ABSTRACT:

The Flood Inundation Mapping (FIM) Visualization Deck is a web-based application designed to display and compare flood extent and depth information across various temporal and scenario conditions. It provides a front-end interface for accessing geospatial flood data and interacting with mapped outputs generated from hydraulic modeling.

Core Functions:
• Flood Extent Mapping: Visualizes flood extents from modeled scenarios (e.g., 2-year, 10-year, 100-year events) and real-time conditions based on streamflow observations or forecasts.
• Flood Depth Visualization: Displays depth rasters over affected areas, derived from hydraulic simulations (e.g., HEC-RAS).
• Scenario Comparison: Allows side-by-side viewing of multiple FIM outputs to support calibration or decision analysis.
• Layer Management Toolbox: Users can toggle basemaps, adjust layer transparency, load datasets, and control map extents.

Data Inputs:
• Precomputed flood inundation extents (raster/tile layers)
• Depth grids
• Stream gauge metadata
• Associated hydraulic model outputs

Technical Stack:
• Front-end: Built with JavaScript, primarily using Leaflet.js for interactive map rendering.
• Back-end Services: Uses GeoServer to serve raster tiles and vector layers (via WMS/WFS). Uses OGC-compliant services and REST endpoints for data queries.
• Data Formats: Raster layers (e.g., GeoTIFF, PNG tiles), vector layers (GeoJSON, shapefiles), elevation models, and model-derived grid outputs.
• Database: Integrates with a PostgreSQL/PostGIS backend or similar spatial database for hydrologic and geospatial data management.
• Deployment: Hosted via University of Iowa infrastructure, with modular UI elements tied to specific watersheds or study areas.

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 software introduces HydroLang, an open-source and integrated community-driven computational web framework for hydrology and water resources research and education. HydroLang employs client-side web technologies and standards to carry out various routines aimed at acquiring, managing, transforming, analyzing, and visualizing hydrological datasets. HydroLang consists of four major high-cohesion low-coupling modules: (1) retrieving, manipulating, and transforming raw hydrological data, (2) statistical operations, hydrological analysis, and model creation, (3) generating graphical and tabular data representations, and (4) mapping and geospatial data visualization. HydroLang's unique modular architecture and open-source nature allow it to be easily tailored into any use case and web framework, and it encourages iterative enhancements with community involvement to establish the comprehensive next-generation hydrological software toolkit. Case studies can be found in the repositories linked to the software.