From columns to catchments: estimating et and p from TROPOMI water isotopologue measurements

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From columns to catchments: estimating et and p from TROPOMI water isotopologue measurements

A look into the possibilities of deep learning and TROPOMI water isotopologue data for studying global water cycles

Master Thesis (2025)

Author(s)

D. Soler Alvarez - Miranda (TU Delft - Aerospace Engineering)

Contributor(s)

N. A.K. Doan – Mentor (TU Delft - Aerodynamics)

Tobias Borsdorff – Mentor (SRON–Netherlands Institute for Space Research)

Faculty

Aerospace Engineering

Deep Learning Remote Sensing Climate change Hydrology

To reference this document use:

https://resolver.tudelft.nl/uuid:bfc2c2b0-c71c-43f2-8629-4b4199ffe4b6

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Publication Year

2025

Language

English

Graduation Date

20-10-2025

Awarding Institution

Delft University of Technology

Programme

['Aerospace Engineering']

Faculty

Aerospace Engineering

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Abstract

Evapotranspiration (ET) and precipitation (P) shape water cycles globally, with a very large impact on climate and societies. This work explores the possibilities of estimating them using Deep Learning models and water isotopologue data from the TROPOMI instrument, and a suite of other sources of data, such as Flux Towers, ERA5, IMERG, etc.

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File under embargo until 20-10-2026