scholarly journals Comparison of different efficiency criteria for hydrological model assessment

2005 ◽  
Vol 5 ◽  
pp. 89-97 ◽  
Author(s):  
P. Krause ◽  
D. P. Boyle ◽  
F. Bäse
Keyword(s):  
Hydrological Model ◽  
Objective Assessment ◽  
Hydrologic Model ◽  
Coefficient Of Determination ◽  
Evaluation Procedure ◽  
Efficiency Coefficient ◽  
Model Assessment ◽  
Different Types ◽  
Index Of Agreement ◽  
And Performance

Abstract. The evaluation of hydrologic model behaviour and performance is commonly made and reported through comparisons of simulated and observed variables. Frequently, comparisons are made between simulated and measured streamflow at the catchment outlet. In distributed hydrological modelling approaches, additional comparisons of simulated and observed measurements for multi-response validation may be integrated into the evaluation procedure to assess overall modelling performance. In both approaches, single and multi-response, efficiency criteria are commonly used by hydrologists to provide an objective assessment of the "closeness" of the simulated behaviour to the observed measurements. While there are a few efficiency criteria such as the Nash-Sutcliffe efficiency, coefficient of determination, and index of agreement that are frequently used in hydrologic modeling studies and reported in the literature, there are a large number of other efficiency criteria to choose from. The selection and use of specific efficiency criteria and the interpretation of the results can be a challenge for even the most experienced hydrologist since each criterion may place different emphasis on different types of simulated and observed behaviours. In this paper, the utility of several efficiency criteria is investigated in three examples using a simple observed streamflow hydrograph.

scholarly journals Balancing uncertainty and complexity to incorporate fire spread in an eco-hydrological model

2017 ◽  
Vol 26 (8) ◽  
pp. 706 ◽  
Author(s):  
Maureen C. Kennedy ◽  
Donald McKenzie ◽  
Christina Tague ◽  
Aubrey L. Dugger
Keyword(s):  
Hydrological Model ◽  
Fire Regimes ◽  
Fire Spread ◽  
Fire Effects ◽  
Hydrologic Model ◽  
Simulation System ◽  
Model Assessment ◽  
Topographic Slope ◽  
Spread Model ◽  
Fire Spread Model

Wildfire affects the ecosystem services of watersheds, and climate change will modify fire regimes and watershed dynamics. In many eco-hydrological simulations, fire is included as an exogenous force. Rarely are the bidirectional feedbacks between watersheds and fire regimes integrated in a simulation system because the eco-hydrological model predicts variables that are incompatible with the requirements of fire models. WMFire is a fire-spread model of intermediate complexity designed to be integrated with the Regional Hydro-ecological Simulation System (RHESSys). Spread in WMFire is based on four variables that (i) represent known influences on fire spread: litter load, relative moisture deficit, wind direction and topographic slope, and (ii) are derived directly from RHESSys outputs. The probability that a fire spreads from pixel to pixel depends on these variables as predicted by RHESSys. We tested a partial integration between WMFire and RHESSys on the Santa Fe (New Mexico) and the HJ Andrews (Oregon State) watersheds. Model assessment showed correspondence between expected spatial patterns of spread and seasonality in both watersheds. These results demonstrate the efficacy of an approach to link eco-hydrologic model outputs with a fire spread model. Future work will develop a fire effects module in RHESSys for a fully coupled, bidirectional model.

scholarly journals Comparison of statistical indices for the evaluation of crop models performance

2021 ◽  
Vol 74 (3) ◽  
pp. 9675-9684
Author(s):  
Tatiana María Saldaña Villota ◽  
José Miguel Cotes Torres
Keyword(s):  
Mean Squared Error ◽  
Potato Crop ◽  
Coefficient Of Determination ◽  
Model Assessment ◽  
Data Set ◽  
Root Mean Squared Error ◽  
Squared Error ◽  
Statistical Indices ◽  
Index Of Agreement ◽  
Relative Root

This study presents a comparison of the usual statistical methods used for crop model assessment. A case study was conducted using a data set from observations of the total dry weight in diploid potato crop, and six simulated data sets derived from the observationsaimed to predict the measured data. Statistical indices such as the coefficient of determination, the root mean squared error, the relative root mean squared error, mean error, index of agreement, modified index of agreement, revised index of agreement, modeling efficiency, and revised modeling efficiency were compared. The results showed that the coefficient of determination is not a useful statistical index for model evaluation. The root mean squared error together with the relative root mean squared error offer an excellent notion of how deviated the simulations are in the same unit of the variable and percentage terms, and they leave no doubt when evaluating the quality of the simulations of a model.

Characteristics of Physicians Referred for a Competence Assessment: A Comparison of State Medical Board and Hospital Referred Physicians

2010 ◽  
Vol 96 (3) ◽  
pp. 8-15 ◽  
Author(s):  
Elizabeth S. Grace ◽  
Elizabeth J. Korinek ◽  
Zung V. Tran
Keyword(s):  
Clinical Competence ◽  
Competence Assessment ◽  
Average Performance ◽  
Medical Board ◽  
Key Characteristics ◽  
Different Types ◽  
Specialty Board ◽  
And Performance ◽  
State Medical Boards ◽  
State Medical Board

ABSTRACT This study compares key characteristics and performance of physicians referred to a clinical competence assessment and education program by state medical boards (boards) and hospitals. Physicians referred by boards (400) and by hospitals (102) completed a CPEP clinical competence assessment between July 2002 and June 2010. Key characteristics, self-reported specialty, and average performance rating for each group are reported and compared. Results show that, compared with hospital-referred physicians, board-referred physicians were more likely to be male (75.5% versus 88.3%), older (average age 54.1 versus 50.3 years), and less likely to be currently specialty board certified (80.4% versus 61.8%). On a scale of 1 (best) to 4 (worst), average performance was 2.62 for board referrals and 2.36 for hospital referrals. There were no significant differences between board and hospital referrals in the percentage of physicians who graduated from U.S. and Canadian medical schools. The most common specialties referred differed for boards and hospitals. Conclusion: Characteristics of physicians referred to a clinical competence program by boards and hospitals differ in important respects. The authors consider the potential reasons for these differences and whether boards and hospitals are dealing with different subsets of physicians with different types of performance problems. Further study is warranted.

A Review of Different Types of DOE Methods as a Useful Platform for Improving the Performance of Nano Adsorbents in Removal Systems of Pollutants

2020 ◽  
Vol 10 (3) ◽  
pp. 219-227
Author(s):  
Ali Behmaneshfar ◽  
Abdolhossein Sadrnia ◽  
Hassan Karimi-Maleh
Keyword(s):  
Response Surface Methodology ◽  
Design Of Experiments ◽  
Web Of Science ◽  
Computer Software ◽  
Coefficient Of Determination ◽  
Design Expert ◽  
Number Of Factors ◽  
Different Types ◽  
Matlab Programming ◽  
Nano Adsorbent

Background: In recent years, the Design of Experiments (DOE) is used for removing pollutant from wastewater by nano-adsorbent. Some methods are Taguchi, Response Surface Methodology (RSM) and factorial design. The aim of this paper is to review different used methods of DOE in removing pollutant to suggest some notations to scholars. Methods: The reviewed papers were searched in Google Scholar, Scopus, and Web of Science randomly and categorized based on DOE methods. Results: Number of factors and responses in DOE for removing pollutants from wastewater are between 2-6 and 1-4, respectively. There are several computer software programs that provide simple use of these methods, such as Qualitek, Design Expert, Minitab, R and Matlab Programming. All models have a coefficient of determination R-sq more than 0.9. Conclusion: All the mentioned methods are appropriate because of the high R-sq value. Since the largest number of runs are used in RSM, it is not suitable for the experiments which are conducted by expensive materials and process. Furthermore, Design Expert and Minitab are the most popular software used by scholars in DOE methods for the removal of pollutant.

An Enhanced Two Stage MMSE Equalizer for Coded FBMC/OQAM Systems

2019 ◽  
Vol 10 (1) ◽  
pp. 69-82 ◽  
Author(s):  
Mohammad Rizk Assaf ◽  
Abdel-Nasser Assimi
Keyword(s):  
Error Propagation ◽  
Channel Model ◽  
Error Correcting Codes ◽  
Two Stage ◽  
Probability Of Error ◽  
Second Stage ◽  
Different Types ◽  
Mmse Equalizer ◽  
And Performance ◽  
Ici Cancellation

In this article, the authors investigate the enhanced two stage MMSE (TS-MMSE) equalizer in bit-interleaved coded FBMC/OQAM system which gives a tradeoff between complexity and performance, since error correcting codes limits error propagation, so this allows the equalizer to remove not only ICI but also ISI in the second stage. The proposed equalizer has shown less design complexity compared to the other MMSE equalizers. The obtained results show that the probability of error is improved where SNR gain reaches 2 dB measured at BER compared with ICI cancellation for different types of modulation schemes and ITU Vehicular B channel model. Some simulation results are provided to illustrate the effectiveness of the proposed equalizer.

scholarly journals Sensitivity and Performance Analyses of the Distributed Hydrology–Soil–Vegetation Model Using Geomorphons for Landform Mapping

Water ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 2032
Author(s):  
Pâmela A. Melo ◽  
Lívia A. Alvarenga ◽  
Javier Tomasella ◽  
Carlos R. Mello ◽  
Minella A. Martins ◽  
...  
Keyword(s):  
Complex Terrain ◽  
Overland Flow ◽  
Hydrological Model ◽  
Model Performance ◽  
Soil Parameters ◽  
Vegetation Model ◽  
Landform Classification ◽  
Physically Based ◽  
And Performance ◽  
Streamflow Simulation

Landform classification is important for representing soil physical properties varying continuously across the landscape and for understanding many hydrological processes in watersheds. Considering it, this study aims to use a geomorphology map (Geomorphons) as an input to a physically based hydrological model (Distributed Hydrology Soil Vegetation Model (DHSVM)) in a mountainous headwater watershed. A sensitivity analysis of five soil parameters was evaluated for streamflow simulation in each Geomorphons feature. As infiltration and saturation excess overland flow are important mechanisms for streamflow generation in complex terrain watersheds, the model’s input soil parameters were most sensitive in the “slope”, “hollow”, and “valley” features. Thus, the simulated streamflow was compared with observed data for calibration and validation. The model performance was satisfactory and equivalent to previous simulations in the same watershed using pedological survey and moisture zone maps. Therefore, the results from this study indicate that a geomorphologically based map is applicable and representative for spatially distributing hydrological parameters in the DHSVM.

scholarly journals Modeling of Lake Malombe Annual Fish Landings and Catch per Unit Effort (CPUE)

Forecasting ◽  
2021 ◽  
Vol 3 (1) ◽  
pp. 39-55
Author(s):  
Rodgers Makwinja ◽  
Seyoum Mengistou ◽  
Emmanuel Kaunda ◽  
Tena Alemiew ◽  
Titus Bandulo Phiri ◽  
...  
Keyword(s):  
Time Series ◽  
Information Criterion ◽  
Coefficient Of Determination ◽  
Series Data ◽  
Efficiency Coefficient ◽  
Arima Models ◽  
Catch Per Unit Effort ◽  
Annual Fish ◽  
Unit Effort ◽  
The Mean

Forecasting, using time series data, has become the most relevant and effective tool for fisheries stock assessment. Autoregressive integrated moving average (ARIMA) modeling has been commonly used to predict the general trend for fish landings with increased reliability and precision. In this paper, ARIMA models were applied to predict Lake Malombe annual fish landings and catch per unit effort (CPUE). The annual fish landings and CPUE trends were first observed and both were non-stationary. The first-order differencing was applied to transform the non-stationary data into stationary. Autocorrelation functions (AC), partial autocorrelation function (PAC), Akaike information criterion (AIC), Bayesian information criterion (BIC), square root of the mean square error (RMSE), the mean absolute error (MAE), percentage standard error of prediction (SEP), average relative variance (ARV), Gaussian maximum likelihood estimation (GMLE) algorithm, efficiency coefficient (E2), coefficient of determination (R2), and persistent index (PI) were estimated, which led to the identification and construction of ARIMA models, suitable in explaining the time series and forecasting. According to the measures of forecasting accuracy, the best forecasting models for fish landings and CPUE were ARIMA (0,1,1) and ARIMA (0,1,0). These models had the lowest values AIC, BIC, RMSE, MAE, SEP, ARV. The models further displayed the highest values of GMLE, PI, R2, and E2. The “auto. arima ()” command in R version 3.6.3 further displayed ARIMA (0,1,1) and ARIMA (0,1,0) as the best. The selected models satisfactorily forecasted the fish landings of 2725.243 metric tons and CPUE of 0.097 kg/h by 2024.

scholarly journals Rainfall-Runoff Modeling Using the HEC-HMS Model for the Al-Adhaim River Catchment, Northern Iraq

Hydrology ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 58
Author(s):  
Ahmed Naseh Ahmed Hamdan ◽  
Suhad Almuktar ◽  
Miklas Scholz
Keyword(s):  
Geographical Information Systems ◽  
Hydrological Model ◽  
Daily Rainfall ◽  
Curve Number ◽  
Geographical Information ◽  
Coefficient Of Determination ◽  
Rainfall Runoff ◽  
Time Step ◽  
River Catchment ◽  
Northern Iraq

It has become necessary to estimate the quantities of runoff by knowing the amount of rainfall to calculate the required quantities of water storage in reservoirs and to determine the likelihood of flooding. The present study deals with the development of a hydrological model named Hydrologic Engineering Center (HEC-HMS), which uses Digital Elevation Models (DEM). This hydrological model was used by means of the Geospatial Hydrologic Modeling Extension (HEC-GeoHMS) and Geographical Information Systems (GIS) to identify the discharge of the Al-Adhaim River catchment and embankment dam in Iraq by simulated rainfall-runoff processes. The meteorological models were developed within the HEC-HMS from the recorded daily rainfall data for the hydrological years 2015 to 2018. The control specifications were defined for the specified period and one day time step. The Soil Conservation Service-Curve number (SCS-CN), SCS Unit Hydrograph and Muskingum methods were used for loss, transformation and routing calculations, respectively. The model was simulated for two years for calibration and one year for verification of the daily rainfall values. The results showed that both observed and simulated hydrographs were highly correlated. The model’s performance was evaluated by using a coefficient of determination of 90% for calibration and verification. The dam’s discharge for the considered period was successfully simulated but slightly overestimated. The results indicated that the model is suitable for hydrological simulations in the Al-Adhaim river catchment.

scholarly journals How Do Parameters of Implant Primary Stability Correspond with CT-Evaluated Bone Quality in the Posterior Maxilla? A Correlation Analysis

Materials ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 270
Author(s):  
Ji-Hyun Kim ◽  
Young-Jun Lim ◽  
Bongju Kim ◽  
Jungwon Lee
Keyword(s):  
Bone Density ◽  
Bone Quality ◽  
Objective Assessment ◽  
Primary Stability ◽  
Insertion Torque ◽  
Hounsfield Units ◽  
Stability Parameters ◽  
Posterior Maxilla ◽  
Different Types ◽  
Edentulous Patients

The aim of the present study was to evaluate correlations between bone density and implant primary stability, considering various determinants such as age, gender, and geometry of implants (design, diameter). Bone density of edentulous posterior maxillae was assessed by computed tomography (CT)-derived Hounsfield units, and implant primary stability values were measured with insertion torque and resonance frequency analysis (RFA). A total of 60 implants in 30 partially edentulous patients were evaluated in the posterior maxilla with two different types of dental implants. The bone density evaluated by CT-derived Hounsfield units showed a significant correlation with primary stability parameters. The bone quality was more influenced by gender rather than age, and the type of implant was insignificant when determining primary stability. Such results imply that primary stability parameters can be used for objective assessment of bone quality, allowing surgical modifications especially in sites suspected of poor bone quality.

Sign in / Sign up

Export Citation Format

Share Document