TY - JOUR
T1 - Multi-constrained catchment scale optimization of groundwater abstraction using linear programming
AU - Danapour, Mehrdis
AU - Fienen, Michael N.
AU - Højberg, Anker Lajer
AU - Jensen, Karsten Høgh
AU - Stisen, Simon
N1 - Funding Information:
The authors acknowledge the financial support for the SPACE project by the Villum Foundation (http://villumfonden.dk/) through their Young Investigator Program (grant VKR023443). The authors would also like to thank Paul M. Barlow, Joe Donovan, Peter Andersen, and the anonymous reviewer for their comments, insightful suggestions, and careful reading of the manuscript. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
Funding Information:
The authors acknowledge the financial support for the SPACE project by the Villum Foundation ( http://villumfonden.dk/ ) through their Young Investigator Program (grant VKR023443). The authors would also like to thank Paul M. Barlow, Joe Donovan, Peter Andersen, and the anonymous reviewer for their comments, insightful suggestions, and careful reading of the manuscript. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
Publisher Copyright:
© 2021, National Ground Water Association.
PY - 2021/7/1
Y1 - 2021/7/1
N2 - Due to increasing water demands globally, freshwater ecosystems are under constant pressure. Groundwater resources, as the main source of accessible freshwater, are crucially important for irrigation worldwide. Over-abstraction of groundwater leads to declines in groundwater levels; consequently, the groundwater inflow to streams decreases. The reduction in baseflow and alteration of the streamflow regime can potentially have an adverse effect on groundwater-dependent ecosystems. A spatially distributed, coupled groundwater–surface water model can simulate the impacts of groundwater abstraction on aquatic ecosystems. A constrained optimization algorithm and a simulation model in combination can provide an objective tool for the water practitioner to evaluate the interplay between economic benefits of groundwater abstractions and requirements to environmental flow. In this study, a holistic catchment-scale groundwater abstraction optimization framework has been developed that allows for a spatially explicit optimization of groundwater abstraction, while fulfilling a predefined maximum allowed reduction of streamflow (baseflow [Q95] or median flow [Q50]) as constraint criteria for 1484 stream locations across the catchment. A balanced K-Means clustering method was implemented to reduce the computational burden of the optimization. The model parameters and observation uncertainties calculated based on Bayesian linear theory allow for a risk assessment on the optimized groundwater abstraction values. The results from different optimization scenarios indicated that using the linear programming optimization algorithm in conjunction with integrated models provides valuable information for guiding the water practitioners in designing an effective groundwater abstraction plan with the consideration of environmental flow criteria important for the ecological status of the entire system.
AB - Due to increasing water demands globally, freshwater ecosystems are under constant pressure. Groundwater resources, as the main source of accessible freshwater, are crucially important for irrigation worldwide. Over-abstraction of groundwater leads to declines in groundwater levels; consequently, the groundwater inflow to streams decreases. The reduction in baseflow and alteration of the streamflow regime can potentially have an adverse effect on groundwater-dependent ecosystems. A spatially distributed, coupled groundwater–surface water model can simulate the impacts of groundwater abstraction on aquatic ecosystems. A constrained optimization algorithm and a simulation model in combination can provide an objective tool for the water practitioner to evaluate the interplay between economic benefits of groundwater abstractions and requirements to environmental flow. In this study, a holistic catchment-scale groundwater abstraction optimization framework has been developed that allows for a spatially explicit optimization of groundwater abstraction, while fulfilling a predefined maximum allowed reduction of streamflow (baseflow [Q95] or median flow [Q50]) as constraint criteria for 1484 stream locations across the catchment. A balanced K-Means clustering method was implemented to reduce the computational burden of the optimization. The model parameters and observation uncertainties calculated based on Bayesian linear theory allow for a risk assessment on the optimized groundwater abstraction values. The results from different optimization scenarios indicated that using the linear programming optimization algorithm in conjunction with integrated models provides valuable information for guiding the water practitioners in designing an effective groundwater abstraction plan with the consideration of environmental flow criteria important for the ecological status of the entire system.
UR - http://www.scopus.com/inward/record.url?scp=85101628537&partnerID=8YFLogxK
U2 - 10.1111/gwat.13083
DO - 10.1111/gwat.13083
M3 - Article
C2 - 33533499
AN - SCOPUS:85101628537
VL - 59
SP - 503
EP - 516
JO - Groundwater
JF - Groundwater
SN - 0017-467X
IS - 4
ER -