KARST: Predicting flow and transport in complex Karst systems

Información del proyecto

KARST

Identificador del acuerdo de subvención: 101071836

DOI

10.3030/101071836

Fecha de la firma de la CE 8 Marzo 2023

Fecha de inicio 1 Mayo 2023

Fecha de finalización 30 Abril 2029

Financiado con arreglo a

• European Research Council (ERC)

Coste total

€ 9 884 611,25

Aportación de la UE

€ 9 884 611,00

Coordinado por

AGENCIA ESTATAL CONSEJO SUPERIOR DE INVESTIGACIONES CIENTIFICAS
Spain

Periodic Reporting for period 2 - KARST (KARST: Predicting flow and transport in complex Karst systems)

Período documentado: 2024-11-01 hasta 2026-04-30

Resumen del contexto y de los objetivos generales del proyecto

Karst aquifers are a treasure and a threat: while up to 25 percent of the world population depends on them for drinking water, they also have capabilities for extremely fast conduction of water and contaminants. In the light of climate change, we need to prepare for extreme flooding and understand the consequences for karst aquifers. Despite their socio-economic importance, decades of research, and high-profile disasters, karst structures and processes remain notoriously difficult to assess. Because of the complexity of karst and its hidden nature, the foundations of flow and transport models in karst systems are weak. Key phenomena related to extreme events such as flash floods and heavy tails in tracer recovery are still beyond current modeling capabilities. KARST will establish the next generation of coupled stochastic modeling frameworks to predict karst processes, assess the vulnerability of karst aquifers, and forecast their response to extreme events. Our approach will bridge structures and processes on all scales, far beyond the capabilities of current theories and computer simulations. This will be achieved by targeting three key objectives: (i) Identification and quantification of flow and transport at the conduit scale. (ii) Characterization and modeling of karst network structure at the catchment scale. (iii) Derivation of a new upscaled approach to predict karst processes at different resolution scales. Together, this will result in an unprecedented multiscale modeling framework for the prediction of flow and transport in karst.

Trabajo realizado desde el comienzo del proyecto hasta el final del período abarcado por el informe y los principales resultados hasta la fecha

KARST progresses in all work packages and tasks as planned. In WP1, UNINE has continued scanning individual karst geometries and thus extended the LIDAR data base. INRIA progressed with the 3D printing of cave models for the laboratory experiments and fabricated a total of 6 cave models according to the LIDAR scans and 2 cave models with idealized random and periodic geometries. IFPEN has validated the experimental setup for turbulent and laminar flow experiments, and installed and tested the setup for particle imaging velocimetry and particle tracking velocimetry. Experiments have been performed for regular pipes, wavy pipe geometries and two cave models. CSIC has implemented an immersed boundary method to numerically represent complex cave wall geometries, and a random walk particle tracking simulator. It has performed direct numerical simulations for laminar and turbulent flows in wavy pipe geometries and in real cave geometries, as well as particle tracking on wavy pipe geometries. In WP2, UNINE has continued collecting data sets of karst network maps from around the world (>100 networks world-wide, the currently largest karst network data base in the world). UNINE has continued advancing in karst simulation and characterization together with UL. In WP3, CSIC has developed the first dedicated simulator for laminar and turbulent flow in karst networks under pressurized and unsaturated flow conditions (https://openkarst.org). IFPEN and CSIC have progressed in the characterization and upscaling of network flow network simplification, and started the systematic quantification and upscaling of network scale flow. In WP 4, IFPEN has initiated work on flood prediction, UNINE in collaboration with CSIC have initiated the modelling of a karst aquifer in Switzerland based on the openKARST model, UL, IFPEN and CSIC have been working on the emergence of karst structure using both numerical models and analogue experiments.

Avances que van más allá del estado de la técnica e impacto potencial esperado (incluida la repercusión socioeconómica y las implicaciones sociales más amplias del proyecto hasta la fecha)

In the following, we summarize the main results during the first 36 months.
 
WP1:
 
•    Unprecedented inventory of three-dimensional cave geometries at the conduit scale
•    Critical Reynolds number for transition to turbulent flow conditions decreases with increasing aperture variability.
•    Colebrook-White model and similar cannot be used for flow parameterization in strongly variable conduits.
 
WP2:
 
•    Unprecedented data set of karst network geometries worldwide
•    Novel simulator for stochastic karst networks based on combination of GraphRNN and GraphDDPM
•    Novel approaches for karst network classification based on combined graph theoretical and speleogenetical approach.
 
WP3:
 
•    Fully coupled non-linear network flow simulator for pressurized-open-channel flow under laminar and turbulent flow conditions
•    Network scale pressurized flow can be quantified by an effective friction factor that depends on the network heterogeneity
•    Network scale transport can be predicted by a stochastic time-domain random walk model in terms of the flow statistics under laminar and turbulent flow conditions.