A5068296049- Climate change impacts on agriculture
- Hydrology and Watershed Management Studies
- Hydrology and Drought Analysis
- Agricultural risk and resilience
- Flood Risk Assessment and Management
- Place Attachment and Urban Studies
- Rice Cultivation and Yield Improvement
- Urban Green Space and Health
- Education and Islamic Studies
- Complex Network Analysis Techniques
- Agricultural Productivity and Crop Improvement
- Hydrological Forecasting Using AI
- Climate variability and models
- Complex Systems and Time Series Analysis
- Linguistic, Cultural, and Literary Studies
- Climate Change Communication and Perception
- Geotechnical Engineering and Soil Stabilization
- Mental Health Research Topics
- Pancasila Values in Education
- Groundwater and Isotope Geochemistry
- Microbial bioremediation and biosurfactants
- Psychological Well-being and Life Satisfaction
- Agricultural Science and Fertilization
- Social Acceptance of Renewable Energy
- Microplastics and Plastic Pollution
Florida A&M University - Florida State University College of Engineering
2024-2025
University of Tabriz
2014-2024
Arak University of Medical Sciences
2022
Politecnico di Milano
2020-2021
Khorramshahr University of Marine Science and Technology
2019
Islamic Azad University, Karaj
2018
Karaj Payam Noor University
2018
Payame Noor University
2018
Abstract. Compound weather events may lead to extreme impacts that can affect many aspects of society including agriculture. Identifying the underlying mechanisms cause impacts, such as crop failure, is crucial importance improve their understanding and forecasting. In this study, we investigate whether key meteorological drivers be identified using least absolute shrinkage selection operator (LASSO) in a model environment, method allows for automated variable able handle collinearity...
The influence of the concentration total petroleum hydrocarbons (TPHs) on competition between isolated oil-degrading bacteria (ODB) and finished compost microorganisms (FCM) was investigated in composting bioreactors over 12 weeks period. First, batch tests were performed Bushnell–Haas medium (BHM) to evaluate biodegradation activities six native ODB from sludge (PS). Then, added containing 10 30 g/kg TPHs. Based BHM results, highest degradation efficiency crude oil (1%–3% concentration)...
Soil moisture, a key hydrologic variable that determines hydroclimatic extremes including catastrophic flooding, is generally considered less important in cities compared to natural, agricultural and rural areas due the prevalence of impervious surfaces. However, recent empirical studies on stormwater runoff reduction by turfgrass lawns (which cover nearly half cumulative urban area USA), have demonstrated soil moisture highly significant factor flooding. Yet, remains uncertain high...
Drought is one of the most severe climate-induced phenomena; with significant impacts on agriculture, water resources, and ecosystems. monitoring under climate change scenarios becomes crucial, particularly in regions vulnerable to scarcity, such as semi-arid areas Iran. Although Global Climate Models (GCMs) contain coarse spatial resolutions, they provide valuable insights better assessing variability drought characteristics—such duration, severity, intensity future. To achieve...
Land surface temperature (LST) derived from satellite thermal sensors is a crucial dataset for environmental and urban studies. However, the limited spatial resolution accuracy of these datasets may present significant challenges various applications. This study introduces two innovative approaches to improve LST: (1) regression-based model integrating multiple sources information (2) physically-based Surface Energy Balance (SEB). The employs, decision-level fusion approach minimize impact...
Floods are among the most common and impactful natural events. The hazard of a flood event depends on its peak (Q), volume (V) duration (D), which interconnected to each other. Here, we used worldwide dataset daily discharge, two statistics (Kendall's tau Spearman's rho) conceptual hydrological rainfall-runoff model as model-dependent realism, investigate factors controlling origin dependence between couple characteristics, with focus rainfall-driven From statistical analysis dataset, found...
Abstract Some argue that complementing climate change mitigation measures with solar radiation management (SRM) might prove a last resort to limit global warming 1.5 °C. To make socially responsible decision on whether use SRM, it is important consider also public opinion, across the globe and particularly in Global South, which would face greatest risks from both SRM. However, most research opinion about SRM stems North. We report findings first large-scale, cross-cultural study among...
Abstract Projecting future climate variables is essential for comprehending the potential impacts on hydroclimatic hazards like floods and droughts. Evaluating these challenging due to coarse spatial resolution of global models (GCMs); therefore, bias correction widely used. Here, we applied two statistical methods—standard empirical quantile mapping (EQM) a hybrid approach, EQM with linear (EQM‐LIN)—to correct precipitation air temperature simulated by nine GCMs. We used historical...
To evaluate the effects of irrigation with saline water Bahmanshir River in southwestern Iran, 11 samples from river two flow and ebb periods 22 soil depths 0–20 20–40 cm were taken. The suitability indexes Wilcox, USSL, Doneen charts used to determine quality agricultural water. texture, SAR, EC, pH parameters quality. Important factors on are ebb, wastewater discharge, hydrogeochemical climatic processes. Based most studied indexes, is classified as permissible unsuitable. Wilcox USSL...
Abstract In a network of binarized precipitation (i.e., wet or dry value), the connection dependence between each pair nodes can occur following one more conditions: wet‐wet, dry‐dry, wet‐dry, dry‐wet. Here, we firstly investigate different types dependence, year by year, within variables. We compare sample estimate probability co‐occurrence (or occurrence with lag time ±3 days) four possible combinations respect to correspondent confidence interval in hypothesis independence. develop...
Abstract Compound events, like compound floods, have rapidly aroused interest due to the strong impacts associated with them. The spatial dependence has a fundamental role in dynamics of these and causative investigations their origins could contribute elucidate dynamics. Here, we addressed pairwise between annual maximum (instantaneous) discharges occurring river stations located United Kingdom. First, tested hypothesis that comes from co-occurrence maxima using Kendall’s tau measure...
Education plays an important role in the worldly life and Hereafter of human being order to achieve a better society which provides grounds for personal development social areas, benefitting form different methods training is quite useful. In other words, education, fact, way, change attitude, because attitudes have close relationship with insights worldview ontology person, it enjoys certain stability. To this attitude one should implement programs complex process do that person bring him...
Abstract This research examines the ability of soft computing approaches (i.e. Linear Regression (LR), Gaussian Process regression (GP), Adaptive neuro-fuzzy inference system (ANFIS),Support Vector Machine (SVM) and deep neural network (DNN)) to predict undrained shear strength (SU) soil mixed waste crushed tires. Data set consisting 72 different samples were used obtained from laboratory experiments. Out experimental observations randomly separated 50 selected for model development whereas...
Abstract. Compound weather events may lead to extreme impacts that can affect many aspects of society including agriculture. Identifying the underlying mechanisms cause impacts, such as crop failure, is crucial importance improve understanding and forecasting. In this study we investigate whether key meteorological drivers be identified using Least Absolute Shrinkage Selection Operator (Lasso) in a model environment, method allows for automated variable selection able handle collinearity...
<p>Compound weather events may lead to extreme impacts that can affect many aspects of society including agriculture. Identifying the underlying mechanisms cause impacts, such as crop failure, is crucial importance improve their understanding and forecasting. In this study we investigate whether key meteorological drivers be identified using Least Absolute Shrinkage Selection Operator (Lasso) in a model environment, method allows for automated variable selection able handle...