Sujan Chandra Mondol

Hydrologic Modeling

Software and Tools: Watershed Modeling System (WMS), HEC-HMS, Gridded Surface Subsurface Hydrologic Analysis (GSSHA), Lisem Integrated Spatial Earth Modeller (openLISEM)

Abilities:

• Develop lumped and distributed models in HEC-HMS and GSSHA to solve analysis and design problems.
• Formulate combinations of hydrologic modeling components and suitable equations to match a specific case.
• Calibrate models through stochastic or optimization runs with an understanding of objective functions and error metrics.
• Apply physical principles of hydrology in hydrologic modeling and refer back to the principles in interpreting results.
• Collect digital elevation model, precipitation, land-use, soil-type, etc., data from publicly available sources and process and analyze these data to compute necessary inputs and parameters.

Courses: Hydrologic Modeling, Hydrology

MOOC: Flood Hazard and Exposure Mapping (UNESCO)

Project: Hydrologic Modeling of Big Sulphur Creek near Cloverdale Watershed

Hydraulic Routing Simulations

Software and Tools: Surface-water Modeling System (SMS), HEC-RAS, Sedimentation and River Hydraulics – Two-Dimension (SRH-2D), Lisem Integrated Spatial Earth Modeller (openLISEM)

Abilities:

• Understand the derivation and simplifications of the Navier-Stokes general equation for fluid flow to Reynolds-Averaged Navier-Stokes (RANS), and to 2D Saint Venant equations and their adapted form in SRH-2D, LISEM (depth-averaged dynamic wave equation), and HEC-RAS 2D (Shallow water equation).
• Construct meshes (or grids) efficiently by combining different types of elements in zonal meshing (or enforcing refinement regions and breaklines) to rerepresent the topography and enable more accurate water flow.
• Integrate hydraulic structures as a 1D (HY-8 Culvert), 1D/2D connection, or 3D components into the model to capture the different flow behaviors around them that may change the overall flow patterns.
• Perform sensitivity analysis of the flow simulations to understand the effect of floodplain domain size, mesh element size, boundary conditions, and roughness values.
• Convert the generated two-dimensional flood simulations to flood hazard risk mapping for decision-making.

Course: Advanced Hydraulic Routing

MOOC: Flood Hazard and Exposure Mapping (UNESCO)

Project: Simulating Flow Routing through a River Reach with Structure(s) and its Floodplain

Workshop: Generating Forcing Scenarios for Compound Flood Inundation Mapping (CIROH DevCon 2025)

Water Systems Analysis & Modeling

Software and Tools: EPANET, MS Excel

Abilities:

• Perform the balance analysis between capacity and demand for water distribution systems, along with the level of service considerations and design components, including pumps and emergency storage.
• Analyze the capacity of existing distribution systems to suggest expansions in line with the projected demand.
• Suggest features of municipal drinking water, wastewater, stormwater, and irrigation systems to meet specific purposes in a project setting.

Courses: Urban Water Infrastructure

MOOCs: Sustainable Urban Water Systems (Coursera)

Data Analytics and Data Science

Software and Tools: pandas, SciPy, NumPy, Statsmodels, Matplotlib, R Programming, SQL, MS Excel

Abilities:

• Explore data with numerical and statistical summaries and visualizations.
• Identify random sampling and randomized assignments for their implications on inference and causality.
• Choose and implement hypothesis tests and create confidence intervals for inference about the population.
• Fit data to statistical regression models for prediction and inference about relationships between variables.
• Create custom Python and R data processing and analysis scripts for unique workflows using built-in, third-party, and user-defined datatypes and packages.
• Parse web data in HTML, XML, JSON, etc. data formats.
• Construct database tables and extract and manipulate data with queries.

MOOC: Statistics with Python Specialization (Coursera) || R Programming (Coursera) ||Introduction to Scripting in Python Specialization (Coursera) || Python for Everybody Specialization (Coursera) || Excel Skills for Business Specialization (Coursera)

Machine Learning and Deep Learning

Software and Tools: scikit-learn, Keras, Tensorflow, PyTorch, SHAP

Abilities:

• Prepare (bring to desired format), clean (address missing values), and pre-process (encoding and feature engineering) large datasets to train machine learning (ML) models.
• Select model features using statistical filter and subset-based wrapper methods and reduce dimensionality by extraction and aggregation techniques (e.g., principal component analysis).
• Possess an understanding of optimization algorithms, such as gradient descent, stochastic gradient descent, adaptive gradient algorithm, root mean square propagation, adaptive moment estimation, etc., and hyperparameter tuning searches.
• Construct and deploy tree-based, support vector-based, and neural network ML models of standard practices and customized variations.
• Produce Shapley-based insights and interpretations of the trained ML models for explainability.

MOOC: Advanced Deep Learning with Keras (DataCamp)

Projects: Improving National Water Model Evapotranspiration Estimates Through Tower Observations and Machine Learning || Deep learning based short-term water demand forecasting for the water distribution system in Bluffdale, Utah || Prediction of Monthly Rainfall in Bangladesh using Artificial Intelligence Techniques (Undergraduate Thesis) || A Deep Learning Approach Using Long Short-Term Memory Networks for Enhanced Prediction of Rainfall in the Northeastern Region of Bangladesh

Workshop: SHAP (SHapley Additive exPlanations) values for Interpretable Machine Learning (CIROH DevCon 2025)

Big Data and Cloud Computing

Tools and Platforms: Apache Beam, Google Cloud (Dataflow, BigQuery, Google Cloud Run), Xarray

Abilities:

• Design and implement efficient extract, transform, and load (ETL) pipelines in Apache Beam.
• Leverage Google Cloud for scalable big data infrastructure (Cloud Run) and processing (Dataflow).
• Query and manage data in relational databases and serverless data warehouses.

Projects: Enhanced and Expanded API for National Water Model Data Access

GIS and Geospatial Tool Development

Software and Tools: ArcGIS Pro, QGIS, Google Earth Engine, Leaflet, GeoPandas, GDAL, Shapely, Rasterio, Folium

Abilities:

• Retrieve, process, store, and manage diverse forms of spatial data and understand data formats.
• Analyze geospatial data to identify patterns and extract meaningful relationships among variables.
• Create professional-level layout maps and technical reports to present solutions to geospatial problems.
• Perform GIS-based multi-criteria decision analysis (MCDA) to generate composite risk maps.
• Build custom geospatial workflows by combining available and custom tools in the graphical interface of ArcGIS Model Builder or in the programmatic interface of Python and/or QGIS.
• Use web mapping tools like Leaflet to share geospatial information interactively.

Courses: Engineering Applications of GIS; Geospatial Software Development

MOOC: Flood Hazard and Exposure Mapping (UNESCO)

Projects: NWM-based web application and QGIS plugin development || Mapping Community Drought Vulnerability for California

Web Applications Development

Software and Tools: Django, Javascript, Leaflet, HTML, CSS

Abilities:

• Develop dynamic and interactive web applications to disseminate hydrologic and water data and model frameworks.
• Integrate web mapping tools to provide a geospatial interface to the user.

Courses: Geospatial Software Development

MOOCs: Django Web Framework (Coursera) || Programming with JavaScript (Coursera)

Projects: NWM-based web application and QGIS plugin development

API Development

Software and Tools: Django REST, FastAPI

Abilities:

• Develop enhanced application programming interfaces for hydrological data products to ensure stateless and analysis-ready data access.

Projects: Enhanced and Expanded API for National Water Model Data Access || Extending the operational CIROH NWM API with the return period endpoint