Irrigation as adaptation strategy to climate change—a biophysical and economic appraisal for Swiss maize production

Abstract

The impact of climate change on Swiss maize production is assessed using an approach that integrates a biophysical and an economic model. Simple adaptation options such as shifts in sowing dates and adjustments of production intensity are considered. In addition, irrigation is evaluated as an adaptation strategy. It shows that the impact of climate change on yield levels is small but yield variability increases in rainfed production. Even though the adoption of irrigation leads to higher and less variable maize yields in the future, economic benefits of this adoption decision are expected to be rather small. Thus, no shift from the currently used rainfed system to irrigated production is expected in the future. Moreover, we find that changes in institutional and market conditions rather than changes in climatic conditions will influence the development of the Swiss maize production and the adoption of irrigation in the future.

Expanding risk consideration in integrated models – The role of downside risk aversion in irrigation decisions

“…Just and Pope, 1978), allows us to extent earlier bio-economic modeling approaches (e.g. Finger et al, 2011, Finger, 2012 by additionally investigating the effects of input use on yield skewness, which represents downside risks.…”

“…In contrast to irrigation, nitrogen is expected to be risk increasing (e.g. Finger et al, 2011, Finger, 2012. To quantify the farmers' benefits from all three effects in monetary terms, certainty equivalents are used.…”

“…We use quasi-experimental data derived for maize production at the Swiss Plateau simulated with deterministic crop yield simulation model CropSyst, derived from Finger et al (2011) andFinger (2012). In CropSyst, above-and below-ground processes such as the soil water budget, soil-plant nitrogen budget, crop phenology, canopy and root growth, and crop yield are simulated in response to crop and soil characteristics, daily weather data, and management options (see Stöckle et al, 2003, for details).…”

“…The assumed soil texture is characterized with 38% clay, 36% silt, and 26% sand, and identical starting conditions regarding soil composition and soil available nutrients are used for each simulation. These simulations lead to 912 observations (see Finger et al, 2011;Finger, 2012, for details on data generation and descriptive summaries). Table 2 shows coefficient estimates for equations 2-4, i.e.…”

An open platform to assess vulnerabilities to climate change: An application to agricultural systems

“…Studies of this type manage to provide quantitative estimates of future consequences for the productivity and other agricultural services, the main focus being essentially to adapt management based on given growing conditions (e.g., planting dates or grazing periods based on soil moisture) in order to counter anticipated risks or to realize any benefits. Though process-based simulation models have been applied for climate change and adaptation studies in agriculture (Finger et al, 2011;Graux et al, 2013;Kristensen et al, 2011;Smith and Olesen, 2010;Trnka et al, 2010;White et al, 2011), answering the question "Are agricultural systems expected to become more vulnerable (and why) owing to climate changes" still requires quite some research.…”