Abstract: Short-term perspectives appear to be relevant in formulating adaptation measures to changed climate variability (CCV) as a part of the European Rural Development Policy (RDP). Indeed, short-run CCV is the variation that farmers would perceive to such an extent that a political demand would be generated for adapting support measures. This study evaluates some relevant agronomic and economic impacts of CCV as modelled in a near future time period at the catchment scale in a rural district in Sardinia (Italy). The effects of CCV are assessed in relation to the availability of irrigation water and the irrigation needs of maize. The Environmental Policy Integrated Climate (EPIC) model was used to simulate the impact of key climatic variables on the irrigation water requirements and yields of maize. A three-stage discrete stochastic programming model was then applied to simulate management and economic responses to those changes. The overall economic impact of a simulated CCV was found to be primarily caused by reduced stability in the future supply of irrigation water. Adaptations to this instability will most likely lead to a higher level of groundwater extraction and a reduction in the demand for labour. Changed climate variability will most likely reduce the income potential of small-scale farming. The most CCV-vulnerable farm typologies were identified, and the implications were discussed in relation to the development of adaptation measures within the context of the Common Agricultural Policy of European Union. (C) 2013 Elsevier Ltd. All rights reserved.

Abstract: A field experiment was conducted in Mediterranean conditions to evaluate the effects of different irrigation volumes and water quality on yield performance of tomato crop. The tomato crop was irrigated reestablishing 50 (I1), 75 (I2) and 100% (I3) of the crop evapotranspiration (ETc) with two water quality: fresh water with EC 0.9 dS m-1 (FW) and saline water with EC 6 dSm-1 (SW). At harvest, total and marketable yield, weight, number, total soluble solids (TSS) and dry matter of fruit were calculated, The results showed no statistical differences among the three different irrigation volumes on tomato yield and quality. The salinity treatment did not affect yield, probably because the soil salinity in the root zone on average remained below the threshold of tomato salt tolerance. Instead, salinity improved fruit quality parameters as dry matter and TSS by 13 and 8%, respectively. After the first field application of saline water, soil saturated extract cations (SSEC), electrical conductivity of soil paste extract (ECe), sodium absorption ratio (SAR) and exchangeable sodium percentage (ESP) cations increased; the largest increase of cations, in particular of Na, occurred in the top layer. At the end of the experiment, the absolute value of SSEC, ECe and SAR, for all the effects studied, were lower than those recorded in 2007. This behavior was suitable to the reduced volumes of treatments administered in 2009 in respect to the 2007. Furthermore, the higher total rainfall recorded in 2009 increased the leaching and downward movement of salts out of the sampling depth.

Abstract: Due to the more frequent use of crop models at regional and national scale, the effects of spatial data input resolution have gained increased attention. However, little is known about the influence of variability in crop management on model outputs. A constant and uniform crop management is often considered over the simulated area and period. This study determines the influence of crop management adapted to climatic conditions and input data resolution on regional-scale outputs of crop models. For this purpose, winter wheat and maize were simulated over 30 years with spatially and temporally uniform management or adaptive management for North Rhine-Westphalia ((similar to)34 083 km(2)), Germany. Adaptive management to local climatic conditions was used for 1) sowing date, 2) N fertilization dates, 3) N amounts, and 4) crop cycle length. Therefore, the models were applied with four different management sets for each crop. Input data for climate, soil and management were selected at five resolutions, from 1 x 1 km to 100 x 100 km grid size. Overall, 11 crop models were used to predict regional mean crop yield, actual evapotranspiration, and drainage. Adaptive management had little effect (< 10% difference) on the 30-year mean of the three output variables for most models and did not depend on soil, climate, and management resolution. Nevertheless, the effect was substantial for certain models, up to 31% on yield, 27% on evapotranspiration, and 12% on drainage compared to the uniform management reference. In general, effects were stronger on yield than on evapotranspiration and drainage, which had little sensitivity to changes in management. Scaling effects were generally lower than management effects on yield and evapotranspiration as opposed to drainage. Despite this trend, sensitivity to management and scaling varied greatly among the models. At the annual scale, effects were stronger in certain years, particularly the management effect on yield. These results imply that depending on the model, the representation of management should be carefully chosen, particularly when simulating yields and for predictions on annual scale.