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Author |
Mansouri, M.; Dumont, B.; Destain, M.-F. |
Title |
Modeling and prediction of nonlinear environmental system using Bayesian methods |
Type |
Journal Article |
Year |
2013 |
Publication |
Computers and Electronics in Agriculture |
Abbreviated Journal |
Computers and Electronics in Agriculture |
Volume |
92 |
Issue |
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Pages |
16-31 |
Keywords |
state and parameter estimation; variational filter; particle filter; extended kalman filter; nonlinear environmental system; leaf area index and soil moisture model; extended kalman filter; state-space models; parameter-estimation; particle filters; navigation; tutorial; tracking |
Abstract |
An environmental dynamic system is usually modeled as a nonlinear system described by a set of nonlinear ODEs. A central challenge in computational modeling of environmental systems is the determination of the model parameters. In these cases, estimating these variables or parameters from other easily obtained measurements can be extremely useful. This work addresses the problem of monitoring and modeling a leaf area index and soil moisture model (LSM) using state estimation. The performances of various conventional and state-of-the-art state estimation techniques are compared when they are utilized to achieve this objective. These techniques include the extended Kalman filter (EKF), particle filter (PF), and the more recently developed technique variational filter (VF). Specifically, two comparative studies are performed. In the first comparative study, the state variables (the leaf-area index LAI, the volumetric water content of the soil layer 1, HUR1 and the volumetric water content of the soil layer 2, HUR2) are estimated from noisy measurements of these variables, and the various estimation techniques are compared by computing the estimation root mean square error (RMSE) with respect to the noise-free data. In the second comparative study, the state variables as well as the model parameters are simultaneously estimated. In this case, in addition to comparing the performances of the various state estimation techniques, the effect of number of estimated model parameters on the accuracy and convergence of these techniques are also assessed. The results of both comparative studies show that the PF provides a higher accuracy than the EKF, which is due to the limited ability of the EKF to handle highly nonlinear processes. The results also show that the VF provides a significant improvement over the PF because, unlike the PF which depends on the choice of sampling distribution used to estimate the posterior distribution, the VF yields an optimum choice of the sampling distribution, which also accounts for the observed data. The results of the second comparative study show that, for all techniques, estimating more model parameters affects the estimation accuracy as well as the convergence of the estimated states and parameters. However, the VF can still provide both convergence as well as accuracy related advantages over other estimation methods. (C) 2013 Elsevier B.V. All rights reserved. |
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0168-1699 |
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MA @ admin @ |
Serial |
4495 |
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Author |
Conradt, T.; Wechsung, F.; Bronstert, A. |
Title |
Three perceptions of the evapotranspiration landscape: comparing spatial patterns from a distributed hydrological model, remotely sensed surface temperatures, and sub-basin water balances |
Type |
Journal Article |
Year |
2013 |
Publication |
Hydrology and Earth System Sciences |
Abbreviated Journal |
Hydrol. Earth System Sci. |
Volume |
17 |
Issue |
7 |
Pages |
2947-2966 |
Keywords |
senegal river-basin; data assimilation; sensing data; regional evapotranspiration; intercomparison project; environmental-models; oklahoma experiments; solar-radiation; satellite data; scale |
Abstract |
A problem encountered by many distributed hydrological modelling studies is high simulation errors at interior gauges when the model is only globally calibrated at the outlet. We simulated river runoff in the Elbe River basin in central Europe (148 268 km(2)) with the semi-distributed eco-hydrological model SWIM (Soil and Water Integrated Model). While global parameter optimisation led to Nash-Sutcliffe efficiencies of 0.9 at the main outlet gauge, comparisons with measured runoff series at interior points revealed large deviations. Therefore, we compared three different strategies for deriving sub-basin evapotranspiration: (1) modelled by SWIM without any spatial calibration, (2) derived from remotely sensed surface temperatures, and (3) calculated from long-term precipitation and discharge data. The results show certain consistencies between the modelled and the remote sensing based evapotranspiration rates, but there seems to be no correlation between remote sensing and water balance based estimations. Subsequent analyses for single sub-basins identify amongst others input weather data and systematic error amplification in inter-gauge discharge calculations as sources of uncertainty. The results encourage careful utilisation of different data sources for enhancements in distributed hydrological modelling. |
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1607-7938 |
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MA @ admin @ |
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4485 |
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Legarrea, S.; Betancourt, M.; Plaza, M.; Fraile, A.; García-Arenal, F.; Fereres, A. |
Title |
Dynamics of nonpersistent aphid-borne viruses in lettuce crops covered with UV-absorbing nets |
Type |
Journal Article |
Year |
2012 |
Publication |
Virus Research |
Abbreviated Journal |
Virus Res. |
Volume |
165 |
Issue |
1 |
Pages |
1-8 |
Keywords |
Absorption; Animals; Aphids/growth & development/radiation effects/*virology; Insect Control/instrumentation/*methods; Insect Vectors/growth & development/radiation effects/*virology; Lettuce/parasitology/*virology; Plant Diseases/prevention & control/*virology; Plant Viruses/*physiology; Protective Devices/virology; Ultraviolet Rays |
Abstract |
Aphid-transmitted viruses frequently cause severe epidemics in lettuce grown under Mediterranean climates. Spatio-temporal dynamics of aphid-transmitted viruses and its vector were studied on lettuce (Lactuca sativa L.) grown under tunnels covered by two types of nets: a commercial UV-absorbing net (Bionet) and a Standard net. A group of plants infected by Cucumber mosaic virus (CMV, family Bromoviridae, genus Cucumovirus) and Lettuce mosaic virus (LMV, family Potyviridae, genus Potyvirus) was transplanted in each plot. The same virus-infected source plants were artificially infested by the aphid Macrosiphum euphorbiae (Thomas). Secondary spread of insects was weekly monitored and plants were sampled for the detection of viruses every two weeks. In 2008, the infection rate of both CMV and LMV were lower under the Bionet than under the Standard cover, probably due to the lower population density and lower dispersal rate achieved by M. euphorbiae. However, during spring of 2009, significant differences in the rate of infection between the two covers were only found for LMV six weeks after transplant. The spatial distribution of the viruses analysed by SADIE methodology was “at random”, and it was not associated to the spatial pattern of the vector. The results obtained are discussed analyzing the wide range of interactions that occurred among UV-radiation, host plant, viruses, insect vector and environmental conditions. Our results show that UV-absorbing nets can be recommended as a component of an integrated disease management program to reduce secondary spread of lettuce viruses, although not as a control measure on its own. |
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0168-1702 |
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MA @ admin @ |
Serial |
4475 |
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Author |
Eza, U.; Shtiliyanova, A.; Borras, D.; Bellocchi, G.; Carrère, P.; Martin, R. |
Title |
An open platform to assess vulnerabilities to climate change: An application to agricultural systems |
Type |
Journal Article |
Year |
2015 |
Publication |
Ecological Informatics |
Abbreviated Journal |
Ecological Informatics |
Volume |
30 |
Issue |
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Pages |
389-396 |
Keywords |
climate change; grasslands; modeling platform; vulnerability assessment; pasture simulation-model; software component; solar-radiation; crop production; change impacts; adaptation; indicator; makers |
Abstract |
Numerous climate futures are now available from global climate models. Translation of climate data such as precipitation and temperatures into ecologically meaningful outputs for managers and planners is the next frontier. We describe a model-based open platform to assess vulnerabilities of agricultural systems to climate change on pixel-wise data. The platform includes a simulation modeling engine and is suited to work with NetCDF format of input and output files. In a case study covering a region (Auvergne) in the Massif Central of France, the platform is configured to characterize climate (occurrence of arid conditions in historical and projected climate records), soils and human management, and is then used to assess the vulnerability to climate change of grassland productivity (downscaled to a fine scale). We demonstrate how using climate time series, and process-based simulations vulnerabilities can be defined at fine spatial scales relevant to farmers and land managers, and can be incorporated into management frameworks. (C) 2015 Elsevier B.V. All rights reserved. |
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1574-9541 |
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CropM LiveM, ft_macsur |
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no |
Call Number |
MA @ admin @ |
Serial |
4708 |
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Author |
Sanna, M.; Bellocchi, G.; Fumagalli, M.; Acutis, M. |
Title |
A new method for analysing the interrelationship between performance indicators with an application to agrometeorological models |
Type |
Journal Article |
Year |
2015 |
Publication |
Environmental Modelling & Software |
Abbreviated Journal |
Env. Model. Softw. |
Volume |
73 |
Issue |
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Pages |
286-304 |
Keywords |
model evaluation; performance indicators; stable correlation; solar-radiation; simulation-model; environmental-models; statistical-methods; crop nitrogen; validation; rice; uncertainty; calibration; software |
Abstract |
The use of a variety of metrics is advocated to assess model performance but correlated metrics may convey the same information, thus leading to redundancy. Starting from this assumption, a method was developed for selecting, from among a collection of performance indicators, one or more subsets providing the same information as the entire set. The method, based on the definition of “stable correlation”, was applied to 23 performance indicators of agrometeorological models, calculated on large sets of simulated and observed data of four agronomic and meteorological variables: above-ground biomass, leaf area index, hourly air relative humidity and daily solar radiation. Two subsets were determined: {Squared Bias, Root Mean Squared Relative Error, Coefficient of Determination, Pattern Index, Modified Modelling Efficiency}, {Persistence Model Efficiency, Root Mean Squared Relative Error, Coefficient of Determination, Pattern Index}. The method needs corroboration but is statistically founded and can support the implementation of standardized evaluation tools. (C) 2015 Elsevier Ltd. All rights reserved. |
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1364-8152 |
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CropM LiveM, ftnotmacsur |
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Call Number |
MA @ admin @ |
Serial |
4503 |
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