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Ayman H Alzraiee, PhD

Ayman H. Alzraiee - Research Hydrologist - California Water Science Center

Professional Experience

  • 2016 to present - Research Hydrologist - US Geological Survey California Water Science Center: Sacramento, CA

     

  • 2015 to 2016 - Senior member of technical staff - Sandia National Laboratories: Albuquerque, NM

Education and Certifications

  • 2011 - PhD - (Civil and Environmental Engineering) - Colorado State University: Fort Collins, CO

  • 2005 -  MSc (Civil & Environmental Engineering) - Colorado State University: Fort Collins, CO

Science and Products

link
location map of the Yucaipa area in Southern California. Faults in the area are also displayed.

Yucaipa Subbasin Integrated Hydrologic Model

The USGS is developing a hydrologic model of the Yucaipa Subbasin to aid in evaluating and managing the groundwater resources in the area. The study results will provide a greater understanding of the geohydrology of the subbasin, and aid in the development of a groundwater-monitoring plan, as well as in the evaluation of potential hydrologic effects of future groundwater development and...
By
California Water Science Center
link

Yucaipa Subbasin Integrated Hydrologic Model

The USGS is developing a hydrologic model of the Yucaipa Subbasin to aid in evaluating and managing the groundwater resources in the area. The study results will provide a greater understanding of the geohydrology of the subbasin, and aid in the development of a groundwater-monitoring plan, as well as in the evaluation of potential hydrologic effects of future groundwater development and...
Learn More
link
Photo #9 of well site YVDA being drilled

Yucaipa Valley Hydrogeology

This study assesses the quality of water in the Yucaipa area, primarily in the Yucaipa plain. This hydrogeology study will aid local water purveyors in understanding and evaluating local resources and using those resources effectively in combination with water imported from northern California and from the adjacent San Bernardino area.
By
California Water Science Center
link

Yucaipa Valley Hydrogeology

This study assesses the quality of water in the Yucaipa area, primarily in the Yucaipa plain. This hydrogeology study will aid local water purveyors in understanding and evaluating local resources and using those resources effectively in combination with water imported from northern California and from the adjacent San Bernardino area.
Learn More

Russian River Integrated Hydrologic Model (RRIHM): Groundwater & Streamflow Observations

The Russian River Watershed (RRW) covers about 1300 square miles (without Santa Rosa Plain) of urban, agricultural, and forested lands in northern Sonoma County and southern Mendocino County, California. Communities in the RRW depend on a combination of Russian River water and groundwater to meet their water-supply demands. Water is used primarily for agricultural irrigation, municipal and private
By
California Water Science Center

Next generation public supply water withdrawal estimation for the conterminous United States using machine learning and operational frameworks

Estimation of human water withdrawals is more important now than ever due to uncertain water supplies, population growth, and climate change. Fourteen percent of the total water withdrawal in the United States is used for public supply, typically including deliveries to domestic, commercial, and occasionally including industrial, irrigation, and thermoelectric water withdrawal. Stewards of water r
Authors
Ayman H. Alzraiee, Richard G. Niswonger, Carol L. Luukkonen, Joshua Larsen, Donald Martin, Deidre Mary Herbert, Cheryl A. Buchwald, Cheryl A. Dieter, Lisa D. Miller, Jana Stewart, Natalie Houston, Scott R. Paulinski, Kristen Valseth
By
Water Resources Mission Area, California Water Science Center, Colorado Water Science Center, Upper Midwest Water Science Center, Oklahoma-Texas Water Science Center

A probabilistic approach to training machine learning models using noisy data

Machine learning (ML) models are increasingly popular in environmental and hydrologic modeling, but they typically contain uncertainties resulting from noisy data (erroneous or outlier data). This paper presents a novel probabilistic approach that combines ML and Markov Chain Monte Carlo simulation to (1) detect and underweight likely noisy data, (2) develop an approach capable of detecting noisy
Authors
Ayman H. Alzraiee, Richard G. Niswonger
By
Water Resources Mission Area, California Water Science Center

Integrated hydrologic model development and postprocessing for GSFLOW using pyGSFLOW

pyGSFLOW is a python package designed to create new GSFLOW integrated hydrologic models, read existing models, edit model input data, run GSFLOW models, process output, and visualize model data.
Authors
Joshua Larsen, Ayman H. Alzraiee, Richard G. Niswonger
By
Water Resources Mission Area, California Water Science Center

Yucaipa valley integrated hydrological model

IntroductionThe hydrologic system in the Yucaipa Valley watershed (YVW) was simulated using the coupled Groundwater and Surface-water FLOW model (GSFLOW; Markstrom and others, 2008). This study uses version 2.0 of GSFLOW, which is a combination of the Precipitation-Runoff Modeling System (PRMS; Markstrom and others, 2015), and the Newton-Raphson formulation of the Modular Groundwater-Flow Model (M
Authors
Ayman H. Alzraiee, John A. Engott, Geoffrey Cromwell, Linda R. Woolfenden
By
Water Resources Mission Area, California Water Science Center

Hydrogeologic characterization of the Yucaipa groundwater subbasin

IntroductionWater management in the Santa Ana River watershed in San Bernardino and Riverside Counties in southern California (fig. A1) is complex with various water purveyors navigating geographic, geologic, hydrologic, and political challenges to provide a reliable water supply to stakeholders. As the population has increased throughout southern California, so has the demand for water. The Yucai
Authors
Geoffrey Cromwell, John A. Engott, Ayman H. Alzraiee, Christina Stamos-Pfeiffer, Gregory Mendez, Meghan C. Dick, Sandra Bond
By
Water Resources Mission Area, California Water Science Center

Hydrology of the Yucaipa groundwater subbasin: Characterization and integrated numerical model, San Bernardino and Riverside Counties, California

Executive SummaryWater management in the Santa Ana River watershed in San Bernardino and Riverside Counties in southern California is a complex task with various water purveyors navigating geographic, geologic, hydrologic, and political challenges to provide a reliable water supply to stakeholders. As the population has increased throughout southern California, so has the demand for water. The Yuc
By
Water Resources Mission Area, California Water Science Center

A scalable model-independent iterative data assimilation tool for sequential and batch estimation of high dimensional model parameters and states

Ensemble-based data assimilation (DA) methods have displayed strong potential to improve model state and parameter estimation across several disciplines due to their computational efficiency, scalability, and ability to estimate uncertainty in the dynamic states and the parameters. However, a barrier to adoption of ensemble DA methods remains. Namely, there is currently a lack of available tools t
Authors
Ayman H. Alzraiee, Jeremy T. White, Matthew Knowling, Randall J. Hunt, Michael N. Fienen
By
Water Resources Mission Area, California Water Science Center

Non-USGS Publications**

**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.

Science and Products

link
location map of the Yucaipa area in Southern California. Faults in the area are also displayed.

Yucaipa Subbasin Integrated Hydrologic Model

The USGS is developing a hydrologic model of the Yucaipa Subbasin to aid in evaluating and managing the groundwater resources in the area. The study results will provide a greater understanding of the geohydrology of the subbasin, and aid in the development of a groundwater-monitoring plan, as well as in the evaluation of potential hydrologic effects of future groundwater development and...
By
California Water Science Center
link

Yucaipa Subbasin Integrated Hydrologic Model

The USGS is developing a hydrologic model of the Yucaipa Subbasin to aid in evaluating and managing the groundwater resources in the area. The study results will provide a greater understanding of the geohydrology of the subbasin, and aid in the development of a groundwater-monitoring plan, as well as in the evaluation of potential hydrologic effects of future groundwater development and...
Learn More
link
Photo #9 of well site YVDA being drilled

Yucaipa Valley Hydrogeology

This study assesses the quality of water in the Yucaipa area, primarily in the Yucaipa plain. This hydrogeology study will aid local water purveyors in understanding and evaluating local resources and using those resources effectively in combination with water imported from northern California and from the adjacent San Bernardino area.
By
California Water Science Center
link

Yucaipa Valley Hydrogeology

This study assesses the quality of water in the Yucaipa area, primarily in the Yucaipa plain. This hydrogeology study will aid local water purveyors in understanding and evaluating local resources and using those resources effectively in combination with water imported from northern California and from the adjacent San Bernardino area.
Learn More

Russian River Integrated Hydrologic Model (RRIHM): Groundwater & Streamflow Observations

The Russian River Watershed (RRW) covers about 1300 square miles (without Santa Rosa Plain) of urban, agricultural, and forested lands in northern Sonoma County and southern Mendocino County, California. Communities in the RRW depend on a combination of Russian River water and groundwater to meet their water-supply demands. Water is used primarily for agricultural irrigation, municipal and private
By
California Water Science Center

Next generation public supply water withdrawal estimation for the conterminous United States using machine learning and operational frameworks

Estimation of human water withdrawals is more important now than ever due to uncertain water supplies, population growth, and climate change. Fourteen percent of the total water withdrawal in the United States is used for public supply, typically including deliveries to domestic, commercial, and occasionally including industrial, irrigation, and thermoelectric water withdrawal. Stewards of water r
Authors
Ayman H. Alzraiee, Richard G. Niswonger, Carol L. Luukkonen, Joshua Larsen, Donald Martin, Deidre Mary Herbert, Cheryl A. Buchwald, Cheryl A. Dieter, Lisa D. Miller, Jana Stewart, Natalie Houston, Scott R. Paulinski, Kristen Valseth
By
Water Resources Mission Area, California Water Science Center, Colorado Water Science Center, Upper Midwest Water Science Center, Oklahoma-Texas Water Science Center

A probabilistic approach to training machine learning models using noisy data

Machine learning (ML) models are increasingly popular in environmental and hydrologic modeling, but they typically contain uncertainties resulting from noisy data (erroneous or outlier data). This paper presents a novel probabilistic approach that combines ML and Markov Chain Monte Carlo simulation to (1) detect and underweight likely noisy data, (2) develop an approach capable of detecting noisy
Authors
Ayman H. Alzraiee, Richard G. Niswonger
By
Water Resources Mission Area, California Water Science Center

Integrated hydrologic model development and postprocessing for GSFLOW using pyGSFLOW

pyGSFLOW is a python package designed to create new GSFLOW integrated hydrologic models, read existing models, edit model input data, run GSFLOW models, process output, and visualize model data.
Authors
Joshua Larsen, Ayman H. Alzraiee, Richard G. Niswonger
By
Water Resources Mission Area, California Water Science Center

Yucaipa valley integrated hydrological model

IntroductionThe hydrologic system in the Yucaipa Valley watershed (YVW) was simulated using the coupled Groundwater and Surface-water FLOW model (GSFLOW; Markstrom and others, 2008). This study uses version 2.0 of GSFLOW, which is a combination of the Precipitation-Runoff Modeling System (PRMS; Markstrom and others, 2015), and the Newton-Raphson formulation of the Modular Groundwater-Flow Model (M
Authors
Ayman H. Alzraiee, John A. Engott, Geoffrey Cromwell, Linda R. Woolfenden
By
Water Resources Mission Area, California Water Science Center

Hydrogeologic characterization of the Yucaipa groundwater subbasin

IntroductionWater management in the Santa Ana River watershed in San Bernardino and Riverside Counties in southern California (fig. A1) is complex with various water purveyors navigating geographic, geologic, hydrologic, and political challenges to provide a reliable water supply to stakeholders. As the population has increased throughout southern California, so has the demand for water. The Yucai
Authors
Geoffrey Cromwell, John A. Engott, Ayman H. Alzraiee, Christina Stamos-Pfeiffer, Gregory Mendez, Meghan C. Dick, Sandra Bond
By
Water Resources Mission Area, California Water Science Center

Hydrology of the Yucaipa groundwater subbasin: Characterization and integrated numerical model, San Bernardino and Riverside Counties, California

Executive SummaryWater management in the Santa Ana River watershed in San Bernardino and Riverside Counties in southern California is a complex task with various water purveyors navigating geographic, geologic, hydrologic, and political challenges to provide a reliable water supply to stakeholders. As the population has increased throughout southern California, so has the demand for water. The Yuc
By
Water Resources Mission Area, California Water Science Center

A scalable model-independent iterative data assimilation tool for sequential and batch estimation of high dimensional model parameters and states

Ensemble-based data assimilation (DA) methods have displayed strong potential to improve model state and parameter estimation across several disciplines due to their computational efficiency, scalability, and ability to estimate uncertainty in the dynamic states and the parameters. However, a barrier to adoption of ensemble DA methods remains. Namely, there is currently a lack of available tools t
Authors
Ayman H. Alzraiee, Jeremy T. White, Matthew Knowling, Randall J. Hunt, Michael N. Fienen
By
Water Resources Mission Area, California Water Science Center

Non-USGS Publications**

**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.

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