scholarly journals Modeling erythemal ultraviolet diffuse fraction

2017 ◽  
Author(s):  
Guadalupe Sanchez Hernandez ◽  
Antonio Serrano ◽  
Maria Luisa Cancillo
Keyword(s):  
Empirical Models ◽  
Experimental Measurements ◽  
Strong Impact ◽  
Diffuse Fraction ◽  
Additional Information ◽  
Mathematical Expressions ◽  
Physically Based ◽  
Physically Based Models ◽  
Ultraviolet Irradiance ◽  
Semi Empirical

Abstract. Although being extremely interesting, the diffuse component of the erythemal ultraviolet irradiance (UVER) is scarcely measured at standard radiometric stations and, therefore, needs to be estimated. This study proposes and compares ten empirical models to estimate the UVER diffuse fraction. These models are inspired on mathematical expressions originally used to estimate total diffuse fraction, but, in this study, they are applied to the UVER case and tested against experimental measurements. In addition to adapting to the UVER range the various independent variables involved in these models, the total ozone column has been added in order to account for its strong impact on the attenuation of ultraviolet radiation. The proposed models are fitted to experimental measurements and validated against an independent subset. Six models perform notably well, with the best performing model RAU3 showing values of r2 equal to 0.91 and rRMSE equal to 6.1 %. The performance achieved by this model is better than those obtained by previous semi-empirical approaches, with the advantage of being entirely empirical and, therefore, needing no additional information from physically-based models. This study expands previous research to the ultraviolet range, and provides reliable empirical models to accurately estimate the UVER diffuse fraction.

scholarly journals Modeling the erythemal surface diffuse irradiance fraction for Badajoz, Spain

2017 ◽  
Vol 17 (20) ◽  
pp. 12697-12708 ◽  
Author(s):  
Guadalupe Sanchez ◽  
Antonio Serrano ◽  
María Luisa Cancillo
Keyword(s):  
Empirical Models ◽  
Experimental Measurements ◽  
Strong Impact ◽  
Diffuse Fraction ◽  
Additional Information ◽  
Mathematical Expressions ◽  
Physically Based ◽  
Physically Based Models ◽  
Ultraviolet Irradiance ◽  
Semi Empirical

Abstract. Despite its important role on the human health and numerous biological processes, the diffuse component of the erythemal ultraviolet irradiance (UVER) is scarcely measured at standard radiometric stations and therefore needs to be estimated. This study proposes and compares 10 empirical models to estimate the UVER diffuse fraction. These models are inspired from mathematical expressions originally used to estimate total diffuse fraction, but, in this study, they are applied to the UVER case and tested against experimental measurements. In addition to adapting to the UVER range the various independent variables involved in these models, the total ozone column has been added in order to account for its strong impact on the attenuation of ultraviolet radiation. The proposed models are fitted to experimental measurements and validated against an independent subset. The best-performing model (RAU3) is based on a model proposed by Ruiz-Arias et al. (2010) and shows values of r2 equal to 0.91 and relative root-mean-square error (rRMSE) equal to 6.1 %. The performance achieved by this entirely empirical model is better than those obtained by previous semi-empirical approaches and therefore needs no additional information from other physically based models. This study expands on previous research to the ultraviolet range and provides reliable empirical models to accurately estimate the UVER diffuse fraction.

Estimation of parameters for the Philip two-term infiltration equation applied to field soil experiments

Soil Research ◽  
1987 ◽  
Vol 25 (4) ◽  
pp. 369 ◽  
Author(s):  
KL Bristow ◽  
MJ Savage
Keyword(s):  
Empirical Models ◽  
The Other ◽  
Original Form ◽  
Field Soil ◽  
Estimation Of Parameters ◽  
Mathematical Transformation ◽  
System Parameters ◽  
Physically Based ◽  
Physically Based Models ◽  
The One

Two methods based on least squares analysis used to estimate coefficients in the Philip two-term infiltration equation are compared. The one method maintains the infiltration equation in its original form, while the other involves a mathematical transformation which introduces self-correlation and yields different estimates of the coefficients. Data from field infiltration experiments are used to illustrate these differences, and the need to distinguish between fitting data to empirical models and deriving system parameters from analysis of physically based models is emphasized.

scholarly journals Impact of modellers' decisions on hydrological a priori predictions

2014 ◽  
Vol 18 (6) ◽  
pp. 2065-2085 ◽  
Author(s):  
H. M. Holländer ◽  
H. Bormann ◽  
T. Blume ◽  
W. Buytaert ◽  
G. B. Chirico ◽  
...  
Keyword(s):  
Initial Conditions ◽  
A Priori ◽  
Ungauged Catchments ◽  
Data Set ◽  
Additional Information ◽  
Hard Information ◽  
Process Understanding ◽  
Groundwater Response ◽  
Physically Based ◽  
Physically Based Models

Abstract. In practice, the catchment hydrologist is often confronted with the task of predicting discharge without having the needed records for calibration. Here, we report the discharge predictions of 10 modellers – using the model of their choice – for the man-made Chicken Creek catchment (6 ha, northeast Germany, Gerwin et al., 2009b) and we analyse how well they improved their prediction in three steps based on adding information prior to each following step. The modellers predicted the catchment's hydrological response in its initial phase without having access to the observed records. They used conceptually different physically based models and their modelling experience differed largely. Hence, they encountered two problems: (i) to simulate discharge for an ungauged catchment and (ii) using models that were developed for catchments, which are not in a state of landscape transformation. The prediction exercise was organized in three steps: (1) for the first prediction the modellers received a basic data set describing the catchment to a degree somewhat more complete than usually available for a priori predictions of ungauged catchments; they did not obtain information on stream flow, soil moisture, nor groundwater response and had therefore to guess the initial conditions; (2) before the second prediction they inspected the catchment on-site and discussed their first prediction attempt; (3) for their third prediction they were offered additional data by charging them pro forma with the costs for obtaining this additional information. Holländer et al. (2009) discussed the range of predictions obtained in step (1). Here, we detail the modeller's assumptions and decisions in accounting for the various processes. We document the prediction progress as well as the learning process resulting from the availability of added information. For the second and third steps, the progress in prediction quality is evaluated in relation to individual modelling experience and costs of added information. In this qualitative analysis of a statistically small number of predictions we learned (i) that soft information such as the modeller's system understanding is as important as the model itself (hard information), (ii) that the sequence of modelling steps matters (field visit, interactions between differently experienced experts, choice of model, selection of available data, and methods for parameter guessing), and (iii) that added process understanding can be as efficient as adding data for improving parameters needed to satisfy model requirements.

scholarly journals On the residual strength of aging cast iron trunk mains: Physically-based models for asset failure

2016 ◽  
Vol 663 ◽  
pp. 204-212 ◽  
Author(s):  
Azadeh Fahimi ◽  
Timothy S. Evans ◽  
Jeff Farrow ◽  
David A. Jesson ◽  
Mike J. Mulheron ◽  
...  
Keyword(s):  
Cast Iron ◽  
Residual Strength ◽  
Physically Based ◽  
Physically Based Models

scholarly journals Performance of the dynamically dimensioned search algorithm: influence of parameter initialization strategy when calibrating a physically based hydrological model

2017 ◽  
Vol 49 (4) ◽  
pp. 971-988 ◽  
Author(s):  
Franck Lespinas ◽  
Ashu Dastoor ◽  
Vincent Fortin
Keyword(s):  
Search Algorithm ◽  
Low Cost ◽  
Initial Parameter ◽  
Cost Strategy ◽  
Physically Based ◽  
Physically Based Models ◽  
Calibration Solution ◽  
Low Cost Strategy ◽  
Parameter Values ◽  
Initialization Strategy

Abstract This study presents an evaluation of the performance of the dynamically dimensioned search (DDS) algorithm when calibrating the hydrological component of the Visualizing Ecosystems for Land Management Assessments (VELMA) ecohydrological model. Two calibration strategies were tested for the initial parameter values: (1) a ‘high-cost strategy’, where 100 sets of initial parameter values were randomly chosen within the overall parameter space, and (2) a ‘low-cost strategy’, where a unique set of initial parameter values was derived from the available field data. Both strategies were tested for six different values of the maximum number of model evaluations ranging between 100 and 10,000. Results revealed that DDS is able to converge rapidly to a good parameter calibration solution of the VELMA hydrological component regardless of the parameter initialization strategy used. The accuracy and convergence efficiency of the DDS algorithm were, however, slightly better for the low-cost strategy. This study suggests that initializing the parameter values of complex physically based models using information on the watershed characteristics can increase the efficiency of the automatic calibration procedures.

scholarly journals Evaluating performances of simplified physically based models for landslide susceptibility

2015 ◽  
Vol 12 (12) ◽  
pp. 13217-13256 ◽  
Author(s):  
G. Formetta ◽  
G. Capparelli ◽  
P. Versace
Keyword(s):  
Landslide Susceptibility ◽  
Goodness Of Fit ◽  
Shallow Landslides ◽  
Model Parameters ◽  
Test Case ◽  
Susceptibility Analysis ◽  
Physically Based ◽  
Private And Public ◽  
Physically Based Models

Abstract. Rainfall induced shallow landslides cause loss of life and significant damages involving private and public properties, transportation system, etc. Prediction of shallow landslides susceptible locations is a complex task that involves many disciplines: hydrology, geotechnical science, geomorphology, and statistics. Usually to accomplish this task two main approaches are used: statistical or physically based model. Reliable models' applications involve: automatic parameters calibration, objective quantification of the quality of susceptibility maps, model sensitivity analysis. This paper presents a methodology to systemically and objectively calibrate, verify and compare different models and different models performances indicators in order to individuate and eventually select the models whose behaviors are more reliable for a certain case study. The procedure was implemented in package of models for landslide susceptibility analysis and integrated in the NewAge-JGrass hydrological model. The package includes three simplified physically based models for landslides susceptibility analysis (M1, M2, and M3) and a component for models verifications. It computes eight goodness of fit indices by comparing pixel-by-pixel model results and measurements data. Moreover, the package integration in NewAge-JGrass allows the use of other components such as geographic information system tools to manage inputs-output processes, and automatic calibration algorithms to estimate model parameters. The system was applied for a case study in Calabria (Italy) along the Salerno-Reggio Calabria highway, between Cosenza and Altilia municipality. The analysis provided that among all the optimized indices and all the three models, the optimization of the index distance to perfect classification in the receiver operating characteristic plane (D2PC) coupled with model M3 is the best modeling solution for our test case.

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