I Managing Groundwater for Agriculture, with Hydrologic
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Managing Groundwater for Agriculture, with Hydrologic Uncertainty and Salinity By YIQING YAO B.S. (Shanghai Jiao Tong University, China) 2013 M.S. (Carnegie Mellon University, U.S.) 2014 DISSERTATION Submitted in partial satisfaction of the requirements for the degree of DOCTOR OF PHILOSOPHY in Civil and Environmental Engineering in the OFFICE OF GRADUATE STUDIES of the UNIVERSITY OF CALIFORNIA DAVIS Approved: Jay Lund, Chair Jonathan Herman Samuel Sandoval Solis Committee in Charge 2020 i To my grandpa, Guozhu Yao, I met you in the dream when I finished the writing, and you smiled and waved. Merry Christmas! ii ACKNOWLEDGEMENTS I would like to first thank Jay Lund, who offered me great opportunity to join his research group as a volunteer graduate researcher. I should say thank you to Jay again for inviting me to rejoin his group as a formal PhD student after I left the group for seven months. He made me alert when I was too off the way in the first year and guided me to figure out what to focus on. He supported me with readerships and GSR and encouraged me with confidence and hope under the unprecedented time of Covid-19. His kindness, enthusiasm and insight make my entire graduate study full of joy. Besides Jay, this dissertation also owes its completion to committee members: Jon Herman, for his kind GSR sponsorship, his great class on evolutionary algorithm in which I coded for the first time, and his valuable comments on my dissertation; and Sam Sandoval Solis, for his generous feedback. Special thanks go to: Josue Medellín-Azuara, who helped me develop the model from the scratch and gave me valuable insights on my dissertation; Graham Fogg, who kindly served my Qualification Exam; Carlos Puente for his beautiful book The Fig Tree & The Bell; Thomas Harter, who introduced the world of groundwater to me with insightful knowledge on salinity; Yueyue Fan, who offered me a great chance to be a TA after the hearty conversation; Bassam Younis, whose readership cemented my knowledge on hydraulics; Hui Zhang for his continuous support on my MS and PhD applications; and David Dzombak, who kindly encouraged me to further my research. During my daily study and research, I have received continuous support from former and current research group members, in particular, Ellie White, Mustafa Dogan, Kathy Schaefer, Nicholas Santos, Ann Willis, Kathleen Stone, Alessia Siclari Melchor, and Hui Rui, for their many helps. I also need to thank all my dear friends for enriching my life outside of academia when times were hard: Yixin Yao, Bingru Chen, Yinyin Wang, Yiyan Zhu, and Yan Feng. Animals in Animal Crossing have been giving me company since the pandemic: Tia, Marina, Tangy, Molly, Lolly, Mac, Reneigh, Broccolo, Pango, Colton, Angus, Gigi, Norma, Julia, Zucker, Willow, Whitney, Poncho, and Fang, without whom I will not survive these days. Finally, I should say thank you to my family. My dad Liejun Yao, my mom Zhujin Yu, and my grandma Songde Zheng have been educating me to be an honest person, to strive for excellence, and to contribute to society. I particularly want to thank my husband Wenjie Zhao, a talented PhD candidate in Statistics at UCSC. He helped me a lot in the coding, speeded up my model running, and accompanied me throughout the difficult time. I am so grateful to have all the encouragement, support, and infinite love from the beautiful but challenging world. iii ABSTRACT Coordinated management of groundwater, surface water, and crops across wet and dry water years is of growing importance in California and other (semi)arid parts of the world. Water agencies are seeking to manage agricultural water supplies while ending chronic groundwater overdraft with the least economic loss. Including salinity considerations makes this goal more complex and demanding. Chapter 1 introduces the potential benefits and problems of conjunctive water management in California and summarizes conclusions from the following chapters which analyze and quantify the effect of conjunctive use and salinity in the context of agriculture in California’s southern Central Valley. Chapter 2 begins with a two-stage stochastic quadratic model to develop optimal intermediate (10-year) crop mix decisions and conjunctive water use operations with a stochastic surface water supply to maximize the net expected economic benefits of crop production and conjunctive use, given a fixed groundwater storage change target. Perennial crop planting decisions are made in the first stage. Decisions on annual crop planting, groundwater pumping, and land and water for recharging are made in the second stage with probabilistic hydrologic events. Without salinity, this model’s results indicate conjunctive water management can greatly smooth hydrologic variability in water availability to stabilize crop decisions and productions and improve agricultural profitability across water year types, with greater pumping in dry years and refilling groundwater in wetter years. In Chapter 3, groundwater salinity is added to this intermediate-term model, which makes perennial crop profit probabilistic as perennial crop yield depends on the salinity of irrigation water from groundwater and available surface water in each hydrologic event. Model results show that salinity suppresses pumping in dry years when fresh surface water limits ability to dilute saline groundwater from becoming too salty for salt-sensitive, high-value perennial crops. Groundwater salinity can fundamentally change and limit conjunctive use operations and benefits. Chapter 4 extends the planning horizon. A 10-year inner stochastic quadratic model from Chapter 2 is embedded in a 10-stage (10 year per stage) outer dynamic programming (DP) optimization to develop optimal long-term (100-year) decisions on perennial and annual crop acreages and conjunctive water use operations with stochastic surface water availability. The best combination of groundwater storage and perennial crop acreage are found from the outer DP, while corresponding decisions on annual crop acreage, groundwater pumping and artificial recharge for each stage are found from the inner stochastic quadratic model. The DP results show that without salinity, it is most profitable to continue pumping at a slower rate until a long-term water balance is reached at a desired groundwater storage target. Similarly, Chapter 5 embeds the 10-year stochastic quadratic model from Chapter 3 in a 10- stage DP optimization, with groundwater salinity as an additional state variable. The model results show perennial crop acreage decreases with time from accumulating groundwater salinity. Greatly reduced pumping and much earlier groundwater storage recovery slow salinity accumulation and prolong the agricultural utility of aquifer storage. Again, higher groundwater salinity can fundamentally alter optimal conjunctive use operations. iv TABLE OF CONTENTS ACKNOWLEDGEMENTS ................................................................................................... III ABSTRACT............................................................................................................................ IV CHAPTER 1: CONJUNCTIVE WATER MANAGEMENT AND THE FUTURE OF CALIFORNIA’S AGRICULTURE .........................................................................................1 References..................................................................................................................................7 CHAPTER 2: TWO-STAGE STOCHASTIC QUADRATIC MODELING OF CROP DECISIONS AND CONJUNCTIVE WATER USE ................................................................9 Abstract .....................................................................................................................................9 1. Introduction .................................................................................................................... 10 1.1 Overdraft ................................................................................................................. 10 1.1 Sustainable Groundwater Management Act (SGMA) ............................................... 10 1.2 Climate Change in California .................................................................................. 10 2. Method ........................................................................................................................... 11 2.1 Conjunctive Use Modeling ...................................................................................... 11 2.2 Quadratic Programing of Agricultural Production Decisions .................................... 11 2.3 Model Formulation .................................................................................................. 12 3. Results and Discussion ................................................................................................... 16 3.1 Case Study Site ....................................................................................................... 16 3.2 Optimal Planning Results Summary ........................................................................ 18 3.3 Sensitivity Analysis ................................................................................................. 25 3.4 Limitations .............................................................................................................. 30 Conclusions .............................................................................................................................. 30 References...............................................................................................................................