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Bellocchi, G., Rivington, M., & Acutis, M. (2014). Protocol for model evaluation (Vol. 3).
Abstract: This deliverable focuses on the development of methods for model evaluation in order to have unambiguous indications derived from the use of several evaluation metrics. The information about model quality is aggregated into a single indicator using a fuzzy expert system that can be applied to a wide range of model estimates where suitable test data are available. This is a cross-cutting activity between CropM (C1.4) and LiveM (L2.2). No Label
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Robinson, S., van Meijl, H., Willenbockel, D., Valin, H., Fujimori, S., Masui, T., et al. (2014). Comparing supply-side specifications in models of global agriculture and the food system. Agric. Econ., 45(1), 21–35.
Abstract: This article compares the theoretical and functional specification of production in partial equilibrium (PE) and computable general equilibrium (CGE) models of the global agricultural and food system included in the AgMIP model comparison study. The two model families differ in their scopepartial versus economy-wideand in how they represent technology and the behavior of supply and demand in markets. The CGE models are deep structural models in that they explicitly solve the maximization problem of consumers and producers, assuming utility maximization and profit maximization with production/cost functions that include all factor inputs. The PE models divide into two groups on the supply side: (1) shallow structural models, which essentially specify area/yield supply functions with no explicit maximization behavior, and (2) deep structural models that provide a detailed activity-analysis specification of technology and explicit optimizing behavior by producers. While the models vary in their specifications of technology, both within and between the PE and CGE families, we consider two stylized theoretical models to compare the behavior of crop yields and supply functions in CGE models with their behavior in shallow structural PE models. We find that the theoretical responsiveness of supply to changes in prices can be similar, depending on parameter choices that define the behavior of implicit supply functions over the domain of applicability defined by the common scenarios used in the AgMIP comparisons. In practice, however, the applied models are more complex and differ in their empirical sensitivity to variations in specificationcomparability of results given parameter choices is an empirical question. To illustrate the issues, sensitivity analysis is done with one global CGE model, MAGNET, to indicate how the results vary with different specification of technical change, and how they compare with the results from PE models.
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Witkowska-Walczak, B., Sławiński, C., Bartmiński, P., Melke, J., & Cymerman, J. (2014). Water conductivity of arctic zone soils (Spitsbergen). International Agrophysics, 28(4), 529–535.
Abstract: The water conductivity of arctic zone soils derived in different micro-relief forms was determined. The greatest water conductivity at the 0-5 cm depth for the higher values of water potentials (> -7 kJ m(-3)) was shown by tundra polygons (Brunic-Turbic Cryosol, Arenic) – 904-0.09 cm day(-1), whereas the lowest were exhibited by Turbic Cryosols – 95-0.05 cm day(-1). Between -16 and -100 kJ m(-3), the water conductivity for tundra polygons rapidly decreased to 0.0001 cm day(-1), whereas their decrease for the other forms was much lower and in consequence the values were 0.007, 0.04, and 0.01 cm day(-1) for the mud boils (Turbic Cryosol (Siltic, Skeletic)), cell forms (Turbic Cryosol (Siltic, Skeletic)), and sorted circles (Turbic Cryosol (Skeletic)), respectively. In the 10-15 cm layer, the shape of water conductivity curves for the higher values of water potentials is nearly the same as for the upper layer. Similarly, the water conductivity is the highest -0.2 cm day(-1) for tundra polygons. For the lower water potentials, the differences in water conductivity increase to the decrease of soil water potential. At the lowest potential the water conductivity is the highest for sorted circles -0.02 cm day(-1) and the lowest in tundra polygons -0.00002 cm day(-1).
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Rusu, T. (2014). Impact of Climate Change on Crop Land and Technological Recommendations for the Main Crops in Transylvanian Plain, Romania (Vol. 3).
Abstract: The Transylvanian Plain (TP) is an important agricultural production area of Romania that is included among the areas with the lowest potential of adapting to climate changes in Europe. Thermal and hydric regime monitoring is necessary to identify and implement measures of adaptation to the impacts of climate change. Soil moisture and temperature regimes were evaluated using a set of 20 data logging stations positioned throughout the plain. Each station stores electronic data regarding ground temperature at 3 depths (10, 30, 50 cm), humidity at a depth of 10 cm, air temperature (at 1 m) and precipitation. For agricultural crops, the periods of drought and extreme temperatures require specific measures of adaptation to climate changes. During the growing season of crops in the spring (April – October) in the southeastern, southern, and eastern escarpments, precipitation decreased by 43.8 mm, the air temperature increased by 0.37°C, and the ground temperature increased by 1.91°C at a depth of 10 cm, 2.22°C at a depth of 20 cm and 2.43°C at a depth of 30 cm compared with values recorded for the northern, northwestern or western escarpments. Water requirements were ensured within an optimal time frame for 58.8-62.1% of the spring row crop growth period, with irrigation being necessary to guarantee the optimum production potential. The biologically active temperature recorded in the TP demonstrates the need to renew the division of the crop areas reported in the literature. No Label
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Rusu, T. (2014). Impact of Climate Change on Crop Land and Technological Recommendations for the Main Crops in Transylvanian Plain, Romania. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: The Transylvanian Plain (TP) is an important agricultural production area of Romania that is included among the areas with the lowest potential of adapting to climate changes in Europe. Thermal and hydric regime monitoring is necessary to identify and implement measures of adaptation to the impacts of climate change. Soil moisture and temperature regimes were evaluated using a set of 20 data logging stations positioned throughout the plain. Each station stores electronic data regarding ground temperature at 3 depths (10, 30, 50 cm), humidity at a depth of 10 cm, air temperature (at 1 m) and precipitation. For agricultural crops, the periods of drought and extreme temperatures require specific measures of adaptation to climate changes. During the growing season of crops in the spring (April – October) in the southeastern, southern, and eastern escarpments, precipitation decreased by 43.8 mm, the air temperature increased by 0.37°C, and the ground temperature increased by 1.91°C at a depth of 10 cm, 2.22°C at a depth of 20 cm and 2.43°C at a depth of 30 cm compared with values recorded for the northern, northwestern or western escarpments. Water requirements were ensured within an optimal time frame for 58.8-62.1% of the spring row crop growth period, with irrigation being necessary to guarantee the optimum production potential. The biologically active temperature recorded in the TP demonstrates the need to renew the division of the crop areas reported in the literature.
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