| dc.contributor.author | Akhila, R. | |
| dc.contributor.author | Pramada, S. K. | |
| dc.contributor.author | Berndtsson, R. | |
| dc.date.accessioned | 2026-08-20T11:07:58Z | |
| dc.date.available | 2026-08-20T11:07:58Z | |
| dc.date.copyright | 2026/04/23 | |
| dc.date.issued | 2026 | |
| dc.identifier.other | JHYEFF.HEENG-6766.pdf | |
| dc.identifier.uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4311734 | |
| dc.description.abstract | AbstractHigh-resolution rainfall data are essential for various hydrological applications
such as flood modeling, soil erosivity studies, and urban water management. However,
the scarcity of subdaily data, particularly in remote regions, necessitates ... | |
| dc.publisher | American Society of Civil Engineers | |
| dc.title | Hybrid Approach to Rainfall Disaggregation Using Artificial Intelligence and Multivariate Disaggregation Considering Spatial Correlation | |
| dc.type | Journal Article | |
| dc.journal.volume | 31 | |
| dc.journal.issue | 4 | |
| dc.journal.title | Journal of Hydrologic Engineering | |
| dc.identifier.doi | 10.1061/JHYEFF.HEENG-6766 | |
| dc.journal.fristpage | 04026011-1 | |
| dc.journal.lastpage | 04026011-13 | |
| dc.page | 13 | |
| dc.tree | Journal of Hydrologic Engineering:;2026:;Volume ( 031 ):;issue: 004 | |
| dc.contenttype | Fulltext | |
