Optimizing Water Supply through Reservoir Conversion and Storage of Return Flow- A Case Study at Joe Pool Lake
Cover photo: A view of the Milky Way over Phoinix Ranch in Jim Wells and Live Oak counties.  ©2022 Rey Garza and Jim Quisenberry


Trinity River Basin
Joe Pool Lake
Mixed integer linear Programming
Cost Efficiency

How to Cite

Sekar, S., Daghighi, A. ., Chen, V., Clingenpeel, G., Zhang, Y. ., Rosenberger, J. M. ., & Boskabadi, A. . (2022). Optimizing Water Supply through Reservoir Conversion and Storage of Return Flow- A Case Study at Joe Pool Lake. Texas Water Journal, 13(1), 1–12. https://doi.org/10.21423/twj.v13i1.7124


Maintaining an adequate water supply is one of the key challenges faced by the Dallas-Fort Worth Metroplex, where increasing population and rising water demand have elevated the vulnerability of the communities to water shortages. In this paper, we conducted a preliminary study exploring the possibility of converting flood storage in the Joe Pool Lake (JPL) as a means to improve water supply reliability and achieve better cost efficiency. This study employs a mixed integer linear programming (MILP) approach that considers the costs of meeting conversion demand and supply requirements over the northern portion of the Trinity River Basin. It includes trade-offs between capturing and storing natural flow versus return flow from the treatment facilities of the Trinity River Authority (TRA). A set of hypothetical prices and demand figures with the record drought of 1940-1996 considered to test the LP model. The optimal strategy yields expansion of JPL and associated storage-diversion on an annual basis. Also, the outcomes of the analyses suggest that, while the conversion would have a positive impact on water availability, storing the return flow might not produce sufficient cost savings; unless higher prices were imposed on the stored-return flow.



Asgari-Motlagh X, Ketabchy M, Daghighi A. 2019. Probabilistic quantitative precipitation forecasting using machine learning methods and probable maximum precipitation. International Journal of Engineering Science. 6(1):1-14. Available from: https://doi.org/10.9756/IAJSE/V6I1/1910001.

Cervellera C, Chen VCP, Wen A. 2006. Optimization of a large-scale water reservoir network by stochastic dynamic programming with efficient state space discretization. European Journal of Operational Research. 171(3):1139-1151. Available from: https://doi.org/10.1016/j.ejor.2005.01.022.

Cromarty AS, Ellis RH, Roberts EH. 1982. The design of seed storage facilities for genetic conservation. Rome (Italy): Bioversity International. Available from: https://hdl.handle.net/10568/104304.

Daghighi A, Nahvi A, Kim U. 2017. Optimal cultivation pattern to increase revenue and reduce water use: Application of linear programming to Arjan plain in Fars province. Agriculture. 07(09):73. Available from: https://doi.org/10.3390/agriculture7090073.

Daghighi A, Nahvi A, Nazif S, Kim U. 2020. Seeking substantiality: evaluation of public attitudes toward resilient wastewater reuse management. Journal of Water Management Modeling. 28: C470. Available from: https://doi.org/10.14796/JWMM.C470.

Demirel M, Wurbs RA. 2015. Assessment of flood control capabilities for alternative reservoir storage allocations. Turkish Journal of Water Sciences and Management. 1(1):108-137. Available from: https://doi.org/10.31807/tjwsm.297150.

Eusuff MM, Lansey KE. 2003. Optimization of water distribution network design using the shuffled frog leaping algorithm. Journal of Water Resources Planning and Management. 129(3):210-225. Available from: https://doi.org/10.1061/(ASCE)0733-9496(2003)129:3(210).

Ghahraman B, Sepaskhah AR. 2004. Linear and non‐linear optimization models for allocation of a limited water supply. Irrigation and Drainage. 53(1):39-54. Available from: https://doi.org/10.1002/ird.108.

Gheytaspour M, Habibzadeh Bigdarvish O. 2018. Forecasting oxygen demand in treatment plant using artificial neural networks. International Journal of Advanced Engineering Research and Science. 5(3):50-57. Available from: https://doi.org/10.22161/ijaers.5.3.8.

Ghimire MK. 2014. The impact of impoundment and urbanization on shallow groundwater conditions in the Joe Pool Lake catchment, Texas [dissertation]. [Arlington (Texas)]: University of Texas at Arlington. Available from: http://hdl.handle.net/10106/24927.

Haghiri S, Daghighi A, Moharramzadeh S. 2018. Optimum coagulant forecasting by modeling jar test experiments using ANNs. Drinking Water Engineering & Science. 11(1):1-8. Available from: https://doi.org/10.5194/dwes-11-1-2018.

LeComte D. 2020. U.S. weather highlights 2019: the second-wettest year on record. Weatherwise. 73(3):14-23. Available from: https://doi.org/10.1080/00431672.2020.1736464.

Naden R, Platt R. n.d. The Association of La Niña on Midland, Texas Precipitation. National Weather Service. [accessed 2021 May 21]. Available from: https://www.weather.gov/maf/research_lanina.

Nielsen-Gammon JW. 2012. The 2011 Texas drought. Texas Water Journal. 3(1):59-95. Available from: https://doi.org/10.21423/twj.v3i1.6463.

National Centers for Environmental Information. 2022. Climate at a Glance. Asheville (North Carolina): National Centers for Environmental Information. [accessed 2022 Jan 28]. Available from: https://www.ncdc.noaa.gov/cag/.

Pu B, Fu R, Dickinson RE, Fernando DN. 2016. Why do summer droughts in the Southern Great Plains occur in some La Niña years but not others? Journal of Geophysical Research: Atmospheres. 121(3)1120-1137. Available from: https://doi.org/10.1002/2015JD023508.

Reynolds RL, Rosenbaum JG, van Metre P, Tuttle M, Callender E, Goldin A. 1999. Greigite (Fe3S4) as an indicator of drought – The 1912–1994 sediment magnetic record from White Rock Lake, Dallas, Texas, USA. Journal of Paleolimnology. 21:193-206. Available from: https://doi.org/10.1023/A:1008027815203.

Samani HMV, Mottaghi A. 2006. Optimization of water distribution networks using integer linear programming. Journal of Hydraulic Engineering. 132(5):501-509. Available from: https://doi.org/10.1061/(ASCE)0733-9429(2006)132:5(501).

Slade RM. 2020. Runoff inflow volumes to the Highland Lakes in Central Texas: temporal trends in volumes, and relations between volumes and selected climatic indices. Texas Water Journal. 11(1):32-60. Available from https://doi.org/10.21423/twj.v11i1.7025.

[TWDB] Texas Water Development Board. 2017. Water for Texas 2017 state water plan. Austin (Texas): Texas Water Development Board. 150 p. Available from: https://www.twdb.texas.gov/waterplanning/swp/2017/index.asp.

[TWDB] Texas Water Development Board. 2019. State flood assessment: report to the 86th Texas Legislature. Austin (Texas): Texas Water Development Board. 58 p. Available from: http://www.texasfloodassessment.com/.

[TWDB] Texas Water Development Board. 2012. Water for Texas 2012 state water plan. Austin (Texas): Texas Water Development Board. 314 p. Available from: https://www.twdb.texas.gov/waterplanning/swp/2012/index.asp.

[USACE] U.S. Army Corps of Engineers. n.d. Fort Worth District – Joe Pool Lake. Fort Worth (Texas): U.S. Army Corps of Engineers Fort Worth District. [accessed 2022 Jan 27]. Available from: https://www.swf-wc.usace.army.mil/joepool/.

Wurbs RA. 2001. Assessing water availability under a water rights priority system. Journal of Water Resources Planning and Management. 127(4):235-243. Available from: https://doi.org/10.1061/(ASCE)0733-9496(2001)127:4(235).

Yaghoubi B, Hosseini SA, Nazif S, Daghighi A. 2020. Development of reservoir’s optimum operation rules considering water quality issues and climatic change data analysis. Sustainable Cities and Society. 63:102467. Available from: https://doi.org/10.1016/j.scs.2020.102467.

Yang T, Gao X, Sellars SL, Sorooshian S. 2015. Improving the multi-objective evolutionary optimization algorithm for hydropower reservoir operations in the California Oroville–Thermalito complex. Environmental Modelling & Software. 69:262-279. Available from: https://doi.org/10.1016/j.envsoft.2014.11.016.

Yeh WW‐G. 1985. Reservoir management and operations models: a state‐of‐the‐art review. Water Resources Research. 21(12):1797-1818. Available from: https://doi.org/10.1029/WR021i012p01797.

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright (c) 2022 Srividya Sekar, Amin Daghighi, Victoria Chen, Glenn Clingenpeel, Yu Zhang, Jay Michael Rosenberger, Azam Boskabadi