Find all session, oral, and poster contributions and their abstracts below.
A – Innovative sensing methods for the critical zone
Abstract: The advancement of critical zone research relies on innovative methods to sense states and fluxes at high a spatiotemporal resolution. The emergence of such novel measurements has been and will continue to be an important driver for the ability to analyze critical zone processes and to evaluate models. In this session, we encourage submissions dealing with new types of sensing methods and data to investigate the critical zone (e.g. wireless distributed sensors, novel use of hydrogeophysical methods, cosmic-ray neutron probes, etc.). Submissions that provide a fresh look on more traditional types of data are also welcome. In the past decade, integrated terrestrial observatories have been established that produce massive amounts of data for a range of critical zone processes. As it remains challenging to analyze such data sets, we are also soliciting submissions that present novel strategies to support critical zone studies in the light of big data.
B – Long-term environmental observation - Advancing the understanding of Earth System in the Anthropocene
Abstract: Environmental research is challenged by the question, how life supporting systems (ecosystems, the critical zone etc.) and their services will develop in the next decades. Long-term environmental observation is a key tool to generate the knowledge about the development of interrelated Earth Systems. Several global and international research networks like ILTER, ICOS, CZO, eLTER are committed to this challenge. However, addressing changes in structure and function requires an integrated approach from the subsurface to the vegetation and atmosphere, across scales and ecosystems types, and combining observation, ecosystem theories and modelling. Such integrated approach affects most aspects of how environmental research and observation are shaped, comprising seamless collaborations amongst involved disciplines, the interactions of actual research with other stakeholders, research infrastructure design and operation. In this session we invite contributions addressing integrated approaches of environmental research, conceptual frameworks for long-term environmental research and examples of the use of observation network data in research.
C – Remote Sensing and Ecosystem Services
Abstract: Remote sensing sensors, both airborne and spaceborne, deliver Earth observation data in high spatial and temporal resolution. The challenge is to understand the dependency of the data products on environmental observables and to develop methodologies to actually retrieve environmentally relevant information. The latter can contribute to the understanding of dynamic Earth systems and be used as indicators in Earth system models. In this session, we are looking forward to interesting contributions concerning (1) recent developments of methodologies for estimating bio- or geophysical parameters from remote sensing data and (2) studies investigating the use of parameters derived from remote sensing data to address key environmental science questions.
D – Biodiversity Monitoring: Past, presence, future
Convener: S. Klotz (UFZ)
Abstract: Biodiversity and ecosystem resilience are interrelated. The impact of global change including land use change, climate change and the global spread of organisms (biological invasions) have enormous consequences on the different elements of biodiversity (populations, species, biotic interactions etc.). In this session the history and the future of biodiversity monitoring are the focal points. The main question is: How can the state of biodiversity be measured and explained by observations and experiments.
E – Integration of in-situ and remote sensing data for the earth surface-atmosphere system
Abstract: Deriving Earth surface properties relevant for understanding the surface-atmosphere system requires the integration of remote sensing and in-situ measurements, in particular if the focus is on larger spatial scales (regional, continental). This session focuses on concepts and method developments combining in-situ data and spatial remote sensing data. We seek contributions addressing (1) issues of scale between in-situ and remote sensing data, (2) advances in multisensor analysis of the surface-atmosphere system, (3) uncertainty analysis for remote sensing based parameter retrieval, and (4) the integration of eddy covariance and remote sensing data.
F – Decadal and centennial variability from high-resolution bio- and geoarchives
Abstract: The climatic observations over the instrumental era cover a period too short to document the full range of climate variability. The study of paleoclimates provides a longer perspective allowing to explore the behavior of the climate system in a wider range of conditions and forcings. This allows us to characterize more precisely the decadal to centennial climate variability, to test for potential mechanisms responsible, or to estimate the probability and return period of some specific events. Such insights also help to comprehend landscape changes and ecosystem dynamics in relation to climate variations. The main objective of this session is to focus on the origin and mechanisms involved in decadal- to centennial-scale climate variability and to further investigate the effects of this climate variability on landscape changes and ecosystem dynamics.
G – Improving water quality management using new observation and modeling strategies
Abstract: Water quality and matter fluxes at the catchment scale are critical to pressing societal issues such as agricultural sustainability, drinking water quality, ecosystem health, and global climate change. Cutting edge studies are improving the understanding of biogeochemical and anthropogenic factors affecting diffuse mass fluxes of nutrients, pesticides, emerging contaminants, trace elements, greenhouse gases and other chemicals. Predictions are needed for changing land use and climate conditions which fulfill the increasing needs for sustainable decision making. Recent advances in in situ water quality monitoring technologies have improved monitoring programs and provided new insights into watershed hydrology and biogeochemical processes. Water quality assessment covers the chemical and ecological status and links hydrology and aquatic ecology. As water quality assessment is affected by errors in input data, model errors, inappropriate model complexity and process knowledge, new strategies combining monitoring and modeling are needed to improve the prediction capabilities of hydrological water quality models at the management scale. Contributions are welcome dealing with new monitoring and modeling techniques ranging from deterministic process based water quality models to simple GIS based approaches. Also of interest are contributions focusing on the use of water quality data for hydrological process analyses. We furthermore welcome submissions about innovative approaches for analysis of continuous water quality data at high temporal resolution in support of monitoring and research.
H – Management and integration of environmental observation data
Convener: R. Kunkel (FZJ)
Abstract: Together with the rapid development of sensor technologies and the implementation of environmental observation networks (e.g. TERENO, eLTER, CUAHSI, ICOS, MOSES, ENOHA,…) a large number of data infrastructures are being created to manage and provide access to observation data. However, significant advances in earth system understanding can only be achieved through better and easier integration of data from distributed infrastructures. In particular, the development of methods for the automatic real-time processing and integration of observation data in models is required in many applications. Improvement in this field strongly depends on the capabilities of dealing with fast growing multi-parameter data and on effort employing data science methods, adapting new algorithms and developing digital workflows tailored to specific scientific needs. Automated quality assessment/control algorithms, data discovery and exploration tools, standardized interfaces and vocabularies as well as data exchange strategies and security concepts are required to interconnecting distributed data infrastructures.This session focuses on the specific requirements, techniques and solutions to process, provide and couple observation data from (distributed) infrastructures and to make observation data available for modelling and other scientific needs.
I – Measuring and modeling water storage dynamics
Abstract: Understanding fundamental catchment functions of water collection, storage and release is vital for predicting the hillslope and catchment response to changing climate or land use characteristics. Storage dynamics reflect the water balance of all fluxes entering and leaving the catchment and depend on physiographic catchment properties and the varying connectivity of storage compartments and stream network. This session welcomes contributions on (1) recent advances in measuring, monitoring and characterizing water storage dynamics at different spatial and temporal scales, and from individual storage compartments to integrated catchment storage, or on (2) modeling studies that make use of storage observations for model validation or calibration and that analyze the role of water storage for the hydrological or hydro-chemical response of hillslopes or catchments.
J – Novel Approaches to monitor dynamic events
Abstract: Although it is well known that global change affects the environment on many different temporal and spatial scales, currently only very limited knowledge is available on the importance of distinct dynamic events such as heat waves, droughts or hydrological extremes for the long-term development of the Earth system. This session will focus on advancements in observation strategies and observing systems to capture the impacts of such highly dynamic events on the surrounding Earth compartments.
K – Biogeochemical processes in soil-plant-atmosphere systems
Convener: N. Brüggemann (FZJ)
Abstract: Climate change affects the biogeochemical cycles of water, carbon and nutrients in terrestrial systems and influences their exchange with the atmosphere, groundwater and surface waters. Due to the large spatial heterogeneity of environmental factors such as soil type, groundwater distance, topography, land use and vegetation cover, as well as the high spatio-temporal variability of climatic parameters, the prediction of changes in biogeochemical fluxes remains subject to great uncertainties. However, it is very likely that the water, carbon and nutrient fluxes between the pedosphere, biosphere, atmosphere and hydrosphere will change in the future, with positive and negative feedbacks on climate change. This session invites contributions that advance our understanding of the effects of climate change on biogeochemical processes in the soil-plant-atmosphere system of natural and managed ecosystems, such as: Stability of soil organic matter, availability of water and nutrients, plant performance and greenhouse gas emissions. Research using new methods and experimental techniques is particularly encouraged.
L – Relevance of soils in terrestrial matter fluxes - measurements and model concepts
Abstract: Soils are hotspots for terrestrial matter turnover and due to their retention capacity for water and solutes they also control fluxes between the atmosphere and ground- and surface waters. In unsaturated soils these fluxes are in general vertical following the gradients in capillarity forces and gravity. The spatial distribution of soil types in the landscape reflect the geological parent material, relief, vegetation and locale climate. Hence, the spatial correlation scale of soil properties is typically much smaller the catchments. The inherent nonlinearity of flow and turnover processes in soil prohibit the averaging of soil properties, i.e. model parameters, for describing flow and matter turnover. Hence the hidden, below-ground spatial pattern of soil properties is critical to predict matter fluxes and turnover.
M – Model-data fusion: Improving predictions and improving process understanding
Convener: H.-J. Hendricks-Franssen (FZJ)
Abstract: Model-data fusion methods are for example data assimilation, inverse modelling or more data driven approaches. Model-data fusion methods can improve short-term model predictions as models are informed by the data. This is for example important for meteorological and hydrological predictions. Model-data fusion methods can also be used to estimate parameters, which is important for improving long-term predictions like the evolution of the carbon sink/source strength of the land. Measurement data captured by large scale measurement infrastructure networks like TERENO can be used to improve model predictions, and the value of the different data types for improving model predictions can be evaluated. Another important contribution from model-data fusion methods is that systematic differences between simulated and measured values can be detected and analyzed in more detail, in order to identify model structural errors and improve models.This session focuses on model-data fusion studies, with a special focus on integrating of data captured by in situ terrestrial networks like TERENO, but also assimilation of remotely sensed data is a topic of interest for this session. We would be especially interested in contributions where the role of model structural error is investigated and where it is shown how model-data fusion methods can contribute to detect model structural errors and improve simulation models. Contributions are welcomed from a broad range of disciplines like soil science, hydrology, atmospheric sciences, biogeosciences and other geosciences. Studies involving multiple compartments of the terrestrial system are of special interest. Although the focus of this session will be on assimilation of monitoring data, also methodological data assimilation contributions are appreciated.
N – Ecotrons and lysimeters: complementary tools for observation and experimentation on the critical zone
Abstract: The measurement and the understanding of water and chemical fluxes in the unsaturated zone pose a challenge today. Several techniques are used at different scales to determine these fluxes. Often there is a lack of precision between measurements made at different scales. TERENO-SOILCan is the only lysimeter network in the world to investigate the influence of climate change on soil functions. This session provides an up-to-date overview of the application and scientific value of lysimetry. During the last couple of years lysimeter technology has made tremendous progress with respect to the accuracy of measurements, instrumentation, data acquisition, and the avoidance of typical lysimeter errors. The best available large lysimeters nowadays are contain undisturbed monoliths, are continuously weighed with high accuracy, have a suction control at the lower boundary, and avoid any island effect by a perfect embedding into the surrounding environment. By that, large lysimeters can nowadays be used as precision measurement tools for validation of many coupled processes like evaporation, dew formation, transpiration, and solute transport. The session should aim on observations to these coupled processes. Contributions addressing methods of measurement and their impact on flux determination focussing on lysimeters are also sought. Experimental as well as modelling contributions related to flux determination and interpretation are welcome.
OralsThu, 13:30 and 15:30
O – Soil greenhouse gas exchange - Linking methods, bridging scales
Abstract: Soils of natural and agricultural ecosystems act as significant sources and sinks for greenhouse gases (GHG) such as carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). Quantifying sources and sinks of soil GHG is crucial to better constrain their importance in global atmospheric budgets and how they are influenced by climate and land use change. In this session, we seek for contributions of quantifying soil GHG emissions and their underlying biotic and abiotic controls from site to regional/ national scales by means of field measurements (including chambers, micrometeorological and air-borne methods) and modelling approaches (empiric, stochastic and numerical methods).
P – Modeling the Hydrological System – Balancing of complexity and Uncertainty
Convener: S. Attinger (UFZ)
Abstract: Complex water resources management problems require predictive tools for modeling of water- and solute fluxes on different spatial and temporal scales. Central problems comprise e.g. climate change impact on water availability and flooding risks, water allocation under scarce water conditions and water quality deterioration from intensive agriculture or mining activities.Traditionally, both complex physically based hydrological modeling systems and lumped conceptual model systems are applied to serve and support decision making in water management. While lumped hydrological model systems usually focus on streamflow reproduction and are computationally efficient and have parameters that can be identified by calibration, they suffer from a lack of physical relevance and physical parameter interpretability. This implies e.g. that their predictability for new climate or environmental boundary conditions might be rather restricted. Physically based hydrological models, on the other hand, have reached highly increased complexity by integrating and coupling to adjacent compartments like the atmosphere or by including detailed additional process descriptions e.g. for energy fluxes. This may allow the enhanced consideration of feedback processes over compartments and different spatial and temporal scales. While hydrological predictability might increase here, data demands have increased in parallel. Because of these information constraints that result in high parameter uncertainties, non-validity of process equations at different scales, non-uniqueness of field data for model representations, etc., complex hydrological models also show limitations to provide reliable hydrological predictions.The session therefore would like to address recent developments in both complex and lumped hydrological model development, limitations and potentials of complex physical models vs. ensembles of lumped models, and predictability of hydrological model systems under transient forcing conditions, like climate, land use, and consumption.