A pattern-based approach to a cell tracking ontology

Time-lapse microscopy has thoroughly transformed our understanding of biological motion and developmental dynamics from single cells to entire organisms. The increasing amount of cell tracking data demands the creation of tools to make extracted data searchable and interoperable between experiment and data types. In order to address that problem, the current paper reports on the progress in building the Cell Tracking Ontology (CTO): An ontology framework for describing, querying and integrating data from complementary experimental techniques in the domain of cell tracking experiments. CTO is based on a basic knowledge structure: the cellular genealogy serving as a backbone model to integrate specific biological ontologies into tracking data. As a first step we integrate the Phenotype and Trait Ontology (PATO) as one of the most relevant ontologies to annotate cell tracking experiments. The CTO requires both the integration of data on various levels of generality as well as the proper structuring of collected information. Therefore, in order to provide a sound foundation of the ontology, we have built on the rich body of work on top-level ontologies and established three generic ontology design patterns addressing three modeling challenges for properly representing cellular genealogies, i.e. representing entities existing in time, undergoing changes over time and their organization into more complex structures such as situations

Magnetic reversals - Their application to stratigraphic problems

Magnetic reversal applications to stratigraphic problems in geolog

The CommunityWater Model (CWATM) / Development of a community driven global water model

With a growing population and economic development, it is expected that water demands will increase significantly in the future, especially in developing regions. At the same time, climate change is expected to alter spatial patterns of hydrological cycle and will have global, regional and local impacts on water availability. Thus, it is important to assess water supply, water demand and environmental needs over time to identify the populations and locations that will be most affected by these changes linked to water scarcity, droughts and floods. The Community Water Model (CWATM) will be designed for this purpose in that it includes an accounting of how future water demands will evolve in response to socioeconomic change and how water availability will change in response to climate. CWATM represents one of the new key elements of IIASA’s Water program. It has been developed to work flexibly at both global and regional level at different spatial resolutions. The model is open source and community-driven to promote our work amongst the wider water community worldwide and is flexible enough linking to further planned developments such as water quality and hydro-economic modules. CWATM will be a basis to develop a next-generation global hydro-economic modeling framework that represents the economic trade-offs among different water management options over a basin looking at water supply infrastructure and demand managements. The integrated modeling framework will consider water demand from agriculture, domestic, energy, industry and environment, investment needs to alleviate future water scarcity, and will provide a portfolio of economically optimal solutions for achieving future water management options under the Sustainable Development Goals (SDG) for example. In addition, it will be able to track the energy requirements associated with the water supply system e.g., pumping, desalination and interbasin transfer to realize the linkage with the water-energy economy. In a bigger framework of nexus – water, energy, food, ecosystem - CWATM will be coupled to the existing IIASA models including the Integrated Assessment Model MESSAGE and the global land and ecosystem model GLOBIOM in order to realize an improved assessments of water-energy-food-ecosystem nexus and associated feedback. Our vision for the short to medium term work is to introduce water quality (e.g., salinization in deltas and eutrophication associated with mega cities) into CWATM and to consider qualitative and quantitative measures of transboundary river and groundwater governance into an integrated modelling framework

Towards a Pan-European Integrated Groundwater and Surface Water Model: Development and Applications

During the last years, we have developed a model, which is able to simulate hydrological processes at a Pan-European scale. The model has multiple possible uses, including flood forecasting, identification of groundwater recharge / discharge zones and large-scale water resources management. The integrated model is based on the LISFLOOD model, which simulates hydrological processes with a focus on snow and soil hydrology and streamflow routing. The area of interest is the full European continent, divided in 5 × 5 km cells. A conceptual 2D MODFLOW model was linked to improve groundwater simulation. With this coupling, it is now possible to simulate the water exchanges between adjacent cells, and between groundwater and river. Available meteorological data from 1-1-1990 to 31-10-2014 were used as input for the coupled model, together with values of aquifer properties derived from literature. We used observed data of recharge, discharge and hydraulic heads from the Danube river basin to check if the model results correspond to reality. The results show a reasonably high degree of agreement between observed and simulated data, taking into account the limitations of large scale modelling. This model is the first step to improve integrated groundwater and surface water modelling which includes the collection of data and the production of Pan-European groundwater parameter maps

The impact of lake and reservoir parameterization on global streamflow simulation

Lakes and reservoirs affect the timing and magnitude of streamflow, and are therefore essential hydrological model components, especially in the context of global flood forecasting. However, the parameterization of lake and reservoir routines on a global scale is subject to considerable uncertainty due to lack of information on lake hydrographic characteristics and reservoir operating rules. In this study we estimated the effect of lakes and reservoirs on global daily streamflow simulations of a spatially-distributed LISFLOOD hydrological model. We applied state-of-the-art global sensitivity and uncertainty analyses for selected catchments to examine the effect of uncertain lake and reservoir parameterization on model performance. Streamflow observations from 390 catchments around the globe and multiple performance measures were used to assess model performance. Results indicate a considerable geographical variability in the lake and reservoir effects on the streamflow simulation. Nash-Sutcliffe Efficiency (NSE) and Kling-Gupta Efficiency (KGE) metrics improved for 65% and 38% of catchments respectively, with median skill score values of 0.16 and 0.2 while scores deteriorated for 28% and 52% of the catchments, with median values - 0.09 and -0.16, respectively. The effect of reservoirs on extreme high flows was substantial and widespread in the global domain, while the effect of lakes was spatially limited to a few catchments. As indicated by global sensitivity analysis, parameter uncertainty substantially affected uncertainty of model performance. Reservoir parameters often contributed to this uncertainty, although the effect varied widely among catchments. The effect of reservoir parameters on model performance diminished with distance downstream of reservoirs in favor of other parameters, notably groundwater-related parameters and channel Manning’s roughness coefficient. This study underscores the importance of accounting for lakes and, especially, reservoirs and using appropriate parameterization in large-scale hydrological simulations

Using the Budyko Framework for Calibrating a Global Hydrological Model

Global hydrological models (GHMs) have become an established tool to simulate water resources worldwide. Most of the GHMs are however uncalibrated and typically use a set of basic hydrological parameters, that could potentially lead to unrealistic projections of the terrestrial water cycle. The calibration of hydrological models is usually performed by using and comparing modeled to observed discharge. Accurate station data and reliable time series data of discharge are, however, often not available for many parts of the world and classic calibration approaches are therefore not feasible. In this paper, we aim to develop a new calibration approach that requires no additional data, is easy to implement, and substantially improves model performance, especially in regions where uncalibrated model performance is rather poor. This is achieved by using the Budyko framework, which provides a conceptual representation of the long‐term water and energy balance. We use a state‐of‐the‐art GHM and calibrate the model within nine river catchments of different sizes and characteristics. Since observed river discharge is available for these catchments, we are able to compare the Budyko‐based calibration approach to a classic discharge‐based calibration scheme and the uncalibrated model version. In all catchments, the Budyko‐based calibration approach decreases biases and increases model performance compared to the uncalibrated model version although performance improvements obtained through a classic calibration approach are greater. Nonetheless, a Budyko‐based calibration is a valuable, intermediate approach between use of a basic set of a priori hydrological parameters and classical calibration against discharge data

Accuracy assessment of ISI-MIP modelled flows in the Hidukush-Karakoram-Himalayan basins

Large Asian rivers heading in the Hindukush-Karakoram-Himalayan mountains, and whose streamflow includes significant snow-melt and glacier-melt components, may be highly susceptible to climate warming and pattern changes. Millions of people depend on these streamflows for agriculture and power generation. Reliable predictions of future water availability are therefore needed for planning under a changing climate, and depend on the quality of hydro-climatic modelling. ISI-MIP provides global hydrological modelling results, and need validation at regional scale. This study evaluates the accuracy of modelled flows from the hydrological models used in ISI-MIP, in various sub-basins of the Upper Indus Basin (UIB) and for the reference period 1985-1998. The modelled flows are based on six hydrological models, which are: i) H08, ii) VIC, iii) WaterGAP, iv) WBM, v) MPI-HM, vi) PCR-GLOBWB. Of these models, H08 and VIC are energy-based hydrological models, while the others are temperature-based hydrological models. WBM and MPI are not suitable for the UIB, due to significant under-estimation (by 70-90%) of measured flows by their modelled flows. The remaining four models provide consistent, but still significantly under-estimated flows (up to 60% of measured flows) in all sub-basins, except the Kharmong basin. Monthly differences between modelled and measured flows vary between sub-basins, but with noticeable over-estimation in winter-spring months and under-estimation during summer months. Accuracy of the bias-corrected precipitation data sets (based on five GCMs) used in the ISI-MIP hydrological models has been assessed, using a basin-wide water balance assessment method. This method shows that all precipitation data sets significantly under-estimate precipitation in the UIB, particularly in the Karakoram sub-basins. The selected ISI-MIP hydrological models have used precipitation data which are under-estimates, which may be a main reason for under-estimated flows. ISI-MIP hydrological modelling needs to use the best available precipitation data for the UIB, but other input data and calibration parameters also need revision. An important message from this study is that caution must be exercised in selecting precipitation data sets and hydrological models in alpine regions such as the Hindukush-Karakoram-Himalayas