ABSTRACT:

This presentation introduces HydroSuite, an open-source ecosystem of more than 140 software tools and libraries developed by the HydroInformatics Lab at Tulane University to support hydrological education, research, and operations. The collection is organized around four areas — data, computing, communication, and community portals — and is built on modern web technologies including WebAssembly, Web Workers, WebRTC, and WebGPU, with the goal of bringing complex hydrologic analysis into the browser with minimal server-side dependency. Core components include HydroLang, a client-side programming framework for hydrological analysis; HydroCompute, a multi-CPU and GPU parallel computing library; HydroRTC, a real-time communication library for decentralized data streaming and sharing; BMI-JS, a JavaScript implementation of the CSDMS Basic Model Interface for coupling models to models and data; and markup-based component libraries (HydroLang-ML and Geo-WC) that expose data retrieval and visualization from agencies such as USGS, EPA, NWS, and FEMA through custom HTML elements. The presentation also lays out a five-phase development roadmap that moves from technical client- and server-side coding toward more intuitive interfaces, including HydroBlox (a block-based visual programming environment), the HydroSuite AI Helper (LLM-driven code assistance), and HydroAI (a voice-enabled agentic interface that generates workflows on a map from natural language).

Acknowledgements:
This research was supported by the Cooperative Institute for Research to Operations in Hydrology (CIROH) with funding under award NA22NWS4320003 from the NOAA Cooperative Institute Program. The statements, findings, conclusions, and recommendations are those of the author(s) and do not necessarily reflect the opinions of NOAA.

ABSTRACT:

The data collected with Acoustic Doppler Current Profiler (ADCP)and Multi-Beam Echosounder (MBES) during a high flow in Mississippi River at Memphis for supporting numerical modeling and testing innovative bedload measurement technologies. These data were processed with a new image-based protocol applied to the acoustic maps collected by MBES and ADCP to proof the performance of a new technique, labelled Acoustic Mapping Velocimetry (AMV). The ADCP data processed with various protocols provided quantification of the bedload geometry and bedload transport rates (via AMV-ADCP technique), suspended sediment in water column (via customized algorithms to process the returned acoustic signal collected along the beams), and the flow hydrodynamics (via ADCP manufacturer processing algorithms).

The ADCP files are provided in customized formats used by the instrument manufacturers. For more information access the instrument manuals at: https://www.teledynemarine.com/brands/rdi/workhorse-sentinel-adcp and https://geo-matching.com/products/geoswath-4r-500-khz for ADCP and MBES, respectively.

ABSTRACT:

This is a cumulative rainfall map for Iowa for the period between August 24 and September 6, 2016.