Analyzing California Climate Change Time Series Data and Its Impact on Crop Production

Abstract

Climate change has become an increasingly concerning problem in California over the last years, stemming from lack of precipitation and snowfall as well as constantly rising temperatures. Many aspects of Californian life including water availability and crop production have been negatively impacted by this recent trend. Due to the significance of agriculture on California, the farming com- munity within California and its consumers, including both in-state consumers and those who California exports its produce to, are at risk to be harmed by the negative impacts of climate change. Significant changes to the state’s temperature, precipitation rate, and water consumption and supply all would have the potential to harm crop production and the agricultural industry. Using the data obtained from various sources for each of these factors, we hope to calculate predicted changes in indemnity losses due to crop production over time. By modeling temperature and precipitation as sinusoidal functions and water consumption as a linear relation to temperature, it becomes possible to predict future indemnity losses based on these factor values using polynomial regression. By passing a moving average filter and eliminating the cyclic nature of the loss function, we were able to deduce that average temperature seemed to increase, average precipitation rate seemed to decrease, and average water consumption also increased. The combination of these factors led to a steady increase in predicted indemnity losses within the next 50 years. As water consumption is the only factor that can be changed through human intervention, it is logical for us to base our recommendations off of it. Agricultural water consumption is the main use of water in the state and a transition into more conservative irrigation methods would allow for a reduction in the net water consumption. Over long periods of time, this would decrease water consumption and therefore indemnity losses based on our models.