Distributed Hydrologic Modeling Using Gis

This book presents a unified approach for modeling hydrologic processes distributed in space and time using geographic information systems (GIS). This Third Edition focuses on the principles of implementing a distributed model using geospatial data to simulate hydrologic processes in urban, rural and peri-urban watersheds. The author describes fully distributed representations of hydrologic processes, where physics is the basis for modeling, and geospatial data forms the cornerstone of parameter and process representation. A physics-based approach involves conservation laws that govern the movement of water, ranging from precipitation over a river basin to flow in a river. Global geospatial data have become readily available in GIS format, and a modeling approach that can utilize this data for hydrology offers numerous possibilities. GIS data formats, spatial interpolation and resolution have important effects on the hydrologic simulation of the major hydrologic components of a watershed, and the book provides examples illustrating how to represent a watershed with spatially distributed data along with the many pitfalls inherent in such an undertaking. Since the First and Second Editions, software development and applications have created a richer set of examples, and a deeper understanding of how to perform distributed hydrologic analysis and prediction. This Third Edition describes the development of geospatial data for use in Vflo® physics-based distributed modeling.

During ten years serving with the USDA Soil Conservation Service (SCS), now known as the Natural Resources Conservation Service (NRCS), I became amazed at how millions of dollars in contract monies were spent based on simplistic hydrologic models. As project engineer in western Kansas, I was responsible for building flood control dams (authorized under Public Law 566) in the Wet Walnut River watershed. This watershed is within the Arkansas-Red River basin, as is the Illinois River basin referred to extensively in this book. After building nearly 18 of these structures, I became Assistant State Engineer in Michigan and, for a short time, State Engineer for NRCS. Again, we based our entire design and construction program on simplified relationships variously referred to as the SCS method. I recall announcing that I was going to pursue a doctoral degree and develop a new hydrologic model. One of my agency's chief engineers remarked, "Oh no, not another model!" Since then, I hope that I have not built just another model but have significantly advanced the state of hydrologic modeling for both researchers and practitioners. Using distributed hydrologic techniques described in this book, I also hope one day to forecast the response of the dams I built.

The last few years have witnessed an enormous interest in application of GIS in hydrology and water resources. This is partly evidenced by organization of sev eral national and international symposia or conferences under the sponsorship of various professional organizations. This increased interest is, in a large measure, in response to growing public sensitivity to environmental quality and management. The GIS technology has the ability to capture, store, manipulate, analyze, and visualize the diverse sets of geo-referenced data. On the other hand, hydrology is inherently spatial and distributed hydrologic models have large data requirements. The integration of hydrology and GIS is therefore quite natural. The integration involves three major components: (1) spatial data construction, (2) integration of spatial model layers, and (3) GIS and model interface. GIS can assist in design, calibration, modification and comparison of models. This integration is spreading worldwide and is expected to accelerate in the foreseeable future. Substantial op portunities exist in integration of GIS and hydrology. We believe there are enough challenges in use of GIS for conceptualizing and modeling complex hydrologic processes and for globalization of hydrology. The motivation for this book grew out of the desire to provide under one cover a range of applications of GIS tech nology in hydrology. It is hoped that the book will stimulate others to write more comprehensive texts on this subject of growing importance.

Prepared by the Task Committee on GIS Modules and Distributed Models of the Watershed of ASCE. This report guides professionals in selecting the most advantageous applications of geographic information system (GIS) modules and distributed models for watershed runoff. Recent advances in technology offer hydrologic engineers, watershed managers, and data collection agencies unprecedented capabilities for storing and manipulating data. With the advent of Digital Elevation Models (DEM), Triangulated Irregular Networks (TIN), Digital Line Graphs (DLG), and GIS software, the use of watershed modeling among industry professionals has increased at an incredible rate. With this growth, it is increasingly difficult for practitioners to choose the most effective use of the technology. This report identifies state-of-the-art GIS hydrology analysis software and techniques, as well as GIS types and map projections. It covers data commonly required for hydrologic analysis, limitations of available data, and the integration of watershed hydrological analysis software and GIS techniques. The appendix highlights nine examples of watershed modeling systems, including the Watershed Modeling System (WMS), the Soil and Water Assessment Tool (SWAT), and the Hydrologic Model CASC2D.

It is the task of the engineer, as of any other professional person, to do everything that is reasonably possible to analyse the difficulties with which his or her client is confronted, and on this basis to design solutions and implement these in practice. The distributed hydrological model is, correspondingly, the means for doing everything that is reasonably possible - of mobilising as much data and testing it with as much knowledge as is economically feasible - for the purpose of analysing problems and of designing and implementing remedial measures in the case of difficulties arising within the hydrological cycle. Thus the aim of distributed hydrologic modelling is to make the fullest use of cartographic data, of geological data, of satellite data, of stream discharge measurements, of borehole data, of observations of crops and other vegetation, of historical records of floods and droughts, and indeed of everything else that has ever been recorded or remembered, and then to apply to this everything that is known about meteorology, plant physiology, soil physics, hydrogeology, sediment transport and everything else that is relevant within this context. Of course, no matter how much data we have and no matter how much we know, it will never be enough to treat some problems and some situations, but still we can aim in this way to do the best that we possibly can.

Why Arc hydro? / David Maidment / - Arc Hydro framwork / David Maidment, Scott Morehouse / - Hydro networks / Francisco Olivera, David Maidment / - Drainage systems / Francisco Olivera, Jordan Furnans / River channels / Nawajish Noma, James Nelson / Hydrography / Kim Davis, Jordan Furnans / - Time series / Damid Maidment, Venkatesh Merwade / - Hydrologic modeling / Steve Grise, David Arctur.

The Encyclopedia of GIS provides a comprehensive and authoritative guide, contributed by experts and peer-reviewed for accuracy, and alphabetically arranged for convenient access. The entries explain key software and processes used by geographers and computational scientists. Major overviews are provided for nearly 200 topics: Geoinformatics, Spatial Cognition, and Location-Based Services and more. Shorter entries define specific terms and concepts. The reference will be published as a print volume with abundant black and white art, and simultaneously as an XML online reference with hyperlinked citations, cross-references, four-color art, links to web-based maps, and other interactive features.

A number of strategies in conjunctive use of hydrologic models and GIS are outlined. By using data base structure and functions of GRASS GIS this particular effort follows the "full integration" strategy by reprogramming CASC2D distributed parameter hydrologic model within GRASS GIS. Several advantages gained in fully integrating these two components are highlighted. While major features of the hydrologic model CASC2D are briefly described, the input requirements and output options in relation to GRASS are discussed in more detail. Some general issues in conjunctive use of hydrologic models and GIS are also addressed.