Modeling climate change and biophysical impacts of crop production in the Austrian Marchfeld Region

Abstract

Climate change affects major biophysical processes in agricultural crop production (e.g. evaporation of plants and soils, nutrient cycles, and growth of plants). This analysis aims to assess some of these effects by simulating regional climate projections that are integrated in the biophysical process model EPIC (Environmental Policy Integrated Climate). Statistical climate models have been developed for six weather parameters based on daily weather records of a weather station in the Austrian Marchfeld region from 1975 to 2006. These models have been used to estimate daily weather parameters for the period 2007-2038. The resulting projections have been compared to climate scenarios provided from the TYNDALL Centre for Climate Change Research, which are based on General Circulation Models (GCMs). The comparison indicates some differences, namely a smaller temperature increase and a higher precipitation amount in the TYNDALL data. Both climate datasets have been used to simulate impacts of climate change on crop yields, topsoil organic carbon content, and nitrate leaching with EPIC and thus to perform a sensitivity analysis of EPIC. Yield impacts have been assessed for four simulated crops, i.e. 6.2 t/ha for winter wheat for statistical climate projections compared to 5.7 t/ha for TYNDALL scenarios, 10.6 t/ha for corn compared to 10.5 t/ha, 3.9 t/ha for sunflower compared to 3.7 t/ha, and 4.5 t/ha for spring barley compared to 4.3 t/ha-all values as an average over the period 2007-2038. Smaller differences have been simulated for topsoil Climatic Change (2012) 111:641-664 organic carbon content i.e. 55.1 t/ha for the statistical climate projections compared to 55.3 t/ha for the TYNDALL scenarios and nitrate leaching i.e. 7.1 kg/ha compared to 11.1 kg/ha. All crop yields as well as topsoil organic carbon content and nitrate leaching show highest sensitivity to temperature and solar radiation.

Simulating dry matter yield of two cropping systems with the simulation model HERMES to evaluate impact of future climate change

“…5). Aurbacher et al (2013) and Strauss et al (2012) also found a minor increase in summer crop yields due to preponed sowing dates, but, like in the present study, the authors did not consider adapted or improved cultivars, which may exhibit a higher yield potential, especially in combination with longer growth periods. Findings by Olesen et al (2012) further confirm the increasing relevance of preponed sowing dates under conditions of climate change.…”

Spatially Explicit Modeling of Long-Term Drought Impacts on Crop Production in Austria

“…Soil data are extracted from [41] and contain soil layer specific contents of silt, sand and clay, humus, pH, calcium carbonate, and coarse fragments. Up to 25 crop rotation systems per municipality have been derived with the CropRota model [42] using historical land use data of 22 crops [32]. These crops, respectively crop rotations, cover about 89% of total arable land in Austria.…”

Phosphorus and Nitrogen Yield Response Models for Dynamic Bio-Economic Optimization: An Empirical Approach

“…To the best of our knowledge, this is the only prior study that simultaneously considered the N and P inputs with P carryover in an economic analysis of crop production. The joint impact of N and P inputs on crop yield was explicitly considered in dynamic crop growth simulation models, such as DAISY [19], HYPE [20], APSIM [21], and EPIC [22,23], and in decision support systems for agrotechnology transfer like DSSAT [24]. Although these models provide a rich and detailed description of the processes driving the yield response, they are not directly suited to dynamic economic optimization due to the large number of state variables and the extensive data requirements [25].…”