Chinese researchers have proposed a novel hybrid deep-learning model to address streamflow forecasting for water catchment areas at a global scale, with a view to improving flood prediction, according to a recent research article published in the journal The Innovation. Streamflow and flood forecasting remains one of the long-standing challenges in hydrology. Traditional physically based models are hampered by sparse parameters and complex calibration procedures particularly in ungauged catchments. More than 95 percent of small and medium-sized water catchments in the world lack monitoring data, according to the Chinese Academy of Sciences (CAS). Researchers from the Institute of Mountain Hazards and Environment of the CAS used the datasets of more than 2,000 catchments around the world to conduct model training in order to cope with streamflow forecasting at a global scale for all gauged and ungauged catchments. The distribution of these catchments was significantly different, ensuring the diversity of data. The results show that the forecasting accuracy of the model was higher than traditional hydrological models and other AI models. The study demonstrated the potential of deep-learning methods to overcome the lack of hydrologic data and deficiencies in physical model structure and parameterization, the research article noted. |
The Simpsons producer apologizes to fans for killing off longJOHN MACLEOD: Could soaring prices mean the humble fish supper has finally had its chips?REVEALED: OJ Simpson's official cause of deathElliss, Jenkins, McCaffrey join Harrison and Alt in following their fathers into the NFLMore than 50 aerospace information companies registered in Xiong'an New Area: officialBrit reveals all the wild items she bought in an American WalmartMacKinnon, Nichushkin lead 5Southwest Airlines is considering changes to its quirky boarding and seating practicesA former Democratic Georgia congressman hopes abortion can power his state Supreme Court bidThe surprising sexual kink that is most likely to result in orgasm, new study suggests