Multi Scale Spectral Analysis In Hydrology

Accurate prediction of hydrological variables is essential for efficient water resources planning and management. Proper understanding of the characteristics of the time series may help in improving the simulation and forecasting accuracy of hydrological variables. This book presents a detailed description and application of multiscale time-frequency characterization tool for the spectral analysis of hydrological time series. It presents spectral analysis methods for hydrological applications through a wide variety of illustrative case studies including Wavelet transforms, Hilbert Huang Transform and their extensions.

Accurate prediction of hydrological variables is essential for efficient water resources planning and management. Proper understanding of the characteristics of the time series may help in improving the simulation and forecasting accuracy of hydrological variables. This book presents a detailed description and application of multiscale time-frequency characterization tool for the spectral analysis of hydrological time series. It presents spectral analysis methods for hydrological applications through a wide variety of illustrative case studies including Wavelet transforms, Hilbert Huang Transform and their extensions.

Accurate prediction of hydrological variables is essential for efficient water resources planning and management. Proper understanding of the characteristics of the time series may help in improving the simulation and forecasting accuracy of hydrological variables. This book presents a detailed description and application of multiscale time-frequency characterization tool for the spectral analysis of hydrological time series. It presents spectral analysis methods for hydrological applications through a wide variety of illustrative case studies including Wavelet transforms, Hilbert Huang Transform and their extensions.

Water is essential to life for humans and their food crops, and for ecosystems. Effective water management requires tracking the inflow, outflow, quantity and quality of ground-water and surface water, much like balancing a bank account. Currently, networks of ground-based instruments measure these in individual locations, while airborne and satellite sensors measure them over larger areas. Recent technological innovations offer unprecedented possibilities to integrate space, air, and land observations to advance water science and guide management decisions. This book concludes that in order to realize the potential of integrated data, agencies, universities, and the private sector must work together to develop new kinds of sensors, test them in field studies, and help users to apply this information to real problems.

This book provides a simplified description of the procedures to be used to perform an analysis of hydrological data within a multifractal framework. After a review of multifractal theory and the presentation of one model for identifying scale invariance properties, examples of applications to rainfall and discharge time series are given. It will be of interest to teachers and researchers in this field, both nationally and abroad.

Published by the American Geophysical Union as part of the Geophysical Monograph Series, Volume 171. Groundwater is a critical resource and the PrinciPal source of drinking water for over 1.5 billion people. In 2001, the National Research Council cited as a "grand challenge" our need to understand the processes that control water movement in the subsurface. This volume faces that challenge in terms of data integration between complex, multi-scale hydrologie processes, and their links to other physical, chemical, and biological processes at multiple scales. Subsurface Hydrology: Data Integration for Properties and Processes presents the current state of the science in four aspects: Approaches to hydrologie data integration Data integration for characterization of hydrologie properties Data integration for understanding hydrologie processes Meta-analysis of current interpretations Scientists and researchers in the field, the laboratory, and the classroom will find this work an important resource in advancing our understanding of subsurface water movement.

This dissertation investigates and describes several ways of using spectral analysis as a frequency domain approach for mathematical hydrological modeling. Hydrologists have used spectral analysis for modeling in the past in various ways. However, one of the novelties of this research is that it is a simplification of previous techniques, which involved acquiring information about several parameters. Many of these parameters are time consuming to collect as data or are only estimated using intricate mathematical equations. In the first chapter the relationship between stream discharge and wetland water elevations in a watershed located in North Madison, CT was successfully modeled using exclusively independent measurements of discharge and wetland water elevations. This relationship was previously modeled using six parameters, three of which had to be estimated for their instantaneous behavior. Using the methods developed in this study conserved time and effort and produced the same results. The second chapter describes how to model discharge with measures of water table elevations in a runoff source area using the same techniques described in the first chapter. Using water table elevations across a lower part of the hillslope and in a near stream area of Townbrook watershed in the Catskills of New York, spectral analysis was used to determine the rate of water transport at these various locations and to successfully model stream discharge. The third chapter describes a method of using spectral analysis to determine chemical transport throughout a catchment area. Three watersheds were analyzed to describe a relationship between wet deposition and stream water concentrations of chloride (Cl) and nitrate (NO3). Spectral analysis was also used to define a distribution of travel times associated with the transport of input concentrations of Cl, NO3, ammonium (NH4), total Phosphorus (TP), total dissolved phosphorus (TDP), total particulate phosphorus (TPP), soluble reactive phosphorus (SRP) suspended solids (SS), total kjeldahl nitrogen (TKN), and total organic carbon (TOC). All of these studies combined indicate that spectral analysis is a tool than can be of further use in many aspects of hydrology and in studies of water quality and chemical transport. (Abstract).

Multivariate Frequency Analysis of Hydro-Meteorological Variables: A Copula-Based Approach provides comprehensive and detailed descriptions of the approaches and techniques used in multivariate frequency analysis (including, but not limited to copula functions), with illustrative examples and real-life case studies provided. The book presents all background material and new developments in one place, presenting the material in a homogeneous and pedagogical way in order to allow students, engineers and researchers to access and efficiently use all information surrounding this topic. This reference can be used as a guide to apply the available and recent approaches to evaluate hydro-meteorological risks, to design hydraulic structures, in teaching (faculty members), and as a literature review to go to the next steps in research projects (graduate students and postdocs). Presents methods for analysis of hydro-meteorological risks followed by illustrative examples based on real life data sets Provides definitions throughout on all new topics and key terms Includes case studies and real-life examples covering a variety of situations and showing how this work can be applied in the reader’s own work