Ben Jarihani
University of the Sunshine Coast
Australia
Title: Studying hydrological processes in dryland landscapes: Can satellites help in data-poor regions?
Biography
Biography: Ben Jarihani
Abstract
Drylands occupy one third of the Earth’s surface and are home to around 400 million people, yet the water resources of these regions are often poorly understood because of a lack of fundamental hydrological data. Thus fundamental questions of (eco) hydrological function of these river systems cannot be understood at a detailed scale. Earth observation satellites have been proved to provide data and information on water cycle in multiple spatio-temporal scales.
This research project aims to develop remotely-sensed data approaches in order to improve our understanding of hydrological processes in data-sparse dryland landscapes. Four objectives were investigated: (i) to evaluate the accuracy and effectiveness of satellite derived altimetry data for estimating flood water depths in low-gradient, multi-channel rivers; (ii) to detect and map flood extents and optimize the trade-off between image frequency and spatial resolution using Landsat and MODIS satellites imagery; (iii) to assess satellite-based Digital Elevation Models (DEMs) accuracy for hydrodynamic modelling; and (iv) to use a hydrodynamic model supported by satellite-derived data to investigate flood water transmission loss.
This research concluded that it is now possible to realistically constrain water balances in data-sparse dryland rivers using hydrodynamic models in combination with satellite-derived data to address limitations in the availability of conventional hydrological datasets. This research has implications for the opportunities, limitations, and future directions of using remotely-sensed data to better understand water balance and hydrodynamics of data-sparse regions. This knowledge is imperative for improved management of the limited water resources in dryland, both in Australia and around the world.