D. Yates | USGS Science

USGS2009

Migration patterns and wintering range of common loons breeding in the Northeastern United States

A study, using satellite telemetry, was conducted to determine the precise migration patterns and wintering locations of Common Loons (Gavia immer) breeding in the northeastern United States. Transmitters were implanted in 17 loons (16 adults and one juvenile) that were captured on breeding lakes in New York, New Hampshire, and Maine during the summers of 2003, 2004, and 2005. Transmitters from ten of the birds provided adequate location data to document movement to wintering areas. Most adult loons appeared to travel non-stop from breeding lakes, or neighboring lakes (within 15 km), to the Atlantic coast. Adult loons marked in New Hampshire and Maine wintered 152 to 239 km from breeding lakes, along the Maine coast. Adult loons marked in the Adirondack Park of New York wintered along the coasts of Massachusetts (414 km from breeding lake), Rhode Island (362 km), and southern New Jersey (527 km). Most of the loons remained relatively stationary throughout the winter, but the size of individual wintering areas of adult loons ranged from 43 to 1,159 km 2 , based on a 95% fixed kernel utilization distribution probability. A juvenile bird from New York made a number of stops at lakes and reservoirs en route to Long Island Sound (325 km from breeding lake). Maximum functional life of transmitters was about 12 months, providing an opportunity to document spring migration movements as well. This work provides essential information for development and implementation of regional Common Loon conservation strategies in the Northeastern U.S.

Waterbirds↗

USGS2001

Evaluation of flash-flood discharge forecasts in complex terrain using precipitation

Operational prediction of flash floods produced by thunderstorm (convective) precipitation in mountainous areas requires accurate estimates or predictions of the precipitation distribution in space and time. The details of the spatial distribution are especially critical in complex terrain because the watersheds are generally small in size, and small position errors in the forecast or observed placement of the precipitation can distribute the rain over the wrong watershed. In addition to the need for good precipitation estimates and predictions, accurate flood prediction requires a surface-hydrologic model that is capable of predicting stream or river discharge based on the precipitation-rate input data. Different techniques for the estimation and prediction of convective precipitation will be applied to the Buffalo Creek, Colorado flash flood of July 1996, where over 75 mm of rain from a thunderstorm fell on the watershed in less than 1 h. The hydrologic impact of the precipitation was exacerbated by the fact that a significant fraction of the watershed experienced a wildfire approximately two months prior to the rain event. Precipitation estimates from the National Weather Service's operational Weather Surveillance Radar-Doppler 1988 and the National Center for Atmospheric Research S-band, research, dual-polarization radar, colocated to the east of Denver, are compared. In addition, very short range forecasts from a convection-resolving dynamic model, which is initialized variationally using the radar reflectivity and Doppler winds, are compared with forecasts from an automated-algorithmic forecast system that also employs the radar data. The radar estimates of rain rate, and the two forecasting systems that employ the radar data, have degraded accuracy by virtue of the fact that they are applied in complex terrain. Nevertheless, the radar data and forecasts from the dynamic model and the automated algorithm could be operationally useful for input to surface-hydrologic models employed for flood warning. Precipitation data provided by these various techniques at short time scales and at fine spatial resolutions are employed as detailed input to a distributed-parameter hydrologic model for flash-flood prediction and analysis. With the radar-based precipitation estimates employed as input, the simulated flood discharge was similar to that observed. The dynamic-model precipitation forecast showed the most promise in providing a significant discharge-forecast lead time. The algorithmic system's precipitation forecast did not demonstrate as much skill, but the associated discharge forecast would still have been sufficient to have provided an alert of impending flood danger.

Journal of Hydrologic Engineering↗