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Browsing by Subject "Model"

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A study of pasture cropping as an alternative cropping system for sub-saharan Africa
(2020) Orford, Rohan; Asch, Folkard
With food security and soil degradation being a major concern and hurdle in the development goals of sub-Saharan Africa (SSA), there has been and continues to be an attempt to find an alternative cropping system to conventional monocropping that rehabilitates soils whilst increasing productivity and efficiency of the subsistence cropping system. Such a cropping system needs to be realistically adoptable within the SSA social and ecological constraints. An alternative Australian winter rainfall relay cropping system coined pasture cropping (PaCr) was identified as an option that may surmount some of these limitations.This research involved completing a field trial through to model scale introductory assessment of the water dynamics in PaCr and the implications thereof in yield, water use efficiency (WUE) and competition for water; ultimately assessing the potential of PaCr in SSA. PaCr was adapted to an intercropping system for SSA summer rainfall conditions. The three treatments included the representative subsistence crop cowpea (Vigna unguiculate) and a common indigenous pasture (Eragrostis curvula) and an additive PaCr setup of cowpea directly seeded into pasture in water limited (rainfed) field trials in Pretoria, South Africa between 2013-2015. The DM yields of PaCr were 17% and 293% higher in both seasons compared to the conventional cowpea monocrop yield. When comparing PaCr yield to conventional pasture, there was a 12% and 89% higher yield in both seasons compared to the conventional pasture monocrop yield. The greater yield advantage in 2015 with the limited rainfall indicates that PaCr was most advantageous in terms of DM yield in a drier year which is a time of greatest risk and food insecurity. PaCr was also more WUE in both seasons, being significantly higher than the cowpea monocrop in 2015. Competition also showed a higher degree of competitiveness by cowpea in the wetter 2013-14 season and lower competitive ability in the drier 2015, whereas pasture showed little competitive response in 2013-14 and attaining significantly higher yields than the monocrop in 2015. The results of the field trials were used to adapt the University of Pretoria’s Soil Water Balance (SWBsci) crop model to simulate an intercropping system. Observed field results were compared to simulated results and statistical goodness of fit indicators were assessed, concluding that with all the variations of season and systems, the results were acceptable as an inaugural adaptation of the Soil Water Balance model. Other relevant crop water use parameters were extrapolated from the simulated data allowing for a more complete insight into the field trials. With the adapted SWBsci model, 14-year simulations were run in three different climates and on three different soil types for all three cropping systems to map out the viability of PaCr across an aridity index continuum as a reference for further application in research or in industry and to stress test SWBsci. Results demonstrated that PaCr was only advantageous in dry sub-humid to humid conditions on clay-loam to sandy soils, whereas pasture was dominant in more semi-arid conditions on the three different soils. Cowpea only performed better on clay soils in dry-sub humid to sub humid conditions. These advantages are attributed to differing plant water availability at various root depths suiting growth and/or competition of either one or both crops. These plant water availability differences were determined by water holding capacity of various soil types and rainfall volumes. From a WUE perspective, the pasture and PaCr did have a higher WUE but with the extreme variation in rainfall there was no significant difference. But pasture and PaCr both had a very high WUE in arid to semi-arid conditions due to the deeper roots of pasture accessing stored soil water. Competition also showed insignificant results due to the variation in the rainfall. However, in more arid to semi-arid conditions on clay-loam and sand competition outweighed facilitation thus resulting in land equivalent ratios (LER) of below 1, whereas on clay for the same aridity levels the average LER was greater than one. This was attributed to cowpea have a better competitive ability when clay water holding capacity confined plant available water to the top soil layers. The converse is true in the dry sub-humid conditions and wetter conditions because LER was less than one on clay soils while being greater than one on clay-loam and sand. This was attributed to the lower water holding capacity of sand spreading the plant available water through the profile allowing for niche root partitioning to be effective. For subsistence farmers, PaCr out-yielded the cowpea monocrop in arid conditions on all three soil types and on clay in semi-arid conditions. In the wetter dry sub-humid conditions, PaCr out-yielded cowpea on sand. In the wet sub-humid conditions PaCr does well on clay-loam and sand, but cowpea yields under these conditions are more than adequate to make the choice of PaCr debatable form a yield point of view. However, if soil rehabilitation is a necessity in the sub-humid areas, this makes PaCr a very realistic option.
Land use management under climate change : a microeconomic analysis with emphasis on risk
(2018) Reinmuth, Evelyn; Dabbert, Stephan
This cumulative dissertation was conducted under a grant from the German Research Foundation (DFG) for the research group FOR 1695 - “Agricultural Landscapes under Global Climate Change – Processes and Feedbacks on a Regional Scale”. The goal of the sub-project from which this dissertation stems from was to explore, extend and strengthen the scientific basis for learning and risk strategies and the adaptation behavior of farmers’ economic planning decisions in crop production under the influence of climate change. The integrated bioeconomic simulation model FarmActor, was to be used as an experimental tool to develop an interdisciplinary methodological approach supported by empirical work in two study regions in Southwest Germany, the Kraichgau and the Swabian Alb. This dissertation examines risk in the context of land use management and specifically crop production. Risk in this context is related to how outcome distributions are affected by climatic influences. Risk strategies assess these contributions and account for them in the resulting decisions. The thesis is written as a cumulative dissertation and is composed of five articles. Four articles have been published by peer-reviewed journals. A fifth article has been published as a peer-reviewed conference proceeding. The article at fifth place represents the results of the main focus of this dissertation as presented in the following. Available economic models assume that farmers assess climatic risks only through yields or costs when building their land use management risk strategy for crop production. However, the available methodological approaches have been criticized for either under- or overestimating farmers’ actual behavior. In reality, and as a basis for field allocation planning, farmers have additional knowledge from monitoring crop development throughout the whole season. Yield is actually just the last point in a long sequence of (economic) evaluative observations about the production process. This influences how farmers define not only the riskiness of a yield distribution but also its costs. We hypothesize that, because it is not possible to methodologically integrate process evaluations in economic planning decisions, models lack performance, and as a consequence, it is very difficult to conduct proper research on the climate’s influences on land use management decisions. In this original research, we present a newly developed downside risk measure based on evaluations throughout the production process that can be included in the planning process as an additional parameter—so-called Annual Risk Scores. A comparative static analysis was performed to demonstrate how ARS scores assess future climatic conditions in the example of winter wheat production in the Kraichgau region as supported by empirical data. It was shown that the mechanism is sensitive to different climatic conditions. Furthermore, the ARS scores provide a different picture of climatic influence compared to an analysis based only on yields. The last article presented in this dissertation represents an integrative review that promotes more efficient model development and the reuse of newly developed methodologies in the field of integrated bio-economic simulation models. The review is based on lessons learned from working with the simulation model. Thus, the intended and outstanding full implementation of the ARS mechanism is presented in the last part of the synthesis, where we advise including the ARS scores as another constraint in the field allocation mechanisms of the FarmActor model. This is expected to improve the integration of both bio-physical and economic dimensions for complex integrated bio-economic simulation models.
Qualitativer Vergleich von Modellen zur Bewertung von Klimaschutzmaßnahmen in Europa unter besonderer Berücksichtigung der Landwirtschaft
(2006) Vabitsch, Anna Maria; Zeddies, Jürgen
Agriculture in Europe is responsible for a considerable fraction of greenhouse gas emissions. Methane, nitrous oxide and carbon dioxide emissions from agricultural sources account for about 10% of the total European greenhouse gas emissions. The contribution that agriculture can and should make to the achievement of the agreed European goals for emission reductions has to be assessed. The aim of this study is to analyse the possibilities and conditions for greenhouse gas mitigation in the agricultural sector in comparison to other economic sectors. It addresses the question of how meaningful and efficient it is to reduce greenhouse gas emissions from farming. A review of the literature showed that various measures for emissions reductions are available for agriculture as well as for the other sectors. In order to assess the efficiency of these mitigation measures, a quantification of abatement costs is necessary. For this purpose, economic-ecological models were chosen which were developed mostly for political advice and analysis. A detailed analysis and assessment of the chosen models was carried out in order to evaluate the model results. The comparative assessment of model results arrives at the conclusion that there is presently no model available that satisfies all the requirements demanded of an environmental indicator for climate policy. For this comparison of models, a selection of representative models was described and analysed in detail. The following models were chosen for the detailed analysis and assessment: POLES, MERGE, EPPA-EU, PRIMES / GENESIS, RAINS / GAINS, CAPRI, AROPA GHG and RAUMIS. They were differentiated between highly aggregated models which represent the global economy with its impacts on the climate system and, in contrast, disaggregated models which focus on a single sector and/or region. Two categories of model structures were observed: general and partial equilibrium models based on the neo-classical economic theory of perfect markets and, on the other hand, optimisation models which were solved by the maximisation of (regionally weighted) profit and benefit. An important feature which distinguishes between the models is the sectoral and material resolution. Aggregated energy models are commonly used, most of which not only reproduce the energy sector, but also the other sectors. However, they only account for energy-related CO2 emissions. These models provide important information on the most relevant emitting sector (energy) and the most important greenhouse gas (CO2), but they neglect the presence of the other Kyoto-gases and the possibilities of an integrated approach for emission reductions. The results of assessments of mitigation potential in the agricultural sector using energy models are incomplete because the relevance of non-CO2 emissions and their possible contribution to overall emission reductions are disregarded. As a second focus models of the agricultural sector were analysed and assessed. These models describe the agricultural production process with a high degree of resolution and determine specific mitigation costs of single measures and options. Additionally, some of these models assess the interactions and effects of simultaneously reducing emissions of different greenhouse gases. However, the problem still exists that results from models of different sectors are not comparable with one another. The main reasons for this are the varying model assumptions and the specific conditions. A method to resolve this dilemma is provided by the models that integrate top-down and bottom-up elements in one model framework. This means that several sectors and countries are simultaneously modelled (top-down) but detailed information on specific gases and mitigation options is integrated as well (bottom-up). Using this procedure, the comparison of different sectors is possible and sector-specific accuracy in the definition of abatement costs, for instance, is also achieved. This procedure is most advanced in the case of integrated assessment models. This approach aims to account for as many aspects as possible of one environmental problem as well as for all its interactions and impacts on other environmental goals. At present, these very complex model systems are most readily applicable to find solutions for the optimal spatial, temporal and material allocation of mitigation measures and investment. The significance of these model results is, of course, also dependent on the available database and on the assumptions made. These models come to the conclusion, among other things, that the integration of agricultural greenhouse gas emissions into a holistic mitigation approach may provide a significant reduction in mitigation costs. Despite the high level of uncertainties regarding the model results, it can be concluded that the agricultural sector should definitely contribute to achieving the agreed emission reductions.
Regionalising a soil-plant model ensemble to simulate future yields under changing climatic conditions
(2023) Bendel, Daniela Silke; Streck, Thilo
Models are supportive in depicting complex processes and in predicting their effects. Climate models are applied in many areas to assess the possible consequences of climate change. Even though Global Climate Models (GCM) have now been regionalised to the national level, their resolution of down to 5x5 km2 is still rather coarse from the perspective of a plant modeller. Plant models were developed for the field scale and work spatially explicitly. This requires to make adjustments if they are applied at coarser scales. The regionalisation of plant models is reasonable and advantageous against the background of climate change and policy advice, both gaining in importance. The higher the spatial and temporal heterogeneity of a region, the greater the computational need. The (dis)aggregation of data, frequently available in differing resolutions or quality, is often unavoidable and fraught with high uncertainties. In this dissertation, we regionalised a spatially-explicit crop model ensemble to improve yield projections for winter wheat under a changing climate. This involved upscaling a crop model ensemble consisting of three crop models to the Stuttgart region, which has an area of 3,654 km2. After a thorough parameter estimation performed with a varying number of Agricultural Response Units on a high-performance computing cluster, yield projections up to the year 2100 were computed. The representative concentration pathways of the Intergovernmental Panel on Climate Change (IPCC) RCP2.6 (large reduction of CO2 emissions) and RCP8.5 (worst case scenario) served as a framework for this effort. Under both IPCC scenarios, the model ensemble predicts stable winter wheat yields up to 2100, with a moderate decrease of 5 dt/ha for RCP2.6 and a small increase of 1 dt/ha for RCP8.5. The variability within the model ensemble is particularly high for RCP8.5. Results were obtained without accounting for a potential progress in wheat breeding.

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