2026/1/30
Omid Asadi Nalivan

Omid Asadi Nalivan

Academic rank: Assistant Professor
ORCID: https://orcid.org/0000-0003-2077-9413
Education: PhD.
H-Index:
Faculty: Faculty of Agriculture
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E-mail: o.asadi [at] maragheh.ac.ir
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Phone: 041-37278001
ResearchGate: View

Research

Title
Application of sample fraction and machine learning models for groundwater potential mapping: a remedy for Urmia Lake? (Chapter Book)
Type
Book
Keywords
machine learning, groundwater, Urmia Lake
Year
2025
Researchers Omid Asadi Nalivan ، Esmaeil Silakhori ، Adel Soltani ، Mehdi Teimouri ، Mahdiyeh Karvarinasab ، Ayding Kornejady

Abstract

Water resources in Mediterranean, semiarid, and arid ecosystems are highly dependent on aquifer storage (Arabameri et al., 2019; Khan et al., 2019; Rahaman et al., 2019; Salem et al., 2019). These ecosystems are characterized by a permanent shortage of water resources due to an imbalance between water recharge and extraction rates, which is, to some extent, caused by low precipitation and high evaporation rates. In parallel, environmental conditions affect the livelihoods of humans because of their high dependence on groundwater resources, as surface conditions are scarce. This is why a holistic survey of groundwater resources is essential (Mussa et al., 2020; Termeh et al., 2019; Thomas et al., 2019).