Presentation is loading. Please wait.

Presentation is loading. Please wait.

Iowa Rivers Information System Inventory, Modeling, and Evaluation of Basin, In-Stream Habitat, and Fishery Resource Relationships Kevin Kane, Iowa State.

Published byMaximillian Fitzgerald Modified over 8 years ago

Similar presentations

Presentation on theme: "Iowa Rivers Information System Inventory, Modeling, and Evaluation of Basin, In-Stream Habitat, and Fishery Resource Relationships Kevin Kane, Iowa State."— Presentation transcript:

1 Iowa Rivers Information System Inventory, Modeling, and Evaluation of Basin, In-Stream Habitat, and Fishery Resource Relationships Kevin Kane, Iowa State University

2 Iowa Rivers Information System IRIS Goals  Provide a consistent base layer for locational accuracy  Document the health of Iowa’s riverine environments through data coordination  Track biodiversity locally within a global perspective l Helping to direct management, protection, restoration, and educational efforts within Iowa’s river resources l Prioritizing conservation efforts  Easy accessibility to all information

3 Iowa Rivers Information System IRIS Overview IRIS (DNR/GSB & ISU) IOWATER Mussel Survey Many, many others DNR EPD In-Stream Habitat ISU/DNR Fisheries DNR GSB Nature Mapping Watershed/ Stream Bio-Prediction Aquatic GAP ISIS Reach Valley Seg Dyn. Seg.

4 Iowa Rivers Information System Three Major Responsibilities  Build the spatial database for IRIS with the DNR's GIS Section using the National Hydrographic Dataset (NHD) including: l coding stream IDs, l watersheds, l stream names, l stream length, l stream route and order, and l boundaries, l counties, l TRS (public land survey), l USGS quads, etc.

5 Iowa Rivers Information System Three Major Responsibilities  Collecting and adding specific data attributes to the IRIS spatial structure. These attributes will include: stream access sites, bankside land cover, EPA BIOSTORET Cross-Index, bridges, Biological Stream Character Rating, channelization, dams and levees, elevation, fish kills, historic sites, lake endpoints, stewardship (natural and recreation areas), and water sampling stations. The original listing of these attributes are taken from the "Illinois Streams Information System - ISIS Users Manual", Johnston, et al, 1999.

6 Iowa Rivers Information System Three Major Responsibilities  Integrating IRIS into a GIS environment where queries can be done for location or attribute information from a user's desktop. This will involve writing programming code in an ArcView environment using Avenue, Visual Basic, or C++. ArcIMS

7 Consistent Hydrologic Base Layer

8 Iowa Rivers Information System Consistent Spatial Database  Using National Hydrography Dataset (NHD)  Two phases of development: l Phase I – Reach based inventory l Phase II – Dynamic Segmentation model  Linkages by reach to other attribute databases

9 Iowa Rivers Information System http://nhd.usgs.gov/

10 Iowa Rivers Information System Phase I Reach Based Percent Cropland By Reach

11 Iowa Rivers Information System Phase II Dynamic Segmentation Begin Reach End Reach Begin Sample End Sample

12 Attribute Database Coordination

13 Iowa Rivers Information System IRIS Coordination IRIS (DNR/GSB & ISU) IOWATER Mussel Survey Many, many others DNR EPD In-Stream Habitat ISU/DNR Fisheries DNR GSB Nature Mapping Watershed/ Stream Bio-Prediction Aquatic GAP ISIS Reach Valley Seg Dyn. Seg.

14 Iowa Rivers Information System Spatial Database Comparisons

15 Iowa Rivers Information System Attribute Data Comparisons

16 Tracking Biodiversity & Prioritizing Conservation Efforts

17 Iowa Rivers Information System Watershed / Stream Bio-prediction General Approach Step 1. Classify Iowa’s riverine resources into distinct valley segment types Step 2. Assess the relative conservation status of each valley segment type and develop initial conservation priorities (quality and quantity) Step 3. Predict the biological potential of each valley segment Step 4. Revise initial conservation priorities using biological information Step 5. Identify valley segments which are both biologically significant and of relatively high quality

18 Iowa Rivers Information System Developing a Digital Data Layer of Valley Segment Types  Purpose l Delineate distinct stream environments l Evolutionary and Ecologically Meaningful Units (See EDUs below) l Serve as the habitat template for predicting biological potential  Protocol l The Nature Conservancy’s Aquatic Community Classification Framework l Based on Ecoregions and Watersheds aka EcoDrainage Units (EDUs)

19 Iowa Rivers Information System Examples of Distinct Valley Segment Types * Ecoregion: Des Moines Lobe * Basin: Des Moines * River Size: Medium * Structure: Unconfined valley * Flow: Perennial * Temperature: Warm * Gradient: Moderate * Substrate: Fine * Hydrograph: Stable Factors / Variables:

20 Iowa Rivers Information System Species Habitat Affinity Database

21 Iowa Rivers Information System Species Habitat Affinity Database

22 Iowa Rivers Information System Species Habitat Affinity Database

23 Iowa Rivers Information System Predicting the Biological Potential of each Valley Segment Habitat Affinity Database Statewide Known Distributions by Hydrologic Unit Valley Segment Datalayer

24 Iowa Rivers Information System Predicted Distribution for Species X By Watershed and Reach

25 Iowa Rivers Information System Predictive Modeling Habitat Affinity Databse Historic and Sampled Distributions Predictive Model Watershed Influence to Habitat Classifying Rivers

26 Accessibility to Information

27 Iowa Rivers Information System ISIS - Illinois Stream Information System

28 Iowa Rivers Information System ISIS - Illinois Stream Information System

29 Iowa Rivers Information System ISIS - Illinois Stream Information System

30 Iowa Rivers Information System ISIS - Illinois Stream Information System

31 Iowa Rivers Information System IRIS ArcIMS Application http://siberia.gis.iastate.edu/iris

32 Iowa Rivers Information System Applications – Landcover Buffer

33 Iowa Rivers Information System Applications – Landcover Buffer http://ortho.gis.iastate.edu/

34 Iowa Rivers Information System Percent Cropland By Reach Applications – Landcover Buffer

35 Iowa Rivers Information SystemCredits  Missouri Resource Assessment Partnership  National Gap Analysis Program  Illinois Stream Information System  Iowa Dept. of Natural Resources  Iowa State University

Download ppt "Iowa Rivers Information System Inventory, Modeling, and Evaluation of Basin, In-Stream Habitat, and Fishery Resource Relationships Kevin Kane, Iowa State."

Similar presentations

Salmonid Population and Habitat Monitoring in the Lower Columbia/Columbia Estuary Provinces Oregon Department of Fish and Wildlife.

Salmonid Population and Habitat Monitoring in the Lower Columbia/Columbia Estuary Provinces Oregon Department of Fish and Wildlife.
Caddo Lake/Upper West Gulf Coastal Plain NFWF Project Ryan Smith Steve Gilbert Jesse Valdez The Nature Conservancy.

Caddo Lake/Upper West Gulf Coastal Plain NFWF Project Ryan Smith Steve Gilbert Jesse Valdez The Nature Conservancy.
Summary of Aquatic Programs Administered by the WV Division of Natural Resources Dan Cincotta WVDNR P. O. Box 67 Elkins, WV 26241.

Summary of Aquatic Programs Administered by the WV Division of Natural Resources Dan Cincotta WVDNR P. O. Box 67 Elkins, WV
Yakama Nation Pacific Lamprey Recovery Project Core Data And Monitoring Framework.

Yakama Nation Pacific Lamprey Recovery Project Core Data And Monitoring Framework.
Step 1: Valley Segment Classification Our first step will be to assign environmental parameters to stream valley segments using a series of GIS tools developed.

Step 1: Valley Segment Classification Our first step will be to assign environmental parameters to stream valley segments using a series of GIS tools developed.
Updating the National Hydrography Data for the Twin Cities with Local Subsurface Drainage Information NHD Stewardship Conference Lakewood, Colorado April.

Updating the National Hydrography Data for the Twin Cities with Local Subsurface Drainage Information NHD Stewardship Conference Lakewood, Colorado April.
Developing Modeling Tools in Support of Nutrient Reduction Policies Randy Mentz Adam Freihoefer, Trip Hook, & Theresa Nelson Water Quality Modeling Technical.

Developing Modeling Tools in Support of Nutrient Reduction Policies Randy Mentz Adam Freihoefer, Trip Hook, & Theresa Nelson Water Quality Modeling Technical.
Development of a Comprehensive Wildlife Conservation Strategy for Georgia Georgia Department of Natural Resources Wildlife Resources Division.

Development of a Comprehensive Wildlife Conservation Strategy for Georgia Georgia Department of Natural Resources Wildlife Resources Division.
Wetland and Riparian Mapping in Montana Karen Newlon, Montana Natural Heritage Program Helena, MT Montana Wetland Council University of Montana-Missoula.

Wetland and Riparian Mapping in Montana Karen Newlon, Montana Natural Heritage Program Helena, MT Montana Wetland Council University of Montana-Missoula.
The adequacy of the existing reserve system for the protection of freshwater ecosystems Janet Stein Fenner School of Environment and Society.

The adequacy of the existing reserve system for the protection of freshwater ecosystems Janet Stein Fenner School of Environment and Society.
Developing a Valley Segment Classification for Wisconsin Streams Jana Stewart U.S. Geological Survey.

Developing a Valley Segment Classification for Wisconsin Streams Jana Stewart U.S. Geological Survey.
The National Hydrologic Dataset Brian Brodeur GIS Program Director Mass DEP

The National Hydrologic Dataset Brian Brodeur GIS Program Director Mass DEP
Putting NHDPlus to Work 2006 ESRI User Conference San Diego, CA August 8, 2006 2006 ESRI User Conference San Diego, CA August 8, 2006 NHD and NHDPlus Applications.

Putting NHDPlus to Work 2006 ESRI User Conference San Diego, CA August 8, ESRI User Conference San Diego, CA August 8, 2006 NHD and NHDPlus Applications.
A spatial framework for managing Hawaii’s aquatic resources: Dana Infante Department of Fisheries and Wildlife, Michigan State University.

A spatial framework for managing Hawaii’s aquatic resources: Dana Infante Department of Fisheries and Wildlife, Michigan State University.
Relationship to E-Flows Riparian Areas Influences groundwater/surface water relationships Provides filters to improve water quality Provides habitat for.

Relationship to E-Flows Riparian Areas Influences groundwater/surface water relationships Provides filters to improve water quality Provides habitat for.
National Hydrography Data Use and Applications.

National Hydrography Data Use and Applications.
Regional River Management: Recent developments in the Great Lakes Basin M. J. Wiley & M. Omair School of Natural Resources and Environment University of.

Regional River Management: Recent developments in the Great Lakes Basin M. J. Wiley & M. Omair School of Natural Resources and Environment University of.
Development of Aquatic Ecosystem Models Lizhu Wang, Shaw Lacy, Paul Seebach, Mike Wiley Institute for Fisheries Research MDNR and U of M.

Development of Aquatic Ecosystem Models Lizhu Wang, Shaw Lacy, Paul Seebach, Mike Wiley Institute for Fisheries Research MDNR and U of M.
Applications of GIS to River Management: Recent developments in the Great Lakes Basin M. J. Wiley & M. Omair School of Natural Resources and Environment.

Applications of GIS to River Management: Recent developments in the Great Lakes Basin M. J. Wiley & M. Omair School of Natural Resources and Environment.
Aquatic Gap Analysis and Biodiversity Management The AGAP Team: Kevin Kane, Co-PI AIT GIS Facility, ISU, Clay Pierce, Co-PI Dept. Natural.

Aquatic Gap Analysis and Biodiversity Management The AGAP Team: Kevin Kane, Co-PI AIT GIS Facility, ISU, Clay Pierce, Co-PI Dept. Natural.

Similar presentations

Ads by Google