// hydroinformatics · geospatial · deep learning

Raidan
Bassah

Hydroinformatics & Geospatial Specialist

I integrate spatial data, remote sensing, physically based hydrological models, and deep learning to analyze and forecast water and climate processes — with a focus on data-scarce, conflict-affected regions.

Amsterdam, Netherlands
IHE Delft MSc Graduate
Open to PhD & research roles

I am a hydroinformatics and geospatial specialist with a multidisciplinary background spanning civil engineering, machine learning, and environmental data science. My work sits at the intersection of water systems science and computational methods, focusing on how data-driven and process-based approaches can address real-world water challenges.

My MSc research at IHE Delft applied ConvLSTM deep learning to spatiotemporal water level forecasting in the Florida Everglades — work that has since been published in the Journal of Hydrology. Alongside, I co-authored a study on historical water and agriculture governance published in Agricultural Water Management.

In my current role at the Sana'a Center for Strategic Studies, I build geospatial data pipelines and interactive visualizations to analyze extreme environmental events and hydrologically-linked displacement patterns in Yemen and the wider GCC region — work that connects hydrology directly to conflict and humanitarian research.

I am actively seeking PhD opportunities in hydroinformatics, water security, or machine learning for earth systems — particularly where geospatial methods can help understand water dynamics in data-scarce settings.

2
Journal publications (2025)
6+
Years field & research experience
4
Research projects led
HPC
Snellius supercomputer user
MENA-CD
IHE Delft Fellowship recipient

MAIN AUTHOR · Q1 JOURN

Forecasting water levels using the ConvLSTM algorithm in the Everglades, USA

Journal of Hydrology, 2025

ConvLSTM Deep learning Spatiotemporal forecasting Everglades Remote sensing

CO-AUTHOR · Q1 JOURNAL

Historical Change of Water and Agriculture Practices and Regulatory Frameworks in Yemen

Agricultural Water Management, 2025

Yemen Water governance Agriculture Policy analysis
Geospatial Data Analyst
Sep 2024 – Present
Sana'a Center for Strategic Studies · Amsterdam (remote)
  • Designing data processing pipelines to extract and structure large volumes of environmental event data from Yemen and the GCC region.
  • Developing interactive maps and statistical visualizations of extreme hydrological events for research and policy audiences.
  • Building automated geospatial archiving systems using Python and SQLite.
  • Collaborating with conflict researchers to analyze hydrologically-linked displacement patterns.
  • Conducting systematic literature reviews on extreme events in Yemen and surrounding regions.
Hydrologist
Oct 2021 – Oct 2022
NEOM Projects · Saudi Arabia
  • Designed workflows to assess hydrological extremes and environmental variability at multiple scales.
  • Built automated hydrological models and 3D interactive simulations for stakeholder communication.
  • Conducted terrain and hydrological analyses to guide planning in climate-impacted, agriculture-heavy regions.
  • Modeled flash floods and groundwater depletion using large-scale environmental and climate datasets.
GIS and Remote Sensing Specialist
Oct 2019 – Nov 2021
Yemen Flowers for Agricultural Services · Yemen
  • Gathered remote sensing and in-field data; performed data cleaning and statistical analyses.
  • Integrated satellite imagery and modeling for agricultural flood and drought risk assessment.
  • Used statistical trend analysis to detect land and water anomalies.

2023 · MSc Thesis · IHE Delft

ConvLSTM Water Level Forecasting — Everglades, USA

Developed spatiotemporal deep learning models integrating remote sensing, time series, and in-situ hydrological data to predict water level dynamics using ConvLSTM networks.

2021 · Research Project · Yemen

Early Flood Warning System — Sana'a Basin

Applied CNN models to forecast daily rainfall, emphasizing physical-hydrological relevance in training data selection and exploring extreme event detection for early warning signals.

2019 · BSc Thesis · Sana'a University

Hydraulic Connectivity — Groundwater-Surface Water, Sana'a Basin

Studied multi-layered interactions between surface and groundwater systems using numerical simulations to understand extreme recharge and discharge scenarios.

GIS & Remote Sensing

  • ArcGIS, QGIS, Google Earth Engine
  • FME, Remote Sensing
  • Spatiotemporal analysis
  • ERA5, TRMM, CMORPH, GPM
  • GIS development & mapping

Hydrological Modelling

  • HEC-RAS, HEC-HMS, SWAT
  • Lisflood
  • Numerical modelling
  • Flood & drought modelling
  • Groundwater assessment

Machine Learning & Python

  • ConvLSTM, LSTM, CNN, ANN
  • Transformer architectures
  • TensorFlow, PyTorch
  • Pandas, NumPy, SciPy
  • GDAL, GeoPandas

Computing & Data

  • HPC — Snellius supercomputer
  • PostgreSQL, MySQL, SQLite
  • Microsoft Azure, AWS
  • Parallel computing
  • Data pipeline engineering

MSc Water and Sustainable Development — Hydroinformatics profile

IHE Delft Institute for Water Education · The Netherlands

Thesis: Applying ConvLSTM Algorithm to Forecast Water Levels in the Everglades, USA

Fellowship: IHE Delft MENA-CD (full tuition + stipend)

2022 – 2023

BSc Civil Engineering

Sana'a University · Yemen

Project: Hydraulic Connectivity in the Sana'a Basin — Groundwater-Surface Water Interaction

2014 – 2019

CERTIFICATIONS

Machine Learning — Stanford (2021) GIS Specialization — UC Davis (2020) Spatial Data Science — Esri (2020)

Dr. Biswa Bhattacharya

Head of the Hydroinformatics Department
IHE Delft Institute for Water Education

b.bhattacharya@un-ihe.org

MSc thesis supervisor · co-author

Dr. Musaed Aklan

Senior Researcher — Water & Environment
Sana'a Center for Strategic Studies

musaedaklan@gmail.com

Current direct manager

Let's connect

I am open to PhD positions, research collaborations, and specialist roles in hydroinformatics, geospatial data science, or water systems. Feel free to reach out.