Journal of Aeronautics & Aerospace Engineering
Open Access
ISSN: 2168-9792
ISSN: 2168-9792
Ben Jarihani
University of the Sunshine Coast, Australia
Posters & Accepted Abstracts: J Aeronaut Aerospace Eng
Dry lands 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 remotelysensed data approaches in order to improve our understanding of hydrological processes in data-sparse dry land 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 modeling; 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 dry land 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 dry land, both in Australia and around the world.
Email: bjarihan@usc.edu.au