Grantee Research Project Results
1999 Progress Report: A National Assessment of Low-Streamflow Estimation Using a Physically Based Statistical Methodology
EPA Grant Number: R826888Title: A National Assessment of Low-Streamflow Estimation Using a Physically Based Statistical Methodology
Investigators: Kroll, Charles , Vogel, Richard
Institution: The State University of New York , Tufts University
EPA Project Officer: Hahn, Intaek
Project Period: September 1, 1998 through August 31, 2001 (Extended to December 31, 2003)
Project Period Covered by this Report: September 1, 1998 through August 31, 1999
Project Amount: $363,500
RFA: Environmental Statistics (1998) RFA Text | Recipients Lists
Research Category: Human Health , Aquatic Ecosystems , Environmental Statistics
Objective:
Low streamflow estimates are crucial for water quality management, issuing and/or renewing National Pollution Discharge Elimination System (NPDES) permits, planning water supplies, hydropower, and irrigation systems, and for assessing the impact of prolonged droughts on aquatic ecosystems. Unfortunately, there is no agreed upon methodology for estimating low streamflow statistics in the United States. The current methods for estimating low streamflow statistics are based on techniques recommended for flood frequency analyses. Combining recent advances and new methods in both physical and statistical hydrology with Geographic Information System (GIS) mapping techniques will improve our ability to estimate low flow statistics in riverways throughout the entire United States. The methodology developed will provide water resource planners with a scientifically based procedure to estimate low streamflow statistics at both gauged and ungauged river sites throughout the United States. Physical-Statistical models developed will also aid in understanding the potential impact of global climate fluctuations on low streamflows.Progress Summary:
We are finishing the first segment of this research, which examined streamflow series at gauged river sites across the United States. This has involved three major tasks.- An Analysis of Trends in Low Streamflows in the United States Over the Past 50 Years. With much discourse involving global climate fluctuation, an important issue is whether we are observing any significant trends in streamflows. We have investigated the importance of accounting for both spatial and temporal correlation on a Mann-Kendall trend test, and the problems with employing trend tests with correlated data. Results indicate evidence of an upward trend in low streamflows in the upper Midwestern United States, which may be due to increased precipitation resulting from climate change. No significant trends were observed in other portions of the country.
- An Analysis of How Probability Distributions Fit Low Streamflow Series Throughout the United States. We used L-moment diagrams to analyze the goodness-of-fit of various probability distributions across the United States. Using an analysis of over 1,500 sites, it was still difficult to ascertain the "best" probability distribution to fit low streamflow series in various regions of the United States. Shifts in L-moments due to censoring indicated that a real-spaced probability distribution (such as GEV or Pearson) may better describe low streamflow series, though commonly a log-spaced distribution is employed in practice.
- The Development of a Watershed Characteristic Database Using a Geographic Information System. Using the TOPO30 1 km digital elevation model of the United States, we have delineated water boundaries for over 1,600 gauged river sites. Using many new digital grids, including grids of orographically weighted precipitation and temperature, land use, and geology, we are developing the most comprehensive database of watershed characteristics available. This information will then be employed in the physical and statistical modeling of low streamflows.
Future Activities:
Our next steps are to analyze various statistical and physical modeling techniques in estimated low streamflow statistics at ungauged river sites across the United States. Using a delete-one Jackknife simulation, a comparative analysis of various approaches will be performed. Approaches to be examined include regional regression, baseflow correlation, index-drought, and rainfall-runoff modeling. We expect the results to better indicate the uncertainty involved with various low streamflow statistic estimators, and provide a recommendation for each region of the United States as to the best methodology to employ.Journal Articles on this Report : 1 Displayed | Download in RIS Format
Other project views: | All 13 publications | 5 publications in selected types | All 5 journal articles |
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Type | Citation | ||
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Douglas EM, Vogel RM, Kroll CN. Trends in floods and low flows in the United States: impact of spatial correlation. Journal of Hydrology 2000;240(1-2):90-105. |
R826888 (1999) R826888 (2000) R824992 (Final) |
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Supplemental Keywords:
stochastic hydrology, surface water, groundwater., RFA, Scientific Discipline, Economic, Social, & Behavioral Science Research Program, Air, Ecosystem Protection/Environmental Exposure & Risk, Hydrology, Ecosystem/Assessment/Indicators, Ecosystem Protection, exploratory research environmental biology, Chemical Mixtures - Environmental Exposure & Risk, climate change, Ecological Effects - Environmental Exposure & Risk, Ecological Effects - Human Health, Ecology and Ecosystems, Atmospheric Sciences, Ecological Risk Assessment, Environmental Statistics, Ecological Indicators, ecological exposure, flood frequency analysis, risk assessment, estimating low stream flow, global environmental data, meteorology, physical environmental statistics research, streams, environmental risks, drinking water supplies, low stream flow estimation model, water resource planners, mitigation strategies, physically based statistical methodology, hydropower, statistical models, aquatic ecosystems, ecosystem impacts, stream flow, data analysis, data collection, spatial-temporal methods, water quality, data models, global warming, innovative statistical models, statistical methodology, land useProgress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.