Volume II of Geospatial Information Handbook for Water Resources and Watershed Management discusses Geospatial Technology (GT) approaches using integrated modeling as applied to advanced water resource assessments. Features include multiple date land cover analyses as change in land cover influences water quality, model sensitivity analyses of DEM resolution and influences on modeling water characteristics like Manning’s n, development of seabed cover classification and sensitivity, and forecasting urban growth over time with climate vulnerability impacts on water. A detailed case study presents a range of water quality issues, all effectively demonstrating GT inputs to water quality studies from headwaters to receiving estuarine waters. Also analyzed are the comparison of evapotranspiration simulation performance by APEX model in dryland and irrigated cropping systems and perspectives on the future of transient storage modeling.
- Captures advanced technologies and applications for implementation with models to address a broad spectrum of water issues
- Provides real-world applications and case studies using advanced spectral and spatial sensors combined with geospatially facilitated water process models
- Features a Neuse River Basin case study integrating hydrologic methods and modeling along with remote sensing and GIS technologies for nonpoint source water quality evaluations
- Global coverage with applications demonstrated by more than 170 experts from around the world
This handbook is a wide-ranging and contemporary reference of advanced geospatial techniques used in numerous practical applications at the local and regional scale and is an in-depth resource for professionals and the water research community worldwide.
Author(s): John G. Lyon, Lynn Lyon
Publisher: CRC Press
Year: 2022
Language: English
Pages: 275
City: Boca Raton
Cover
Half Title
Title Page
Copyright Page
Table of Contents
Editors
Contributors
1. Introduction to Volume II and Neuse River Watershed and Water Quality Case Study
History
Traditional Approaches Augmented
Building Spatial Datasets
Spatial Positioning
Spectral Resolution
Scaling and Modeling
Deterministic Modeling
Verification
Applications
2. Neuse Case Study and Water Quality–Related Methods
Neuse River Watershed and Water Quality Case Study
Volume II, Chapter 3, Ground Truthing Land Cover (LULC)
Volume II, Chapter 4, Land Cover Dynamics and Accuracy of Indices
Volume II, Chapter 5, Multiple Sensor Land Cover Changes
Volume II, Chapter 6 Land Cover Change via High-Frequency Monitoring
Volume II, Chapter 7 Land Cover and Nitrogen Compound Watershed Modeling
Volume II, Chapter 8, Downstream Transport and Fate
Volume II, Chapter 9, DEM Sensitivity Analyses
Volume II, Chapter 10 Forecasting Land Cover Change
Volume II, Chapter 11, Sensitivity Analysis of Seabed Covers
3. Virtual Field Reference Database for Assessment of Land Cover Data and Variability
Introduction and Background
Study Area
Methods
Sampling Frame Design
Field Sampling Protocol
Location and Time
Physical Measurements
Biophysical Measurements
Digital Photographic Documentation
Quality Assurance and Quality Control
Database Design and Functionality
Data Entry
Quality Control
Data Display and Distribution
Results
Conclusions
Acknowledgments
References
4. Vegetation Dynamics and Identification of Land Cover Change in a Complex Land Use Community
Introduction
Background
Study Site
Study Objectives
Methods
Data Preprocessing
Calibration Reference Data Set Development
NDVI Change Analysis
MID Change Analysis
Accuracy Assessment of Change Detection Images
Results
Discussion
Conclusions
Acknowledgments
References
5. Land-Cover Change Detection Using Multi-Temporal MODIS NDVI Data
Introduction
Background
Study Objectives
Study Area
Methods
Accuracy Assessment
Results
NDVI Profiles
Change Detection
Discussion
Conclusions
Acknowledgments
References
6. Spectral and GIS Rule-Based Land-Cover Classification in the Neuse River
Introduction
Study Area
Methods
Initial Classification
Sub-Level Classifications
Agriculture and Herbaceous
Wetland and Water
Urban (Impervious)
Spectrally Inseparable Areas
Final Data Processing
Accuracy Assessment
Sampling Frame Design
Results
Reference Data Variability
Accuracy Assessment
Discussion
LC Classification
Accuracy Assessment
Conclusions
Acknowledgments
References
7. Modeling the Distribution of Diffuse Nitrogen Sources and Sinks in the Neuse River Basin
Introduction
Study Overview
Study Area
Methods
Land-Cover Classification
Mass Balance Modeling
Hydrologic Modeling
Surface Runoff
Percolation and Subsurface Runoff
Evapotranspiration
Transported Nitrogen
Denitrification
Results
Land-Cover Products
Model Performance
Modeling Products
Model Comparisons
Discussion
Conclusions
Acknowledgments
References
8. Monitoring of Water Colorants Using AVIRIS Hyperspectral Sensing
Introduction
Study Area
Study Objectives
Methods
Imagery Collection
Field Data
Atmospheric Corrections
Sun Glint
Water Vapor and Aerosol Corrections
Chl a
SeaWiFS Algorithms
CDOM and TSS
Results
Chl a
CDOM, TSS, and FSS
Spatial Patterns and Distributions
Discussion
Conclusions
Acknowledgments
References
9. DEM Resolution and Roughness Effect in Relation to Model Performance
Introduction and Background
Study Areas and Data Used
Methods
DEM Data Processing
Hydraulic Simulations and Ensemble Modeling
Model Performance Quantification
Volume Estimation
Results
Overall Performance Results
Variation in Sizes of Overlap, Over- and Underestimation, and Disparities as Separate Effect of DEM and Manning's n Used
Comparison of Cross-Sectional Profiles and Water Surface Elevations
Maximum Depth and Total Volume Variations as Separate Effects of DEM and Manning's n
Conclusions
Acknowledgments
References
10. Application of Densely Stacked Satellite Image Classification and Multinomial Logistic Regression Analysis in Predicting Urban Sprawl
Introduction
GIS Based CA-MARKOV Chain Model
Identification of Causative Factors
Design Methodology to Identify the Relationship between Causative Factors and Built-up Pixels
Data Acquisition
Identification of Built-up Pixels
Accuracy Assessment
Selection of the Causative Factors
Statistical Analysis of Causative Factors vs. Built-up Pixels
CA-Markov Chain Model Run for Decadal Prediction
Variation of Built-up Area Till the Year 2020 Using Supervised Classification Algorithm
Predicted Urban Sprawl from 2020 to 2050
Resultant Changes in the Range of Urban Sprawl
Significant Findings
Acknowledgment
References
11. A Feasibility Study of Seabed Cover Classification Standards
Introduction
Evaluation of SNI 7987–2014
Evaluation of Prototype Feasibility
How to Determine the Seabed Cover Map Custodian?
Conclusions and Recommendations
Acknowledgment
References
Index
