Planning & Management

Oral

395095 - A Bayesian Network based model for decision making on a farm scale impacted by salinity

Monday, June 4
10:30 AM - 12:00 PM
Location: Greenway GH
Co-Authors: Saurav Kumar, University of Texas El Paso – Civil Engineering; Wissam Atwah, University of Texas El Paso – Civil Engineering; Andrew Ellerson, University of Texas El Paso – Civil Engineering

Managing water resources is a formidable challenge in the face of the rising population. There are no clear solutions for most lingering chronic water resources management issues, and every option requires balancing complex and often contradictory stakeholder objectives. Substantial stakeholder involvement in decision-making can alleviate some of the issues by taking advantage of local stakeholder knowledge, improving the chances of project acceptance, increasing fairness and equity, decreasing reliance on expert opinion, and ideally, reaching a consensus decision. However, implementation of such a solution remains an outstanding challenge. With a goal to understand if graphical models may be used with conventional water quality models to encourage participation, we have developed a Bayesian Network (BN) based model. The BN model will be used to understand decision making in a farm near El Paso, TX. The primary limitation that we have tried to address with the BN model is the salinity in water. The model will provide farmers with tools to understand the impact of alternative irrigation practices (e.g., flood irrigation, and drip irrigation) and evaluate the resilience of the farm in the long-run subjected to different climatic and other socio-economic conditions (e.g., lack of reuse water, competing demands from growing cites, etc.).

Yohtaro C. Kobayashi

Undergraduate Research Assistant
Civil Engineering - University of Texas El Paso

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395095 - A Bayesian Network based model for decision making on a farm scale impacted by salinity



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