Abstract: • Systematic analysis of the influence of spatial soil data resolution on simulated regional yields and total growing season evapotranspiration. • The responses of four crop models of different complexity are compared. • Differences between models are larger than the effect of the chosen spatial soil data resolution. • Low influence of soil data resolution due to: high precipitation amount, methods for calculating water retention and method of data aggregation. The spatial variability of soil properties is an important driver of yield variability at both field and regional scale. Thus, when using crop growth simulation models, the choice of spatial resolution of soil input data might be key in order to accurately reproduce observed yield variability. In this study we used four crop models (SIMPLACE<LINTUL-SLIM>, DSSAT-CSM, EPIC and DAISY) differing in the detail of modeling above-ground biomass and yield as well as of modeling soil water dynamics, water uptake and drought effects on plants to simulate winter wheat in two (agro-climatologically and geo-morphologically) contrasting regions of the federal state of North-Rhine-Westphalia (Germany) for the period from 1995 to 2008. Three spatial resolutions of soil input data were taken into consideration, corresponding to the following map scales: 1:50 000, 1:300 000 and 1:1 000 000. The four crop models were run for water-limited production conditions and model results were evaluated in the form of frequency distributions, depicted by bean-plots. In both regions, soil data aggregation had very small influence on the shape and range of frequency distributions of simulated yield and simulated total growing season evapotranspiration for all models. Further analysis revealed that the small influence of spatial resolution of soil input data might be related to: (a) the high precipitation amount in the region which partly masked differences in soil characteristics for water holding capacity, (b) the loss of variability in hydraulic soil properties due to the methods applied to calculate water retention properties of the used soil profiles, and (c) the method of soil data aggregation. No characteristic “fingerprint” between sites, years and resolutions could be found for any of the models. Our results support earlier recommendation to evaluate model results on the basis of frequency distributions since these offer quick and better insight into the distribution of simulation results as compared to summary statistics only. Finally, our results support conclusions from other studies about the usefulness of considering a multi-model approach to quantify the uncertainty in simulated yields introduced by the crop growth simulation approach when exploring the effects of scaling for regional yield impact assessments.

Abstract: This study aimed to determine short term farm responses of Irish dairy farms under climate change. The Irish National Farm Survey data and Irish weather data were the main datasets used in this study. A set of simulation models were used to determine grass yields and field time under a baseline scenario and a future climate scenario. An optimising farm level model which maximises farm net income under limiting farm resources was then run under these scenarios. Changes in farm net incomes under the climate change scenario compared to the baseline scenario were taken as a measure to determine the effect of climate change on farms. Any changes in farm activities under the climate run compared to the baseline run were considered as farm’s responses to maximise farm profits. The results showed that there was a substantial increase in yields of grass (49% to 56%) in all regions. The impact of climate change on farms was different based on the regions. Dairy farms in the Border, Midlands and South East regions suffered whereas dairy farms in other regions generally fared better under the climate change scenario. For a majority of farms, a substitution of concentrate feed with grass based feeds and increasing stocking rate were identified as the most common farm responses. However, farms replaced concentrate feed at varying degree. Dairy farms in the Mid East showed a move towards beef production system where medium dairy farms in the South East regions shifted entire tillage land to grass land. Farms in the South East region also kept animals on grass longer under the climate change scenario compared to the baseline scenario.