Data-Driven Drought Prediction Project Model Outputs: Daily Streamflow and Streamflow Percentile Predictions for the Colorado River Basin Region

This metadata record describes outputs from 12 configurations of long short-term memory (LSTM) models which were used to predict streamflow drought occurrence at 384 stream gage locations in the Colorado River Basin region. The models were trained on data from 01-Oct-1981 to 31-Mar-2005 and validated over the period of record spanning 01-Apr-2005 to 31-Mar- 2014. The models use explanatory variable inputs described in Wieczorek (2023) (doi.org/10.5066/P98IG8LO) to predict daily streamflow and streamflow percentiles as described in Simeone (2022) (doi.org/10.5066/P92FAASD). Separate models were trained to predict daily streamflow and streamflow percentiles. Two types of percentiles were modeled: (1) fixed-threshold...

Categories: Data; Tags: Colorado River Basin, climatologyMeteorologyAtmosphere, deep learning, drought prediction, droughts, All tags... hydrology, long short-term memory, machine learning, modeling, river systems, statistical analysis, streamflow, streamflow percentiles, streamflow predictions, Fewer tags