H2i expands hydrological modelling team

The Hydroinformatics Institute (H2i) is growing its team of hydrological modelers and we would like to warmly welcome our newest addition, junior modeler Zhang Yuxi.

Yuxi recently graduated from the National University of Singapore (NUS) and holds a degree in Environmental Engineering. Her final year project combined her interests in environmental issues and civil infrastructure - she studied the potential impact of climate change and fertilizer application on water quality in the Gardens by the Bay lake system.

She looks forward to learning from our experts and tackling even bigger projects.

Welcome on board, Yuxi!

H2i specialist shares strategies to tackle Harmful Algal Blooms (HABs) at leading water conference

Harmful algal bloom outbreaks like the one that turned the Singapore River green in October 2017 may be predicted earlier and better prevented with the help of technology, Dr. Jingjie Zhang told attendees of the Singapore International Water Week (SIWW) on Tuesday afternoon, July 10th, 2018

“As water quality deteriorates rapidly worldwide due to climate change and anthropogenic activities, the prediction and control of algal bloom becomes increasingly important. Technology that gives us access to real-time monitoring and the capability to predict   the change of the water quality in the water bodies could be key to preventing such outbreaks”, said Dr. Zhang who was invited by Xylem, a global water technology company, to speak to the audience of international water specialists attending the three-day event at Marina Bay Sands.

The conventional way of detecting algal blooms requires time to wait for the water samples to be lab-tested. Timing is critical in ensuring that the algal bloom is controlled, any delays could potentially worsen the outbreak. Hence, PUB, Deltares, NUS and H2i have worked together to develop an integrated monitoring and prediction system for algal bloom prediction, which can combine lab tests, online sensors and advanced modelling techniques.

This integrated modelling system combines results from several different models, namely, the water quality model, catchment model, hydrological model and emission model and can be implemented in the Operational Management (OMS) platform for daily operation and management. This system allows us to monitor and predict the change in water quality and test proper mitigation measures to be implemented.  By combining real-time data from online sensors with integrated data assimilation techniques and process-based modelling system, we can prevent outbreaks of harmful algal blooms.

The talk also sparked a discussion about the possibilities of how to better combine different techniques and advanced tools to improve the integrated online-sensors and modeling approach for better monitoring and early-warning and prediction of algal blooms.

SIWW is Singapore’s leading water conference and the global platform to share and co-create innovative water solutions. SIWW draws crowds of over 20,000 to exchange innovative ideas, tap global business opportunities, and showcase leading technologies.

H2i seminar at SIWW 2018

Improving algal species predictions and forecasting with combination of real-time sensors and water quality modeling: Singapore Reservoirs as Case Study  by Dr Jingjie ZHANG, Chief Water Quality Specialist of H2i and Visiting Research Professor of SUSTec Shenzhen, China 

DATE       : Tuesday, July 10th

TIME       : 4.30 pm

VENUE    : Level 3, Room Heliconia Jr. 3412