Overview
Part A of the HEC-MetVue Time Series Sampling tutorial provides the HEC-MetVue project file, settings, and viewing the precipitation datasets for analyzing the June 2024 precipitation event that affected a number of the West North Central States through the following :
2024 June Rainfall
In 20-22 June 2024, a multi-day heavy rainfall event led to widespread flooding across southeast South Dakota, southwest Minnesota, and northwest Iowa. Observed rainfall amounts between 10 to 20 inches were reported and these amounts exceeded the 0.2-0.1% annual exceedance probability in some areas. The rapid onset of heavy rainfall created significant flash flooding and widespread riverine flooding. Record flooding was observed at 25 river points in the affected area (NWS 2024). This event led to widespread destruction and impacted many communities.
NWS Sioux Falls, SD Weather Forecast Office - Rainfall Total

Landsat Satellite Image Before Flooding

Landsat Satellite Image After Flooding

HEC-MetVue Project and Dataset orientation
For this exercise, observed and forecast datasets are available for you to inspect. The datasets include observed and forecasted precipitation for the Missouri River Basin extents from the National Weather Service. The HEC-MetVue project file contains four Map Windows with the different precipitation datasets.
- The "MBRFC Precip 1HR" Map Window uses the observed hourly quantitative precipitation estimate grids from the MBRFC.
- The "MBRFC QPF 6HR" Map Window uses the 6-hour quantitative precipitation forecast grids from the MBRFC.
- The "MRMS Precip 1HR" Map Window uses the observed hourly Multi-Radar/Multi-Sensor (MRMS) precipitation grids from the National Severe Storms Laboratory.
- The "WPC QPF 6HR" Map Window uses the 6-hour quantitative precipitation forecast grids from the Weather Prediction Center.
This tutorial will analyze the different datasets for the June 2024 event. The user will be able to:
- Compare two different observed products
- Compare two different forecasted products, and
- Compare a forecast to the actual observation that transpired.