A5066655516- Flood Risk Assessment and Management
- Hydrology and Watershed Management Studies
- Hydrology and Drought Analysis
- Landslides and related hazards
- Hydrological Forecasting Using AI
- Groundwater and Watershed Analysis
- Soil erosion and sediment transport
- Fire effects on ecosystems
- Hydrology and Sediment Transport Processes
- Tree Root and Stability Studies
- Geotechnical Engineering and Analysis
- Dam Engineering and Safety
- Water Quality and Pollution Assessment
- Remote Sensing in Agriculture
- Land Use and Ecosystem Services
- Remote Sensing and Land Use
- Tropical and Extratropical Cyclones Research
- Water Quality Monitoring Technologies
- Marine and environmental studies
- Groundwater and Isotope Geochemistry
- Cryospheric studies and observations
- Heavy metals in environment
- Synthetic Aperture Radar (SAR) Applications and Techniques
- Irrigation Practices and Water Management
- Climate variability and models
University of Bucharest
2015-2025
Transylvania University of Brașov
2021-2025
National Institute of Hydrology and Water Management
2015-2024
Danube Delta National Institute for Research and Development
2021-2024
King Saud University
2024
Aliah University
2023
Bucharest University of Economic Studies
2022
Mihail Kogălniceanu University
2018-2019
Flood is a devastating natural hazard that may cause damage to the environment infrastructure, and society. Hence, identifying susceptible areas flood an important task for every country prevent such dangerous consequences. The present study developed framework flood-prone of Topľa river basin, Slovakia using geographic information system (GIS), multi-criteria decision making approach (MCDMA), bivariate statistics (Frequency Ratio (FR), Statistical Index (SI)) machine learning (Naïve Bayes...
Forest fire disaster is currently the subject of intense research worldwide. The development accurate strategies to prevent potential impacts and minimize occurrence disastrous events as much possible requires modeling forecasting severe conditions. In this study, we developed five new hybrid machine learning algorithms namely, Frequency Ratio-Multilayer Perceptron (FR-MLP), Ratio-Logistic Regression (FR-LR), Ratio-Classification Tree (FR-CART), Ratio-Support Vector Machine (FR-SVM),...
Concerning the significant increase in negative effects of flash-floods worldwide, main goal this research is to evaluate power Analytical Hierarchy Process (AHP), fi (kNN), K-Star (KS) algorithms and their ensembles flash-flood susceptibility mapping. To train two stand-alone models ensembles, for first stage, areas affected past by torrential phenomena are identified using remote sensing techniques. Approximately 70% these used as a training data set along with 10 predictors. It should be...
Hazards and disasters have always negative impacts on the way of life. Landslide is an overwhelming natural as well man-made disaster that causes loss resources human properties throughout world. The present study aimed to assess compare prediction efficiency different models in landslide susceptibility Kysuca river basin, Slovakia. In this regard, fuzzy decision-making trial evaluation laboratory combining with analytic network process (FDEMATEL-ANP), Naïve Bayes (NB) classifier, random...
Historical exploration of flash flood events and producing flash-flood susceptibility maps are crucial steps for decision makers in disaster management. In this article, classification regression tree (CART) methodology its ensemble models random forest (RF), boosted trees (BRT) extreme gradient boosting (XGBoost) were implemented to create a map the Bâsca Chiojdului River Basin, one areas Romania that is constantly exposed floods. The torrential including 962 delineated from orthophotomaps...
Recurrent floods are one of the major global threats among people, particularly in developing countries like India, as this nation has a tropical monsoon type climate. Therefore, flood susceptibility (FS) mapping is indeed necessary to overcome natural hazard phenomena. With mind, we evaluated prediction performance FS Koiya River basin, Eastern India. The present research work was done through preparation sophisticated inventory map; eight conditioning variables were selected based on...
Landslides are dangerous events which threaten both human life and property. The study aims to analyze the landslide susceptibility (LS) in Kysuca river basin, Slovakia. For this reason, previous were analyzed with 16 conditioning factors. Landslide inventory was divided into training (70% of locations) validating dataset (30% locations). heuristic approach Fuzzy Decision Making Trial Evaluation Laboratory (FDEMATEL)-Analytic Network Process (ANP) applied first, followed by bivariate...
Flooding is a natural disaster that causes considerable damage to different sectors and severely affects economic social activities. The city of Saqqez in Iran susceptible flooding due its specific environmental characteristics. Therefore, susceptibility vulnerability mapping are essential for comprehensive management reduce the harmful effects flooding. primary purpose this study combine Analytic Network Process (ANP) decision-making method statistical models Frequency Ratio (FR),...
In the present study, gully erosion susceptibility was evaluated for area of Robat Turk Watershed in Iran. The assessment performed using four state-of-the-art data mining techniques: random forest (RF), credal decision trees (CDTree), kernel logistic regression (KLR), and best-first tree (BFTree). To best our knowledge, KLR CDTree algorithms have been rarely applied to modeling. first step, from 242 locations that were identified, 70% (170 gullies) selected as training dataset, other 30%...