| dc.contributor.author | Alaba Boluwade | |
| dc.contributor.author | Chandra Madramootoo | |
| dc.contributor.author | Aghil Yari | |
| dc.date.accessioned | 2017-05-08T22:26:04Z | |
| dc.date.available | 2017-05-08T22:26:04Z | |
| dc.date.copyright | January 2016 | |
| dc.date.issued | 2016 | |
| dc.identifier.other | 44897827.pdf | |
| dc.identifier.uri | http://yetl.yabesh.ir/yetl/handle/yetl/80583 | |
| dc.description.abstract | Sustainable water management is paramount to effective and efficient irrigation water management. Over decades, excessive irrigation water application has caused erosion, poor crop quality, water logging, salinity, and wastage of scarce water resources. Variable rate irrigation (VRI) is a recent technique that aids the application of irrigation water according to crop needs and soil physical and chemical properties. A challenge in applying VRI is the determination of appropriate water management zones (MZs). Two software and associated clustering techniques stand out as the best in determining the optimal number of MZs: | |
| dc.publisher | American Society of Civil Engineers | |
| dc.title | Application of Unsupervised Clustering Techniques for Management Zone Delineation: Case Study of Variable Rate Irrigation in Southern Alberta, Canada | |
| dc.type | Journal Paper | |
| dc.journal.volume | 142 | |
| dc.journal.issue | 1 | |
| dc.journal.title | Journal of Irrigation and Drainage Engineering | |
| dc.identifier.doi | 10.1061/(ASCE)IR.1943-4774.0000936 | |
| dc.tree | Journal of Irrigation and Drainage Engineering:;2016:;Volume ( 142 ):;issue: 001 | |
| dc.contenttype | Fulltext | |