Modeling the sensitivity of agricultural water use to price variability and climate change—An application to Swiss maize production

Finger, Robert

doi:10.1016/j.agwat.2012.03.002

Cited by 30 publications

(18 citation statements)

References 39 publications

(41 reference statements)

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“…Underlining findings from earlier research (e.g. Finger, 2012), expected levels of input use may differ substantially depending on the assumed risk aversion. We find optimal nitrogen use to decrease from 86 to 76 kg/ha and optimal water use to increase from 98 to 131 mm, if comparing results for risk neutrality ( ) and moderate risk aversion with .…”

Section: Datamentioning

confidence: 95%

“…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.…”

Section: Estimating Moments Of Profit Margin Distributionsmentioning

confidence: 99%

“…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.…”

Section: Datamentioning

confidence: 99%

“…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.…”

Section: Integrating Risk In Economic Model Componentsmentioning

confidence: 99%

“…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).…”

Section: Datamentioning

confidence: 99%

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

Finger

2013

Environmental Modelling & Software

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Section: Datamentioning

confidence: 95%

Section: Estimating Moments Of Profit Margin Distributionsmentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

Section: Integrating Risk In Economic Model Componentsmentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

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

Finger

2013

Environmental Modelling & Software

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Modeling irrigation behavior in groundwater systems

Foster

Brozović

Butler

2014

Water Resources Research

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Integrated hydro-economic models have been widely applied to water management problems in regions of intensive groundwater-fed irrigation. However, policy interpretations may be limited as most existing models do not explicitly consider two important aspects of observed irrigation decision making, namely the limits on instantaneous irrigation rates imposed by well yield and the intraseasonal structure of irrigation planning. We develop a new modeling approach for determining irrigation demand that is based on observed farmer behavior and captures the impacts on production and water use of both well yield and climate. Through a case study of irrigated corn production in the Texas High Plains region of the United States we predict optimal irrigation strategies under variable levels of groundwater supply, and assess the limits of existing models for predicting land and groundwater use decisions by farmers. Our results show that irrigation behavior exhibits complex nonlinear responses to changes in groundwater availability. Declining well yields induce large reductions in the optimal size of irrigated area and irrigation use as constraints on instantaneous application rates limit the ability to maintain sufficient soil moisture to avoid negative impacts on crop yield. We demonstrate that this important behavioral response to limited groundwater availability is not captured by existing modeling approaches, which therefore may be unreliable predictors of irrigation demand, agricultural profitability, and resilience to climate change and aquifer depletion.

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Irrigation water policy analysis using a business simulation game

2016

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Despite numerous studies on farmers' responses to changing irrigation water policies, uncertainties remain about the potential of water pricing schemes and water quotas to reduce irrigation. Thus far, policy impact analysis is predominantly based upon rational choice models that assume behavioral assumptions, such as a perfectly rational profit‐maximizing decision maker. Also, econometric techniques are applied which could lack internal validity due to uncontrolled field data. Furthermore, such techniques are not capable of identifying ill‐designed policies prior to their implementation. With this in mind, we apply a business simulation game for ex ante policy impact analysis of irrigation water policies at the farm level. Our approach has the potential to reveal the policy‐induced behavioral change of the participants in a controlled environment. To do so, we investigate how real farmers from Germany, in an economic experiment, respond to a water pricing scheme and a water quota intending to reduce irrigation. In the business simulation game, the participants manage a “virtual” cash‐crop farm for which they make crop allocation and irrigation decisions during several production periods, while facing uncertain product prices and weather conditions. The results reveal that a water quota is able to reduce mean irrigation applications, while a water pricing scheme does not have an impact, even though both policies exhibit equal income effects for the farmers. However, both policies appear to increase the variation of irrigation applications. Compared to a perfectly rational profit‐maximizing decision maker, the participants apply less irrigation on average, both when irrigation is not restricted and when a water pricing scheme applies. Moreover, the participants' risk attitude affects the irrigation decisions.

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Modeling the sensitivity of agricultural water use to price variability and climate change—An application to Swiss maize production

Cited by 30 publications

References 39 publications

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

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

Modeling irrigation behavior in groundwater systems

Irrigation water policy analysis using a business simulation game

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