The floodplain inundation history of the Murray-Darling Basin through two-monthly maximum water depth maps.

With growing concerns over water management in rivers worldwide, researchers are seeking innovative solutions to monitor and understand changing flood patterns. In a noteworthy advancement, stakeholders interested in the changing flood patterns of the Murray Darling Basin (MDB) in Australia, covering an area of 1 million km, can now access a consistent timeseries of water depth maps for the entire basin. The dataset covers the period from 1988 to 2022 at two-monthly timestep and was developed using remotely sensed imagery and a flood depth estimation model at a spatial resolution of ≈30 m, providing a comprehensive picture of maximum observed inundation depth across the MDB.

Physics-informed deep learning framework to model intense precipitation events at super resolution.

Physical modeling of precipitation at fine (sub-kilometer) spatial scales is computationally very expensive. This study develops a highly efficient framework for this task by coupling deep learning (DL) and physical modeling. This framework is developed and tested using regional climate simulations performed over a domain covering Montreal and adjoining regions, for the summers of 2015-2020, at 2.

Multi-decadal trends in global terrestrial evapotranspiration and its components.

Evapotranspiration (ET) is the process by which liquid water becomes water vapor and energetically this accounts for much of incoming solar radiation. If this ET did not occur temperatures would be higher, so understanding ET trends is crucial to predict future temperatures. Recent studies have reported prolonged declines in ET in recent decades, although these declines may relate to climate variability.

Assessing irrigated agriculture's surface water and groundwater consumption by combining satellite remote sensing and hydrologic modelling.

Globally, irrigation accounts for more than two thirds of freshwater demand. Recent regional and global assessments indicate that groundwater extraction (GWE) for irrigation has increased more rapidly than surface water extraction (SWE), potentially resulting in groundwater depletion. Irrigated agriculture in semi-arid and arid regions is usually from a combination of stored surface water and groundwater.