Omid Asadi Nalivan

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Alireza ArabameriDepartment of Geomorphology, Tarbiat Modares UniversityVerifierad e-postadress på modares.ac.ir
Davoud Davoudi MoghaddamPostdoctoral FellowVerifierad e-postadress på sfu.ca
Omid Rahmati2021& 2022 Clarivate Highly Cited Researcher| AREEOVerifierad e-postadress på areeo.ac.ir
John P. TiefenbacherProfessor of Geography, Texas State UniversityVerifierad e-postadress på txstate.edu
Asish SahaPhD Research Scholar (UGC-SRF), Department of Geography, The University of BurdwanVerifierad e-postadress på scholar.buruniv.ac.in
Mahmood SamadiM.S. (Watershed Management), University of Tehran, Iran.Verifierad e-postadress på ut.ac.ir
Saro LeeKorea Institute of Geoscience and Mineral ResourcesVerifierad e-postadress på kigam.re.kr
Anvar SanaeiPost Doctoral Researcher, Universität LeipzigVerifierad e-postadress på uni-leipzig.de
Hamid DarabiUniversity of HelsinkiVerifierad e-postadress på helsinki.fi
Ali Torabi HaghighiAssociate Professor, University of OuluVerifierad e-postadress på oulu.fi
Arshad AliProfessor of Forest Ecology, Hebei UniversityVerifierad e-postadress på njfu.edu.cn
Ahmad ValipourForestry, Faculty of Natural Resources,University of Kurdistan, Sanandaj, IranVerifierad e-postadress på uok.ac.ir
Seyed Hasan KaboliFaculty of Desert Studies, Semnan University, Semnan, IranVerifierad e-postadress på semnan.ac.ir
Yousef AskariResearch Division of Natural Resources, Kohgiluyeh and Boyerahmad Agriculture and NaturalVerifierad e-postadress på areeo.ac.ir
Professor Biswajeet Pradhan, SMIEEE...Distinguished Prof. & Director, CAMGIS Center, University of Technology Sydney, AustraliaVerifierad e-postadress på uts.edu.au
Seyed Saeid GhiasiPhD Candidate, Tarbiat Modares UniversityVerifierad e-postadress på modares.ac.ir
Zahra KalantariAssociate Professor, KTH Royal Institute of Technology and Stockholm UniversityVerifierad e-postadress på natgeo.su.se
Khaled AhmadaaliDepartment of Arid and Mountainous Regions ReclamationVerifierad e-postadress på ut.ac.ir
Mahdi Panahi, Ph.D.Department of Physical Geography at Stockholm UniversityVerifierad e-postadress på natgeo.su.se
Ali HaghizadehProfessor. Water Resources Engineering(Hydrology) , Lorestan University,IRANVerifierad e-postadress på lu.ac.ir

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Omid Asadi Nalivan

University of Maragheh

Verifierad e-postadress på maragheh.ac.ir

Groundwater Resources Watershed Health GIS Integrated Water Resources Management Machine


Titel Sortera efter citat Sortera efter år Sortera efter titel	Citeras av Citeras av	År
The effect of sample size on different machine learning models for groundwater potential mapping in mountain bedrock aquifers DD Moghaddam, O Rahmati, M Panahi, J Tiefenbacher, H Darabi, ... Catena 187, 104421, 2020	117	2020
Modeling groundwater potential using novel GIS-based machine-learning ensemble techniques A Arabameri, SC Pal, F Rezaie, OA Nalivan, I Chowdhuri, A Saha, S Lee, ... Journal of Hydrology: Regional Studies 36, 100848, 2021	101	2021
GIS-based site selection for check dams in watersheds: considering geomorphometric and topo-hydrological factors O Rahmati, Z Kalantari, M Samadi, E Uuemaa, DD Moghaddam, ... Sustainability 11 (20), 5639, 2019	78	2019
Novel machine learning approaches for modelling the gully erosion susceptibility A Arabameri, O Asadi Nalivan, S Chandra Pal, R Chakrabortty, A Saha, ... Remote Sensing 12 (17), 2833, 2020	77	2020
Urban flood hazard modeling using self-organizing map neural network O Rahmati, H Darabi, AT Haghighi, S Stefanidis, A Kornejady, OA Nalivan, ... Water 11 (11), 2370, 2019	57	2019
Novel ensemble approaches of machine learning techniques in modeling the gully erosion susceptibility A Arabameri, O Asadi Nalivan, S Saha, J Roy, B Pradhan, ... Remote Sensing 12 (11), 1890, 2020	56	2020
Impacts of climatic and edaphic factors on the diversity, structure and biomass of species-poor and structurally-complex forests YA Arshad Ali, Anvar Sanaei, Mingshi Li, Omid Asadi Nalivan, Khaled ... Science of the Total Environment 706 (135719), 1-12, 2020	49*	2020
Identifying sources of dust aerosol using a new framework based on remote sensing and modelling O Rahmati, F Mohammadi, SS Ghiasi, J Tiefenbacher, DD Moghaddam, ... Science of the Total Environment 737, 139508, 2020	48	2020
K-fold and state-of-the-art metaheuristic machine learning approaches for groundwater potential modelling A Arabameri, A Arora, SC Pal, S Mitra, A Saha, OA Nalivan, S Panahi, ... Water Resources Management 35, 1837-1869, 2021	23	2021
Big-trees–Energy mechanism underlies forest diversity and aboveground biomass A Ali, A Sanaei, M Li, OA Nalivan, MJ Pour, A Valipour, J Karami, ... Forest Ecology and Management 461, 117968, 2020	22	2020
Performance evaluation of GIS-based novel ensemble approaches for land subsidence susceptibility mapping A Arabameri, S Lee, F Rezaie, S Chandra Pal, O Asadi Nalivan, A Saha, ... Frontiers in Earth Science 9, 663678, 2021	20	2021
A hybrid intelligent model for spatial analysis of groundwater potential around Urmia Lake, Iran O Asadi Nalivan, SA Mousavi Tayebi, M Mehrabi, H Ghasemieh, ... Stochastic Environmental Research and Risk Assessment 37 (5), 1821-1838, 2023	16	2023
Data on assessment of corrosion-scaling potential and chemical parameters of groundwater quality for industrial and agricultural sectors in the Piranshahr Watershed in the West … OA Nalivan, E Mollaefar, E Soltani, M Karvarinasab Data in brief 27, 104627, 2019	11	2019
Comparison of two methods of IUCN and watershed, range and forest management in assessing watershed sustainability (Case study: Talleghan-Zeidasht) O Asadi Nalivan, M Mohseni Saravi, GA Zahedi Amiri, AA Nazari Samani Journal of Watershed Management Research 6 (11), 73-89, 2015	11	2015
TET: An automated tool for evaluating suitable check-dam sites based on sediment trapping efficiency O Rahmati, H Ghasemieh, M Samadi, Z Kalantari, JP Tiefenbacher, ... Journal of Cleaner Production 266, 122051, 2020	10	2020
Environmental filtering, predominance of strong competitor trees and exclusion of moderate-weak competitor trees shape species richness and biomass A Ali, A Sanaei, OA Nalivan, K Ahmadaali, MJ Pour, A Valipour, J Karami, ... Science of The Total Environment 723, 138105, 2020	10	2020
Optimizing machine learning algorithms for spatial prediction of gully erosion susceptibility with four training scenarios G Liu, A Arabameri, M Santosh, OA Nalivan Environmental Science and Pollution Research 30 (16), 46979-46996, 2023	9	2023
Susceptibility Zoning and Prioritization of the Factors Affecting Landslide Using MaxEnt, Geographic Information System and Remote Sensing Models (Case study: Lorestan Province) M Teimouri, OA Nalivan Hydrogeomorphology 6 (21), 155-179, 2020	9	2020
Spatial mapping of gully erosion susceptibility using an efficient metaheuristic neural network M Mehrabi, OA Nalivan, M Scaioni, M Karvarinasab, A Kornejady, ... Environmental Earth Sciences 82 (20), 459, 2023	8	2023
Land-subsidence susceptibility mapping: assessment of an adaptive neuro-fuzzy inference system–genetic algorithm hybrid model T Wen, W Tiewang, A Arabameri, O Asadi Nalivan, SC Pal, A Saha, ... Geocarto International 37 (26), 12194-12218, 2022	7	2022

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