scholarly journals Simulation of the Growth Potential of Sugarcane as an Energy Crop Based on the APSIM Model

Energies ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 2173
Author(s):  
Ting Peng ◽  
Jingying Fu ◽  
Dong Jiang ◽  
Jinshuang Du
Keyword(s):  
Production Systems ◽  
Meteorological Data ◽  
Growth Potential ◽  
Energy Crop ◽  
Model Parameters ◽  
Marginal Land ◽  
Ethanol Fuel ◽  
Production Potential ◽  
Sugarcane Production ◽  
Global Energy Supply

Research on the development of plants grown for energy purposes is important for ensuring the global energy supply and reducing greenhouse gas emissions, and simulation is an important method to study its potential. This paper evaluated the marginal land that could be used to grow sugarcane in the Guangxi Zhuang Autonomous Region. Based on the meteorological data from 2009 to 2017 in this region and field observations from sugarcane plantations, the sensitivity of the APSIM (Agricultural Production Systems sIMulator) model parameters was analyzed by an extended Fourier amplitude sensitivity test, and the APSIM model was validated for sugarcane phenology and yields. During the process of model validation, the value of the determination coefficient R2 of the observed and simulated values was between 0.76 and 0.91, and the consistency index D was between 0.91 and 0.97, indicating a good fit. On this basis, the APSIM sugarcane model was used to simulate the sugarcane production potential of the marginal land on a surface scale, and the distribution pattern of sugarcane production potential in the marginal land was obtained. The simulation results showed that if sugarcane was planted as an energy crop on the marginal land in Guangxi, it would likely yield approximately 42,522.05 × 104 t of cane stalks per year. It was estimated that the sugarcane grown on the marginal land plus 50% of the sugarcane grown on the cropland would be sufficient to produce approximately 3847.37 × 104 t of ethanol fuel. After meeting the demands for vehicle ethanol fuel in Guangxi, 3808.14 × 104 t of ethanol fuel would remain and could be exported to the ASEAN (Association of Southeast Asian Nations).

scholarly journals Spatial Assessment of Jerusalem Artichoke’s Potential as an Energy Crop in the Marginal Land of the Shaanxi Province, China

2021 ◽  
Vol 13 (24) ◽  
pp. 13576
Author(s):  
Fang Yin ◽  
Ziyue Jin ◽  
Jiazheng Zhu ◽  
Lei Liu ◽  
Danyun Zhao
Keyword(s):  
Production Systems ◽  
Production Capacity ◽  
Jerusalem Artichoke ◽  
Assessment Method ◽  
Shaanxi Province ◽  
Energy Crop ◽  
Marginal Land ◽  
Land Resources ◽  
Agricultural Production Systems ◽  
Suitable Land

As a foodstuff crop, Jerusalem artichoke has a promising prospect for providing sustainable feed-stock sources for bioenergy development. Due to relatively limited cultivated land resources in China, it is crucial to evaluate Jerusalem artichoke’s potential production capacity in marginal land. Based on Jerusalem artichoke’s growth and photosynthetic characteristics, the agricultural production systems simulator model (APSIM) and multi-factor integrated assessment method were integrated to provide an operational method for comprehensively evaluating the marginal land resources suitable for developing the plantation of Jerusalem artichoke in the Shaanxi province, China. The results showed that 0.73 million ha of marginal land was suitable for Jerusalem artichoke cultivation in the Shaanxi province, and 5.4 million ha of marginal land was fairly suitable for Jerusalem artichoke cultivation, with the yield reaching 44,289 kg/ha and 38,861 kg/ha, respectively. The suitable land resources are mainly located in Yan’an (0.18 million ha), Hanzhong (0.13 million ha), and Baoji (0.08 million ha), most of which are moderate dense grassland (accounting for 50.6% of suitable land), dense grassland (accounting for 16.2% of suitable land), shrubland (accounting for 14.7% of suitable land), and sparse forest land (accounting for 9.18% of suitable land). The findings of this study can be used to establish targeted policies for Jerusalem artichoke development in China and other countries, particularly those along the Silk Road.

Lifetime Estimation of a Photovoltaic Module Subjected to Corrosion Due to Damp Heat Testing

2012 ◽  
Vol 135 (2) ◽  
Author(s):  
R. Laronde ◽  
A. Charki ◽  
D. Bigaud
Keyword(s):  
Crystalline Silicon ◽  
Meteorological Data ◽  
Photovoltaic Module ◽  
Model Parameters ◽  
Solar Panels ◽  
Power Requirement ◽  
Pv Module ◽  
Accelerated Life ◽  
Mean Lifetime ◽  
Initial Power

In this paper, a methodology is presented for estimating the lifetime of a photovoltaic (PV) module. Designers guarantee an acceptable level of power (80% of the initial power) up to 25 yr for solar panels without having sufficient feedback to validate this lifetime. Accelerated life testing (ALT) can be carried out in order to determine the lifetime of the equipment. Severe conditions are used to accelerate the ageing of components and the reliability is then deduced in normal conditions, which are considered to be stochastic rather than constant. Environmental conditions at normal operations are simulated using IEC 61725 standard and meteorological data. The mean lifetime of a crystalline-silicon photovoltaic module that meets the minimum power requirement is estimated. The main results show the influence of lifetime distribution and Peck model parameters on the estimation of the lifetime of a photovoltaic module.

scholarly journals Analysis of evapotranspiration and biomass in pastures with degradation indicatives in the Upper Tocantins River Basin, in Brazilian Savanna

Revista CERES ◽  
2016 ◽  
Vol 63 (6) ◽  
pp. 754-760 ◽  
Author(s):  
Ricardo Guimarães Andrade ◽  
Antônio Heriberto de Castro Teixeira ◽  
Janice Freitas Leivas ◽  
Sandra Furlan Nogueira
Keyword(s):  
River Basin ◽  
Large Scale ◽  
Meteorological Data ◽  
Simple Algorithm ◽  
Production Potential ◽  
Pasture Degradation ◽  
Ndvi Time Series ◽  
Tocantins River ◽  
Remote Sensing Techniques ◽  
Degraded Pastures

ABSTRACT The objective of this study was to apply the Simple Algorithm For Evapotranspiration Retrieving (SAFER) with MODIS images together with meteorological data to analyze evapotranspiration (ET) and biomass production (BIO) according to indicative classes of pasture degradation in Upper Tocantins River Basin. Indicative classes of degraded pastures were obtained from the NDVI time-series (2002-2012). To estimate ET and BIO in each class, MODIS images and data from meteorological stations of the year 2012 were used. The results show that compared to not-degraded pastures, ET and BIO were different in pastures with moderate to strong degradation, mainly during water stress period. Therefore, changes in energy balance partition may occur according to the degradation levels, considering that those indicatives of degradation processes were identified in 24% of the planted pasture areas. In this context, ET and BIO estimates using remote sensing techniques can be a reliable indicator of forage availability, and large-scale aspects related to the degradation of pastures. It is expected that this knowledge may contribute to initiatives of public policies aimed at controlling the loss of production potential of pasture areas in the Upper Tocantins River Basin in the state of Goiás, Brazil.

scholarly journals Application and evaluation of the dendroclimatic process-based model MAIDEN during the last century in Canada and Europe

2020 ◽  
Vol 16 (3) ◽  
pp. 1043-1059
Author(s):  
Jeanne Rezsöhazy ◽  
Hugues Goosse ◽  
Joël Guiot ◽  
Fabio Gennaretti ◽  
Etienne Boucher ◽  
...  
Keyword(s):  
Tree Ring ◽  
Tree Growth ◽  
Meteorological Data ◽  
Ring Width ◽  
Complex Model ◽  
Added Value ◽  
Model Parameters ◽  
Sources Of Information ◽  
Calibration And Validation

Abstract. Tree-ring archives are one of the main sources of information to reconstruct climate variations over the last millennium with annual resolution. The links between tree-ring proxies and climate have usually been estimated using statistical approaches, assuming linear and stationary relationships. Both assumptions may be inadequate, but this issue can be overcome by ecophysiological modelling based on mechanistic understanding. In this respect, the model MAIDEN (Modeling and Analysis In DENdroecology) simulating tree-ring growth from daily temperature and precipitation, considering carbon assimilation and allocation in forest stands, may constitute a valuable tool. However, the lack of local meteorological data and the limited characterization of tree species traits can complicate the calibration and validation of such a complex model, which may hamper palaeoclimate applications. The goal of this study is to test the applicability of the MAIDEN model in a palaeoclimate context using as a test case tree-ring observations covering the 20th century from 21 Eastern Canadian taiga sites and 3 European sites. More specifically, we investigate the model sensitivity to parameter calibration and to the quality of climatic inputs, and we evaluate the model performance using a validation procedure. We also examine the added value of using MAIDEN in palaeoclimate applications compared to a simpler tree-growth model, i.e. VS-Lite. A Bayesian calibration of the most sensitive model parameters provides good results at most of the selected sites with high correlations between simulated and observed tree growth. Although MAIDEN is found to be sensitive to the quality of the climatic inputs, simple bias correction and downscaling techniques of these data improve significantly the performance of the model. The split-sample validation of MAIDEN gives encouraging results but requires long tree ring and meteorological series to give robust results. We also highlight a risk of overfitting in the calibration of model parameters that increases with short series. Finally, MAIDEN has shown higher calibration and validation correlations in most cases compared to VS-Lite. Nevertheless, this latter model turns out to be more stable over calibration and validation periods. Our results provide a protocol for the application of MAIDEN to potentially any site with tree-ring width data in the extratropical region.

The Influence of Uncertainty in Air Temperature and Albedo on Snowmelt

1991 ◽  
Vol 22 (2) ◽  
pp. 95-108 ◽  
Author(s):  
G. Blöschl
Keyword(s):  
Snow Cover ◽  
Air Temperature ◽  
Meteorological Data ◽  
Model Parameters ◽  
Local Effects ◽  
Austrian Alps ◽  
Air Temperatures ◽  
Basin Scale ◽  
Simulation Results

Extrapolating meteorological data to the basin scale represents a major problem of spatial snowmelt modelling in alpine terrain. Within this study errors in air temperature introduced by regionalization are analyzed for the Sellrain region in the Austrian Alps. Albedo is simulated using a range of model parameters representing different snow cover conditions. The influence on snowmelt is assessed by simulating water equivalent at the site scale using estimated air temperatures and albedoes. Simulation results indicate that a bias in measured temperatures as produced by local effects may be significantly more important than interpolation errors. Uncertainty in albedo appears to affect snowmelt to a higher degree than air temperature.

scholarly journals Exploiting data in smart factories: real-time state estimation and model improvement in metal forming mass production

2019 ◽  
Vol 13 (5) ◽  
pp. 663-673 ◽  
Author(s):  
Jos Havinga ◽  
Pranab K. Mandal ◽  
Ton van den Boogaard
Keyword(s):  
State Estimation ◽  
Mass Production ◽  
Metal Forming ◽  
Particle Filtering ◽  
Production Systems ◽  
Model Parameters ◽  
Real Process ◽  
Sheet Bending ◽  
Model Improvement ◽  
Pseudo Data

Abstract Modern production systems have numerous sensors that produce large amounts of data. This data can be exploited in many ways, from providing insight into the manufacturing process to facilitating automated decision making. These opportunities are still underexploited in the metal forming industry, due to the complexity of these processes. In this work, a probabilistic framework is proposed for simultaneous model improvement and state estimation in metal forming mass production. Recursive Bayesian estimation is used to simultaneously track the evolution of process state and to estimate the deviation between the physics-based model and the real process. A sheet bending mass production process is used to test the proposed framework. A metamodel of the process is built using proper orthogonal decomposition and radial basis function interpolation. The model is extended with a deviation model in order to account for the difference between model and real process. Particle filtering is used to track the state evolution and to estimate the deviation model parameters simultaneously. The approach is tested and analysed using a large number of simulations, based on pseudo-data obtained from a numerical sheet bending model.

Sustainability assessment of sugarcane production systems: SustenAgro Decision Support System

2019 ◽  
Vol 32 ◽  
pp. 100444 ◽  
Author(s):  
Katia Regina Evaristo de Jesus ◽  
Sérgio Alves Torquato ◽  
Pedro Gerber Machado ◽  
Catiana Regina Brumatti Zorzo ◽  
Bruno Oliveira Cardoso ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Sustainability Assessment ◽  
Production Systems ◽  
Sugarcane Production

scholarly journals Hydrologic and water quality impacts and biomass production potential on marginal land

2015 ◽  
Vol 72 ◽  
pp. 230-238 ◽  
Author(s):  
Qingyu Feng ◽  
Indrajeet Chaubey ◽  
Young Gu Her ◽  
Raj Cibin ◽  
Bernard Engel ◽  
...  
Keyword(s):  
Water Quality ◽  
Biomass Production ◽  
Marginal Land ◽  
Production Potential

An Evaluation of the Literature on Integrated Sugarcane Production Systems

2011 ◽  
Vol 40 (1) ◽  
pp. 79-88 ◽  
Author(s):  
C.N. Bezuidenhout ◽  
T.J.A. Baier
Keyword(s):  
Production Systems ◽  
Sugarcane Production
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