ABSTRACT:

A synopsis of the progress made on the term project at the time of presentation Nov, 27 2017

ABSTRACT:

As global temperatures increase, the volatility of localized weather patterns increases. Precipitation distribution becomes more severe, leading to storm and flooding events with higher frequency and greater intensity (Armel et al, 2018). In order to adapt to this change, there is a need for the scientific community to advance our methods of predicting events of high precipitation and stream flows. The National Water Model (NWM) seeks to answer this call as a great step forwards in the precision and scope in which extreme weather events in the continental United States can be predicted. This study seeks to evaluate the accuracy of the NWM through comparison to observed stream flow data in a network of stream gages in the city of Austin, TX.

ABSTRACT:

The National Water Model is a recently developed hydrologic model that simulates observed and forecast streamflow over the entire continental United States. The model uses an advanced system of inputs to produce three ranges of water models: short-range (18-hour forecast), medium-range (10 day forecast), and long-range (30 day forecast). In this study, short-range streamflow data from the NWM was compared to independent stream gage data gathered from 32 points within the city of Austin. A visual representation of the statistical comparison was prepared in ArcGIS pro.