California's escalating water shortage, aggravated by ongoing climate change and persistent droughts, necessitates urgent action to preserve this valuable resource. According to the United States Environmental Protection Agency, 50 percent of water used for landscape irrigation and agriculture are wasted through evaporation, wind, and runoff due to overwatering of crops1. Equally important is preventing the under watering of crops, as they can face life-threatening conditions amid California's harsh climate. To strike the delicate balance between water conservation and crop health, this paper explores a method employing soil moisture sensors for precise irrigation control. The sensors measure soil water content, enabling targeted water delivery when levels are low and immediate cessation when optimal moisture is achieved. The system is managed through an Arduino microcontroller, which efficiently regulates the irrigation process based on data gathered through the moisture sensors. The Arduino processes the information received and triggers the water supply, delivered through a pump and a hose. A sprinkler attachment at the end of the hose ensures even water distribution across all plant areas, effectively preventing overwatering in any specific spot. The results indicate over a 45 percent decrease in water use while demonstrating healthier plants. This approach presents a promising solution to California's water scarcity while ensuring sustainable crop growth and efficient resource consumption. The future plans involve using solar energy to power the device's batteries and incorporating artificial intelligence (AI) technologies to detect various factors such as plant species, soil type, terrain, and real-time weather conditions. By leveraging these advanced technologies, the research aims to transform irrigation management for enhanced water efficiency and environmental sustainability concerning California's agricultural practices.

As concerns about climate change intensify, understanding the relationships between industrial consequences, natural processes, and agricultural practices becomes increasingly critical: it is important to separately dissect the individual components that eventually cumulate to cause stark global warming effects. This study investigates the correlation between fertilizer application, fertilizer emissions, and temperature change, aiming to elucidate their interplay and possible correlations within the context of climate change. Utilizing data acquired from the Food and Agriculture Organization of the United Nations (FAO), we analyze the relationship between temperature change (an indicator of climate change), nutrient nitrogen (N) fertilizer application per area of cropland, and synthetic fertilizer emissions of nitrous oxide (N 2 O). Each of the 3 components for the datasets are analyzed over 6 countries: Australia, Brazil, China, India, Italy, and the United States of America. By spanning the study over diverse geographic regions, the concluding emerging patterns will be those that can be applied globally and holistically to provide genuine context for the implications of agriculture's impact on climate change. Although the fertilizer application and synthetic fertilizer emissions did show a particularly strong correlation, there was a minimal correlation between these factors and temperature change-contrary to initial expectations. However, this finding only serves to underscore the complexity of climate dynamics and prevalence of other cumulative factors. We discuss potential explanations for these findings, while also considering the economic and agricultural stand of the selected countries by taking global dynamics such as the World Systems Theory into account. Despite the absence of a direct link between fertilizer-related emissions and temperature change, our study highlights the importance of mitigating greenhouse gas emissions from agricultural sources to address the border challenges of climate change, whose effects may not be felt directly; it will take a multitude of years for greenhouse gas emissions to be felt starkly after being accumulated for long periods prior.