Omid Asadi Nalivan

ORCID: 0000-0003-2077-9413
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About
Contact & Profiles
Research Areas
  • Flood Risk Assessment and Management
  • Groundwater and Watershed Analysis
  • Soil erosion and sediment transport
  • Hydrology and Watershed Management Studies
  • Groundwater flow and contamination studies
  • Groundwater and Isotope Geochemistry
  • Forest ecology and management
  • Ecology and Vegetation Dynamics Studies
  • Geochemistry and Geologic Mapping
  • Landslides and related hazards
  • Aeolian processes and effects
  • Hydrology and Sediment Transport Processes
  • Hydrological Forecasting Using AI
  • Synthetic Aperture Radar (SAR) Applications and Techniques
  • Water Quality and Pollution Assessment
  • Geophysical and Geoelectrical Methods
  • Atmospheric aerosols and clouds
  • Plant Water Relations and Carbon Dynamics
  • Soil and Environmental Studies
  • Transboundary Water Resource Management
  • Hydrology and Drought Analysis
  • Soil and Land Suitability Analysis
  • Soil Geostatistics and Mapping
  • Soil Moisture and Remote Sensing
  • Agroforestry and silvopastoral systems

Gorgan University of Agricultural Sciences and Natural Resources
2019-2023

Watershed
2021-2023

Tarbiat Modares University
2023

Soil Conservation and Watershed Management Research
2023

Agricultural Research & Education Organization
2023

Louisiana Department of Natural Resources
2023

Islamic Azad University Kerman
2023

The present study has been carried out in the Tabriz River basin (5397 km2) north-western Iran. Elevations vary from 1274 to 3678 m above sea level, and slope angles range 0 150.9 %. average annual minimum maximum temperatures are 2 °C 12 °C, respectively. rainfall ranges 243 641 mm, northern southern parts of receive highest amounts. In this study, we mapped groundwater potential (GWP) with a new hybrid model combining random subspace (RS) multilayer perception (MLP), naïve Bayes tree...

10.1016/j.ejrh.2021.100848 article EN cc-by Journal of Hydrology Regional Studies 2021-06-26

Check dams are widely used watershed management measures for reducing flood peak discharge and sediment transport, increasing lag time groundwater recharge throughout the world. However, identifying best suitable sites check within stream networks of various watersheds remains challenging. This study aimed to develop an open-source software with user-friendly interface screening network possibilities guiding selection watersheds. In this developed site (SSS), multi-criteria decision analysis...

10.3390/su11205639 article EN Sustainability 2019-10-13

The extreme form of land degradation caused by the formation gullies is a major challenge for sustainability resources. This problem more vulnerable in arid and semi-arid environment associated damage to agriculture allied economic activities. Appropriate modeling such erosion therefore needed with optimum accuracy estimating regions taking appropriate initiatives. Golestan Dam has faced an acute gully over last decade adversely affected society. Here, artificial neural network (ANN),...

10.3390/rs12172833 article EN cc-by Remote Sensing 2020-09-01

Floods are the most common natural disaster globally and lead to severe damage, especially in urban environments. This study evaluated efficiency of a self-organizing map neural network (SOMN) algorithm for flood hazard mapping case Amol city, Iran. First, inventory database was prepared using field survey data covering 118 flooded points. A 70:30 ratio applied training validation purposes. Six factors (elevation, slope percent, distance from river, channel, curve number, precipitation) were...

10.3390/w11112370 article EN Water 2019-11-12

Gully erosion has become one of the major environmental issues, due to severity its impact in many parts world. directly and indirectly affects agriculture infrastructural development. The Golestan Dam basin, where soil degradation are very severe problems, was selected as study area. This research maps gully susceptibility (GES) by integrating four models: maximum entropy (MaxEnt), artificial neural network (ANN), support vector machine (SVM), general linear model (GLM). Of 1042 locations,...

10.3390/rs12111890 article EN cc-by Remote Sensing 2020-06-11

The optimal prediction of land subsidence (LS) is very much difficult because limitations in proper monitoring techniques, field-base surveys and knowledge related to functioning behavior LS. Thus, due the lack LS susceptibility maps it almost impossible identify prone areas as a result influences severe economic human losses. Hence, preparation mapping (LSSM) can help prevent natural catastrophes reduce damages significantly. Machine learning (ML) techniques are becoming increasingly...

10.3389/feart.2021.663678 article EN cc-by Frontiers in Earth Science 2021-05-13

The present work sets out to 1) evaluate the corrosion-scaling potential of groundwater resources for industrial sector as well 2) examine chemical parameters agricultural in Piranshahr Watershed West Azerbaijan province, Iran, using geostatistical analyses and Wilcox diagram a GIS environment. A total 145 spring locations representatives potentiality were recorded by handheld GPS device corrosion scaling states further scrutinized. latter was carried on basis examining at each sample...

10.1016/j.dib.2019.104627 article EN cc-by-nc-nd Data in Brief 2019-10-09

AbstractLand-subsidence (LS) is a common geo-hazard in many regions of the world. The overexploitation subsurface and ground water, followed by collapse underground cavities, one mechanisms that cause LS. Optimal prediction LS difficult due to limitations monitoring, surveying information about mechanism process Therefore, susceptibility mapping (LSSM) crucial prevent reduce economic damage natural manmade catastrophes. This study Isfahan Province, Iran, aimed map using hybrid model adaptive...

10.1080/10106049.2022.2066198 article EN Geocarto International 2022-04-13

Abstract Gully erosion causes high soil rates and is an environmental concern posing major risk to the sustainability of cultivated areas world. Gullies modify land, shape new landforms damage agricultural fields. mapping essential understand mechanism, development, evolution gullies. In this work, a modeling approach was employed for gully susceptibility (GESM) in Golestan Dam basin Iran. The measurements 14 gully-erosion (GE) factors at 1042 GE locations were compiled spatial database....

10.21203/rs.3.rs-1977325/v1 preprint EN cc-by Research Square (Research Square) 2022-10-17

Identification of Groundwater Potential Zones using Geographic Information System and Analytical Hierarchy Process (AHP) (Case Study: Hable-rud River Basin-Iran)

10.52547/jwmr.11.21.36 article EN Journal of watershed management research 2020-06-01

هدف از این تحقیق تعیین مناطق دارای پتانسیل حضور چشمة آب زیرزمینی و اولویت‌بندی عوامل مؤثر در آن، با استفاده روش حداکثر آنتروپی (مدل MaxEnt)، سیستم اطلاعات جغرافیایی سنجش دور است. حاضر، چهارده شاخص تأثیرگذار شامل شاخص‌های توپوگرافیکی، زمین‌شناسی، اقلیمی، هیدرولوژیکی کاربری اراضی همچنین، جدید ارتفاع سطح نزدیک‌ترین زهکش (HAND) شده ابتدا، شاخص‌ها به دو بخش توپوگرافیکی سایر تقسیم شدند نقشة براساس آنها تهیه شد. سپس، تلفیق شاخص‌ها، نهایی به‌دست آمد. مجموع 2547 چشمه، فاصلة ماهالانوبیس، 60% به‌منزلة...

10.52547/gisj.13.2.119 article FA Journal of Remote Sensing and Gis 2021-07-23
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