Bookcover of Rainfall-Runoff Modeling Using Artificial Neural Networks
Booktitle:

Rainfall-Runoff Modeling Using Artificial Neural Networks

Rainfall-Runoff Modeling Using Artificial Neural Networks(ANNs) and Physically-based Model-Theory Simulation and Results

LAP LAMBERT Academic Publishing (2010-07-19 )

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ISBN-13:

978-3-8383-8339-2

ISBN-10:
3838383397
EAN:
9783838383392
Book language:
English
Blurb/Shorttext:
The book addresses a two-pronged approach for the determination of a watershed''s response by developing a physically-based model and a neural network-based model. For the physically-based model, the watershed is partitioned into a series of one-dimensional overland flow planes and channel elements, and water is routed over these elements in a cascading fashion. A system of partial differential equations under the kinematic wave approximation was used to describe surface water movement. The applicability of ANNs was investigated by developing a neural network-based runoff predictive model. The performance of ANNs, with different architectures, was evaluated using monthly precipitation and temperature data (input) and watershed runoff (output) for 3 medium-sized watersheds – El Dorado, Marion, and Council Grove in Kansas, USA. The prediction of watershed response was also studied using several existing empirical rainfall-runoff models. The advantage of ANNs over the physically-based models is that they require only input and output data for mapping of an unknown function such as rainfall-runoff relationship. In the case of physically-based models a lot more data is required.
Publishing house:
LAP LAMBERT Academic Publishing
Website:
https://www.lap-publishing.com/
By (author) :
Jagadeesh Anmala
Number of pages:
200
Published at:
2010-07-19
Stock:
Available
Category:
Physics, astronomy
Price:
68.00 €
Keywords:
Rainfall-Runoff, modeling, Watershed response, Artificial Neural Networks, Physically-based model, stream flow, Overland flow, Precipitation, prediction, watershed

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