John C. Risley
United States Geological Survey
Network
Latest external collaboration on country level. Dive into details by clicking on the dots.
Publication
Featured researches published by John C. Risley.
Scientific Investigations Report | 2008
John C. Risley; Adam J. Stonewall; Tana L. Haluska
Flow statistical datasets, basin-characteristic datasets, and regression equations were developed to provide decision makers with surface-water information needed for activities such as water-quality regulation, water-rights adjudication, biological habitat assessment, infrastructure design, and water-supply planning and management. The flow statistics, which included annual and monthly period of record flow durations (5th, 10th, 25th, 50th, and 95th percent exceedances) and annual and monthly 7-day, 10-year (7Q10) and 7-day, 2-year (7Q2) low flows, were computed at 466 streamflow-gaging stations at sites with unregulated flow conditions throughout Oregon and adjacent areas of neighboring States. Regression equations, created from the flow statistics and basin characteristics of the stations, can be used to estimate flow statistics at ungaged stream sites in Oregon. The study area was divided into 10 regression modeling regions based on ecological, topographic, geologic, hydrologic, and climatic criteria. In total, 910 annual and monthly regression equations were created to predict the 7 flow statistics in the 10 regions. Equations to predict the five flow-duration exceedance percentages and the two low-flow frequency statistics were created with Ordinary Least Squares and Generalized Least Squares regression, respectively. The standard errors of estimate of the equations created to predict the 5th and 95th percent exceedances had medians of 42.4 and 64.4 percent, respectively. The standard errors of prediction of the equations created to predict the 7Q2 and 7Q10 low-flow statistics had medians of 51.7 and 61.2 percent, respectively. Standard errors for regression equations for sites in western Oregon were smaller than those in eastern Oregon partly because of a greater density of available streamflow-gaging stations in western Oregon than eastern Oregon. High-flow regression equations (such as the 5th and 10th percent exceedances) also generally were more accurate than the low-flow regression equations (such as the 95th percent exceedance and 7Q10 low-flow statistic).The regression equations predict unregulated flow conditions in Oregon. Flow estimates need to be adjusted if they are used at ungaged sites that are regulated by reservoirs or affected by water-supply and agricultural withdrawals if actual flow conditions are of interest. The regression equations are installed in the USGS StreamStats Web-based tool (http://water.usgs.gov/osw/streamstats/index.html, accessed July 16, 2008). StreamStats provides users with a set of annual and monthly flow-duration and low-flow frequency estimates for ungaged sites in Oregon in addition to the basin characteristics for the sites. Prediction intervals at the 90-percent confidence level also are automatically computed.
Environmental Research Letters | 2013
Il Won Jung; Heejun Chang; John C. Risley
An understanding of the role of hydro-climatic and geographic regimes on regional actual evapotranspiration (AET) change is essential to improving our knowledge on predicting water availability in a changing climate. This study investigates the relationship between AET change for a 60 year period (1951?2010) and the runoff sensitivity in 255 undisturbed catchments over the US. The runoff sensitivity to climate change is simply defined as the relative magnitude between runoff and precipitation changes with time. Runoff sensitivity can readily explain the conflicting directions of AET changes under similar precipitation change. Under increasing precipitation, AET decreases when runoff is increasing more rapidly than precipitation based on the water balance. Conversely, AET increases when runoff is decreasing more rapidly than precipitation. This result indicates that runoff sensitivity to climate change is a key factor for understanding regional water availability change at the catchment scale. In addition, a stepwise multiple regression analysis and a geographically weighted regression analysis show that the portion of evergreen forest and the mean elevation of a catchment may play a secondary role in the spatial pattern of the AET change, and the relative importance of such explanatory variables may change over space.
Scientific Investigations Report | 2012
Norman L. Buccola; Stewart A. Rounds; Annett B. Sullivan; John C. Risley
A hydrodynamic and water temperature model was developed for Big Cliff Reservoir on the North Santiam River in western Oregon for calendar years 2002 and 2003. This model allows the connection of an existing model of Detroit Lake upstream to an existing model of the North Santiam River downstream. The Big Cliff Reservoir model was able to reproduce the daily as well as hourly fluctuations in water surface elevation well. Initial runs showed that the magnitude and seasonal patterns in modeled water temperature released from Big Cliff Dam matched measured temperature just downstream in the North Santiam River generally well; however, model temperatures were 2 to 3°C too warm in late October to early November. Sensitivity testing and other investigations into this issue led to modifications in the setup of the modeled Detroit Lake model releases, which formed the upstream boundary of the Big Cliff Reservoir model. These changes led to somewhat higher water temperature errors within the Detroit Lake model, but improved the measuredto-modeled fit for the Big Cliff release in late October to early November in both 2002 and 2003.
Earth Interactions | 2011
John C. Risley; Hamid Moradkhani; Lauren E. Hay; Steve Markstrom
Water-Resources Investigations Report | 1997
Antonius Laenen; John C. Risley
Natural Hazards | 2006
John C. Risley; Joseph S. Walder; Roger P. Denlinger
Water-Resources Investigations Report | 2003
John C. Risley; Edwin A. Roehl; Paul A. Conrads
Scientific Investigations Report | 2012
Steven L. Markstrom; Lauren E. Hay; D. Christian Ward-Garrison; John C. Risley; William A. Battaglin; David M. Bjerklie; Katherine J. Chase; Daniel E. Christiansen; Robert W. Dudley; Randall J. Hunt; Kathryn M. Koczot; Mark C. Mastin; R. Steven Regan; Roland J. Viger; Kevin C. Vining; John F. Walker
Water Resources Research | 2010
John C. Risley; Jim Constantz; Hedeff I. Essaid; Stewart A. Rounds
Journal of The American Water Resources Association | 2009
Lauren E. Hay; Gregory J. McCabe; Martyn P. Clark; John C. Risley