A container-based approach for sharing environmental models as web services

Figures & data

Figure 1. OGMS-WS workflow diagram.

Table 1. Content of the Model Description Language (MDL) file.

Interface	Node	Information
Model description	AttributeSet	name, version, abstract, keywords, category
Model execution	Behavior	inputs, outputs, data formats
Model deployment	Runtime	entry function, hardware configuration, software dependencies

Figure 2. Generation of a model service deployment package.

Figure 3. OGMS-WS Service Management Page.

Figure 4. Local Services Items Module.

Figure 5. The OGMS-WS-Docker approach.

Figure 6. The workflow of the Streamflow Prediction System (gray boxes are inputs).

Figure 7. Interactions between users, service interface, OGMS-WS, and the model container.

Table 2. Variable design of the streamflow prediction service.

Service variable	Data	Format
Input 1: lsm_data	LSM Runoff NetCDF files	Zip file
Input 2: rapid_io_files	RAPID input files; River connectivity file Weight table Muskingum k file Muskingum x file Initialization file (optional)	Zip file
Input 3: python_file	The launch function of the system	Python file
Output: streamflow	Simulated streamflow result	NetCDF

Figure 8. Streamflow prediction service GUIs.

Figure 9. Streamflow results visualization.

Figure 10. High resolution river network in Bangladesh.

Table 3. Selected reach segments.

Reach	COMID	Located river
A	281577	Ganges
B	273300	Jamuna
C	288491	Padma
D	292364	Meghna

Figure 11. Simulated streamflow of selected reach segments.

Figure 12. Streamflow monthly distribution from 1995 to 2014.