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See detailMonitoring surface water content using visible and short-wave infrared SPOT-5 data of wheat plots in irrigated semi-arid regions
Benabdelouahab, Tarik ULg; Balaghi, Riad; Hadria, Rachid et al

in International Journal of Remote Sensing (2015), 36(15), 4018-4036

Irrigated agriculture is an important strategic sector in arid and semi-arid regions. Given the large spatial coverage of irrigated areas, operational tools based on satellite remote sensing can ... [more ▼]

Irrigated agriculture is an important strategic sector in arid and semi-arid regions. Given the large spatial coverage of irrigated areas, operational tools based on satellite remote sensing can contribute to their optimal management. The aim of this study was to evaluate the potential of two spectral indices, calculated from SPOT-5 high-resolution visible (HRV) data, to retrieve the surface water content values (from bare soil to completely covered soil) over wheat fields and detect irrigation supplies in an irrigated area. These indices are the normalized difference water index (NDWI) and the moisture stress index (MSI), covering the main growth stages of wheat. These indices were compared to corresponding in situ measurements of soil moisture and vegetation water content in 30 wheat fields in an irrigated area of Morocco, during the 2012–2013 and 2013–2014 cropping seasons. NDWI and MSI were highly correlated with in situ measurements at both the beginning of the growing season (sowing) and at full vegetation cover (grain filling). From sowing to grain filling, the best correlation (R2 = 0.86; p < 0.01) was found for the relationship between NDWI values and observed soil moisture values. These results were validated using a k-fold cross-validation methodology; they indicated that NDWI can be used to estimate and map surface water content changes at the main crop growth stages (from sowing to grain filling). NDWI is an operative index for monitoring irrigation, such as detecting irrigation supplies and mitigating wheat water stress at field and regional levels in semi-arid areas. [less ▲]

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See detailLe réseau scientifique wallon Agriculture - changement climatique
Minet, Julien ULg

Scientific conference (2015, May 20)

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See detailModelling carbon fluxes of forest and grassland ecosystems in Western Europe using the CARAIB dynamic vegetation model: evaluation against eddy covariance data.
Henrot, Alexandra-Jane ULg; François, Louis ULg; Dury, Marie ULg et al

in Geophysical Research Abstracts (2015, April), 17

Eddy covariance measurements are an essential resource to understand how ecosystem carbon fluxes react in response to climate change, and to help to evaluate and validate the performance of land surface ... [more ▼]

Eddy covariance measurements are an essential resource to understand how ecosystem carbon fluxes react in response to climate change, and to help to evaluate and validate the performance of land surface and vegetation models at regional and global scale. In the framework of the MASC project (« Modelling and Assessing Surface Change impacts on Belgian and Western European climate »), vegetation dynamics and carbon fluxes of forest and grassland ecosystems simulated by the CARAIB dynamic vegetation model (Dury et al., iForest - Biogeosciences and Forestry, 4:82-99, 2011) are evaluated and validated by comparison of the model predictions with eddy covariance data. Here carbon fluxes (e.g. net ecosystem exchange (NEE), gross primary productivity (GPP), and ecosystem respiration (RECO)) and evapotranspiration (ET) simulated with the CARAIB model are compared with the fluxes measured at several eddy covariance flux tower sites in Belgium and Western Europe, chosen from the FLUXNET global network (http://fluxnet.ornl.gov/). CARAIB is forced either with surface atmospheric variables derived from the global CRU climatology, or with in situ meteorological data. Several tree (e.g. Pinus sylvestris, Fagus sylvatica, Picea abies) and grass species (e.g. Poaceae, Asteraceae) are simulated, depending on the species encountered on the studied sites. The aim of our work is to assess the model ability to reproduce the daily, seasonal and interannual variablility of carbon fluxes and the carbon dynamics of forest and grassland ecosystems in Belgium and Western Europe. [less ▲]

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See detailunité: Eau-Environnement-Développement (ULg Campus Arlon): la télédétection au service de l'agriculture
Wellens, Joost ULg; Lang, Marie ULg; Benabdelouahab, Tarik et al

Diverse speeche and writing (2015)

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See detailRumination time, milk yield, milking frequency of grazing dairy cows milked by a mobile automatic system during mild heat stress
Lessire, Françoise ULg; Hornick, Jean-Luc ULg; Minet, Julien ULg et al

in Advances in Animal Biosciences (2015), 6(01), 12-14

Grazing dairy cows milked by an automatic system (AS) experienced mild heat stress (HS) periods, twice during the summer. The daily temperature humidity index (THI) during these periods were higher than ... [more ▼]

Grazing dairy cows milked by an automatic system (AS) experienced mild heat stress (HS) periods, twice during the summer. The daily temperature humidity index (THI) during these periods were higher than 72. Milk production, as well as milking frequency, rumination time and milk fat to protein ratio (F/P) during these periods were compared to adjacent periods with mean THI of 61. The daily milking frequency, the total number of visits to AS and the milk production were significantly higher in HS periods (2.12 vs 1.97, 2.99 vs 2.69, and 19.7 vs 18.5 kg milk per cow, respectively). There were significant interactions between times and periods for milking frequency and number of visits, while the daily rumination time was significantly lower (339 vs 419 min) and the F/P in milk tended to be decreased (1.17 vs 1.23). These results could be explained by changes in cow behaviour during HS periods. [less ▲]

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See detailWheat yield sensitivity to climate change across a European transect for a large ensemble of crop models
Pirttioja, N.; Carter, Timothy; Fronzek, S. et al

in Soussana, Jean-Francois (Ed.) Proceedings of the Climate Smart Agriculture 2015 conference (2015, March)

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See detailLIVESTOCK SYSTEMS--TECHNICAL REPORT
Minet, Julien ULg; Diouf, Abdoul Aziz; Garba, Issa et al

Report (2015)

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See detailUncertainty in simulating biomass yield and carbon-water fluxes from grasslands under climate change
Sándor, Renata; Ma, Shaoxiu; Acutis, Marco et al

in Advances in Animal Biosciences (2015), 6(01), 49--51

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See detailSensitivity analysis for climate change impacts, adaptation and mitigation projection with pasture models
Bellocchi, G.; Ehrhardt, F.; Soussana, J. F. et al

in Climate-Smart Agriculture 2015 (2015)

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See detailBayesian inversions of a dynamic vegetation model at four European grassland sites
Minet, Julien ULg; Laloy, Eric; Tychon, Bernard ULg et al

in Biogeosciences (2015), 12(9), 2809--2829

Eddy covariance data from four European grassland sites are used to probabilistically invert the CARAIB (CARbon Assimilation In the Biosphere) dynamic vegetation model (DVM) with 10 unknown parameters ... [more ▼]

Eddy covariance data from four European grassland sites are used to probabilistically invert the CARAIB (CARbon Assimilation In the Biosphere) dynamic vegetation model (DVM) with 10 unknown parameters, using the DREAM(ZS) (DiffeRential Evolution Adaptive Metropolis) Markov chain Monte Carlo (MCMC) sampler. We focus on comparing model inversions, considering both homoscedastic and heteroscedastic eddy covariance residual errors, with variances either fixed a priori or jointly inferred together with the model parameters. Agreements between measured and simulated data during calibration are comparable with previous studies, with root mean square errors (RMSEs) of simulated daily gross primary productivity (GPP), ecosystem respiration (RECO) and evapotranspiration (ET) ranging from 1.73 to 2.19, 1.04 to 1.56 g C m−2 day−1 and 0.50 to 1.28 mm day−1, respectively. For the calibration period, using a homoscedastic eddy covariance residual error model resulted in a better agreement between measured and modelled data than using a heteroscedastic residual error model. However, a model validation experiment showed that CARAIB models calibrated considering heteroscedastic residual errors perform better. Posterior parameter distributions derived from using a heteroscedastic model of the residuals thus appear to be more robust. This is the case even though the classical linear heteroscedastic error model assumed herein did not fully remove heteroscedasticity of the GPP residuals. Despite the fact that the calibrated model is generally capable of fitting the data within measurement errors, systematic bias in the model simulations are observed. These are likely due to model inadequacies such as shortcomings in the photosynthesis modelling. Besides the residual error treatment, differences between model parameter posterior distributions among the four grassland sites are also investigated. It is shown that the marginal distributions of the specific leaf area and characteristic mortality time parameters can be explained by site-specific ecophysiological characteristics. [less ▲]

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See detailUncertainty in simulating biomass yield and carbon-water fluxes from Euro-Mediterranean grasslands under climate changes
Sandor, R; Ma, S; Acutis, M et al

Conference (2014, October 15)

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See detailOutcomes from the MACSUR grassland model inter-comparison with the model CARAIB
Minet, Julien ULg; Laloy, Eric; Tychon, Bernard ULg et al

Conference (2014, October 15)

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See detailThe grassland model intercomparison of the MACSUR (Modelling European Agriculture with Climate Change for Food Security) European knowledge hub
Ma, Shaoxiu; Acutis, Marco; Barcza, Zoltan et al

in Proceedings of the 7th International Congress on Environmental Modelling and Software (iEMSs) June 15-19, 2014, San Diego, California, USA (2014, June)

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See detailBayesian inference of a dynamic vegetation model for grassland
Minet, Julien ULg; Laloy, Eric; Tychon, Bernard ULg et al

Conference (2014, April 02)

As a part of the MACSUR task L2.4, we probabilistically calibrated the CARAIB dynamic vegetation model by Markov chain Monte Carlo (MCMC) simulation with the DREAMZS sampler.. CARAIB is a mechanistic ... [more ▼]

As a part of the MACSUR task L2.4, we probabilistically calibrated the CARAIB dynamic vegetation model by Markov chain Monte Carlo (MCMC) simulation with the DREAMZS sampler.. CARAIB is a mechanistic model that calculates the carbon assimilation of the vegetation as a function of the soil and climatic conditions, and can thus be used for simulating grassland production under cutting or grazing management. Bayesian model inversion was performed at 4 grassland sites across Europe: Oensingen, CH; Grillenburg, DE; Laqueuille, FR and Monte-Bodone, IT. Four daily measured variables from these sites: the Gross Primary Productivity (GPP), Net Ecosystem Exchange (NEE), Evapotranspiration (ET) and Soil Water Content (SWC) were used to sample 10 parameters related to rooting depth, stomatal conductance, specific leaf area, carbon-nitrogen ratio and water stresses. The maximized likelihood function therefore involved four objectives, whereas the applied Bayesian framework allowed for assessing the so called parameter posterior probability density function (pdf), which quantifies model parameter uncertainty caused by measurement and model errors. Sampling trials were performed using merged data from all sites (all-sites-sampling) and for each site (site-specific sampling) separately. The derived posterior parameter pdfs from the all-sites sampling and site-specific sampling runs showed differences in relation with the specificities of each site. Analysis of these distributions also revealed model sensitivity to parameters conditioned on the measured data, as well as parameter correlations. [less ▲]

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See detailExamining wheat yield sensitivity to temperature and precipitation changes for a large ensemble of crop models using impact response surfaces"
Pirttioja, N.; Fronzek, S.; Bindi, Marco et al

in Rotter, Reimund; Ewert, Frank (Eds.) Modelling climate change impacts on crop production for food security - Abstract book (2014, February)

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See detailCan a global dynamic vegetation model be used for both grassland and crop modeling at the local scale?
Minet, Julien ULg; Tychon, Bernard ULg; Jacquemin, Ingrid ULg et al

Poster (2014, February)

We report on the use of a dynamic vegetation model, CARAIB, within two modeling exercises in the framework of MACSUR. CARAIB is a physically-based, mechanistic model that calculates the carbon ... [more ▼]

We report on the use of a dynamic vegetation model, CARAIB, within two modeling exercises in the framework of MACSUR. CARAIB is a physically-based, mechanistic model that calculates the carbon assimilation of the vegetation as a function of the soil and climatic conditions. Within MACSUR, it was used in the model intercomparison exercises for grassland and crop modeling, in the LiveM 2.4 and CropM WP4 tasks, respectively. For grassland modeling, blind model runs at 11 locations were performed for various time ranges (few years). For crop modeling, a sensitivity analysis for building impact response surfaces (IRS) was performed, based on a bench of model runs at different levels of perturbation in the temperature and precipitation input data over 30 years. For grassland modeling, specific management functions accounting for the cutting or grazing of the grass were added to the model, in the framework of the MACSUR intercomparison. Initially developed for modeling the carbon dynamics of the natural vegetation, CARAIB was already adapted for crop modeling but further modifications regarding the management, i.e., yearly-dependent sowing dates, were introduced. For grassland modeling, simulation results will be further intercompared with other modeling groups, but preliminary results showed that the model could cope with the introduction of the grass cutting module. For crop modeling, building the IRS over 30 years permitted to assess the sensitivity of the model to temperature and precipitation changes. So far, the participation of CARAIB in the intercomparison exercises within MACSUR resulted in further improvements of the model by introducing new functionalities. [less ▲]

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See detailImplementing agricultural land-use in the CARAIB dynamic vegetation model
François, Louis ULg; Jacquemin, Ingrid ULg; Fontaine, Corentin et al

Conference (2014)

CARAIB (Dury et al., iForest - Biogeosciences and Forestry, 4:82-99, 2011) is a state-of-the-art dynamic vegetation model with various modules dealing with (i) soil hydrology, (ii) photosynthesis/stomatal ... [more ▼]

CARAIB (Dury et al., iForest - Biogeosciences and Forestry, 4:82-99, 2011) is a state-of-the-art dynamic vegetation model with various modules dealing with (i) soil hydrology, (ii) photosynthesis/stomatal regulation, (iii) carbon allocation and biomass growth, (iv) litter/soil carbon dynamics, (v) vegetation cover dynamics, (vi) seed dispersal, and (vii) vegetation fires. Climate and atmospheric CO2 are the primary inputs. The model calculates all major water and CO2/carbon fluxes and pools. It can be run with plant functional types or species (up to 100 different species) at various spatial scales, from the municipality to country or continental levels. Within the VOTES project (Fontaine et al., Journal of Land Use Science, 2013, DOI:10.1080/1747423X.2013.786150), the model has been improved to include crops and meadows, and some modules have been written to translate model outputs into quantitative indicators of ecosystem services (e.g., evaluate crop yield from net primary productivity or calculate soil erosion from runoff, slope, grown species and various soil attributes). The model was run over an area covering four municipalities in central Belgium, where land-use is dominated by crops, meadows, housing and some forests and was introduced in the model at the land parcel level. Simulations were also performed for the future. In these simulations, CARAIB was combined with the Aporia Agent-Based Model, to project land-use changes up to 2050. This approach is currently extended within the MASC project (funded by Belgian Science Policy, BELSPO) to the whole Belgian territory (at 1 km2) and to Western Europe (at 20 km x 20 km). [less ▲]

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