A5032283113- Hydrology and Watershed Management Studies
- Geophysics and Gravity Measurements
- Environmental Monitoring and Data Management
- Hydrological Forecasting Using AI
- Geophysical and Geoelectrical Methods
- Scientific Computing and Data Management
- GNSS positioning and interference
- Soil Moisture and Remote Sensing
- Climate change impacts on agriculture
- Groundwater and Watershed Analysis
- Flood Risk Assessment and Management
- Solar and Space Plasma Dynamics
- Hydrology and Drought Analysis
- Geological Modeling and Analysis
- Precipitation Measurement and Analysis
- Distributed and Parallel Computing Systems
- Remote Sensing in Agriculture
- Climate variability and models
- Groundwater and Isotope Geochemistry
- Water Quality Monitoring Technologies
- Meteorological Phenomena and Simulations
- Big Data Technologies and Applications
- Computational Physics and Python Applications
- Cryospheric studies and observations
- Time Series Analysis and Forecasting
University of Mississippi
2022-2024
Marshall Space Flight Center
2019
National Aeronautics and Space Administration
2019
Universities Space Research Association
2017-2018
Accurately assessing groundwater storage changes in Niger is critical for long-term water resource management but difficult due to sparse field data. We present a study of and recharge Southern Niger, computed using data from NASA Gravity Recovery Climate Experiment (GRACE) mission. compute anomaly estimate by subtracting the surface provided Global Land Data Assimilation System (GLDAS) model GRACE total anomaly. use statistical fill gaps analyze time period 2002 2021, which corresponds life...
The current influx of climate related information required scientists to communicate their findings decision makers in governments, disaster preparedness organizations, and the general public. Soil Water Assessment Tool (SWAT) is a powerful modelling tool that allows simulate many physical processes involved water cycle. This article presents design, methods development efforts overcome some limitations previously developed SWAT visualization software programs by creating set modular web...
Understanding the spatial and temporal distribution of hydrologic variables, such as streamflow, is important for sustainable development, especially with global population growth climate variations. Typical monitoring streamflow conducted using in situ gauging stations; however, stations are costly to setup maintain, leading data gaps regions that cannot afford gauges. Satellite data, including altimetry used supplement observations some cases supply information where they lacking. This...
Abstract Since 2002, National Aeronautics and Space Administration’s Gravity Recovery Climate Experiment (GRACE) allows scientists of various disciplines to analyze map changes in total water storage globally. Although the raw data are available public, process viewing, manipulating, analyzing GRACE can be difficult for those without strong technological backgrounds programming or geospatial software. This is particularly true managers developing countries, where could a valuable asset...
Monitoring and managing groundwater resources is critical for sustaining livelihoods supporting various human activities, including irrigation drinking water supply. The most common method of monitoring well level measurements. These records can be difficult to collect maintain, especially in countries with limited infrastructure resources. However, long-term data collection required characterize evaluate trends. To address these challenges, we propose a framework that uses from the Gravity...
Tethys Platform is an open source framework for developing web-based applications Earth Observation data. Our experience shows that significantly lowers the barrier cloud-based app development, simplifies process of accessing scalable distributed cloud computing resources and leverages additional software data computationally intensive modelling. The development kit allows users to create web apps visualizing, analyzing modelling platform provides a collaborative environment scientists...
This study presents ‘Synthetic Wells’, a method for generating synthetic groundwater level time series data using machine learning (ML) aimed at improving management in contexts where real are scarce. Utilizing from the National Water Information System of US Geological Survey, this research employs Synthetic Data Vault (SDV) framework’s Probabilistic AutoRegressive (PAR) synthesizer model to simulate real-world fluctuations. The generated approximately 100 wells align closely with data,...
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The accessibility and deployment of complex hydrological models remain significant challenges in water resource management research. This study presents a comprehensive workflow for converting Python-based into web APIs, addressing the need more accessible interoperable modeling tools. leverages modern technologies containerization to streamline process. was applied three distinct models: GRACE downscaling model, synthetic time series generator, MODFLOW groundwater model. implementation...
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