A5016190617- Hydrology and Watershed Management Studies
- Hydrological Forecasting Using AI
- Flood Risk Assessment and Management
- Groundwater and Watershed Analysis
- Soil erosion and sediment transport
- Hydrology and Sediment Transport Processes
- Water Systems and Optimization
- Soil and Unsaturated Flow
- Soil Moisture and Remote Sensing
- Groundwater and Isotope Geochemistry
- Hydraulic flow and structures
- Groundwater flow and contamination studies
- Landslides and related hazards
- Plant Water Relations and Carbon Dynamics
- Cryospheric studies and observations
- Climate change and permafrost
- Disaster Management and Resilience
- Greenhouse Technology and Climate Control
- Climate change impacts on agriculture
- Water management and technologies
- Synthetic Aperture Radar (SAR) Applications and Techniques
- Tropical and Extratropical Cyclones Research
- Water resources management and optimization
- Hydrology and Drought Analysis
- Transboundary Water Resource Management
Ferdowsi University of Mashhad
2018-2022
<abstract> This study intends to investigate the performance of boosted regression tree (BRT) and frequency ratio (FR) models in groundwater potential mapping. For this purpose, location springs was determined western parts Mashhad Plain using national reports field surveys. In addition, thirteen conditioning factors were prepared mapped for modelling process. Those factor maps are: slope degree, aspect, altitude, plan curvature, profile length, topographic wetness index, distance from...
In the current paper, efficiency of three new standalone data-mining algorithms [M5 Prime (M5P), Random Forest (RF), M5Rule (M5R)] and six novel hybrid bagging (BA-M5P, BA-RF BA-M5R) Attribute Selected Classifier (ASC-M5P, ASC-RF ASC-M5R) for streamflow prediction were assessed compared with an autoregressive integrated moving average (ARIMA) model as a benchmark. The models used precipitation (P) (Q) data from period 1979–2012 training validation (70% 30% data, respectively). Different...
Soil water erosion (SWE) is an important global hazard that affects food availability through soil degradation, a reduction in crop yield, and agricultural land abandonment. A map of susceptibility first vital step management conservation. Several machine learning (ML) algorithms optimized using the Grey Wolf Optimizer (GWO) metaheuristic algorithm can be used to accurately SWE susceptibility. These include Convolutional Neural Networks (CNN CNN-GWO), Support Vector Machine (SVM SVM-GWO),...
Land subsidence (LS), which mainly results from poor watershed management, is a complex and nonlinear phenomenon. In the present study, LS at country-wide assessment of Iran was mapped by using several geo-environmental conditioning factors (namely, altitude, slope degree aspect, plan profile curvature, distance river, road or fault, rainfall, geology land use) into machine learning algorithm-based artificial neural network (ANN), powerful group method data handling (GMDH). The total dataset...
In recent years, drought has inflicted significant damage on agriculture and rural communities in Iran. Resilience is the capability of to handle tolerate exterior pressures such as drought. The purpose this study was identify indicators affecting social resilience against drought, determining cause reduction or increase different regions. It also focuses strategies for increasing through provision services required information collected using a questionnaire from five villages, including...
In the present study, three widely used modeling approaches: (1) sediment rating curve (SRC) and optimized OSRC, (2) machine learning models (ML) (random forest (RF) Dagging-RF (DA-RF)) (3) semi-physically based soil water assessment tool (SWAT) are applied to predict suspended load (Qs) at Talar watershed in Iran. Various graphical quantitative methods were evaluate goodness of fit. Results indicated that RF model had best prediction power training phase, while dagging-RF hybrid algorithm...
Agricultural hillslopes with susceptible loess enters a large amount of runoff and sediment into the Gorgan city annually, due to inappropriate drainage system which cause lot financial losses city.The purpose this study was investigate effect different vegetation scenarios on discharge from three catchment 5.9 hectares.The were simulated for one year using WEPP model.In addition, eight include present condition, extremum potential scenario, existence lack annual permanent compared in...
Abstract Direct soil temperature (ST) measurement is time-consuming and costly; thus, the use of a simple cost-effective machine learning (ML) tool helpful. In this study, ML approaches, including KStar, instance-based K-nearest learner (IBK) locally weighted (LWL) coupled with resampling algorithms bagging (BA) dagging (DA) were developed tested for multi-step ahead (3, 6 9 days ahead) ST forecasting. addition, linear regression model (LR) was used as benchmark to compare results. A dataset...
Abstract Labyrinth weirs are utilized to increase the weir crest length transport a greater discharge during floods in contrast conventional weirs. Nevertheless, due increased geometric complexity of labyrinth weirs, determination accurate coefficients and accordingly, head-discharge ratings quite essential issues practical application. Hence, as first step present study proposes following eight standalone algorithms: decision table (DT), Kstar, least median square (LMS), M5 prime (M5P),...