HydroSuite

Table of Contents

• Introduction
• Description of HydroSuite
• Community Involvement
• List of Repositories
• Acknowledgements
• References

Introduction

This repository serves as an information site for the framework named HydroSuite - A collection of open source software developed using web technologies tailoring hydrological and environmental domain. For more information, the reader should explore the list of repositories below.

Description of HydroSuite

HydroSuite is a compilation of open-source software and libraries that encompasses a broad range of topics within the hydrological and environmental domains. These topics include:

• Data
• Computing
• Communication
• Community Portals

The projects within HydroSuite have been developed using state-of-the-art web technologies designed to foster better integration between client and server-side resources. This highly data and modeling-driven concept facilitates collaboration among diverse entities for the development of new tools and libraries. Furthermore, it expands existing semantics to create a more robust and highly scalable product. HydroSuite is an integral part of a larger ecosystem that incorporates various open-source tools for education, research, and operational purposes.

The purpose of the suite is to democratize the tools created to cater to diverse needs and foster an environment where the tools developed within the scope of HydroSuite can be utilized by a wider public.

Community Involvement

All the repositories listed below are open source and encourage collaboration by allowing the addition of various features, improvements, and comments to the code through the utilization of pull requests, contacting the respective authors via email, or raising issues in the repository.

List of Repositories

Topic	Library	Repositories	References
Data	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	uhilab/WaterBench	Demir et al., 2022
	IowaRain	uihilab/IowaRain	Sit et al., 2021
Computing	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
Communication	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
Community Portals	EarthAIHub	uihilab/EarthAIHub	Sit & Demir, 2023
	HLM Web	uihilab/HLM-Web	Ewing et al., 2022b
	HydroLSTM	uihilab/HydroLSTM	Xiang et al., 2021
	HydroLang Models	uihilab/HydroLang-Models
	Training Repos	uihilab/Education

Acknowledgements

These projects have developed by the University of Iowa Hydroinformatics Lab (UIHI Lab):

https://hydroinformatics.uiowa.edu/.

References

References

• 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

• 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

• 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

• 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

• 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. EarthArxiv preprint. https://doi.org/10.31223/x5pq5r

• 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

• Ewing, G., Mantilla, R., Krajewski, W., & Demir, I. (2022b). 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

• 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

• 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

• 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

• 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

• 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

• 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

• Sit, M., Seo, B.C. and Demir, I., 2021. Iowarain: A statewide rain event dataset based on weather radars and quantitative precipitation estimation. arXiv preprint arXiv:2107.03432.

• 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

• Xiang, Z., Demir, I., Mantilla, R., & Krajewski, W. (2021). A regional semi-distributed Streamflow model using deep learning. https://doi.org/10.31223/x5gw3v

• 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