EOS4.3

The amount and diversity of digitally available environmental data is continuously increasing.  However, they are often hardly accessible or scientifically usable. The virtual research environment V-FOR-WaTer aims at simplifying data access for environmental sciences, fostering data publications and facilitating data analyses.

V-FOR-WaTer already contains many of the necessary functionalities to provide and display data from various sources and disciplines. The detailed metadata scheme is adapted to water and terrestrial environmental data. Present datasets in the web portal originate from university projects and state offices. We are also finalising the connection of V-FOR-WaTer to GFZ Data Services, an established repository for geoscientific data. This will ease publication of data from the portal and in turn give access to datasets stored in this repository. Key to being compatible with GFZ Data Services and other systems is the compliance of the metadata scheme with international standards (INSPIRE, ISO19115).

The web portal is designed to facilitate typical workflows in environmental sciences. Map operations and filter options ensure easy selection of the data, while the workspace area provides tools for data pre-processing, scaling, and common hydrological applications. The toolbox also contains more specific tools, e.g. for geostatistics and for evapotranspiration. It is easily extendable and will ultimately include user-developed tools, reflecting the current research topics and methodologies in the hydrology community. Tools are accessed through Web Processing Services (WPS) and can be joined, saved and shared as workflows, enabling complex analyses and ensuring reproducibility of the results. To build workflows we include an easy-to-use drag and drop user interface.

How to cite: Strobl, M., Azmi, E., Hassler, S. K., Mälicke, M., Meyer, J., and Zehe, E.: The V-FOR-WaTer Virtual Research Environment for Environmental Research, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6258, https://doi.org/10.5194/egusphere-egu22-6258, 2022.

Hype Data Delivery Service: Data provision for decision support and scientific collaboration

Reliable access to quality assured data is essential to decision support for society and a crucial component to scientific enquiry. This presentation introduces the HYPE Data Delivery Service and highlights its potential and versatility in serving the science community and society at large.

The hydrological catchment model HYPE simulates water flow and substances on their way from precipitation through soil, river and lakes to the river outlet (Lindström et al., 2010). The catchment is divided into sub basins and further into classes depending on land use, soil type and elevation. The global implementation of the Hydrological Predictions for the Environment (HYPE) model covers an area of 135 million km², delineated to about 131 300 catchments, following river networks from source to sea (Arheimer et al, 2020). The HYPE Data Delivery Services provides results from the Global HYPE for all continental domains of the world except Antarctica. Results for the European domain are taken from the European (E-HYPE) model (Donnelly et al. 2016). The results range from historical simulations, forecasts (1-10 day, monthly, seasonal) to climate impact projections, essentially encapsulating the past, present and future. HYPE forecasts are driven by near-real-time adjusted reanalysis forcing data for hydrology (HydroGFD, Berg et al. 2018) while projections are driven by an ensemble of CMIP5 GCMs and CORDEX RCM output.

While the Hypeweb service (hypbeweb.smhi.se) visualization service provides spatial Open Data and time series points of interest, the delivery service offers high volume, high availability data covering whole continental domains. Through purchased subscriptions, the delivery service meets the data needs of many users including national hydrometeorological services, hydropower industry, hydrological consultancy and re-insurance companies. The delivery service also fosters research partnerships and collaborations through data and model sharing Research Agreements. Research Agreements with academic and research-based institutions carry obligations for collaborative research and peer reviewed publications in furtherance of scientific knowledge. The Hype Data Delivery Service is a definite win-win for science serving society through data provision.

Arheimer, B., Pimentel, R., Isberg, K., Crochemore, L., Andersson, J. C. M., Hasan, A., and Pineda, L., 2020. Global catchment modelling using World-Wide HYPE (WWH), open data and stepwise parameter estimation, Hydrol. Earth Syst. Sci. 24, 535–559, https://doi.org/10.5194/hess-24-535-2020

Berg, P., Donnelly, C., and Gustafsson, D.(2018). Near-real-time adjusted reanalysis forcing data for hydrology, Hydrol. Earth Syst. Sci., 22, 989–1000, https://doi.org/10.5194/hess-22-989-2018.

Donnelly, C, Andersson, J.C.M. and Arheimer, B., 2016. Using flow signatures and catchment similarities to evaluate a multi-basin model (E-HYPE) across Europe. Hydr. Sciences Journal 61(2):255-273, doi: 10.1080/02626667.2015.1027710

Lindström, G., Pers, C.P., Rosberg, R., Strömqvist, J., and Arheimer, B. (2010). Development and test of the HYPE (Hydrological Predictions for the Environment) model – A water quality model for different spatial scales. Hydrology Research 41.3-4:295-319.

How to cite: Gbobaniyi, E., Gyllensvärd, F., Popp, A., Capell, R., Andersson, J., and Arheimer, B.: Hype Data Delivery Service: Data provision for decision support and scientific collaboration, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12439, https://doi.org/10.5194/egusphere-egu22-12439, 2022.

The Modular Assessment of Rainfall–Runoff Models Toolbox (MARRMoT) is a flexible framework for hydrological modelling designed for model intercomparison studies and hypothesis testing. It reproduces 47 established conceptual hydrologic models of varying complexity including Sacramento, HBV, GR4J, VIC and TOPMODEL, amongst others. The package also allows to modify them or create new ones by mixing-and-matching components and modules from different models. We radically restructured MARRMoT compared to versions v1.x using an object-oriented programming approach to enhance code clarity and computational efficiency.

MARRMoT v2.1 is structured around two hierarchical classes, where a high-level superclass provides the template of all common model operations, while model-specific code is defined into individual subclasses derived from the single superclass. This reduces the verbosity and repetitiveness of the code, improving readability and facilitating debugging. Additionally, it simplifies the procedure to modify model structures or create new ones, also ensuring that best practices for solving model equations are followed as these are contained in the definition of the superclass and deployed automatically across all models.

We also updated MARRMoT’s numerical solving routine by including a Newton-Raphson solver. This lets us obtain satisfying solutions to the implicit Euler approximations of the models’ differential equations in a number of cases where the previous solving routine had failed, while also obtaining a 2.6-fold runtime improvement on average. We tested these changes by comparing outputs of 36 of the models in the framework between this object-oriented version and the previous version (v1.4) using calibrated parameters and climate inputs from the CAMELS US dataset.

The new version of the toolbox (v2.1) and user manual, including several workflow examples for common application, is available from GitHub (https://github.com/wknoben/MARRMoT).

How to cite: Trotter, L., Knoben, W., Fowler, K., Saft, M., and Peel, M.: Modular Assessment of Rainfall–Runoff Models Toolbox (MARRMoT) v2.1: better, faster and more accessible hydrological modelling through object-oriented programming., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6849, https://doi.org/10.5194/egusphere-egu22-6849, 2022.

The Renku platform developed at the Swiss Data Science Center integrates state-of-the-art data science and open source software tools to enable collaborative, reproducible and reusable data science. Data, code, workflows and computational environments in every project are versioned from the start, allowing researchers to focus on their task of discovery rather than worrying about preserving their work. In addition, Renku provides a hosted solution for running those computational environments, which allows researchers to share their fully reproducible work instantly with others. Renku treats all aspects of the data analysis process (code, data, workflows) as nodes in an indexed, searchable Knowledge Graph, meaning that datasets, algorithms or full workflows can be discovered, shared and reused. In this talk we will describe how Renku lowers the bar for researchers to participate in open-science and provides scientific communities with tools to gain a deeper understanding of pathways of discovery within their disciplines.

How to cite: Roškar, R.: Renku: a platform for collaborative, reusable and reproducible research, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10697, https://doi.org/10.5194/egusphere-egu22-10697, 2022.

The goals of open science include easy reproducibility of research results, transparency of research methods and re-usability of artefacts, e.g. data, code, and graphics. Consequently, open science is expected to foster scientific collaboration and sustainability of research, as it enables building on each others' methods and results for many years and decades to come.

Here we report about our collective attempts in the last 4-10 years of taking open science to the extreme by using exclusively open formats, open-source software, sharing all stages of our work online and recording workflows and provenance of code and data. Most of our analyses are carried out in Jupyter Notebooks, which are all shared online through gitlab. In these notebooks and our python-analyses, we integrate the python package essm for transparent and easily reproducible mathematical derivations. For more complex analyses, including large model runs, we use the tool Renku of the Swiss Data Science Center in order to record workflows and provenance of code and data.

Find out where we succeeded, where we failed, what we gained and what we lost in pursuing open science to the extreme. Hear about the views and experiences with open science at the undergraduate, postgraduate, postdoc, engineer and senior researcher level. Eventually, we will also report about what we are still missing for entirely reproducible, verifiable, and reusable open science. We hope we can foster a debate about good open science practices, and how we can remove obstacles that are still in our way.

How to cite: Schymanski, S. J., Ceolin, S., Corvi, O., Gama, A., Krieger, L., Minette, F., Nijzink, R. C., O'Nagy, O., Osuebi-Iyke, E., and Thakur, G.: Open and collaborative science: 4+ years of going to the extreme, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8851, https://doi.org/10.5194/egusphere-egu22-8851, 2022.

Directly measuring GHG gas emissions, carbon sequestration, evapotranspiration and heat fluxes via the Eddy Covariance method has been widely used by expert micrometeorologists for over 30 years, covering 2155 stationary locations globally, and numerous mobile campaigns over land and water surfaces. Latest measurement technologies and automated processing software are rapidly expanding the use of the method to non-micrometeorological research. Regulatory and commercial uses of the method also increase year-by-year.

Despite the widening adoption of the method, academic investigators outside the area of micrometeorology and the majority of non-academic investigators are still not familiar enough with the proper implementation of the method required for conducting high-quality, reliable, traceable, and defensible measurements in their respective areas of interest.

Although data collection and processing are now automated, the method still requires significant care to correctly design the experiment, set up the site, organize and analyze a large amount of data. Efforts of the flux networks (e.g., FluxNet, AmeriFlux, Asiaflux, ICOS, NEON, OzFlux, etc.) have led to major progress in the standardization of the method. The project-specific workflow, however, is difficult to unify because various experimental sites and purposes of studies demand different treatments, and site-, measurement- and purpose-specific approaches.

To address this situation, step-by-step simple instructions were created to introduce a novice to general principles, requirements, applications, processing, and analysis steps of the conventional Eddy Covariance technique in the form of the free electronic resource, a 660-page textbook titled "Eddy Covariance Method for Scientific, Regulatory, and Commercial Applications". The explanations are provided using easy-to-understand illustrations and real-life examples, and the text is written in a non-technical language to be practically useful to those new to this field.

Information is provided on the theory of the method (including the state of methodology, basic derivations, practical formulations, major assumptions, sources of errors, error treatments, etc.), practical workflow ow (e.g., experiment design, implementation, data processing, quality control, and analysis), data sharing and flux stations networking, key alternative methods, and the most frequently overlooked details.

The book is organized by topic for ease of access to specific information. Each topic is presented in a three-tier structure: an illustration and summary, more in-depth information, and references to more advanced textbooks, networking guidelines, and journal papers for further exploration.

How to cite: Burba, G.: Writing a New Free Book on Using Direct GHG Measurements in Disciplines beyond Micrometeorology, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6206, https://doi.org/10.5194/egusphere-egu22-6206, 2022.

Sedimentologika is a community-driven Diamond Open Access (DOA) scientific journal about sedimentology. The journal aims to create a place where people can publish their research and access scientific studies on all types of sedimentary processes, methods, deposits, and environments, across all spatial and temporal scales, on Earth or any other planetary body, for free. The published material will be free to share (i.e., no embargo period) since authors retain the copyright. Sedimentologika is driven by the community for the community and is part of a broader DOA movement in geosciences. Sedimentologika aspires at emancipating from the financial barriers associated to private publishing houses to provide direct and equal access to science to all citizens, scientists, and institutions all over the globe. This journal will be defined by Open Science principles to promote ethical dissemination of science and knowledge, following high equality, diversity, and inclusion standards. Each step of the review and publication process will be visible and easy to follow for authors, reviewers and the community. Sedimentologika will be launched by mid-2022 and we are always looking for motivated people keen on giving a little bit of their time to make Sedimentologika a viable and recognized peer-reviewed scientific journal. Interested in this initiative? Come discuss with us!

How to cite: Marchegiano, M., Chiarella, D., Jarochowska, E., Kane, I., Mitten, A., Privat, A., Poyatos-Moré, M., Soutter, E., Spychala, Y., Thomas, C., Vaucher, R., and Zuchuat, V.: Sedimentologika: a community-driven DOA journal, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8870, https://doi.org/10.5194/egusphere-egu22-8870, 2022.

Tektonika is a new community-led diamond open-access journal (DOAJ) for structural geology and tectonics. It will join the growing body of DOAJs established over recent years and expand the open science movement within academia. Tektonika is a grass-roots initiative, driven by the enthusiasm and devotion of a wide and diverse spectrum of Earth Scientists from around the globe. This project endeavors to set up an open platform, devoid of any paywall, to publish, disseminate, and promote structural geology and tectonics research, and shape, alongside the other initiatives, the bright future of open access publishing.

This contribution comes shortly after the official kick-off date of Tektonika and is a great opportunity to provide an overview of our experience setting up a DOAJ and highlight the milestones that have been achieved. These include the selection of executive and associate editorial teams, as well as journal policies regarding submissions, peer-review, article types, journal scope, ethos, and relevant guidelines. A shop with journal merchandise has been set to support the journal costs and may also fund other activities, such as mentoring programs, awards, and seminars. Most importantly, Tektonika is currently welcoming submissions as the first diamond (free-to-publish, free-to-read) open-access platform in the fields of tectonics and structural geology.

How to cite: Fernández-Blanco, D., Gouiza, M., Bond, C., McCarthy, D., Lee, A., and Pérez-Díaz, L. and the Tektonika DOAJ community: Tektonika, the new Diamond Open Access journal for structural geology and tectonics, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12042, https://doi.org/10.5194/egusphere-egu22-12042, 2022.