Sustainable optimization of agricultural water management in Pajaro Valley, California

Abstract

Climate variability, population growth, urbanization, economic development, and the industrialization of food production have intensified water management challenges worldwide (M. A. Hanjra, J. Blackwell, G. Carr, F. H. Zhang, & T. M. Jackson, 2012). These challenges are well illustrated in the study case of Pajaro Valley, a highly productive agriculture area, located within the central coast region of California (CA), United States. In Pajaro Valley, groundwater has been the primary water resource for agriculture, as farmers increase their reliance on groundwater supplies, the natural infiltration of rainfall and percolation of irrigation water is becoming inadequate to refill the aquifer. This reoccurring imbalance between pumping and recharge has severe consequences, such as basin overdraft and depletion, which can cause permanent loss of storage, seawater intrusion, and an unreliable water supply (J. Hoogesteger & P. Wester, 2015). The goal of this study was to build a simulation-optimization model to serve as an integrated agriculture-aquifer management tool in order to decrease groundwater depletion by maximizing agriculture net revenue while allocating land and water in a sustainable way. The methodology started by collecting and analyzing hydrological data and water management information such as water allocation, costs and demand from 1966 to 2015. With these data, the groundwater simulation model was built in the Water Evaluation And Planning system software (WEAP). In parallel, acreage and water allocation objective-functions (mathematical equations) and constraints where defined for a linear optimization model and a genetic algorithm optimization model, developed in MATLAB by the Water Resource Management Research Group of the University of California Davis. Then, the simulation and optimization models were linked throughout Excel Visual Basic and WEAP. The coupled models were run from 1966 to 2015 in periods of 25 years. This linkage addressed the complex nature of determining the best or optimal strategies of water and landallocation that often affect groundwater management policies for future projections. Simulation model results showed how aquifer storage from 1966 to 2009 was depleted annually in average by -12.85 thousand acre-ft (TAF) (-16 million m3). Future projection trends showed an increase in storage depletion from 2016 to 2040 of -38.83 TAF (47.89 million m3). On the other hand, by applying optimization modelling, results in a future projection showed an average annual groundwater storage of -8.42 TAF (10 million m3) and -8.26 TAF (-10 million m3) from 2016 to 2040, and of -1.71 (-2 million m3) and -1.75 TAF (-2million m3) from 2016 to 2030, using linear optimization and genetic optimization respectively. In average an improvement of 96% for the shorter period and 79% for the larger, is observed from the optimized scenarios when compared to the actual or baseline trend, meaning that optimization models can help the reduction of overdraft and propitiate an increase in the recharge of the basin. The use of combined simulation-optimization models in water management, enhances the possibility to observe a future scenario with desired attributes and trade-offs, by improving water conservation and groundwater resource management policies. In this case, agriculture water use in an optimization scenario, dropped from yearly average of 51 TAF (63 million m3) to only use 40 TAF (49 million m3) by 2030 until 2040. However, trade-offs affect food production and profitability, net revenue will decrease in average by 45 million dollars while food production will drop 20%. Overall the use of this simulation-optimization model provides a powerful tool to look at a future window on agriculture water management. Depletion of aquifers and other water bodies pose a threat to the numerous ecosystem services they provide. Awareness of potential impacts and implementation of long-term strategies such as hydro-economic models, can offer better understanding on agriculture water resources at future scenarios. These make a suitable tool for developing improved water management policies and for addressing problems and needs of farmers, general population and ecological concerns.