Identifier
etd-10312011-162534
Degree
Master of Science in Biological and Agricultural Engineering (MSBAE)
Department
Biological and Agricultural Engineering
Document Type
Thesis
Abstract
Water management represents an essential component in all agricultural activities, where significant improvements can be achieved through the implementation of field measuring devices and irrigation scheduling models. The methods that integrate these tools may be based on information regarding the soil, crop, and weather. Evapotranspiration (ET) is one of the most important components of the soil water-balance used in modeling. A number of estimation methods have been developed to determine Reference Evapotranspiration (ETo) under various types of weather conditions. In this research, an analysis was conducted between different ETo estimation methods and ETo calculated from soil water content measurements and a soil-water budget, in Northeast Louisiana during the 2010 sweetpotato growing season. Similarly, the standardize ASCE Penman-Monteith equation was then compared to ETo equations using limited weather inputs. Additionally, a Sweetpotato Irrigation Scheduler (SPIS) based on a simple soil-water balance approach was developed to improve irrigation scheduling using weather, crop, and soil data. The model’s predictions were validated, for the critical first 30 Days after Transplanting (DAT) and for the entire growing season, against field data obtained from soil water content probes. A previously developed phenology-driven Bayesian belief network model was used to establish the timing and depth of irrigation. Some difficulties where found during the assessment of ETo and the simulation of the soil-water content under unsaturated soil and dry weather conditions. These circumstances reduced the capacity of the soil to move water appropriately, slowing down some of the processes involved in the soil-water budget, causing a misrepresentation by the ETo equations and the irrigation scheduling model.
Date
2011
Document Availability at the Time of Submission
Release the entire work immediately for access worldwide.
Recommended Citation
Rojas Jimenez, Jose Pablo, "Integrated weather sensor platform and decision support system for improved sweet potato production" (2011). LSU Master's Theses. 4161.
https://repository.lsu.edu/gradschool_theses/4161
Committee Chair
Sheffield, Ronald
DOI
10.31390/gradschool_theses.4161