Hydrologic Drought Decision Support System (HyDroDSS)

Abstract

For more information on the USGS-the Federal source for science about the Earth, its natural and living resources, natural hazards, and the environment, visit http://www.usgs.gov or call 1-888-ASK-USGS.For an overview of USGS information products, including maps, imagery, and publications, visit http://www.usgs.gov/pubprodTo order this and other USGS information products, visit http://store.usgs.gov Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.Although this information product, for the most part, is in the public domain, it also may contain copyrighted materials as noted in the text. Permission to reproduce copyrighted items must be secured from the copyright owner.Suggested citation: Granato, G.E., 2014, Hydrologic Drought Decision Support System (HyDroDSS): U.S. Geological Survey Open-File Report 2014-1003. ISSN 2331ISSN -1258 iii AcknowledgmentsThe author thanks Carl Carlson, David Bjerklie, Mary Ashman, and Kevin Breen of the U.S. Geological Survey (USGS) and Kathleen Crawley of the Rhode Island Water Resources Board for providing thoughtful and thorough technical and editorial reviews of this report, the HyDroDSS program, and accompanying digital media. Richard Vogel of Tufts University identified the position analysis approaches developed by Hirsch (1981b) as a potential method for drought-projection analyses and provided information on use of the probability-plot correlation coefficient method for evaluating the distribution of the random numbers generated by the HyDroDSS. Robert Hirsch of the USGS provided information on the application of position analysis, and Gary Tasker of the USGS provided background information on the use of bootstrap methods in the application of position analysis (Tasker and Dunne, 1997). Altitude, as used in this report, refers to distance above the vertical datum.Withdrawal rates from some production wells are reported in million gallons per month (Mgal/mo) and in million gallons per year (Mgal/yr). Hydrologic Drought Decision Support System (HyDroDSS)By Gregory E. Granato AbstractThe hydrologic drought decision support system (HyDroDSS) was developed by the U.S. Geological Survey (USGS) in cooperation with the Rhode Island Water Resources Board (RIWRB) for use in the analysis of hydrologic variables that may indicate the risk for streamflows to be below userdefined flow targets at a designated site of interest, which is defined herein as data-collection site on a stream that may be adversely affected by pumping. Hydrologic drought is defined for this study as a period of lower than normal streamflows caused by precipitation deficits and (or) water withdrawals. The HyDroDSS is designed to provide water managers with risk-based information for balancing water-supply needs and aquatic-habitat protection goals to mitigate potential effects of hydrologic drought.This report describes the theory and methods for retrospective streamflow-depletion analysis, rank correlation analysis, and drough...

Nutrient and metal loads estimated by using discrete, automated, and continuous water-quality monitoring techniques for the Blackstone River at the Massachusetts-Rhode Island State line, water years 2013–14

“…Temperature generally followed seasonal patterns, except during runoff events, and was warmest during summer months and coldest in winter months over the period of record (WYs 2013 and2014). The median water temperature recorded at the Millville station was about 11.5 °C over the period of record.…”

“…Analysis of the correlation coefficients indicates the potential for developing quantitative regression equations between variables or the potential for multicollinearity among predictor variables if multiple linear regression equations are developed (Helsel and Hirsch, 2002). Spearman's rho is a robust estimator of a monotonic relation between two variables that is resistant to outliers; the rho value is not dependent on the linearity of the relation between variables (Haan, 1977;Press and others, 1992;Helsel and Hirsch, 2002;Granato, 2014).…”

“…Correlation coefficients, the associated 95-percent confidence intervals, and statistical-significance probability values for the coefficients were calculated by use of standard methods (Fisher, 1924;Haan, 1977;Press and others, 1992;Caruso and Cliff, 1997;Helsel and Hirsch, 2002;Granato, 2013Granato, , 2014. Paired sample sizes of five or more values were used to estimate correlation coefficients because Abdel-Megeed (1984) determined that at least five data pairs were necessary to begin to quantify the correlation.…”

“…Correlation analysis is a method to quantify the type and strength of relations between two variables (Haan, 1977;Press and others, 1992;Helsel and Hirsch, 2002;Granato, 2013Granato, , 2014. Correlation coefficients were calculated for all of the water-quality variables collected during the monitoring period, as well as for the estimated streamflow and the precipitation variables (precipitation during the sampling event and precipitation recorded during the preceding 24, 48, and 72 hours).…”

SWToolbox: A surface-water tool-box for statistical analysis of streamflow time series

“…(The algorithms are based on methods described by Fisher, 1924;Haan, 1977;Caruso and Cliff, 1997;and Granato, 2014; additional information is available in statistical texts such as Helsel and Hirsch, 2002). In the SWToolbox, the test is used as a second screening test for monotonic trend by testing the correlation between the n-day series and year.…”