Hydrologic And Hydraulic Modeling Support

Digital elevation model issues in water resources modeling - Preparation of DEMs for use in environmental modeling analysis - Source water protection project : a comparison of watershed delineation methods in ARC/INFO and arcView GIS - DEM preprocessing for efficient watershed delineation - Gis tools for HMS modeling support - Hydrologic model of the buffalo bayou using GIS - Development of digital terrain representation for use in river modeling - HEC-GeoRAS : linking GIS to hydraulic analysis using ARC/INFO and HEC-RAS - Floodplain determination using arcView GIS and HEC-RAS - The accuracy and efficiency of GIS-Based floodplain determinations.

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.

This book contains seven parts. The first part deals with some aspects of rainfall analysis, including rainfall probability distribution, local rainfall interception, and analysis for reservoir release. Part 2 is on evapotranspiration and discusses development of neural network models, errors, and sensitivity. Part 3 focuses on various aspects of urban runoff, including hydrologic impacts, storm water management, and drainage systems. Part 4 deals with soil erosion and sediment, covering mineralogical composition, geostatistical analysis, land use impacts, and land use mapping. Part 5 treats remote sensing and geographic information system (GIS) applications to different hydrologic problems. Watershed runoff and floods are discussed in Part 6, encompassing hydraulic, experimental, and theoretical aspects. Water modeling constitutes the concluding Part 7. Soil and Water Assessment Tool (SWAT), Xinanjiang, and Soil Conservation Service-Curve Number (SCS-CN) models are discussed. The book is of interest to researchers and practitioners in the field of water resources, hydrology, environmental resources, agricultural engineering, watershed management, earth sciences, as well as those engaged in natural resources planning and management. Graduate students and those wishing to conduct further research in water and environment and their development and management find the book to be of value.

This book carefully considers hydrological models which are essential for predicting floods, droughts, soil moisture estimation, land use change detection, geomorphology and water structures. The book highlights recent advances in the area of hydrological modelling in the Ganga Basin and other internationally important river basins. The impact of climate change on water resources is a global concern. Water resources in many countries are already stressed, and climate change along with burgeoning population, rising standard of living and increasing demand are adding to the stress. Furthermore, river basins are becoming less resilient to climatic vagaries. Fundamental to addressing these issues is hydrological modelling which is covered in this book. Integrated water resources management is vital to ensure water and food security. Integral to the management is groundwater and solute transport, and this book encompasses tools that will be useful to mitigate the adverse consequences of natural disasters.

This book explores a new realm in data-based modeling with applications to hydrology. Pursuing a case study approach, it presents a rigorous evaluation of state-of-the-art input selection methods on the basis of detailed and comprehensive experimentation and comparative studies that employ emerging hybrid techniques for modeling and analysis. Advanced computing offers a range of new options for hydrologic modeling with the help of mathematical and data-based approaches like wavelets, neural networks, fuzzy logic, and support vector machines. Recently machine learning/artificial intelligence techniques have come to be used for time series modeling. However, though initial studies have shown this approach to be effective, there are still concerns about their accuracy and ability to make predictions on a selected input space.

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.

A practical introduction on today's challenge of controlling and managing the water resources used by and affected by cities and urbanized communities. The book offers an integrated engineering approach, covering the spectrum of urban watershed management, urban hydraulic systems, and overall stormwater management. Each chapter concludes with helpful problems. Solutions Manual available to qualified professors and instructors upon request. Introduces the reader to two popular, non-proprietary computer-modeling pro-grams: HEC-HMS (U.S. Army Corps of Engineers) and SWMM (U.S EPA).

In recent years, the continued technological advances have led to the spread of low-cost sensors and devices supporting crowdsourcing as a way to obtain observations of hydrological variables in a more distributed way than the classic static physical sensors. The main advantage of using these type of sensors is that they can be used not only by technicians but also by regular citizens. However, due to their relatively low reliability and varying accuracy in time and space, crowdsourced observations have not been widely integrated in hydrological and/or hydraulic models for flood forecasting applications. Instead, they have generally been used to validate model results against observations, in post-event analyses. This research aims to investigate the benefits of assimilating the crowdsourced observations, coming from a distributed network of heterogeneous physical and social (static and dynamic) sensors, within hydrological and hydraulic models, in order to improve flood forecasting. The results of this study demonstrate that crowdsourced observations can significantly improve flood prediction if properly integrated in hydrological and hydraulic models. This study provides technological support to citizen observatories of water, in which citizens not only can play an active role in information capturing, evaluation and communication, leading to improved model forecasts and better flood management.

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.