Kimberly (Kim) A Jones
Kim is a valuable member of the Utah Water Science Center staff. She manages the work of Center GIS Specialists, balancing the needs of the Center and the National Watershed Boundary Dataset (NWBD) workgroup.
Science and Products
Development of a regionally consistent geospatial dataset of agricultural lands in the Upper Colorado River Basin, 2007-10
Irrigation in arid environments can alter the natural rate at which salts are dissolved and transported to streams. Irrigated agricultural lands are the major anthropogenic source of dissolved solids in the Upper Colorado River Basin (UCRB). Understanding the location, spatial distribution, and irrigation status of agricultural lands and the method used to deliver water to agricultural lands are i
Authors
Susan G. Buto, Brittany L. Gold, Kimberly A. Jones
Stream macroinvertebrate response models for bioassessment metrics: addressing the issue of spatial scale
We developed independent predictive disturbance models for a full regional data set and four individual ecoregions (Full Region vs. Individual Ecoregion models) to evaluate effects of spatial scale on the assessment of human landscape modification, on predicted response of stream biota, and the effect of other possible confounding factors, such as watershed size and elevation, on model performance
Authors
Ian R. White, Jonathan Kennen, Jason T. May, Larry R. Brown, Thomas F. Cuffney, Kimberly A. Jones, James L. Orlando
Comparison of stream invertebrate response models for bioassessment metric
We aggregated invertebrate data from various sources to assemble data for modeling in two ecoregions in Oregon and one in California. Our goal was to compare the performance of models developed using multiple linear regression (MLR) techniques with models developed using three relatively new techniques: classification and regression trees (CART), random forest (RF), and boosted regression trees (B
Authors
Ian R. Waite, Jonathan Kennen, Jason T. May, Larry R. Brown, Thomas F. Cuffney, Kimberly A. Jones, James L. Orlando
Comparison of watershed disturbance predictive models for stream benthic macroinvertebrates for three distinct ecoregions in western US
The successful use of macroinvertebrates as indicators of stream condition in bioassessments has led to heightened interest throughout the scientific community in the prediction of stream condition. For example, predictive models are increasingly being developed that use measures of watershed disturbance, including urban and agricultural land-use, as explanatory variables to predict various metric
Authors
Ian R. Waite, Larry R. Brown, Jonathan Kennen, Jason T. May, Thomas F. Cuffney, James L. Orlando, Kimberly A. Jones
Science and Products
- Publications
Development of a regionally consistent geospatial dataset of agricultural lands in the Upper Colorado River Basin, 2007-10
Irrigation in arid environments can alter the natural rate at which salts are dissolved and transported to streams. Irrigated agricultural lands are the major anthropogenic source of dissolved solids in the Upper Colorado River Basin (UCRB). Understanding the location, spatial distribution, and irrigation status of agricultural lands and the method used to deliver water to agricultural lands are iAuthorsSusan G. Buto, Brittany L. Gold, Kimberly A. JonesStream macroinvertebrate response models for bioassessment metrics: addressing the issue of spatial scale
We developed independent predictive disturbance models for a full regional data set and four individual ecoregions (Full Region vs. Individual Ecoregion models) to evaluate effects of spatial scale on the assessment of human landscape modification, on predicted response of stream biota, and the effect of other possible confounding factors, such as watershed size and elevation, on model performanceAuthorsIan R. White, Jonathan Kennen, Jason T. May, Larry R. Brown, Thomas F. Cuffney, Kimberly A. Jones, James L. OrlandoComparison of stream invertebrate response models for bioassessment metric
We aggregated invertebrate data from various sources to assemble data for modeling in two ecoregions in Oregon and one in California. Our goal was to compare the performance of models developed using multiple linear regression (MLR) techniques with models developed using three relatively new techniques: classification and regression trees (CART), random forest (RF), and boosted regression trees (BAuthorsIan R. Waite, Jonathan Kennen, Jason T. May, Larry R. Brown, Thomas F. Cuffney, Kimberly A. Jones, James L. OrlandoComparison of watershed disturbance predictive models for stream benthic macroinvertebrates for three distinct ecoregions in western US
The successful use of macroinvertebrates as indicators of stream condition in bioassessments has led to heightened interest throughout the scientific community in the prediction of stream condition. For example, predictive models are increasingly being developed that use measures of watershed disturbance, including urban and agricultural land-use, as explanatory variables to predict various metricAuthorsIan R. Waite, Larry R. Brown, Jonathan Kennen, Jason T. May, Thomas F. Cuffney, James L. Orlando, Kimberly A. Jones - News