A5060999305- Hydrological Forecasting Using AI
- Hydrology and Watershed Management Studies
- Hydrology and Drought Analysis
- Energy Load and Power Forecasting
- Neural Networks and Applications
- Cryospheric studies and observations
- Flood Risk Assessment and Management
- Climate change and permafrost
- Climate variability and models
- Transboundary Water Resource Management
- Landslides and related hazards
- Water resources management and optimization
- Water Quality and Pollution Assessment
- Winter Sports Injuries and Performance
- Hydrocarbon exploration and reservoir analysis
- GNSS positioning and interference
- Remote Sensing and LiDAR Applications
- Water management and technologies
- Water Quality Monitoring and Analysis
- Solar and Space Plasma Dynamics
- Groundwater flow and contamination studies
- Advanced Image Fusion Techniques
- Stock Market Forecasting Methods
- Hydraulic Fracturing and Reservoir Analysis
- Geophysics and Gravity Measurements
Soil Conservation and Watershed Management Research
2009-2022
Tarbiat Modares University
2008-2020
Ministry of Energy
2010-2011
Graduate University of Advanced Technology
2010
ABSTRACT In this research, two scenarios of drought forecast were studied. the first scenario, time series monthly streamflow converted into Standardized Hydrological Drought Index ( SHDI ), a similar index to well‐known Precipitation SPI ). Multi‐layer feed‐forward artificial neural network FFANN ) was trained with hydrological Karoon River in southwestern Iran. second discharge forecasted directly and then . Principal component analysis PCA forward selection FS techniques applied remove...
Much research is carried out for predicting the longitudinal dispersion coefficient (LDC) in natural streams based on regression models. However, few methods are accurate enough to predict LDC parameter satisfactorily. In present investigation, two data-driven developed hydraulic and geometric data that easily obtained streams. We have tried determine deficiencies of previously models, subsequently develop an optimum model. For this purpose, a support vector machine (SVM) structural risk...
Abstract Developing a robust flood forecasting and warning system ( FFWS ) is essential in flood‐prone areas. Hydrodynamic models, which are major part of such systems, usually suffer from computational instabilities long runtime problems, particularly important real‐time applications. In this study, two artificial intelligence namely neural network ANN adaptive neuro‐fuzzy inference ANFIS ), were used for routing an M adarsoo river basin, I ran. For purpose, different rainfall patterns...
The Volga River, as the primary supplier of Caspian Sea, plays a huge role in its ecosystem sustainability. In this study, we analyze runoff predictability for different monthly forecast horizons. Additionally, meteorological and hydrological variables affecting each month are identified. A wide range potential was first collected Boruta variable preprocessing method employed to select important ones. Then hybrid models were created by combining selected data-driven [i.e., support vector...
In the present work, joint response of key hydrologic variables, including total precipitation depths and corresponding simulated peak discharges, are investigated for different antecedent soil moisture conditions using copula method. The procedure started with calibration validation accounting (SMA) loss rate algorithm incorporated in Hydrologic Engineering Center – modeling system (HEC–HMS) model study watershed. A 1000 year long time series hourly rainfall was then generated by...
In the present era, Climate change and its impact on available water resources are one of main challenges. this regard, temporal spatial analysis temperature precipitation, which important parameters in determining status resources, can be used to assess hydro-climatological conditions watershed appropriate management policies. research, trend precipitation distribution over 30 years testing period 1981-2010 was investigated using non-parametric tests such as Man-Kendal, Spearman, Sen’s...
In this study, multi-temporal high-resolution satellite and Unmanned Aerial Vehicle (UAV) images were obtained to determine glacier kinematics dynamics for the first time in Iran, which could enhance our understanding of debris-covered change mechanisms part world. flow velocity Alamkouh Iran was surveyed using combination very UAV imageries from 2005 2020. Glacier surface (GSV) during last 15 years analysed by employing frequency cross-correlation technique Co-registration Optically Sensed...
To answer questions about linkages between changes in glaciers and climate change—e.g., How much of the current global sea-level rise can be attributed to melting glaciers?—more precise quantitative studies are required. This includes systematically extending available situ remote sensing data, putting together a more-detailed world glacier inventory (WGI), continuing strategically enlarging mass balance monitoring network, conducting rigorous uncertainty assessment data series.