This report documents the development of the combined optimization-simulation model and recommends future efforts. The combined model was tested using a case study involving high mountain recreation reservoirs in the Poudre River Basin. The selected optimization model was combined with the MODSIM model and used to automatically calibrate the model for application to the particular Poudre case.

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.

This book comprehensively accounts the advances in data-based approaches for hydrologic modeling and forecasting. Eight major and most popular approaches are selected, with a chapter for each — stochastic methods, parameter estimation techniques, scaling and fractal methods, remote sensing, artificial neural networks, evolutionary computing, wavelets, and nonlinear dynamics and chaos methods. These approaches are chosen to address a wide range of hydrologic system characteristics, processes, and the associated problems. Each of these eight approaches includes a comprehensive review of the fundamental concepts, their applications in hydrology, and a discussion on potential future directions.

The book describes the carefully made measurements in the pasture and rainforest at a series of sites across Amazonia. The data are analysed and interpreted to allow them to be used as the basis of accurate and realistic description of the land surface in the global circulation model which are used to predict the climate effect of large scale deforestation. Results are presented at all scales: for the centimetre scale of leaf and soil moisture measurementes, the field scale of micrometeorological flux measurements, through to the scale of meteorological models which predict the climate of the whole Amazonian basin.