Planning & Management

Oral

360284 - Toward Whole Watershed Management: Reservoir Reoperation Using a Hybrid Multi-Objective Optimization Approach

Wednesday, June 6
8:30 AM - 10:00 AM
Location: Northstar B
Co-Authors: Robert Gailey, Davis, CA – University of California, Davis; Stephen Maples, Davis, CA – University of California, Davis; Mohammad Azizipour, Tehran, Iran – Iran University of Science and Technology; Vahid Ghelenoei, Tehran, Iran – Iran University of Science and Technology; Samuel Sandoval-Solis, Davis, CA – University of California, Davis; Graham Fogg, Davis, CA – University of California, Davis

As exemplified by the 2012-16 drought and its aftermath, water scarcity has a profound effect on agriculture and ecological functions in California. While surface reservoir storage fell to extraordinarily low levels during the drought, groundwater levels reached record lows in many areas. Sustainable Groundwater Management Act (SGMA), passed in 2014, promises a sustainable groundwater management in California by 2042. SGMA identifies managed aquifer recharge (MAR) approach as a key management option to secure the refill of underground water storage and return of groundwater quality to a desirable condition. However, the main question remain is how much water is available for MAR. This study offers a hybrid optimization approach to integrate the management of surface and groundwater resources systems. The integrated management provides an opportunity to adapt surface water systems operation to increase the groundwater recharge and to maximize the total storage of water within the basin. To re-operate Folsom Reservoir, two main objectives are considered, maximizing the water storage in the whole basin and maximizing hydropower generation. A linear programing (LP) module maximizes the total groundwater recharge by spreading water over suitable lands. Moreover, Non-dominated Sorting Genetic Algorithm is used to re-operate the reservoir systems and control releases for recharge. Preliminary results show additional releases from the reservoir for groundwater recharge during high flow seasons. Moreover, tradeoffs between the objectives show that new operation performs satisfactorily to increase the storage in the basin, with nonsignificant violations of other objectives.

Erfan Goharian, PhD

Postdoctoral Researcher
Unviersity of California, Davis

Dr. Goharian joined UC Water in January 2016 and resides with the Department of Land, Air, and Water Resources and the Water Resources Management Research Group at UC Davis. He is leading the research on integrated modeling and management of water resource systems in California.
Erfan Goharian holds a Bachelor’s degree in Civil Engineering and earned his Master’s degrees from the University of Tehran, Iran, in Civil/Water Engineering. He obtained his Ph.D. in Civil Engineering from the University of Utah in 2015 with his dissertation on performance and vulnerability assessment of integrated water resources systems. He has several publications in peer-reviewed journals, conference proceedings, and project reports, and has received multiple international awards and fellowships. Before joining UC Davis, he was a researcher in the CI-Water Project and USAID Partner Center for Advanced Studies in Water. Erfan Goharian's research interests include integrated water resources modeling and management, system analysis, and hydroinformatics. He has additional expertise related to hydrologic modeling, climate change impact assessment on water resources, and stormwater management. Beyond his technical background, he has experience working in collaborations across institutions and disciplinary boundaries.

Presentation(s):

Send Email for Erfan Goharian


Assets

360284 - Toward Whole Watershed Management: Reservoir Reoperation Using a Hybrid Multi-Objective Optimization Approach



Attendees who have favorited this

Please enter your access key

The asset you are trying to access is locked. Please enter your access key to unlock.

Send Email for Toward Whole Watershed Management: Reservoir Reoperation Using a Hybrid Multi-Objective Optimization Approach