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Mathematical Models of Small Watershed Hydrology and Applications by Vijay P. Singh,Donald K. Frevert Pdf
Comprehensive account of some of the most popular models of small watershed hydrology and application ~~ of interest to all hydrologic modelers and model users and a welcome and timely edition to any modeling library
Mathematical Models of Large Watershed Hydrology by Vijay P. Singh,Donald K. Frevert Pdf
Comprehensive account of some of the most popular models of large watershed hydrology ~~ of interest to all hydrologic modelers and model users and a welcome and timely edition to any modeling library
Watershed Models by Vijay P. Singh,Donald K. Frevert Pdf
Watershed modeling is at the heart of modern hydrology, supplying rich information that is vital to addressing resource planning, environmental, and social problems. Even in light of this important role, many books relegate the subject to a single chapter while books devoted to modeling focus only on a specific area of application. Recognizing the
Recent Advances in the Modeling of Hydrologic Systems by David S. Bowles,P. Enda O'Connell Pdf
This book offers a wealth of information to anyone seeking a survey of the state of the hydrologic modeling disciple in the research community in the late 1980sThe book is an excellent source of information for students seeking topics that may prove worthy of further research and study. Practitioners of hydrology would also benefit from exposure to the activities at the leading edge of their filed of interest. It also serves as a means of introducing people to aspects of hydrology that are outside their editors are to be commended for their efforts in presenting this material to the hydrologic community.' Bulletin American meteorological Society 73:12 1992
Hydrological Modelling and the Water Cycle by Soroosh Sorooshian,Kuo-lin Hsu,Erika Coppola,Barbara Tomassetti,Marco Verdecchia,Guido Visconti Pdf
This volume is a collection of a selected number of articles based on presentations at the 2005 L’Aquila (Italy) Summer School on the topic of “Hydrologic Modeling and Water Cycle: Coupling of the Atmosphere and Hydrological Models”. The p- mary focus of this volume is on hydrologic modeling and their data requirements, especially precipitation. As the eld of hydrologic modeling is experiencing rapid development and transition to application of distributed models, many challenges including overcoming the requirements of compatible observations of inputs and outputs must be addressed. A number of papers address the recent advances in the State-of-the-art distributed precipitation estimation from satellites. A number of articles address the issues related to the data merging and use of geo-statistical techniques for addressing data limitations at spatial resolutions to capture the h- erogeneity of physical processes. The participants at the School came from diverse backgrounds and the level of - terest and active involvement in the discussions clearly demonstrated the importance the scienti c community places on challenges related to the coupling of atmospheric and hydrologic models. Along with my colleagues Dr. Erika Coppola and Dr. Kuolin Hsu, co-directors of the School, we greatly appreciate the invited lectures and all the participants. The members of the local organizing committee, Drs Barbara Tomassetti; Marco Verdecchia and Guido Visconti were instrumental in the success of the school and their contributions, both scienti cally and organizationally are much appreciated.
Calibration of Watershed Models by Qingyun Duan,Hoshin V. Gupta,Soroosh Sorooshian,Alain N. Rousseau,Richard Turcotte Pdf
Published by the American Geophysical Union as part of the Water Science and Application Series, Volume 6. During the past four decades, computer-based mathematical models of watershed hydrology have been widely used for a variety of applications including hydrologic forecasting, hydrologic design, and water resources management. These models are based on general mathematical descriptions of the watershed processes that transform natural forcing (e.g., rainfall over the landscape) into response (e.g., runoff in the rivers). The user of a watershed hydrology model must specify the model parameters before the model is able to properly simulate the watershed behavior.
Frequency and Risk Analyses in Hydrology by Geoff W Kite Pdf
Hydrology is the science through which man tries to understand the properties and the distribution of water. Frequency analysis is a set of mathematical and statistical techniques used to describe the probability of occurrence of events. Every year, floods and droughts cause loss of life and millions of dollar's worth of damage in many countries of the world. In many cases, these consequences could be reduced either by nonstructural means such as restricting building in flood plains and by limiting water abstractions, or by better design of regulatory structures to reduce flood peaks and increase low flows. In all these cases, the key is knowledge of the distribution of flows in the river. Frequency and Risk Analyses in Hydrologydescribes some of the methods currently used to apply frequency analysis techniques to hydrological data in order to provide planners and engineers with figures that they can use in practice to reduce the losses caused by flood and drought. Risk analysis is an extension of the technique used to assess the probability that the estimated design event will differ from the actual event.
Hydrological Data Driven Modelling by Renji Remesan,Jimson Mathew Pdf
This book explores a new realm in data-based modeling with applications to hydrology. Pursuing a case study approach, it presents a rigorous evaluation of state-of-the-art input selection methods on the basis of detailed and comprehensive experimentation and comparative studies that employ emerging hybrid techniques for modeling and analysis. Advanced computing offers a range of new options for hydrologic modeling with the help of mathematical and data-based approaches like wavelets, neural networks, fuzzy logic, and support vector machines. Recently machine learning/artificial intelligence techniques have come to be used for time series modeling. However, though initial studies have shown this approach to be effective, there are still concerns about their accuracy and ability to make predictions on a selected input space.
Charles Thomas Haan,Howard P. Johnson,Donald L. Brakensiek,American Society of Agricultural Engineers
Author : Charles Thomas Haan,Howard P. Johnson,Donald L. Brakensiek,American Society of Agricultural Engineers Publisher : Unknown Page : 552 pages File Size : 42,9 Mb Release : 1982 Category : Nature ISBN : UOM:39015007670568
