An Improved Methodology for Estimating Future Reservoir Storage Capacities: Application to Surface Water Supply Reservoirs in Illinois (Second Edition)

published or submitted for publicationis peer reviewedOpe

Optimal Use of the Kaskaskia Navigation Canal: Management Strategies and Guidelines

published or submitted for publicationis peer reviewedOpe

Reduction in Peak Flows and Improvement in Water Quality in the Illinois Waterway Downstream of Lockport Due to Implementation of Phases I and II of TARP: Volume 1: Hydraulics and Hydrology

published or submitted for publicationis peer reviewedOpe

An Improved Methodology for Estimating Future Reservoir Storage Capacities: Application to Surface Water Supply Reservoirs in Illinois

published or submitted for publicationis peer reviewedOpe

Pace Watershed Model (PWM): Volume 1: Model Development

published or submitted for publicationis peer reviewedOpe

A Review of Rainfall-runoff Modeling for Stormwater Management

published or submitted for publicationis peer reviewedOpe

Pace Watershed Model (PWM): Volume 2, Weather Modification Simulations

published or submitted for publicationis peer reviewedOpe

Reduction in Peak Flows and Improvements in Water Quality in the Illinois Waterway Downstream of Lockport Dam Due to Implementation of Phases I and II of TARP

published or submitted for publicationis peer reviewedOpe

Precipitation Augmentation for Crops Experiments: Pre-experimental Phase Studies

published or submitted for publicationis peer reviewedOpe

SPECTRAL ANALYSIS AND FORECASTING OF HYDROLOGIC TIME SERIES

Two important aspects of hydrologic analysis--the spectral analysis and forecasting hydrologic time series--are considered in this study. Five recently developed parametric spectral estimation methods, which are claimed to be without the major drawbacks of the conventional spectrum estimation methods, are analyzed in this study. These spectral estimation methods are proposed by Marple, Kay, Cadzow, Friedlander and Pisarenko. These methods are analyzed first by using synthetic data and then by using real data. The models are selected for these methods by using three objective model selection criteria: Akaike\u27s information, Bayesian, and Hannan-Quinn criteria. Daily rainfall runoff is forecast by using both stochastic and deterministic models. The parameters of the stochastic models (autoregressive moving average -ARMA, threshold autoregressive -TAR, and ARMA models with exogenous inputs -ARMAX) are estimated by a recursive maximum likelihood (RML) method. The deterministic model used in the present study is an improved constrained linear system (CLS) model. The parameters of the CLS model are estimated by using quadratic programming. Friedlander\u27s and Pisarenko\u27s methods are recommended for spectral analysis of hydrologic time series. For forecasting daily rainfall-runoff processes, ARMAX and improved CLS models are found to be superior to the other methods