Title
Assessment of optimal irrigation water allocation for pressurized irrigation system using water balance approach, learning machines, and remotely sensed data
Date Issued
01 May 2015
Access level
metadata only access
Resource Type
journal article
Author(s)
Utah State University
Publisher(s)
Elsevier
Abstract
Efficient irrigation can help avoid crop water stress, undesirable levels of nutrient leaching, and yield reduction due to water shortage, runoff or over irrigation. Gains in water use efficiency can be achieved when water application is precisely matched to the spatially distributed crop water demand. Thus, greater irrigation efficiency will facilitate quality crops and help to minimize additional agricultural and financial inputs. Irrigation efficiency is defined based on indicators such as irrigation uniformity, crop production, economic return, and water resources sustainability. This paper introduces a modeling approach for optimal water allocation relative to maximizing irrigation uniformity and minimizing yield reduction. Landsat images, local weather data, and field measurements were used to develop a model that describes field conditions using a soil water balance approach. The model includes two main modules: optimization of water allocation and forecasting the components of soil water balance model. Each module includes two sub-modules that consider two objectives. The optimization sub-module use genetic algorithms (GA) to identify optimal crop water application rates based on the crop type, growing stage, and sensitivity to water stress. Results from the optimization module are passed to the forecasting sub-module, which allocate water through time across the area covered by the center pivot based on the results from the previous period of irrigation (previous day) and the operational capacity of the center pivot irrigation system. The model was tested for a farm installed with alfalfa and oats and equipped with a center pivot in Scipio, Utah. The model products were assessed based on ground data (soil moisture measurements) under optimized and simulated (irrigator decisions) center pivot operations. Based on the simulation and optimization results obtained from the model, study area irrigator could use up to 20 percent less water (saved quantity over total quantity of water) over the growing season, compared to traditional operating procedures, without reducing the benefits.
Start page
42
End page
50
Volume
153
Language
English
OCDE Knowledge area
Ciencia del suelo
Otras ciencias agrícolas
Subjects
Scopus EID
2-s2.0-84923546385
Source
Agricultural Water Management
ISSN of the container
03783774
Sponsor(s)
This project was financially supported by MLFSEED grant 2013 . The authors would like to thank the Utah Water Research laboratory (UWRL), Utah State University and Provo/Utah Office of US Bureau of Reclamation for their support of this research. Also authors acknowledge AggieAir team Dr. Austin Jensen, Dr. Andres Ticlavilca, Dr. Roula Bachour, Dr. Leila Ahmadi and Manal Elarab. The authors appreciate the supports of Ivan Robins, the farm owner, which greatly improved the performance of data collection procedure
Sources of information:
Directorio de Producción Científica
Scopus