Integrierte Landsystemmodellierung
Zusammenfassung der Projektergebnisse
So far, there has been a mismatch of modeling approaches in earth and land system science that severely hampers progress in climate impact research at the regional scale. While atmosphere-land surface models work with very fine temporal resolution over coarse temporal and spatial extents, soilplant and agro-economic decision models are typically specified for average crops and average farms which are then aggregated to match the scale of atmosphere-land surface models. Impact analysis with this conventional modeling approach is unsatisfactory because of the information loss associated with model aggregation and integration. Although the direct effect of rising temperature and atmospheric CO2 levels on potential crop yields can grossly be captured, this does not apply for the still unknown indirect effects on farmer crop management. As a consequence, changes in crop productivity simulated with these mismatched model ensembles tend to be “over-driven,” suggesting biased policy interventions that might not be appropriate in terms of resourcefulness and sustainability. P8’s agenda in FOR 1695 was to develop the conceptual and technical integration of atmosphere-land surface, soil-plant and agro-economic decision models in order to jointly investigate feedbacks between land-use and climate in the two study landscapes in Southwest Germany. Within this scope, P8 has simulated (using BEMS) the adaptation of land users to climate change and climate variability based on sound scientific process understanding (and not based on exogenous and somewhat ambiguous expert land-use scenarios). The modeling system (ILMS) to explore the feedbacks between future climate and land use has been implemented. Its functioning is currently thoroughly being tested. Quantification of the feedbacks, however, has to be left to future work. In all other respects, P8 and FOR 1695 have succeeded, to our knowledge as the first interdisciplinary research team worldwide: (1) The project developed anonymity-preserving algorithms for using the fullest possible amount of information from agricultural census data in agro-economic decision modeling. This path-breaking achievement was awarded the Gerhard-Fürst-Prize of the Federal Statistical Office. (2) The soil-plant and agro-economic decision models were upgraded for massively parallel computing, which was the prerequisite for loss-free coupling with atmosphere-land surface models using highperformance computing. This achievement was rewarded with the recent DFG approval of the High-Performance Computing application (Tier-2-HPC) of the Steinbuch Center for Computing at KIT that was motivated explicitly with better prospects for regional climate impact research in agriculture. (3) The article featuring the quantification of direct versus indirect climate effects on agricultural land use was published in the international top journal of the field, where it was acknowledged as one of the highly cited articles of American Journal of Agricultural Economics published in 2015. (4) Simulation work on endogenous adaptation of land users is not yet completed (P8 was granted a costneutral extension due to delay in recruitment) but intermediate results show that climate signals indeed trigger endogenous response of computational agents, which can be taken as a preliminary confirmation of P8’s well-matched modeling efforts. The novel simulation methods developed in P8 have been reused and cross-verified in other research projects in Brazil, Chile, Ethiopia, South-Africa and Uganda. The next step will be to explore the opportunities of big-data technology for informing bioeconomic modeling.
Projektbezogene Publikationen (Auswahl)
- 2014. Agent-based modelling of climate adaptation and mitigation options in agriculture. Journal of Agricultural Economics 65, 323–348
Berger, T., Troost, C.
(Siehe online unter https://doi.org/10.1111/1477-9552.12045) - 2015. Climate, energy and environmental policies in agriculture: Simulating likely farmer responses in Southwest Germany. Land Use Policy 46, 50–64
Troost, C., Walter, T., Berger, T.
(Siehe online unter https://doi.org/10.1016/j.landusepol.2015.01.028) - 2015. Dealing with uncertainty in agent-based simulation: Farm-level modeling of adaptation to climate change in Southwest Germany. American Journal of Agricultural Economics 97, 833-854
Troost, C., Berger, T.
(Siehe online unter https://doi.org/10.1093/ajae/aau076) - 2015. Process-based simulation of regional agricultural supply functions in Southwestern Germany using farm-level and agent-based models. In: International Association of Agricultural Economists, 2015 Conference, August 9-14, 2015, Milan, Italy
Troost, C., Berger, T.
(Siehe online unter https://dx.doi.org/10.22004/ag.econ.211929) - 2015. Quantifying the economic importance of irrigation water reuse in a Chilean watershed using an integrated agent-based model. Water Resources Research 51, 648-668
Arnold, R.T., Troost, C., Berger, T.
(Siehe online unter https://doi.org/10.1002/2014WR015382) - 2016. Advances in probabilistic and parallel agent-based simulation: Modelling climate change adaptation in agriculture. In: Sauvage, S., Sánchez Pérez, J.-M., Rizzoli, A.E. (Eds.) Proceedings of the 8th International Congress on Environmental Modelling and Software, July 10-14, Toulouse, France
Troost, C., Berger, T.
- 2016. Mikrosimulation landwirtschaftlicher Produktion auf der Schwäbischen Alb. Wirtschaft und Statistik 1/2016
Troost, C.
- 2016. Simulating structural change in agriculture: Modelling farming households and farm succession. In: Sauvage, S., Sánchez-Pérez, J.-M., Rizzoli, A. (Eds.) Proceedings of the 8th International Congress on Environmental Modelling and Software, July 10-14, Toulouse, France
Troost, C., Berger, T.
- 2017. Simulating climate change adaptation and structural change in agriculture using microsimulation and agent-based modeling. In: Richling, S., Baumann, M., Heuveline, V. (Eds.) Proceedings of the 3rdbwHPC-Symposium Heidelberg 2016
Troost, C., Berger, T.
- 2017. Can smallholder farmers adapt to increasing climate variability, and how effective are policy interventions? Agentbased simulation results for Ethiopia. Agricultural Economics 48, 693-706
Berger, T., Troost, C., Wossen, T., Latynskiy, E., Tesfaye, K., Gbegbelegbe, S.
(Siehe online unter https://doi.org/10.1111/agec.12367) - 2018. Representation of decision-making in European agricultural agentbased models. Agricultural Systems 167, 143–160
Huber, R., Bakker, M., Balmann, A., Berger, T., Bithell, M., Brown, C., Grêt-Regamey, A., Xiong, H., Le, Q.B., Mack, G., Meyfroidt, P., Millington, J., Müller, B., Polhill, J.G., Sun, Z., Seidl, R., Troost, C., Finger, R.
(Siehe online unter https://doi.org/10.1016/j.agsy.2018.09.007) - 2018. The biophysical and socio-economic dimension of yield gaps in the southern Amazon - A bio-economic modelling approach. Agricultural Systems 165, 1-13
Hampf, A.C., Carauta, M., Latynskiy, E., Libera, A.A., Monteiro, L., Sentelhas, P., Troost, C., Berger, T., Nendel, C.
(Siehe online unter https://doi.org/10.1016/j.agsy.2018.05.009)
