References of "Minet, Julien"
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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 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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See detailCARAIB USER'S GUIDE
Minet, Julien ULg; Jacquemin, Ingrid ULg; François, Louis ULg

Learning material (2013)

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See detailCommunity gardening in Wallonia and Brussels : proposals for research and actions
Minet, Julien ULg; Stevenne, Kari; Loicq, Gaël et al

Scientific conference (2013, May 23)

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See detailValidation of ground penetrating radar full-waveform inversion for field scale soil moisture mapping
Minet, Julien ULg; Bogaert, P.; Vanclooster, M. et al

in Journal of Hydrology (2012), 424-425

Ground penetrating radar (GPR) is an efficient method for soil moisture mapping at the field scale, bridging the scale gap between small-scale invasive sensors and large-scale remote sensing instruments ... [more ▼]

Ground penetrating radar (GPR) is an efficient method for soil moisture mapping at the field scale, bridging the scale gap between small-scale invasive sensors and large-scale remote sensing instruments. Nevertheless, commonly-used GPR approaches for soil moisture characterization suffer from several limitations and the determination of the uncertainties in GPR soil moisture sensing has been poorly addressed. Herein, we used an advanced proximal GPR method based on full-waveform inversion of ultra-wideband radar data for mapping soil moisture and uncertainties in the soil moisture maps were evaluated by three different methods. First, GPR-derived soil moisture uncertainties were computed from the GPR data inversion, according to measurements and modeling errors and to the sensitivity of the electromagnetic model to soil moisture. Second, the reproducibility of the soil moisture mapping was evaluated. Third, GPR-derived soil moisture was compared with ground-truth measurements (soil core sampling). The proposed GPR method appeared to be highly precise and accurate, with spatially averaged GPR inversion uncertainty of 0.0039 m3m-3, a repetition uncertainty of 0.0169 m3m-3 and an uncertainty of 0.0233 m3m-3 when compared with ground-truth measurements. These uncertainties were mapped and appeared to be related to some local model inadequacies and to small-scale variability of soil moisture. In a soil moisture mapping framework, the interpolation was found to be the determinant source of the observed uncertainties. The proposed GPR method was proven to be largely reliable in terms of accuracy and precision and appeared to be highly efficient for soil moisture mapping at the field scale. [less ▲]

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See detailIntegrating coarse-scale uncertain soil moisture data into a fine-scale hydrological modelling scenario
Vernieuwe, H.; De Baets, B.; Minet, Julien ULg et al

in Hydrology & Earth System Sciences (2011), 15

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See detailReconstruction of sub-wavelength fractures and physical properties of masonry media using full-waveform inversion of proximal penetrating radar
Patriarca, C.; Lambot, S.; Mahmoudzadeh, M. R. et al

in Journal of Applied Geophysics (2011), 74(1)

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See detailEffect of high-resolution spatial soil moisture variability on simulated runoff response using a distributed hydrologic model
Minet, Julien ULg; Laloy, E.; Lambot, S. et al

in Hydrology & Earth System Sciences (2011), 15

The importance of the spatial variability of antecedent soil moisture conditions on runoff response is widely acknowledged in hillslope hydrology. Using a distributed hydrologic model, this paper aims at ... [more ▼]

The importance of the spatial variability of antecedent soil moisture conditions on runoff response is widely acknowledged in hillslope hydrology. Using a distributed hydrologic model, this paper aims at investigating the effects of soil moisture spatial variability on runoff in various field conditions and at finding the structure of the soil moisture pattern that approaches the measured soil moisture pattern in terms of field scale runoff. High spatial resolution soil moisture was surveyed in ten different field campaigns using a proximal ground penetrating radar (GPR) mounted on a mobile platform. Based on these soil moisture measurements, seven scenarios of spatial structures of antecedent soil moisture were used and linked with a field scale distributed hydrological model to simulate field scale runoff. Accounting for spatial variability of soil moisture resulted in higher predicted field scale runoff as compared to the case where soil moisture was kept constant. The ranges of possible hydrographs were delineated by the extreme scenarios where soil moisture was directly and inversely modelled according to the topographic wetness index (TWI). These behaviours could be explained by the sizes and relative locations of runoff contributing areas, knowing that runoff was generated by infiltration excess over a certain soil moisture threshold. The most efficient scenario for modeling the within field spatial structure of soil moisture appeared to be when soil moisture is directly arranged according to the TWI, especially when measured soil moisture and TWI were correlated. The novelty of this work is to benefit from a large set of high-resolution soil moisture measurements allowing to model effectively the within field distribution of soil moisture and its impact on the field scale hydrograph. These observations contributed to the current knowledge of the impact of antecedent soil moisture spatial variability on the field scale runoff. [less ▲]

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See detailMapping shallow soil moisture profiles at the field scale using full-waveform inversion of ground penetrating radar data
Minet, Julien ULg; Wahyudi, A.; Bogaert, P. et al

in Geoderma (2011), 161

Full-waveform inversions were applied to retrieve surface, two-layered and continuous soil moisture profiles from ground penetrating radar (GPR) data acquired in an 11-ha agricultural field situated in ... [more ▼]

Full-waveform inversions were applied to retrieve surface, two-layered and continuous soil moisture profiles from ground penetrating radar (GPR) data acquired in an 11-ha agricultural field situated in the loess belt area in central Belgium. The radar system consisted of a vector network analyzer combined with an off-ground horn antenna operating in the frequency range 200–2000 MHz. The GPR system was computer controlled and synchronized with a differential GPS for real-time data acquisition. Several inversion strategies were also tested using numerical experiments, which in particular demonstrated the potentiality to reconstruct simplified two-layered configurations from more complex, continuous dielectric profiles as prevalent in the environment. The surface soil moisture map obtained assuming a one-layered model showed a global moisture pattern mainly explained by the topography while local moisture patterns indicated a line effect. Two-layered and profile inversions provided consistent estimates with respect to each other and field observations, showing significant moisture increases with depth. However, some discrepancies were ob- served between the measured and modeled GPR data in the higher frequency ranges, mainly due to surface roughness effects which were not accounted for. The proposed GPR method and inversion strategies showed great promise for high-resolution, real-time mapping of soil moisture at the field scale. [less ▲]

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See detailSpatial fields' dispersion as a farmer strategy to reduce agro-climatic risk at the household level in pearl millet-based systems in the Sahel: A modeling perspective
Akponikpe, Pierre B. I.; Minet, Julien ULg; Gerard, Bruno et al

in Agricultural and Forest Meteorology (2011), 151(2), 215-227

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See detailSoil surface water content estimation by full-waveform GPR signal inversion in the presence of thin layers
Minet, Julien ULg; Lambot, Sébastien; Slob, Evert C. et al

in IEEE Transactions on Geoscience and Remote Sensing (2010), 48

We analyzed the effect of shallow thin layers on the estimation of soil surface water content using full-waveform inversion of off-ground ground penetrating radar (GPR) data. Strong dielectric contrasts ... [more ▼]

We analyzed the effect of shallow thin layers on the estimation of soil surface water content using full-waveform inversion of off-ground ground penetrating radar (GPR) data. Strong dielectric contrasts are expected to occur under fast wetting or drying weather conditions, thereby leading to constructive and destructive interferences with respect to the surface reflection. First, synthetic GPR data were generated and subsequently inverted considering different thin-layer model configurations. The resulting inversion errors when neglecting the thin layer were quantified, and then, the possibility to reconstruct these layers was investigated. Second, laboratory experiments reproducing some of the numerical experiments configurations were conducted to assess the stability of the inverse solution with respect to actual measurement and modeling errors. Results showed that neglecting shallow thin layers may lead to significant errors on the estimation of soil surface water content ($\Delta\theta$ > 0.03 $m^3/m^3$), depending on the contrast. Accounting for these layers in the inversion process strongly improved the results, although some optimization issues were encountered. In the laboratory, the proposed full-waveform method permitted to reconstruct thin layers with a high resolution up to 2 cm and to retrieve the soil surface water content with an rmse less than 0.02 $m^3/m^3$, owing to the full-waveform inverse modeling. These results suggest that the proposed GPR approach is promising for field-scale mapping of soil surface water content of nondispersive soils with low electrical conductivity and for instances when soil layering is encountered. [less ▲]

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See detailA generalized frequency domain reflectometry forward and inverse modeling technique for soil electrical properties determination
Minet, Julien ULg; Lambot, Sébastien; Delaide, Géraldine et al

in Vadose Zone Journal (2010), 9(4)

We have developed a generalized frequency domain reflectometry (FDR) technique for soil characterization that is based on an electromagnetic model decoupling the cable and probe head from the ground using ... [more ▼]

We have developed a generalized frequency domain reflectometry (FDR) technique for soil characterization that is based on an electromagnetic model decoupling the cable and probe head from the ground using frequency-dependent reflection and transmission transfer functions. The FDR model represents an exact solution of Maxwell’s equations for wave propagation in one-dimensional multilayered media. The benefit of the decoupling is that the FDR probe can be fully described by its characteristic transfer functions, which are determined using only a few measurements. The soil properties are retrieved after removing the probe effects from the raw FDR data by iteratively inverting a global reflection coefficient. The proposed method was validated under laboratory conditions for measurements in water with different salt concentrations and sand with different water contents. For the salt water, inversions of the data led to dielectric permittivity and electrical conductivity values very close to the expected theoretical or measured values. In the frequency range for which the probe is efficient, a good agreement was obtained between measured, inverted and theoretically predicted signals. For the sand, results were consistent with the different water contents and also in close agreement with traditional time domain reflectometry measurements. The proposed method offers great promise for accurate soil electrical characterization because it inherently permits maximization of the information that can be retrieved from the FDR data and shows a high practicability. [less ▲]

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