GIS and Geocomputation for Water Resource Science and Engineering
GIS and Geocomputation for Water Resource Science and Engineering
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Author(s): Dixon, Barnali
Ray, Chittaranjan
ISBN No.: 9781118826171
Pages: 568
Year: 201603
Format: E-Book
Price: $ 238.67
Dispatch delay: Dispatched between 7 to 15 days
Status: Available

Preface xiii About the Companion Website xv List of Acronyms xvii Part I GIS, Geocomputation, and GIS Data 1 1 Introduction 3 1.1 What is geocomputation? 3 1.2 Geocomputation and water resources science and engineering 4 1.3 GIS-enabled geocomputation in water resources science and engineering 5 1.4 Why should water resources engineers and scientists study GIS 5 1.5 Motivation and organization of this book 6 1.6 Concluding remarks 7 References 9 2 A Brief History of GIS and Its Use in Water Resources Engineering 11 2.1 Introduction 11 2.


2 Geographic Information Systems (GIS) - software and hardware 11 2.3 Remote sensing and global positioning systems and development of GIS 12 2.4 History of GIS in water resources applications 13 2.5 Recent trends in GIS 19 2.6 Benefits of using GIS in water resources engineering and science 20 2.7 Challenges and limitations of GIS-based approach to water resources engineering 20 2.8 Concluding remarks 23 References 25 3 Hydrologic Systems and Spatial Datasets 27 3.1 Introduction 27 3.


2 Hydrological processes in a watershed 27 3.3 Fundamental spatial datasets for water resources planning: management and modeling studies 28 3.4 Sources of data for developing digital elevation models 30 3.4.1 Accuracy issues surrounding digital elevation models 30 3.5 Sensitivity of hydrologic models to DEM resolution 31 3.6 Accuracy issues surrounding land use land cover maps 32 3.7 Sensitivity of hydrologic models to LULC resolution 34 3.


8 Sources of data for developing soil maps 36 3.9 Accuracy issues surrounding soil mapping 37 3.10 Sensitivity of hydrologic models to soils resolution 38 3.11 Concluding remarks 43 References 44 4 Water-Related Geospatial Datasets 47 4.1 Introduction 47 4.2 River basin, watershed, and subwatershed delineations 47 4.3 Streamflow and river stage data 48 4.4 Groundwater level data 48 4.


5 Climate datasets 48 4.6 Vegetation indices 49 4.7 Soil moisture mapping 49 4.8 Water quality datasets 51 4.9 Monitoring strategies and needs 51 4.10 Sampling techniques and recent advancements in sensing technologies 52 4.11 Concluding remarks 53 References 53 5 Data Sources and Models 55 5.1 Digital data warehouses and repositories 55 5.


2 Software for GIS and geocomputations 55 5.3 Software and data models for water resources applications 59 5.4 Concluding remarks 60 References 60 Part II Foundations of GIS 61 6 Data Models for GIS 63 6.1 Introduction 63 6.2 Data types, data entry, and data models 63 6.2.1 Discrete and continuous data 63 6.3 Categorization of spatial datasets 65 6.


4 Database structure, storage, and organization 71 6.5 Data storage and encoding 75 6.6 Data conversion 76 6.7 Concluding remarks 78 References 80 7 Global Positioning Systems (GPS) and Remote Sensing 81 7.1 Introduction 81 7.2 The global positioning system (GPS) 81 7.3 Use of GPS in water resources engineering studies 82 7.4 Workflow for GPS data collection 83 7.


5 Aerial and satellite remote sensing and imagery 83 7.6 Data and cost of acquiring remotely sensed data 84 7.7 Principles of remote sensing 85 7.8 Remote sensing applications in water resources engineering and science 88 7.9 Bringing remote sensing data into GIS 91 7.10 Concluding remarks 94 References 95 8 Data Quality, Errors, and Uncertainty 97 8.1 Introduction 97 8.2 Map projection, datum, and coordinate systems 97 8.


3 Projections in GIS software 101 8.4 Errors, data quality, standards, and documentation 102 8.5 Error and uncertainty 106 8.6 Role of resolution and scale on data quality 107 8.7 Role of metadata in GIS analysis 109 8.8 Concluding remarks 109 References 109 9 GIS Analysis: Fundamentals of Spatial Query 111 9.1 Introduction to spatial analysis 111 9.2 Querying operations in GIS 116 9.


2.1 Spatial query 116 9.3 Structured query language (SQL) 119 9.4 Raster data query by cell value 122 9.5 Spatial join and relate 125 9.6 Concluding remarks 128 References 128 10 Topics in Vector Analysis 129 10.1 Basics of geoprocessing (buffer, dissolve, clipping, erase, and overlay) 129 10.2 Topology and geometric computations (various measurements) 137 10.


3 Proximity and network analysis 143 10.4 Concluding remarks 145 References 147 11 Topics in Raster Analysis 149 11.1 Topics in raster analysis 149 11.2 Local operations 149 11.3 Reclassification 155 11.4 Zonal operations 157 11.5 Calculation of area, perimeter, and shape 163 11.6 Statistical operations 164 11.


7 Neighborhood operations 165 11.8 Determination of distance, proximity, and connectivity in raster 167 11.9 Physical distance and cost distance analysis 169 11.10 Buffer analysis in raster 174 11.11 Viewshed analysis 175 11.12 Raster data management (mask, spatial clip, and mosaic) 178 11.13 Concluding remarks 179 References 181 12 Terrain Analysis and Watershed Delineation 183 12.1 Introduction 183 12.


2 Topics in watershed characterization and analysis 191 12.3 Concluding remarks 200 References 200 Part III Foundations of Modeling 203 13 Introduction to Water Resources Modeling 205 13.1 Mathematical modeling in water resources engineering and science 205 13.2 Overview of mathematical modeling in water resources engineering and science 206 13.3 Conceptual modeling: phenomena, processes, and parameters of a system 206 13.4 Common approaches used to develop mathematical models in water resources engineering 206 13.5 Coupling mathematical models with GIS 209 13.6 Concluding remarks 210 References 211 14 Water Budgets and Conceptual Models 213 14.


1 Flow modeling in a homogeneous system (boxed or lumped model) 213 14.2 Flow modeling in heterogeneous systems (control volume approach) 215 14.3 Conceptual model: soil conservation survey curve number method 217 14.4 Fully coupled watershed-scale water balance model: soil water assessment tool (SWAT) 218 14.5 Concluding remarks 219 References 220 15 Statistical and Geostatistical Modeling 221 15.1 Introduction 221 15.2 Ordinary least squares (OLS) linear regression 221 15.3 Logistic regression 222 15.


4 Data reduction and classification techniques 223 15.5 Topics in spatial interpolation and sampling 223 15.6 Geostatistical Methods 227 15.7 Kriging 230 15.8 Critical issues in interpolation 231 15.9 Concluding remarks 232 References 234 16 Decision Analytic and Information Theoretic Models 235 16.1 Introduction 235 16.2 Decision analytic models 235 16.


3 Information theoretic approaches 238 16.4 Spatial data mining (SDM) for knowledge discovery in a database 245 16.5 The trend of temporal data modeling in GIS 245 16.6 Concluding remarks 246 References 246 17 Considerations for GIS and Model Integration 249 17.1 Introduction 249 17.2 An overview of practical considerations in adopting and integrating GIS into water resources projects 250 17.3 Theoretical considerations related to GIS and water resources model integration 251 17.4 Concluding remarks 256 References 257 18 Useful Geoprocessing Tasks While Carrying Out Water Resources Modeling 259 18.


1 Introduction 259 18.2 Getting all data into a common projection 259 18.3 Adding point (X, Y) data and calculating their projected coordinates 260 18.4 Image registration and rectification 264 18.5 Editing tools to transfer information to vectors 266 18.6 GIS for cartography and visualization 270 18.7 Concluding remarks 271 References 271 19 Automating Geoprocessing Tasks in GIS 273 19.1 Introduction 273 19.


2 Object-oriented programming paradigm 273 19.3 Vectorized (array) geoprocessing 274 19.4 Making nongeographic attribute calculations 274 19.5 Using ModelBuilder to automate geoprocessing tasks 279 19.6 Using Python scripting for geoprocessing 287 19.7 Introduction to some useful Python constructs 288 19.8 ArcPy geoprocessing modules and site-package 289 19.9 Learning Python and scripting with ArcGIS 289 19.


10 Concluding remarks 290 References 291 Part IV Illustrative Case Studies 293 A Preamble to Case Studies 295 20 Watershed Delineation 297 20.1 Introduction 297 20.2 Background 297 20.3 Methods 298 20.4 Concluding remarks 311 References 311 21 Loosely Coupled Hydrologic Model 313 21.1 Introduction 313 21.2 Study area 313 21.3 Methods 314 21.


4 Results and discussions 318 21.5 Conclusions 323 Acknowledgment 324 References 324 22 Watershed Characterization 325 22.1 Introduction 325 22.2 Background 325 22.3 Approach 326 22.4 Summary and conclusions 332 References 345 23 Tightly Coupled Mod.


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