A5074028012- Hydrology and Watershed Management Studies
- Flood Risk Assessment and Management
- Hydrology and Drought Analysis
- Meteorological Phenomena and Simulations
- Climate variability and models
- Precipitation Measurement and Analysis
- Hydrological Forecasting Using AI
- Climate change impacts on agriculture
- Anomaly Detection Techniques and Applications
- Disaster Management and Resilience
- Cryospheric studies and observations
- Mechanics and Biomechanics Studies
- Irrigation Practices and Water Management
- Non-Invasive Vital Sign Monitoring
- Water resources management and optimization
- Mosquito-borne diseases and control
- Underwater Vehicles and Communication Systems
- COVID-19 epidemiological studies
- Geophysics and Gravity Measurements
- Heart Rate Variability and Autonomic Control
- Network Security and Intrusion Detection
- Cardiovascular and exercise physiology
- Ionosphere and magnetosphere dynamics
- Earthquake Detection and Analysis
- Viral Infections and Vectors
Helmholtz Centre for Environmental Research
2023-2025
Norsk Hydro (Germany)
2025
University of Stuttgart
2021-2022
Islamic Azad University, Science and Research Branch
2016
Islamic Azad University, Tehran
2015
Amran University
2015
Iran Gridded precipitation products are of great interest for hydrological applications. The inhomogeneous geography and uneven spatial distribution rain gauges in make it difficult to estimate valuable interpolated with daily or monthly resolutions. Therefore, we evaluated the performance two empirical four geostatistical interpolation methods. Atmospheric circulation pattern (CP) classification was used understand behavior improve interpolation. Based on 500 hPa geopotential fields, six...
Monitoring heart rate (HR) is vital for health management and athletic performance, wearable technology enables scientists to obtain real-time cardiovascular insights. This study compares Machine Learning (ML) techniques, including Long Short-Term Memory (LSTM) networks, Physics-Informed Neural Networks (PINNs), 1D Convolutional (1D CNNs). Then, we develop a hybrid Singular Spectrum Analysis (SSA)-Augmented ML technique predict HR using sensor data. Additionally, investigate the impact of...
AbstractClimate change significantly influences the spread of infectious diseases, including leishmaniasis, a vector-borne disease transmitted by infected sand flies. Leishmaniasis affects approximately 12 million people globally, with significant health, economic, and social impacts.Despite ongoing research, there is no registered vaccine, treatment options remain limited due to drug toxicity emerging resistance.The geographical range flies has expanded from Mediterranean region toward...
This study provides a comparison of water balance components and model performance, using the LSM/HMs models: TETIS, mesoscale Hydrologic Model (mHM), PCRaster Global Water Balance (PCR-GLOBWB) Community Land (CLM), between three different experiments. The first one is calibrated EMO1 [1] precipitation as meteorological forcing, without explicit irrigation representation. second experiment simulation with EO irrigation [2] added to previous rainfall input. resulting...
Accurate representation of terrestrial Essential Climate Variables (tECVs) is crucial for practically understanding the Earth's climate system and supporting policy decisions. This study initiates benchmarking practices within Land Surface/Hydrologic Model (LSM/HM) communities by integrating high-resolution data with hyper-resolution hydrological modelling. The European Space Agency (ESA)-funded 4DHydro project employs six advanced LSM/HMs: Community (CLM), GEOfram, mesoscale Hydrologic...
Hydrological models often require gridded atmospheric fields, yet such datasets, particularly in high-resolution and near real-time, are unavailable. Al- though precipitation is the most dominant variable hydrological processes, temperature can influence river flow by influencing snowmelt, leading to snowmelt floods. Daily data insufficient capture floods, highlight- ing importance of hourly temporal resolution. Currently, there a lack reliable for Germany. The DWD provides historical that...
Long-lasting droughts have become more common worldwide in recent decades, such as Australia (2001-2009), California (2012-2014), Chile (2010-2023), and Europe (2018-2022). The combination of heatwaves has led to intense flash droughts, worsening soil moisture deficits. This resulted global shortages essential food, serious public health issues, prolonged forest fires that harm air quality populated areas. Extended also contribute food insecurity, reduced energy production, increased crises,...
Hydrological modelling forms a pivotal component in assessing water balance closure and providing valuable seasonal forecasts for essential climate variables such as soil moisture streamflow. In the pursuit of enhancing forecasting capabilities, this study employs four land surface hydrological models (HTESSEL, JULES, mHM, PCR-GLOBWB) driven by distinct meteorological forcings (ERA5LAND, EM-EARTH, MSWEP, WE5E). The investigation spans reference period from 1993 to 2019, focusing on...
<p>Investigation of extreme events and their spatial extent is one the crucial tasks in hydrology. Most hydrological models are not able to accurately simulate upper quantile discharge time series. In this research, a new method for determining spatiotemporal similarity floods was developed. The maximum absolute difference among CDFs combined with an agglomerative hierarchical cluster, tree based on clustering distribution properties done. Initially, continuous series 46 gauges...
Flood protection is crucial for making socioeconomic policies due to the high losses of extreme floods. So far, synchronous occurrences flood events have not been deeply investigated. In this paper, multivariate analysis was implemented reveal interconnection between these floods in spatiotemporal resolution. The discharge measurements 46 gauges with a continuous daily time series 55 years were taken over Neckar catchment. Initially, simultaneous identified. Kendall correlation pair sets...
A primary objective of hydrological modelling (HM) is to monitor the water balance in catchments and provide forecasts key variables fluxes (i.e., soil moisture streamflow) at seasonal scale. Within Copernicus Climate Change Service, a global forecasting framework using four state-of-the-art HMs HTESSEL, Jules, mHM PCR-GLOBWB) developed. The system required skillful an added-value society. In this study, we evaluate skill streamflow established metrics such as Continuous Rank Probability...
<p>Partitioning a dataset in multivariate analysis is one of the key points to better understanding hydrological process. Different regions catchment may bring floods variously due distinct types or their simultaneous occurrence. Therefore, it needed determine spatial extent brought together. In multidimensional space, demanding investigate floods. It not clear which kind clustering methods dimension reduction techniques are appropriate for visualizing initial similarities...
<p>The gridded interpolated daily precipitation data has a vast application in hydrometeorology. The fine resolution gained terrestrial measurements is tool to evaluate satellite, reanalysis, and radar-based products. In this study, the time series of 1561 rain gauges over Iran for period 2003-20010 used compute 1 km * maps. nearest neighborhood, Inverse Distance Weighting (IDW), Ordinary Kriging (OK), External Drift (EDK), Quantile (QK) interpolation methods are applied...