Thomas C. Pagano

A Review of Quantitative Precipitation Forecasts and Their Use in Short- to Medium-Range Streamflow Forecasting

AbstractUnknown future precipitation is the dominant source of uncertainty for many streamflow forecasts. Numerical weather prediction (NWP) models can be used to generate quantitative precipitation forecasts (QPF) to reduce this uncertainty. The usability and usefulness of NWP model outputs depend on the application time and space scales as well as forecast lead time. For streamflow nowcasting (very short lead times; e.g., 12 h), many applications are based on measured in situ or radar-based real-time precipitation and/or the extrapolation of recent precipitation patterns. QPF based on NWP model output may be more useful in extending forecast lead time, particularly in the range of a few days to a week, although low NWP model skill remains a major obstacle. Ensemble outputs from NWP models are used to articulate QPF uncertainty, improve forecast skill, and extend forecast lead times. Hydrologic prediction driven by these ensembles has been an active research field, although operational adoption has lagge...

Application of Partial Least-Squares Regression in Seasonal Streamflow Forecasting

The application of partial least-squares regression (PLSR) in seasonal streamflow forecasting was investigated using snow water equivalent, precipitation, temperature from automatic Snow Telemetry sites, and previous flow conditions as input variables. The forecast performance of PLSR models was compared to principal components regression (PCR) models as well as to the Natural Resources Conservation Service (NRCS) official forecasts in three Rio Grande watersheds including the Rio Grande Headwater Basin, Conejos River Basin in Colorado, and Rio Grande Basin above Elephant Butte Reservoir, New Mexico. The results indicated that using a correlation-weighted precipitation index is a relatively effective method in both improving forecast accuracy and developing relatively parsimonious regression models. In comparison of PLSR and PCR, similar forecast accuracies were obtained for both methods in jackknife cross validation and the test period (2003–2007) although PLSR has higher calibration coefficient of deter...