scholarly journals An Improved Calibration and Uncertainty Analysis Approach Using a Multicriteria Sequential Algorithm for Hydrological Modeling

2021 ◽  
Author(s):  
Hongjing Wu ◽  
Bing Chen ◽  
Xudong Ye ◽  
Huaicheng Guo ◽  
Xianyong Meng ◽  
...  
Keyword(s):  
Uncertainty Analysis ◽  
Water Resource Management ◽  
Hydrological Modeling ◽  
High Reliability ◽  
Sequential Algorithm ◽  
Posterior Density ◽  
Traditional Methods ◽  
And Performance ◽  
Generalized Likelihood Uncertainty Estimation ◽  
Highest Posterior Density

Abstract Hydrological models are widely used as simplified, conceptual, mathematical representatives for water resource management. The performance of hydrological modeling is usually challenged by model calibration and uncertainty analysis during modeling exercises. In this study, a multicriteria sequential calibration and uncertainty analysis (MS-CUA) method was proposed to improve hydrological modeling efficiency and performance with high reliability. To evaluate the performance, the proposed MS-CUA method was applied to two case studies comparing two traditional methods: sequential uncertainty fitting algorithm (SUFI-2) and generalized likelihood uncertainty estimation (GLUE). The results indicated that the MS-CUA method can quickly locate the highest posterior density (HPD) regions of parameters to improve computational efficiency. It also provided better-calibrated results and more balanced uncertainty analysis results comparing with other traditional methods.

scholarly journals An improved calibration and uncertainty analysis approach using a multicriteria sequential algorithm for hydrological modeling

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hongjing Wu ◽  
Bing Chen ◽  
Xudong Ye ◽  
Huaicheng Guo ◽  
Xianyong Meng ◽  
...  
Keyword(s):  
Uncertainty Analysis ◽  
Case Studies ◽  
Water Resource Management ◽  
Hydrological Modeling ◽  
High Reliability ◽  
Sequential Algorithm ◽  
Posterior Density ◽  
R Ratio ◽  
Generalized Likelihood Uncertainty Estimation ◽  
Highest Posterior Density

AbstractHydrological models are widely used as simplified, conceptual, mathematical representatives for water resource management. The performance of hydrological modeling is usually challenged by model calibration and uncertainty analysis during modeling exercises. In this study, a multicriteria sequential calibration and uncertainty analysis (MS-CUA) method was proposed to improve the efficiency and performance of hydrological modeling with high reliability. To evaluate the performance and feasibility of the proposed method, two case studies were conducted in comparison with two other methods, sequential uncertainty fitting algorithm (SUFI-2) and generalized likelihood uncertainty estimation (GLUE). The results indicated that the MS-CUA method could quickly locate the highest posterior density regions to improve computational efficiency. The developed method also provided better-calibrated results (e.g., the higher NSE value of 0.91, 0.97, and 0.74) and more balanced uncertainty analysis results (e.g., the largest P/R ratio values of 1.23, 2.15, and 1.00) comparing with other traditional methods for both case studies.

scholarly journals Parameter uncertainty analysis for an operational hydrological model using residual-based and limits of acceptability approaches

2018 ◽  
Vol 22 (9) ◽  
pp. 5021-5039 ◽  
Author(s):  
Aynom T. Teweldebrhan ◽  
John F. Burkhart ◽  
Thomas V. Schuler
Keyword(s):  
Uncertainty Analysis ◽  
Parameter Uncertainty ◽  
Hydrological Modeling ◽  
Hydrological Model ◽  
Behavioral Model ◽  
Uncertainty Estimation ◽  
Model Parameters ◽  
Observation Error ◽  
Generalized Likelihood Uncertainty Estimation ◽  
Parameter Uncertainty Analysis

Abstract. Parameter uncertainty estimation is one of the major challenges in hydrological modeling. Here we present parameter uncertainty analysis of a recently released distributed conceptual hydrological model applied in the Nea catchment, Norway. Two variants of the generalized likelihood uncertainty estimation (GLUE) methodologies, one based on the residuals and the other on the limits of acceptability, were employed. Streamflow and remote sensing snow cover data were used in conditioning model parameters and in model validation. When using the GLUE limit of acceptability (GLUE LOA) approach, a streamflow observation error of 25 % was assumed. Neither the original limits nor relaxing the limits up to a physically meaningful value yielded a behavioral model capable of predicting streamflow within the limits in 100 % of the observations. As an alternative to relaxing the limits, the requirement for the percentage of model predictions falling within the original limits was relaxed. An empirical approach was introduced to define the degree of relaxation. The result shows that snow- and water-balance-related parameters induce relatively higher streamflow uncertainty than catchment response parameters. Comparable results were obtained from behavioral models selected using the two GLUE methodologies.

scholarly journals Parameter Determination and Ion Current Improvement of the Ion Current Sensor Used for Flame Monitoring

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 697
Author(s):  
Hanqing Xu ◽  
Weijun Fan ◽  
Jianwei Feng ◽  
Peiliang Yan ◽  
Shuchan Qi ◽  
...  
Keyword(s):  
Contact Area ◽  
High Reliability ◽  
Ion Current ◽  
Parameter Determination ◽  
Current Sensor ◽  
Vertical Position ◽  
Excitation Voltage ◽  
Burner Exit ◽  
And Performance ◽  
Flame Monitoring

Flame monitoring of industrial combustors with high-reliability sensors is essential to operation security and performance. An ion current flame sensor with a simple structure has great potential to be widely used, but a weak ion current is the critical defect to its reliability. In this study, parameters of the ion current sensor used for monitoring flames on a Bunsen burner are suggested, and a method of further improving the ion current is proposed. Effects of the parameters, including the excitation voltage, electrode area, and electrode radial and vertical positions on the ion current, were investigated. The ion current grew linearly with the excitation voltage. Given that the electrodes were in contact with the flame fronts, the ion current increased with the contact area of the cathode but independent of the contact area of the anode. The smaller electrode radial position resulted in a higher ion current. The ion current was insensitive to the anode vertical position but largely sensitive to the cathode vertical position. Based on the above ion current regularities, the sensor parameters were suggested as follows: The burner served as a cathode and the platinum wire acted as an anode. The excitation voltage, anode radial and vertical positions were 120 V, 0 mm, and 6 mm, respectively. The method of further improving the ion current by adding multiple sheet cathodes near the burner exit was proposed and verified. The results show that the ion current sensor with the suggested parameters could correctly identify the flame state, including the ignition, combustion, and extinction, and the proposed method could significantly improve the magnitude of the ion current.

scholarly journals Spatial evapotranspiration, rainfall and land use data in water accounting – Part 1: Review of the accuracy of the remote sensing data

2015 ◽  
Vol 19 (1) ◽  
pp. 507-532 ◽  
Author(s):  
P. Karimi ◽  
W. G. M. Bastiaanssen
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Water Resource Management ◽  
Hydrological Modeling ◽  
Remote Sensing Data ◽  
Actual Evapotranspiration ◽  
Primary Concern ◽  
Suitable Alternative ◽  
Sensing Data ◽  
Water Accounting

Abstract. The scarcity of water encourages scientists to develop new analytical tools to enhance water resource management. Water accounting and distributed hydrological models are examples of such tools. Water accounting needs accurate input data for adequate descriptions of water distribution and water depletion in river basins. Ground-based observatories are decreasing, and not generally accessible. Remote sensing data is a suitable alternative to measure the required input variables. This paper reviews the reliability of remote sensing algorithms to accurately determine the spatial distribution of actual evapotranspiration, rainfall and land use. For our validation we used only those papers that covered study periods of seasonal to annual cycles because the accumulated water balance is the primary concern. Review papers covering shorter periods only (days, weeks) were not included in our review. Our review shows that by using remote sensing, the absolute values of evapotranspiration can be estimated with an overall accuracy of 95% (SD 5%) and rainfall with an overall absolute accuracy of 82% (SD 15%). Land use can be identified with an overall accuracy of 85% (SD 7%). Hence, more scientific work is needed to improve the spatial mapping of rainfall and land use using multiple space-borne sensors. While not always perfect at all spatial and temporal scales, seasonally accumulated actual evapotranspiration maps can be used with confidence in water accounting and hydrological modeling.

scholarly journals Self-efficacy and performance of the roundhouse kick in taekwondo

2014 ◽  
Vol 9 (2) ◽  
pp. 97 ◽  
Author(s):  
Isaac Estevan ◽  
Octavio Álvarez ◽  
Coral Falcó ◽  
Isabel Castillo
Keyword(s):  
Self Efficacy ◽  
Impact Force ◽  
High Reliability ◽  
Sport Performance ◽  
Total Response Time ◽  
Psychological Training ◽  
Males And Females ◽  
And Performance ◽  
Performance Results ◽  
The Relationship

Development of self-efficacy scales allows the analysis of athletes’ perceptions and examination of the relationship between perception and performance. The aim of this paper was to: (1) develop a specific self-efficacy scale in a taekwondo task, the roundhouse kick, and (2) analyse the sport performance and its relationship with two self-efficacy scales (specific and general) outcomes according to the athletes’ gender.<strong> </strong>Forty-three taekwondo athletes (33 male and 10 female) participated in this study. The Physical (PSE) and Specific (RKSES) self-efficacy scales were administered. Performance data (impact force and total response time) were acquired by athletes kicking twice to an instrumented target. Results showed that the specific self-efficacy scale has high reliability and is able to predict sport performance in males and females. Males had higher self-efficacy scores and also higher performance results than females. Females’ taekwondo psychological training should be focus on improving their self-efficacy perception in order to increase their performance in the roundhouse kick. This specific self-efficacy scale for the taekwondo roundhouse kick offers empirical information to coaches, sport psychologists and researchers that allow them to predict athletes’ sport performance in the roundhouse kick.

scholarly journals Efeito materno e paterno sobre as taxas de fertilização e eclosão em curimba (Prochilodus lineatus)

2012 ◽  
Vol 64 (6) ◽  
pp. 1584-1590 ◽  
Author(s):  
I.B. Allaman ◽  
R.T.F. Freitas ◽  
A.T.M. Viveiros ◽  
A.F. Nascimento ◽  
G.R. Oliveira ◽  
...  
Keyword(s):  
Posterior Density ◽  
Prochilodus Lineatus ◽  
Highest Posterior Density

Avaliou-se o quanto fêmeas e machos contribuem para a variação total das taxas de fertilização e de eclosão em curimba (Prochilodus lineatus). Utilizou-se sêmen criopreservado proveniente de cinco machos para fertilizar ovócitos de seis fêmeas em um esquema fatorial cruzado 5x6, totalizando 30 famílias. Além das características reprodutivas dos machos e fêmeas, foram avaliadas as taxas de fertilização e eclosão para cômputo dos efeitos materno e paterno. Os componentes da variância foram estimados por meio da máxima verossimilhança restrita, sendo construídos intervalos Highest Posterior Density (HPD) para cada componente. Verificou-se que as fêmeas contribuíram muito mais para a variação total em relação aos machos para as taxas de fertilização e eclosão. Para a taxa de fertilização, as fêmeas contribuíram com 26,3% da variação total e os machos com 8,9%. Em relação à taxa de eclosão, as fêmeas contribuíram com 11,9% e os machos com 1,6%. Concluiu-se que houve efeito materno sobre as taxas de fertilização e eclosão e que o efeito paterno avaliado individualmente foi pouco expressivo ou até mesmo insignificante.

scholarly journals Modeling of Stage-Discharge Using Back Propagation ANN, ANFIS, and WANN-based Computing Technique

2021 ◽  
Author(s):  
Ravi Shukla ◽  
Pravendra Kumar ◽  
Dinesh Kumar Vishwakarma ◽  
Rawshan Ali ◽  
Rohitashw Kumar ◽  
...  
Keyword(s):  
Water Resource Management ◽  
Hydrological Modeling ◽  
Fuzzy Inference ◽  
Back Propagation ◽  
Activation Function ◽  
Neural System ◽  
Back Propagation Algorithm ◽  
Inference System ◽  
Computing Technique ◽  
Artificial Neural

Abstract The development of the stage-discharge relationship is a fundamental issue in hydrological modeling. Due to the complexity of the stage-discharge relationship, discharge prediction plays an essential role in planning and water resource management. The present study was conducted for modeling of discharge at the Gaula barrage site in Uttarakhand state of India. The study evaluated, Adaptive Neuro-Fuzzy Inference System (ANFIS), Artificial Neural Network (ANN) and Wavelet-Based Artificial Neural System (WANN) based models to estimate the discharge. The daily data of 12 years (2007-2018) were used to train and test the models. The Gamma test was used to identify the best model for discharge prediction. The input data having a stage with one-day lag and discharge with one and two-days lag and current-day discharge as output was used for discharge modeling. In the case of ANN models, the back-propagation algorithm and hyperbolic tangent sigmoid activation function was used. WANN used Haar, a trous based wavelet function. In ANFIS models, triangular, psig, generalized bell, and Gaussian membership functions were used to train and test the models. The models were evaluated qualitatively and quantitatively using correlation coefficient, root means square error, Willmott index, and coefficient of efficiency. It was found that ANFIS model performed better than ANN and WANN-based models for discharge prediction at the Gaula barrage.

scholarly journals Performance Prediction Equation for 2000 m Youth Indoor Rowing Using a 100 m Maximal Test

Biology ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1082
Author(s):  
Luiz Felipe da Silva ◽  
Paulo Francisco de Almeida-Neto ◽  
Dihogo Gama de Matos ◽  
Steven E. Riechman ◽  
Victor de Queiros ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Reliability Index ◽  
High Reliability ◽  
Low Cost ◽  
Time Trial ◽  
Prediction Equation ◽  
Daily Routine ◽  
Negative Consequences ◽  
Maximum Effort ◽  
And Performance

Background: The exhaustive series of tests undergone by young athletes of Olympic rowing prior to important competitions imply loads of physical stress that can ultimately impact on mood and motivation, with negative consequences for their training and performance. Thus, it is necessary to develop a tool that uses only the performance of short distances but is highly predictive, offering a time expectancy with high reliability. Such a test must use variables that are easy to collect with high practical applicability in the daily routine of coaches. Objective: The objective of the present study was to develop a mathematical model capable of predicting 2000 m rowing performance from a maximum effort 100 m indoor rowing ergometer (IRE) test in young rowers. Methods: The sample consisted of 12 male rowing athletes in the junior category (15.9 ± 1.0 years). A 100 m time trial was performed on the IRE, followed by a 2000 m time trial 24-h later. Results: The 2000 m mathematical model to predict performance in minutes based on the maximum 100 m test demonstrated a high correlation (r = 0.734; p = 0.006), strong reliability index (ICC: 0.978; IC95%: [0.960; 0.980]; p = 0.001) and was within usable agreement limits (Bland -Altman Agreement: −0.60 to 0.60; 95% CI [−0.65; 0.67]). Conclusion: The mathematical model developed to predict 2000 m performance is effective and has a statistically significant reliability index while being easy to implement with low cost.

scholarly journals Computation of posterior distribution in Bayesian analysis – application in an intermittently used reliability system

2002 ◽  
Vol 21 (3) ◽  
pp. 78-82
Author(s):  
V. S.S. Yadavalli ◽  
P. J. Mostert ◽  
A. Bekker ◽  
M. Botha
Keyword(s):  
Posterior Distribution ◽  
Jeffreys Prior ◽  
Posterior Density ◽  
Unknown Parameters ◽  
Stationary Rate ◽  
Analysis Application ◽  
Definition Of ◽  
Hpd Intervals ◽  
Highest Posterior Density ◽  
Bayes Procedure

Bayesian estimation is presented for the stationary rate of disappointments, D∞, for two models (with different specifications) of intermittently used systems. The random variables in the system are considered to be independently exponentially distributed. Jeffreys’ prior is assumed for the unknown parameters in the system. Inference about D∞ is being restrained in both models by the complex and non-linear definition of D∞. Monte Carlo simulation is used to derive the posterior distribution of D∞ and subsequently the highest posterior density (HPD) intervals. A numerical example where Bayes estimates and the HPD intervals are determined illustrates these results. This illustration is extended to determine the frequentistical properties of this Bayes procedure, by calculating covering proportions for each of these HPD intervals, assuming fixed values for the parameters.

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