observed and predicted values in the case of the dissolved oxygen (DO) and chlorophyll-a (Chl-a) in the lowest part of the river; therefore, two weighting factors (1 and 5) were applied for DO and Chl-a in the lower river. The sums of the errors for DO and Chl-a with a weighting factor of 5 were slightly lower compared with the application of a factor of 1. However, with a weighting factor of 5 the sums of errors for other water-quality variables were slightly increased in comparison to the case with a factor of 1. Generally, the results of the POMIG were slightly better than those of the QUAL2Kw.

CALIBRATED ULTRA FAST IMAGE SIMULATIONS FOR THE DARK ENERGY SURVEY

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bruderer, Claudio; Chang, Chihway; Refregier, Alexandre

2016-01-20

Image simulations are becoming increasingly important in understanding the measurement process of the shapes of galaxies for weak lensing and the associated systematic effects. For this purpose we present the first implementation of the Monte Carlo Control Loops (MCCL), a coherent framework for studying systematic effects in weak lensing. It allows us to model and calibrate the shear measurement process using image simulations from the Ultra Fast Image Generator (UFig) and the image analysis software SExtractor. We apply this framework to a subset of the data taken during the Science Verification period (SV) of the Dark Energy Survey (DES). Wemore » calibrate the UFig simulations to be statistically consistent with one of the SV images, which covers ∼0.5 square degrees. We then perform tolerance analyses by perturbing six simulation parameters and study their impact on the shear measurement at the one-point level. This allows us to determine the relative importance of different parameters. For spatially constant systematic errors and point-spread function, the calibration of the simulation reaches the weak lensing precision needed for the DES SV survey area. Furthermore, we find a sensitivity of the shear measurement to the intrinsic ellipticity distribution, and an interplay between the magnitude-size and the pixel value diagnostics in constraining the noise model. This work is the first application of the MCCL framework to data and shows how it can be used to methodically study the impact of systematics on the cosmic shear measurement.« less

Thermospheric density and wind retrieval from Swarm observations

NASA Astrophysics Data System (ADS)

Visser, Pieter; Doornbos, Eelco; van den IJssel, Jose; Teixeira da Encarnação, João

2013-11-01

The three-satellite ESA Swarm mission aims at mapping the Earth's global geomagnetic field at unprecedented spatial and temporal resolution and precision. Swarm also aims at observing thermospheric density and possibly horizontal winds. Precise orbit determination (POD) and Thermospheric Density and Wind (TDW) chains form part of the Swarm Constellation and Application Facility (SCARF), which will provide the so-called Level 2 products. The POD and TDW chains generate the orbit, accelerometer calibration, and thermospheric density and wind Level 2 products. The POD and TDW chains have been tested with data from the CHAMP and GRACE missions, indicating that a 3D orbit precision of about 10 cm can be reached. In addition, POD allows to determine daily accelerometer bias and scale factor values with a precision of around 10-15 nm/s2 and 0.01-0.02, respectively, for the flight direction. With these accelerometer calibration parameter values, derived thermospheric density is consistent at the 9-11% level (standard deviation) with values predicted by models (taking into account that model values are 20-30% higher). The retrieval of crosswinds forms part of the processing chain, but will be challenging. The Swarm observations will be used for further developing and improving density and wind retrieval algorithms.

How Does Higher Frequency Monitoring Data Affect the Calibration of a Process-Based Water Quality Model?

NASA Astrophysics Data System (ADS)

Jackson-Blake, L.

2014-12-01

Process-based catchment water quality models are increasingly used as tools to inform land management. However, for such models to be reliable they need to be well calibrated and shown to reproduce key catchment processes. Calibration can be challenging for process-based models, which tend to be complex and highly parameterised. Calibrating a large number of parameters generally requires a large amount of monitoring data, but even in well-studied catchments, streams are often only sampled at a fortnightly or monthly frequency. The primary aim of this study was therefore to investigate how the quality and uncertainty of model simulations produced by one process-based catchment model, INCA-P (the INtegrated CAtchment model of Phosphorus dynamics), were improved by calibration to higher frequency water chemistry data. Two model calibrations were carried out for a small rural Scottish catchment: one using 18 months of daily total dissolved phosphorus (TDP) concentration data, another using a fortnightly dataset derived from the daily data. To aid comparability, calibrations were carried out automatically using the MCMC-DREAM algorithm. Using daily rather than fortnightly data resulted in improved simulation of the magnitude of peak TDP concentrations, in turn resulting in improved model performance statistics. Marginal posteriors were better constrained by the higher frequency data, resulting in a large reduction in parameter-related uncertainty in simulated TDP (the 95% credible interval decreased from 26 to 6 μg/l). The number of parameters that could be reliably auto-calibrated was lower for the fortnightly data, leading to the recommendation that parameters should not be varied spatially for models such as INCA-P unless there is solid evidence that this is appropriate, or there is a real need to do so for the model to fulfil its purpose. Secondary study aims were to highlight the subjective elements involved in auto-calibration and suggest practical improvements that could make models such as INCA-P more suited to auto-calibration and uncertainty analyses. Two key improvements include model simplification, so that all model parameters can be included in an analysis of this kind, and better documenting of recommended ranges for each parameter, to help in choosing sensible priors.

Genetic algorithms for the application of Activated Sludge Model No. 1.

PubMed

Kim, S; Lee, H; Kim, J; Kim, C; Ko, J; Woo, H; Kim, S

2002-01-01

The genetic algorithm (GA) has been integrated into the IWA ASM No. 1 to calibrate important stoichiometric and kinetic parameters. The evolutionary feature of GA was used to configure the multiple local optima as well as the global optimum. The objective function of optimization was designed to minimize the difference between estimated and measured effluent concentrations at the activated sludge system. Both steady state and dynamic data of the simulation benchmark were used for calibration using denitrification layout. Depending upon the confidence intervals and objective functions, the proposed method provided distributions of parameter space. Field data have been collected and applied to validate calibration capacity of GA. Dynamic calibration was suggested to capture periodic variations of inflow concentrations. Also, in order to verify this proposed method in real wastewater treatment plant, measured data sets for substrate concentrations were obtained from Haeundae wastewater treatment plant and used to estimate parameters in the dynamic system. The simulation results with calibrated parameters matched well with the observed concentrations of effluent COD.

Applying 3-PG, a simple process-based model designed to produce practical results, to data from loblolly pine experiments

Treesearch

Joe J. Landsberg; Kurt H. Johnsen; Timothy J. Albaugh; H. Lee Allen; Steven E. McKeand

2001-01-01

3-PG is a simple process-based model that requires few parameter values and only readily available input data. We tested the structure of the model by calibrating it against loblolly pine data from the control treatment of the SETRES experiment in Scotland County, NC, then altered the fertility rating to simulate the effects of fertilization. There was excellent...

Device-scale CFD modeling of gas-liquid multiphase flow and amine absorption for CO 2 capture: Original Research Article: Device-scale CFD modeling of gas-liquid multiphase flow and amine absorption for CO 2 capture

DOE PAGES

Pan, Wenxiao; Galvin, Janine; Huang, Wei Ling; ...

2018-03-25

In this paper we aim to develop a validated device-scale CFD model that can predict quantitatively both hydrodynamics and CO 2 capture efficiency for an amine-based solvent absorber column with random Pall ring packing. A Eulerian porous-media approach and a two-fluid model were employed, in which the momentum and mass transfer equations were closed by literature-based empirical closure models. We proposed a hierarchical approach for calibrating the parameters in the closure models to make them accurate for the packed column. Specifically, a parameter for momentum transfer in the closure was first calibrated based on data from a single experiment. Withmore » this calibrated parameter, a parameter in the closure for mass transfer was next calibrated under a single operating condition. Last, the closure of the wetting area was calibrated for each gas velocity at three different liquid flow rates. For each calibration, cross validations were pursued using the experimental data under operating conditions different from those used for calibrations. This hierarchical approach can be generally applied to develop validated device-scale CFD models for different absorption columns.« less

Device-scale CFD modeling of gas-liquid multiphase flow and amine absorption for CO 2 capture: Original Research Article: Device-scale CFD modeling of gas-liquid multiphase flow and amine absorption for CO 2 capture

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pan, Wenxiao; Galvin, Janine; Huang, Wei Ling

In this paper we aim to develop a validated device-scale CFD model that can predict quantitatively both hydrodynamics and CO 2 capture efficiency for an amine-based solvent absorber column with random Pall ring packing. A Eulerian porous-media approach and a two-fluid model were employed, in which the momentum and mass transfer equations were closed by literature-based empirical closure models. We proposed a hierarchical approach for calibrating the parameters in the closure models to make them accurate for the packed column. Specifically, a parameter for momentum transfer in the closure was first calibrated based on data from a single experiment. Withmore » this calibrated parameter, a parameter in the closure for mass transfer was next calibrated under a single operating condition. Last, the closure of the wetting area was calibrated for each gas velocity at three different liquid flow rates. For each calibration, cross validations were pursued using the experimental data under operating conditions different from those used for calibrations. This hierarchical approach can be generally applied to develop validated device-scale CFD models for different absorption columns.« less

MOESHA: A genetic algorithm for automatic calibration and estimation of parameter uncertainty and sensitivity of hydrologic models

EPA Science Inventory

Characterization of uncertainty and sensitivity of model parameters is an essential and often overlooked facet of hydrological modeling. This paper introduces an algorithm called MOESHA that combines input parameter sensitivity analyses with a genetic algorithm calibration routin...

Online geometric calibration of cone-beam computed tomography for arbitrary imaging objects.

PubMed

Meng, Yuanzheng; Gong, Hui; Yang, Xiaoquan

2013-02-01

A novel online method based on the symmetry property of the sum of projections (SOP) is proposed to obtain the geometric parameters in cone-beam computed tomography (CBCT). This method requires no calibration phantom and can be used in circular trajectory CBCT with arbitrary cone angles. An objective function is deduced to illustrate the dependence of the symmetry of SOP on geometric parameters, which will converge to its minimum when the geometric parameters achieve their true values. Thus, by minimizing the objective function, we can obtain the geometric parameters for image reconstruction. To validate this method, numerical phantom studies with different noise levels are simulated. The results show that our method is insensitive to the noise and can determine the skew (in-plane rotation angle of the detector), the roll (rotation angle around the projection of the rotation axis on the detector), and the rotation axis with high accuracy, while the mid-plane and source-to-detector distance will be obtained with slightly lower accuracy. However, our simulation studies validate that the errors of the latter two parameters brought by our method will hardly degrade the quality of reconstructed images. The small animal studies show that our method is able to deal with arbitrary imaging objects. In addition, the results of the reconstructed images in different slices demonstrate that we have achieved comparable image quality in the reconstructions as some offline methods.

Description, calibration and sensitivity analysis of the local ecosystem submodel of a global model of carbon and nitrogen cycling and the water balance in the terrestrial biosphere

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kercher, J.R.; Chambers, J.Q.

1995-10-01

We have developed a geographically-distributed ecosystem model for the carbon, nitrogen, and water dynamics of the terrestrial biosphere TERRA. The local ecosystem model of TERRA consists of coupled, modified versions of TEM and DAYTRANS. The ecosystem model in each grid cell calculates water fluxes of evaporation, transpiration, and runoff; carbon fluxes of gross primary productivity, litterfall, and plant and soil respiration; and nitrogen fluxes of vegetation uptake, litterfall, mineralization, immobilization, and system loss. The state variables are soil water content; carbon in live vegetation; carbon in soil; nitrogen in live vegetation; organic nitrogen in soil and fitter; available inorganic nitrogenmore » aggregating nitrites, nitrates, and ammonia; and a variable for allocation. Carbon and nitrogen dynamics are calibrated to specific sites in 17 vegetation types. Eight parameters are determined during calibration for each of the 17 vegetation types. At calibration, the annual average values of carbon in vegetation C, show site differences that derive from the vegetation-type specific parameters and intersite variation in climate and soils. From calibration, we recover the average C{sub v} of forests, woodlands, savannas, grasslands, shrublands, and tundra that were used to develop the model initially. The timing of the phases of the annual variation is driven by temperature and light in the high latitude and moist temperate zones. The dry temperate zones are driven by temperature, precipitation, and light. In the tropics, precipitation is the key variable in annual variation. The seasonal responses are even more clearly demonstrated in net primary production and show the same controlling factors.« less

Considerations for SphygmoCor radial artery pulse wave analysis: side selection and peripheral arterial blood pressure calibration.

PubMed

Martin, Jeffrey S; Borges, Alexandra R; Christy, John B; Beck, Darren T

2015-10-01

Methods employed for pulse wave analysis (PWA) and peripheral blood pressure (PBP) calibration vary. The purpose of this study was to evaluate the agreement of SphygmoCor PWA parameters derived from radial artery tonometry when considering (1) timing (before vs. after tonometry) and side selection (ipsilateral vs. contralateral limb) for PBP calibration and (2) side selection for tonometry (left vs. right arm). In 34 subjects (aged 21.9 ± 2.3 years), bilateral radial artery tonometry was performed simultaneously on three instances. PBP assessment via oscillometric sphygmomanometry in the left arm only and both arms simultaneously occurred following the first and second instances of tonometry, respectively. Significant within arm differences in PWA parameters derived before and after PBP measurement were observed in the right arm only (for example, aortic systolic blood pressure, Δ=0.38 ± 0.64 mm Hg). Simultaneously captured bilateral PWA variables demonstrated significant between arm differences in 88% (14/16) and 56% (9/16) of outcome variables when calibrated to within arm and equivalent PBP, respectively. Moreover, the right arm consistently demonstrated lower values for clinical PWA variables (for example, augmentation index, bias=-2.79%). However, 26% (n=9) of participants presented with clinically significant differences (>10 mm Hg) in bilateral PBP and their exclusion from analysis abolished most between arm differences observed. SphygmoCor PWA in the right radial artery results in greater variability independent of the timing of PBP measurement and magnitude of calibration pressures in young subjects. Moreover, bilateral PBP measurement is imperative to identify subjects in whom a significant difference in bilateral PWA outcomes may exist.

CALIBRATION OF THE MIXING-LENGTH THEORY FOR CONVECTIVE WHITE DWARF ENVELOPES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tremblay, P.-E.; Ludwig, H.-G.; Freytag, B.

2015-02-01

A calibration of the mixing-length parameter in the local mixing-length theory (MLT) is presented for the lower part of the convection zone in pure-hydrogen-atmosphere white dwarfs. The parameterization is performed from a comparison of three-dimensional (3D) CO5BOLD simulations with a grid of one-dimensional (1D) envelopes with a varying mixing-length parameter. In many instances, the 3D simulations are restricted to the upper part of the convection zone. The hydrodynamical calculations suggest, in those cases, that the entropy of the upflows does not change significantly from the bottom of the convection zone to regions immediately below the photosphere. We rely on thismore » asymptotic entropy value, characteristic of the deep and adiabatically stratified layers, to calibrate 1D envelopes. The calibration encompasses the convective hydrogen-line (DA) white dwarfs in the effective temperature range 6000 ≤ T {sub eff} (K) ≤15, 000 and the surface gravity range 7.0 ≤ log g ≤ 9.0. It is established that the local MLT is unable to reproduce simultaneously the thermodynamical, flux, and dynamical properties of the 3D simulations. We therefore propose three different parameterizations for these quantities. The resulting calibration can be applied to structure and envelope calculations, in particular for pulsation, chemical diffusion, and convective mixing studies. On the other hand, convection has no effect on the white dwarf cooling rates until there is a convective coupling with the degenerate core below T {sub eff} ∼ 5000 K. In this regime, the 1D structures are insensitive to the MLT parameterization and converge to the mean 3D results, hence they remain fully appropriate for age determinations.« less

A calibration-free formulation of the complementary relationship of evaporation for continental-scale hydrology

NASA Astrophysics Data System (ADS)

Szilagyi, Jozsef; Crago, Richard; Qualls, Russell

2017-01-01

An important scaling consideration is introduced into the formulation of the complementary relationship (CR) of land surface evapotranspiration (ET) by specifying the maximum possible evaporation rate (Epmax) of a small water body (or wet patch) as a result of adiabatic drying from the prevailing near-neutral atmospheric conditions. In dimensionless form the CR therefore becomes yB = f(Epmax-EpEpmax-EwxB) = f(X) = 2X2 - X3, where yB = ET/Ep, xB = Ew/Ep. Ew is the wet-environment evaporation rate as given by the Priestley-Taylor equation, Ep is the evaporation rate of the same small wet surface for which Epmax is specified and estimated by the Penman equation. With the help of North American Regional Reanalysis data, the CR this way yields better continental-scale performance than earlier, calibrated versions of it and is on par with current land surface model results, the latter requiring vegetation, soil information and soil moisture bookkeeping. Validation has been performed by Parameter-Elevation Regressions on Independent Slopes Model precipitation and United States Geological Survey runoff data. A novel approach is also introduced to calculate the value of the Priestley-Taylor parameter to be used with continental-scale data, making the new formulation of the CR completely calibration free.

Calibrated Hydrothermal Parameters, Barrow, Alaska, 2013

DOE Data Explorer

Atchley, Adam; Painter, Scott; Harp, Dylan; Coon, Ethan; Wilson, Cathy; Liljedahl, Anna; Romanovsky, Vladimir

2015-01-29

A model-observation-experiment process (ModEx) is used to generate three 1D models of characteristic micro-topographical land-formations, which are capable of simulating present active thaw layer (ALT) from current climate conditions. Each column was used in a coupled calibration to identify moss, peat and mineral soil hydrothermal properties to be used in up-scaled simulations. Observational soil temperature data from a tundra site located near Barrow, AK (Area C) is used to calibrate thermal properties of moss, peat, and sandy loam soil to be used in the multiphysics Advanced Terrestrial Simulator (ATS) models. Simulation results are a list of calibrated hydrothermal parameters for moss, peat, and mineral soil hydrothermal parameters.

A Consistency Evaluation and Calibration Method for Piezoelectric Transmitters.

PubMed

Zhang, Kai; Tan, Baohai; Liu, Xianping

2017-04-28

Array transducer and transducer combination technologies are evolving rapidly. While adapting transmitter combination technologies, the parameter consistencies between each transmitter are extremely important because they can determine a combined effort directly. This study presents a consistency evaluation and calibration method for piezoelectric transmitters by using impedance analyzers. Firstly, electronic parameters of transmitters that can be measured by impedance analyzers are introduced. A variety of transmitter acoustic energies that are caused by these parameter differences are then analyzed and certified and, thereafter, transmitter consistency is evaluated. Lastly, based on the evaluations, consistency can be calibrated by changing the corresponding excitation voltage. Acoustic experiments show that this method accurately evaluates and calibrates transducer consistencies, and is easy to realize.

Least-Squares Self-Calibration of Imaging Array Data

NASA Technical Reports Server (NTRS)

Arendt, R. G.; Moseley, S. H.; Fixsen, D. J.

2004-01-01

When arrays are used to collect multiple appropriately-dithered images of the same region of sky, the resulting data set can be calibrated using a least-squares minimization procedure that determines the optimal fit between the data and a model of that data. The model parameters include the desired sky intensities as well as instrument parameters such as pixel-to-pixel gains and offsets. The least-squares solution simultaneously provides the formal error estimates for the model parameters. With a suitable observing strategy, the need for separate calibration observations is reduced or eliminated. We show examples of this calibration technique applied to HST NICMOS observations of the Hubble Deep Fields and simulated SIRTF IRAC observations.

Camera calibration for multidirectional flame chemiluminescence tomography

NASA Astrophysics Data System (ADS)

Wang, Jia; Zhang, Weiguang; Zhang, Yuhong; Yu, Xun

2017-04-01

Flame chemiluminescence tomography (FCT), which combines computerized tomography theory and multidirectional chemiluminescence emission measurements, can realize instantaneous three-dimensional (3-D) diagnostics for flames with high spatial and temporal resolutions. One critical step of FCT is to record the projections by multiple cameras from different view angles. For high accuracy reconstructions, it requires that extrinsic parameters (the positions and orientations) and intrinsic parameters (especially the image distances) of cameras be accurately calibrated first. Taking the focus effect of the camera into account, a modified camera calibration method was presented for FCT, and a 3-D calibration pattern was designed to solve the parameters. The precision of the method was evaluated by reprojections of feature points to cameras with the calibration results. The maximum root mean square error of the feature points' position is 1.42 pixels and 0.0064 mm for the image distance. An FCT system with 12 cameras was calibrated by the proposed method and the 3-D CH* intensity of a propane flame was measured. The results showed that the FCT system provides reasonable reconstruction accuracy using the camera's calibration results.

Conceptual and numerical models of groundwater flow in the Ogallala aquifer in Gregory and Tripp Counties, South Dakota, water years 1985--2009

USGS Publications Warehouse

Davis, Kyle W.; Putnam, Larry D.

2013-01-01

The Ogallala aquifer is an important water resource for the Rosebud Sioux Tribe in Gregory and Tripp Counties in south-central South Dakota and is used for irrigation, public supply, domestic, and stock water supplies. To better understand groundwater flow in the Ogallala aquifer, conceptual and numerical models of groundwater flow were developed for the aquifer. A conceptual model of the Ogallala aquifer was used to analyze groundwater flow and develop a numerical model to simulate groundwater flow in the aquifer. The MODFLOW–NWT model was used to simulate transient groundwater conditions for water years 1985–2009. The model was calibrated using statistical parameter estimation techniques. Potential future scenarios were simulated using the input parameters from the calibrated model for simulations of potential future drought and future increased pumping. Transient simulations were completed with the numerical model. A 200-year transient initialization period was used to establish starting conditions for the subsequent 25-year simulation of water years 1985–2009. The 25-year simulation was discretized into three seasonal stress periods per year and used to simulate transient conditions. A single-layer model was used to simulate flow and mass balance in the Ogallala aquifer with a grid of 133 rows and 282 columns and a uniform spacing of 500 meters (1,640 feet). Regional inflow and outflow were simulated along the western and southern boundaries using specified-head cells. All other boundaries were simulated using no-flow cells. Recharge to the aquifer occurs through precipitation on the outcrop area. Model calibration was accomplished using the Parameter Estimation (PEST) program that adjusted individual model input parameters and assessed the difference between estimated and model-simulated values of hydraulic head and base flow. This program was designed to estimate parameter values that are statistically the most likely set of values to result in the smallest differences between simulated and observed values, within a given set of constraints. The potentiometric surface of the aquifer calculated during the 200-year initialization period established initial conditions for the transient simulation. Water levels for 38 observation wells were used to calibrate the 25-year simulation. Simulated hydraulic heads for the transient simulation were within plus or minus 20 feet of observed values for 95 percent of observation wells, and the mean absolute difference was 5.1 feet. Calibrated hydraulic conductivity ranged from 0.9 to 227 feet per day (ft/d). The annual recharge rates for the transient simulation (water years 1985–2009) ranged from 0.60 to 6.96 inches, with a mean of 3.68 inches for the Ogallala aquifer. This represents a mean recharge rate of 280.5 ft3/s for the model area. Discharge from the aquifer occurs through evapotranspiration, discharge to streams through river leakage and flow from springs and seeps, and well withdrawals. Water is withdrawn from wells for irrigation, public supply, domestic, and stock uses. Simulated mean discharge rates for water years 1985–2009 were about 185 cubic feet per second (ft3/s) for evapotranspiration, 66.7 ft3/s for discharge to streams, and 5.48 ft3/s for well withdrawals. Simulated annual evapotranspiration rates ranged from about 128 to 254 ft3/s, and outflow to streams ranged from 52.2 to 79.9 ft3/s. A sensitivity analysis was used to examine the response of the calibrated model to changes in model parameters for horizontal hydraulic conductivity, recharge, evapotranspiration, and spring and riverbed conductance. The model was most sensitive to recharge and maximum potential evapotranspiration and least sensitive to riverbed and spring conductances. Two potential future scenarios were simulated: a potential drought scenario and a potential increased pumping scenario. To simulate a potential drought scenario, a synthetic drought record was created, the mean of which was equal to 60 percent of the mean estimated recharge rate for the 25-year simulation period. Compared with the results of the calibrated model (non-drought simulation), the simulation representing a potential drought scenario resulted in water-level decreases of as much as 30 feet for the Ogallala aquifer. To simulate the effects of potential future increases in pumping, well withdrawal rates were increased by 50 percent from those estimated for the 25-year simulation period. Compared with the results of the calibrated model, the simulation representing an increased pumping scenario resulted in water-level decreases of as much as 26 feet for the Ogallala aquifer. Groundwater budgets for the potential future scenario simulations were compared with the transient simulation representing water years 1985–2009. The simulation representing a potential drought scenario resulted in lower aquifer recharge from precipitation and decreased discharge from streams, springs, seeps, and evapotranspiration. The simulation representing a potential increased pumping scenario was similar to results from the transient simulation, with a slight increase in well withdrawals and a slight decrease in discharge from river leakage and evapotranspiration. This numerical model is suitable as a tool that could be used to better understand the flow system of the Ogallala aquifer, to approximate hydraulic heads in the aquifer, and to estimate discharge to rivers, springs, and seeps in the study area. The model also is useful to help assess the response of the aquifer to additional stresses, including potential drought conditions and increased well withdrawals.

Quantification of the specific yield in a two-layer hard-rock aquifer model

NASA Astrophysics Data System (ADS)

Durand, Véronique; Léonardi, Véronique; de Marsily, Ghislain; Lachassagne, Patrick

2017-08-01

Hard rock aquifers (HRA) have long been considered to be two-layer systems, with a mostly capacitive layer just below the surface, the saprolite layer, and a mainly transmissive layer underneath, the fractured layer. Although this hydrogeological conceptual model is widely accepted today within the scientific community, it is difficult to quantify the respective storage properties of each layer with an equivalent porous medium model. Based on an HRA field site, this paper attempts to quantify in a distinct manner the respective values of the specific yield (Sy) in the saprolite and the fractured layer, with the help of a deterministic hydrogeological model. The study site is the Plancoët migmatitic aquifer located in north-western Brittany, France, with piezometric data from 36 observation wells surveyed every two weeks for eight years. Whereas most of the piezometers (26) are located where the water table lies within the saprolite, thus representing the specific yield of the unconfined layer (Sy1), 10 of them are representative of the unconfined fractured layer (Sy2), due to their position where the saprolite is eroded or unsaturated. The two-layer model, based on field observations of the layer geometry, runs with the MODFLOW code. 81 values of the Sy1/Sy2 parameter sets were tested manually, as an inverse calibration was not able to calibrate these parameters. In order to calibrate the storage properties, a new quality-of-fit criterion called ;AdVar; was also developed, equal to the mean squared deviation of the seasonal piezometric amplitude variation. Contrary to the variance, AdVar is able to select the best values for the specific yield in each layer. It is demonstrated that the saprolite layer is about 2.5 times more capacitive than the fractured layer, with Sy1 = 10% (7% < Sy1 < 15%) against Sy2 = 2% (1% < Sy2 < 3%), in this particular example.

Robust and Accurate Image-Based Georeferencing Exploiting Relative Orientation Constraints

NASA Astrophysics Data System (ADS)

Cavegn, S.; Blaser, S.; Nebiker, S.; Haala, N.

2018-05-01

Urban environments with extended areas of poor GNSS coverage as well as indoor spaces that often rely on real-time SLAM algorithms for camera pose estimation require sophisticated georeferencing in order to fulfill our high requirements of a few centimeters for absolute 3D point measurement accuracies. Since we focus on image-based mobile mapping, we extended the structure-from-motion pipeline COLMAP with georeferencing capabilities by integrating exterior orientation parameters from direct sensor orientation or SLAM as well as ground control points into bundle adjustment. Furthermore, we exploit constraints for relative orientation parameters among all cameras in bundle adjustment, which leads to a significant robustness and accuracy increase especially by incorporating highly redundant multi-view image sequences. We evaluated our integrated georeferencing approach on two data sets, one captured outdoors by a vehicle-based multi-stereo mobile mapping system and the other captured indoors by a portable panoramic mobile mapping system. We obtained mean RMSE values for check point residuals between image-based georeferencing and tachymetry of 2 cm in an indoor area, and 3 cm in an urban environment where the measurement distances are a multiple compared to indoors. Moreover, in comparison to a solely image-based procedure, our integrated georeferencing approach showed a consistent accuracy increase by a factor of 2-3 at our outdoor test site. Due to pre-calibrated relative orientation parameters, images of all camera heads were oriented correctly in our challenging indoor environment. By performing self-calibration of relative orientation parameters among respective cameras of our vehicle-based mobile mapping system, remaining inaccuracies from suboptimal test field calibration were successfully compensated.

Estimating catchment-scale groundwater dynamics from recession analysis - enhanced constraining of hydrological models

NASA Astrophysics Data System (ADS)

Skaugen, Thomas; Mengistu, Zelalem

2016-12-01

In this study, we propose a new formulation of subsurface water storage dynamics for use in rainfall-runoff models. Under the assumption of a strong relationship between storage and runoff, the temporal distribution of catchment-scale storage is considered to have the same shape as the distribution of observed recessions (measured as the difference between the log of runoff values). The mean subsurface storage is estimated as the storage at steady state, where moisture input equals the mean annual runoff. An important contribution of the new formulation is that its parameters are derived directly from observed recession data and the mean annual runoff. The parameters are hence estimated prior to model calibration against runoff. The new storage routine is implemented in the parameter parsimonious distance distribution dynamics (DDD) model and has been tested for 73 catchments in Norway of varying size, mean elevation and landscape type. Runoff simulations for the 73 catchments from two model structures (DDD with calibrated subsurface storage and DDD with the new estimated subsurface storage) were compared. Little loss in precision of runoff simulations was found using the new estimated storage routine. For the 73 catchments, an average of the Nash-Sutcliffe efficiency criterion of 0.73 was obtained using the new estimated storage routine compared with 0.75 using calibrated storage routine. The average Kling-Gupta efficiency criterion was 0.80 and 0.81 for the new and old storage routine, respectively. Runoff recessions are more realistically modelled using the new approach since the root mean square error between the mean of observed and simulated recession characteristics was reduced by almost 50 % using the new storage routine. The parameters of the proposed storage routine are found to be significantly correlated to catchment characteristics, which is potentially useful for predictions in ungauged basins.

Applicability of geomechanical classifications for estimation of strength properties in Brazilian rock masses.

PubMed

Santos, Tatiana B; Lana, Milene S; Santos, Allan E M; Silveira, Larissa R C

2017-01-01

Many authors have been proposed several correlation equations between geomechanical classifications and strength parameters. However, these correlation equations have been based in rock masses with different characteristics when compared to Brazilian rock masses. This paper aims to study the applicability of the geomechanical classifications to obtain strength parameters of three Brazilian rock masses. Four classification systems have been used; the Rock Mass Rating (RMR), the Rock Mass Quality (Q), the Geological Strength Index (GSI) and the Rock Mass Index (RMi). A strong rock mass and two soft rock masses with different degrees of weathering located in the cities of Ouro Preto and Mariana, Brazil; were selected for the study. Correlation equations were used to estimate the strength properties of these rock masses. However, such correlations do not always provide compatible results with the rock mass behavior. For the calibration of the strength values obtained through the use of classification systems, ​​stability analyses of failures in these rock masses have been done. After calibration of these parameters, the applicability of the various correlation equations found in the literature have been discussed. According to the results presented in this paper, some of these equations are not suitable for the studied rock masses.

Constructing a cosmological model-independent Hubble diagram of type Ia supernovae with cosmic chronometers

NASA Astrophysics Data System (ADS)

Li, Zhengxiang; Gonzalez, J. E.; Yu, Hongwei; Zhu, Zong-Hong; Alcaniz, J. S.

2016-02-01

We apply two methods, i.e., the Gaussian processes and the nonparametric smoothing procedure, to reconstruct the Hubble parameter H (z ) as a function of redshift from 15 measurements of the expansion rate obtained from age estimates of passively evolving galaxies. These reconstructions enable us to derive the luminosity distance to a certain redshift z , calibrate the light-curve fitting parameters accounting for the (unknown) intrinsic magnitude of type Ia supernova (SNe Ia), and construct cosmological model-independent Hubble diagrams of SNe Ia. In order to test the compatibility between the reconstructed functions of H (z ), we perform a statistical analysis considering the latest SNe Ia sample, the so-called joint light-curve compilation. We find that, for the Gaussian processes, the reconstructed functions of Hubble parameter versus redshift, and thus the following analysis on SNe Ia calibrations and cosmological implications, are sensitive to prior mean functions. However, for the nonparametric smoothing method, the reconstructed functions are not dependent on initial guess models, and consistently require high values of H0, which are in excellent agreement with recent measurements of this quantity from Cepheids and other local distance indicators.

Large ensemble modeling of the last deglacial retreat of the West Antarctic Ice Sheet: comparison of simple and advanced statistical techniques

NASA Astrophysics Data System (ADS)

Pollard, David; Chang, Won; Haran, Murali; Applegate, Patrick; DeConto, Robert

2016-05-01

A 3-D hybrid ice-sheet model is applied to the last deglacial retreat of the West Antarctic Ice Sheet over the last ˜ 20 000 yr. A large ensemble of 625 model runs is used to calibrate the model to modern and geologic data, including reconstructed grounding lines, relative sea-level records, elevation-age data and uplift rates, with an aggregate score computed for each run that measures overall model-data misfit. Two types of statistical methods are used to analyze the large-ensemble results: simple averaging weighted by the aggregate score, and more advanced Bayesian techniques involving Gaussian process-based emulation and calibration, and Markov chain Monte Carlo. The analyses provide sea-level-rise envelopes with well-defined parametric uncertainty bounds, but the simple averaging method only provides robust results with full-factorial parameter sampling in the large ensemble. Results for best-fit parameter ranges and envelopes of equivalent sea-level rise with the simple averaging method agree well with the more advanced techniques. Best-fit parameter ranges confirm earlier values expected from prior model tuning, including large basal sliding coefficients on modern ocean beds.

Inverse problem to constrain the controlling parameters of large-scale heat transport processes: The Tiberias Basin example

NASA Astrophysics Data System (ADS)

Goretzki, Nora; Inbar, Nimrod; Siebert, Christian; Möller, Peter; Rosenthal, Eliyahu; Schneider, Michael; Magri, Fabien

2015-04-01

Salty and thermal springs exist along the lakeshore of the Sea of Galilee, which covers most of the Tiberias Basin (TB) in the northern Jordan- Dead Sea Transform, Israel/Jordan. As it is the only freshwater reservoir of the entire area, it is important to study the salinisation processes that pollute the lake. Simulations of thermohaline flow along a 35 km NW-SE profile show that meteoric and relic brines are flushed by the regional flow from the surrounding heights and thermally induced groundwater flow within the faults (Magri et al., 2015). Several model runs with trial and error were necessary to calibrate the hydraulic conductivity of both faults and major aquifers in order to fit temperature logs and spring salinity. It turned out that the hydraulic conductivity of the faults ranges between 30 and 140 m/yr whereas the hydraulic conductivity of the Upper Cenomanian aquifer is as high as 200 m/yr. However, large-scale transport processes are also dependent on other physical parameters such as thermal conductivity, porosity and fluid thermal expansion coefficient, which are hardly known. Here, inverse problems (IP) are solved along the NW-SE profile to better constrain the physical parameters (a) hydraulic conductivity, (b) thermal conductivity and (c) thermal expansion coefficient. The PEST code (Doherty, 2010) is applied via the graphical interface FePEST in FEFLOW (Diersch, 2014). The results show that both thermal and hydraulic conductivity are consistent with the values determined with the trial and error calibrations. Besides being an automatic approach that speeds up the calibration process, the IP allows to cover a wide range of parameter values, providing additional solutions not found with the trial and error method. Our study shows that geothermal systems like TB are more comprehensively understood when inverse models are applied to constrain coupled fluid flow processes over large spatial scales. References Diersch, H.-J.G., 2014. FEFLOW Finite Element Modeling of Flow, Mass and Heat Transport in Porous and Fractured Media. Springer- Verlag Berlin Heidelberg ,996p. Doherty J., 2010, PEST: Model-Independent Parameter Estimation. user manual 5th Edition. Watermark, Brisbane, Australia Magri, F., Inbar, N., Siebert C., Rosenthal, E., Guttman, J., Möller, P., 2015. Transient simulations of large-scale hydrogeological processes causing temperature and salinity anomalies in the Tiberias Basin. Journal of Hydrology, 520(0), 342-355.

Uncertainty quantification for constitutive model calibration of brain tissue.

PubMed

Brewick, Patrick T; Teferra, Kirubel

2018-05-31

The results of a study comparing model calibration techniques for Ogden's constitutive model that describes the hyperelastic behavior of brain tissue are presented. One and two-term Ogden models are fit to two different sets of stress-strain experimental data for brain tissue using both least squares optimization and Bayesian estimation. For the Bayesian estimation, the joint posterior distribution of the constitutive parameters is calculated by employing Hamiltonian Monte Carlo (HMC) sampling, a type of Markov Chain Monte Carlo method. The HMC method is enriched in this work to intrinsically enforce the Drucker stability criterion by formulating a nonlinear parameter constraint function, which ensures the constitutive model produces physically meaningful results. Through application of the nested sampling technique, 95% confidence bounds on the constitutive model parameters are identified, and these bounds are then propagated through the constitutive model to produce the resultant bounds on the stress-strain response. The behavior of the model calibration procedures and the effect of the characteristics of the experimental data are extensively evaluated. It is demonstrated that increasing model complexity (i.e., adding an additional term in the Ogden model) improves the accuracy of the best-fit set of parameters while also increasing the uncertainty via the widening of the confidence bounds of the calibrated parameters. Despite some similarity between the two data sets, the resulting distributions are noticeably different, highlighting the sensitivity of the calibration procedures to the characteristics of the data. For example, the amount of uncertainty reported on the experimental data plays an essential role in how data points are weighted during the calibration, and this significantly affects how the parameters are calibrated when combining experimental data sets from disparate sources. Published by Elsevier Ltd.

Calibration of CORSIM models under saturated traffic flow conditions.

DOT National Transportation Integrated Search

2013-09-01

This study proposes a methodology to calibrate microscopic traffic flow simulation models. : The proposed methodology has the capability to calibrate simultaneously all the calibration : parameters as well as demand patterns for any network topology....

Important observations and parameters for a salt water intrusion model

USGS Publications Warehouse

Shoemaker, W.B.

2004-01-01

Sensitivity analysis with a density-dependent ground water flow simulator can provide insight and understanding of salt water intrusion calibration problems far beyond what is possible through intuitive analysis alone. Five simple experimental simulations presented here demonstrate this point. Results show that dispersivity is a very important parameter for reproducing a steady-state distribution of hydraulic head, salinity, and flow in the transition zone between fresh water and salt water in a coastal aquifer system. When estimating dispersivity, the following conclusions can be drawn about the data types and locations considered. (1) The "toe" of the transition zone is the most effective location for hydraulic head and salinity observations. (2) Areas near the coastline where submarine ground water discharge occurs are the most effective locations for flow observations. (3) Salinity observations are more effective than hydraulic head observations. (4) The importance of flow observations aligned perpendicular to the shoreline varies dramatically depending on distance seaward from the shoreline. Extreme parameter correlation can prohibit unique estimation of permeability parameters such as hydraulic conductivity and flow parameters such as recharge in a density-dependent ground water flow model when using hydraulic head and salinity observations. Adding flow observations perpendicular to the shoreline in areas where ground water is exchanged with the ocean body can reduce the correlation, potentially resulting in unique estimates of these parameter values. Results are expected to be directly applicable to many complex situations, and have implications for model development whether or not formal optimization methods are used in model calibration.

Important observations and parameters for a salt water intrusion model.

PubMed

Shoemaker, W Barclay

2004-01-01

Sensitivity analysis with a density-dependent ground water flow simulator can provide insight and understanding of salt water intrusion calibration problems far beyond what is possible through intuitive analysis alone. Five simple experimental simulations presented here demonstrate this point. Results show that dispersivity is a very important parameter for reproducing a steady-state distribution of hydraulic head, salinity, and flow in the transition zone between fresh water and salt water in a coastal aquifer system. When estimating dispersivity, the following conclusions can be drawn about the data types and locations considered. (1) The "toe" of the transition zone is the most effective location for hydraulic head and salinity observations. (2) Areas near the coastline where submarine ground water discharge occurs are the most effective locations for flow observations. (3) Salinity observations are more effective than hydraulic head observations. (4) The importance of flow observations aligned perpendicular to the shoreline varies dramatically depending on distance seaward from the shoreline. Extreme parameter correlation can prohibit unique estimation of permeability parameters such as hydraulic conductivity and flow parameters such as recharge in a density-dependent ground water flow model when using hydraulic head and salinity observations. Adding flow observations perpendicular to the shoreline in areas where ground water is exchanged with the ocean body can reduce the correlation, potentially resulting in unique estimates of these parameter values. Results are expected to be directly applicable to many complex situations, and have implications for model development whether or not formal optimization methods are used in model calibration.

Two-dimensional advective transport in ground-water flow parameter estimation

USGS Publications Warehouse

Anderman, E.R.; Hill, M.C.; Poeter, E.P.

1996-01-01

Nonlinear regression is useful in ground-water flow parameter estimation, but problems of parameter insensitivity and correlation often exist given commonly available hydraulic-head and head-dependent flow (for example, stream and lake gain or loss) observations. To address this problem, advective-transport observations are added to the ground-water flow, parameter-estimation model MODFLOWP using particle-tracking methods. The resulting model is used to investigate the importance of advective-transport observations relative to head-dependent flow observations when either or both are used in conjunction with hydraulic-head observations in a simulation of the sewage-discharge plume at Otis Air Force Base, Cape Cod, Massachusetts, USA. The analysis procedure for evaluating the probable effect of new observations on the regression results consists of two steps: (1) parameter sensitivities and correlations calculated at initial parameter values are used to assess the model parameterization and expected relative contributions of different types of observations to the regression; and (2) optimal parameter values are estimated by nonlinear regression and evaluated. In the Cape Cod parameter-estimation model, advective-transport observations did not significantly increase the overall parameter sensitivity; however: (1) inclusion of advective-transport observations decreased parameter correlation enough for more unique parameter values to be estimated by the regression; (2) realistic uncertainties in advective-transport observations had a small effect on parameter estimates relative to the precision with which the parameters were estimated; and (3) the regression results and sensitivity analysis provided insight into the dynamics of the ground-water flow system, especially the importance of accurate boundary conditions. In this work, advective-transport observations improved the calibration of the model and the estimation of ground-water flow parameters, and use of regression and related techniques produced significant insight into the physical system.

Optimizing weather radar observations using an adaptive multiquadric surface fitting algorithm

NASA Astrophysics Data System (ADS)

Martens, Brecht; Cabus, Pieter; De Jongh, Inge; Verhoest, Niko

2013-04-01

Real time forecasting of river flow is an essential tool in operational water management. Such real time modelling systems require well calibrated models which can make use of spatially distributed rainfall observations. Weather radars provide spatial data, however, since radar measurements are sensitive to a large range of error sources, often a discrepancy between radar observations and ground-based measurements, which are mostly considered as ground truth, can be observed. Through merging ground observations with the radar product, often referred to as data merging, one may force the radar observations to better correspond to the ground-based measurements, without losing the spatial information. In this paper, radar images and ground-based measurements of rainfall are merged based on interpolated gauge-adjustment factors (Moore et al., 1998; Cole and Moore, 2008) or scaling factors. Using the following equation, scaling factors (C(xα)) are calculated at each position xα where a gauge measurement (Ig(xα)) is available: Ig(xα)+-? C (xα) = Ir(xα)+ ? (1) where Ir(xα) is the radar-based observation in the pixel overlapping the rain gauge and ? is a constant making sure the scaling factor can be calculated when Ir(xα) is zero. These scaling factors are interpolated on the radar grid, resulting in a unique scaling factor for each pixel. Multiquadric surface fitting is used as an interpolation algorithm (Hardy, 1971): C*(x0) = aTv + a0 (2) where C*(x0) is the prediction at location x0, the vector a (Nx1, with N the number of ground-based measurements used) and the constant a0 parameters describing the surface and v an Nx1 vector containing the (Euclidian) distance between each point xα used in the interpolation and the point x0. The parameters describing the surface are derived by forcing the surface to be an exact interpolator and impose that the sum of the parameters in a should be zero. However, often, the surface is allowed to pass near the observations (i.e. the observed scaling factors C(xα)) on a distance aαK by introducing an offset parameter K, which results in slightly different equations to calculate a and a0. The described technique is currently being used by the Flemish Environmental Agency in an online forecasting system of river discharges within Flanders (Belgium). However, rescaling the radar data using the described algorithm is not always giving rise to an improved weather radar product. Probably one of the main reasons is the parameters K and ? which are implemented as constants. It can be expected that, among others, depending on the characteristics of the rainfall, different values for the parameters should be used. Adaptation of the parameter values is achieved by an online calibration of K and ? at each time step (every 15 minutes), using validated rain gauge measurements as ground truth. Results demonstrate that rescaling radar images using optimized values for K and ? at each time step lead to a significant improvement of the rainfall estimation, which in turn will result in higher quality discharge predictions. Moreover, it is shown that calibrated values for K and ? can be obtained in near-real time. References Cole, S. J., and Moore, R. J. (2008). Hydrological modelling using raingauge- and radar-based estimators of areal rainfall. Journal of Hydrology, 358(3-4), 159-181. Hardy, R.L., (1971) Multiquadric equations of topography and other irregular surfaces, Journal of Geophysical Research, 76(8): 1905-1915. Moore, R. J., Watson, B. C., Jones, D. A. and Black, K. B. (1989). London weather radar local calibration study. Technical report, Institute of Hydrology.

Efficient Calibration of Distributed Catchment Models Using Perceptual Understanding and Hydrologic Signatures

NASA Astrophysics Data System (ADS)

Hutton, C.; Wagener, T.; Freer, J. E.; Duffy, C.; Han, D.

2015-12-01

Distributed models offer the potential to resolve catchment systems in more detail, and therefore simulate the hydrological impacts of spatial changes in catchment forcing (e.g. landscape change). Such models may contain a large number of model parameters which are computationally expensive to calibrate. Even when calibration is possible, insufficient data can result in model parameter and structural equifinality. In order to help reduce the space of feasible models and supplement traditional outlet discharge calibration data, semi-quantitative information (e.g. knowledge of relative groundwater levels), may also be used to identify behavioural models when applied to constrain spatially distributed predictions of states and fluxes. The challenge is to combine these different sources of information together to identify a behavioural region of state-space, and efficiently search a large, complex parameter space to identify behavioural parameter sets that produce predictions that fall within this behavioural region. Here we present a methodology to incorporate different sources of data to efficiently calibrate distributed catchment models. Metrics of model performance may be derived from multiple sources of data (e.g. perceptual understanding and measured or regionalised hydrologic signatures). For each metric, an interval or inequality is used to define the behaviour of the catchment system, accounting for data uncertainties. These intervals are then combined to produce a hyper-volume in state space. The state space is then recast as a multi-objective optimisation problem, and the Borg MOEA is applied to first find, and then populate the hyper-volume, thereby identifying acceptable model parameter sets. We apply the methodology to calibrate the PIHM model at Plynlimon, UK by incorporating perceptual and hydrologic data into the calibration problem. Furthermore, we explore how to improve calibration efficiency through search initialisation from shorter model runs.

The use of multiobjective calibration and regional sensitivity analysis in simulating hyporheic exchange

USGS Publications Warehouse

Naranjo, Ramon C.; Niswonger, Richard G.; Stone, Mark; Davis, Clinton; McKay, Alan

2012-01-01

We describe an approach for calibrating a two-dimensional (2-D) flow model of hyporheic exchange using observations of temperature and pressure to estimate hydraulic and thermal properties. A longitudinal 2-D heat and flow model was constructed for a riffle-pool sequence to simulate flow paths and flux rates for variable discharge conditions. A uniform random sampling approach was used to examine the solution space and identify optimal values at local and regional scales. We used a regional sensitivity analysis to examine the effects of parameter correlation and nonuniqueness commonly encountered in multidimensional modeling. The results from this study demonstrate the ability to estimate hydraulic and thermal parameters using measurements of temperature and pressure to simulate exchange and flow paths. Examination of the local parameter space provides the potential for refinement of zones that are used to represent sediment heterogeneity within the model. The results indicate vertical hydraulic conductivity was not identifiable solely using pressure observations; however, a distinct minimum was identified using temperature observations. The measured temperature and pressure and estimated vertical hydraulic conductivity values indicate the presence of a discontinuous low-permeability deposit that limits the vertical penetration of seepage beneath the riffle, whereas there is a much greater exchange where the low-permeability deposit is absent. Using both temperature and pressure to constrain the parameter estimation process provides the lowest overall root-mean-square error as compared to using solely temperature or pressure observations. This study demonstrates the benefits of combining continuous temperature and pressure for simulating hyporheic exchange and flow in a riffle-pool sequence. Copyright 2012 by the American Geophysical Union.

Uav Cameras: Overview and Geometric Calibration Benchmark

NASA Astrophysics Data System (ADS)

Cramer, M.; Przybilla, H.-J.; Zurhorst, A.

2017-08-01

Different UAV platforms and sensors are used in mapping already, many of them equipped with (sometimes) modified cameras as known from the consumer market. Even though these systems normally fulfil their requested mapping accuracy, the question arises, which system performs best? This asks for a benchmark, to check selected UAV based camera systems in well-defined, reproducible environments. Such benchmark is tried within this work here. Nine different cameras used on UAV platforms, representing typical camera classes, are considered. The focus is laid on the geometry here, which is tightly linked to the process of geometrical calibration of the system. In most applications the calibration is performed in-situ, i.e. calibration parameters are obtained as part of the project data itself. This is often motivated because consumer cameras do not keep constant geometry, thus, cannot be seen as metric cameras. Still, some of the commercial systems are quite stable over time, as it was proven from repeated (terrestrial) calibrations runs. Already (pre-)calibrated systems may offer advantages, especially when the block geometry of the project does not allow for a stable and sufficient in-situ calibration. Especially for such scenario close to metric UAV cameras may have advantages. Empirical airborne test flights in a calibration field have shown how block geometry influences the estimated calibration parameters and how consistent the parameters from lab calibration can be reproduced.

Delineation and Analysis of Uncertainty of Contributing Areas to Wells at the Southbury Training School, Southbury, Connecticut

USGS Publications Warehouse

Starn, J. Jeffrey; Stone, Janet Radway; Mullaney, John R.

2000-01-01

Contributing areas to public-supply wells at the Southbury Training School in Southbury, Connecticut, were mapped by simulating ground-water flow in stratified glacial deposits in the lower Transylvania Brook watershed. The simulation used nonlinear regression methods and informational statistics to estimate parameters of a ground-water flow model using drawdown data from an aquifer test. The goodness of fit of the model and the uncertainty associated with model predictions were statistically measured. A watershed-scale model, depicting large-scale ground-water flow in the Transylvania Brook watershed, was used to estimate the distribution of groundwater recharge. Estimates of recharge from 10 small basins in the watershed differed on the basis of the drainage characteristics of each basin. Small basins having well-defined stream channels contributed less ground-water recharge than basins having no defined channels because potential ground-water recharge was carried away in the stream channel. Estimates of ground-water recharge were used in an aquifer-scale parameter-estimation model. Seven variations of the ground-water-flow system were posed, each representing the ground-water-flow system in slightly different but realistic ways. The model that most closely reproduced measured hydraulic heads and flows with realistic parameter values was selected as the most representative of the ground-water-flow system and was used to delineate boundaries of the contributing areas. The model fit revealed no systematic model error, which indicates that the model is likely to represent the major characteristics of the actual system. Parameter values estimated during the simulation are as follows: horizontal hydraulic conductivity of coarse-grained deposits, 154 feet per day; vertical hydraulic conductivity of coarse-grained deposits, 0.83 feet per day; horizontal hydraulic conductivity of fine-grained deposits, 29 feet per day; specific yield, 0.007; specific storage, 1.6E-05. Average annual recharge was estimated using the watershed-scale model with no parameter estimation and was determined to be 24 inches per year in the valley areas and 9 inches per year in the upland areas. The parameter estimates produced in the model are similar to expected values, with two exceptions. The estimated specific yield of the stratified glacial deposits is lower than expected, which could be caused by the layered nature of the deposits. The recharge estimate produced by the model was also lower?about 32 percent of the average annual rate. This could be caused by the timing of the aquifer test with respect to the annual cycle of ground-water recharge, and by some of the expected recharge going to parts of the flow system that were not simulated. The data used in the calibration were collected during an aquifer test from October 30 to November 4, 1996. The model fit was very good, as indicated by the correlation coefficient (0.999) between the weighted simulated values and weighted observed values. The model also reproduced the general rise in ground-water levels caused by ground-water recharge and the cyclic fluctuations caused by pumping prior to the aquifer test. Contributing areas were delineated using a particle-tracking procedure. Hypothetical particles of water were introduced at each model cell in the top layer and were tracked to determine whether or not they reached the pumped well. A deterministic contributing area was calculated using the calibrated model, and a probabilistic contributing area was calculated using a Monte Carlo approach along with the calibrated model. The Monte Carlo simulation was done, using the parameter variance/covariance matrix generated by the regression model, to estimate probabilities associated with the contributing area to the wells. The probabilities arise from uncertainty in the estimated parameter values, which in turn arise from the adequacy of the data available to comprehensively describe the groundwater-flow sy

Absolute Isotopic Abundance Ratios and the Accuracy of Δ47 Measurements

NASA Astrophysics Data System (ADS)

Daeron, M.; Blamart, D.; Peral, M.; Affek, H. P.

2016-12-01

Conversion from raw IRMS data to clumped isotope anomalies in CO2 (Δ47) relies on four external parameters: the (13C/12C) ratio of VPDB, the (17O/16O) and (18O/16O) ratios of VSMOW (or VPDB-CO2), and the slope of the triple oxygen isotope line (λ). Here we investigate the influence that these isotopic parameters exert on measured Δ47 values, using real-world data corresponding to 7 months of measurements; simulations based on randomly generated data; precise comparisons between water-equilibrated CO2 samples and between carbonate standards believed to share quasi-identical Δ47 values; reprocessing of two carbonate calibration data sets with different slopes of Δ47 versus T. Using different sets of isotopic parameters generally produces systematic offsets as large as 0.04 ‰ in final Δ47 values. What's more, even using a single set of isotopic parameters can produce intra- and inter-laboratory discrepancies in final Δ47 values, if some of these parameters are inaccurate. Depending on the isotopic compositions of the standards used for conversion to "absolute" values, these errors should correlate strongly with either δ13C or δ18O, or more weakly with both. Based on measurements of samples expected to display identical Δ47 values, such as 25°C water-equilibrated CO2 with different carbon and oxygen isotope compositions, or high-temperature standards ETH-1 and ETH-2, we conclude that the isotopic parameters used so far in most clumped isotope studies produces large, systematic errors controlled by the relative bulk isotopic compositions of samples and standards, which should be one of the key factors responsible for current inter-laboratory discrepancies. By contrast, the isotopic parameters of Brand et al. [2010] appear to yield accurate Δ47 values regardless of bulk isotopic composition. References:Brand, Assonov and Coplen [2010] http://dx.doi.org/10.1351/PAC-REP-09-01-05

Fluid density and concentration measurement using noninvasive in situ ultrasonic resonance interferometry

DOEpatents

Pope, Noah G.; Veirs, Douglas K.; Claytor, Thomas N.

1994-01-01

The specific gravity or solute concentration of a process fluid solution located in a selected structure is determined by obtaining a resonance response spectrum of the fluid/structure over a range of frequencies that are outside the response of the structure itself. A fast fourier transform (FFT) of the resonance response spectrum is performed to form a set of FFT values. A peak value for the FFT values is determined, e.g., by curve fitting, to output a process parameter that is functionally related to the specific gravity and solute concentration of the process fluid solution. Calibration curves are required to correlate the peak FFT value over the range of expected specific gravities and solute concentrations in the selected structure.

Fluid density and concentration measurement using noninvasive in situ ultrasonic resonance interferometry

DOEpatents

Pope, N.G.; Veirs, D.K.; Claytor, T.N.

1994-10-25

The specific gravity or solute concentration of a process fluid solution located in a selected structure is determined by obtaining a resonance response spectrum of the fluid/structure over a range of frequencies that are outside the response of the structure itself. A fast Fourier transform (FFT) of the resonance response spectrum is performed to form a set of FFT values. A peak value for the FFT values is determined, e.g., by curve fitting, to output a process parameter that is functionally related to the specific gravity and solute concentration of the process fluid solution. Calibration curves are required to correlate the peak FFT value over the range of expected specific gravities and solute concentrations in the selected structure. 7 figs.

TH-CD-201-03: A Real-Time Method to Simultaneously Measure Linear Energy Transfer and Dose for Proton Therapy Using Organic Scintillators

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alsanea, F; Therriault-Proulx, F; Sawakuchi, G

Purpose: The light generated in organic scintillators depends on both the radiation dose and the linear energy transfer (LET). The LET dependence leads to an under-response of the detector in the Bragg peak of proton beams. This phenomenon, called ionization quenching, must be corrected to obtain accurate dose measurements of proton beams. This work exploits the ionization quenching phenomenon to provide a method of measuring LET and auto correcting quenching. Methods: We exposed simultaneously four different organic scintillators (BCF-12, PMMA, PVT, and LSD; 1mm in diameter) and a plane parallel ionization chamber in passively scattered proton beams to doses betweenmore » 32 and 43 cGy and fluence averaged LET values from 0.47 to 1.26 keV/µm. The LET values for each irradiation condition were determined using a validated Monte Carlo model of the beam line. We determined the quenching parameter in the Birk’s equation for scintillation in BCF-12 for dose measurements. One set of irradiation conditions was used to correlate the scintillation response ratio to the LET values and plot a scintillation response ratio versus LET calibration curve. Irradiation conditions independent from the calibration ones were used to validate this method. Comparisons to the expected values were made on both the basis of dose and LET. Results: Among all the scintillators investigated, the ratio of PMMA to BCF-12 provided the best correlation to LET values and was used as the LET calibration curve. The expected LET values in the validation set were within 2%±6%, which resulted in dose accuracy of 1.5%±5.8% for the range of LET values investigated in this work. Conclusion: We have demonstrated the feasibility of using the ratio between the light output of two organic scintillators to simultaneously measure LET and dose of therapeutic proton beams. Further studies are needed to verify the response in higher LET values.« less

Global SWOT Data Assimilation of River Hydrodynamic Model; the Twin Simulation Test of CaMa-Flood

NASA Astrophysics Data System (ADS)

Ikeshima, D.; Yamazaki, D.; Kanae, S.

2016-12-01

CaMa-Flood is a global scale model for simulating hydrodynamics in large scale rivers. It can simulate river hydrodynamics such as river discharge, flooded area, water depth and so on by inputting water runoff derived from land surface model. Recently many improvements at parameters or terrestrial data are under process to enhance the reproducibility of true natural phenomena. However, there are still some errors between nature and simulated result due to uncertainties in each model. SWOT (Surface water and Ocean Topography) is a satellite, which is going to be launched in 2021, can measure open water surface elevation. SWOT observed data can be used to calibrate hydrodynamics model at river flow forecasting and is expected to improve model's accuracy. Combining observation data into model to calibrate is called data assimilation. In this research, we developed data-assimilated river flow simulation system in global scale, using CaMa-Flood as river hydrodynamics model and simulated SWOT as observation data. Generally at data assimilation, calibrating "model value" with "observation value" makes "assimilated value". However, the observed data of SWOT satellite will not be available until its launch in 2021. Instead, we simulated the SWOT observed data using CaMa-Flood. Putting "pure input" into CaMa-Flood produce "true water storage". Extracting actual daily swath of SWOT from "true water storage" made simulated observation. For "model value", we made "disturbed water storage" by putting "noise disturbed input" to CaMa-Flood. Since both "model value" and "observation value" are made by same model, we named this twin simulation. At twin simulation, simulated observation of "true water storage" is combined with "disturbed water storage" to make "assimilated value". As the data assimilation method, we used ensemble Kalman filter. If "assimilated value" is closer to "true water storage" than "disturbed water storage", the data assimilation can be marked effective. Also by changing the input disturbance of "disturbed water storage", acceptable rate of uncertainty at the input may be discussed.

Determination of noise equivalent reflectance for a multispectral scanner: A scanner sensitivity study

NASA Technical Reports Server (NTRS)

Gibbons, D. E.; Richard, R. R.

1979-01-01

The methods used to calculate the sensitivity parameter noise equivalent reflectance of a remote-sensing scanner are explored, and the results are compared with values measured over calibrated test sites. Data were acquired on four occasions covering a span of 4 years and providing various atmospheric conditions. One of the calculated values was based on assumed atmospheric conditions, whereas two others were based on atmospheric models. Results indicate that the assumed atmospheric conditions provide useful answers adequate for many purposes. A nomograph was developed to indicate sensitivity variations due to geographic location, time of day, and season.

Improving Hydrological Simulations by Incorporating GRACE Data for Parameter Calibration

NASA Astrophysics Data System (ADS)

Bai, P.

2017-12-01

Hydrological model parameters are commonly calibrated by observed streamflow data. This calibration strategy is questioned when the modeled hydrological variables of interest are not limited to streamflow. Well-performed streamflow simulations do not guarantee the reliable reproduction of other hydrological variables. One of the reasons is that hydrological model parameters are not reasonably identified. The Gravity Recovery and Climate Experiment (GRACE) satellite-derived total water storage change (TWSC) data provide an opportunity to constrain hydrological model parameterizations in combination with streamflow observations. We constructed a multi-objective calibration scheme based on GRACE-derived TWSC and streamflow observations, with the aim of improving the parameterizations of hydrological models. The multi-objective calibration scheme was compared with the traditional single-objective calibration scheme, which is based only on streamflow observations. Two monthly hydrological models were employed on 22 Chinese catchments with different hydroclimatic conditions. The model evaluation was performed using observed streamflows, GRACE-derived TWSC, and evapotranspiraiton (ET) estimates from flux towers and from the water balance approach. Results showed that the multi-objective calibration provided more reliable TWSC and ET simulations without significant deterioration in the accuracy of streamflow simulations than the single-objective calibration. In addition, the improvements of TWSC and ET simulations were more significant in relatively dry catchments than in relatively wet catchments. This study highlights the importance of including additional constraints besides streamflow observations in the parameter estimation to improve the performances of hydrological models.

Inflight Radiometric Calibration of New Horizons' Multispectral Visible Imaging Camera (MVIC)

NASA Technical Reports Server (NTRS)

Howett, C. J. A.; Parker, A. H.; Olkin, C. B.; Reuter, D. C.; Ennico, K.; Grundy, W. M.; Graps, A. L.; Harrison, K. P.; Throop, H. B.; Buie, M. W.;

Can we calibrate simultaneously groundwater recharge and aquifer hydrodynamic parameters ?

NASA Astrophysics Data System (ADS)

Hassane Maina, Fadji; Ackerer, Philippe; Bildstein, Olivier

2017-04-01

By groundwater model calibration, we consider here fitting the measured piezometric heads by estimating the hydrodynamic parameters (storage term and hydraulic conductivity) and the recharge. It is traditionally recommended to avoid simultaneous calibration of groundwater recharge and flow parameters because of correlation between recharge and the flow parameters. From a physical point of view, little recharge associated with low hydraulic conductivity can provide very similar piezometric changes than higher recharge and higher hydraulic conductivity. If this correlation is true under steady state conditions, we assume that this correlation is much weaker under transient conditions because recharge varies in time and the parameters do not. Moreover, the recharge is negligible during summer time for many climatic conditions due to reduced precipitation, increased evaporation and transpiration by vegetation cover. We analyze our hypothesis through global sensitivity analysis (GSA) in conjunction with the polynomial chaos expansion (PCE) methodology. We perform GSA by calculating the Sobol indices, which provide a variance-based 'measure' of the effects of uncertain parameters (storage and hydraulic conductivity) and recharge on the piezometric heads computed by the flow model. The choice of PCE has the following two benefits: (i) it provides the global sensitivity indices in a straightforward manner, and (ii) PCE can serve as a surrogate model for the calibration of parameters. The coefficients of the PCE are computed by probabilistic collocation. We perform the GSA on simplified real conditions coming from an already built groundwater model dedicated to a subdomain of the Upper-Rhine aquifer (geometry, boundary conditions, climatic data). GSA shows that the simultaneous calibration of recharge and flow parameters is possible if the calibration is performed over at least one year. It provides also the valuable information of the sensitivity versus time, depending on the aquifer inertia and climatic conditions. The groundwater levels variations during recharge (increase) are sensitive to the storage coefficient whereas the groundwater levels variations after recharge (decrease) are sensitive to the hydraulic conductivity. The performed model calibration on synthetic data sets shows that the parameters and recharge are estimated quite accurately.

Unifying distance-based goodness-of-fit indicators for hydrologic model assessment

NASA Astrophysics Data System (ADS)

Cheng, Qinbo; Reinhardt-Imjela, Christian; Chen, Xi; Schulte, Achim

2014-05-01

The goodness-of-fit indicator, i.e. efficiency criterion, is very important for model calibration. However, recently the knowledge about the goodness-of-fit indicators is all empirical and lacks a theoretical support. Based on the likelihood theory, a unified distance-based goodness-of-fit indicator termed BC-GED model is proposed, which uses the Box-Cox (BC) transformation to remove the heteroscedasticity of model errors and the generalized error distribution (GED) with zero-mean to fit the distribution of model errors after BC. The BC-GED model can unify all recent distance-based goodness-of-fit indicators, and reveals the mean square error (MSE) and the mean absolute error (MAE) that are widely used goodness-of-fit indicators imply statistic assumptions that the model errors follow the Gaussian distribution and the Laplace distribution with zero-mean, respectively. The empirical knowledge about goodness-of-fit indicators can be also easily interpreted by BC-GED model, e.g. the sensitivity to high flow of the goodness-of-fit indicators with large power of model errors results from the low probability of large model error in the assumed distribution of these indicators. In order to assess the effect of the parameters (i.e. the BC transformation parameter λ and the GED kurtosis coefficient β also termed the power of model errors) of BC-GED model on hydrologic model calibration, six cases of BC-GED model were applied in Baocun watershed (East China) with SWAT-WB-VSA model. Comparison of the inferred model parameters and model simulation results among the six indicators demonstrates these indicators can be clearly separated two classes by the GED kurtosis β: β >1 and β ≤ 1. SWAT-WB-VSA calibrated by the class β >1 of distance-based goodness-of-fit indicators captures high flow very well and mimics the baseflow very badly, but it calibrated by the class β ≤ 1 mimics the baseflow very well, because first the larger value of β, the greater emphasis is put on high flow and second the derivative of GED probability density function at zero is zero as β >1, but discontinuous as β ≤ 1, and even infinity as β < 1 with which the maximum likelihood estimation can guarantee the model errors approach zero as well as possible. The BC-GED that estimates the parameters (i.e. λ and β) of BC-GED model as well as hydrologic model parameters is the best distance-based goodness-of-fit indicator because not only the model validation using groundwater levels is very good, but also the model errors fulfill the statistic assumption best. However, in some cases of model calibration with a few observations e.g. calibration of single-event model, for avoiding estimation of the parameters of BC-GED model the MAE i.e. the boundary indicator (β = 1) of the two classes, can replace the BC-GED, because the model validation of MAE is best.

Modeling GPR data to interpret porosity and DNAPL saturations for calibration of a 3-D multiphase flow simulation

USGS Publications Warehouse

Sneddon, Kristen W.; Powers, Michael H.; Johnson, Raymond H.; Poeter, Eileen P.

2002-01-01

Dense nonaqueous phase liquids (DNAPLs) are a pervasive and persistent category of groundwater contamination. In an effort to better understand their unique subsurface behavior, a controlled and carefully monitored injection of PCE (perchloroethylene), a typical DNAPL, was performed in conjunction with the University of Waterloo at Canadian Forces Base Borden in 1991. Of the various geophysical methods used to monitor the migration of injected PCE, the U.S. Geological Survey collected 500-MHz ground penetrating radar (GPR) data. These data are used in determining calibration parameters for a multiphase flow simulation. GPR data were acquired over time on a fixed two-dimensional surficial grid as the DNAPL was injected into the subsurface. Emphasis is on the method of determining DNAPL saturation values from this time-lapse GPR data set. Interactive full-waveform GPR modeling of regularized field traces resolves relative dielectric permittivity versus depth profiles for pre-injection and later-time data. Modeled values are end members in recursive calculations of the Bruggeman-Hanai-Sen (BHS) mixing formula, yielding interpreted pre-injection porosity and post-injection DNAPL saturation values. The resulting interpreted physical properties of porosity and DNAPL saturation of the Borden test cell, defined on a grid spacing of 50 cm with 1-cm depth resolution, are used as observations for calibration of a 3-D multiphase flow simulation. Calculated values of DNAPL saturation in the subsurface at 14 and 22 hours after the start of injection, from both the GPR and the multiphase flow modeling, are interpolated volumetrically and presented for visual comparison.

ATR-FTIR membrane-based sensor for the simultaneous determination of surfactant and oil total indices in industrial degreasing baths.

PubMed

Lucena, Rafael; Cárdenas, Soledad; Gallego, Mercedes; Valcárcel, Miguel

2006-03-01

Monitoring the exhaustion of alkaline degreasing baths is one of the main aspects in metal mechanizing industrial process control. The global level of surfactant, and mainly grease, can be used as ageing indicators. In this paper, an attenuated total reflection-Fourier transform infrared (ATR-FTIR) membrane-based sensor is presented for the determination of these parameters. The system is based on a micro-liquid-liquid extraction of the analytes through a polymeric membrane from the aqueous to the organic solvent layer which is in close contact with the internal reflection element and continuously monitored. Samples are automatically processed using a simple, robust sequential injection analysis (SIA) configuration, on-line coupled to the instrument. The global signal obtained for both families of compounds are processed via a multivariate calibration technique (partial least squares, PLS). Excellent correlation was obtained for the values given by the proposed method compared to those of the gravimetric reference one with very low error values for both calibration and validation.

Optimal Bayesian Adaptive Design for Test-Item Calibration.

PubMed

van der Linden, Wim J; Ren, Hao

2015-06-01

An optimal adaptive design for test-item calibration based on Bayesian optimality criteria is presented. The design adapts the choice of field-test items to the examinees taking an operational adaptive test using both the information in the posterior distributions of their ability parameters and the current posterior distributions of the field-test parameters. Different criteria of optimality based on the two types of posterior distributions are possible. The design can be implemented using an MCMC scheme with alternating stages of sampling from the posterior distributions of the test takers' ability parameters and the parameters of the field-test items while reusing samples from earlier posterior distributions of the other parameters. Results from a simulation study demonstrated the feasibility of the proposed MCMC implementation for operational item calibration. A comparison of performances for different optimality criteria showed faster calibration of substantial numbers of items for the criterion of D-optimality relative to A-optimality, a special case of c-optimality, and random assignment of items to the test takers.

Model Calibration in Watershed Hydrology

NASA Technical Reports Server (NTRS)

Yilmaz, Koray K.; Vrugt, Jasper A.; Gupta, Hoshin V.; Sorooshian, Soroosh

2009-01-01

Hydrologic models use relatively simple mathematical equations to conceptualize and aggregate the complex, spatially distributed, and highly interrelated water, energy, and vegetation processes in a watershed. A consequence of process aggregation is that the model parameters often do not represent directly measurable entities and must, therefore, be estimated using measurements of the system inputs and outputs. During this process, known as model calibration, the parameters are adjusted so that the behavior of the model approximates, as closely and consistently as possible, the observed response of the hydrologic system over some historical period of time. This Chapter reviews the current state-of-the-art of model calibration in watershed hydrology with special emphasis on our own contributions in the last few decades. We discuss the historical background that has led to current perspectives, and review different approaches for manual and automatic single- and multi-objective parameter estimation. In particular, we highlight the recent developments in the calibration of distributed hydrologic models using parameter dimensionality reduction sampling, parameter regularization and parallel computing.

Sensitivity analysis of hydraulic and thermal parameters inducing anomalous heat flow in the Lower Yarmouk Gorge

NASA Astrophysics Data System (ADS)

Goretzki, Nora; Inbar, Nimrod; Kühn, Michael; Möller, Peter; Rosenthal, Eliyahu; Schneider, Michael; Siebert, Christian; Magri, Fabien

2016-04-01

The Lower Yarmouk Gorge, at the border between Israel and Jordan, is characterized by an anomalous temperature gradient of 46 °C/km. Numerical simulations of thermally-driven flow show that ascending thermal waters are the result of mixed convection, i.e. the interaction between the regional flow from the surrounding heights and buoyant flow within permeable faults [1]. Those models were calibrated against available temperature logs by running several forward problems (FP), with a classic "trial and error" method. In the present study, inverse problems (IP) are applied to find alternative parameter distributions that also lead to the observed thermal anomalies. The investigated physical parameters are hydraulic conductivity and thermal conductivity. To solve the IP, the PEST® code [2] is applied via the graphical interface FEPEST® in FEFLOW® [3]. The results show that both hydraulic and thermal conductivity are consistent with the values determined with the trial and error calibrations, which precede this study. However, the IP indicates that the hydraulic conductivity of the Senonian Paleocene aquitard can be 8.54*10-3 m/d, which is three times lower than the originally estimated value in [1]. Moreover, the IP suggests that the hydraulic conductivity in the faults can increase locally up to 0.17 m/d. These highly permeable areas can be interpreted as local damage zones at the faults/units intersections. They can act as lateral pathways in the deep aquifers that allow deep outflow of thermal water. This presentation provides an example about the application of FP and IP to infer a wide range of parameter values that reproduce observed environmental issues. [1] Magri F, Inbar N, Siebert C, Rosenthal E, Guttman J, Möller P (2015) Transient simulations of large-scale hydrogeological processes causing temperature and salinity anomalies in the Tiberias Basin. Journal of Hydrology, 520, 342-355 [2] Doherty J (2010) PEST: Model-Independent Parameter Estimation. user manual 5th Edition. Watermark, Brisbane, Australia [3] Diersch H.-J.G. (2014) FEFLOW Finite Element Modeling of Flow, Mass and Heat Transport in Porous and Fractured Media. Springer- Verlag Berlin Heidelberg, 996p

Cosmic CARNage I: on the calibration of galaxy formation models

NASA Astrophysics Data System (ADS)

Knebe, Alexander; Pearce, Frazer R.; Gonzalez-Perez, Violeta; Thomas, Peter A.; Benson, Andrew; Asquith, Rachel; Blaizot, Jeremy; Bower, Richard; Carretero, Jorge; Castander, Francisco J.; Cattaneo, Andrea; Cora, Sofía A.; Croton, Darren J.; Cui, Weiguang; Cunnama, Daniel; Devriendt, Julien E.; Elahi, Pascal J.; Font, Andreea; Fontanot, Fabio; Gargiulo, Ignacio D.; Helly, John; Henriques, Bruno; Lee, Jaehyun; Mamon, Gary A.; Onions, Julian; Padilla, Nelson D.; Power, Chris; Pujol, Arnau; Ruiz, Andrés N.; Srisawat, Chaichalit; Stevens, Adam R. H.; Tollet, Edouard; Vega-Martínez, Cristian A.; Yi, Sukyoung K.

2018-04-01

We present a comparison of nine galaxy formation models, eight semi-analytical, and one halo occupation distribution model, run on the same underlying cold dark matter simulation (cosmological box of comoving width 125h-1 Mpc, with a dark-matter particle mass of 1.24 × 109h-1M⊙) and the same merger trees. While their free parameters have been calibrated to the same observational data sets using two approaches, they nevertheless retain some `memory' of any previous calibration that served as the starting point (especially for the manually tuned models). For the first calibration, models reproduce the observed z = 0 galaxy stellar mass function (SMF) within 3σ. The second calibration extended the observational data to include the z = 2 SMF alongside the z ˜ 0 star formation rate function, cold gas mass, and the black hole-bulge mass relation. Encapsulating the observed evolution of the SMF from z = 2 to 0 is found to be very hard within the context of the physics currently included in the models. We finally use our calibrated models to study the evolution of the stellar-to-halo mass (SHM) ratio. For all models, we find that the peak value of the SHM relation decreases with redshift. However, the trends seen for the evolution of the peak position as well as the mean scatter in the SHM relation are rather weak and strongly model dependent. Both the calibration data sets and model results are publicly available.

Development of an automated procedure for estimation of the spatial variation of runoff in large river basins

USDA-ARS?s Scientific Manuscript database

The use of distributed parameter models to address water resource management problems has increased in recent years. Calibration is necessary to reduce the uncertainties associated with model input parameters. Manual calibration of a distributed parameter model is a very time consuming effort. There...

An initial investigation of the long-term trends in the fluxgate magnetometer (FGM) calibration parameters on the four Cluster spacecraft

NASA Astrophysics Data System (ADS)

Alconcel, L. N. S.; Fox, P.; Brown, P.; Oddy, T. M.; Lucek, E. L.; Carr, C. M.

2014-07-01

Over the course of more than 10 years in operation, the calibration parameters of the outboard fluxgate magnetometer (FGM) sensors on the four Cluster spacecraft are shown to be remarkably stable. The parameters are refined on the ground during the rigorous FGM calibration process performed for the Cluster Active Archive (CAA). Fluctuations in some parameters show some correlation with trends in the sensor temperature (orbit position). The parameters, particularly the offsets, of the spacecraft 1 (C1) sensor have undergone more long-term drift than those of the other spacecraft (C2, C3 and C4) sensors. Some potentially anomalous calibration parameters have been identified and will require further investigation in future. However, the observed long-term stability demonstrated in this initial study gives confidence in the accuracy of the Cluster magnetic field data. For the most sensitive ranges of the FGM instrument, the offset drift is typically 0.2 nT per year in each sensor on C1 and negligible on C2, C3 and C4.

An initial investigation of the long-term trends in the fluxgate magnetometer (FGM) calibration parameters on the four Cluster spacecraft

NASA Astrophysics Data System (ADS)

Alconcel, L. N. S.; Fox, P.; Brown, P.; Oddy, T. M.; Lucek, E. L.; Carr, C. M.

2014-01-01

Over the course of more than ten years in operation, the calibration parameters of the outboard fluxgate magnetometer (FGM) sensors on the four Cluster spacecraft are shown to be remarkably stable. The parameters are refined on the ground during the rigorous FGM calibration process performed for the Cluster Active Archive (CAA). Fluctuations in some parameters show some correlation with trends in the sensor temperature (orbit position). The parameters, particularly the offsets, of the Spacecraft1 (C1) sensor have undergone more long-term drift than those of the other spacecraft (C2, C3 and C4) sensors. Some potentially anomalous calibration parameters have been identified and will require further investigation in future. However, the observed long-term stability demonstrated in this initial study gives confidence in the relative accuracy of the Cluster magnetic field data. For the most sensitive ranges of the FGM instrument, the offset drift is typically 0.2 nT yr-1 in each sensor on C1 and negligible on C2, C3 and C4.

Calibration of numerical models for small debris flows in Yosemite Valley, California, USA

USGS Publications Warehouse

Bertolo, P.; Wieczorek, G.F.

2005-01-01

This study compares documented debris flow runout distances with numerical simulations in the Yosemite Valley of California, USA, where about 15% of historical events of slope instability can be classified as debris flows and debris slides (Wieczorek and Snyder, 2004). To model debris flows in the Yosemite Valley, we selected six streams with evidence of historical debris flows; three of the debris flow deposits have single channels, and the other three split their pattern in the fan area into two or more channels. From field observations all of the debris flows involved coarse material, with only very small clay content. We applied the one dimensional DAN (Dynamic ANalysis) model (Hungr, 1995) and the two-dimensional FLO2D model (O'Brien et al., 1993) to predict and compare the runout distance and the velocity of the debris flows observed in the study area. As a first step, we calibrated the parameters for the two softwares through the back analysis of three debris- flows channels using a trial-and-error procedure starting with values suggested in the literature. In the second step we applied the selected values to the other channels, in order to evaluate their predictive capabilities. After parameter calibration using three debris flows we obtained results similar to field observations We also obtained a good agreement between the two models for velocities. Both models are strongly influenced by topography: we used the 30 m cell size DTM available for the study area, that is probably not accurate enough for a highly detailed analysis, but it can be sufficient for a first screening. European Geosciences Union ?? 2005 Author(s). This work is licensed under a Creative Commons License.

The Lyman-Continuum Fluxes and Stellar Parameters of O and Early B-Type Stars

NASA Technical Reports Server (NTRS)

Vacca, William D.; Garmany, Catherine D.; Shull, J. Michael

1996-01-01

Using the results of the most recent stellar atmosphere models applied to a sample of hot stars, we construct calibrations of effective temperature (T(sub eff)), and gravity (log(sub g)) with a spectral type and luminosity class for Galactic 0-type and early B-type stars. From the model results we also derive an empirical relation between the bolometric correction and T(sub eff) and log g. Using a sample of stars with known distances located in OB associations in the Galaxy and the Large Magellanic Cloud, we derive a new calibration of M(sub v) with spectral class. With these new calibrations and the stellar atmosphere models of Kurucz, we calculate the physical parameters and ionizing photon luminosities in the H(0) and He(0) continua for O and early B-type stars. We find substantial differences between our values of the Lyman- continuum luminosity and those reported in the literature. We also discuss the systematic discrepancy between O-type stellar masses derived from spectroscopic models and those derived from evolutionary tracks. Most likely, the cause of this 'mass discrepancy' lies primarily in the atmospheric models, which are plane parallel and hydrostatic and therefore do not account for an extended atmosphere and the velocity fields in a stellar wind. Finally, we present a new computation of the Lyman-continuum luminosity from 429 known O stars located within 2.5 kpc of the Sun. We find the total ionizing luminosity from this population ((Q(sub 0)(sup T(sub ot))) = 7.0 x 10(exp 51) photons/s) to be 47% larger than that determined using the Lyman continuum values tabulated by Panagia.

Signal Space Separation Method for a Biomagnetic Sensor Array Arranged on a Flat Plane for Magnetocardiographic Applications: A Computer Simulation Study

PubMed Central

2018-01-01

Although the signal space separation (SSS) method can successfully suppress interference/artifacts overlapped onto magnetoencephalography (MEG) signals, the method is considered inapplicable to data from nonhelmet-type sensor arrays, such as the flat sensor arrays typically used in magnetocardiographic (MCG) applications. This paper shows that the SSS method is still effective for data measured from a (nonhelmet-type) array of sensors arranged on a flat plane. By using computer simulations, it is shown that the optimum location of the origin can be determined by assessing the dependence of signal and noise gains of the SSS extractor on the origin location. The optimum values of the parameters LC and LD, which, respectively, indicate the truncation values of the multipole-order ℓ of the internal and external subspaces, are also determined by evaluating dependences of the signal, noise, and interference gains (i.e., the shield factor) on these parameters. The shield factor exceeds 104 for interferences originating from fairly distant sources. However, the shield factor drops to approximately 100 when calibration errors of 0.1% exist and to 30 when calibration errors of 1% exist. The shielding capability can be significantly improved using vector sensors, which measure the x, y, and z components of the magnetic field. With 1% calibration errors, a vector sensor array still maintains a shield factor of approximately 500. It is found that the SSS application to data from flat sensor arrays causes a distortion in the signal magnetic field, but it is shown that the distortion can be corrected by using an SSS-modified sensor lead field in the voxel space analysis. PMID:29854364

A glucose monitoring system for on line estimation in man of blood glucose concentration using a miniaturized glucose sensor implanted in the subcutaneous tissue and a wearable control unit.

PubMed

Poitout, V; Moatti-Sirat, D; Reach, G; Zhang, Y; Wilson, G S; Lemonnier, F; Klein, J C

1993-07-01

We have developed a miniaturized glucose sensor which has been shown previously to function adequately when implanted in the subcutaneous tissue of rats and dogs. Following a glucose load, the sensor output increases, making it possible to calculate a sensitivity coefficient to glucose in vivo, and an extrapolated background current in the absence of glucose. These parameters are used for estimating at any time the apparent subcutaneous glucose concentration from the current. In the previous studies, this calibration was performed a posteriori, on the basis of the retrospective analysis of the changes in blood glucose and in the current generated by the sensor. However, for clinical application of the system, an on line estimation of glucose concentration would be necessary. Thus, this study was undertaken in order to assess the possibility of calibrating the sensor in real time, using a novel calibration procedure and a monitoring unit which was specifically designed for this purpose. This electronic device is able to measure, to filter and to store the current. During an oral glucose challenge, when a stable current is reached, it is possible to feed the unit with two different values of blood glucose and their corresponding times. The unit calculates the in vivo parameters, transforms every single value of current into an estimation of the glucose concentration, and then displays this estimation. In this study, 11 sensors were investigated of which two did not respond to glucose. In the other nine trials, the volunteers were asked to record every 30 s what appeared on the display during the secondary decrease in blood glucose.(ABSTRACT TRUNCATED AT 250 WORDS)

An Improved Fast Self-Calibration Method for Hybrid Inertial Navigation System under Stationary Condition

PubMed Central

Liu, Bingqi; Wei, Shihui; Su, Guohua; Wang, Jiping; Lu, Jiazhen

2018-01-01

The navigation accuracy of the inertial navigation system (INS) can be greatly improved when the inertial measurement unit (IMU) is effectively calibrated and compensated, such as gyro drifts and accelerometer biases. To reduce the requirement for turntable precision in the classical calibration method, a continuous dynamic self-calibration method based on a three-axis rotating frame for the hybrid inertial navigation system is presented. First, by selecting a suitable IMU frame, the error models of accelerometers and gyros are established. Then, by taking the navigation errors during rolling as the observations, the overall twenty-one error parameters of hybrid inertial navigation system (HINS) are identified based on the calculation of the intermediate parameter. The actual experiment verifies that the method can identify all error parameters of HINS and this method has equivalent accuracy to the classical calibration on a high-precision turntable. In addition, this method is rapid, simple and feasible. PMID:29695041

An Improved Fast Self-Calibration Method for Hybrid Inertial Navigation System under Stationary Condition.

PubMed

Liu, Bingqi; Wei, Shihui; Su, Guohua; Wang, Jiping; Lu, Jiazhen

2018-04-24

The navigation accuracy of the inertial navigation system (INS) can be greatly improved when the inertial measurement unit (IMU) is effectively calibrated and compensated, such as gyro drifts and accelerometer biases. To reduce the requirement for turntable precision in the classical calibration method, a continuous dynamic self-calibration method based on a three-axis rotating frame for the hybrid inertial navigation system is presented. First, by selecting a suitable IMU frame, the error models of accelerometers and gyros are established. Then, by taking the navigation errors during rolling as the observations, the overall twenty-one error parameters of hybrid inertial navigation system (HINS) are identified based on the calculation of the intermediate parameter. The actual experiment verifies that the method can identify all error parameters of HINS and this method has equivalent accuracy to the classical calibration on a high-precision turntable. In addition, this method is rapid, simple and feasible.

Response simulation and theoretical calibration of a dual-induction resistivity LWD tool

NASA Astrophysics Data System (ADS)

Xu, Wei; Ke, Shi-Zhen; Li, An-Zong; Chen, Peng; Zhu, Jun; Zhang, Wei

2014-03-01

In this paper, responses of a new dual-induction resistivity logging-while-drilling (LWD) tool in 3D inhomogeneous formation models are simulated by the vector finite element method (VFEM), the influences of the borehole, invaded zone, surrounding strata, and tool eccentricity are analyzed, and calibration loop parameters and calibration coefficients of the LWD tool are discussed. The results show that the tool has a greater depth of investigation than that of the existing electromagnetic propagation LWD tools and is more sensitive to azimuthal conductivity. Both deep and medium induction responses have linear relationships with the formation conductivity, considering optimal calibration loop parameters and calibration coefficients. Due to the different depths of investigation and resolution, deep induction and medium induction are affected differently by the formation model parameters, thereby having different correction factors. The simulation results can provide theoretical references for the research and interpretation of the dual-induction resistivity LWD tools.

Camera calibration based on the back projection process

NASA Astrophysics Data System (ADS)

Gu, Feifei; Zhao, Hong; Ma, Yueyang; Bu, Penghui

2015-12-01

Camera calibration plays a crucial role in 3D measurement tasks of machine vision. In typical calibration processes, camera parameters are iteratively optimized in the forward imaging process (FIP). However, the results can only guarantee the minimum of 2D projection errors on the image plane, but not the minimum of 3D reconstruction errors. In this paper, we propose a universal method for camera calibration, which uses the back projection process (BPP). In our method, a forward projection model is used to obtain initial intrinsic and extrinsic parameters with a popular planar checkerboard pattern. Then, the extracted image points are projected back into 3D space and compared with the ideal point coordinates. Finally, the estimation of the camera parameters is refined by a non-linear function minimization process. The proposed method can obtain a more accurate calibration result, which is more physically useful. Simulation and practical data are given to demonstrate the accuracy of the proposed method.

The Future Spaceborne Hyperspectral Imager Enmap: its In-Flight Radiometric and Geometric Calibration Concept

NASA Astrophysics Data System (ADS)

Schneider, M.; Müller, R.; Krawzcyk, H.; Bachmann, M.; Storch, T.; Mogulsky, V.; Hofer, S.

2012-07-01

The German Aerospace Center DLR - namely the Earth Observation Center EOC and the German Space Operations Center GSOC - is responsible for the establishment of the ground segment of the future German hyperspectral satellite mission EnMAP (Environmental Mapping and Analysis Program). The Earth Observation Center has long lasting experiences with air- and spaceborne acquisition, processing, and analysis of hyperspectral image data. In the first part of this paper, an overview of the radiometric in-flight calibration concept including dark value measurements, deep space measurements, internal lamps measurements and sun measurements is presented. Complemented by pre-launch calibration and characterization these analyses will deliver a detailed and quantitative assessment of possible changes of spectral and radiometric characteristics of the hyperspectral instrument, e.g. due to degradation of single elements. A geometric accuracy of 100 m, which will be improved to 30 m with respect to a used reference image, if it exists, will be achieved by ground processing. Therfore, and for the required co-registration accuracy between SWIR and VNIR channels, additional to the radiometric calibration, also a geometric calibration is necessary. In the second part of this paper, the concept of the geometric calibration is presented in detail. The geometric processing of EnMAP scenes will be based on laboratory calibration results. During repeated passes over selected calibration areas images will be acquired. The update of geometric camera model parameters will be done by an adjustment using ground control points, which will be extracted by automatic image matching. In the adjustment, the improvements of the attitude angles (boresight angles), the improvements of the interior orientation (view vector) and the improvements of the position data are estimated. In this paper, the improvement of the boresight angles is presented in detail as an example. The other values and combinations follow the same rules. The geometric calibration will mainly be executed during the commissioning phase, later in the mission it is only executed if required, i.e. if the geometric accuracy of the produced images is close to or exceeds the requirements of 100 m or 30 m respectively, whereas the radiometric calibration will be executed periodically during the mission with a higher frequency during commissioning phase.

Calibration of imaging parameters for space-borne airglow photography using city light positions

NASA Astrophysics Data System (ADS)

Hozumi, Yuta; Saito, Akinori; Ejiri, Mitsumu K.

2016-09-01

A new method for calibrating imaging parameters of photographs taken from the International Space Station (ISS) is presented in this report. Airglow in the mesosphere and the F-region ionosphere was captured on the limb of the Earth with a digital single-lens reflex camera from the ISS by astronauts. To utilize the photographs as scientific data, imaging parameters, such as the angle of view, exact position, and orientation of the camera, should be determined because they are not measured at the time of imaging. A new calibration method using city light positions shown in the photographs was developed to determine these imaging parameters with high accuracy suitable for airglow study. Applying the pinhole camera model, the apparent city light positions on the photograph are matched with the actual city light locations on Earth, which are derived from the global nighttime stable light map data obtained by the Defense Meteorological Satellite Program satellite. The correct imaging parameters are determined in an iterative process by matching the apparent positions on the image with the actual city light locations. We applied this calibration method to photographs taken on August 26, 2014, and confirmed that the result is correct. The precision of the calibration was evaluated by comparing the results from six different photographs with the same imaging parameters. The precisions in determining the camera position and orientation are estimated to be ±2.2 km and ±0.08°, respectively. The 0.08° difference in the orientation yields a 2.9-km difference at a tangential point of 90 km in altitude. The airglow structures in the photographs were mapped to geographical points using the calibrated imaging parameters and compared with a simultaneous observation by the Visible and near-Infrared Spectral Imager of the Ionosphere, Mesosphere, Upper Atmosphere, and Plasmasphere mapping mission installed on the ISS. The comparison shows good agreements and supports the validity of the calibration. This calibration technique makes it possible to utilize photographs taken on low-Earth-orbit satellites in the nighttime as a reference for the airglow and aurora structures.[Figure not available: see fulltext.

Calibration of a texture-based model of a ground-water flow system, western San Joaquin Valley, California

USGS Publications Warehouse

Phillips, Steven P.; Belitz, Kenneth

1991-01-01

The occurrence of selenium in agricultural drain water from the western San Joaquin Valley, California, has focused concern on the semiconfined ground-water flow system, which is underlain by the Corcoran Clay Member of the Tulare Formation. A two-step procedure is used to calibrate a preliminary model of the system for the purpose of determining the steady-state hydraulic properties. Horizontal and vertical hydraulic conductivities are modeled as functions of the percentage of coarse sediment, hydraulic conductivities of coarse-textured (Kcoarse) and fine-textured (Kfine) end members, and averaging methods used to calculate equivalent hydraulic conductivities. The vertical conductivity of the Corcoran (Kcorc) is an additional parameter to be evaluated. In the first step of the calibration procedure, the model is run by systematically varying the following variables: (1) Kcoarse/Kfine, (2) Kcoarse/Kcorc, and (3) choice of averaging methods in the horizontal and vertical directions. Root mean square error and bias values calculated from the model results are functions of these variables. These measures of error provide a means for evaluating model sensitivity and for selecting values of Kcoarse, Kfine, and Kcorc for use in the second step of the calibration procedure. In the second step, recharge rates are evaluated as functions of Kcoarse, Kcorc, and a combination of averaging methods. The associated Kfine values are selected so that the root mean square error is minimized on the basis of the results from the first step. The results of the two-step procedure indicate that the spatial distribution of hydraulic conductivity that best produces the measured hydraulic head distribution is created through the use of arithmetic averaging in the horizontal direction and either geometric or harmonic averaging in the vertical direction. The equivalent hydraulic conductivities resulting from either combination of averaging methods compare favorably to field- and laboratory-based values.

Parameterisation of rainfall-runoff models for forecasting low and average flows, I: Conceptual modelling

NASA Astrophysics Data System (ADS)

Castiglioni, S.; Toth, E.

2009-04-01

In the calibration procedure of continuously-simulating models, the hydrologist has to choose which part of the observed hydrograph is most important to fit, either implicitly, through the visual agreement in manual calibration, or explicitly, through the choice of the objective function(s). Changing the objective functions it is in fact possible to emphasise different kind of errors, giving them more weight in the calibration phase. The objective functions used for calibrating hydrological models are generally of the quadratic type (mean squared error, correlation coefficient, coefficient of determination, etc) and are therefore oversensitive to high and extreme error values, that typically correspond to high and extreme streamflow values. This is appropriate when, like in the majority of streamflow forecasting applications, the focus is on the ability to reproduce potentially dangerous flood events; on the contrary, if the aim of the modelling is the reproduction of low and average flows, as it is the case in water resource management problems, this may result in a deterioration of the forecasting performance. This contribution presents the results of a series of automatic calibration experiments of a continuously-simulating rainfall-runoff model applied over several real-world case-studies, where the objective function is chosen so to highlight the fit of average and low flows. In this work a simple conceptual model will be used, of the lumped type, with a relatively low number of parameters to be calibrated. The experiments will be carried out for a set of case-study watersheds in Central Italy, covering an extremely wide range of geo-morphologic conditions and for whom at least five years of contemporary daily series of streamflow, precipitation and evapotranspiration estimates are available. Different objective functions will be tested in calibration and the results will be compared, over validation data, against those obtained with traditional squared functions. A companion work presents the results, over the same case-study watersheds and observation periods, of a system-theoretic model, again calibrated for reproducing average and low streamflows.

Calibration method for spectroscopic systems

DOEpatents

Sandison, David R.

1998-01-01

Calibration spots of optically-characterized material placed in the field of view of a spectroscopic system allow calibration of the spectroscopic system. Response from the calibration spots is measured and used to calibrate for varying spectroscopic system operating parameters. The accurate calibration achieved allows quantitative spectroscopic analysis of responses taken at different times, different excitation conditions, and of different targets.