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Title: Estimating groundwater dynamics at a Colorado River floodplain site using historical hydrological data and climate information

Long-term prediction of groundwater dynamics is important for assessing water resources and their impacts on biogeochemical cycling. However, estimating future groundwater dynamics is challenging due to the wide range of spatiotemporal scales in hydrological processes and uncertainty in future climate conditions. In this study, we develop a Bayesian model to combine small-scale historical hydrological data with large-scale climate information to estimate groundwater dynamics at a floodplain site in Rifle, Colorado. Although we have only a few years of groundwater elevation measurements, we have 47 years of streamflow data from a gaging station approximately 43 km upstream and long-term climate prediction on the Upper Colorado River Basin. To estimate future daily groundwater dynamics, we first develop a time series model to downscale the monthly streamflow derived from climate information to daily streamflow, and then transform the daily streamflow to groundwater dynamics at the downstream floodplain site. We use Monte Carlo methods to estimate future groundwater dynamics at the site through sampling from the joint posterior probability distribution. The results suggest that although future groundwater levels are expected to be similar to the current levels, the timing of the high groundwater levels is predicted to occur about 1 month earlier. The developedmore » framework is extendable to other sites to estimate future groundwater dynamics given disparate data sets and climate projections. Additionally, the obtained estimates are being used as input to a site-specific watershed reactive transport models to predict how climate-induced changes will influence future biogeochemical cycling relevant to a variety of ecosystem services.« less
Authors:
 [1] ;  [1] ;  [1] ;  [2]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Earth and Environmental Sciences Area
  2. Indiana Univ., Bloomington, IN (United States). Dept. of Geography
Publication Date:
Grant/Contract Number:
AC02-05CH11231
Type:
Accepted Manuscript
Journal Name:
Water Resources Research
Additional Journal Information:
Journal Volume: 52; Journal Issue: 3; Journal ID: ISSN 0043-1397
Publisher:
American Geophysical Union (AGU)
Research Org:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
Country of Publication:
United States
Language:
English
Subject:
58 GEOSCIENCES
OSTI Identifier:
1474925

Chen, Jinsong, Hubbard, Susan S., Williams, Kenneth H., and Ficklin, Darren L.. Estimating groundwater dynamics at a Colorado River floodplain site using historical hydrological data and climate information. United States: N. p., Web. doi:10.1002/2015WR017777.
Chen, Jinsong, Hubbard, Susan S., Williams, Kenneth H., & Ficklin, Darren L.. Estimating groundwater dynamics at a Colorado River floodplain site using historical hydrological data and climate information. United States. doi:10.1002/2015WR017777.
Chen, Jinsong, Hubbard, Susan S., Williams, Kenneth H., and Ficklin, Darren L.. 2016. "Estimating groundwater dynamics at a Colorado River floodplain site using historical hydrological data and climate information". United States. doi:10.1002/2015WR017777. https://www.osti.gov/servlets/purl/1474925.
@article{osti_1474925,
title = {Estimating groundwater dynamics at a Colorado River floodplain site using historical hydrological data and climate information},
author = {Chen, Jinsong and Hubbard, Susan S. and Williams, Kenneth H. and Ficklin, Darren L.},
abstractNote = {Long-term prediction of groundwater dynamics is important for assessing water resources and their impacts on biogeochemical cycling. However, estimating future groundwater dynamics is challenging due to the wide range of spatiotemporal scales in hydrological processes and uncertainty in future climate conditions. In this study, we develop a Bayesian model to combine small-scale historical hydrological data with large-scale climate information to estimate groundwater dynamics at a floodplain site in Rifle, Colorado. Although we have only a few years of groundwater elevation measurements, we have 47 years of streamflow data from a gaging station approximately 43 km upstream and long-term climate prediction on the Upper Colorado River Basin. To estimate future daily groundwater dynamics, we first develop a time series model to downscale the monthly streamflow derived from climate information to daily streamflow, and then transform the daily streamflow to groundwater dynamics at the downstream floodplain site. We use Monte Carlo methods to estimate future groundwater dynamics at the site through sampling from the joint posterior probability distribution. The results suggest that although future groundwater levels are expected to be similar to the current levels, the timing of the high groundwater levels is predicted to occur about 1 month earlier. The developed framework is extendable to other sites to estimate future groundwater dynamics given disparate data sets and climate projections. Additionally, the obtained estimates are being used as input to a site-specific watershed reactive transport models to predict how climate-induced changes will influence future biogeochemical cycling relevant to a variety of ecosystem services.},
doi = {10.1002/2015WR017777},
journal = {Water Resources Research},
number = 3,
volume = 52,
place = {United States},
year = {2016},
month = {3}
}