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NEW SOLUTIONS FOR DATA ASSIMILATION AND COMMUNICATION TO IMPROVE HYDROLOGICAL MODELLING AND FORECASTING

English title NEW SOLUTIONS FOR DATA ASSIMILATION AND COMMUNICATION TO IMPROVE HYDROLOGICAL MODELLING AND FORECASTING
Applicant Brunner Philip
Number 195533
Funding scheme CHIST-ERA
Research institution Centre d'hydrogéologie et de géothermie Université de Neuchâtel
Institution of higher education University of Neuchatel - NE
Main discipline Other disciplines of Earth Sciences
Start/End 01.09.2021 - 31.08.2024
Approved amount 291'727.00
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All Disciplines (5)

Discipline
Other disciplines of Earth Sciences
Other disciplines of Environmental Sciences
Other disciplines of Engineering Sciences
Geology
Other disciplines of Physics

Keywords (4)

water resrouces management; hydrogeology; numerical modelling; data assimilation

Lay Summary (German)

Lead
Die Zuverlässigkeit von hydrologischen und hydrogeologischen Modellen kann durch die Integration von Felddaten erheblich erhöht werden. Das Projekt setzt hier an: durch innovative Datenerfassung, neuen Downscaling-Ansätzen und neuesten Modellansätzen werden die Unsicherheiten dieser Modelle gezielt reduziert. Die Modellresultate werden durch Stakeholder genutzt und zur Optmierung von Wasserressourcen eingesetzt.
Lay summary

Hydrologische Modelle sind wichtige Instrumente für das Management von Wasserressourcen. Die neuste Generation dieser Modelle  können die relevanten physikalischen Prozesse und ihre Rückkopplungsmechanismen simulieren. Ein limitierender Faktor ist jedoch der Mangel an Messungen zur Kalibrierung der Modellparameter und zur Beurteilung der Robustheit der Modelle. WATERLINE wird Multi-Source-Informationen aus der Fernerkundung, historischen Daten, In-situ-Daten aus meteorologischen Netzwerken sowie Crowdsourced-Messungen nutzen, um hydrologische Modelle und deren Vorhersagen zu verbessern. Leider können weder In-situ-Netzwerke noch Fernerkundung allein ausreichende Informationen liefern, um die hohe räumliche und zeitliche Variabilität hydrologischer Prozesse zu erfassen. In jüngster Zeit wurden Downscaling-Frameworks entwickelt, welche grobskaligen Produkten und hochaufgelösten Daten unter Verwendung von In-situ-Messungen integrieren. Damit kann die Effizienz und Robustheit von hydrologischen Modellen erheblich verbessert werden.

 

Das WATERLINE-Konzept wird durch die Entwicklung eines Webservice-Tools mit drei modularen Anwendungen umgesetzt, die auf a) die Nutzung durch Wissenschaftler (Datenzugriff, Downscaling, Filterung, Unsicherheitsanalyse, Modellierungsanwendungen); b) die Nutzung durch nicht technisch geschulte Stakeholder, und; c) Nutzung durch hydrologisch interessierte Benutzer über eine Crowdsourcing-App, die es jedem Benutzer ermöglicht, über jedes hydrologisch relevante Ereignis und dessen Schweregrad mittels ortsbezogener Dienste und Texteingaben zu berichten. Solche Informationen können als zusätzliche Informationsquelle in den Modellierungs- und Vorhersageprozess miteinbezogen werden.

Direct link to Lay Summary Last update: 21.07.2021

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Associated projects

Number Title Start Funding scheme
179017 Advancing hydrogeological modeling through novel tracer approaches, the explicit simulation of tracers and advanced inversion methods 01.12.2018 Project funding
162754 Integrating spatial predictions of vegetation, soils, geomorphology and hydrology for improved assessment of ecosystem services under climate change 01.01.2016 Interdisciplinary projects

Abstract

Hydrological models are an essential tool for water resources assessment and management. Advanced computational algorithms are capable of simulating the relevant physical processes and form the feedback mechanism across a wide range of spatial and temporal scales. However, a bottleneck of these models is the lack of environmental observations to calibrate model parameters and to assess the robustness of model predictions. WATERLINE will employ multi-source information from remote sensing, historical data, in-situ data from meteorological networks as well as crowdsourced data to improve hydrological models and their predictions. The relevant physical processes and heterogeneity of hydrological catchments need to be integrated in hydrological models as a basis for reliable model predictions. A major challenge in this endeavour is identifying the observation data with the highest information content to constrain model parameters.Unfortunately, neither in-situ networks nor remote sensing alone can provide sufficient information to capture the high spatial and temporal variability of hydrological processes. Recently, downscaling frameworks have been developed, building robust models between coarse scale products and high-resolution ancillary variables using in-situ measurements. The lack of in-situ measurements to train such models can be overcome by the growing availability of crowdsourced observations. WATERLINE will improve the efficiency and robustness of hydrological models through strategic integration of variables covering different spatial and temporal scales. Furthermore, we will optimize the computational performances to provide near real-time and short-term predictions of various hydrological states with unprecedented spatial detail. Improved representation of soil moisture, groundwater levels and recharge, stream discharge, and evapotranspiration can significantly advance the sustainable management of water resources for a wide range of stakeholders.The WATERLINE concept will be implemented through development of a web services tool with three modular applications, targeting a) use by scientists (data access, downscaling, filtering, uncertainty analysis, modelling applications), b) use by non-technically trained stakeholders, providing enhanced visualization outputs, in the form of maps, graphs, indices enhanced with Augmented Reality and Virtual Reality functionalities, and c) crowdsourcing of hydrological information where a random user can report about any hydrological-related event and its severity using location-based service and textual input, which is then considered as an additional source of information for modelling and forecast estimation. User groups, such as farmers, water authorities, fire brigade services, entrepreneurs in tourist, agricultural, industrial sector will be actively involved in the development of the web-based interfaces to ensure the usability and adoption of the outcomes by relevant user communities.
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