Search Results for "river model"

Caesar Lisflood is a geomorphological / Landscape evolution model that combines the Lisflood-FP 2d hydrodynamic flow model (Bates et al, 2010) with the CAESAR geomorphic model to simulate erosion and deposition in river catchments and reaches over time scales from hours to 1000's of years. These sourceforge pages provide downloads of the .exe and the source code for CAESAR-lisflood and instructions and additional documentation can be found in the Wiki tab. ...

Please go to project home (https://hypeweb.smhi.se/model-water/) or wiki-pages (http://hype.smhi.net/wiki/doku.php?id=start) for more information. The hydrological model HYPE is developed at the Swedish Meteorological and Hydrological Institute (SMHI). The model simulates water, nutrients and other substances in small and large river catchments. Included in the project is HYSS, which is needed to run the model.

Input 1 - A training dataset (multiple observations) of up to four variables (predictors) against one (response variable) Input 2 - A test dataset (multiple observations) of the same four variables with unknown response variable Output - Calculation of the response variable for each test observation using fuzzy logic or fuzzy rule-based Bayesian algorithms HABFUZZ is a habitat model, which can be used in ecohydraulic modelling applications for the calculation of the instream habitat suitability in various discharge scenarios in a simulated river reach. It comes with no graphical user interface but it's a one-click tool. Just provide your input and let HABFUZZ provide you the output. The HABFUZZ manual https://github.com/chtheodoro/habfuzz/blob/master/HABFUZZ_v2.5_manual.pdf HABFUZZ in the Journal of Open Source Software http://joss.theoj.org/papers/1ad27db8f0976c28a75e20d34eba5ee2 HABFUZZ website https://chtheodoro.wixsite.com/habfuzz

This ArcGIS toolbox is used for linking the data from the field measurements of the river bed and Digital Terrain Model (DTM). The main assumption is that the tools included in the RiverBox toolbox will simplify the data processing before the preparation of the river flow model. The most important element of such process is generation of river bed batymetry on the basis of the measurements. Such batymetry should be in the form of typical DTM to be easily linked with DTM of the river valley. ...

...It provides all the latest state-of-the-art models (transformers, attention models, GRUs) and cutting-edge concepts with easy-to-understand interpretability metrics, cloud provider integration, and model serving capabilities. Flow Forecast was the first time series framework to feature support for transformer-based models and remains the only true end-to-end deep learning for time series forecasting framework. Currently, Task-TS from CoronaWhy primarily maintains this repository. Pull requests are welcome. Historically, this repository provided open-source benchmarks and codes for flash flood and river flow forecasting. ...

KLT-IV v1.0 has been designed to offer a user-friendly graphical user interface for the determination of river flow velocity and river discharge using videos acquired using a variety of fixed and moving platforms. KLT-IV employs optical flow and computer vision techniques for the tracking of features present on the river surface with pixel displacements being converted to real-world velocities using an optimised camera model approach.