Since the pioneering work of Shannon in the late 1940's on the
development of the theory of entropy and the landmark contributions of
Jaynes a decade later leading to the development of the principle of
maximum entropy (POME), the concept of entropy has been increasingly
applied in a wide spectrum of areas, including chemistry, electronics
and communications engineering, data acquisition and storage and
retreival, data monitoring network design, ecology, economics,
environmental engineering, earth sciences, fluid mechanics, genetics,
geology, geomorphology, geophysics, geotechnical engineering,
hydraulics, hydrology, image processing, management sciences, operations
research, pattern recognition and identification, photogrammetry,
psychology, physics and quantum mechanics, reliability analysis,
reservoir engineering, statistical mechanics, thermodynamics, topology,
transportation engineering, turbulence modeling, and so on. New areas
finding application of entropy have since continued to unfold. The
entropy concept is indeed versatile and its applicability widespread. In
the area of hydrology and water resources, a range of applications of
entropy have been reported during the past three decades or so. This
book focuses on parameter estimation using entropy for a number of
distributions frequently used in hydrology. In the entropy-based
parameter estimation the distribution parameters are expressed in terms
of the given information, called constraints. Thus, the method lends
itself to a physical interpretation of the parameters. Because the
information to be specified usually constitutes sufficient statistics
for the distribution under consideration, the entropy method provides a
quantitative way to express the information contained in the
distribution.
