A5039567207- Flood Risk Assessment and Management
- Hydrology and Watershed Management Studies
- Groundwater and Watershed Analysis
- Soil erosion and sediment transport
- Hydrology and Drought Analysis
- Landslides and related hazards
- Hydrology and Sediment Transport Processes
- Soil and Land Suitability Analysis
- Aeolian processes and effects
- Hydrological Forecasting Using AI
- Groundwater and Isotope Geochemistry
- Fire effects on ecosystems
- Remote Sensing in Agriculture
- Cryospheric studies and observations
- Tropical and Extratropical Cyclones Research
- Land Use and Ecosystem Services
- Tree Root and Stability Studies
- Groundwater flow and contamination studies
- Dam Engineering and Safety
- Atmospheric aerosols and clouds
- Species Distribution and Climate Change
- Urban Heat Island Mitigation
- Karst Systems and Hydrogeology
- Disaster Management and Resilience
- Atmospheric chemistry and aerosols
Soil Conservation and Watershed Management Research
2019-2024
Agricultural Research & Education Organization
2019-2024
Lorestan University
2015-2022
University of Tehran
2014-2022
Ton Duc Thang University
2019-2020
Islamic Azad University, Khorramabad Branch
2018-2019
Flood is one of the most devastating natural disasters with socio-economic and environmental consequences. Thus, comprehensive flood management essential to reduce effects on human lives livelihoods. The main goal this study was investigate application frequency ratio (FR) weights-of-evidence (WofE) models for susceptibility mapping in Golestan Province, Iran. At first, a inventory map prepared using Iranian Water Resources Department extensive field surveys. In total, 144 locations were...
Flood is considered to be the most common natural disaster worldwide during last decades. hazard potential mapping required for management and mitigation of flood. The present research was aimed assess efficiency analytical hierarchical process (AHP) identify flood zones by comparing with results a hydraulic model. Initially, four parameters via distance river, land use, elevation slope were used in some part Yasooj River, Iran. In order determine weight each effective factor, questionnaires...
Mapping flood-prone areas is a key activity in flood disaster management. In this paper, we propose new susceptibility mapping technique. We employ ensemble models based on bagging as meta-classifier and K-Nearest Neighbor (KNN) coarse, cosine, cubic, weighted base classifiers to spatially forecast flooding the Haraz watershed northern Iran. identified using data from Sentinel-1 sensor. then selected 10 conditioning factors predict floods assess their predictive power Relief Attribute...
Modelling the flood in watersheds and reducing damages caused by this natural disaster is one of primary objectives watershed management. This study aims to investigate application frequency ratio maximum entropy models for susceptibility mapping Madarsoo watershed, Golestan Province, Iran. Based on methods as well analysis relationship between events belonging training group factors affecting risk flooding, weight classes each factor was determined a GIS environment. Finally, prediction map...
Identification of flood-prone sites in urban environments is necessary, but there insufficient hydraulic information and time series data on surface runoff. To date, several attempts have been made to apply deep-learning models for flood hazard mapping areas. This study evaluated the capability convolutional neural network (NNETC) recurrent (NNETR) mapping. A flood-inundation inventory (including 295 flooded sites) was used as response variable 10 flood-affecting factors were considered...
The rapid increase in human population has increased the groundwater resources demand for drinking, agricultural and industrial purposes. main purpose of this study is to produce potential map (GPM) using weights-of-evidence (WOE) evidential belief function (EBF) models based on geographic information system Azna Plain, Lorestan Province, Iran. A total number 370 wells with discharge more than 10 m3s−1were considered out them, 256 (70%) were randomly selected training purpose, while...