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Author  |
Cassardo, C.; Andreoli, V. |
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Title |
On the Representativeness of UTOPIA Land Surface Model for Creating a Database of Surface Layer, Vegetation and Soil Variables in Piedmont Vineyards, Italy |
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Journal Article |
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Year |
2019 |
Publication |
Applied Sciences-Basel |
Abbreviated Journal |
Applied Sciences-Basel |
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Volume |
9 |
Issue |
18 |
Pages |
3880 |
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Keywords |
land-surface; UTOPIA; NOAH; GLDAS; micrometeorology; exchanges; processes; vineyards; cabernet-sauvignon; climate-change; wine color; temperature; parameterization; simulations; circulation; balances; moisture; sunlight |
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The main aim of the paper is to show how, and how many, simulations carried out using the Land Surface Model UTOPIA (University of TOrino model of land Process Interaction with Atmosphere) are representative of the micro-meteorological conditions and exchange processes at the atmosphere/biosphere interface, with a particular focus on heat and hydrologic transfers, over an area of the Piemonte (Piedmont) region, NW Italy, which is characterized by the presence of many vineyards. Another equally important aim is to understand how much the quality of the simulation outputs was influenced by the input data, whose measurements are often unavailable for long periods over country areas at an hourly basis. Three types of forcing data were used: observations from an experimental campaign carried out during the 2008, 2009, and 2010 vegetative seasons in three vineyards, and values extracted from the freely available Global Land Data Assimilation System (GLDAS, versions 2.0 and 2.1). Since GLDAS also contains the outputs of the simulations performed using the Land Surface Model NOAH, an additional intercomparison between the two models, UTOPIA and NOAH, both driven by the same GLDAS datasets, was performed. The intercomparisons were performed on the following micro-meteorological variables: net radiation, sensible and latent turbulent heat fluxes, and temperature and humidity of soil. The results of this study indicate that the methodology of employing land surface models driven by a gridded database to evaluate variables of micro-meteorological and agronomic interest in the absence of observations is suitable and gives satisfactory results, with uncertainties comparable to measurement errors, thus, allowing us to also evaluate some time trends. The comparison between GLDAS2.0 and GLDAS2.1 indicates that the latter generally produces simulation outputs more similar to the observations than the former, using both UTOPIA and NOAH models. |
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2020-02-14 |
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CropM, ft_macsur |
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MA @ admin @ |
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5228 |
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Author |
Cantelaube, P.; Jayet, P. |
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Title |
Geographical downscaling of outputs provided by an economic farm model calibrated at the regional level |
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Journal Article |
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Year |
2012 |
Publication |
Land Use Policy |
Abbreviated Journal |
Land Use Policy |
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Volume |
29 |
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Pages |
35-44 |
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Keywords |
Downscaling; Land use; Spatial statistics; Farm-groups; Farm Accountancy Data Network; FADN |
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There is a strong need for accurate and spatially referenced information regarding policy making and model linkage. This need has been expressed by land users, and policy and decision makers in order to estimate both spatially and locally the impacts of European policy (like the Common Agricultural Policy) and/or global changes on farm-groups. These entities are defined according to variables such as altitude, economic size and type of farming (referring to land uses). European farm-groups are provided through the Farm Accountancy Data Network (FADN) as statistical information delivered at regional level. The aim of the study is to map locally farm-group probabilities within each region. The mapping of the farm-groups is done in two steps: (1) by mapping locally the co-variables associated to the farm-groups, i.e. altitude and land uses; (2) by using regional FADN data as a priori knowledge for transforming land uses and altitude information into farm-groups location probabilities within each region. The downscaling process focuses on the land use mapping since land use data are originally point information located every 18 km. Interpolation of land use data is done at 100 m by using co-variables like land cover, altitude, climate and soil data which are continuous layers usually provided at fine resolution. Once the farm-groups are mapped, European Policy and global changes scenarios are run through an agro-economic model for assessing environmental impacts locally. |
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TradeM, ftnotmacsur |
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MA @ admin @ |
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4582 |
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Author |
Camacho, C.; Pérez-Barahona, A. |
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Title |
Land use dynamics and the environment |
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Journal Article |
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2015 |
Publication |
Journal of Economic Dynamics and Control |
Abbreviated Journal |
Journal of Economic Dynamics and Control |
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52 |
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96-118 |
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Keywords |
land use; spatial dynamics; pollution; climate-change; air-pollution; agriculture; instability; allocation; principle; pattern; quality; health; impact |
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This paper builds a benchmark framework to study optimal land use, encompassing land use activities and environmental degradation. We focus on the spatial externalities of land use as drivers of spatial patterns: land is immobile by nature, but local actions affect the whole space since pollution flows across locations resulting in both local and global damages. We prove that the decision maker problem has a solution, and characterize the corresponding social optimum trajectories by means of the Pontryagin conditions. We also show that the existence and uniqueness of time-invariant solutions are not in general guaranteed. Finally, a global dynamic algorithm is proposed in order to illustrate the spatial-dynamic richness of the model. We find that our simple set-up already reproduces a great variety of spatial patterns related to the interaction between land use activities and the environment. In particular, abatement technology turns out to play a central role as pollution stabilizer, allowing the economy to reach a time-invariant equilibrium that can be spatially heterogeneous. (C) 2014 Elsevier B.V. All rights reserved. |
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2015-10-09 |
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0165-1889 |
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TradeM, ft_macsur |
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MA @ admin @ |
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4698 |
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Author |
Bourgeois, C.; Fradj, N.B.; Jayet, P.-A. |
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Title |
How cost-effective is a mixed policy targeting the management of three agricultural N-pollutants |
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Journal Article |
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Year |
2014 |
Publication |
Environmental Modelling & Assessment |
Abbreviated Journal |
Environmental Modelling & Assessment |
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19 |
Issue |
5 |
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389-405 |
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cost-effectiveness; mixed policy; n-input tax; land use policy; nitrogen pollutants; bioeconomic model; mathematical linear programming; miscanthus; nonpoint pollution-control; reed canary grass; biomass production; abatement costs; energy crop; miscanthus; nitrogen; model; efficiencies; instruments |
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This paper assesses the cost-effectiveness of a mixed policy in attempts to reduce the presence of three nitrogen pollutants: NO (3), N O-2, and NH (3). The policy under study combines a tax on nitrogen input and incentives promoting perennial crops assumed to require low input. We show that the mixed policy improves the cost-effectiveness of regulation with regard to nitrates, whereas no improvement occurs, except for a very low level of subsidy in some cases, for gas pollutants. A quantitative analysis provides an assessment of impacts in terms of land use, farmers’ income, and nitrogen losses throughout France and at river-basin scale. |
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1420-2026 |
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TradeM |
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MA @ admin @ |
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4661 |
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Author |
Bennetzen, E.H.; Smith, P.; Soussana, J.-F.; Porter, J.R. |
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Title |
Identity-based estimation of greenhouse gas emissions from crop production: case study from Denmark |
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Journal Article |
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Year |
2012 |
Publication |
European Journal of Agronomy |
Abbreviated Journal |
European Journal of Agronomy |
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41 |
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66-72 |
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kaya identity; kaya-porter identity; crop production; greenhouse gas emission; energy intensity; mitigation; food system; agriculture; mitigation; energy; opportunities; inventory; europe; policy; land |
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In order to feed the world we need innovative thinking on how to increase agricultural production whilst also mitigating climate change. Agriculture and land-use change are responsible for approximately one-third of total anthropogenic greenhouse gas (GHG) emissions but hold potential for climate change mitigation but are only tangentially included in UNFCCC mitigation policies. To get a full estimate of GHG emissions from agricultural crop production both energy-based emissions and land-based emissions need to be accounted for. Furthermore, the major mitigation potential is likely to be indirect reduction of emissions i.e. reducing emissions per unit of agricultural product rather than the absolute emissions per se. Hence the system productivity must be included in the same analysis. This paper presents the Kaya-Porter identity, derived from the Maya identity, as a new way to calculate GHG emissions from agricultural crop production by deconstructing emissions into five elements; the GHG intensity of the energy used for production (kg CO2-eq./MJ), energy intensity of the production (MJ/kg dry matter), areal productivity (kg dry matter/ha), areal land-based GHG emissions (CO2-eq./ha) and area (ha). These separate elements in the identity can be targeted in emissions reduction and mitigation policies and are useful to analyse past and current trends in emissions and to explore future scenarios. Using the Kaya-Porter identity we have performed a case study on Danish crop production and find emissions to have been reduced by 12% from 1992 to 2008, whilst yields per unit area have remained constant. Both land-based emissions and energy-based emissions have decreased, mainly due to a 41% reduction in nitrogen fertilizer use. The initial identity based analysis for crop production presented here needs to be extended to include livestock to reflect the entire agricultural production and food demand sectors, thereby permitting analysis of the trade-offs between animal and plant food production, human dietary preferences and population and resulting GHG emissions. (C) 2012 Elsevier B.V. All rights reserved. |
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2016-07-22 |
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1161-0301 |
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CropM, ftnotmacsur |
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MA @ admin @ |
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4581 |
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