Differentiable modelling to unify machine learning and physical models for geosciences
Process-based modelling offers interpretability and physical consistency in many domains of
geosciences but struggles to leverage large datasets efficiently. Machine-learning methods …
geosciences but struggles to leverage large datasets efficiently. Machine-learning methods …
[HTML][HTML] Sensitivity analysis of environmental models: A systematic review with practical workflow
Sensitivity Analysis (SA) investigates how the variation in the output of a numerical model
can be attributed to variations of its input factors. SA is increasingly being used in …
can be attributed to variations of its input factors. SA is increasingly being used in …
[HTML][HTML] The future of sensitivity analysis: an essential discipline for systems modeling and policy support
Sensitivity analysis (SA) is en route to becoming an integral part of mathematical modeling.
The tremendous potential benefits of SA are, however, yet to be fully realized, both for …
The tremendous potential benefits of SA are, however, yet to be fully realized, both for …
[HTML][HTML] A Matlab toolbox for global sensitivity analysis
Abstract Global Sensitivity Analysis (GSA) is increasingly used in the development and
assessment of environmental models. Here we present a Matlab/Octave toolbox for the …
assessment of environmental models. Here we present a Matlab/Octave toolbox for the …
Karst water resources in a changing world: Review of hydrological modeling approaches
Abstract Karst regions represent 7–12% of the Earth's continental area, and about one
quarter of the global population is completely or partially dependent on drinking water from …
quarter of the global population is completely or partially dependent on drinking water from …
Global sensitivity analysis in hydrological modeling: Review of concepts, methods, theoretical framework, and applications
Sensitivity analysis (SA) aims to identify the key parameters that affect model performance
and it plays important roles in model parameterization, calibration, optimization, and …
and it plays important roles in model parameterization, calibration, optimization, and …
A decade of Predictions in Ungauged Basins (PUB)—a review
Abstract The Prediction in Ungauged Basins (PUB) initiative of the International Association
of Hydrological Sciences (IAHS), launched in 2003 and concluded by the PUB Symposium …
of Hydrological Sciences (IAHS), launched in 2003 and concluded by the PUB Symposium …
Characterising performance of environmental models
In order to use environmental models effectively for management and decision-making, it is
vital to establish an appropriate level of confidence in their performance. This paper reviews …
vital to establish an appropriate level of confidence in their performance. This paper reviews …
[图书][B] Rainfall-runoff modelling: the primer
KJ Beven - 2012 - books.google.com
Rainfall-Runoff Modelling: The Primer, Second Edition is the follow-up of this popular and
authoritative text, first published in 2001. The book provides both a primer for the novice and …
authoritative text, first published in 2001. The book provides both a primer for the novice and …
Evaluating the performance of random forest for large-scale flood discharge simulation
L Schoppa, M Disse, S Bachmair - Journal of Hydrology, 2020 - Elsevier
The machine learning algorithm 'random forest'has been applied in many areas of water
resources research including discharge simulation. Due to low setup and operation cost …
resources research including discharge simulation. Due to low setup and operation cost …