Water Sampling at Kulim, 2018
Artificial Intelligence in Hydrology
Due to the fast progress in computer technology and also the development of more advanced AI algorithms, researchers in artificial intelligence (AI) have been able to develop more accurate and reliable hydrologic models, such as rainfall-runoff modelling, flood forecasting, rainfall prediction, river stage prediction, evaporation estimation, sediment load modelling, and water quality simulation. This is an area with many opportunities for further applications and development.
Due to the fast progress in computer technology and also the development of more advanced AI algorithms, researchers in artificial intelligence (AI) have been able to develop more accurate and reliable hydrologic models, such as rainfall-runoff modelling, flood forecasting, rainfall prediction, river stage prediction, evaporation estimation, sediment load modelling, and water quality simulation. This is an area with many opportunities for further applications and development.
Assessment of Climate Change
The development and study of climate are progressing rapidly. Many recent models and tools describe trends in meteorological variables under climate scenarios, compared with previous models. These recent advances will help prepare civil structures, including hydrological and hydraulic structures, to adapt to climate change.
A general trend of the annual runoff corresponding to the A2 and B2 scenarios (example of the publication)
In line with these advancements, ZH-RainSim has been developed as a standalone desktop tool to generate future rainfall ensembles from Global Climate Models (GCMs). It utilizes a Markov Chain occurrence model coupled with a Gamma distribution for intensity to downscale and simulate daily rainfall series. The source code and user interface of ZH-RainSim are protected by copyright (MyIPO: CRLY2026P00740).
 |
| Interface of ZH-RainSim |
Other links related to Research: