This monograph provides a unified approach to distributed parameter hydrologic modeling using Geographic Information Systems (GIS). Hydrologic models that can utilize the information content of global digital datasets offer tantalizing prospects for improved simulation of surface runoff processes. As data from newly deployed remote sensing platforms come online, hydrologic modeling techniques must keep pace with such high-resolution data. As soon as we embark on simulating hydrologic processes using these digital datasets with GIS, we must address the issues that are the subject of this book, which are the spatial and temporal characteristics of radar rainfall (NEXRAD), topography, soils, and land use/cover. Distributed modeling is demonstrated through case studies and an appendix that sets forth model results using Arc.water.fea. Comparison of model results with observed flood events demonstrates the importance of incorporating spatial variability into model parameters affecting the transformation of precipitation into surface runoff at the river basin scale. Audience: This volume will be valuable for faculty members, seniors and graduate students, practitioners from civil, agricultural, water resources and environmental engineering fields, hydrologists, physical geographers, and hydrometeorologists engaged in hydrologic modeling.
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From the Foreword Second Edition:
"All of the above make this a unique, invaluable book for the student, professor, or hydrologist seeking to acquire a thorough understanding of this area of hydrology" Philip B. Bedient, Rice University, Texas, USA
From the reviews:
"Although this book is generally concerned with surface runoff and flood periods, the conceptions and methods, as well as the method of utilizing GIS for distributed models, are remakably useful. Careful study of this excellent book will help achieve understanding of GIS-based distributed modelling, and it is highly recommended to students, teachers, researchers, and engineers involved in hydrology, water resources, and environmental Sciences." (Bulletin of the American Meteological Society, May 2002)
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