Elena Crowley-Ornelas is a research hydrologist with the Lower Mississippi-Gulf Water Science Center in the Nashville office.
Elena joined the USGS as a Student Trainee while completing her undergraduate degree in Geosciences at Texas Tech University.
Education and Certifications
Geosciences at Texas Tech University
M.S. in Geosciences at Texas Tech University
Science and Products
Assessment of hydrologic alteration at 12-digit hydrologic unit code (HUC12) pour points in the southeastern United States, 1950 - 2009
Two methods of calculating hydrologic alteration were applied to modeled daily streamflow data for 9,201 12-digit hydrologic unit code (HUC12) pour points draining to the Gulf of Mexico (Robinson and others, 2020). The first method is a new modified method of calculating ecosurplus and ecodeficit called hydro change. For this project, ecosurplus and ecodeficit have been combined to assess overall
Supporting data and model outputs for hydrologic alteration modeling in the Pearl and Pascagoula river basins
Anthropogenic hydrologic alteration threatens the health of riverine ecosystems. This study assesses hydrologic alteration in the Pearl and Pascagoula river basins using modeled daily streamflow. Machine learning was used to identify locations that have undergone statistically significant streamflow alteration, quantify the volume of the alteration, and predict alteration using cubist models. Stat
Estimated quantiles of decadal flow-duration curves using selected probability distributions fit to no-flow fractions and L-moments predicted for streamgages and for pour points of level-12 hydrologic unit codes in the southeastern United States, 1950-201
Using previously published (Robinson and others, 2019) no-flow fractions and L-moments of nonzero streamflow from decadal streamflow flow-duration analysis (daily mean streamflow), probability distributions were fit to provide 27 estimated quantiles of decadal flow-duration curves, and hence the probability distributions are a form of parametric modeling that ensures monotonicity of the quantiles
Investigating hydrologic alteration in the Pearl and Pascagoula River basins using rule-based model trees
Anthropogenic hydrologic alteration threatens the health of riverine ecosystems. Machine learning algorithms that employ the use of model trees to predict hydrologic alteration are underrepresented in related literature. This study assesses hydrologic alteration in the Pearl and Pascagoula River basins using modeled daily streamflow. Hydrologic alteration was determined by hypothesis testing and t
Authors
Victor L. Roland, Elena Crowley-Ornelas, Kirk D. Rodgers
Generalized additive model estimation of no-flow fractions and L-moments to support flow-duration curve quantile estimation using selected probability distributions for bay and estuary restoration in the Gulf States
Censored and uncensored generalized additive models (GAMs) were developed using streamflow data from 941 U.S. Geological Survey streamflow-gaging stations (streamgages) to predict decadal statistics of daily streamflow for streams draining to the Gulf of Mexico. The modeled decadal statistics comprise no-flow fractions and L-moments of logarithms of nonzero streamflow for six decades (1950–2009).
Authors
Elena Crowley-Ornelas, William H. Asquith, Scott C. Worland
An analysis of streamflow trends in the southern and southeastern US from 1950-2015
In this article, the mean daily streamflow at 139 streamflow-gaging stations (sites) in the southern and southeastern United States are analyzed for spatial and temporal patterns. One hundred and thirty-nine individual time-series of mean daily streamflow were reduced to five aggregated time series of Z scores for clusters of sites with similar temporal variability. These aggregated time-series co
Authors
Kirk D. Rodgers, Victor L. Roland, Anne B. Hoos, Elena Crowley-Ornelas, Rodney Knight
RESTORE/covESTUSAL, Source code for construction of covariates bound to daily salinity and specific conductance data for purposes of statistical modeling in coastal regions of the Gulf of Mexico, United States
The RESTORE/covESTUSAL software repository contains R language source code useful for the construction of input tables of daily salinity and specific conductance (response variables) from multi-agency monitoring stations and potential predictor variables (covariates) intended for reuse in statistical model construction in coastal regions of the Gulf of Mexico, United States. The source code is exp
RESTORE/fdclmrpplo, Source code for estimation of L-moments and percent no-flow conditions for decadal flow-duration curves and estimation at level-12 hydrologic unit codes along with other statistical computations
The RESTORE/fdclmrpplo repository contains R language source code used for estimation of the L-moments and percent no-flow conditions (no-flow fractions) for decadal flow-duration curves and estimation at streamgages and level-12 hydrologic unit codes using generalized additive models and censored generalized additive models. The source code is designed to streamline the workflow for the Gulf Coas
Science and Products
- Data
Assessment of hydrologic alteration at 12-digit hydrologic unit code (HUC12) pour points in the southeastern United States, 1950 - 2009
Two methods of calculating hydrologic alteration were applied to modeled daily streamflow data for 9,201 12-digit hydrologic unit code (HUC12) pour points draining to the Gulf of Mexico (Robinson and others, 2020). The first method is a new modified method of calculating ecosurplus and ecodeficit called hydro change. For this project, ecosurplus and ecodeficit have been combined to assess overallSupporting data and model outputs for hydrologic alteration modeling in the Pearl and Pascagoula river basins
Anthropogenic hydrologic alteration threatens the health of riverine ecosystems. This study assesses hydrologic alteration in the Pearl and Pascagoula river basins using modeled daily streamflow. Machine learning was used to identify locations that have undergone statistically significant streamflow alteration, quantify the volume of the alteration, and predict alteration using cubist models. StatEstimated quantiles of decadal flow-duration curves using selected probability distributions fit to no-flow fractions and L-moments predicted for streamgages and for pour points of level-12 hydrologic unit codes in the southeastern United States, 1950-201
Using previously published (Robinson and others, 2019) no-flow fractions and L-moments of nonzero streamflow from decadal streamflow flow-duration analysis (daily mean streamflow), probability distributions were fit to provide 27 estimated quantiles of decadal flow-duration curves, and hence the probability distributions are a form of parametric modeling that ensures monotonicity of the quantiles - Publications
Investigating hydrologic alteration in the Pearl and Pascagoula River basins using rule-based model trees
Anthropogenic hydrologic alteration threatens the health of riverine ecosystems. Machine learning algorithms that employ the use of model trees to predict hydrologic alteration are underrepresented in related literature. This study assesses hydrologic alteration in the Pearl and Pascagoula River basins using modeled daily streamflow. Hydrologic alteration was determined by hypothesis testing and tAuthorsVictor L. Roland, Elena Crowley-Ornelas, Kirk D. RodgersGeneralized additive model estimation of no-flow fractions and L-moments to support flow-duration curve quantile estimation using selected probability distributions for bay and estuary restoration in the Gulf States
Censored and uncensored generalized additive models (GAMs) were developed using streamflow data from 941 U.S. Geological Survey streamflow-gaging stations (streamgages) to predict decadal statistics of daily streamflow for streams draining to the Gulf of Mexico. The modeled decadal statistics comprise no-flow fractions and L-moments of logarithms of nonzero streamflow for six decades (1950–2009).AuthorsElena Crowley-Ornelas, William H. Asquith, Scott C. WorlandAn analysis of streamflow trends in the southern and southeastern US from 1950-2015
In this article, the mean daily streamflow at 139 streamflow-gaging stations (sites) in the southern and southeastern United States are analyzed for spatial and temporal patterns. One hundred and thirty-nine individual time-series of mean daily streamflow were reduced to five aggregated time series of Z scores for clusters of sites with similar temporal variability. These aggregated time-series coAuthorsKirk D. Rodgers, Victor L. Roland, Anne B. Hoos, Elena Crowley-Ornelas, Rodney Knight - Software
RESTORE/covESTUSAL, Source code for construction of covariates bound to daily salinity and specific conductance data for purposes of statistical modeling in coastal regions of the Gulf of Mexico, United States
The RESTORE/covESTUSAL software repository contains R language source code useful for the construction of input tables of daily salinity and specific conductance (response variables) from multi-agency monitoring stations and potential predictor variables (covariates) intended for reuse in statistical model construction in coastal regions of the Gulf of Mexico, United States. The source code is expRESTORE/fdclmrpplo, Source code for estimation of L-moments and percent no-flow conditions for decadal flow-duration curves and estimation at level-12 hydrologic unit codes along with other statistical computations
The RESTORE/fdclmrpplo repository contains R language source code used for estimation of the L-moments and percent no-flow conditions (no-flow fractions) for decadal flow-duration curves and estimation at streamgages and level-12 hydrologic unit codes using generalized additive models and censored generalized additive models. The source code is designed to streamline the workflow for the Gulf Coas