Developed by the Hydroinformatics Lab (IHI Lab) at Tulane University
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- Introduction
- Ecosystem Pillars
- Architecture Diagram
- Quick Start & Tutorials
- Community Involvement
- Acknowledgements
- References
HydroSuite is an open-source initiative that democratizes hydrological and environmental research through community-led development, transparent governance, and powerful browser-native technologies. It is a compilation of software, libraries, and datasets encompassing a broad range of topics, organized into four core pillars:
- Data — Domain-specific datasets, ontologies, and benchmarks
- Computing — Client-side parallel simulation and real-time data exchange
- Communication — Advanced geospatial visualization and rendering tools
- Community Portals — Model portals, AI assistants, and educational platforms
All projects within HydroSuite are built using state-of-the-art web technologies designed to foster integration between client and server-side resources, facilitating collaboration across academia, government, and industry.
Domain-specific datasets, ontologies, and benchmarks for flood events, rainfall, and streamflow — unified under open standards.
| Library | Repository | Reference |
|---|---|---|
| Flood-ML | uihilab/FloodML | Xiang & Demir, 2022 |
| Flood Event DOM | uihilab/Flood-Event-Data-Specification | Haltas et al., 2021 |
| IS Ontology | uihilab/floodontology | Sermet & Demir, 2019 |
| WaterBench | uihilab/WaterBench | Demir et al., 2022 |
| IowaRain | uihilab/IowaRain | Sit et al., 2021 |
WebAssembly and WebRTC libraries enabling client-side parallel simulations and real-time P2P data exchange without relying on dedicated servers.
| Library | Repository | Reference |
|---|---|---|
| HydroLang | uihilab/HydroLang | Erazo Ramirez et al., 2022 |
| HydroLang-ML | uihilab/HydroLang-ML | Erazo Ramirez et al., 2023 |
| HydroLang-BMI | uihilab/HydroLang-BMI | Ewing et al., 2024 |
| HydroCompute | uihilab/HydroCompute | Erazo Ramirez et al., 2024a |
| HydroRTC | uihilab/HydroRTC | Erazo Ramirez et al., 2024b |
Advanced 3D, VR, and geospatial rendering tools specifically optimized for water events, flood impacts, and watershed delineation — running directly in the browser.
| Library | Repository | Reference |
|---|---|---|
| RasterJS | uihilab/RasterJS | Shahid et al., 2023 |
| Hydro3DJS | uihilab/Hydro3DJS | — |
| Instant Expert | uihilab/InstantExpert | Sermet & Demir, 2021 |
| GeospatialVR | uihilab/GeospatialVR | Sermet & Demir, 2022 |
| Watershed Delineation | uihilab/Watershed-Delineation | Sit et al., 2019 |
Model portals, collaborative learning platforms, AI assistants, and open educational tools driving capacity building worldwide.
| Library | Repository | Reference |
|---|---|---|
| EarthAIHub | uihilab/EarthAIHub | Sit & Demir, 2023 |
| HLM Web | uihilab/HLM-Web | Ewing et al., 2022 |
| HydroLSTM | uihilab/HydroLSTM | Xiang et al., 2021 |
| HydroLang Models | uihilab/HydroLang-Models | — |
| Training Repos | Tulane Hydroinformatics Education | — |
The HydroSuite core computing libraries are available as npm packages and can be embedded directly in any webpage. Interactive tutorials run fully in-browser — no server required.
| Library | npm | Tutorial |
|---|---|---|
| HydroLang | npm install hydrolang |
Tutorial |
| HydroCompute | npm install hydrocompute |
Tutorial |
| HydroRTC | npm install hydrortc |
Tutorial |
🧪 Try it live: Explore the HydroSuite libraries directly in your browser using the CodeSandbox Live Demo.
HydroSuite is built by and for the community. All repositories are open source and welcome contributions through:
- Pull Requests — Feature additions, bug fixes, and improvements
- Email — Reach out to the respective library authors directly
- Issues — Raise issues in the specific repository
We invite scientists, engineers, educators, and developers worldwide to join us in building the next generation of web-native water computing tools.
⭐ Enjoying HydroSuite? A star on this repository goes a long way — it helps others discover the project and signals community support for continued open-source development. Star HydroSuite ↗
HydroSuite is developed and maintained by the Hydroinformatics Lab (HILab) at Tulane: https://hydroinformatics.tulane.edu/
This initiative is supported by the National Science Foundation (NSF) through the Pathways to Enable Open-Source Ecosystems (POSE) program.
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Demir, I., Xiang, Z., Demiray, B., & Sit, M. (2022). WaterBench-Iowa: A large-scale benchmark dataset for data-driven streamflow forecasting. Earth System Science Data, 14(12), 5605–5616. https://doi.org/10.5194/essd-14-5605-2022
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Erazo Ramirez, C., Sermet, Y., Molkenthin, F., & Demir, I. (2022). HydroLang: An open-source web-based programming framework for hydrological sciences. Environmental Modelling & Software, 157, 105525. https://doi.org/10.1016/j.envsoft.2022.105525
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Erazo Ramirez, C., Sermet, Y., & Demir, I. (2023). HydroLang markup language: Community-driven web components for hydrological analyses. Journal of Hydroinformatics, 25(4), 1171–1187. https://doi.org/10.2166/hydro.2023.149
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Erazo Ramirez, C., Sermet, Y., & Demir, I. (2024a). HydroCompute: An open-source web-based computational library for hydrology and environmental sciences. Environmental Modelling & Software, 175, 106005. https://doi.org/10.1016/j.envsoft.2024.106005
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Erazo Ramirez, C., Sermet, M., Shahid, M., & Demir, I. (2024b). HydroRTC: A web-based data transfer and communication library for collaborative data processing and sharing in the hydrological domain. Environmental Modelling & Software, 106068. https://doi.org/10.1016/j.envsoft.2024.106068
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Ewing, G., Erazo Ramirez, C., Vaidya, A., & Demir, I. (2024). Client-side web-based model coupling using basic model interface for hydrology and water resources. Journal of Hydroinformatics, 26(2), 494–502. https://doi.org/10.2166/hydro.2024.212
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Ewing, G., Mantilla, R., Krajewski, W., & Demir, I. (2022). Interactive hydrological modelling and simulation on client-side web systems: An educational case study. Journal of Hydroinformatics, 24(6), 1194–1206. https://doi.org/10.2166/hydro.2022.061
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Haltas, I., Yildirim, E., Oztas, F., & Demir, I. (2021). A comprehensive flood event specification and inventory: 1930–2020 Turkey case study. International Journal of Disaster Risk Reduction, 56, 102086. https://doi.org/10.1016/j.ijdrr.2021.102086
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Sermet, Y., & Demir, I. (2019). Towards an information centric flood ontology for information management and communication. Earth Science Informatics, 12(4), 541–551. https://doi.org/10.1007/s12145-019-00398-9
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Sermet, Y., & Demir, I. (2021). A Semantic Web framework for automated smart assistants: A case study for public health. Big Data and Cognitive Computing, 5(4), 57. https://doi.org/10.3390/bdcc5040057
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Sermet, Y., & Demir, I. (2022). GeospatialVR: A web-based virtual reality framework for collaborative environmental simulations. Computers & Geosciences, 159, 105010. https://doi.org/10.1016/j.cageo.2021.105010
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Shahid, M., Sermet, Y., Mount, J., & Demir, I. (2023). Towards progressive geospatial information processing on web systems: A case study for watershed analysis in Iowa. Earth Science Informatics, 16(2), 1597–1610. https://doi.org/10.1007/s12145-023-00993-x
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Sit, M., & Demir, I. (2023). Democratizing deep learning applications in earth and climate sciences on the web: EarthAIHub. Applied Sciences, 13(5), 3185. https://doi.org/10.3390/app13053185
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Sit, M., Seo, B.C., & Demir, I. (2021). IowaRain: A statewide rain event dataset based on weather radars and quantitative precipitation estimation. arXiv preprint arXiv:2107.03432.
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Sit, M., Sermet, Y., & Demir, I. (2019). Optimized watershed delineation library for server-side and client-side web applications. Open Geospatial Data, Software and Standards, 4(1). https://doi.org/10.1186/s40965-019-0068-9
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Xiang, Z., Demir, I., Mantilla, R., & Krajewski, W. (2021). A regional semi-distributed streamflow model using deep learning. https://doi.org/10.31223/x5gw3v
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Xiang, Z., & Demir, I. (2022). Flood markup language – A standards-based exchange language for flood risk communication. Environmental Modelling & Software, 152, 105397. https://doi.org/10.1016/j.envsoft.2022.105397
HydroSuite · Hydroinformatics Lab at Tulane · Open Source · Web-Native · Community-Governed