Name: A National Streamflow Network Gap Analysis (en Inglés)
Price: 38.55 USD
Availability: InStock
Author: Stewart, David W. ; Archfield, Stacey A. ; Osborne, Emily B.
ISBN: 9781500265854

portada A National Streamflow Network Gap Analysis (en Inglés)

A National Streamflow Network Gap Analysis (en Inglés)

Formato

Libro Físico

Autor

Editorial

Idioma

Inglés

N° páginas

Encuadernación

Tapa Blanda

Dimensiones

28.0 x 21.6 x 0.5 cm

Peso

0.23 kg.

ISBN13

9781500265854

Categorías

Ríos y lagos
La tierra: historia natural general. interés general

A National Streamflow Network Gap Analysis (en Inglés)

David W. Stewart (Autor) · Stacey A. Archfield (Autor) · Emily B. Osborne (Autor) · Createspace · Tapa Blanda

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Reseña del libro "A National Streamflow Network Gap Analysis (en Inglés)"

The U.S. Geological Survey (USGS) conducted a gap analysis to evaluate how well the USGS streamgage network meets a variety of needs, focusing on the ability to calculate various statistics at locations that have streamgages (gaged) and that do not have streamgages (ungaged). This report presents the results of analysis to determine where there are gaps in the network of gaged locations, how accurately desired statistics can be calculated with a given length of record, and whether the current network allows for estimation of these statistics at ungaged locations. The analysis indicated that there is variability across the Nation's streamflow data-collection network in terms of the spatial and temporal coverage of streamgages. In general, the Eastern United States has better coverage than the Western United States. The arid Southwestern United States, Alaska, and Hawaii were observed to have the poorest spatial coverage, using the dataset assembled for this study. Except in Hawaii, these areas also tended to have short streamflow records. Differences in hydrology lead to differences in the uncertainty of statistics calculated in different regions of the country. Arid and semiarid areas of the Central and Southwestern United States generally exhibited the highest levels of interannual variability in flow, leading to larger uncertainty in flow statistics.