Assessing salinity impacts on crop yield and economic returns in the Central Valley

This study aimed to assess the impact of salinity in the root zone on crop yields and profitability in the Central Valley. A comprehensive biophysical model was developed by integrating soil variables, climate conditions, irrigation inputs, and economic data. The model considered four key crops (alfalfa, almonds, table grapes, and processing tomatoes), five levels of irrigation water salinity (ranging from 0.5 to 5.5 dS/m), and daily irrigation water amounts (ranging from 0 to 12 mm). The results indicated strong predictive capabilities of the model, with R2 values for predicted yields of 0.82, 0.77, 0.78, and 0.64 for alfalfa, almonds, grapes, and tomatoes, respectively. The corresponding RMSE values were 9%, 8%, 23%, and 11% for the same crops. Profit predictions showed an R2 value of 0.99 for alfalfa, almonds, and processing tomatoes, and 0.74 for grapes. The RMSE values were 48, 211, 2461, and 68 $/ha for alfalfa, almonds, grapes, and processing tomatoes, respectively. Furthermore, the model incorporated a spatial component, revealing variations in yield and profitability based on soil type and groundwater salinity across the Central Valley. Results indicated that at daily irrigation rates of 3 mm, no profits were predicted for any of the crops. However, a daily irrigation rate of 6 mm produced profits of up to $1000/ha for alfalfa and processing tomatoes, while almonds and grapes required more than 8 mm/day to achieve profitable outcomes. This integrated modeling framework provides valuable insights for policymakers to identify areas unsuitable for sustainable and profitable irrigated agriculture. It can help prioritize such areas for multi-benefit land repurposing, reducing agricultural water demand, and achieving groundwater sustainability. Additionally, the model serves as a decision-aid tool for growers in arid regions, enabling them to anticipate potential losses in crop yield and profitability due to irrigation water salinity.