GIS and Geocomputation for Water Resource Science and Engineering.

Cover -- Title Page -- Copyright -- Contents -- Preface -- About the Companion Website -- List of Acronyms -- Part 1 GIS, Geocomputation, and GIS Data -- Chapter 1 Introduction -- 1.1 What is geocomputation? -- 1.2 Geocomputation and water resources science and engineering -- 1.3 GIS-enabled geocomputation in water resources science and engineering -- 1.4 Why should water resources engineers and scientists study GIS -- 1.5 Motivation and organization of this book -- 1.6 Concluding remarks -- References -- Chapter 2 A Brief History of GIS and Its Use in Water Resources Engineering -- 2.1 Introduction -- 2.2 Geographic Information Systems (GIS)-software and hardware -- 2.3 Remote sensing and global positioning systems and development of GIS -- 2.4 History of GIS in water resources applications -- 2.5 Recent trends in GIS -- 2.6 Benefits of using GIS in water resources engineering and science -- 2.7 Challenges and limitations of GIS-based approach to water resources engineering -- 2.7.1 Limitation 1: incompatibilities between real-world and GIS modeled systems -- 2.7.2 Limitation 2: inability of GIS to effectively handle time dimension -- 2.7.3 Limitation 3: subjectivity arising from the availability of multiple geoprocessing tools -- 2.7.4 Limitation 4: ground-truthing and caution against extrapolation -- 2.7.5 Limitation 5: crisp representation of fuzzy geographic boundaries -- 2.7.6 Limitation 6: dynamic rescaling of maps and intrinsic resampling operations by GIS software -- 2.7.7 Limitation 7: inadequate or improper understanding of scale and resolution of the datasets -- 2.7.8 Limitation 8: limited support for handling of advanced mathematical algorithms -- 2.8 Concluding remarks -- References -- Chapter 3 Hydrologic Systems and Spatial Datasets -- 3.1 Introduction -- 3.2 Hydrological processes in a watershed.

3.3 Fundamental spatial datasets for water resources planning: management and modeling studies -- 3.3.1 Digital elevation models (DEMs) -- 3.4 Sources of data for developing digital elevation models -- 3.4.1 Accuracy issues surrounding digital elevation models -- 3.5 Sensitivity of hydrologic models to DEM resolution -- 3.5.1 Land use and land cover (LULC) -- 3.5.2 Sources of data for developing digital land use land cover maps -- 3.6 Accuracy issues surrounding land use land cover maps -- 3.6.1 Anderson classification and the standardization of LULC mapping -- 3.7 Sensitivity of hydrologic models to LULC resolution -- 3.7.1 LULC, impervious surface, and water quality -- 3.7.2 Soil datasets -- 3.8 Sources of data for developing soil maps -- 3.9 Accuracy issues surrounding soil mapping -- 3.10 Sensitivity of hydrologic models to soils resolution -- 3.11 Concluding remarks -- References -- Chapter 4 Water-Related Geospatial Datasets -- 4.1 Introduction -- 4.2 River basin, watershed, and subwatershed delineations -- 4.3 Streamflow and river stage data -- 4.4 Groundwater level data -- 4.5 Climate datasets -- 4.6 Vegetation indices -- 4.7 Soil moisture mapping -- 4.7.1 Importance of soil moisture in water resources applications -- 4.7.2 Methods for obtaining soil moisture data -- 4.7.3 Remote sensing methods for soil moisture assessments -- 4.7.4 Role of GIS in soil moisture modeling and mapping -- 4.8 Water quality datasets -- 4.9 Monitoring strategies and needs -- 4.10 Sampling techniques and recent advancements in sensing technologies -- 4.11 Concluding remarks -- References -- Chapter 5 Data Sources and Models -- 5.1 Digital data warehouses and repositories -- 5.2 Software for GIS and geocomputations -- 5.3 Software and data models for water resources applications -- 5.4 Concluding remarks -- References -- Part 2 Foundations of GIS.

Chapter 6 Data Models for GIS -- 6.1 Introduction -- 6.2 Data types, data entry, and data models -- 6.2.1 Discrete and continuous data -- 6.3 Categorization of spatial datasets -- 6.3.1 Raster and vector data structures -- 6.3.2 Content-based data classification -- 6.3.3 Data classification based on measurement levels -- 6.3.4 Primary and derived datasets -- 6.3.5 Data entry for GIS -- 6.3.6 GIS data models -- 6.4 Database structure, storage, and organization -- 6.4.1 What is a relational data structure? -- 6.4.2 Attribute data and tables -- 6.4.3 Geodatabase -- 6.4.4 Object-oriented database -- 6.5 Data storage and encoding -- 6.6 Data conversion -- 6.7 Concluding remarks -- References -- Chapter 7 Global Positioning Systems (GPS) and Remote Sensing -- 7.1 Introduction -- 7.2 The global positioning system (GPS) -- 7.3 Use of GPS in water resources engineering studies -- 7.4 Workflow for GPS data collection -- 7.4.1 12 Steps to effective GPS data collection and compilation -- 7.5 Aerial and satellite remote sensing and imagery -- 7.5.1 Low-resolution imagery -- 7.5.2 Medium-resolution imagery -- 7.5.3 High-resolution imagery -- 7.6 Data and cost of acquiring remotely sensed data -- 7.7 Principles of remote sensing -- 7.8 Remote sensing applications in water resources engineering and science -- 7.9 Bringing remote sensing data into GIS -- 7.9.1 Twelve steps for integration of remotely sensed data into GIS -- 7.10 Concluding remarks -- References -- Chapter 8 Data Quality, Errors, and Uncertainty -- 8.1 Introduction -- 8.2 Map projection, datum, and coordinate systems -- 8.3 Projections in GIS software -- 8.4 Errors, data quality, standards, and documentation -- 8.5 Error and uncertainty -- 8.6 Role of resolution and scale on data quality -- 8.7 Role of metadata in GIS analysis -- 8.8 Concluding remarks -- References.

Chapter 9 GIS Analysis: Fundamentals of Spatial Query -- 9.1 Introduction to spatial analysis -- 9.2 Querying operations in GIS -- 9.2.1 Spatial query -- 9.3 Structured query language (SQL) -- 9.4 Raster data query by cell value -- 9.5 Spatial join and relate -- 9.6 Concluding remarks -- References -- Chapter 10 Topics in Vector Analysis -- 10.1 Basics of geoprocessing (buffer, dissolve, clipping, erase, and overlay) -- 10.1.1 Buffer -- 10.1.2 Dissolve, clip, and erase -- 10.1.3 Overlay -- 10.2 Topology and geometric computations (various measurements) -- 10.2.1 Length and distance measurements -- 10.2.2 Area and perimeter-to-area ratio (PAR) calculations -- 10.3 Proximity and network analysis -- 10.3.1 Proximity -- 10.3.2 Network analysis -- 10.4 Concluding remarks -- References -- Chapter 11 Topics in Raster Analysis -- 11.1 Topics in raster analysis -- 11.2 Local operations -- 11.2.1 Local operation with a single raster -- 11.2.2 Local operation with multiple rasters -- 11.2.3 Map algebra for geocomputation in water resources -- 11.3 Reclassification -- 11.4 Zonal operations -- 11.4.1 Identification of regions and reclassification -- 11.4.2 Category-wide overlay -- 11.5 Calculation of area, perimeter, and shape -- 11.6 Statistical operations -- 11.7 Neighborhood operations -- 11.7.1 Spatial aggregation analysis -- 11.7.2 Filtering -- 11.7.3 Computation of slope and aspect -- 11.7.4 Resampling -- 11.8 Determination of distance, proximity, and connectivity in raster -- 11.9 Physical distance and cost distance analysis -- 11.9.1 Cost surface analysis -- 11.9.2 Allocation and direction analysis -- 11.9.3 Path analysis -- 11.10 Buffer analysis in raster -- 11.11 Viewshed analysis -- 11.12 Raster data management (mask, spatial clip, and mosaic) -- 11.13 Concluding remarks -- References -- Chapter 12 Terrain Analysis and Watershed Delineation.

12.1 Introduction -- 12.1.1 Contouring -- 12.1.2 Hill shading and insolation -- 12.1.3 Perspective view -- 12.1.4 Slope and aspect -- 12.1.5 Surface curvature -- 12.2 Topics in watershed characterization and analysis -- 12.2.1 Watershed delineation -- 12.2.2 Critical considerations during watershed delineation -- 12.3 Concluding remarks -- References -- Part 3 Foundations of Modeling -- Chapter 13 Introduction to Water Resources Modeling -- 13.1 Mathematical modeling in water resources engineering and science -- 13.2 Overview of mathematical modeling in water resources engineering and science -- 13.3 Conceptual modeling: phenomena, processes, and parameters of a system -- 13.4 Common approaches used to develop mathematical models in water resources engineering -- 13.4.1 Data-driven models -- 13.4.2 Physics-based models -- 13.4.3 Expert-driven or stakeholder-driven models -- 13.5 Coupling mathematical models with GIS -- 13.5.1 Loose coupling of GIS and mathematical models -- 13.5.2 Tight coupling of GIS and mathematical models -- 13.5.3 What type of coupling to pursue? -- 13.6 Concluding remarks -- References -- Chapter 14 Water Budgets and Conceptual Models -- 14.1 Flow modeling in a homogeneous system (boxed or lumped model) -- 14.2 Flow modeling in heterogeneous systems (control volume approach) -- 14.3 Conceptual model: soil conservation survey curve number method -- 14.4 Fully coupled watershed-scale water balance model: soil water assessment tool (SWAT) -- 14.5 Concluding remarks -- References -- Chapter 15 Statistical and Geostatistical Modeling -- 15.1 Introduction -- 15.2 Ordinary least squares (OLS) linear regression -- 15.3 Logistic regression -- 15.4 Data reduction and classification techniques -- 15.5 Topics in spatial interpolation and sampling -- 15.5.1 Local area methods -- 15.5.2 Spline interpolation method -- 15.5.3 Thiessen polygons.

15.5.4 Density estimation.

Description based on publisher supplied metadata and other sources.

Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.