h1

h2

h3

h4

h5
h6

001     1031957
005     20260317050504.0
024 7 _ |a 0378-3774
|2 ISSN
024 7 _ |a 1873-2283
|2 ISSN
024 7 _ |a SCOPUS:2-s2.0-105031065589
|2 SCOPUS
024 7 _ |a WOS:001706190800001
|2 WOS
024 7 _ |a 10.1016/j.agwat.2026.110254
|2 doi
024 7 _ |a 10.18154/RWTH-2026-03209
|2 datacite_doi
037 _ _ |a RWTH-2026-03209
041 _ _ |a English
082 _ _ |a 640
100 1 _ |0 P:(DE-82)1031959
|a Sahu, Hempushpa
|b 0
|u rwth
245 _ _ |a Predictive drivers and transferability of multi-scale machine learning based crop yield prediction under drought across European and Asian climates
|h online, print
260 _ _ |a Amsterdam
|b Elsevier
|c 2026
300 _ _ |a [1]-16
336 7 _ |0 0
|2 EndNote
|a Journal Article
336 7 _ |0 PUB:(DE-HGF)16
|2 PUB:(DE-HGF)
|a Journal Article
|b journal
|m journal
336 7 _ |2 BibTeX
|a ARTICLE
336 7 _ |2 DRIVER
|a article
336 7 _ |2 DataCite
|a Output Types/Journal article
336 7 _ |2 ORCID
|a JOURNAL_ARTICLE
588 _ _ |a Dataset connected to , , , CrossRef, Journals: publications.rwth-aachen.de
591 _ _ |a Germany
591 _ _ |a India
700 1 _ |a Garg, Pradeep Kumar
|b 1
700 1 _ |a Vijay, Saurabh
|b 2
700 1 _ |0 P:(DE-82)IDM06471
|a Dasgupta, Antara
|b 3
|e Corresponding author
|u rwth
773 _ _ |0 PERI:(DE-600)2012450-8
|a 10.1016/j.agwat.2026.110254
|p 110254
|t Agricultural water management
|v 327
|x 1873-2283
|y 2026
856 4 _ |u https://publications.rwth-aachen.de/record/1031957/files/1031957.pdf
|y OpenAccess
909 C O |o oai:publications.rwth-aachen.de:1031957
|p openaire
|p open_access
|p VDB
|p driver
|p dnbdelivery
910 1 _ |0 I:(DE-588b)36225-6
|6 P:(DE-82)1031959
|a RWTH Aachen
|b 0
|k RWTH
910 1 _ |0 I:(DE-588b)36225-6
|6 P:(DE-82)IDM06471
|a RWTH Aachen
|b 3
|k RWTH
914 1 _ |y 2026
915 1 _ |0 StatID:(DE-HGF)0031
|2 StatID
|a Peer reviewed article
|x 0
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2025-11-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2025-11-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1050
|2 StatID
|b BIOSIS Previews
|d 2025-11-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1190
|2 StatID
|b Biological Abstracts
|d 2025-11-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0600
|2 StatID
|b Ebsco Academic Search
|d 2025-11-11
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b AGR WATER MANAGE : 2022
|d 2025-11-11
915 _ _ |a IF >= 5
|0 StatID:(DE-HGF)9905
|2 StatID
|b AGR WATER MANAGE : 2022
|d 2025-11-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0501
|2 StatID
|b DOAJ Seal
|d 2025-08-21T14:42:16Z
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2025-11-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0500
|2 StatID
|b DOAJ
|d 2025-08-21T14:42:16Z
915 _ _ |a Fees
|0 StatID:(DE-HGF)0700
|2 StatID
|d 2025-11-11
915 _ _ |a OpenAccess
|0 StatID:(DE-HGF)0510
|2 StatID
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b DOAJ : Anonymous peer review
|d 2025-08-21T14:42:16Z
915 _ _ |a Article Processing Charges
|0 StatID:(DE-HGF)0561
|2 StatID
|d 2025-11-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1060
|2 StatID
|b Current Contents - Agriculture, Biology and Environmental Sciences
|d 2025-11-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2025-11-11
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2025-11-11
915 _ _ |a Creative Commons Attribution CC BY 4.0
|0 LIC:(DE-HGF)CCBY4
|2 HGFVOC
915 _ _ |a Nationallizenz
|0 StatID:(DE-HGF)0420
|2 StatID
|d 2025-11-11
|w ger
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2025-11-11
920 1 _ |0 I:(DE-82)314410_20140620
|k 314410
|l Lehrstuhl und Institut für Wasserbau und Wasserwirtschaft
|x 0
920 1 _ |0 I:(DE-82)316830_20230509
|k 316830
|l Juniorprofessur für Data-driven Computing in Civil Engineering
|x 1
980 _ _ |a I:(DE-82)314410_20140620
980 _ _ |a I:(DE-82)316830_20230509
980 _ _ |a UNRESTRICTED
980 _ _ |a VDB
980 _ _ |a journal
980 1 _ |a FullTexts

LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21