GEO 327G Semester Project. Urbanization in the Onion Creek Watershed

Similar documents
Urbanization factors in the Gilleland Creek watershed, Travis County, Texas. Michael Kanarek GEO386G Final Project Dec. 2, 2011

GIS Final Project Determining Regions of Anthropogenic Recharge

Protocol for Prioritizing Conservation Opportunity Areas in Centre County and Clinton County

Effects of Rising Sea Levels on Coral Reef and Mangrove Distributions along the Great Barrier Reef in Australia

Land Cover Data Processing Land cover data source Description and documentation Download Use Use

Delineation of high landslide risk areas as a result of land cover, slope, and geology in San Mateo County, California

Geo 327G Semester Project. Landslide Suitability Assessment of Olympic National Park, WA. Fall Shane Lewis

Exercise 6: Working with Raster Data in ArcGIS 9.3

Calhoun County, Texas Under 5 Meter Sea Level Rise

Getting Started. Start ArcMap by opening up a new map.

Determining the Location of the Simav Fault

LANDSLIDE HAZARD ANALYSIS AND ITS EFFECT ON ENDANGERED SPECIES HABITATS, GRAND COUNTY, UTAH

Erosion Susceptibility in the area Around the Okanogan Fire Complex, Washington, US

Raster Analysis: An Example

Goodbye Galveston. The Effects of Rising Sea Level on the. Coast of Galveston, TX. Maria Reistroffer GEO 327G

COMMON GIS TECHNIQUES FOR VECTOR AND RASTER DATA PROCESSING. Ophelia Wang, Department of Geography and the Environment, University of Texas

Creating Watersheds from a DEM

Preparing a NFIE-Geo Database for Travis County

HEC & GIS Modeling of the Brushy Creek HEC & GIS Watershed Modeling of the

Tutorial 8 Raster Data Analysis

Classification of Erosion Susceptibility

Abstract: Contents. Literature review. 2 Methodology.. 2 Applications, results and discussion.. 2 Conclusions 12. Introduction

Raster Analysis; A Yellowstone Example 10/24/2013. M. Helper GEO327G/386G, UT Austin 2. M. Helper GEO327G/386G, UT Austin 4

Raster Analysis; A Yellowstone Example 3/29/2018

Raster Analysis: An Example

Analysis of Sulfate and Chloride Concentrations

Analysis of Change in Land Use around Future Core Transit Corridors: Austin, TX, Eric Porter May 3, 2012

Hazard Assessment of Lava Flows, Wildfires, and Tsunamis on the Big Island of Hawaii s population. By: Thomas Ditges

Sea Level Scare in South Carolina. by William Witmer GEO 327G 5 December 2016

Introduction. Purpose

Predictive Modelling of Ag, Au, U, and Hg Ore Deposits in West Texas Carl R. Stockmeyer. December 5, GEO 327G

Fire Susceptibility Analysis Carson National Forest New Mexico. Can a geographic information system (GIS) be used to analyze the susceptibility of

The Looming Threat of Rising Sea Levels to the Florida Keys

Final Group Project Paper. Where Should I Move: The Big Apple or The Lone Star State

In this exercise we will learn how to use the analysis tools in ArcGIS with vector and raster data to further examine potential building sites.

SPATIAL MODELING GIS Analysis Winter 2016

Huron Creek Watershed 2005 Land Use Map

Watershed Analysis of the Blue Ridge Mountains in Northwestern Virginia

Within this document, the term NHDPlus is used when referring to NHDPlus Version 2.1 (unless otherwise noted).

Designing a Dam for Blockhouse Ranch. Haley Born

Water Volume Calculation of Hill Country Trinity Aquifer Blanco, Hays, and Travis Counties, Central Texas

How to Create Stream Networks using DEM and TauDEM

Using ArcGIS for Hydrology and Watershed Analysis:

Effects of sea level rise on shallow atolls in the South Pacific

GIS IN ECOLOGY: ANALYZING RASTER DATA

Creating Watersheds from a DEM in ArcGIS 9.x

caused displacement of ocean water resulting in a massive tsunami. II. Purpose

Sea Level Rise and Manhattan

Civil Engineering 394K: Topic 3 Geographic Information Systems (GIS) in Water Resources Engineering FALL 2014

Watershed Delineation

Determination of Urban Runoff Using ILLUDAS and GIS

Using the Stock Hydrology Tools in ArcGIS

The University of Texas at Austin. Icebox Model Projections for Sea Level Fall in the Gulf Coast and Caribbean Sea Region

Title: ArcMap: Calculating Soil Areas for Storm Water Pollution Prevention Plans Authors: Brandy Woodcock, Benjamin Byars

GRAPEVINE LAKE MODELING & WATERSHED CHARACTERISTICS

Hydrology and Watershed Analysis

Hennepin GIS. Tree Planting Priority Areas - Analysis Methodology. GIS Services April 2018 GOAL:

GIS Level 2. MIT GIS Services

GIS 2010: Coastal Erosion in Mississippi Delta

Glaciers of Mt. Baker. Mt. Baker is located in Mt. Baker National for in the North West part of Washington. There are

Lab#8: Working With Geodatabases. create a geodatabase with feature datasets, tables, raster datasets, and raster catalogs

AN ASSESSMENT OF THE IMPACT OF RETENTION PONDS

GIS Semester Project Working With Water Well Data in Irion County, Texas

Software requirements * :

Vector Analysis: Farm Land Suitability Analysis in Groton, MA

Identifying Wildfire Risk Areas in Western Washington State

Leon Creek Watershed October 17-18, 1998 Rainfall Analysis Examination of USGS Gauge Helotes Creek at Helotes, Texas

A GIS-based Approach to Watershed Analysis in Texas Author: Allison Guettner

Exercise 2. Building a Base Dataset of the San Marcos Basin

Acknowledgments xiii Preface xv. GIS Tutorial 1 Introducing GIS and health applications 1. What is GIS? 2

Outline. Chapter 1. A history of products. What is ArcGIS? What is GIS? Some GIS applications Introducing the ArcGIS products How does GIS work?

Outcrop suitability analysis of blueschists within the Dry Lakes region of the Condrey Mountain Window, North-central Klamaths, Northern California

Using Ice Thickness and Bed Topography to Pick Field Sites Near Swiss Camp, Greenland

Learning Unit Student Guide. Title: Estimating Areas of Suitable Grazing Land Using GPS, GIS, and Remote Sensing

Laboratory Exercise - Temple-View Least- Cost Mountain Bike Trail

Height Above Nearest Drainage in Houston THE UNIVERSITY OF TEXAS AT AUSTIN

Outline Anatomy of ArcGIS Metadata Data Types Vector Raster Conversion Adding Data Navigation Symbolization Methods Layer Files Editing Help Files

Lauren Jacob May 6, Tectonics of the Northern Menderes Massif: The Simav Detachment and its relationship to three granite plutons

Catchment modelling using PIHMgis By Harish Sangireddy The University of Texas at Austin

GIS Project: Groundwater analysis for the Rhodes property (Socorro, NM).

used to transport sediments throughout the lands. In this regard, understanding erosion is

Determining a Useful Interpolation Method for Surficial Sediments in the Gulf of Maine Ian Cochran

GIS IN ECOLOGY: ANALYZING RASTER DATA

Exercise 4 Estimating the effects of sea level rise on coastlines by reclassification

GEOGRAPHIC INFORMATION SYSTEMS

Coastal Flooding in Brevard County, Florida

Gravity and Magnetic Anomalies Compared to Moho Depth throughout the State of Texas

Model Calibration and Forecast Error for NFIE-Hydro

Spatial Data Analysis with ArcGIS Desktop: From Basic to Advance

BSEN 6220 GIS LAB #5

Automatic Watershed Delineation using ArcSWAT/Arc GIS

GIS CONCEPTS ARCGIS METHODS AND. 2 nd Edition, July David M. Theobald, Ph.D. Natural Resource Ecology Laboratory Colorado State University

LANDSLIDE RISK ASSESSMENT IN YOSEMITE NATIONAL PARK. Edna Rodriguez December 1 st, 2016 Final Project

Lab 7: Cell, Neighborhood, and Zonal Statistics

Semester Project Final Report. Logan River Flood Plain Analysis Using ArcGIS, HEC-GeoRAS, and HEC-RAS

These modules are covered with a brief information and practical in ArcGIS Software and open source software also like QGIS, ILWIS.

CE 394K/CEE6440 GIS in Water Resources Fall 2018 Final Exam Solution

GIS Project: Study on Gulf of Mexico basin provenance in Lower Miocene

Exercise 5e: Estimating the impact of sea level rise in coastal areas of the United States and comparing to the impact in coastal Asia

Handling Raster Data for Hydrologic Applications

Transcription:

GEO 327G Semester Project Urbanization in the Onion Creek Watershed Hanes, Ian M 12-4-2014

Hanes 1 Problem Formulation The Onion Creek Watershed is located southeast of Austin where population and urbanization has been increasing at a sustained rate over the past 10-15 years. Recently, the area has endured numerous flood events, most notably the Halloween Flood of 2013. The Austin City Council has bought out over 300 homes in the watershed since 1999 due to the areas susceptibility to flooding. The goal of this project is to investigate which areas of the Onion Creek watershed have seen the largest increase in impervious cover and determine how much (if any) role urbanization has played in the increase of floods in the area. Data Collection Data used was collected from the following sources: TNRIS (National Land Cover Dataset): City of Austin: Texas impervious cover data http://www.tnris.org/get-data?quicktabs_maps_data=1 Watersheds, County Boundaries, and Creek Lines ftp://ftp.ci.austin.tx.us/gis-data/regional/coa_gis.html Data Preprocessing No preprocessing was required. ArcGIS Processing I began by adding the watershed and county boundary files to ArcMap Figure 1: County and Watershed Shapefiles

Hanes 2 Next, I selected the watersheds I wanted to observe for this project and dissolved their boundaries. This was done by using the editor toolbar (Edit>select features>merge) and used the Clip tool to clip the county boundaries to the watershed to create a new file ClipCounty. I then added label features to the ClipCounty shapefile. Figure 2: Watershed with county boundaries clipped After this step, the 2006 impervious cover raster was added to the TOC and its projection was changed to match that of the ClipCounty layer (properties>coordinate system>nad83 StatePlane Texas Central). Figure 3: Changing the projection of the original 2006 raster

Hanes 3 Using the Extract by Mask tool, the 2006 impervious cover raster was clipped to the ClipCounty shapefile and the resulting raster was named WSCoverClip. Figure 4: Clipping the 2006 raster to the ClipCounty layer This raster was reclassified using the reclassify tool in order to rank the data based on my ranking scheme. Figure 5: Reclassifying the WSCoverClip Raster

Hanes 4 Making the ClipCounty layer 75% transparent shows that the majority of the impervious cover is in Travis County Figure 6: Reclassified 2006 Impervious Cover raster The same procedure was applied with the 2001 and 2011 impervious cover datasets. After all the impervious cover rasters were created, using the raster calculator I subtracted the 2001 raster from the 2011 raster to get a raster that represents the change in impervious cover between those years. This was done using the raster calculator. Figure 7: Raster algebra to create a raster that represents the change in impervious cover

Hanes 5 The resulting raster shows that some areas actually had some decreases in impervious cover, but the vast majority had no change or a positive change. The final step was taking the Creeks_lines shapefile and clipping it to the county line shapefile using the same process as described before. Onion Creek was then selected and its symbology changed to differentiate it from the other streams. This procedure was followed again for Figure 9. After the final change raster was created, the clipped and resampled 2011 raster was analyzed to determine what percentage of land in the watershed was 100% impervious. Using the Value Attribute Table, it was determined that is raster included 991,998 total cells, and 6,099 of those were completely impervious and 864,923 had no impervious cover, leaving 120,976 cells that fell somewhere in between. Each cell was 30x30 meters, so nearly 5.5 km 2 is completely impervious, 778 km 2 has no impervious cover, and 109 km 2 falls in between. Conclusion It is evident that the vast majority of the urbanization that has taken place in the Onion Creek watershed has been in Travis County (western portion). Over the study period, Hays and Blanco counties have seen relatively insignificant amounts of urbanization. Also noteworthy is that the southernmost areas of the watershed (including Buda and Kyle) are urbanizing faster than anywhere else, though the already established residential areas closer to Austin are becoming more impervious, as opposed to spreading impervious cover. What was a little surprising was that only 0.7% of the area in the watershed was completely impervious, and 87% had no cover at all. In light of this, I suspect that urbanization is not the sole reason that the Onion Creek watershed has seen so many floods. I think it is reasonable to assume that the watershed is intrinsically prone to flooding and that continued urbanization in Travis County is exacerbating the issue.

Hanes 6 Maps Figure 8: Final Map displaying the change in Impervious Cover

Figure 9: Total Impervious cover in the Onion Creek watershed in 2011 Hanes 7