Title

Multiple Satellites Remote Sensing Images For The Derivation Of A Water Availability Index

Keywords

Imaging techniques; Remote sensing; Satellites

Abstract

Recent drought events in the U.S. have threatened drinking water supplies for communities in Maryland and Chesapeake Bay in 2001 through September 2002, Lake Mead in Las Vegas in 2000 through 2004, the Peace River and Lake Okeechobee in South Florida in 2006, and Lake Lanier in Atlanta, Georgia in 2007. In the environmental science community, there is a renewed interest to develop a new "Water Availability Index (WAI)" that serves for short-term water resources planning and water infrastructure management in dry periods. Such a development may be geared toward presenting a near real-time, risk informed and forward-looking instrumental message in terms of both the quantity and quality of available fresh water in major metropolitan regions. The success of this effort could incorporate the use of integrated remote sensing technologies in concert with intermediate- and long-term climate change forecasts. It is the aim of this paper to present a state-of-the-art review about: 1) How the multi-scale and multi-dimensional databases are collected by optical and microwave satellite images, such as the NASA GOES, MODIS Terra and Aqua etc., and ground-based radar stations, such as the NOAA NEXRAD system, and 2) How these databases can be applied to support the development of a new WAI and help reduce the managerial risks of water infrastructure across the continental U.S. These discussions lead to the derivation of a new WAI with the aid of remote sensing technology. © 2008 ASCE.

Publication Date

12-1-2008

Publication Title

World Environmental and Water Resources Congress 2008: Ahupua'a - Proceedings of the World Environmental and Water Resources Congress 2008

Volume

316

Number of Pages

-

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1061/40976(316)99

Socpus ID

79251492662 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/79251492662

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