Deputy Regional Director
Office of the Northeast Regional Director
Email:
jkiang@usgs.gov
Office Phone:
703-648-5364
Fax:
703-648-6693
ORCID:
0000-0003-0653-4225
Location
John W Powell FB
12201 Sunrise Valley Drive
Reston
, VA
20192-0002
US
Supervisor:
Michael H Tupper
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There has been increasing attention placed on the need for water availability information at ungauged locations, particularly related to balancing human and ecological needs for water. Critical to assessing water availability is the necessity for daily streamflow time series; however, most of the rivers in the United States are ungauged. This proposal leverages over $1M currently allocated to the USGS National Water Census Program towards developing an integrated modeling approach to estimate daily streamflow at ungauged locations, with the ultimate goal of providing daily streamflow estimates at 160,000 ungauged catchments across the United States. By assembling a diverse and prolific group of international scientists,...
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Several USGS National Programs require data from USGS streamgages for statistical analyses and for model calibration and verification. In support of those programs, a dataset containing locations, basin characteristics, and regulation information for USGS streamgages was created. This dataset includes most of the streamgages in GAGES-II (Falcone, 2011) plus 5519 additional sites and incorporates reviews by scientists in many USGS Water Science Centers. Each phase of the SWIM project will be published as a data release and available below. USGS Streamgages in the Conterminous United States Indexed to NHDPlus v2.1 Flowlines to Support Streamgage Watershed InforMation (SWIM), 2021 includes location information for...
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This data release replicates the methods detailed in the 2017 publication titled "Improving predictions of hydrological low-flow indices in ungaged basins using machine learning" for a different data set. The original data set and the associated readme file for the model archive can be viewed here: https://doi.org/10.5066/F7CR5S4T. The original data set contained streamflow data for sites located in South Carolina, Georgia, and Alabama. The data set used in this data release is for 6 states in the Southern Midwest U.S.A. The datafile contains the annual minimum seven-day mean streamflow with an annual exceedance probability of 90% (7Q10) for 173 basins in Arkansas (AR), Iowa (IA), Kansas (KS), Missouri (MO), Nebraska...
Categories: Data;
Tags: Arkansas,
Iowa,
Kansas,
Missouri,
Nebraska, All tags...
Oklahoma,
USGS Science Data Catalog (SDC),
Water Resources,
low flow,
machine learning,
regionalization,
statistical modeling,
streamflow, Fewer tags
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This data set contains U.S. Geological Survey (USGS) streamgage identification numbers, begin and end years of the periods of streamflow record tested, Sen slope trends in the annual minimum 7-day streamflow for the period of record tested, the p-values (significance) of the trends, and the trend Sen slopes standardized by the standard deviations of the residual errors defined as the difference between observations and the Sen slope lines, for 174 USGS streamgages with 56 to 75 years of record in the Chesapeake Bay watershed, Mid-Atlantic U.S.
Categories: Data;
Tags: Chesapeake Bay,
Delaware,
Maryland,
New York,
Pennsylvania, All tags...
USGS Science Data Catalog (SDC),
Virginia,
Water Resources,
West Virginia,
streamflow, Fewer tags
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In the past, hydrologic modeling of surface water resources has mainly focused on simulating the hydrologic cycle at local to regional catchment modeling domains. There now exists a level of maturity among the catchment, global water security, and land surface modeling communities such that these communities are converging toward continental domain hydrologic models. This commentary, written from a catchment hydrology community perspective, provides a review of progress in each community toward this achievement, identifies common challenges the communities face, and details immediate and specific areas in which these communities can mutually benefit one another from the convergence of their research perspectives....
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