scholarly journals Step-wise modifications of the Vegetation Optimality Model

2021 ◽  
Author(s):  
Remko Christiaan Nijzink ◽  
Jason Beringer ◽  
Lindsay Beaumont Hutley ◽  
Stanislaus Josef Schymanski
Keyword(s):  
Soil Texture ◽  
Optimality Theory ◽  
Input Data ◽  
Optimization Approach ◽  
Flux Tower ◽  
Optimality Model ◽  
Free Drainage ◽  
The Mean ◽  
Conventional Models ◽  
Modified Soil

Abstract. The Vegetation Optimality Model (VOM, Schymanski et al., 2009, 2015) is an optimality-based, coupled water-vegetation model that predicts vegetation properties and behaviour based on optimality theory, rather than calibrating vegetation properties or prescribing them based on observations, as most conventional models do. In order to determine wheter optimality theory can alleviate common shortcomings of conventional models, as identified in a previous model inter-comparison study along the North Australian Tropical Transect (NATT) (Whitley et al., 2016), a range of updates to previous applications of the VOM have been made for increased generality and improved comparability with conventional models. To assess in how far the updates to the model and input data would have affected the original results, we implemented them one-by-one while reproducing the analysis of Schymanski et al. (2015). The model updates included extended input data, the use of variable atmospheric CO2-levels, modified soil properties, implementation of free drainage conditions, and the addition of grass rooting depths to the optimized vegetation properties. A systematic assessment of these changes was carried out by adding each individual modification to the original version of the VOM at the flux tower site of Howard Springs, Australia. The analysis revealed that the implemented changes affected the simulation of mean annual evapo-transpiration (ET) and gross primary productivity (GPP) by no more than 20 %, with the largest effects caused by the newly imposed free drainage conditions and modified soil texture. Free drainage conditions led to an underestimation of ET and GPP, whereas more fine-grained soil textures increased the water storage in the soil and resulted in increased GPP. Although part of the effect of free drainage was compensated for by the updated soil texture, when combining all changes, the resulting effect on the simulated fluxes was still dominated by the effect of implementing free drainage conditions. Eventually, the relative error for the mean annual ET, in comparison with flux tower observations, changed from an 8.4 % overestimation to an 10.2 % underestimation, whereas the relative errors for the mean annual GPP stayed similar with a change from 17.8 % to 14.7 %. The sensitivity to free drainage conditions suggests that a realistic representation of groundwater dynamics is very important for predicting ET and GPP at a tropical open-forest savanna site as investigated here. The modest changes in model outputs highlighted the robustness of the optimization approach that is central to the VOM architecture.

scholarly journals Modeling the Excess Velocity of Low-Viscous Taylor Droplets in Square Microchannels

Fluids ◽  
2019 ◽  
Vol 4 (3) ◽  
pp. 162 ◽  
Author(s):  
Thorben Helmers ◽  
Philip Kemper ◽  
Jorg Thöming ◽  
Ulrich Mießner
Keyword(s):  
High Speed ◽  
Process Intensification ◽  
Continuous Phase ◽  
Channel Cross Section ◽  
Optimization Approach ◽  
Mean Flow ◽  
Bypass Flow ◽  
Wall Film ◽  
Proposed Model ◽  
The Mean

Microscopic multiphase flows have gained broad interest due to their capability to transfer processes into new operational windows and achieving significant process intensification. However, the hydrodynamic behavior of Taylor droplets is not yet entirely understood. In this work, we introduce a model to determine the excess velocity of Taylor droplets in square microchannels. This velocity difference between the droplet and the total superficial velocity of the flow has a direct influence on the droplet residence time and is linked to the pressure drop. Since the droplet does not occupy the entire channel cross-section, it enables the continuous phase to bypass the droplet through the corners. A consideration of the continuity equation generally relates the excess velocity to the mean flow velocity. We base the quantification of the bypass flow on a correlation for the droplet cap deformation from its static shape. The cap deformation reveals the forces of the flowing liquids exerted onto the interface and allows estimating the local driving pressure gradient for the bypass flow. The characterizing parameters are identified as the bypass length, the wall film thickness, the viscosity ratio between both phases and the C a number. The proposed model is adapted with a stochastic, metaheuristic optimization approach based on genetic algorithms. In addition, our model was successfully verified with high-speed camera measurements and published empirical data.

scholarly journals Optimization of the balance between effort and yield in unilateral surgical transfer of mouse embryos

2017 ◽  
Vol 51 (6) ◽  
pp. 622-628 ◽  
Author(s):  
Pablo González-Jara ◽  
Tomás Fontela ◽  
Esther López-Mimbela ◽  
Marta Cereceda ◽  
Daniel Del Olmo ◽  
...  
Keyword(s):  
Embryo Transfer ◽  
Mouse Embryos ◽  
Mouse Strains ◽  
Optimization Approach ◽  
Use Of Resources ◽  
Heterogeneous Nature ◽  
Laboratory Manuals ◽  
The Mean ◽  
Transfer Procedures

Surgical transfer of embryos is carried out daily in animal facilities worldwide for the rederivation of mouse strains/lines, among other purposes. Current protocols described in laboratory manuals recommend using a high number of embryos during transfer, typically in the range of 15 up to 25. To optimize the use of resources it is necessary to estimate and relate the effort required and the yield obtained. Here, we analyse the balance between the number of embryos transferred (the effort), and the yield as the number of born pups obtained from surgical embryo transfer. To accomplish this, we have analyzed data obtained during rederivation of nearly one hundred lines of mice to a new animal facility. Our results confirm that the use of increasing numbers of embryos per transfer increases the yields of born pups, as has been described previously in the literature, but they also highlight the disproportionate effort required, i.e. in the number of embryos that needed to be transferred. An estimate of the mean expected yields of surgical transfers and their comparison with the actual observed yields indicated that the balance between effort and yield is optimized when using lower numbers of embryos than in currently used protocols, in the range of 8 to 12. Given the heterogeneous nature of the data presented and analyzed here, which is from a population of mice that may be considered as representative of any animal facility, our optimization approach should help save resources in similar facilities and improve the yields of embryo transfer procedures.

Inoptimality losses in forest management decisions caused by errors in an inventory based on airborne laser scanning and aerial photographs

2010 ◽  
Vol 40 (12) ◽  
pp. 2427-2438 ◽  
Author(s):  
Md. Nurul Islam ◽  
Mikko Kurttila ◽  
Lauri Mehtätalo ◽  
Timo Pukkala
Keyword(s):  
Input Data ◽  
Laser Scanning ◽  
Basal Area ◽  
Airborne Laser Scanning ◽  
Aerial Photographs ◽  
Stand Age ◽  
Inventory Data ◽  
Airborne Laser ◽  
Mean Diameter ◽  
The Mean

Errors in inventory data may lead to inoptimal decisions that ultimately result in financial losses for forest owners. We estimated the expected monetary losses resulting from data errors that are similar to errors in laser-based forest inventory. The mean loss was estimated for 67 stands by simulating 100 realizations of inventory data for each stand with errors that mimic those in airborne laser scanning (ALS) based inventory. These realizations were used as input data in stand management optimization, which maximized the present value of all future net incomes (NPV). The inoptimality loss was calculated as the difference between the NPV of the optimal solution and the true NPV of the solution obtained with erroneous input data. The results showed that the mean loss exceeded €300·ha–1 (US$425·ha–1) in 84% of the stands. On average, the losses increased with decreasing stand age and mean diameter. Furthermore, increasing errors in the basal area weighted mean diameter and basal area of spruce were found to significantly increase the loss. It has been discussed that improvements in the accuracy of ALS-based inventory could be financially justified.

Multistate life tables using Stata

2020 ◽  
Vol 20 (3) ◽  
pp. 721-745
Author(s):  
Jerônimo Oliveira Muniz
Keyword(s):  
Life Table ◽  
Input Data ◽  
Average Duration ◽  
Transition Rates ◽  
Absorbing State ◽  
Multistate Life Tables ◽  
The Mean ◽  
Time Specific ◽  
Number Of Individuals ◽  
Multistate Life Table

The mslt command calculates the functions of a multistate life table and plots a graph of conditional and unconditional life expectancies by time. The command provides linear and exponential solutions to estimate the number of individuals, transitions, probabilities, person-years, and years of life in a given cohort and state of occupancy. The input data are time-specific transition rates (or survivorship proportions) between nonabsorbing and at most one absorbing state. In addition to the mean age at transfer between states, mslt calculates the following summary measures: the mean age, the probability of dying, the average duration, and the proportion of life spent in a specific state.

Site Index Curves for Norway Spruce in Southern Ontario1

1989 ◽  
Vol 6 (1) ◽  
pp. 23-26 ◽  
Author(s):  
Andrew M. Gordon ◽  
Peter A. Williams ◽  
Edward P. Taylor
Keyword(s):  
Norway Spruce ◽  
Soil Texture ◽  
Sandy Soils ◽  
Site Index ◽  
Height Growth ◽  
Stem Analysis ◽  
Mean Values ◽  
Breast Height ◽  
Drainage Class ◽  
The Mean

Abstract Four dominant or codominant Norway spruce trees from each of 55 sites were destructively sampled and the annual height growth determined by stem analysis. The sampled sites were stratified by soil textural class (coarse, medium, and fine) and depth to distinct mottling (0-16, 16-40, and 40 in.). Two sets of an-amorphic site index curves were constructed using a total age of 30 years (SI30), and breast height age of 25 years (SIBH25) as base ages. The mean SI30 from Ontario (53 ft) was found to be 17.8% higher than the mean values published from Vermont (45 ft) and currently used in Ontario. SIBH25 values had a range of 34.6 to 74.8 ft with a mean of 55.3 ft. Analysis of variance showed significant differences in SIBH25 due to soil texture and drainage class, and in years to breast height (BH) due to drainage class. SIBH25 was highest on sites with loamy soils and distinct mottling at 16-40 in. It took an average of 6.5 years for seedlings to reach BH with a range of 3 to 12 years. Years to BH was lowest on sites with sandy soils and those with distinct mottling below 40 in. North. J. Appl. For. 6(1):23-26, March 1989.

scholarly journals Accuracy and Transferability of Artificial Neural Networks in Predicting in Situ Root-Zone Soil Moisture for Various Regions across the Globe

Water ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 3109
Author(s):  
Roïya Souissi ◽  
Ahmad Al Bitar ◽  
Mehrez Zribi
Keyword(s):  
Neural Network ◽  
Soil Moisture ◽  
Soil Texture ◽  
Surface Soil ◽  
Root Zone ◽  
Data Filtering ◽  
Surface Soil Moisture ◽  
The Mean ◽  
Artificial Neural

This paper explores the accuracy in using an artificial neural network (ANN) to estimate root-zone soil moisture (RZSM) at multiple worldwide locations using only in situ surface soil moisture (SSM) as a training dataset. The paper also addresses the transferability of the trained ANN across climatic and soil texture conditions. Data from the International Soil Moisture Network (ISMN) were collected for several networks with variable soil texture and climate classes. Several scaling, feature extraction, and training approaches were tested. An artificial neural network employing rolling averages (ANNRAV) of SSM over 10, 30, and 90 days was developed. The results show that applying a standard scaling (SSCA) to the ANN input features improves the correlation, Nash–Sutcliffe efficiency (NSE), and root mean square error (RMSE) for 52%, 91%, and 87%, respectively, of the tested stations, compared to MinMax scaling (MMSCA). Different training sets are suggested, namely, training on data from all networks, data from one network, or data of all networks excluding one. Based on these trainings, new transferability (TranI) and contribution (ContI) indices are defined. The results show that one network cannot provide the best prediction accuracy if used alone to train the ANN. They also show that the removal of the less contributing networks enhances performance. For example, elimination of the densest network (SCAN) from the training enhances the mean correlation by 20.5% and the mean NSE by 42.5%. This motivates the implementation of a data filtering technique based on the ANN’s performance. A median, max, and min correlation of 0.77, 0.96, and 0.65, respectively, are obtained by the model after data filtering. The performances are also analyzed with respect to the covered climatic regions and soil texture, providing insights into the robustness and limitations of the approach, namely, the need for complementary information in highly evaporative regions. In fact, the ANN using only SSM to predict RZSM has low performance when decoupling between the surface and root zones is observed. The application of ANN to obtain spatialized RZSM will require integrating remote sensing-based surface soil moisture in the future.

New Tolerance Analysis Model for Normal Mean Shift in Manufacturing Process

2008 ◽  
Vol 594 ◽  
pp. 339-350 ◽  
Author(s):  
Chang Hsin Kuo ◽  
Jhy Cherng Tsai
Keyword(s):  
Normal Distribution ◽  
Uniform Distribution ◽  
Manufacturing Process ◽  
Mean Shift ◽  
Tolerance Analysis ◽  
Analysis Model ◽  
Normal Mean ◽  
The Mean ◽  
The Difference ◽  
Conventional Models

In this paper, we discuss the tolerance analysis methods for the component with a mean shift or drift. A new tolerance analysis model that assumes the mean shift in normal distribution rather than in uniform distribution is proposed. Simulation shows that the difference between the uniform distribution and normal distribution is 1.7%, which can be ignored, for mean shift to one standard deviation (σ). However, the difference becomes significant when the mean shift increases. The difference increases to 5.2% with 1.5σ shift, to 10.9% for 2σ shift, and up to 30.4% for 3σ shift. As normal distribution is a better model for statistical mean shift in manufacturing process, this investigation shows that the proposed tolerance analysis model can give a better model compared to conventional models.

Developing the soil texture effects on the surface resistance to bare soil based on MOD16 algorithm to estimate evapotranspiration over the Tibetan Plateau

2020 ◽  
Author(s):  
Ling Yuan ◽  
Yaoming Ma ◽  
Xuelong Chen
Keyword(s):  
Tibetan Plateau ◽  
Soil Texture ◽  
Land Surface ◽  
Bare Soil ◽  
The Other ◽  
Accurate Estimation ◽  
Surface Model ◽  
The Tibetan Plateau ◽  
The Mean ◽  
Modified Algorithm

<p>Evapotranspiration (ET), composed of evaporation (ETs) and transpiration (ETc) and intercept water (ETw), plays an indispensable role in the water cycle and energy balance of land surface processes. A more accurate estimation of ET variations is essential for natural hazard monitoring and water resource management. For the cold, arid, and semi-arid regions of the Tibetan Plateau (TP), previous studies often overlooked the decisive role of soil properties in ETs rates. In this paper, an improved algorithm for ETs in bare soil and an optimized parameter for ETc over meadow based on MOD16 model are proposed for the TP. The nonlinear relationship between surface evaporation resistance (r<sub>s</sub><sup>s</sup>) and soil surface hydration state in different soil texture is redefined by ground-based measurements over the TP. Wind speed and vegetation height were integrated to estimate aerodynamic resistance by Yang et al. (2008). The validated value of the mean potential stomatal conductance per unit leaf area (C<sub>L</sub>) is 0.0038m s<sup>-1</sup>. And the algorithm was then compared with the original MOD16 algorithm and a soil water index–based Priestley-Taylor algorithm (SWI–PT). After examining the performance of the three models at 5 grass flux tower sites in different soil texture over the TP, East Asia, and America, the validation results showed that the half-hour estimates from the improved-MOD16 were closer to observations than those of the other models under the all-weather in each site. The average correlation coefficient(R<sup>2</sup>) of the improved-MOD16 model was 0.83, compared with 0.75 in the original MOD16 model and 0.78 in SWI-PT model. The average values of the root mean square error (RMSE) are 35.77W m<sup>-2</sup>, 79.46 W m<sup>-2</sup>, and 73.88W m<sup>-2</sup> respectively. The average values of the mean bias (MB) are -4.08W m<sup>-2</sup>, -52.36W m<sup>-2</sup>, and -11.74 W m<sup>-2</sup> overall sites, respectively. The performance of these algorithms are better achieved on daily (R<sup>2</sup>=0.81, RMSE=17.22W m<sup>-2</sup>, MB=-4.12W m<sup>-2</sup>; R<sup>2</sup>=0.64, RMSE=56.55W m<sup>-2</sup>, MB=-48.74W m<sup>-2</sup>; R2=0.78, RMSE=22.3W m<sup>-2</sup>, MB=-9.82W m<sup>-2</sup>) and monthly (R2=0.93, RMSE=23.35W m<sup>-2</sup>, MB=-2.8W m<sup>-2</sup>; R2=0.86, RMSE=69.11W m<sup>-2</sup>, MB=-39.5W m<sup>-2</sup>; R2=0.79, RMSE=62.8W m<sup>-2</sup>, MB=-9.7W m<sup>-2</sup>) scales. Overall, the results showed that the newly developed MOD16 model captured ET more accurately than the other two models. The comparisons between the modified algorithm and two mainstream methods suggested that the modified algorithm could produce high accuracy ET over the meadow sites and has great potential for land surface model improvements and remote sensing ET promotion for the ET region.</p>

Soil texture controls vegetation biomass and organic carbon storage in arid desert grassland in the middle of Hexi Corridor region in Northwest China

Soil Research ◽  
2015 ◽  
Vol 53 (4) ◽  
pp. 366 ◽  
Author(s):  
Yongzhong Su ◽  
Jiuqiang Wang ◽  
Rong Yang ◽  
Xiao Yang ◽  
Guiping Fan
Keyword(s):  
Organic Carbon ◽  
Soil Texture ◽  
Clay Content ◽  
Northwest China ◽  
Hexi Corridor ◽  
Desert Grassland ◽  
Vegetation Biomass ◽  
Below Ground ◽  
The Mean ◽  
Arid Desert

Soil texture plays an important role in controlling vegetation production and soil organic carbon (SOC) concentration in arid desert grassland ecosystems. However, little is known about the occurrence and extent of these textural effects in the arid desert grasslands of Northwest China. This study used 160 soil profiles taken from 32 desert grassland sites in similar topographical units (alluvial–diluvial fans) in the middle of Hexi Corridor region of Northwest China to investigate vegetation biomass, SOC storage, and soil texture of seven layers in the top 100 cm of soil. The mean aboveground biomass, below-ground biomass, and total biomass in arid desert grassland were 155.3, 95.3, and 256.3 g m–2, respectively. More than 95% of the below-ground biomass was distributed in the top 30 cm of soil. Spatially, vegetation biomass was positively related to soil clay content and silt + clay content. The mean SOC density in the top 100 cm was 2.94 kg m–2 and ~46.8% of the storage was concentrated in the top 30 cm. SOC concentrations and stocks were positively and significantly related to clay content and silt + clay content in the seven soil layers sampled from the top 100 cm. The soil silt + clay content explained 42–79% of the variation in SOC stocks in the different soil depths. In conclusion, soil texture appears to be an important control on vegetation productivity and SOC capacity in arid Hexi Corridor desert grassland soils.

Robust Design Through the Use of a Hybrid Genetic Algorithm

2002 ◽  
Author(s):  
Kurt Hacker ◽  
Kemper Lewis
Keyword(s):  
Robust Design ◽  
Hybrid Genetic Algorithm ◽  
Design Parameters ◽  
Optimization Approach ◽  
Engineering Systems ◽  
Local Optima ◽  
Good Design ◽  
Mean And Variance ◽  
The Mean

In this paper we present a hybrid optimization approach to perform robust design. The motivation for this work is the fact that many realistic engineering systems are mutimodal in nature with multiple local optima, and moreover may have one or more uncertain design parameters. The approach that is presented utilizes both local and global optimization algorithms to find good design points more efficiently than either could alone. The mean and variance of the objective function at a design point is calculated using Monte Carlo simulation and is used to drive the optimization process. To demonstrate the usefulness of this approach a case study is considered involving the design of a beam with dimensional uncertainty.

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