Authors: Di Wu*, Southern Illinois University Carbondale, Amina Naliaka, Southern Illinois University Carbondale, Ruopu Li, Southern Illinois University Carbondale
Topics: Water Resources and Hydrology, Agricultural Geography
Keywords: Irrigation, data-driven
Session Type: Virtual Paper
Start / End Time: 9:35 AM / 10:50 AM
Room: Virtual 56
Presentation File: No File Uploaded
In many semi-arid regions, agricultural productivity highly relies on groundwater supply for irrigation. To ensure sustainable groundwater use, it is critical to understand the behavioral patterns of irrigation activities regarding their spatiotemporal variability and contributing factors. Such information is important to water managers for developing planning and management strategies for groundwater sustainability. This study aims to examine the spatiotemporal patterns of irrigation activities in a semi-arid agricultural landscape using autonomous irrigation sensor measurements and a range of environmental and social variables. We characterized the irrigation patterns based on the irrigation volume and frequency using principal component analysis, clustering analysis, and existing knowledge. Relevant environmental and social factors were explored to contextualize different irrigation patterns. Our preliminary results indicate such a data-driven approach can identify explanatory variables to account for the patterns of irrigation activities, which may be used to inform the development of more sophisticated irrigation decision-making models.