Digital Skills

Basic

1. Operating software: Windows

2. Microsoft office suite: MS Word, Excel, Access, and PowerPoint 

3. Graphical representation software: Microsoft Visio, Edraw Max and Prezi

4. Communication: Microsoft Teams, Skype, Zoom, and Discord

Research and reporting

1. Reference management Software: Endnote, Mendeley, and Zotero

2. Bibliography Analysis tools: MAXQDA, and VOSviewer

Modelling and data analysis (work details are available in academic research and publication page) 

• Hydrological Modelling 

  • SWAT - Soil & Water Assessment Tool 

    • QSWAT - QGIS interface for SWAT  

    • RSWAT or R-SWAT -  R packagae for SWAT/SWAT+ calibration, parameter sensitivity/uncertainty analysis

    • SWAT-CUP - Calibration and Uncertainty Programs for SWAT

I used SWAT to understand how different scenarios of historical and projected data (like CMIP6, SSP-RCP, CHIRPS, GeoMIP, and WorldClim) affect the water quality and quantity, identify sensitive hydrological parameters after calibrating river discharge data, and examine the impact of soil water conservation and aquifer recharge techniques on water sustainability. Further details are provided here.

• • • • • MOHID Land - Three-dimensional Water Modelling System (link)

• • AquaCrop - FAO Crop Water Productivity Model

I utilized AquaCrop modeling to demonstrate the significance of automated irrigation in optimizing biomass yield and water productivity for paddy cultivation compared to rainfed or fixed strategies. See here for more details. 

• • WEAP - Water Evaluation and Adaptation Planning

• Hydraulic Modelling

  • • • • HEC-RAS - Hydrologic Engineering Center - River Analysis System

        • BASEMENT - Basic Simulation Environment 

I did flood simulation of Elbe River both 1D and 2D using HEC-RAS and BASEMENT respectively. This study included simulation until the steady state situation achieved, sensitivity analysis and comparing the model output with 10, 100 and 200 years return periods flood. More details here.

• • SWMM - Storm Water Management Model

• Groundwater Modelling

  • MODFLOW - USGS Modular (Finite-Difference) Ground-Water Model

    • GMS - Groundwater Modeling System

    • PMWIN - Processing MODFLOW for Windows 

    • ModelMuse - A Graphical User Interface for MODFLOW

I explored the use of MODFLOW to simulate the surface-groundwater interaction, changes in baseflow after incorporating reservoirs and artificial ponds and observing the long-term impact of climate data on storage. More details here. Moreover I have experience in evaluating  the impact of climate change and abstraction demand on the water supply dunes' groundwater resilience and Managed Aquifer Recharge (MAR) efficiency. See here for more details. I utilized SEAWAT to simulate variable-density groundwater flow and saline-freshwater interactions, benchmarking results against Henry and Elder problems to optimize extraction rates and design mitigation strategies for saltwater intrusion.

• • Surfer - Golden Software's 2D and 3D models

• Hydrogeochemical

  • PHREEQC - pH-REdox-EQuilibrium

I utilized PHREEQC to simulate 1D reactive transport and ion speciation, analyzing the impact of onsite sanitation on aquifer chemistry and the environmental fate of antibiotic metabolites in urban groundwater. More details here. I conducted a comprehensive assessment of heavy metal loads (Fe, Zn, Ni, Cu, Cr, Cd) in water and sediment, identifying geogenic reactions and comparing concentrations against WHO and ECR standards to evaluate riverine health. See here for more details. 

• GIS & Remote Sensing 

  • QGIS 

  • ArcGIS 

  • ERDAS Imagine 

  • Google Earth Engine

I leverage machine learning and GEE to analyze land-use change and forest fragmentation for sustainable resource management. More details here. I am also experimenting in GEE for groundwater estimation workflow using GRACE.  

• Programming and statistics

  • Python – Jupyter notebook and VS code

I am familiar with Python programming with understanding popular libraries for geospatial, hydroclimatic data processing automation, statistical analysis, and visualization. See here for more details. 

I utilized PySEBAL and Landsat imagery to perform remote sensing-based assessments of evapotranspiration and biomass production, identifying water deficit hotspots and optimizing irrigation performance for the Irrigation Scheme. More details here.

• • R and SPSS

• In-Situ Field Measurement: Multiparameter water quality meter, lysimeter, water level logger (pressure transducer)

• Laboratory Techniques: Titration, Spectrophotometer, ICP, isotopes and ion analysis