{"id":18368960,"url":"https://github.com/cheginit/si_2019_coastal","last_synced_at":"2025-10-30T23:25:28.187Z","repository":{"id":109632938,"uuid":"192623318","full_name":"cheginit/SI_2019_Coastal","owner":"cheginit","description":"Process-based assessment of US Gulf and East coast","archived":false,"fork":false,"pushed_at":"2019-07-17T03:59:43.000Z","size":242778,"stargazers_count":2,"open_issues_count":0,"forks_count":3,"subscribers_count":4,"default_branch":"master","last_synced_at":"2025-04-06T17:37:46.196Z","etag":null,"topics":["coastal-modelling","national-water-model","numerical-analysis"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/cheginit.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2019-06-18T23:02:32.000Z","updated_at":"2020-03-13T15:10:33.000Z","dependencies_parsed_at":"2023-09-25T07:00:33.479Z","dependency_job_id":null,"html_url":"https://github.com/cheginit/SI_2019_Coastal","commit_stats":{"total_commits":102,"total_committers":3,"mean_commits":34.0,"dds":"0.18627450980392157","last_synced_commit":"4064d323bc62ce2f47a7af41b9a11ea5538ad181"},"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/cheginit/SI_2019_Coastal","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cheginit%2FSI_2019_Coastal","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cheginit%2FSI_2019_Coastal/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cheginit%2FSI_2019_Coastal/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cheginit%2FSI_2019_Coastal/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/cheginit","download_url":"https://codeload.github.com/cheginit/SI_2019_Coastal/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cheginit%2FSI_2019_Coastal/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":281731426,"owners_count":26551804,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-10-29T02:00:06.901Z","response_time":59,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["coastal-modelling","national-water-model","numerical-analysis"],"created_at":"2024-11-05T23:28:00.110Z","updated_at":"2025-10-30T23:25:28.126Z","avatar_url":"https://github.com/cheginit.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Coastal Group: Roll Models\n\nAs part of summer institute 2019 held in National Water Center, Coastal Group works towards systematic analysis of large-scale modeling of coastal areas.\n\n## Project Management\n\u003cimg src=\"https://github.com/taataam/SI_2019_Coastal/blob/master/src/gantt/Gantt.png\" width=\"800\"\u003e\n\n## Objectives\n\nIdentify contributions of relevant physical processes to total water prediction by modeling idealized scenarios in coastal transition zones to provide a framework for efficient forecasting.\n\n## Idealized domains\n\nThe idealized domains were inspired by rivers and bays geometries over the Gulf and East Coast.\n\n A few metrics were chosen to compare different rivers and bays and scale the idealized domains.\n \n  Bay/Estuary geometry:\n- **Wt** Bay width at river end (upstream) - Wt = Wr in triagular geometry\n- **Wb** Bay width at ocean end (downstream)\n- **Lb** Bay length \n- Parameters:\n  * Rbr = Wb / Wr\n  * Rbt = Wb / Wt\n  * Rlb = Lb / Wb\n   \n River geometry:\n- **SI**nuosity = Curvilinear Length / Straight Line Length \n- **Wr** River width\n\nThree main **Classes** determined for this analysis:\n  1) River discharge directly in the ocean\n  2) River discharge in triangular bay\n  3) River discharge in trapezoidal/rectangular bay\n  \nFor **Class 1**, two subdivisions were created to evaluate river sinuosity contribution in comparison with a straight line river:\n  A) SI = 1\n  B) SI = 1.45\n\nFor **Classes 2** and **3**, three subdivisions were created to include the analysis of a barrier island between the bay and the ocean.\n  A) SI = 1\n  B) SI = 1.45\n  C) SI = 1 with barrier island\n\nIdealized models domains\n\n\u003cimg src=\"https://github.com/taataam/SI_2019_Coastal/blob/master/docs/Fig_Domains.png\" width=\"600\"\u003e\n\n## Modeling configuration\n\nA set of scenarios was created to evaluate water levels under tides forcing, storm surge, and discharge and roughness variation.\n\nSimulation Scenarios:\n- **R**oughness Manning's (-)\n- **D**ischarge (cms)\n- **T**ides: **P**redicted, **S**torm Surge\n\n|      | Simulation Name |   R   |   D  |    T    |            status            |\n|:----:|:---------------:|:-----:|:----:|:-------:|:----------------------------:|\n|  S1  |     **Ref**     | 0.025 |    0 |    P    |   \u003cul\u003e\u003cli\u003e- [x] \u003c/li\u003e\u003c/ul\u003e   |\n|  S2  |       R20       | 0.020 |    0 |    P    |   \u003cul\u003e\u003cli\u003e- [x] \u003c/li\u003e\u003c/ul\u003e   |\n|  S3  |       R30       | 0.030 |    0 |    P    |   \u003cul\u003e\u003cli\u003e- [x] \u003c/li\u003e\u003c/ul\u003e   |\n|  S4  |      D1000      | 0.025 | 1000 |    P    |   \u003cul\u003e\u003cli\u003e- [x] \u003c/li\u003e\u003c/ul\u003e   |\n|  S5  |        TS       | 0.025 |    0 |    S    |   \u003cul\u003e\u003cli\u003e- [x] \u003c/li\u003e\u003c/ul\u003e   |\n|  S6  |       D100      | 0.025 |  100 |    P    |   \u003cul\u003e\u003cli\u003e- [x] \u003c/li\u003e\u003c/ul\u003e   |\n|  S7  |       D200      | 0.025 |  200 |    P    |   \u003cul\u003e\u003cli\u003e- [x] \u003c/li\u003e\u003c/ul\u003e   |\n|  S8  |       D500      | 0.025 |  500 |    P    |   \u003cul\u003e\u003cli\u003e- [x] \u003c/li\u003e\u003c/ul\u003e   |\n\n## Results\n\n- Identification of tidal signal in the river upstream for under different geometries and scenarios\n- Identification of river and bay geometry contribution, as well as roughness, discharge, tides and storm surge in total water prediction\n\n## Deliverable\n\n- Final Report and Presentation\n\n## Instructions\nThe following steps should be taken for using the plotting scripts:\n1. Install docker.\n2. Change directory to `src/docker` and create an image from the `Dockerfile`:\n```bash\ndocker build -t plot .\n```\n3. Copy the plotting scripts to the folder that contains the D-Flow outputs and run one of the script e.g., `cross_section.py`, as follows:\n```bash\ndocker run -v \"$PWD\":/home/plot plot python cross_section.py C2_A1_S1_R25_D0_TPG\n```\n\n\nThe following steps should be taken for using `tide_constituents.py`:\n1. Install Anaconda and load it in a command line.\n2. Run the following command to create a new environment called `tides`:\n```bash\nconda create -n tides pip requests shapely beautifulsoup4 pandas scipy\n```\nthen activate the environment ```conda activate tides```.\n\n3. Install some extra packages with `pip`:\n```bash\npip install py_noaa baker astronomia filelike pyparsing\n```\n4. Clone the tappy repository to a location and install it:\n```bash\ngit clone -b py3 https://github.com/taataam/tappy.git\ncd tappy\npython setup.py install\n```\n\n\nAn example showing how to use the code is provided in `src/tide_constituents/mobile_bay.py`\n\nThe following steps should be taken for using `gantt.py`:\n1. Install Anaconda and load it in a command line.\n2. Run the following command to create a new environment called `gantt`:\n```bash\nconda create -n gantt plotly pandas psutil\n```\nthen activate the environment ```conda activate gantt```.\n\n3. Install an extra packages:\n```bash\nconda install -c plotly plotly-orca\n``` \n4. Then go the script's directory and run it:\n```bash\ncd src/gantt\npython gantt_chart.py\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcheginit%2Fsi_2019_coastal","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcheginit%2Fsi_2019_coastal","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcheginit%2Fsi_2019_coastal/lists"}