Microeconomic analysis of decisions on land use responding to climate change with emphasis on learning under changing risk

应对气候变化的土地利用决策的微观经济分析，重点是在不断变化的风险下学习

• 批准号: 82511545
• 负责人: Professor Dr. Stephan Dabbert
• 金额: --
• 依托单位: Rektorat
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2008
• 资助国家: 德国
• 起止时间: 2007-12-31 至 2013-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/82511545?language=en
• 关键词: Microeconomic; analysis; decisions; land; use

The objective of the project is to develop a bio-economic farm model that allows for simulation of farmer’s decisions under the circumstances of climate change. The model will depict the changing land-use, which will be triggered by climate change, and it should help to better understand the decisions of farmers. Following a sequential concept of decision making a mathematical programming model will be coupled with a management module that implements decisions on a daily basis. The management module reacts to daily weather variables in a rulebased way and exchanges information with a field scale and crop specific growth model. The results of a one-year simulation are then compared with the values that served as a basis of the development of the original farm plan in the mathematical programming model. The mathematical programming model is based on expected values and their distributions with particular emphasis on variables that depend on weather. From different sources changing expectations on the development of weather and climate risk can be derived. These will serve as a basis for Bayesian and rule based learning processes. The consequences of different learning strategies under changing risk on land use and farm economic success will be simulated. The economic model will be coupled with a crop model and a meteorological model within the Research Unit.

该项目的目标是开发一个生物经济农场模型，模拟农民在气候变化情况下的决定。该模型将描述气候变化引发的土地使用变化，它应有助于更好地理解农民的决定。按照决策的顺序概念，数学规划模型将与每天实施决策的管理模块相结合。管理模块以基于规则的方式对每日天气变量做出反应，并与田间尺度和作物特定生长模型交换信息。然后将一年模拟的结果与数学规划模型中作为原始农场计划发展基础的值进行比较。数学规划模型基于预期值及其分布，特别强调取决于天气的变量。从不同的来源可以得出对天气和气候风险发展的不断变化的预期。这些将作为贝叶斯和基于规则的学习过程的基础。将模拟不同的学习策略下的土地利用和农业经济成功的变化风险的后果。经济模型将与研究股内的作物模型和气象模型相结合。