scholarly journals Optimal Calibration of Evaporation Models against Penman–Monteith Equation

Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1484
Author(s):  
Dagmar Dlouhá ◽  
Viktor Dubovský ◽  
Lukáš Pospíšil
Keyword(s):  
Model Calibration ◽  
Heat Storage ◽  
Free Water ◽  
Complex Model ◽  
Model Parameters ◽  
Net Radiation ◽  
Statistical Measures ◽  
Pit Lakes ◽  
Evaporation Models ◽  
Monteith Equation

We present an approach for the calibration of simplified evaporation model parameters based on the optimization of parameters against the most complex model for evaporation estimation, i.e., the Penman–Monteith equation. This model computes the evaporation from several input quantities, such as air temperature, wind speed, heat storage, net radiation etc. However, sometimes all these values are not available, therefore we must use simplified models. Our interest in free water surface evaporation is given by the need for ongoing hydric reclamation of the former Ležáky–Most quarry, i.e., the ongoing restoration of the land that has been mined to a natural and economically usable state. For emerging pit lakes, the prediction of evaporation and the level of water plays a crucial role. We examine the methodology on several popular models and standard statistical measures. The presented approach can be applied in a general model calibration process subject to any theoretical or measured evaporation.

scholarly journals Calibration of a simple and a complex model of global marine biogeochemistry

2017 ◽  
Author(s):  
Iris Kriest
Keyword(s):  
Steady State ◽  
Model Calibration ◽  
Organic Phosphorus ◽  
Model Performance ◽  
Parametric Uncertainty ◽  
Complex Model ◽  
Component Model ◽  
Model Parameters ◽  
Model Assessment ◽  
High Level

Abstract. The assessment of the ocean biota's role in climate climate change is often carried out with global biogeochemical ocean models that contain many components, and involve a high level of parametric uncertainty. Examination the models' fit to climatologies of inorganic tracers, after the models have been spun up to steady state, is a common, but computationally expensive procedure to assess model performance and reliability. Using new tools that have become available for global model assessment and calibration in steady state, this paper examines two different model types – a complex seven-component model (MOPS), and a very simple two-component model (RetroMOPS) – for their fit to dissolved quantities. Before comparing the models, a subset of their biogeochemical parameters has been optimised against annual mean nutrients and oxygen. Both model types fit the observations almost equally well. The simple model, which contains only nutrients and dissolved organic phosphorus (DOP), is sensitive to the parameterisation of DOP production and decay. The spatio-temporal decoupling of nitrogen and oxygen, and processes involved in their uptake and release, renders oxygen and nitrate valuable tracers for model calibration. In addition, the non-conservative nature of these tracers (with respect to their upper boundary condition) introduces the global bias as a useful additional constraint on model parameters. Dissolved organic phosphorous at the surface behaves antagonistically to phosphate, and suggests that observations of this tracer – although difficult to measure – may be an important asset for model calibration.

scholarly journals The Calibration of Evaporation Models against the Penman–Monteith Equation on Lake Most

2020 ◽  
Vol 13 (1) ◽  
pp. 313
Author(s):  
Viktor Dubovský ◽  
Dagmar Dlouhá ◽  
Lukáš Pospíšil
Keyword(s):  
Water Cycle ◽  
State Of The Art ◽  
Free Water ◽  
Climate Data ◽  
Area Of Interest ◽  
Measurement Devices ◽  
Main Components ◽  
Evaporation Models ◽  
Monteith Equation

Evaporation is one of the main components of the water cycle in nature. Our interest in free water surface evaporation is due to the needs of ongoing hydric recultivation of the former Ležáky–Most quarry, i.e., Lake Most, and also other planned hydric recultivations in the region. One of the key components of hydric reclamation planning is the securitization of long-term sustainability, which is based on the capability to keep the final water level at a stable level. In our work, we are interested in the evaporation estimation in the area of Lake Most (Czech Republic, Europe). This lake has been artificially created only a few years ago, and nowadays we are looking for a simple evaporation model, based on which we will be able to decide which measurement devices have to be installed at the location to provide more localized data to the model. In this paper, we calibrate state-of-the-art simplified evaporation models against the Penman–Monteith equation based on the Nash–Sutcliffe efficiency maximization. We discuss the suitability of this approach using real-world climate data from the weather station located one km from the area of interest.

scholarly journals Calibration of a simple and a complex model of global marine biogeochemistry

2017 ◽  
Vol 14 (21) ◽  
pp. 4965-4984 ◽  
Author(s):  
Iris Kriest
Keyword(s):  
Steady State ◽  
Model Calibration ◽  
Large Scale ◽  
Organic Phosphorus ◽  
Model Performance ◽  
Complex Model ◽  
Component Model ◽  
Model Parameters ◽  
Model Assessment ◽  
Dissolved Organic Phosphorus

Abstract. The assessment of the ocean biota's role in climate change is often carried out with global biogeochemical ocean models that contain many components and involve a high level of parametric uncertainty. Because many data that relate to tracers included in a model are only sparsely observed, assessment of model skill is often restricted to tracers that can be easily measured and assembled. Examination of the models' fit to climatologies of inorganic tracers, after the models have been spun up to steady state, is a common but computationally expensive procedure to assess model performance and reliability. Using new tools that have become available for global model assessment and calibration in steady state, this paper examines two different model types – a complex seven-component model (MOPS) and a very simple four-component model (RetroMOPS) – for their fit to dissolved quantities. Before comparing the models, a subset of their biogeochemical parameters has been optimised against annual-mean nutrients and oxygen. Both model types fit the observations almost equally well. The simple model contains only two nutrients: oxygen and dissolved organic phosphorus (DOP). Its misfit and large-scale tracer distributions are sensitive to the parameterisation of DOP production and decay. The spatio-temporal decoupling of nitrogen and oxygen, and processes involved in their uptake and release, renders oxygen and nitrate valuable tracers for model calibration. In addition, the non-conservative nature of these tracers (with respect to their upper boundary condition) introduces the global bias (fixed nitrogen and oxygen inventory) as a useful additional constraint on model parameters. Dissolved organic phosphorus at the surface behaves antagonistically to phosphate, and suggests that observations of this tracer – although difficult to measure – may be an important asset for model calibration.

scholarly journals Incremental model breakdown to assess the multi-hypotheses problem

2018 ◽  
Vol 22 (8) ◽  
pp. 4565-4581 ◽  
Author(s):  
Florian U. Jehn ◽  
Lutz Breuer ◽  
Tobias Houska ◽  
Konrad Bestian ◽  
Philipp Kraft
Keyword(s):  
Hydrological Modeling ◽  
Model Performance ◽  
Complex Model ◽  
Model Parameters ◽  
Objective Functions ◽  
Final Model ◽  
Incremental Model ◽  
Model Efficiency ◽  
Improved Model ◽  
Model Structures

Abstract. The ambiguous representation of hydrological processes has led to the formulation of the multiple hypotheses approach in hydrological modeling, which requires new ways of model construction. However, most recent studies focus only on the comparison of predefined model structures or building a model step by step. This study tackles the problem the other way around: we start with one complex model structure, which includes all processes deemed to be important for the catchment. Next, we create 13 additional simplified models, where some of the processes from the starting structure are disabled. The performance of those models is evaluated using three objective functions (logarithmic Nash–Sutcliffe; percentage bias, PBIAS; and the ratio between the root mean square error and the standard deviation of the measured data). Through this incremental breakdown, we identify the most important processes and detect the restraining ones. This procedure allows constructing a more streamlined, subsequent 15th model with improved model performance, less uncertainty and higher model efficiency. We benchmark the original Model 1 and the final Model 15 with HBV Light. The final model is not able to outperform HBV Light, but we find that the incremental model breakdown leads to a structure with good model performance, fewer but more relevant processes and fewer model parameters.

Model Calibration for the High-Purity Oxygen Activated Sludge Process – Algorithm Development and Evaluation

1993 ◽  
Vol 28 (11-12) ◽  
pp. 163-171 ◽  
Author(s):  
Weibo (Weber) Yuan ◽  
David Okrent ◽  
Michael K. Stenstrom
Keyword(s):  
Activated Sludge ◽  
High Purity ◽  
Model Calibration ◽  
Process Model ◽  
Model Parameters ◽  
Complex Method ◽  
Activated Sludge Process ◽  
Activated Sludge Model ◽  
Kinetic Coefficients ◽  
Calibration Algorithm

A model calibration algorithm is developed for the high-purity oxygen activated sludge process (HPO-ASP). The algorithm is evaluated under different conditions to determine the effect of the following factors on the performance of the algorithm: data quality, number of observations, and number of parameters to be estimated. The process model used in this investigation is the first HPO-ASP model based upon the IAWQ (formerly IAWPRC) Activated Sludge Model No. 1. The objective function is formulated as a relative least-squares function and the non-linear, constrained minimization problem is solved by the Complex method. The stoichiometric and kinetic coefficients of the IAWQ activated sludge model are the parameters focused on in this investigation. Observations used are generated numerically but are made close to the observations from a full-scale high-purity oxygen treatment plant. The calibration algorithm is capable of correctly estimating model parameters even if the observations are severely noise-corrupted. The accuracy of estimation deteriorates gradually with the increase of observation errors. The accuracy of calibration improves when the number of observations (n) increases, but the improvement becomes insignificant when n>96. It is also found that there exists an optimal number of parameters that can be rigorously estimated from a given set of information/data. A sensitivity analysis is conducted to determine what parameters to estimate and to evaluate the potential benefits resulted from collecting additional measurements.

scholarly journals CALCULATION OF MULTI-BLADE CUTTING TOOL RELIABILITY

2019 ◽  
Vol 2019 (6) ◽  
pp. 30-37
Author(s):  
Александр Анцев ◽  
Aleksandr Ancev
Keyword(s):  
Cutting Tool ◽  
Complex Model ◽  
Model Parameters ◽  
Average Period ◽  
Blade Number ◽  
Blade Cutting ◽  
Cutting Processes ◽  
Period Decrease ◽  
Tool Durability ◽  
Average Durability

The process effectiveness of blade cutting is defined considerably with the prediction accuracy of cutting tool durability term. But, in spite of that cutting processes have a probabilistic character, in modern mechanical engineering there are used durability de-pendences describing only the dependence of an average period of blade cutting tool durability upon cutting modes without taking into account a stochastic nature of tool wear depending upon many factors. For ac-counting cutting process variability there are offered stochastic models of cutting tool failure, but they hold good for a cutting tool with one cutting edge and in the case with a multi-blade cutting tool they must be speci-fied. In the paper it is defined that at a fan wear model with the increase of the blade number the period of cutting tool durability decreases, as failure likelihood of even one blade increases because of the blade properties spread of one tool. The factor of a durability period variation decreases with the growth of the blade number because of the decrease of an average durability period decrease. In the case of a wear accumulation model the multi-blade tool reliability does not depend upon the blade number. The dependences of an average period of durability and a factor of variation at a complex model of wear are similar to the case with the fan model of wear, but their values will be higher. In the case of a destruction model the factor of multi-blade tool durability variation does not depend upon the blade number, but an average durability depends considerably upon the blade number, but the dependence appearance corresponds to the dependence of an average durability at a fan model of wear. The type of the dependence of durability average period upon on the blade number at a generalized model of failures is similar to the cases considered previously, and a kind of the dependence of a variation factor changes depending on model parameters

scholarly journals Estimation of Net Radiation using satellite based data inputs

2014 ◽  
Vol XL-8 ◽  
pp. 307-313 ◽  
Author(s):  
S. V. S. Sai Krishna ◽  
P. Manavalan ◽  
P. V. N. Rao
Keyword(s):  
Outgoing Longwave Radiation ◽  
Surface Air Temperature ◽  
Longwave Radiation ◽  
Surface Radiation ◽  
Shortwave Radiation ◽  
Net Radiation ◽  
Clear Sky ◽  
Statistical Measures ◽  
Indian Land ◽  
Radiation Fluxes

Daily net surface radiation fluxes are estimated for Indian land mass at spatial grid intervals of 0.1 degree. Two approaches are employed to obtain daily net radiation for four sample days viz., November 19, 2013, December 16, 2013, January 8, 2014 and March 20, 2014. Both the approaches compute net shortwave and net longwave fluxes, separately and sum them up to obtain net radiation. The first approach computes net shortwave radiation using daily insolation product of Kalpana VHRR and 15 days time composited broadband albedo product of Oceansat OCM2. The net outgoing longwave radiation is computed using Stefan Boltzmann equation corrected for humidity and cloudiness. In the second approach, instantaneous clear-sky net-shortwave radiation is estimated using computed clear-sky incoming shortwave radiation and the gridded MODIS 16-day time composited albedo product. The net longwave radiation is obtained by estimating outgoing and incoming longwave radiation fluxes, independently. In this, MODIS derived surface emissivity and skin temperature parameters are used for estimating outgoing longwave radiation component. In both the approaches, surface air temperature data required for estimation of net longwave radiation fluxes are extracted from India Meteorological Department’s (IMD) Automatic Weather Station (AWS) records. Estimates by the two different approaches are evaluated by comparing daily net radiation fluxes with CERES based estimates corresponding to the sample days, through statistical measures. The estimated all sky daily net radiation using the first approach compared well with CERES SYN1deg daily average net radiation with r<sup>2</sup> values of the order of 0.7 and RMS errors of the order of 8&ndash;16 w/m<sup>2</sup>.

scholarly journals Optimizing models of the North Atlantic spring bloom using physical, chemical and bio-optical observations from a Lagrangian float

2010 ◽  
Vol 7 (6) ◽  
pp. 8477-8520 ◽  
Author(s):  
W. Bagniewski ◽  
K. Fennel ◽  
M. J. Perry ◽  
E. A. D'Asaro
Keyword(s):  
North Atlantic ◽  
Spring Bloom ◽  
Deep Ocean ◽  
Complex Model ◽  
Optical Observations ◽  
Model Parameters ◽  
Carbon Export ◽  
The North ◽  
Chemical Measurements ◽  
The North Atlantic

Abstract. The North Atlantic spring bloom is one of the main events that lead to carbon export to the deep ocean and drive oceanic uptake of CO2 from the atmosphere. Here we use a suite of physical, bio-optical and chemical measurements made during the 2008 spring bloom to optimize and compare three different models of biological carbon export. The observations are from a Lagrangian float that operated south of Iceland from early April to late June, and were calibrated with ship-based measurements. The simplest model is representative of typical NPZD models used for the North Atlantic, while the most complex model explicitly includes diatoms and the formation of fast sinking diatom aggregates and cysts under silicate limitation. We carried out a variational optimization and error analysis for the biological parameters of all three models, and compared their ability to replicate the observations. The observations were sufficient to constrain most phytoplankton-related model parameters to accuracies of better than 15%. However, the lack of zooplankton observations leads to large uncertainties in model parameters for grazing. The simulated vertical carbon flux at 100 m depth is similar between models and agrees well with available observations, but at 600 m the simulated flux is much larger for the model with diatom aggregation. While none of the models can be formally rejected based on their misfit with the available observations, the model that includes export by diatom aggregation has slightly better fit to the observations and more accurately represents the mechanisms and timing of carbon export based on observations not included in the optimization. Thus models that accurately simulate the upper 100 m do not necessarily accurately simulate export to deeper depths.

scholarly journals Global sensitivity analysis of parameter uncertainty in landscape evolution models

2018 ◽  
Vol 11 (12) ◽  
pp. 4873-4888 ◽  
Author(s):  
Christopher J. Skinner ◽  
Tom J. Coulthard ◽  
Wolfgang Schwanghart ◽  
Marco J. Van De Wiel ◽  
Greg Hancock
Keyword(s):  
Sensitivity Analysis ◽  
Objective Function ◽  
Landscape Evolution ◽  
Relative Sensitivity ◽  
Function Approach ◽  
Sensitivity Analyses ◽  
Model Parameters ◽  
Model Function ◽  
Sediment Yields ◽  
Statistical Measures

Abstract. The evaluation and verification of landscape evolution models (LEMs) has long been limited by a lack of suitable observational data and statistical measures which can fully capture the complexity of landscape changes. This lack of data limits the use of objective function based evaluation prolific in other modelling fields, and restricts the application of sensitivity analyses in the models and the consequent assessment of model uncertainties. To overcome this deficiency, a novel model function approach has been developed, with each model function representing an aspect of model behaviour, which allows for the application of sensitivity analyses. The model function approach is used to assess the relative sensitivity of the CAESAR-Lisflood LEM to a set of model parameters by applying the Morris method sensitivity analysis for two contrasting catchments. The test revealed that the model was most sensitive to the choice of the sediment transport formula for both catchments, and that each parameter influenced model behaviours differently, with model functions relating to internal geomorphic changes responding in a different way to those relating to the sediment yields from the catchment outlet. The model functions proved useful for providing a way of evaluating the sensitivity of LEMs in the absence of data and methods for an objective function approach.

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