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1. 5 REFERENCES 127 7 DIGITAL TERRAIN 129 1. 1 INTRODUCTION 129 1. 2 DRAINAGE NETWORK 130 1. 3 DEFINITION OF CHANNEL NETWORKS 135 1. 4 RESOLUTION DEPENDENT EFFECTS 138 1. 5 CONSTRAINING DRAINAGE DIRECTION 141 1. 6 SUMMARY 145 1. 7 REFERENCES 146 8 PRECIPITATION MEASUREMENT 149 1. 1 INTRODUCTION 149 1. 2 RAIN GAUGE ESTIMATION OF RAINFALL 151 ADAR STIMATION OF RECIPITATION 1. 3 R E P 155 1. 4 WSR-88D RADAR CHARACTERISTICS 167 1. 5 INPUT FOR HYDROLOGIC MODELING 172 1. 6 SUMMARY 174 1. 7 REFERENCES 175 9 FINITE ELEMENT MODELING 177 1. 1 INTRODUCTION 177 1. 2 MATHEMATICAL FORMULATION 182 1. 3 SUMMARY 194 1. 4 REFERENCES 195 10 DISTRIBUTED MODEL CALIBRATION 197 1. 1 INTRODUCTION 197 1. 2 CALIBRATION APPROACH 199 1. 3 DISTRIBUTED MODEL CALIBRATION 201 1. 4 AUTOMATIC CALIBRATION 208 1. 5 SUMMARY 214 1. 6 REFERENCES 214 11 DISTRIBUTED HYDROLOGIC MODELING 217 1. 1 INTRODUCTION 218 1. 2 CASE STUDIES 218 1. 3 SUMMARY 236 1. 4 REFERENCES 237 12 HYDROLOGIC ANALYSIS AND PREDICTION 239 1. 1 INTRODUCTION 239 x Distributed Hydrologic Modeling Using GIS 1. 2 VFLOTM EDITIONS 241 1. 3 VFLOTM FEATURES AND MODULES 242 1. 4 MODEL FEATURE SUMMARY 245 1. 5 VFLOTM REAL-TIME 256 1. 6 DATA REQUIREMENTS 258 1. 7 RELATIONSHIP TO OTHER MODELS 259 1. 8 SUMMARY 260 1.
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.
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.
This book offers a unique collection of inter- and multidisciplinary studies on river systems. Rivers have been the prime source of sustenance since the advent of civilization and river systems often form the basis for agriculture, transport, water, and land for domestic, commercial, and industrial activities, fostering economic prosperity. A river basin is a basic geographical and climatological unit within which the vagaries of natural processes act and manifest themselves at different spatio-temporal scales. Even if compared side-by-side, no two river basins respond to natural processes in the same way and thus, it has long been recognized that each river basin is unique. Hence, any developmental activity or conservation effort has to be designed and implemented to match each unique river basin. With the burgeoning population and increasing dependency on natural resources, understanding and maintaining river systems has become increasingly important. This book provides a varied reference work on and unprecedented guidelines for conducting and implementing research on river basins, and for managing their ecological development.
Information technology and its convergence issue is emerging rapidly as an exciting new paradigm with user-centric environment to provide computing and communication services. This area will be the most comprehensive topics with various aspects of advances in information technology and its convergence services. This book covers all topics as computational science and applications, electronics engineering, manufacturing technology, services, technical skill to control the robot, automatic operation and application, simulation and testing communication and many more.
The efficiency of a probabilistic hydrological forecasting system with weather radar and the Probability distributed hydrological model (PDM) was evaluated at the Brue catchment; south-western England. The ability of the radar to measure gauged precipitation in 2007 (regarded as the ground truth) was evaluated using Normalized Bias (NB) and Normalized Error (NE) statistics as the objective function of evaluation. The radar overestimated precipitation measurements by average gauges with NB value of 0.41 and a considerably low NE of 0.68. Furthermore, the effectiveness of a Deterministic nowcasting system (DNS) to forecast radar measured precipitation at 132 forecast time series of 6hrs forecast lead time was assessed. The DNS overestimated the radar measured precipitation with a NB value of 87% and recorded an accumulated NE of 146%. Moreover, the efficiencies of 10 ensemble precipitation forecats generated from a Stochastic nowcasting system (SNS) over the singular deterministic forecasts from the DNS was evaluated at 3 major hydrological events. Some of the ensembles significantly performed better than the deterministic forecast and brilliantly captured the radar measured precipitation at most of the forecast time series. Furthermore, the efficiencies of these sources of precipitation measurement to simulate flows with the PDM at the Brue catchment were also assessed by integrating the radar-based forecasts with measurements from average gauges. The PDM performed satisfactorily well in simulating the flows of 17th January 2007 with an average Nash–Sutcliffe Efficiency Index (NSE) of 0.65 and the model was judged insensitive to the significantly high precipitation inputs for the hydrological event of 27th of May 2007. However, the PDM performed poorly in simulating flows for the historical storms of 20th of July 2007; with the model under estimating flows with bias value of over 250 cumecs for an event popular for its devastating flooding in the Southwest of England. The model inadequacies was however associated to poor radar precipitation measurements and forecasts on which flow simulation was based. This work therefore emphasis the need for developments in hydrological modeling as well as advancement in weather radar technology to effectively correct radar errors due to radar calibration, signal attenuation, clutter and anomalous propagation, vertical variation of reflectivity, range effects, Z-R relationships, variations of drop size distributions, vertical air motions, beam overshooting the shallow precipitation and sampling issues, that has been identified to affect radar measurements.