Satellite based remote sensing offers an opportunity to provide information on the Earth system that is not available from any other source. Using satellite data, the HALO Group develops and interprets products that describe various aspects of the water cycle and climate system. We have particular expertise in the development of evapotranspiration products, as well as in the remote sensing of soil moisture, vegetation and other parameters of interest to the hydrological and related sciences. Interpreting this data to better understand the dynamics of the systems we study is a central theme of our research group.

To characterise the water and energy cycles of landscapes, an understanding of the movement, distribution and variability of hydrometeorological variables is required. To do this effectively, a comprehensive assessment of these processes is required. Unfortunately, this is a challenging task due to the (sometimes) limited capacity of measurement devices to effectively capture the observed dynamics and also the inherent uncertainty and variability of these processes within a landscape. The HALO Group undertakes in-situ measurement and monitoring using a range of sophisticated instruments to enable a better understanding of both the processes and their descriptions in our modelling and remote sensing activities.

Land surface models simulate hydrologic states and fluxes useful for improving our understanding of ecosystem functioning and of great importance for water resource management and agricultural monitoring activities. Satellite remote sensing can support such modelling efforts by offering distributed information, which would be very difficult to obtain otherwise. A key objective of our research is to advance the integration of high quality satellite products within land surface modelling schemes for improved monitoring of terrestrial water, carbon and energy cycle processes in space and time.

In collaboration with Prof Georgiy Stenchikov (KAUST) and Prof. Jason Evans (UNSW), the HALO Group is undertaking a research project that seeks to explore the application of regional climate modeling across the Middle East and North Africa (MENA) region. As part of this effort, we are pursuing a number of projects that include the development of downscaled future climate simulations for hydrological applications (such as drought assessment, climate impacts and targeted agricultural studies), characterising the hydroclimatology of the MENA region and analysing retrospective simulations of key hydrometeorological events.

Understanding the characteristics of water and energy cycle behaviour in semi-arid to hyper-arid zones is a considerable challenge for hydrological scientists, not the least because it is in these locations that data is often the hardest to come by. Our research encompasses a range of topics, from describing the surface and sub-surface hydrology of these environments to modeling the flow of water and energy and undertaking in-situ observations to better constrain the uncertainty.

Evapotranspiration describes the process by which water is returned from the land surface back into the atmosphere and represents a key component of the hydrological cycle. This is particularly true in semi-arid and arid environments, where the evaporation can account for 90% of the precipitation that might fall on the land surface from sporadic rain events. In these dry environments, managing and accounting for the water usage is of great importance, so techniques to monitor and measure water exchanges are of great interest.

The reflected satellite signal in the visible to shortwave infrared region has great utility for detecting vegetation dynamics and physiological condition at a range of spatial and temporal scales, highly advantageous for agricultural monitoring and management activities. However advances in the utilization and interpretation of available satellite sensor data is still needed to realize the full potential. The HALO group is involved in various research activities aimed towards an effective use and integration of reflectance observations within physically-based canopy reflectance and land surface modeling frameworks.