Im Fokus der Untersuchungen steht das hydrologische Einzugsgebiet der oberen Wilzsch im Westerzgebirge. Veränderte Stoffausträge des bewaldeten und zum Teil vermoorten hydrologischen Einzugsgebietes führen zu erhöhten Stoffkonzentrationen im Hauptzufluss der Trinkwassertalsperre Weiterswiese (Carlsfeld). Seitens der Trinkwasseraufbereitung stellen insbesondere die gestiegenen Gehalte an gelösten organischen Kohlenstoffen (DOC) Mehraufwendungen dar. Im Zuge der Wiedervernässung der Moorflächen kommt es zu relevanten bodenchemischen Veränderungen, die im Abfluss messbar sind. Eine räumliche Betrachtung der Teileinzugsgebiete des hydrologischen Einzugsgebietes der oberen Wilzsch ermöglicht, das Abflussgebiet in verschiedene Herkunftsräume zu gliedern. Dieser raumbezogene Ansatz leistet einen wesentlichen Beitrag in der Herkunftsanalytik von Wässern, deren Fließwege durch Standorte unterschiedlicher Nutzung geprägt sind. Die Arbeit bedient sich hydrochemischen Analysen sowie multitraceranalytischen Verfahren. Die Analyse der stabilen Umweltisotope ²H und 18O am Wasser, 13C am DIC und DOC, 34S und 18O am Sulfat sowie 15N und 18O am Nitrat hilft bei der Identifizierung von Stoffquellen und Transformationsprozessen. Die Arbeit verfolgt das Ziel, den Beitrag der verschiedenen Stoffsysteme am gesamten Stoffaustrag des Vorfluters aufzuzeigen sowie die atmosphärische Grundlast an den Messstandorten nachzuweisen. Dazu wurden von Mai 2009 bis August 2010 fünf Beprobungskampagnen angelegt. Das Messdesign erstreckte sich auf 19 Standorte in ausgewählten Teileinzugsgebieten, die maßgeblichen Einfluss auf die Vorflut haben. Parallel dazu erfolgte die Untersuchung des Niederschlags an der Station Talsperre Weiterswiese. Erfasst wurden die Inhalte von Wässern verschiedener Moorgebiete, Moorwasserpegel unterschiedlich degradierter Moorbereiche, Gräben und Bodendrainagen im Fichtenforst, der Vorfluter Wilzsch und Kranizsch und des Grundwassers im Fichtenforst. Es kann festgehalten werden, dass je nach Lage bzw. Entfernung der Ursprungsgebiete der Anteil des DOC - Exports unterschiedlich stark ist. So sind die DOC - Austräge saisonal sehr verschieden. Im Ergebnis ist der hydrochemische Beitrag - im Besonderen DOC - der unterschiedlichen Stoffsysteme des hydrologischen Einzugsgebietes letztlich am finalen Pegel der Wilzsch messbar. Die vom Basisabfluss gesteuerten silikatischen Standorte im Fichtenforst leisten einen wesentlichen Anteil zum hydrochemischen Milieu der Vorfluter. Die im Untersuchungsgebiet eingeleiteten Renaturierungsmaßnahmen beeinflussen die Trinkwasserqualität in der Talsperre Carlsfeld nicht. Eine Abgrenzung der atmosphärischen Grundlast ist ebenfalls möglich, atmogen eingetragene Stoffe können an den Standorten ausgewiesen werden.

Thesis (M. Sc. Agriculture (Soil Science)) -- University of Limpopo, 2021 / Globally and in most parts of South Africa, there is a trend of increasing shrub encroachment in savanna rangelands. A number of studies have investigated the impact of shrub encroachment on soil organic carbon content (SOC) and soil organic carbon stocks (SOCs) in savannas. So far there is no clear consensus on whether shrub encroachment increases or decreases the level of SOC and SOCs, especially in semi arid savanna grasslands. Furthermore, knowledge on the effects of shrub encroachment on SOCs is largely restricted to the topsoil, as this is the part of the profile influenced by inputs and losses of soil organic matter. How shrub encroachment affects the vertical distribution of SOCs is rarely considered in the existing literature and the edaphic factors controlling SOCs with depth are poorly understood. The objectives of this study were (i) to quantify the vertical distribution of SOC and SOCs and (ii) to identify the edaphic factors controlling the vertical distribution of SOC and SOCs in a shrub-encroached savanna grassland sited on shallow plinthic soil. To achieve the objectives, a vegetation and soil survey of the savanna grassland was conducted whereby sampling areas were demarcated and characterized into open and shrub encroached grassland plots. In each encroachment level, three pits were randomly dug to the limiting layer on plots sited on the same soil type and similar topographic position. Soil samples were collected from the pits at depth intervals of 0-10, 10-20, 20-30, 30-40, 40-50, 50-60 and 60-70 cm. The collected soil samples were analyzed for chemical and physical properties in the laboratory. Correlation analysis was carried out to determine the relationship between SOC and SOCs, which were the variables of interest in this study and related controlling soil physicochemical properties. The results showed that SOC was significantly greater (P<0.05) in the shrub-encroached grassland compared to open grassland. Furthermore, the results revealed that SOC was on average 19 and 13% greater in the topsoil (0-20 cm) and subsoil (20-70 cm) of shrub encroached grassland compared to open grassland. The greater SOC in the topsoil of the shrub-encroached grassland was mainly attributed to higher SOC inputs from plant litter and detritus derived from trees and grasses, which are the dominant plant life forms in savannas. In the topsoil, SOC and SOCs were positively correlated with extractable phosphorus (P) (r = 0.60; P < 0.05), while in the subsoil they were positively correlated ix with extractable phosphorus (r = 0.54), soil porosity (r = 0.52), extractable copper (r = 0.46), extractable zinc (r = 0.41), exchangeable calcium (r = 0.37) and negatively correlated with mean weight diameter (r = -0.43). Overall, SOC and SOCs under both shrub-encroached and open grasslands vertically decreased with soil depth. The results obtained highlighted that the factors controlling the level of SOC and SOCs differs in the topsoil and subsoil of the studied shrub encroached grassland. These findings suggest that in the shallow plinthic soil investigated in this study, SOC in the topsoil is controlled by the macronutrient P, while in the subsoil it is physically protected by soil aggregates and chemically stabilized via complexation interactions with exchangeable cations and heavy metals. In-depth understanding of the physico-chemical factors controlling SOC storage is critical to foster management practices that will improve the cycling of SOC in shrub-encroached savanna grasslands.

Heterojunctions were generated between tungsten trioxide and tetraphenyl porphyrin with reduced graphene oxide or exfoliated graphite support for mineralisation of acid blue 25 dye under visible light radiation. Moreover, degradation of pharmaceuticals was conducted using p-n heterojunctions between WO3 and Co3O4 and a direct Z-scheme heterojunction between BiOI and Co3O4 prepared using in-situ method and solvothermal self-assembly method respectively. The synthesized materials were characterised using Raman, FTIR, SEM/EDS, TEM, XRD, TGA, BET, UV-Vis and PL techniques. UV-Vis, TOC and HPLC-QTOF-MS were used to study the degradation efficiency and pathway. Scavenger trapping experiments were conducted to propose the charge transfer mechanisms. The highest degradation efficiency (99 %) was achieved for the dye and the pharmaceuticals using visible light. The mineralisation ability of the fabricated nanomaterials was pH dependent with acidic conditions favouring the removal of the dye (pH 5) while alkaline conditions favoured the mineralisation of pharmaceuticals (pH 10 – 11). / Civil and Chemical Engineering

Organic matter (OM) is often considered the “currency” for ecosystem processes, such as respiration and primary production. OM in aquatic ecosystems is derived from multiple sources, and is a complex mixture of thousands of different chemical constituents. Therefore, it is difficult to identify all the sources of OM that enter and exit aquatic ecosystems. As humans develop undisturbed land, the rate at which terrestrial OM (e.g.soil and plants) and associated nutrients (e.g.nitrogen) enters rivers has increased. Increased nutrients may lead to increased primary production from aquatic plants and algae, potentially causing eutrophication and harmful algal blooms. In this study, I identified and characterized different sources of OM in four watersheds of Northeastern Utah with multiple land covers such as cities, forests, and crops. I expected OM in watersheds with human-altered land cover would have more OM produced instream by algae and other primary producers, than OM in less disturbed watersheds, which typically have OM from terrestrial sources. I found that OM at river sites with high human impact had high amounts of OM from instream primary production, but there was also OM produced in-steam at sites with low human impact. The greatest differences in OM across watersheds was due to wastewater treatment effluent. I also measured microbial consumption rates of algal derived and terrestrially derived DOM in experimental streams to quantify how much faster algal derived OM was consumed than terrestrial OM. I found algal derived OM was consumed extremely fast, so fast that realistic measurements of its consumption in some river ecosystems may not be possible. It is important to identify and characterize sources of OM to rivers, so watershed manager scan devise effective OM reduction plans appropriate for the constituent of concern unique to that watershed or region. Constituents of concern associated with OM include pathogens affiliated with manure, toxins in harmful algal blooms, metals, and pharmaceuticals from wastewater treatment effluent. Each pollutant requires a unique mitigation strategy and therefore the first step to pollution mitigation is source identification.

Pour protéger la ressource sol, il est nécessaire de prévoir les conséquences des activités humaines et du changement global sur l'évolution des sols notamment en modélisant cette dernière. Dans cette étude, nous avons démontré la sensibilité de SoilGen2.24 au climat, à l’usage des terres et à la réduction du travail du sol et identifié trois de ses principales limites, à savoir, certains processus trop simplifiés, certains processus manquants et une hypothèse de volume constant du sol. Ainsi, nous avons 1) construit le premier modèle d'évolution du sol entièrement modulaire, OC-VGEN, en intégrant dans VSoil, les processus du modèle SoilGen2.24; 2) testé différents formalismes pour certains des processus clés responsables de la distribution verticale de Corg, à savoir la distribution verticale des racines, la bioturbation et l'évolution verticale du taux de décomposition de Corg; 3) proposé un module mécaniste du changement de volume pour la modélisation de l'évolution du sol à court et moyen terme. OC-VGEN a été utilisé pour reproduire et projeter l’évolution, à l’échelle du siècle, de la distribution verticale de Corg pour des Luvisols ayant connu des historiques d'utilisation des terres et de travail du sol différents. Nous avons montré que 1) l'impact des processus de rétroaction sur la distribution verticale de Corg n'est pas négligeable; 2) l'usage des terres et le travail du sol influencent les rétroactions internes entraînant un impact indirect sur la dynamique de Corg; 3) le manque de connaissances sur les processus a une plus grande influence sur les trajectoires d’évolution des sols que les incertitudes sur les scénarios climatiques ou d'usage des terres. / Soil is a critical natural resource that inherently changes through time. To preserve the soil and protect it, it is necessary to predict the consequences of human activities and global change on soil evolution. This can be achieved using soil evolution modelling. In this study, we demonstrated the sensitivity of SoilGen to climate, land use and tillage reduction and identified three of its main limitations, namely some over-simplified processes, some missing processes and a simplifying assumption of constant soil volume. To overcome these limitations, we 1) built up the first fully modular soil evolution model, OC-VGEN, by using the process of SoilGen2.24 model in a modelling platform, VSoil; 2) tested different formalisms for some of the key processes responsible for the OC depth distribution, namely the root depth distribution, bioturbation and the depth evolution of the OC decomposition rate; 3) proposed a first, mechanistic approach to account for soil volume change in a short to medium time scale soil evolution modelling. OC-VGEN was used to reproduce and project the depth distribution of OC at a century time scale for Luvisols having experienced different histories of land use and tillage. We demonstrated that, at this time scale, 1) the impact of feedback processes on OC depth distribution are not negligible; 2) land use and tillage, beside their direct impact on the input of organic matter to soil, influence the internal feedbacks leading to an indirect impact on OC dynamics; 3) when projecting soil evolution, the lack of knowledge on the process definition has a larger influence on the projected trajectories than uncertainties on climate or land use scenarios.

Carbon storage in agricultural soils is an important measure to mitigate climate change. As the soil management techniques can greatly influence the amount of carbon stored in agricultural soils, the influence of different managements was analyzed in a literature review for northern Europe and Sweden. With a unique dataset, the temporal development of soil organic matter, and in a case study the influence of SOM on crop yield in Sweden was examined, as well as the relationship of SOM towards clay content and pH level. For northern Europe, organic amendments in form of manure and sewage sludge application and crop residue incorporation as well as nitrogen fertilization and diverse crop rotations indicate a positive impact on soil organic carbon. The influence of reduced tillage was found to be less impactful. Detailed development of SOM in Swedish agricultural fields remains unclear due to data restraints and scarcity, but for the Skåne region the data analysis suggests a stable SOM content for the time period analyzed. The relationship of SOM to crop yield remains unclear but indicates that SOM can have a positive effect on crop yield. More research is needed to understand underlying mechanisms of development, management influence and yield response on soil organic carbon for northern Europe.

Monitoring water quality on a near-real-time basis to address water resources management and public health concerns in coupled natural systems and the built environment is by no means an easy task. Furthermore, this emerging societal challenge will continue to grow, due to the ever-increasing anthropogenic impacts upon surface waters. For example, urban growth and agricultural operations have led to an influx of nutrients into surface waters stimulating harmful algal bloom formation, and stormwater runoff from urban areas contributes to the accumulation of total organic carbon (TOC) in surface waters. TOC in surface waters is a known precursor of disinfection byproducts in drinking water treatment, and microcystin is a potent hepatotoxin produced by the bacteria Microcystis, which can form expansive algal blooms in eutrophied lakes. Due to the ecological impacts and human health hazards posed by TOC and microcystin, it is imperative that municipal decision makers and water treatment plant operators are equipped with a rapid and economical means to track and measure these substances. Remote sensing is an emergent solution for monitoring and measuring changes to the earth’s environment. This technology allows for large regions anywhere on the globe to be observed on a frequent basis. This study demonstrates the prototype of a near-real-time early warning system using Integrated Data Fusion and Mining (IDFM) techniques with the aid of both multispectral (Landsat and MODIS) and hyperspectral (MERIS) satellite sensors to determine spatiotemporal distributions of TOC and microcystin. Landsat satellite imageries have high spatial resolution, but such application suffers from a long overpass interval of 16 days. On the other hand, free coarse resolution sensors with daily revisit times, such as MODIS, are incapable of providing detailed water quality information because of low spatial resolution. This iv issue can be resolved by using data or sensor fusion techniques, an instrumental part of IDFM, in which the high spatial resolution of Landsat and the high temporal resolution of MODIS imageries are fused and analyzed by a suite of regression models to optimally produce synthetic images with both high spatial and temporal resolutions. The same techniques are applied to the hyperspectral sensor MERIS with the aid of the MODIS ocean color bands to generate fused images with enhanced spatial, temporal, and spectral properties. The performance of the data mining models derived using fused hyperspectral and fused multispectral data are quantified using four statistical indices. The second task compared traditional two-band models against more powerful data mining models for TOC and microcystin prediction. The use of IDFM is illustrated for monitoring microcystin concentrations in Lake Erie (large lake), and it is applied for TOC monitoring in Harsha Lake (small lake). Analysis confirmed that data mining methods excelled beyond two-band models at accurately estimating TOC and microcystin concentrations in lakes, and the more detailed spectral reflectance data offered by hyperspectral sensors produced a noticeable increase in accuracy for the retrieval of water quality parameters.

Efforts to sequester soil carbon (C) should consider soils intrinsically capable at C retention. Of the mineral soil orders, Mollisols have minimum requirements for soil organic C (SOC; over 0.06 %) and basic saturation (over 50 %). In the U.S., grasslands comprise 93% of the vegetation mapped above Mollisols. Soils beneath the southern extent of Sequoia sempervirens (redwood) forests in central California are mapped as Molliols. It widely accepted that redwood forests harbor considerable biomass C, but the extent to which aboveground C is retained in the soil is not well understood. This study aimed to: (i) to gather baseline soils data (bulk density, pH, basic saturation, cation exchange capacity, SOC, total nitrogen, structure, depth) for an iconic and understudied ecosystem, the southern extent of coast redwood forests and to compare said properties to those in adjacent grasslands, (ii) to identify taxonomic classifications of said soils, (iii) to investigate the influence of vegetative gradation on soil properties between these ecosystems using auger sampling, (iv) to compare levels of basic cations between the forest floor and mineral horizons and, (v) to characterize the total C and active C pools within these ecosystems and to explore interpretations of these pools. In sites randomly selected across two regions, Swanton Pacific Ranch (SPR) and Landels-Hill Big Creek Reserve (LHBCR), soil was collected and described in 24 profiles beneath redwoods and compared to 19 profiles in nearby grasslands. Auger samples at fixed depths were collected in a complimentary study from 5 randomized transects that transitioned through mixed-evergreen forest (and across ecotones) between redwoods and coastal grasslands at SPR. Mineral soil samples were analyzed for SOC, permanganate oxidizable C (POXC), C/N ratio, pH, extractable basic cations, and cation exchange capacity. Samples of forest litter were analyzed for basic cation composition. Multivariate regression models of profile data found higher values of pH, C/N, and CEC in redwoods than in grasslands, and lower values of bulk density in redwoods than in grasslands. Redwood soils were conducive to mollic epipedon formation (21 of 24 profiles in the redwoods as Mollisols) and generally had high base levels, for which extractable calcium from the forest floor was the main driver. Along the transects, multivariate regression returned generally consistent and graded patterns for C/N ratios, POXC/SOC ratios, and pH; these variables were generally highest in the redwood forest and decreased sequentially across mixed-evergreen forest and into the grassland Our look at soil C pools focused on the fraction of SOC that was POXC. Observed higher ratios of POXC/SOC in redwoods than in the grasslands at SPR was corroborated by the transect study; at LHBCR, the regression model provided no evidence for a significant difference in POXC/SOC ratios between communities. Differences in POXC fractions across plant communities and localities were postulated as the result (and combination) of contrasting ecologies, and different management strategies and disturbance histories. The data collected in this study does not provide clear mechanisms to explain these discrepancies, and further research is needed; disharmonious interpretations of POXC across the literature suggested that the replacement of operationally defined C fractions with pools tied to a particular stabilization mechanism would provide clearer insights across ecosystems to land managers. Our estimates of SOC in the top 1 m of soil showed redwood soils stored as much or more C than soils in the neighboring grasslands, at SPR, 144 (± 21) and 123 (± 25) tons SOC per ha in the top 1 m of redwoods and grasslands, respectively, and at LHBCR, 221 (± 23) and 126 (± 24) tons SOC per ha in the top 1 m of redwoods and grasslands, respectively. The carbon densities provided in this study can be used as a baseline to measure changes to SOC and POXC pools in response to future activities to sequester C in our study regions and/or to assess losses from recent 2020 wildfires. We are curious to see how the breadth of information gathered in this study can provide refinement for following questions that will hopefully one day, direct considerate and conscientious management in response to the environmental challenges ahead.

<p>Examinator Professor Peter Jansson, Institutionen för naturgeografi</p> / Research school for teachers on climate and environment grant 2017-06037

Soil characterization provides the basic information necessary for understanding the physical, chemical, and biological properties of soils. Knowledge about soils can in turn be used to inform management practices, optimize agricultural operations, and ensure the continuation of ecosystem services provided by soils. However, current analytical standards for identifying each distinct property are costly and time-consuming. The optimization of laboratory grade technology for wide scale use is demonstrated by advances in a proximal soil sensing technique known as portable X-ray fluorescence spectrometry (pXRF). pXRF analyzers use high energy Xrays that interact with a sample to cause characteristic reflorescence that can be distinguished by the analyzer for its energy and intensity to determine the chemical composition of the sample. While pXRF only measures total elemental abundance, the concentrations of certain elements have been used as a proxy to develop models capable of predicting soil characteristics. This study aimed to evaluate existing models and model building techniques for predicting soil pH, texture, cation exchange capacity (CEC), soil organic carbon (SOC), total nitrogen (TN), and C:N ratio from pXRF spectra and assess their fittingness for California soils by comparing predictions to results from laboratory methods. Multiple linear regression (MLR) and random forest (RF) models were created for each property using a training subset of data and evaluated by R2 , RMSE, RPD and RPIQ on an unseen test set. The California soils sample set was comprised of 480 soil samples from across the state that were subject to laboratory and pXRF analysis in GeoChem mode. Results showed that existing data models applied to the CA soils dataset lacked predictive ability. In comparison, data models generated using MLR with 10-fold cross validation for variable selection improved predictions, while algorithmic modeling produced the best estimates for all properties besides pH. The best models produced for each property gave RMSE values of 0.489 for pH, 10.8 for sand %, 6.06 for clay % (together predicting the correct texture class 74% of the time), 6.79 for CEC (cmolc/kg soil), 1.01 for SOC %, 0.062 for TN %, and 7.02 for C:N ratio. Where R2 and RMSE were observed to fluctuate inconsistently with a change in the random train/test splits, RPD and RPIQ were more stable, which may indicate a more useful representation of out of sample applicability. RF modeling for TN content provided the best predictive model overall (R2 = 0.782, RMSE = 0.062, RPD = 2.041, and RPIQ = 2.96). RF models for CEC and TN % achieved RPD values >2, indicating stable predictive models (Cheng et al., 2021). Lower RPD values between 1.75 and 2 and RPIQ >2 were also found for MLR models of CEC, and TN %, as well as RF models for SOC. Better estimates for chemical properties (CEC, N, SOC) when compared to physical properties (texture), may be attributable to a correlation between elemental signatures and organic matter. All models were improved with the addition of categorical variables (land-use and sample set) but came at a great statistical cost (9 extra predictors). Separating models by land type and lab characterization method revealed some improvements within land types, but these effects could not be fully untangled from sample set. Thus, the consortia of characterizing bodies for ‘true’ lab data may have been a drawback in model performance, by confounding inter-lab errors with predictive errors. Future studies using pXRF analysis for soil property estimation should investigate how predictive v models are affected by characterizing method and lab body. While statewide models for California soils provided what may be an acceptable level of error for some applications, models calibrated for a specific site using consistent lab characterization methods likely provide a higher degree of accuracy for indirect measurements of some key soil properties.