Decoding landscapes, predicting flows.

Flow Velocity Analysis Around a V-Shaped Permeable Groin-Like Structure

B.Sc. engineering thesis, co-authored with Shahriar Ahmed, supervised by Dr. Md. Kabirul Islam, EWCE Department, MIST. Compared the 3D flow velocity field — longitudinal (X), transverse (Y), and vertical (Z) — around a V-shaped bandal-like groin in both Perforated (permeable) and Drum (solid) configurations, at three alignment angles (30°, 45°, 60°), across high and low tide, near the Lebukhali reach of the Payra River.

East/North/Up velocity data (from ADCP measurements, processed in WinRiver2) were transformed into local X/Y/Z components, then decomposed by the energy sharing concept to find each component's share of kinetic energy at every measurement point — across two structure types, three angles, two tide phases, two depth bands, and two positions along the structure.

Surface Drainage Hydraulics Model Simulation Using GeoSWMM — Dhaka City

I built and simulated a surface drainage hydraulic model for a selected urban catchment in Dhaka using GeoSWMM (built on the EPA SWMM 5 engine) integrated with ArcMap 10.8. Delineated the watershed from a DEM sourced via USGS Earth Explorer, configured the drainage network (subcatchments, conduits, junctions, and outfalls), and ran a Kinematic Wave hydraulic simulation using Horton infiltration and a 10-year return period rainfall series.

I verified model performance through the status report — a strong mass-balance continuity of -0.082% on runoff, with all conduits stable and no flooding or surcharging. I analyzed peak conduit velocities and flows, node depths, and subcatchment runoff to flag the most hydraulically loaded points in the network. I also diagnosed and corrected a flow-routing continuity error by refining conduit geometry, rebalancing subcatchment parameters, and adjusting the simulation time step.

Buriganga River Pollution & Waste Disposal Site Suitability

I mapped the spatial distribution of eight water quality parameters along the Buriganga River in Dhaka, identified the river's most environmentally vulnerable zones, and ran a multi-criteria suitability analysis to locate optimal waste disposal sites — weighing river proximity, industrial zones, road access, land use, and population density.

Land Use Land Cover Change — Netrokona District

I classified and compared land cover across Netrokona district in 2015, 2020, and 2025.

Biophysical Indices Mapping — Netrokona District

I derived a set of biophysical index maps for Netrokona district from satellite imagery — vegetation indices (ARVI, SAVI, NDVI, EVI), water indices (MNDWI, NDWI), and a built-up index (NDBI) using Google Earth Engine and ArcGIS.

NDVI & NDBI Comparison — Manchester

I compared NDVI and NDBI for Manchester between 2020 and 2024 to track change in vegetation and built-up extent over the four-year period.

NDVI & NDBI Comparison — Warsaw

I compared NDVI and NDBI for Warsaw between 2020 and 2024 to track change in vegetation and built-up extent over the four-year period.

NDWI Map of France

A Normalized Difference Water Index map of France, classifying surface water content across the country from very low to very high.