the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
DebrisInterMixing-2.3: a finite volume solver for three-dimensional debris-flow simulations with two calibration parameters – Part 2: Model validation with experiments
Albrecht von Boetticher
Jens M. Turowski
Brian W. McArdell
Dieter Rickenmann
Marcel Hürlimann
Christian Scheidl
James W. Kirchner
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smartpebbles allow for the measurement of those conditions directly if a suitable framework for analysis is followed. This paper connects such a framework with the physics used to described sediment motion and presents a series of laboratory and field smart-pebble deployments. Those quantify how grain shape affects the motion of coarse sediments in rivers.
Where does water go when it rains?. Here we present a new way to measure how the terrestrial water cycle partitions precipitation into its two ultimate fates:
green waterthat is evaporated or transpired back to the atmosphere and
blue waterthat is discharged to stream channels. Our analysis may help in gauging the vulnerability of both water resources and terrestrial ecosystems to changes in rainfall patterns.
discharge sensitivityof Fyw and relate it to the dominant streamflow-generating mechanisms.
cmgo(R package) that meets the requirements of academic research.
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Inaccuracies in air–sea heat fluxes severely degrade the accuracy of ocean numerical simulations. Here, we use artificial neural networks to correct air–sea heat fluxes as a function of oceanic and atmospheric state predictors. The correction successfully improves surface and subsurface ocean temperatures beyond the training period and in prediction experiments.
FINAM is not a model), a new coupling framework written in Python to dynamically connect independently developed models. Python, as the ultimate glue language, enables the use of codes from nearly any programming language like Fortran, C++, Rust, and others. FINAM is designed to simplify the integration of various models with minimal effort, as demonstrated through various examples ranging from simple to complex systems.
This study introduces a new 3D lake–ice–atmosphere coupled model that significantly improves winter climate simulations for the Great Lakes compared to traditional 1D lake model coupling. The key contribution is the identification of critical hydrodynamic processes – ice transport, heat advection, and shear-driven turbulence production – that influence lake thermal structure and ice cover and explain the superior performance of 3D lake models to their 1D counterparts.