Researcher

My Expertise

I can provide expert comment on satellite rainfall estimation, precipitation uncertainty, flood-relevant hydrological prediction, and the use of Earth observation for water-resource assessment in data-scarce regions. My expertise also includes hydrological modelling in mountainous and snow-influenced catchments, climate-change impacts on water availability and flood risk, and the development of data-merging methods that improve the reliability of environmental information used in water management.

Keywords

Fields of Research (FoR)

Surface water hydrology, Photogrammetry and remote sensing

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Biography

Suraj Shah is a PhD candidate in Civil and Environmental Engineering at UNSW Sydney, specialising in hydrological remote sensing, statistical hydrology, and climate-sensitive water modelling. His research develops improved satellite-based precipitation merging methods and snow-dominated hydrological models for data-scarce, mountainous regions, with the broader goal of strengthening flood prediction and climate-impact assessment. He works at...view more

Suraj Shah is a PhD candidate in Civil and Environmental Engineering at UNSW Sydney, specialising in hydrological remote sensing, statistical hydrology, and climate-sensitive water modelling. His research develops improved satellite-based precipitation merging methods and snow-dominated hydrological models for data-scarce, mountainous regions, with the broader goal of strengthening flood prediction and climate-impact assessment. He works at the intersection of Earth observation, statistical inference, and process-based modelling, and is driven by a simple standard: methods should not merely perform well, they should withstand scrutiny.


My Research Activities

My research focuses on improving hydrological information in data-scarce and complex regions through satellite remote sensing, statistical hydrology, and hydrological modelling. A central theme of my work is the development of robust data-merging methods for precipitation and other geophysical variables, including frameworks such as CoNE-opt and RainMerge that address limitations in conventional product-merging approaches.

I am also interested in how improved hydroclimatic datasets can strengthen hydrological prediction, particularly for mountainous and snow-influenced basins. More broadly, my research aims to develop methods that are statistically rigorous, physically interpretable, and useful for water-resource assessment and climate-impact studies.


My Engagement

I am involved in a collaborative project supporting the Water Authority of Fiji to strengthen hydrological information systems and turbidity forecasting in data-scarce catchments. My contribution includes developing a cloud-based Hydrological Information System for data access and visualisation, and applying SWAT modelling to assess how land-use change may influence river turbidity and sediment dynamics in Fiji, particularly in the Waimanu and Sigatoka River catchments.

This engagement links hydrological research with operational water-resource and water-quality management, using remote sensing, catchment modelling, and decision-support tools to inform practical planning and monitoring.

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