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Title: Conjunctive management of surface and groundwater resources under projected future climate change scenarios

Abstract

Our study introduces a mixed integer linear fractional programming (MILFP) method to optimize conjunctive use of future surface water and groundwater resources under projected climate change scenarios. The conjunctive management model maximizes the ratio of groundwater usage to reservoir water usage. Future inflows to the reservoirs were estimated from the future runoffs projected through hydroclimate modeling considering the Variable Infiltration Capacity model, and 11 sets of downscaled Coupled Model Intercomparison Project phase 5 global climate model projections. Bayesian model averaging was adopted to quantify uncertainty in future runoff projections and reservoir inflow projections due to uncertain future climate projections. Optimized conjunctive management solutions were investigated for a water supply network in northern Louisiana which includes the Sparta aquifer. Runoff projections under climate change scenarios indicate that runoff will likely decrease in winter and increase in other seasons. Ultimately, results from the developed conjunctive management model with MILFP indicate that the future reservoir water, even at 2.5% low inflow cumulative probability level, could counterbalance groundwater pumping reduction to satisfy demands while improving the Sparta aquifer through conditional groundwater head constraint.

Authors:
 [1];  [1];  [2];  [2];  [2];  [2]
  1. Louisiana State Univ., Baton Rouge, LA (United States)
  2. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1260085
Alternate Identifier(s):
OSTI ID: 1436368
Grant/Contract Number:  
AC05-00OR22725; G11AP20082; LEQSF(2012‐15)‐RD‐A‐03
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Hydrology
Additional Journal Information:
Journal Volume: 540; Journal Issue: C; Journal ID: ISSN 0022-1694
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; Conjunctive use; Multi-reservoir system; Groundwater; Climate Change; Uncertainty; Fractional programming

Citation Formats

Mani, Amir, Tsai, Frank T. -C., Kao, Shih-Chieh, Naz, Bibi S., Ashfaq, Moetasim, and Rastogi, Deeksha. Conjunctive management of surface and groundwater resources under projected future climate change scenarios. United States: N. p., 2016. Web. https://doi.org/10.1016/j.jhydrol.2016.06.021.
Mani, Amir, Tsai, Frank T. -C., Kao, Shih-Chieh, Naz, Bibi S., Ashfaq, Moetasim, & Rastogi, Deeksha. Conjunctive management of surface and groundwater resources under projected future climate change scenarios. United States. https://doi.org/10.1016/j.jhydrol.2016.06.021
Mani, Amir, Tsai, Frank T. -C., Kao, Shih-Chieh, Naz, Bibi S., Ashfaq, Moetasim, and Rastogi, Deeksha. Thu . "Conjunctive management of surface and groundwater resources under projected future climate change scenarios". United States. https://doi.org/10.1016/j.jhydrol.2016.06.021. https://www.osti.gov/servlets/purl/1260085.
@article{osti_1260085,
title = {Conjunctive management of surface and groundwater resources under projected future climate change scenarios},
author = {Mani, Amir and Tsai, Frank T. -C. and Kao, Shih-Chieh and Naz, Bibi S. and Ashfaq, Moetasim and Rastogi, Deeksha},
abstractNote = {Our study introduces a mixed integer linear fractional programming (MILFP) method to optimize conjunctive use of future surface water and groundwater resources under projected climate change scenarios. The conjunctive management model maximizes the ratio of groundwater usage to reservoir water usage. Future inflows to the reservoirs were estimated from the future runoffs projected through hydroclimate modeling considering the Variable Infiltration Capacity model, and 11 sets of downscaled Coupled Model Intercomparison Project phase 5 global climate model projections. Bayesian model averaging was adopted to quantify uncertainty in future runoff projections and reservoir inflow projections due to uncertain future climate projections. Optimized conjunctive management solutions were investigated for a water supply network in northern Louisiana which includes the Sparta aquifer. Runoff projections under climate change scenarios indicate that runoff will likely decrease in winter and increase in other seasons. Ultimately, results from the developed conjunctive management model with MILFP indicate that the future reservoir water, even at 2.5% low inflow cumulative probability level, could counterbalance groundwater pumping reduction to satisfy demands while improving the Sparta aquifer through conditional groundwater head constraint.},
doi = {10.1016/j.jhydrol.2016.06.021},
journal = {Journal of Hydrology},
number = C,
volume = 540,
place = {United States},
year = {2016},
month = {6}
}

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Cited by: 3 works
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    Works referencing / citing this record:

    Multivariate Investigation of Heavy Metals in the Groundwater for Irrigation and Drinking in Garautha Tehsil, Jhansi District, India
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