Browsing by Person "Streck, Thilo"

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Assessment of hydrology and dynamics of pesticides in a tropical headwater catchment in Northern Thailand
(2013) Hugenschmidt, Cindy; Streck, Thilo
The dissertation deals with assessment of hydrology and the dynamics of pesticides in a tropical headwater catchment in northern Thailand. Rainfall and runoff characteristics are recorded and investigated, pesticide dynamics during single events are monitored and studied. Finally, a hydrological model is applied.
Bayesian multi-purpose modelling of plant growth and development across scales
(2024) Viswanathan, Michelle; Streck, Thilo
Crop models are invaluable tools for predicting the impact of climate change on crop production and assessing the fate of agrochemicals in the environment. To ensure robust predictions of crop yield, for example, models are usually calibrated to observations of plant growth and phenological development using different methods. However, various sources of uncertainty exist in the model inputs, parameters, equations, observations, etc., which need to be quantified, especially when model predictions influence decision-making. Bayesian inference is suitable for this purpose since it enables different uncertainties to be taken into account, while also incorporating prior knowledge. Thus, Bayesian methods are used for model calibration to improve the model and enhance prediction quality. However, this improvement in the model and its prediction quality does not always occur due to the presence of model errors. These errors are a result of incomplete knowledge or simplifying assumptions made to reduce model complexity and computational costs. For instance, crop models are used for regional scale simulations thereby assuming that these point-based models are able to represent processes that act at regional scale. Additionally, simple statistical assumptions are made about uncertainty in model errors during Bayesian calibration. In this work, the problems arising from such applications are analysed and other Bayesian approaches are investigated as potential solutions. A conceptually simple Bayesian approach of sequentially updating a maize phenology model, an important component in plant models, was investigated as yearly observation data were gathered. In this approach, model parameters and their uncertainty were estimated while accounting for observation uncertainty. As the model was calibrated to increasing amounts of observation data, the uncertainty in the model parameters reduced as expected. However, the prediction quality of the calibrated model did not always improve in spite of more data being available for potentially improving the model. This discrepancy was attributed to the presence of errors in the model structure, possibly due to missing environmental dependencies that were ignored during calibration. As a potential solution, the model was calibrated using Bayesian multi-level modelling which could account for model errors. Furthermore, this approach accounted for the hierarchical data structure of cultivars nested within maize ripening groups, thus simultaneously obtaining model parameter estimates for the species, ripening groups and cultivars. Applying this approach improved the model's calibration quality and further aided in identifying possible model deficits related to temperature effects in the post-flowering phase of development and soil moisture. As another potential solution, an alternative calibration strategy was tested which accounted for model errors by relaxing the strict statistical assumptions in classical Bayesian inference. This was done by first acknowledging that due to model errors, different data sets may yield diverse solutions to the calibration problem. Thus, instead of fitting the model to all data sets together and finding a compromise solution, a fit was found to each data set. This was implemented by modifying the likelihood, a term that accounts for information content of the data. An additive rather than the classical multiplicative strategy was used to combine likelihood values from different data sets. This approach resulted in conservative but more reliable predictions than the classical approach in most cases. The classical approach resulted in better predictions only when the prediction target represented an average of the calibration data. The above-mentioned results show that Bayesian methods with representative error assumptions lead to improved model performance and a more realistic quantification of uncertainties. This is a step towards the effective application of process-based crop models for developing suitable adaptation and mitigation strategies.
Bedeutung der Stickstoffumsetzung und externer Stickstoffquellen für die Entwicklung von FFH-Mähwiesen in Baden-Württemberg
(2023) Kukowski, Sina Louise; Streck, Thilo
1. AIM AND OBJECTIVES OF THE STUDY. The condition of the species-rich lowland hay meadows (habitat type 6510) in Germany is increasingly deteriorating. One cause of the deterioration is the supply of reactive nitrogen (N). To counteract the ongoing deterioration, it is necessary to understand the relationships between external N inputs via the atmosphere and fertilization, internal N turnover in the soil, plant uptake and growth, as well as possible links to the conservation degree of this habitat type. The overall objective of this dissertation is therefore to contribute to a better process-based understanding of the complete N cycle of Fauna-Flora-Habitat (FFH) meadows. 2. MATERIAL & METHODS. The interdisciplinary structure of this thesis includes different approaches to study inputs, turnover and outputs of N. With respect to N input via the airborne pathway, the focus was primarily placed on the hitherto poorly studied relationships between ammonia concentration and specific N-sensitive species groups in FFH lowland hay meadows. These relations were analyzed by means of generalized mixed models (GLM) based on nationwide data. In addition, further site-specific factors with a significant influence on the conservation degree of FFH meadows were identified using GLM. For the quantification of soil-borne N turnover processes, an empirical approach was chosen, including the determination of gross N turnover rates using the 15N isotope dilution method. To record these N dynamics, an intensive monitoring of gross and net N fluxes (mineralization, nitrification, ammonium consumption, nitrate consumption) in soils from different primary substrate and with different meadow conservation degree was carried out in 2016 and 2017. The results were merged using a process-based agroecosystem model (EXPERT-N), which was adjusted for habitat type 6510 to the collected data. The adapted model was applied to other sites of habitat type 6510 distributed throughout the state of Baden-Württemberg, which served to investigate spatial and temporal patterns of relevant nitrogen fluxes over an extended time period (1996 until 2012) and had been characterized in terms of soil and vegetation. 3. RESULTS. The nationwide data show a statistically significant decrease of habitat-typical low-nutrient indicator species and an increase of N indicator species with increasing atmospheric ammonia concentration on lowland hay meadows in Baden-Württemberg. Whether this is an effect of the atmospheric ammonia concentration or whether differences in agricultural land use structure play the decisive role could not be clarified with the available data. The intensive monitoring on selected FFH lowland hay meadows showed that soil-borne gross nitrification rates on soils from calcareous parent substrate (high pH) differed significantly from those from decalcified substrate (low pH). Both gross mineralization and gross nitrification were characterized by high temporal variability at all sites, which could not be explained by measurements of soil temperature and soil water content. Determination of net N turnover rates showed almost no variability and could not be used to draw conclusions about actual gross turnover rates in soil. The N-turnover model adapted for habitat type 6510 was able to represent spatial and temporal patterns over an extensive period of time. Simulation results showed high spatial and temporal variability for most N cycle variables. Soil organic N mineralization has a critical influence on the amount of plant-available N and thus has a direct impact on yield and N removal. On high clay-content soils and sites with high organic matter content, the model overestimated mineralization. External N inputs, such as moderate organic fertilization or atmospheric N deposition, were less crucial for yield. Additional N input is always a driving factor for N turnover in soil in the short term. With already high turnover levels, N turnover continues to increase and thus the risk of nutrient imbalances also increases. In the long term, the decisive factor for the N balance of FFH lowland hay meadows is whether N supply exceeds removal, whether the mineralizable organic N pools are thus increased, or whether a balance between supply and removal can be achieved. If soil internal N turnover is high, as it was the case on most of the simulated sites, a longer depletion phase should be applied before. In summary, this dissertation provides insight into the complexity of N cycling of FFH meadows. Using various approaches (statistical analyses, field trials, process-based modelling), it contributes to a better understanding of site-specific N turnover and the role of external N sources for the development of this ecosystem.
Comprehensive assessment of climate extremes in high-resolution CMIP6 projections for Ethiopia
(2023) Rettie, Fasil M.; Gayler, Sebastian; Weber, Tobias K. D.; Tesfaye, Kindie; Streck, Thilo
Climate extremes have more far-reaching and devastating effects than the mean climate shift, particularly on the most vulnerable societies. Ethiopia, with its low economic adaptive capacity, has been experiencing recurrent climate extremes for an extended period, leading to devastating impacts and acute food shortages affecting millions of people. In face of ongoing climate change, the frequency and intensity of climate extreme events are expected to increase further in the foreseeable future. This study provides an overview of projected changes in climate extremes indices based on downscaled high-resolution (i.e., 10 × 10 km2) daily climate data derived from global climate models (GCMs). The magnitude and spatial patterns of trends in the projected climate extreme indices were explored under a range of emission scenarios called Shared Socioeconomic Pathways (SSPs). The performance of the GCMs to reproduce the observed climate extreme trends in the base period (1983–2012) was evaluated, the changes in the climate projections (2020–2100) were assessed and the associated uncertainties were quantified. Overall, results show largely significant and spatially consistent trends in the projected temperature-derived extreme indices with acceptable model performance in the base period. The projected changes are dominated by the uncertainties in the GCMs at the beginning of the projection period while by the end of the century proportional uncertainties arise both from the GCMs and SSPs. The results for precipitation-related extreme indices are heterogeneous in terms of spatial distribution, magnitude, and statistical significance coverage. Unlike the temperature-related indices, the uncertainty from internal climate variability constitutes a considerable proportion of the total uncertainty in the projected trends. Our work provides a comprehensive insight into the projected changes in climate extremes at relatively high spatial resolution and the related sources of projection uncertainties.
Diagnosing similarities in probabilistic multi-model ensembles: An application to soil–plant-growth-modeling
(2022) Schäfer Rodrigues Silva, Aline; Weber, Tobias K. D.; Gayler, Sebastian; Guthke, Anneli; Höge, Marvin; Nowak, Wolfgang; Streck, Thilo; Schäfer Rodrigues Silva, Aline; Department of Stochastic Simulation and Safety Research for Hydrosystems, Institute for Modelling Hydraulic and Environmental Systems/Cluster of Excellence “Data-Integrated Simulation Science”, University of Stuttgart, Stuttgart, Germany; Weber, Tobias K. D.; Department of Biogeophysics, Institute of Soil Science and Land Evaluation, University of Hohenheim, Stuttgart, Germany; Gayler, Sebastian; Department of Biogeophysics, Institute of Soil Science and Land Evaluation, University of Hohenheim, Stuttgart, Germany; Guthke, Anneli; Junior Research Group for Statistical Model-Data Integration, Cluster of Excellence “Data-Integrated Simulation Science”, University of Stuttgart, Stuttgart, Germany; Höge, Marvin; Department of Systems Analysis, Integrated Assessment and Modelling, Eawag-Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland; Nowak, Wolfgang; Department of Stochastic Simulation and Safety Research for Hydrosystems, Institute for Modelling Hydraulic and Environmental Systems/Cluster of Excellence “Data-Integrated Simulation Science”, University of Stuttgart, Stuttgart, Germany; Streck, Thilo; Department of Biogeophysics, Institute of Soil Science and Land Evaluation, University of Hohenheim, Stuttgart, Germany
There has been an increasing interest in using multi-model ensembles over the past decade. While it has been shown that ensembles often outperform individual models, there is still a lack of methods that guide the choice of the ensemble members. Previous studies found that model similarity is crucial for this choice. Therefore, we introduce a method that quantifies similarities between models based on so-called energy statistics. This method can also be used to assess the goodness-of-fit to noisy or deterministic measurements. To guide the interpretation of the results, we combine different visualization techniques, which reveal different insights and thereby support the model development. We demonstrate the proposed workflow on a case study of soil–plant-growth modeling, comparing three models from the Expert-N library. Results show that model similarity and goodness-of-fit vary depending on the quantity of interest. This confirms previous studies that found that “there is no single best model” and hence, combining several models into an ensemble can yield more robust results.
Equifinality, sloppiness and emergent minimal structures of biogeochemical models
(2019) Marschmann, Gianna; Streck, Thilo
Process-based biogeochemical models consider increasingly the control of microorganisms on biogeochemical processes. These models are used for a number of important purposes, from small-scale (mm-cm) controls on pollutant turnover to impacts of global climate change. A major challenge is to validate mechanistic descriptions of microbial processes and predicted emergent system responses against experimental observations. The validity of model assumptions for microbial activity in soil is often difficult to assess due to the scarcity of experimental data. Therefore, most complex biogeochemical models suffer from equifinality, i.e. many different model realizations lead to the same system behavior. In order to minimize parameter equifinality and prediction uncertainty in biogeochemical modeling, a key question is to determine what can and cannot be inferred from available data. My thesis aimed at solving the problem of equifinality in biogeochemical modeling. Thereby, I opted to test a novel mathematical framework (the Manifold Boundary Approximation Method) that allows to systematically tailor the complexity of biogeochemical models to the information content of available data.
Improvement of the Barometric Process Separation (BaPS) technique to measure microbial C and N transformation rates in arable high-pH soils
(2023) Munz, Hannah; Streck, Thilo
The Barometric Process Separation (BaPS) technique provides a simple way to determine the rates of heterotrophic microbial respiration, gross nitrification and denitrification in soils by crossbalancing CO2 and O2 production and consumption rates in a closed incubation system via gas balances. The BaPS measuring system has some methodological limitations, especially in soils of pH above 6.5. In these soils, the CO2 balance of the incubation system is strongly influenced by abiotic fluxes driven by thermodynamic equilibration of the CO2 - carbonate system of the soil solution, i.e. a non-negligible fraction of CO2 produced via respiration is buffered by the soil solution. Correct quantification of this flux is necessary to correctly determine the microbial process rates. It has been shown that the thermodynamic calculation of CO2 dissolution does not deliver accurate results, leading to uncertainty in and considerable over- and underestimations of the microbial process rates. In this dissertation, this problem has been solved by developing a method to experimentally determine abiotic CO2 buffering, the Sterilization-CO2-Injection (SCI) method. Moreover, the soil specific adaptation of the Respiratory Quotient (RQ) has been studied in detail in order to reestablishes the advantage of the BaPS of operating isotope-free. Furthermore, in this dissertation we present an easy on-site calibration method for the BaPS sensor set in order to garantee optimal data quality although the maintenance service by the manufacturer has been canceled. Overall, the presented adaptations and improvements enhance the accuracy of BaPS measurements and might enhance its value as a tool for measuring gross nitrification rates in the future.
Measuring and modelling of soil water dynamics in two German landscapes
(2018) Poltoradnev, Maksim; Streck, Thilo
The soil water regime is focus of various disciplines including agricultural sciences, hydrology, weather forecast and climate modelling. As an inherent part of land surface exchange processes, the dynamics of soil water content (SWC) is simulated in distributed hydrological models and land surface models (LSM). The accuracy of the simulated SWC directly influences the simulation outcome and its performance. Biases in modelled temporal SWC dynamics and its spatial distribution lead to errors in evapotranspiration, runoff, cloud and precipitation simulations. The main objective of my thesis was to study the factors that control the SWC dynamics and its spatial variability. Long-term measurements from the soil moisture networks Kraichgau (KR) and Swabian Alb (SA) provided the data basis of this study. SWC was sensed based on the Time Domain Transmission (TDT) technique. In each region, 21 measuring locations were distributed across three spatial domains: an inner domain 3 km × 3 km (5 stations), a middle 9 km × 9 km (8 stations), and an outer domain 27 km × 27 km (8 stations). The sizes of the three domains correspond with typical grid sizes of coupled atmosphere-LSM models. All stations were mounted on cropped agricultural sites. Each station was equipped with a TDT sensor, installed 15 cm deep into the soil, a rain gauge and a remote transfer unit. After adjusting the sensor networks, an in-situ field calibration was performed to derive pedotransfer and site-specific calibrations for TDT soil moisture sensors. The chemical and physical analysis of soil samples collected at each station revealed that soil bulk density influences in both regions the TDT readings. Moreover, the pedotransfer calibrations included electrical conductivity in KR and silt fraction and organic nitrogen content on SA. These variables are relatively easy to measure. Accordingly, the pedotransfer calibrations derived in this study are a quick possibility to calibrate TDT sensors in areas with similar soil properties as in KR and SA. Nevertheless, the site-specific calibrations performed the best and were therefore used for further data analysis. In the second study, a three-year record of SWC and rainfall was evaluated. The response of the regional mean (theta) of SWC to a rain event was influenced by the seasonal water balance (SWB). In KR, the relation was more pronounced for positive SWB and less for neutral and negative SWB. On SA, where SWB was highly positive in all three years, the response of theta to rainfall was always strong. At the seasonal scale, the relationship between the spatial standard deviation of SWC (sigma) and theta was investigated through sigma-theta phase-space diagrams. The results show that with decreasing SWC sigma-theta data pairs are approaching sigma at the permanent wilting point (sigma-thetawp). With increasing SWC, in contrast, sigma-theta data pairs are moving towards sigma at saturation (sigma-thetas). These two points were termed anchor points. The sigma-theta relationships formed combinations of concave and convex hyperbolas reflecting the variability of soil texture and depending on sigma in relation to the anchor points. At the event scale, hysteresis in the sigma-theta was observed. Most sigma-theta clockwise hysteresis cases occurred at an intermediate and intermediate/wet state of SWC. Among the factors that trigger the initiation of a sigma-theta hysteretic loop, the present study revealed the following: rainstorms with spatially highly variable intensities (threshold rainfall intensity of 1.1 ± 0.6 mm and 2.9 ± 2.8 mm for KR and SA, respectively), preferential flow and, possibly, hysteresis in soil water retention curves. Based on these results, the following hypothesis was formulated: sigma-theta phase space diagrams are useful to test whether hydrological models or land surface models (LSMs) capture the realistic range of spatial soil water variability. The concept was tested with the Noah-MP LSM. Observations obtained from KR and SA soil moisture networks over a three-year period from 2010 to 2012 were used to build up the sigma-theta phase-space. The study included two different setups used to compute the hydraulic conductivity and the diffusivity: 1) the default setting: the Clapp and Hornberger approach, and 2) the van Genuchten-Mualem functions. The default model parameterization was stepwise substituted with site-specific rainfall, soil texture, leaf area index (LAI) and green vegetation fraction (GVF) data. The atmospheric forcing was obtained from eddy covariance stations located in the regions. Although the model matched observed temporal theta dynamics fairly well for the loess soils of KR, it performed poorly in the case of the shallow, clayey and stony soils of SA. The best match was achieved with the van Genuchten-Mualem functions and site-specific rainfall, soil texture, GVF and LAI. Nevertheless, the Noah-MP LSM failed to represent the spatial variability of SWC. In most cases, the simulated sigma-theta data points were located below the bottom edge of the envelope, which indicates that the model smooths spatial variability of soil moisture. This smoothing can be mainly attributed to missing topography and terrain information, inadequate representation of the spatial variability of soil texture and hydraulic parameters, and the model assumption of a uniform root distribution.
Microbial regulation of pesticide degradation coupled to carbon turnover in the detritusphere
(2015) Pagel, Holger; Streck, Thilo
Many soil functions, such as nutrient cycling or pesticide degradation, are controlled by microorganisms. Dynamics of microbial populations and biogeochemical cycling in soil are largely determined by the availability of carbon (C). The detritusphere is a microbial “hot spot” of C turnover. It is characterized by a concentration gradient of C from litter (high) into the adjacent soil (lower). Therefore, this microhabitat is very well suited to investigate the influence of C availability on microbial turnover. My thesis aimed at the improved understanding of biochemical interactions involved in the degradation of the herbicide 4-chloro-2-methylphenoxyacetic acid (MCPA) coupled to C turnover. In the detritusphere gradients of organic matter turnover from litter into the adjacent soil could be identified. Increased C availability, due to the transport of dissolved organic substances from litter into soil, resulted in the boost of microbial biomass and activity as well as in the acceleration of MCPA degradation. Fungi and bacterial MCPA-degraders benefited most from litter-C input. Accelerated MCPA degradation was accompanied by increased incorporation of MCPA-C into soil organic matter. The experimental results show that the transport of dissolved organic substances from litter regulates C availability, microbial activity and finally MCPA degradation in the detritusphere. In general, litter-derived organic compounds provide energy and resources for microorganisms. The following possible regulation mechanisms were identified: i) Litter might directly supply the co-substrate alpha-ketoglutarate (or surrogates) required for enzymatic oxidation of MCPA by bacterial MCPA degraders. Alternatively it might provide additional energy and resources for production and regeneration of the needed co-substrate. ii) Additional litter-C might alleviate substrate limitation of enzyme production by bacteria and bacterial consortia resulting in an increased activity of specific enzymes attacking MCPA. iii) Litter-derived organic substances might stimulate MCPA degradation via fungal co-metabolism by unspecific extracellular enzymes, either directly by inducing enzyme production, or by supplying primary substrates that provide the energy consumed by co-metabolic MCPA transformation. A new biogeochemical model abstracts these regulation mechanisms in such a way that C availability controls physiological activity, growth, death and maintenance of microbial pools. Based on a global sensitivity analysis, 41% (n=33) of all considered parameters and input values were classified as “very important” and “important”. These mainly include biokinetic parameters and initial values. The calibration of the model allowed to validate the implemented regulation mechanisms of accelerated MCPA degradation. The Pareto-analysis showed that the model structure was adequate and the identified parameter values were reasonable to reproduce the observed dynamics of C and MCPA. The model satisfactorily matched observed abundances of gene-markers of total bacteria and specific MCPA degraders. However, it underestimated the steep increase of fungal ITS fragments, most probably because this gene-marker is only inadequately suited as a measure of fungal biomass. The model simulations indicate that soil fungi primarily benefit from low-quality C, whereas bacterial MCPA-degraders preferentially use high-quality C. According to the simulations, MCPA was predominantly transformed via co-metabolism to high-quality C. Subsequently, this C was primarily assimilated by bacterial MCPA-degraders. The highest turnover of litter-derived C occurred by substrate uptake for microbial growth. Input and microbial turnover of litter-C stimulated MCPA degradation mainly in a soil layer at 0-3 mm distance to litter. As a consequence of this, a concentration gradient of MCPA formed, which triggered the diffusive upward transport of MCPA from deeper soil layers into the detritusphere. The results of the three studies suggest: The detritusphere is a biogeochemical hot spot where microbial dynamics control matter cycling. The integrated use of experiments and mathematical modelling gives detailed insight into matter cycling and dynamics of microorganisms in soil. Microbial communities need to be explicitly considered to understand the regulation of soil functions.
Micronutrients, silicon and biostimulants as cold stress protectants in maize
(2020) Moradtalab, Narges; Streck, Thilo
Mitigation of abiotic stress in crops is a feature attributed to various so-called biostimulants based on plant growth-promoting microorganisms (PGPMs) plant-, compost- and seaweed extracts, protein hydrolylates, chitosan derivatives etc. but also to mineral nutrients with protective functions, such as zinc (Zn), manganese (Mn), boron (B), calcium (Ca) and silicon (Si), recommended as stress protectants in commercial formulations. This study focussed on the effects of selected biostimulants on cold stress mitigation during early growth in maize, as a major stress factor for cultivation of tropical and subtropical crops in temperate climates. Chilling stress and micronutrient supplementation Chilling stress, induced by moderately low soil temperatures (8-14°C) in a controlled root cooling system, was associated with inhibition of shoot growth, oxidative leaf damage (chlorosis, necrosis accumulation of stress anthocyanins) and a massive decline in root length (Chapter 4 and 5). Due to inhibition of root growth, nutrient acquisition in general was impaired. However, nutrient deficiencies were recorded particularly for the micronutrients zinc (Zn) and manganese (Mn). The impaired Zn and Mn status was obviously related with the observed limitations in plant performance, which were reverted by exogenous Zn and Mn supplementation (0.5 mg plant-1), finally leading to restored nutrient acquisition and improved plant recovery after termination of the cold stress period. Zinc and manganese deficiency was mainly related with impaired uptake of the micronutrients, since the cold stress-induced deficiency symptoms persisted even in hydroponic culture when all nutrients were freely available. Beneficial effects of Zn/Mn supplementation were only detectable when the micronutrients were supplied prior to the onset of the stress period via seed soaking, seed dressing or fertigation, when uptake and internal translocation was still possible. A transcriptome analysis of the shoot tissue (Chapter 5) revealed 1400 differentially expressed transcripts (DETs) after 7-days exposure of maize seedlings to chilling stress of 12°C, mostly associated with down-regulation of selected functional categories (BINs), related with photosynthesis, synthesis of amino acids, lipids and cell wall precursors, transport of mineral nutrients (N, P, K,), metal handling and synthesis of growth hormones (auxins, gibberellic acid) but also of jasmonic (JA) and salicylic acids (SA) involved in stress adaptations. In accordance with the impaired micronutrient status and oxidative leaf damage in response to the cold stress treatments, downregulation was also recorded for transcripts related with oxidative stress defence (superoxide dismutases SOD, catalase, peroxidases POD, synthesis of phenylpropanoids and lignification), particularly dependent on the supply of micronutrients as co-factors. Upregulation was recorded for BINs related with degradation of lipids, of cell wall precursors, synthesis of waxes and certain flavonoids and of stress hormones, such as abscisic acid (ABA) and ethylene but degradation of growth-promoting cytokinins (CK). Accordingly, supplementation of Zn and Mn increased the accumulation of anthocyanins and antioxidants, the activities of superoxide dismutase and peroxidases, associated with reduced ROS accumulation (H2O2), mitigation of oxidative leaf damage and improved plant recovery at the end of the cold stress period (Chapter 5 and 6). Effects of seaweed extracts Cold-protective properties similar to Zn/Mn supplementation, associated with an improved Zn/Mn-nutritional status and reduced oxidative damage, were recorded also after fertigation with seaweed extracts prior to the onset of the stress treatments (Chapter 4). However, this effect was detectable only with seaweed extract formulations rich in Zn/Mn (Algavyt+Zn/Mn; Algafect; 6-70 mg kg DM-1) but not with a more highly purified formulation (Superfifty) without detectable micronutrient contents. This finding suggests that the cold-protective effect by soil application of seaweed extracts is based on an improved micronutrient supply and not to an elicitor effect, frequently reported in the literature for stress-protective functions after foliar application of seaweed extracts. Silicon fertilization Similar to seaweed extracts, also silicon (Si), applied by seed soaking or fertigation with silicic acid, mimicked the cold-protective effects of Zn/Mn supplementation in maize seedlings (Chapter 5). The Zn/Mn status of the Si-treated plants was improved although, in this case no additional micronutrient supply was involved. However, Si application significantly reduced leaching losses of Zn/and Mn by 50-70%, as a consequence of cold stress-induced membrane damage in germinating maize seeds and favoured the root to shoot translocation of Zn. This was associated with a restoration of gene expression, similar to the profiles recorded for unstressed control plants. However, the expression of genes related with synthesis and signal transduction of ABA, as central regulator of adaptive cold stress responses in plants, was even more strongly upregulated than in the cold-stressed controls. Accordingly, expression of cold stress adaptations involved in oxidative stress defence (SOD, peroxidases, phenolics, antioxidants) and the reduction of oxidative leaf damage and improved plant recovery were similar to the plants with Zn/Mn supplementation. Plant growth promoting microorganisms Cold-protective functions were recorded also for selected microbial inoculants (Chapter 6). However, out of five tested inoculant formulations, based on strains of Pseudomonas sp., DSMZ13134, Bacillus amyloliquefaciens FZB42, Bacillus atrophaeus ABI05, Penicillium sp. PK112 (BFOD) and a consortium of Trichoderma harzianum OMG16 and five Bacillus strains (Combi-A), a significant protective effect was detectable only for Penicillium sp. and particularly for CombiA. The CombiA consortium significantly increased root length and reduced oxidative leaf damage of cold-stressed plants, associated with increased SOD and POD activities and accumulation of phenolics and antioxidants. Root growth stimulation was related with increased IAA (indole acetic acid) tissue contents and increased expression of genes involved in IAA biosynthesis (ZmTSA) transport (ZmPIN1A) and perception (ZmAFR12). The tissue concentrations of ABA were not affected by the microbial inoculants, but the shoot concentrations of JA and SA increased, suggesting an effect by induced systemic resistance (ISR). Moreover, root concentrations of cytokinins (CKs) as ABA antagonists and expression of IPT genes involved in CK biosynthesis declined, leading to an increased ABA/cytokinin ratio and accordingly to increased expression of ABA responsive genes (ZmABF2). These findings suggest that CombiA mainly acted via improvement of root growth and nutrient acquisition by activation of the plant auxin metabolism and activation of cold protective metabolic responses by induction of ISR via JA/SA signalling and ABA-mediated responses, due to inhibition of CK biosynthesis. Synergistic interactions While the different cold-stress protectants investigated in this study induced similar protective plant responses, synergistic effects were obtained by combined applications (Chapter 6). The combination of CombiA inoculation with Zn/Mn supplementation further increased the plant micronutrient status and the cold-protective effects of CombiA. For all treatments, generally the expression of cold-protective effects was further improved by use of DMPP-stabilized ammonium fertilizers instead of nitrate fertilization. Ammonium fertilization promoted micronutrient acquisition via root-induced rhizosphere acidification, increased the ABA shoot concentrations with a moderate activation of metabolic cold stress responses and stimulated root colonization of Trichoderma harzianum OMG16 (CombiA). Field performance A comparative evaluation of the various cold protectants under field conditions with stabilized ammonium starter fertilization, revealed a severely reduced seedling emergence at six weeks after sowing (44%) due to extremely cold and wet soil conditions by the end of April in 2016, associated with a low Zn-nutritional status (32 mg kg-1 shoot DM). Significant improvements were recorded particularly for starter treatments including Zn/Mn seed dressing (emergence 56%) or seed priming with K2SiO4 (emergence 72%) and also by inoculation with the fungal PGPM strain Penicillium sp. BFOD (emergence 49%) associated with a doubling of the Zn tissue concentrations. Even after re-sowing, a significant yield increase for silo maize was recorded exclusively for the K2SiO4 treatment (Chapter 5). Taken together, the findings suggest that exploitation of synergistic interactions by combined starter applications of protective nutrients with selected biostimulants, could offer a cost-effective option for cold-stress prophylaxis in sensitive crops.
Modeling microbial regulation of pesticide turnover in soils
(2022) Chavez Rodriguez, Luciana; Streck, Thilo
Pesticides are widely used for pest control in agriculture. Besides their intended use, their long-term fate in real systems is not well understood. They may persist in soils, thereby altering ecosystem functioning and ultimately affecting human health. Pesticide fate is assessed through dissipation experiments in the laboratory or the field. While field experiments provide a close representation of real systems, they are often costly and can be influenced by many unknown or uncontrollable variables. Laboratory experiments, on the other hand, are cheaper and have good control over the governing variables, but due to simplification, extrapolation of the results to real systems can be limited. Mechanistic models are a powerful tool to connect lab and field data and help us to improve our process understanding. Therefore, I used mechanistic, process-based models to assess key microbial regulations of pesticide degradation. I tested my model hypotheses with two pesticide classes: i) chlorophenoxy herbicides (MCPA (2-methyl-4-chlorophenoxyacetic acid) and 2,4-D (2,4-Dichlorophenoxyacetic acid)), and ii) triazines (atrazine (AT)), in an ideal scenario, where bacterial degraders and pesticides are co-localized. This thesis explores some potential controls of pesticide degradation in soils: i) regulated gene expression, ii) mass-transfer process across the bacterial cell membranes, iii) bioenergetic constraints, and iv) environmental factors (soil temperature and moisture). The models presented in this thesis show that including microbial regulations improves predictions of pesticide degradation, compared to conventional models based on Monod kinetics. The gene-centric models achieved a better representation of microbial dynamics and enable us to explore the relationship between functional genes and process rates, and the models that used transition state theory to account for bioenergetic constraints improved the description of degradation at low concentrations. However, the lack of informative data for the validation of model processes hampered model development. Therefore, in the fourth part of this thesis, I used atrazine with its rather complex degradation pathway to apply a prospective optimal design method to find the optimal experimental designs to enable us identifying the degradation pathway present in a given environment. The optimal designs found suggest to prioritize determining metabolites and biomass of specific degraders, which are not typically measured in environmental fate studies. These data will lead to more robust model formulations for risk assessment and decision-making. With this thesis, I revealed important regulations of pesticide degradation in soils that help to improve process understanding and model predictions. I provided simple model formulations, for example the Hill function for gene expression and transition state theory for bioenergetic growth constraints, which can easily be integrated into biogeochemical models. My thesis covers initial but essential steps towards a predictive pesticide degradation model usable for risk assessment and decision-making. I also discuss implication for further research, in particular how mechanistic process-based modeling could be combined with new technologies like omics and machine learning.
Multi-objective and multi-variate global sensitivity analysis of the soil-crop model XN-CERES in Southwest Germany
(2021) Witte, Irene; Streck, Thilo
Soil-crop models enjoy ever-greater popularity as tools to assess the im- pact of environmental changes or management strategies on agricultural production. Soil-crop models are designed to coherently simulate the crop, nitrogen (N) and water dynamics of agricultural fields. However, soil-crop models depend on a vast number of uncertain model inputs, i.e., initial conditions and parameters. To assess the uncertainty in the simulation results (UCSR) and how they can be apportioned among the model inputs of the XN-CERES soil-crop model, an uncertainty and global sensitivity analysis (GSA) was conducted. We applied two different GSA methods, moment-independent and variance-based methods in the sense of the Factor Prioritization and the Factor Fixing setting. The former identifies the key drivers of uncertainty, i.e., which model input, if fixed to its true value, would lead to the greatest reduction of the UCSR. The latter identifies the model inputs that cannot be fixed at any value within their value range without affecting the UCSR. In total we calculated six sensitivity indices (SIs). The overall objective was to assess the cross-sub-model impact of parameters and the overall determinability of the XN-CERES applied on a deep loess soil profile in Southwest Germany. Therefore, we selected 39 parameters and 16 target variables (TGVs) to be included in the GSA. Furthermore, we assessed a weekly time series of the parameter sensitivities. The sub-models were crop, water, nitrogen and flux. In addition, we also compared moment-independent (MI) and variance-based (VB) GSA methods for their suitability for the two settings. The results show that the parameters of the TGVs of the four groups cannot be considered independently. Each group is impacted by the parameters of the other groups. Crop parameters are most important, followed by the Mualem van Genuchten (MvG) parameters. The nitrate (NO3-) content and the matric potential are the two TGVs that are most affected by the inter- action of parameters, especially crop and MvG parameters. However, the model output of these two TGVs is highly skewed and leptokrutic. Therefore, the variance is an unsuitable representation of the UCSR, and the reliability of the variance-based sensitivity indices SIVB is curtailed. Nitrogen group parameters play an overall minor role for the uncertainty of the whole XN-CERES, but nitrification rates can be calibrated on ammonium (NH4+) measurements. Considering the initial conditions shows the high importance of the initial NO3-; content. If it could be fixed, the uncertainty of crop groups’ TGVs, the matric potential and the N content in the soil could be reduced. Hence, multi-year predictions of yield suffer from uncertainty due to the simulated NO3-; content. Temporally resolved parameter show the big dependence between the crop’s development stage and the other 15 TGVs becomes visible. High temporally resolved measurements of the development stage are important to univocally estimate the crop parameters and reduce the uncertainty in the vegetative and generative biomass. Furthermore, potential periods of water and N-limiting situations are assessed, which is helpful for deriving management strategies. In addition, it become clear that measurement campaigns should be conducted at the simulation start and during the vegetation period to have enough information to calibrate the XN-CERES. Regarding the performance of the different GSA methods and the different SIs, we conclude that the sensitivity measure relying on the Kolmogorov-Smirnov metric (betaks) is most stable. It converges quickly and has no issues with highly skewed and leptokrutic model output distributions. The assessments of the first-effect index and the betaks provide information on the additivity of the model and parameters that cannot be fixed without impacting the simulation results. In summary, we could only identify three parameters that have no direct impact on any TGV at any time and are hence not determinable from any measurements of the TGVs considered. Furthermore, we can conclude that the groups’ parameters should not be calibrated independently because they always affect the uncertainty of the selected TGV directly or via interacting. However, no TGV is suitable to calibrate all parameters. Hence, the calibration of the XN-CERES requires measurements of TGVs from each group, even if the modeler is only interested in one specific TGV, e.g., yield. The GSA should be repeated in a drier climate or with restricted rooting depth. The convergence of the values for the Sobol indices remains an issue. Even larger sample sizes, another convergence criteria or graphical inspection cannot alleviate the issue. However, we can conclude that the sub-models of the XN-CERES cannot be considered in- dependently and that the model does what it is designed for: coherently simulating the crop, N and water dynamics with their interactions.
Nitrogen dynamics of grassland soils with differing habitat quality: high temporal resolution captures the details
(2023) Kukowski, Sina; Ruser, Reiner; Piepho, Hans‐Peter; Gayler, Sebastian; Streck, Thilo
Excessive nitrogen (N) input is one of the major threats for species‐rich grasslands. The ongoing deterioration of habitat quality highlights the necessity to further investigate underlying N turnover processes. Our objectives were (1) to quantify gross and net rates of mineral N production (mineralization and nitrification) and consumption in seminatural grasslands in southwest Germany, with excellent or poor habitat quality, (2) to monitor the temporal variability of these processes, and (3) to investigate differences between calcareous and decalcified soils. In 2016 and 2017, gross N turnover rates were measured using the 15N pool dilution technique in situ on four Arrhenatherion meadows in biweekly cycles between May and November. Simultaneously, net rates of mineralization and nitrification, soil temperature, and moisture were measured. The vegetation was mapped, and basic soil properties were determined. The calcareous soils showed higher gross nitrification rates compared with gross mineralization. In contrast, nitrification was inhibited in the decalcified soils, most likely due to the low pH, and mineralization was the dominant process. Both mineralization and nitrification were characterized by high temporal variability (especially the former) and short residence times of N in the corresponding pools (<2 days) at all sites. This illustrates that high temporal resolution is necessary during the growing season to detect N mineralization patterns and capture variability. Parallel determination of net N turnover rates showed almost no variability, highlighting that net rates are not suitable for drawing conclusions about actual gross turnover rates. During the growing season, the data show no clear relationship between soil temperature/soil moisture and gross N turnover rates. For future experiments, recording of microbial biomass, dissolved organic matter, and root N uptake should be considered.
Reducing uncertainty in prediction of climate change impacts on crop production in Ethiopia
(2024) Rettie, Fasil Mequanint; Streck, Thilo
Ethiopia, with an economy heavily reliant on agriculture, is among the countries most vulnerable to climate change. It faces recurrent climate extreme events that result in devastating impacts and acute food shortages for millions of people. Studies that focus on their influence on agriculture, especially crop productivity, are of particular importance. However, only a few studies have been conducted in Ethiopia, and existing studies are spatially limited and show considerable spatial invariance in predicted impacts, as well as discrepancies in the sign and direction of impacts. Therefore, a robust, regionally focused, and multi-model assessment of climate change impacts is urgently needed. To guide policymaking and adaptation strategies, it is essential to quantify the impacts of climate change and distinguish the different sources of uncertainty. Against this backdrop, this study consisted of several key components. Using a multi-crop model ensemble, we began with a local climate change impact assessment on maize and wheat growth and yield across three sites in Ethiopia . We quantified the contributions of different sources of uncertainty in crop yield prediction. Our results projected a of 36 to 40% reduction in wheat grain yield by 2050, while the impact on maize was modest. A significant part of the uncertainty in the projected impact was attributed to differences in the crop growth models. Importantly, our study identified crop growth model-associated uncertainty as larger than the rest of the model components. Second, we produced a high-resolution daily projections database for rainfall and temperature to serve the requirement for impact modeling at regional and local levels using a statistical downscaling technique based on state-of-the-art GCMs under a range of emission scenarios called Shared Socioeconomic Pathways (SSPs). The evaluated results suggest that the downscaling strategy significantly reduced the biases between the GCM outputs and the observation data and minimized the errors in the projections. Third, we explored the magnitude and spatial patterns of trends in observed and projected changes in climate extremes indices based on downscaled high-resolution daily climate data to serve as a baseline for future national or regional-level impact assessment. Our results show largely significant and spatially consistent trends in temperature-derived extreme indices, while precipitation-related extreme indices are heterogeneous in terms of spatial distribution, magnitude, and statistical significance coverage. The projected changes in temperature-related indices are dominated by the uncertainties in the GCMs, followed by uncertainties in the SSPs. Unlike the temperature-related indices, the uncertainty from internal climate variability constitutes a considerable proportion of the total uncertainty in the projected trends. Fourth, we examined the regional-scale impact of climate change on maize and wheat yields by crop modeling, in which we calibrated and validated three process-based crop models to guide the design of national-level adaptation strategies in Ethiopia. Our analysis showed that under a high-emissions scenario, the national-level median wheat yield is expected to decrease by 4%, while maize yield is expected to increase by 2.5% by the end of the century. The CO2 fertilization effect on the crop simulations would offset the projected negative impact. Crop model spread followed by GCMs was identified as the largest contributor to overall uncertainty to the estimated yield changes. In summary, our study quantifies the impact of climate change and demonstrates the importance of a multi-model ensemble approach. We highlight the significant impacts of climate change on wheat yield in Ethiopia and the importance of crop model improvements to reduce overall uncertainty in the projected impact.
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.
The role of Phragmites australis in carbon, water and energy fluxes from a fen in southwest Germany
(2019) van den Berg, Merit; Streck, Thilo
The global carbon emission from peat soils adds up to 0.1 Gt-C per year. Under anaerobic conditions, organic material is decomposed to methane (CH4). Over a 100-year cycle, methane is a 28 times stronger greenhouse gas than carbon dioxide and is an important factor for climate change. Therefore, there is a great interest to get a better understanding of the carbon flows in peatlands. Phragmites peatlands are particularly interesting due to the global abundance of this wetland plant (Phragmites australis, common reed) and the highly efficient internal gas transport mechanism. This is a humidity-induced convective flow (HIC) to transport oxygen (O2) to the roots and rhizomes, with the effect that simultaneously soil gases (CH4 and CO2) can be transported to the atmosphere via the plant. Thereby, Phragmites is expected to have a high evapotranspiration (ET) rate due to the large leaf area, open water habitat and high aerodynamic roughness. This ET could highly influence the hydrology of the system. Because he accumulation of organic material occurs because of limiting oxygen levels, hydrological processes are fundamental in the development of peatlands. The research aims were: 1) to clarify the effect of plant-mediated gas transport on CH4 emission, 2) to find out whether Phragmites peatlands are a net source or sink of greenhouse gases, and 3) to evaluate ET in perspective of surface energy partitioning and compare results with FAO’s Penman-Monteith equation. CO2, CH4 and latent and sensible energy fluxes were measured with the eddy covariance (EC) technique within a Phragmites-dominated fen in southwest Germany in 2013, 2014 and 2016. In 2016, a field experiment was set up to quantify the contribution of plant-mediated CH4 transport to the overall CH4 flux and how it influences ebullition. One year of EC flux data (March 2013–February 2014) shows very clear diurnal and seasonal patterns for both CO2 and CH4. The diurnal pattern of CH4 fluxes was only visible when living green reed was present. This diurnal cycle had the highest correlation with global radiation, which suggests a high influence of HIC on CH4 emission. But if the cause were HIC, relative humidity should correlate stronger with CH4 flux. Therefore, we conclude that in addition to HIC at least one other mechanism must have been involved in the creation of the convective flow within the Phragmites plants. We quantified the influence of pressurized flow within Phragmites on total CH4 emission in a field experiment (see chapter 3) and found between 23% and 45% lower total CH4 flux when pressurized flow was excluded (by cutting or cutting and sealing the reed). The gas transport pathways from the soil to the atmosphere changed as well. Relative contribution of ebullition to the total flux increased from 2% in intact Phragmites to 24-37% in cut vegetation. This increase in ebullition in cut vegetation, obviously, did not compensate the excluded pathway via the pressurized air flow at our site. It also means that the effect of CH4 bypassing the oxic water layer by plant transport on CH4 emission is much larger than the effect of O2 transport through the plants on CH4 oxidation and production in the rhizosphere. Overall, the fen was a sink for carbon and greenhouse gases in the measured year, with a total carbon uptake of 221 g C m-2 yr-1 (26% of the total assimilated carbon). The net uptake of greenhouse gases was 52 g CO2 eq.m-2 yr-1, which is obtained from an uptake of CO2 of 894 g CO2 m-2 yr-1 and a release of CH4 of 842 g CO2 eq.m-2 yr-1. Compared to the long term uptake of carbon by northern peatlands (20–50 g C m-2 yr-1) 212 g C yr-1 is therefore very high. One year of measurements is not enough to draw hard conclusions about the climate change impact of this peatland. The measured ET at our site was lower than other Phragmites wetlands in temperate regions. ET was half the amount of precipitation (see chapter 4). Therefore, the risk of the wetland to dry out is not realistic. ET was especially low when there was little plant activity (May and October). Then, the dominant turbulent energy flux was sensible heat not latent heat. This can be explained by the high density of dead reed in these months. the reed heats up causing a high sensible heat flux. Evaporation was low due to the shading of the water layer below the canopy and low wind velocities near the surface. FAO’s Penman-Monteith equation was a good estimator of measured ET with crop factors from the regression model of Zhou and Zhou (2009) (see chapter 4). Especially the day-to-day variation was modeled very well. Their model had air temperature, relative humidity and net radiation as input variables. This is likely related to stomatal resistance, which depends on the same variables. Therefore, the model of Zhou and Zhou (2009) is an interesting tool for calculating daily crop factors and it is probably robust enough to be used also in different regions.
Towards a better understanding of land surface exchange processes over agricultural crop stands
(2020) Bohm, Kristina; Streck, Thilo
Weather and climate models are useful tools for projecting the influence of global climate change on the regional scale. These models are critically dependent on an accurate representation of soil-plant-atmosphere interactions, which are simulated by Land Surface Models (LSMs). The present PhD thesis was designed to improve the representation of land surface exchange processes of croplands in the Noah-MP land surface model. This thesis aims: a) to elucidate the nature of the energy imbalance over a winter wheat stand and to identify the appropriate post-closure method for the study region Kraichgau, southwest Germany; b) to improve the representation of the green vegetation fraction (GVF) dynamics of croplands in the Noah-MP for a more accurate computation of surface energy and water fluxes; and c) to determine the effect of aggregating different crop types with various shares into a single generic cropland class on the simulation of water and energy exchange between land surface and atmosphere.
Transport of pesticides in a river of a tropical mountainous watershed in northern Thailand
(2013) Sangchan, Walaya; Streck, Thilo
In the northern region of Thailand, in the upland areas population growth and migration of people from the lowlands have rapidly driven land use changes. The expansion of cultivation to increasingly vulnerable areas such as the slopes of mountainous watersheds has led to increasingly adverse impacts on the environment. In particular, intensive application of pesticides poses a contamination risk for stream water and the aquatic ecosystem. This thesis identified the transport patterns of pesticides with different physico-chemical properties during single runoff events under farmer?s practice conditions on the catchment scale. Moreover, the exposure concentrations of frequently used pesticides in surface water and sediment in the watershed were measured in the frame of long-term monitoring. The data were used to calculate pesticide loads in the Mae Sa watershed (Chiang Mai, Thailand) and to assess the ecological risk of pesticides for the aquatic ecosystems. Prior to start of the monitoring program, methods to extract and analyze pesticides in the surface water and sediment samples were established. The pesticides in water samples were extracted by solid phase extraction with a graphitized carbon black sorbent. The recoveries of pesticides in a simultaneous analysis ranged from 58 % to 117 % for the seven pesticides (dichlorvos, atrazine, dimethoate, chlorothalonil, chlorpyrifos, (α, β) endosulfan, cypermethrin) with a high repeatability of the method (Relative Standard Deviation, (RSD)<20 %), except for chlorothalonil (RSD=27 %). For analysis of sediments, the QuEChERS method was adapted. Extraction conditions such as solvent, partitioning of pesticide due to salt effect and clean up step with dispersive solid phase extraction were optimized. Except for dichlorvos in the bed sediment sample and for dimethoate in bed and suspended sediments, recoveries were between 81 % and 116 %. The results show that the QuEChERS method is a valuable method for extracting pesticides from sediment samples. To identify the transport pathways contributing to pesticide losses from soil to the Mae Sa River, automatic gauging stations were installed at the headwater (HW) and outlet (OL) of the watershed to measure discharge and to collect water samples for pesticide analysis. During three runoff events in May, August and September 2008, water samples were collected in a high temporal resolution (1 hour). The potential transport pathways of pesticides were elucidated by time series analysis. Three different input patterns of pesticides were observed: (a) pesticide peaks during the rainfall events as discharge increased, (b) sporadic high concentrations of pesticides during the falling limb of the runoff peak, and (c) low concentrations but more or less continuous values on a baseline level. A chromatographic effect was observed for many pesticides, for example between dimethoate and chlorpyrifos. Highly mobile pesticides such as atrazine and dimethoate were likely to suffer loss at the beginning of the runoff event, while strongly sorbing pesticides such as chlorpyrifos were slightly delayed. This indicates an interaction with the soil matrix, during transport along a sub-surface pathway. The results obtained in the middle of the rainy season in August and September events showed that antecedent rainfall plays an important role in triggering pesticide transport by preferential interflow. In both events the sporadic appearances of strongly sorbing pesticides such as chlorothalonil and chlorpyrifos after peak flow suggest this transport type. For ecotoxicological risk assessment, the highly dynamic nature of pesticide input to surface waters must be considered in the design of representative monitoring schemes. Not only the periods during rain event and peak runoff, but also the following recession phase, during which short and pulsed concentration peaks might show up, must be captured by a representative sampling scheme. Therefore, a high temporal resolution is advisable. To study the long-term dynamics of seven selected pesticides in the Mae Sa River and to evaluate their environmental impacts to aquatic organisms, the exposure concentrations of the pesticides in water and sediment samples were monitored at three stations (HW, Mae Sa Noi flume (MSN), and OL) in the watershed over a period of one and half year (from July 2007 to November 2008). Aquatic risk assessment concerning the observed pesticide concentrations was performed by using the risk characterization ratio (RCR). Chlorpyrifos was the most frequently detected pesticide in surface water at the HW and OL. Cypermethrin was the most frequently detected pesticide in bed and suspended sediment samples along the Mae Sa Noi tributary and at the HW. Regarding the change of pesticide use in the area (compared with data recored in 2002), the measurements suggest that the use of endosulfan has been reduced in recent years, while the observed concentrations of chlorothalonil and chlorpyrifos were in the same concentration ranges as in 2002. The temporal distribution of pesticides shows that the concentrations are highest during the rainy season. Outstandingly high losses of dichlorvos and atrazine were found at Mae Sa Noi flume. Loads of chlorothalonil and chlorpyrifos in stream water were extremely high in the headwater area. Based on interview data of pesticide use in the Mae Sa watershed, in both years the losses of single pesticides to surface water ranged from 0.004 % (chlorothalonil) to 4.7 % (dimethoate) of the applied pesticide mass. The loss of atrazine could not be included because the data did not contain information on the application rate of atrazine. The risk assessment shows that particularly dichlorvos and endosulfan have a high potential to cause adverse effects to the aquatic ecosystem. The RCRs of endosulfan and cypermethrin show that they are the main stressors in the sediment phase. This reveals that aquatic ecosystem of the Mae Sa watershed is facing adverse effects by the contamination of surface water and sediment with pesticides. Hence, measures are urgently needed to reduce the loss of pesticides from soil to surface waters.
Turbulent exchange of energy, water and carbon between crop canopies and the atmosphere : an evaluation of multi-year, multi-site eddy covariance data
(2019) Eshonkulov, Ravshan; Streck, Thilo
The increase of anthropogenic CO2 emissions and other greenhouse gases has raised concern about climate change. Climate change has manifold impacts on yield and yield quality, crop rotations, carbon and nitrogen cycling, water regime and agricultural production systems. To understand its consequences on environmental systems, measuring the matter and energy exchange at the land surface provides data to help validate and inform a wide range of process models. Such flux measurements at the land-surface provide an opportunity to test simulations of processes in the soil-plant-atmosphere continuum. Currently, such measurements are mainly based on the eddy covariance (EC) method, for the quality of which the energy balance closure (EBC) is a problem. The EBC significantly influences the calibration and validity of land-surface models, especially in regard to the energy and water balance at the Earth’s surface. The EBC quantifies the deviation between turbulent fluxes and available energy. It is crucial to obtain high-quality EC measurements to determine the reasons for the EBC. The research aims of this dissertation were: 1) to clarify the role of minor storage and flux terms in the energy balance, 2) to determine the possible reasons for the energy imbalance using a long-term dataset (2010-2017) from agricultural croplands, and 3) to investigate the effects of region, site, year and crop type on carbon fluxes and budgets. In the first study (Chapter 2) the contribution of minor storage terms to the EBC were investigated. I also determined the contribution of ground heat fluxes calculated by different methods. A harmonic analysis method was used to calculate ground heat fluxes from measurements of heat flux plates and soil temperature sensors. Soil heat storage and enthalpy change in the plant canopy were determined at different locations within the EC footprint. Considering minor storage terms improved the energy balance closure on average by 5.0 % in 2015 and by 6.8 % in 2016. The greatest energy balance closure improvement occurred in May of both study years. The dominant fraction of minor energy storage was energy uptake and release through photosynthesis and respiration. Additionally, the energy fluxes related to soil temperature change were also observed. The ground heat flux calculated by harmonic analysis from soil heat flux plates narrowed the EBC by 3 % compared to the calorimetric method. The results indicated that the typical correction approach to achieve energy balance closure, i.e. the Bowen-ratio method, overestimated the turbulent fluxes. The second study (Chapter 3) investigated the effects of crop type, site characteristics, wind directions, atmospheric conditions and footprint on the EBC. The long-term evaluation of EC measurements showed that, with the EC method, 25 % of the available energy could not be detected. Decreasing the flux footprint area increases the chance of a more homogeneous area. Homogeneity plays an important role in achieving a better energy balance closure. The synthesis of long-term EC data indicated that the sonic anemometer is very sensitive to orientation, not allowing accurate measurements from all wind directions. Discarding the measurements from wind directions 0° and 90° at EC4 improved the EBC from 80 to 84 %. In the third study, presented in Chapter 4, a long-term and multi-site experiment was evaluated to clarify the effects of site, year and region on the CO2 fluxes and budgets in agroecosystems. The net ecosystem exchange of CO2 fluxes – measured on six sites during eight years – was comprehensively examined. Winter rapeseed had the lowest CO2 uptake, cropping of silage maize resulted in the highest C losses. The management of harvest residues was the most effective means of controlling the C budgets. Comparing the CO2 fluxes processed with the recently developed ogive optimization method versus the conventional calculation showed that eliminating low-frequency contributions had a considerable effect. On average, the ogive optimization method delivered 6.9 % higher net ecosystem exchange rates than the conventional method. This dissertation provides new insights into how to obtain better measurements of matter and energy fluxes from EC measurements by a) considering storage terms otherwise neglected, b) using harmonic analysis for calculating ground heat fluxes, c) discarding fluxes from behind the anemometer and d) applying the ogive optimization method.
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.