Browsing by Subject "Sensitivity analysis"

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Agent-based modeling of climate change adaptation in agriculture : a case study in the Central Swabian Jura
(2014) Troost, Christian; Berger, Thomas
Using the MPMAS multi-agent software, the present thesis implements an agro-economic agent-based model to analyze climate change adaptation of agricultural production in the Central Swabian Jura. It contributes to the DFG PAK 346 FOR 1695 research projects dedicated to improve the understanding of processes that shape structure and functions of agricultural landscapes in the context of climate change at regional scale. In the context of this example, this thesis discusses, develops and tests novel approaches to deal with four notorious challenges that have so far hampered the empirical use of agent-based models for applied economic analysis: data availability, process uncertainty, model validity and computational requirements. The model is used to examine climatic effects on agriculture, changes in agricultural price responses and biogas support and agri-environmental policies illustrating the applicability of the model to adaptation analysis. The first part of the thesis is dedicated to a methodological discussion of the use of mathematical programming-based multi-agent systems, such as MPMAS, for the analysis of agricultural adaptation to climate change. It synthesizes knowledge about the potential impacts of climate change and processes of farmer adaptation and reviews existing agent-based models for their potential contribution to adaptation analysis. The major focus of the first part is a discussion of available approaches to model validation, calibration and uncertainty analysis and their suitability for the use with mathematical programming-based agent-based models. This discussion is based on four principles required to ensure the validity of conclusions drawn from modeling studies: (i) a transparent model documentation, (ii) that the invariant elements of the model can really be expected to be invariant between scenarios assessed, (iii) that empirical calibration of the model is limited to the extent warranted by available observation and knowledge about the expected error distribution, and (iv) that the effect of process uncertainty on the conclusions is evaluated and communicated. Based on these conclusions, generic extensions of the MPMAS toolbox are developed to allow the application of suitable approaches for validation and uncertainty analysis. The second part of the thesis describes the application of the newly developed methodology in the construction and use of the Central Swabian Jura model. The model focuses on an endogenous representation of heterogeneity in agent behavior, an empirical parameterization of the model, and an incorporation of climate effects on possible crop rotations and suitable days for field work besides the expected effects on yields. It extends the demographic, investment and land market components of MPMAS to improve the simulation of structural change over time. The model was used to analyze potential effects of climate change adaptation on agricultural production and land use in the study area. The results show that besides effects on yields also other climate change-induced effects on the conditions of agricultural production may have important impacts on land use decisions of farmers and deserve more attention in climate change impact analysis. Potential impacts of changes in the time slots suitable for field work and an additional rotation option are predicted to be comparable to the impact of the changes in yields predicted by a crop growth model. Results point to an expansion of wheat and silage maize areas at the expense of barley areas. The partial crowding out of summer barley by wheat area held for current price relations and is less strong at higher relative prices for summer barley. Price response analysis indicated that winter wheat production enters into a substitutive relationship with summer barley production under climate change conditions, while competition with winter barley area diminishes. This leads also to a higher elasticity of the wheat area with respect to relative summer barley prices. The model was then used to analyze biogas support through the Renewable Energy Act (EEG) and the support for grassland extensification and crop rotation diversification through the MEKA scheme. Especially simulated participation in crop rotation diversification is strongly reduced in the climate change scenarios, while the investments in biogas plants are slightly increased. The conditions established by the latest EEG revision imply that further development of biogas capacity will crucially depend on the existence of demand for excess process heat, because the alternative option of using high manure shares seems to be rather unattractive for farmers in the area according to the simulation results.
Predicting nitrogen excretion of cattle kept under tropical and subtropical conditions using semimechanistic models
(2023) Salazar‐Cubillas, Khaterine; Corea, Edgardo; Dickhöfer, Uta
The present study aims at evaluating whether current semimechanistic models developed for temperate cattle systems can be adopted for cattle under (sub‐) tropical husbandry systems to adequately (accurately and precisely) predict total nitrogen (TN), urine nitrogen (UN), faecal nitrogen (FN) excretion and its partition into different FN fractions. Selected models were built based on the feeding recommendations for ruminants of the British (Model A), German (Model G) and French (INRA; Model I) system. Model evaluation was conducted using eight nitrogen balance studies performed in El Salvador, Kenya and Peru (n = 392 individual observations including lactating cows, heifers and steers). Concordance correlation coefficient, root mean square errors (RMSE), and mean biases were estimated to evaluate the models' adequacy in predicting nitrogen excretion. Input variables causing greatest variation in nitrogen excretion prediction were identified by a sensitivity analysis and adjusted. Model G was able to adequately (i.e., RMSE of <25% of observed mean, systematic error of <5% of the mean square error) predict TN excretion through a compensation between overestimation of UN excretion and underestimation of FN excretion. None of the models were able to adequately predict UN, FN, and different FN fractions. Model I adequately predicted FN (RMSE = 18%) when duodenal microbial crude protein flow was increased, and the intercept used to predict FN excretion was reduced from 4.30 to 3.82 g of nitrogen per kilogram of dry matter intake. These adjustments, however, were not sufficient to predict adequately UN excretion (RMSE = 38%), individual FN fractions (RMSE > 56%), and TN (RMSE = 22%) excretion, by Model I.
Ein Vergleich zwischen Barometrischer Prozessseparation (BaPS) und 15N-Verdünnungsmethode zur Bestimmung der Bruttonitrifikationsrate im Boden
(2010) Schwarz, Ulrich; Streck, Thilo
Besides the carbon cycle, the nitrogen cycle plays a central role in soil. A key process of this cycle is nitrification. In practice, nitrification is measured as gross or net nitrification. Net nitrification rates are measured by determining the net change in the nitrate or ammonium pool over a period of time. Net rates are difficult to interpret, because the net nitrification rate is the sum of nitrate producing and consuming processes. In contrast, gross nitrification quantifies the total production of nitrate via nitrification. There are two methods for measuring gross nitrification: the 15N-Pool dilution technique and Barometric Process Separation (BaPS). In the 15N-Pool dilution technique, nitrate en-riched with the heavier isotope 15N is added to soil, and the dilution of the 15N pool and the change in the nitrate pool are measured over time. The BaPS method measures changes in pressure and the oxygen- and carbon dioxide concentration of the atmosphere in a closed chamber. The gross nitrification rate can then be computed by a step-by-step solution of the gas balance equations. In the present study, 15N enriched nitrate was added to soil and then put into the BaPS-incubation chamber. By this procedure gross nitrification rates were measured simultaneously with both the 15N-Pool dilution technique and the BaPS method. The aim of the present study was to find out under which conditions the two methods yield similar results and under which conditions different results. In the latter case, the thesis aimed at elucidating the cause for the disagreement between both methods. For this purpose extensive research on two agricultural soils from North China and three soils from Southwest Germany was undertaken. The two methods were compared under the following conditions: 1) application of ammonium fertilizer, 2) addition of nitrification inhibitors, 3) varying soil wa-ter contents, and 4) different soil temperatures. Moreover, a new methodological approach was tested: the 13CO2-Pool dilution technique. Combining this method with the 15N-Pool dilu-tion technique and the Barometric Process Separation made it possible to exactly determine the pH and respiration coefficient in situ. Both techniques corresponded well in soil with pH<6. In soil with higher pH, both methods led to very different results. The reason is that pH has a strong impact on the calculation of the nitrification rate in the BaPS method. In nearly all experiments with neutral to alkaline soils, the BaPS technique yielded higher nitrification rates than the 15N-Pool dilution technique if pH was determined in 0.01 M CaCl2. With pH determined in water, there was good agreement or nitrification rates were too low. Fertilization with ammonium did not in-duce an increase of nitrification in a sandy soil with pH<6. A decrease in nitrification to less than 60% was achieved by the application of the nitrification inhibitor DCD. For both techniques a positive correlation between temperature and nitrification rates was found. There was no correlation between water filled pore space and nitrification rate.