Julien Minet

University of Liège | ulg · Department of Environmental Sciences and Management

Abstract Crowdsourcing, understood as outsourcing tasks or data collection by a large group of non-professionals, is increasingly used in scientific research and operational applications. In this paper, we reviewed crowdsourcing initiatives in agricultural science and farming activities and further discussed the particular characteristics of this a...

Grassland models often yield more uncertain outputs than arable crop models due to more complex interactions and the largely undocumented sensitivity of grassland models to environmental factors. The aim of the present study was to assess the impact of single-factor changes in temperature, precipitation, and atmospheric [CO 2 ] on simulated soil wa...

Climate change is expected to severely affect cropping systems and food production in many parts of the world unless local adaptation can ameliorate these impacts. Ensembles of crop simulation models can be useful tools for assessing if proposed adaptation options are capable of achieving target yields, whilst also quantifying the share of uncertai...

This work was financially supported by the Spanish National Institute for Agricultural and Food Research and Technology (INIA, MACSUR01-UPM), the Italian Ministry of Agriculture and Forestry and the Finnish Ministry of Agriculture and Forestry (D.M. 24064/7303/15) through FACCE MACSUR − Modelling European Agriculture with Climate Change for Food Se...

Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models applied at sites across a European transect to compare their sensitivity to changes in temperature (-2 to +9°C) and precipitation (-50 to +50%). Mode...

Grassland-based ruminant production systems are integral to sustainable food production in Europe, converting plant materials indigestible to humans into nutritious food, while providing a range of environmental and cultural benefits. Climate change poses significant challenges for such systems, their productivity and the wider benefits they supply...

This study presents results from a major grassland model intercomparison exercise, and highlights the main challenges faced in the implementation of a multi-model ensemble prediction system in grasslands. Nine, independently developed simulation models linking climate, soil, vegetation and management to grassland biogeochemical cycles and productio...

The interactions between land surface and climate are complex. Climate changes can affect ecosystem structure and functions, by altering photosynthesis and productivity or inducing thermal and hydric stresses on plant species. These changes then impact socio-economic systems, through e.g., lower farming or forestry incomes. Ultimately, it can lead...

Introduction A wide variety of dynamic crop growth simulation models have been developed over the past few decades that can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, multi-model ensemble approaches have been adopted to quantify aspects of uncertainty in simulating yield respons...

Renewed interest in heat stress effects on livestock productivity derives from climate change, which is expected to increase temperatures and the frequency of extreme weather events. This study aimed at evaluating the effect of temperature and humidity on milk production in highly selected dairy cattle populations across 3 European regions differin...

This study explored the utility of the impact response surface (IRS) approach for investigating model ensemble crop yield responses under a large range of changes in climate. IRSs of spring and winter wheat Triticum aestivum yields were constructed from a 26-member ensemble of process-based crop simulation models for sites in Finland, Germany and S...

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...

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, co...

FACCE MACSUR Reports 2, 5, SP5-46

The development of climate adaptation services requires an improved accuracy in model projections for climate change impacts on pastures. Moreover, changes in grassland management need to be tested in terms of their adaptation and mitigation potential. Within AgMIP (Agricultural Model Intercomparison and Improvement Project), based on the C3MP prot...

Uncertainty in simulating biomass yield and carbon–water fluxes from grasslands under climate change - Volume 6 Issue 1 - R. Sándor, S. Ma, M. Acutis, Z. Barcza, H. Ben Touhami, L. Doro, D. Hidy, M. Köchy, E. Lellei-Kovács, J. Minet, A. Perego, S. Rolinski, F. Ruget, G. Seddaiu, L. Wu, G. Bellocchi

Rumination time, milk yield, milking frequency of grazing dairy cows milked by a mobile automatic system during mild heat stress - Volume 6 Issue 1 - F. Lessire, J. L. Hornick, J. Minet, I. Dufrasne

Eddy covariance data from four European grassland sites are used to probabilistically invert the CARAIB dynamic vegetation model (DVM) with ten unknown parameters, using the DREAM(ZS) Markov chain Monte Carlo (MCMC) sampler. We compare model inversions considering both homoscedastic and heteroscedastic eddy covariance residual errors, with variance...

The grassland model intercomparison of the FACCE MACSUR knowledge hub involves nine modelling approaches. Grassland-specific approaches (AnnuGrow, PaSim, SPACSYS) were compared to the approaches mainly conceived to simulate crops (ARMOSA, EPIC, STICS) and biomes (Biome-BGC MuSo, CARAIB, LPJmL). The model intercomparison exercise is run over nine gr...

Impact response surfaces (IRSs) depict the response of an impact variable to changes in two explanatory variables as a plotted surface. Here, IRSs of spring and winter wheat yields were constructed from a 25-member ensemble of process-based crop simulation models. Twenty-one models were calibrated by different groups using a common set of calibrati...

Tillage practices influence physical, chemical, and biological soil properties, which also affect soil quality and consequently plant growth. In this study, the main objective was to evaluate the effects of different tillage practices on soil physical properties such as soil water content (SWC) by using geophysical methods, namely, ground-penetrati...

We analyzed the temporal stability of soil moisture patterns acquired using a proximal ground-penetrating radar (GPR) in a 2.5 ha agricultural field at five different dates over three weeks. The GPR system was mounted on a mobile platform, allowing for real-time mapping of soil moisture with a high spatial resolution (2-5 m). The spatio-temporal so...

Knowledge of temporal surface soil moisture variability is an useful key in agriculture, surface hydrology and meteorology. In that respect, ground-penetrating radar (GPR) is a non-invasive and promising tool for high-resolution and large scale characterization. In the case of quantitative analysis, off-ground GPR signal modeling and full-waveform...

Knowledge of temporal surface soil moisture variability is an useful key in agriculture, surface hydrology and meteorology. In that respect, ground-penetrating radar (GPR) is a non-invasive and promising tool for high resolution and large scale characterization. In the case of quantitative analysis, off-ground GPR signal modeling and full-waveform...

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 uncerta...

In a hydrological modelling scenario, often the modeller is confronted with external data, such as remotely-sensed soil moisture observations, that become available to update the model output. However, the scale triplet (spacing, extent and support) of these data is often inconsistent with that of the model. Furthermore, the external data 5 can be...

In a hydrological modelling scenario, often the modeller is confronted with external data, such as remotely-sensed soil moisture observations, that become available to update the model output. However, the scale triplet (spacing, extent and support) of these data is often inconsistent with that of the model. Furthermore, the external data can be cu...

High-frequency, ultra-wideband penetrating radar has the potential to be used as a non-invasive inspection technique for buildings, providing high-resolution images of structures and possible fractures affecting constructions. To test this possibility, numerical and laboratory experiments have been conducted using a proximal, stepped-frequency cont...

The importance of 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...

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 i...

The rainfall pattern in the Sahel is very erratic with a high spatial variability. We tested the often reported hypothesis that the dispersion of farmers’ fields around the village territory helps mitigate agro-climatic risk by increasing yield stability from year to year. We also wished to evaluate whether this strategy had an effect on the yield...

The importance of the spatial variability of the antecedent soil moisture conditions on the 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 the runoff in various field conditions and at finding the soil moisture...

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 pr...

Full-waveform inversion of proximal ground penetrating radar (GPR) data is used to determine the electromagnetic properties of layered media. The radar system consists of a vector network analyzer combined with an off-ground horn antenna operating at ultra wideband. The GPR wave propagation is modeled for a multilayered medium using a recursive Gre...

We present a new technique for real-time, proximal sensing of the soil hydrogeophysical properties using ground-penetrating radar (GPR). The radar system is based on international standard vector network analyser technology, thereby setting up stepped-frequency continuous-wave GPR. The radar is combined with an off-ground, ultra-wideband, and highl...

Characterizing the spatial and temporal variability of soil moisture using geophysical methods is an important issue in many hydrological researches and applications. In order to bridge the scale gap between large-scale remote sensing of soil moisture and small-scale invasive methods, we developed a proximal ground penetrating radar (GPR) technique...

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 t...

Measuring soil surface water content spatial variability is essential for many environmental and agricultural researches and engineering applications, as this variable controls important key processes of the hydrological cycle such as infiltration, runoff, evaporation, and energy exchanges between the earth and the atmosphere. In particular, the ch...

Sustainable and optimal agricultural and environmental management of water and land resources particularly relies on the description and understanding of soil water distribution and dynamics at different scales. We present an advanced ground penetrating radar (GPR) method for mapping the shallow soil water content and unsaturated hydraulic properti...

Measuring soil surface water content is essential in hydrology and agriculture as this variable controls important key processes of the hydrological cycle such as infiltration, runoff, evaporation, and energy exchanges between the earth and the atmosphere. We present a ground-penetrating radar (GPR) method for automated, high-resolution, real-time...