/HydroSuite

HydroSuite

HydroSuite

Table of Contents

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.

hydrosuite-arch

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. Environmental Modelling & Software, 106068. https://doi.org/10.1016/j.envsoft.2024.106068

  • 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